Does the Federal Constitutional Court Ruling Mean

Volume 4, Issue 2, 2018ISSN 2336-6494www.ejobsat.cz

FAKHRY, B., RICHTER, C.:Does the Federal Constitutional Court Ruling Mean the GermanFinancial Market is Efficient?

MÜHLBACHER, J., SIEBENALER, T.:Ready for Changes? The Influence of General Self-Efficacy andResistance to Change on Managers’ Future Competence Requirements

BAKOVÁ, K.:The Financial Accelerator in Europe after the Financial Crisis

ISLAM, M., ADNAN, A.:Factors Influencing Dividend Policy in Bangladesh: Survey Evidencefrom Listed Manufacturing Companies in Dhaka Stock Exchange

GENKOVA, P., KEYSERS, P.:Differences of Diversity Attitudes between Employees with and withoutan Immigration Background: The Case of Germany

KUKLYTĖ, J.:Cybersexual Harassment as ICTs Development Consequences:A Review

TESCHL, E.:An Analysis of Expectations in Industrial Value Engineering Projects

EUROPEAN JOURNALOF BUSINESS SCIENCEAND TECHNOLOGY

Volume 4, Issue 22018

Mendel University in Brnowww.ejobsat.com

EUROPEAN JOURNAL OF BUSINESS SCIENCE AND TECHNOLOGYEditor in ChiefSvatopluk Kapounek, Mendel University in Brno, Czech Republic

e-mail: [email protected] EditorVeronika Kočiš Krůtilová, Mendel University in Brno, Czech Republic

e-mail: [email protected], tel.: +420 545 132 556Editorial BoardAlin Marius Andrieș, Alexandru Ioan Cuza University of Iași, RomaniaIstván Benczes, Corvinus University of Budapest, HungaryPetr David, Mendel University in Brno, Czech RepublicJarko Fidrmuc, Zeppelin University, Friedrichshafen, GermanyHardy Hanappi, Vienna University of Technology, AustriaPeter Huber, Austrian Institute of Economic Research, Vienna, AustriaLea Kubíčková, Mendel University in Brno, Czech RepublicZuzana Kučerová, Mendel University in Brno, Czech RepublicGábor Kutasi, Corvinus University of Budapest, HungaryZuzana Machová, Vysoká škola sociálně správní, Havířov, Czech RepublicPeter Markovič, University of Economics in Bratislava, Slovak RepublicRoman Maršálek, Brno University of Technology, Czech RepublicSergey Maruev, The Russian Presidential Academy of National Economy and Public

Administration, Moscow, RussiaJürgen Mühlbacher, Vienna University of Economics and Business, AustriaMartina Rašticová, Mendel University in Brno, Czech RepublicJana Soukopová, Masaryk University, Brno, Czech RepublicWłodzimierz Sroka, University of Dąbrowa Górnicza, PolandAlexander Troussov, IBM Centre for Advanced Studies, Dublin, IrelandJan Žižka, Mendel University in Brno, Czech RepublicPavel Žufan, Mendel University in Brno, Czech RepublicExecutive BoardFrantišek Dařena, Mendel University in Brno, Czech RepublicPetr Koráb, Mendel University in Brno, Czech RepublicOldřich Trenz, Mendel University in Brno, Czech RepublicJana Turčínková, Mendel University in Brno, Czech Republic

Editorial Office AddressEJOBSAT, Mendel University in Brno, Zemědělská 1, 613 00 Brno, Czech Republic

Registration number MK ČR E22009The journal is published twice a year.Typesetting Pavel Haluza, Jiří RybičkaFirst editionNumber of printed copies 100ISSN 2336-6494

Number 2, 2018 was published on December 28, 2018 by Mendel University Press

109

CONTENTSBachar Fakhry, Christian Richter:

Does the Federal Constitutional Court Ruling Mean the German Financial Market isEfficient? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111

Jürgen Mühlbacher, Tom Siebenaler:Ready for Changes? The Influence of General Self-Efficacy and Resistance to Change onManagers’ Future Competence Requirements . . . . . . . . . . . . . . . . . . . . . . . . 126

Klára Baková:The Financial Accelerator in Europe after the Financial Crisis . . . . . . . . . . . . . . . 143

Mohammad Shahidul Islam, ATM Adnan:Factors Influencing Dividend Policy in Bangladesh: Survey Evidence from ListedManufacturing Companies in Dhaka Stock Exchange . . . . . . . . . . . . . . . . . . . . 156

Petia Genkova, Pia Keysers:Differences of Diversity Attitudes between Employees with and without an ImmigrationBackground: The Case of Germany . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174

Jūratė Kuklytė:Cybersexual Harassment as ICTs Development Consequences: A Review . . . . . . . . . 187

Erhard Teschl:An Analysis of Expectations in Industrial Value Engineering Projects . . . . . . . . . . . 196

Volume 4 Issue 2ISSN 2336-6494

www.ejobsat.com

DOES THE FEDERALCONSTITUTIONAL COURT RULING MEANTHE GERMAN FINANCIAL MARKETIS EFFICIENT?Bachar Fakhry1, Christian Richter21University of Lahore, Pakistan2German University in Cairo, Egypt

FAKHRY, Bachar, and RICHTER, Christian. 2018. Does the Federal Constitutional Court Ruling Mean theGerman Financial Market is Efficient?. European Journal of Business Science and Technology, 4 (2): 111–125.ISSN 2336-6494, DOI http://dx.doi.org/10.11118/ejobsat.v4i2.120.

ABSTRACT

Following the landmark ruling by the German Federal Constitutional Court in Karlsruhe on 7thFebruary 2014 in which they endorsed the efficient market hypothesis, we present evidence onthe efficiency of the German financial market. Introducing a new variance bound test based onthe Component-GARCH model of volatility to analyse the long- and short-runs effects on theefficiency of the German financial market, we test the price volatility of four markets: DAX stockindex, German sovereign debt index as provided by Barclays and Bloomberg, Euro gold indexby the World Gold Council and Euro currency index by the Bank of England. Our use of theComponent-GARCH-T model highlight two key contributions, the first being the analysis of theefficiency of the market in the long and short runs. However, a more important contribution is theresult of our variance bound test highlight the relatively strong acceptance of the efficient markethypothesis in both the short and long runs in all the observed financial markets. It must be statedour research is of importance to researches in both applied finance and portfolio management.The influencing question of what moves specific markets is crucial to market participants seekingmarket alpha for their investments strategies and portfolio optimisations.

KEY WORDS

EMH, volatility tests, C-GARCH-T, financial markets, gold market

JEL CODES

B13, B21, C12, G14, G15, H63

112 Bachar Fakhry and Christian Richter

1 INTRODUCTION

The question of what moves prices in thefinancial market is in itself not a new one.Recently, this debate gained new ground dueto the recent financial crises which started inmid-2007. Therefore, the landmark ruling bythe German Federal Constitutional Court inKarlsruhe on 7th February 2014 in which theyendorsed the efficient market hypothesis perWinkler (2014) is interesting on many levels.In a way, this highlights the question doesthe ruling mean that the German financialmarket is efficient? Furthermore, it raises anissue if the efficient market hypothesis is thekey explanation of the price movement in thefinancial market then are the criticisms, asnoted by Ball (2009) and Fakhry (2016), inthe aftermath of the crises justified? The mainquestion of what moves financial markets isimportant for researchers in the field of appliedfinance and portfolio manager, due to it beingthe underlining factor in investment decisionsand portfolio optimisation. One of the keyreasoning is that it is crucial for market par-ticipants wanting alphas for their investmentsdecisions and portfolio optimisations.

Perhaps an explanation of the efficient mar-ket hypothesis or EMH would be ideal atthis point. The EMH was developed thru thecontribution of prominence articles by Famaand Malkiel such as: Malkiel (1962), Fama(1965), Malkiel and Fama (1970). At the basiclevel, the EMH hypothesize, as proposed byMalkiel (1962) and Fama (1965), that theprice of any asset must immediately reflectfundamental information regarding the asset.The assumption is that market participantsbehave in accordance with the theory of perfectcompetition which is based on an idealise worldwhere market participants are rational, riskaverse and profit maximisers. Of course, recentevents have illustrated that this is not alwaysthe case as Ball (2009) and Fakhry (2018) haveshown. Therefore, there is a need to includebehavioural finance in the pricing of any asset.The key argument underpinning behaviouralfinance is as put so elegantly by Thaler (2015,p. 4) market participants are homo sapiens

and not homo economicus, hence as stated byBernard Baruch: “What is important in marketfluctuations are not the events themselves, butthe human reactions to the events.” (Lee et al.,2002, p. 2277)

A key factor in the efficiency of the marketis the differentiation between long and shortrun price volatility behaviour. As suggested byDe Bondt (2000), the price tends to deviatefrom the fundamental value in the short run.However, the price usually reverts to thefundamental value in the long run. This ismore obvious during an asset price bubble;as hinted by Blanchard and Watson (1982)and Barlevy (2007). Essentially an asset pricebubble is a rapid upwards pressure on theprice, eventually causing systematic downwardspressure to correct the price. Often leading to acrash in the prices where the price is under mas-sive downwards pressure. In the long run, themarket could return to the fundamental priceand hence be “efficient” or it could collapse.The price movements are driven by marketparticipants’ reaction to events and informationwhich differ and may be asymmetric in theshort-run and long-run.

In order to analyse the different impacts fromthe short and long run on the efficiency ofthe German financial market, we change thevariance bound tests of Fakhry and Richter(2015, 2016a, 2016b) and Fakhry et al. (2017) touse an asymmetrical variant of the C-GARCHmodel proposed by Engel and Lee (1999). Thiswill allow us to distinguish between the longand short run efficiency. We also contribute byusing the Euro currency index and German AllMaturity sovereign debt index obtained fromthe Bank of England and Barclays Bank plcrespectively. In addition, we use the DAX stockindex. Since Germany has the second largestgold reserve and is the fourth biggest consumerof gold according to the World Gold Council,we also use the Euro gold index obtained fromthe World Gold Council.

Our findings indicate that unlike previousstudies conducted using the variance boundtest e.g. Fakhry and Richter (2015, 2016a),

Does the Federal Constitutional Court Ruling Mean the German Financial Market is Efficient? 113

we found evidence suggesting that the Germanfinancial market is efficient. All four observedGerman markets: equity, gold, sovereign debtand foreign exchange were efficient in both thelong and short runs. This suggests that thedifferentiation between the short and long runis limited in the case of the German financialmarket. However, another possible explanationis the stability state argument of Fakhry (2016).Fakhry (2016) hints that during large obser-vations containing both high and low volatileperiods, the periods could cancel each other outleading to the market appearing to be stableand efficient. This is usually the case in the longrun as argued by De Bondt (2000). However,as argued Engle and Lee (1999), in the shortrun the market is more volatile and reactive;thus should reflect an inefficient market. Thereis a clue in the previous statement, a reactivemarket can sometime lead to a false stateof stability which gives the impression of anefficient market, especially over a long periodof observation.

Our two key contributions is that we usethe component GARCH-T to analyse the longand short run efficiency of the market. Thus

leading to our main contribution, namely thatthe results defy the conventional wisdom inthat we found that the German financial marketseems to be efficient in both the long and shortruns.

Furthermore we also contribute via the datawe use. although previously many have usedstock and FX indices to observe the efficiencyof the financial markets, yet the use of sovereigndebt and gold market indices has been limitedin the area of financial econometrics in general.The second contribution is that we analysethe efficiency of the Euro currency index asobtained from the Bank of England which havealso been limited.

This article is structured in the followingway. Firstly, we will briefly and criticallyreview the recent empirical literature on theEMH, behavioural finance theory and compo-nent GARCH model. This will lead to themethodology which will describe specification ofthe variance bound test and underlying asym-metrical component GARCH models. Sectionsfour and five presents the data and empiricalresults. Finally, section 6 concludes.

2 LITERATURE REVIEW

The Literature review is divided into three keysubsections: a review of the empirical evident onthe EMH, behavioural finance theory and theComponent GARCH model. This article willnot review the theories and tests underpinningthe EMH and behavioural finance theory, seeFakhry (2016) and Fakhry (2018) for a criticalreview of the theories and tests. The crucialfactor is the differentiation of the long run andshort run on the price volatility which impactthe efficiency of the market.

2.1 Review of the Efficiencyof the Markets

The empirical evidence of the past few yearshave illustrated that markets are not efficientduring a period of highly volatile and reactiveenvironment as highlighted by recent studies

in the sovereign debt market by Fakhry andRichter. In a series of studies into the efficiencyof the sovereign debt market, see Fakhry andRichter (2015, 2016a, 2016b), they found thatin general market participants reacted to eventsrather than fundamental information duringthe recent financial and sovereign debt crises.A similar point was illustrated by Fakhryet al. (2017). However, these studies alsohighlighted some evidence of efficiency duringseveral periods in several markets. Conversely,although Fakhry and Richter (2015, 2016a)provided mixed evidence of the efficiency of theGerman Bund market. In truth, the evidencewas pointing to an inefficient market in thegeneral sense; since in theory any market cannotbe partly efficient.

The evidence in the stock market is alsomixed as illustrated by several recent studies


(i.e. Borges, 2010; Panagiotidis, 2010; Onaliand Goddard, 2011; Todea and Lazar, 2012;Sensoy and Tabak, 2015; Singh et al., 2015).Conversely, Borges (2010) found a split in theEuropean stock markets with the Greek andPortuguese rejecting and the western Europeancountries including Spain accepting the weakform EMH. Also finding that the Germanmarket does accept the weak form of the EMH.Interestingly, Sensoy and Tabak (2015) study-ing the impact of long-time memory on theefficiency of the European Union stock marketsduring the recent financial and sovereign debtcrises found mixed evidence. This seem to bebacking the evidence found in the sovereigndebt market by Fakhry and Richter (2015,2016a, 2016b) and Fakhry et al. (2017).

In a way, the recent evidence on the efficiencyof the FX market is similar to the previoustwo markets in that it is mixed see (Ahmad etal., 2012; Lee and Sodoikhuu, 2012; Boboc andDinică, 2013; Mele, 2015). Lee and Sodoikhuu(2012) analysed the impact of market strategieson the efficiency of the FX Market, findingthat in general the three observed FX marketsare efficient. Conversely, transaction costs dohave a greater impact on the efficiency of theFX market. A key finding in accordance withour article is that the euro/dollar FX rateis efficient. Mele (2015) find that arbitrageopportunities do exist for longer periods inthe FX market, therefore violating one ofthe fundamental rules underpinning the EMH:arbitrage opportunities don’t exist for longperiods. By default, this means that the FXmarket is inefficient. The results conflict withthat of Lee and Sodoikhuu (2012) in illustratingthat the leading FX markets, including theEuro, are inefficient.

Like the other markets, the limited recentempirical evidence for the efficiency of the goldmarket seem to be hinting at an inefficientmarket. Although the empirical evidence isnot direct testing the EMH, the literature isconcentrating on a weak form of efficiency byusing two methods. The first is cointegrationas use in Narayan et al. (2010) and Zhang andWei (2010), the argument is if the market hasa cointegration relationship with other markets

than the market is regarded as inefficient.Narayan et al. (2010) found that the goldmarket has a cointegration relationship withthe oil market. Zhang and Wei (2010) alsofound a strong relationship between the goldand oil markets. The second is multifractal asuse in Wang et al. (2011), the argument isthat if the trend in the market is unexplainedby a single factor then the market is regardedas inefficient. However, Wang et al. (2011)seem to be hinting at a rather mixed evidencewith the gold market appearing to be efficientduring upward trending periods and inefficientduring downward trending periods. Mali andMukhopadhyay (2014) provide further evidenceof the multifractal nature of the gold market inthe Indian, Chinese and Turkish markets there-fore these markets are regarded as inefficient.

2.2 Brief Review of the AlternativeTheory of Asset Pricing:Behavioural Finance

As we have seen the recent empirical evidenceon the efficiency of the market is not strong,Hence there is a need to include the behaviouralfinance theory for a complete picture of financialasset pricing. So we will analyse the empiricalevidence on key behavioural factors in recentyears.

In studies by Fakhry et al. (2017) andMasood et al. (2018), they found evidence ofoverreacting in the sovereign debt market. TheGreek market is relatively small in comparisonwith the size of the eurozone market, hencethe Eurozone crisis was based on overreactingmarket participants. Also as hinted by Fakhry(2018), during the financial crisis market par-ticipants fleeing from the equity markets andmortgage backed securities were underreactingin the sovereign debt market, there is a patternof behaviour during any flight top safety thattend to lead to an underreaction. Conversely,as Ball (2009) points out there was a hint ofunderreaction to the information underpinningthe mortgage back securities during the assetbubble of the mid-2000s.

Analysing the impact of the Tohoku Tsunamiof 2011 on the Japanese financial market,


Fakhry et al. (2017) found overreaction inthe equity, FX and sovereign debt marketduring the immediate aftermath. This is in linewith previous studies like Maierhofer (2011),Luo (2012), Parker and Steenkamp (2012) andFerreira and Karali (2015) who found no impactother than in the immediate aftermath. Thushinting that an overreaction is nearly alwaysshort lived during extreme events.

Another behavioural factor often observed isherding, Nofsinger and Sias (1999) character-ized this phenomena as trading in the samedirection by a group of investors for a period oftime. This is often the case during in extremeconditions such as bubbles as illustrated byJiang et al. (2010), Sornette and Cauwels(2015) and Gerlach et al. (2018) and crashesas highlighted by Brunnermeier (2009) andEconomou et al. (2011) during flights.

2.3 Review of Long/Short RunVolatility

As stated by Pastor and Stambaugh (2012),conventional wisdom dictates there is a differentbetween the long and short run. Generally,markets are less volatile in the long run dueto being less perceptive to shocks; hence theyare increasingly stable. As Engle and Lee (1999)states volatility is greater in the short horizonthan in the long horizon. This indicates amore rapid short run volatility mean reversionthan in the long run as hinted by Engle andLee (1999). Per Colacito et al. (2011), anotherimportant principle often made in economicsis the existence of different long and shortrun sources affecting volatility. Additionally,as De Bondt (2000) hints the price revertsto the fundamental value in the long run.This means that the factors effecting the priceand hence price volatility in the short andlong runs are different. Effectively what DeBondt (2000), Pastor and Stambaugh (2012)and many others like Engle and Lee (1999) arehinting is the reaction of markets participantstend to deviate with time. Another factor,suggested by Engle and Lee (1999), is the

different impact from the leverage effect andmarket risk premium on the market in theshort and long run. In a paper written as partof a book in honour of Clive Granger, Engleand Lee (1999) extended the GARCH modelto account for the permanent (long run) andtransitory (short run) components of volatilityderiving the component GARCH model (aka C-GARCH). In this section, we will review theempirical evidence on the C-GARCH model.

Recent empirical evident for the C-GARCHmodel seem to agree with the general con-ception that financial market volatility differ-entiate between long and short runs. Muchof the literature is concern with the volatilityin the stock market. Guo and Neely (2006)found evident consistent with Engle and Lee(1999) suggesting that long-run volatility betterdetermines the international conditional equitypremium than the short run volatility. Adrianand Rosenberg (2008) interprets the short-run volatility component as a measure offinancial constraints tightness, while the longrun volatility component is related to businesscycle risks. However contrary to the acceptedwisdom, Pastor and Stambaugh (2012) foundthat in accounting for predictor imperfectionstock markets are more volatile in the long run.Du and Hu (2014) analysing the impact of thelong run component in FX volatility on thestock market returns found that it does haveexplanatory power in determining the stockreturns.

Analysing the Eurozone sovereign debt mar-ket, Sosvilla-Rivero and Morales-Zumaquero(2012) found a different between both volatilitycomponents. In general, the permanent compo-nent exhibited long memory while the transi-tory component exhibited short memory. Theyhighlight that shocks are of higher importancethan transitory shifts in the Eurozone sovereigndebt market. Furthermore, they hint at afamiliar split between the core and peripheralEurozone countries in the transitory shiftswith respect to the degree of policymakers’credibility and public finance’s stability.


3 METHODOLOGY

The main aim of this paper is to extend the vari-ance bound test of Fakhry and Richter (2015)and Fakhry and Richter (2016a) to analyse theefficiency of the markets in the long and shortruns. We proposed a new variance bound testby extending Fakhry and Richter (2016a) usingan asymmetrical C-GARCH, proposed by Engleand Lee (1999), variant of the variance boundtest proposed by Shiller (1979, 1981). We usethe 5% critical value F -statistics to test theefficient market hypothesis. As with Fakhryand Richter (2015, 2016a, 2016b) and Fakhryet al. (2017), we follow the pre-requisite stepsadvocated by Shiller (1979, 1981).1. As illustrated by Shiller (1981), the key

factor underlying any variance bound testis the variance calculation. We model thedatasets in our test as a time varying laggedvariance of the price using equation 1. Weused the 5-lagged system, as oppose to the20-lagged system advocated by Fakhry andRichter (2015).

limt→T

var (Pricet) =

Q∑q=1

(Price − µ)2

Q. (1)

2. The first order autoregressive model es-timates the residuals in the econometricmodel underpinning the test as illustratedby equation 2 and 3:

var(Pricet) = a+b1 var(Pricet−1)+µt, (2)

µt = τµt−1 + εt. (3)3. Estimate the first order asymmetrical C-

GARCH (1, 1) model to obtain the longrun and short run volatility coefficients. Itis worth remembering that the GARCH (p,q) model as proposed by Bollerslev (1986)is written as equation 4 where ht = σ2

t andkt = ε2t :

ht = ω + αpkt−1 + βqht−1. (4)

As suggested by Engle and Lee (1999),equation 4 can be slightly transformed into

equation 5 where the dynamics of the structureof conditional variance can be illustrated:

ht = σ2 + (αpkt−1 − σ2) + βqht−1 − σ2). (5)

The issue is that σ2 represents the uncon-ditional long run variance. However as arguedby Engle and Lee (1999), at the heart of thisequation is the question of whether the long runvolatility is truly constant over time. Surely,a more flexible specification where the longrun volatility is allowed to evolve lowly in anautoregressive manner is a more appropriatemodel of volatility, given the empirical evidenceon time varying and mean reverting volatilityas stated by Engle and Lee (1999). A moreflexible model would be equation 6 whereby σ2

is represented by mt, a time-varying long runmodel of volatility.

mt = ω + ρpmt−1 + φq(kt−1 − ht−1), (6)

(ht −mt) = σ2 + (αpkt−1 −mt−1) +

+ (βqht−1 −mt−1). (7)

Hence, equation 6 is a stochastic representa-tives of the long run volatility otherwise knownas the trend in volatility and equation 7 is thedifference between the conditional volatility andtrend, i.e. the long run volatility. Essentiallyequation 7 is the short run or transitoryvolatility.

In essence, this means the dynamics of thevolatility components can be interpreted as inthree steps. Firstly, the short run volatilitycomponent is mean reverting to zero at ageometric rate of (α + β) under the conditionof 0 < (α + β) < 1. Secondly, as highlightedpreviously the long run volatility componentevolves over time in an AR process; converselyif 0 < ρ < 1 then it will converge to aconstant level of ω

1−ρ . The third step is basedon the assumption that the long run volatilitycomponent has a slow rate of mean reversionthan the short run volatility component; simplyput, the long run volatility component is themore persistent of the two components meaning0 < (α+ β) < ρ < 1.


We opt to use a single asymmetrical orderone lagged C-GARCH model in our tests.Remember the short run volatility componentis given by equation 7. The TARCH model asdefined by Zakoian (1994) is given by equation8. Taking equation 8, we could transform it toa single order asymmetrical C-GARCH modelby subtracting the long run volatility fromeach term in the equation to give equation 9.Notice how if the asymmetrical effect is zerothe basic model collapses to a CGARCH modelas illustrated by equation 7. A key factor is thatthe asymmetrical effect is only added to theshort run component of the C-GARCH model,see equation 9. This is mainly due to the shortlife of the asymmetrical effect.

ht = αkt−1 + βht−1 + γkt−1I, (8)

(ht −mt) = σ2 + (αpkt−1 −mt−1) +

+ (βqht−1 −mt−1) +

+ γ(kt−1 −mt−1)I, (9)

where I =

{0, εt ≥ 0,

1, εt < 0.

As with Fakhry and Richter (2016a, 2016b),we also illustrate the impact of the asymmet-rical effect on the efficiency of the market.The key is the γ coefficient in equation 9where γ ̸= 0 then there is an asymmetricaleffect; if γ > 0 then there is a leverage effectmeaning negative shocks have greater impactthan positive shocks.

As noted by Engle and Patton (2001), thereis a story within any member of the GARCH

family of volatility models influenced by thecoefficients in the transitory and permanentvariance equations. Since as illustrated by Engleand Patton (2001), the market shocks andpersistent are indicated by the coefficients α andβ, respectively. Therefore, we can deduce that ϕand ρ indicate the long run market shocks andpersistent, respectively.

The coefficients of the Component-GARCHmodel of volatility are also key to our variancebound test. As mentioned earlier in this section,we derive our EMH test by using the f -statistics; for our observed samples, the f -statistics at the 5% level is 1.96. We calculateour test statistics using equation 10 and 11 asthe short run and long run tests of efficiencyrespectively.

EMH TestSR =(α+ β + γ)− 1

std. dev. (var(x)) ≤

≤ F -statistics, (10)

EMH TestLR =(ρ+ ϕ)− 1

std. dev. (var(x)) ≤

≤ F -statistics. (11)

By definition the market is efficient whenthe conditions as set in equations 10 and 11are true. Theoretically, the market is onlytruly efficient when the EMH test statistics isequal to the f -statistic. Hence, we reject thenull hypothesis for the EMH if the conditionin equations are true but accept the nullhypothesis of the market being too volatile tobe efficient for anything else.

4 DATA DESCRIPTION

As stated previously, this paper analyses thethree major German financial markets to es-tablish whether the court ruling means theyare efficient. With this in mind, we test theefficiency of the equity, FX and sovereign debtmarkets. As illustrated in, we opt to use theprice on indices to reflect the German financialmarket. As with the norm, we choose to use a

five-day week filling in the missing data withthe last known price.

It must be noted that similar to all indices thefour indices are based on weighted ratios of thecomponents prices. The DAX consist of thirtyof the largest listed companies on the Germanequity market each weighted by a given ratio.The Euro Currency Index1 is calculated on a

1For a description of the index and how it is calculated see the following Bank of England website:http://bankofengland.co.uk/statistics/pages/iadb/notesiadb/Effective_exc.aspx.


daily basis by the Bank of England using thefive major currencies with a weighted ratio: USDollar, British Sterling, Japanese Yen, SwissFranc and Swedish Krona. As hinted by thename, the German All Maturities GovernmentIndex consists of all the government bondsmaturities weighted by a ratio. The GoldPrice Index consist of all gold markets in theEurozone indexed to 1st January 1999.

A key issue with our variance bound test wasthe standard deviation of the DAX Index andGold market variances which caused a problemwith the EMH test statistics. We tried severalmethods to resolve the issue, the best solutionwas to divide the daily index price by 100 and10 for the DAX and Gold prices respectivelybefore calculating the five-day variance.

5 EMPIRICAL EVIDENCE

As hinted earlier, the keys to the EMH teststatistics are the coefficients to the varianceequation of the volatility model and standarddeviation of the observed dataset. Hence inessence the model of volatility estimated de-termines the statistics. In Fakhry and Richter(2015) and Fakhry et al. (2017), the estimatedmodel was the GARCH. In Fakhry and Richter(2016a, 2016b), the model used was the GJR-GARCH. The GJR-GARCH had the influentialfactor of allowing for the analysis of theasymmetrical effect on the EMH. We continueto use the asymmetrical effect in this paper,however we also analyse the effect of long andshort runs on EMH. For this reason, we usethe C-GARCH with an asymmetrical factorin the estimation of the coefficients. We testfor overall, long run and short run efficiency.We also analyse the behaviour of the Germanfinancial market volatility.

Tab. 2: Model SettingsOption SettingOptimisation Method EViews LegacyLegacy Method MarquandtMax Iterations 5,000Convergence 0.0001Coefficient Covariance Method OrdinaryStarting Coefficient Values EViews Supplied

Presample Variance Backcast withparameter = 0.7

Derivative Method Accuracy

In estimating the models, we used the settingsin Tab. 2. However, with the error distribution,

we used a different distribution model for eachdataset to get the best estimation: Equity (Nor-mal), FX (GED), Sovereign Debt (Student’s t)and Gold (Student’s t). Crucially, the systemenvironment may influence the estimation: Oursystem is running EViews 9.5 on a Windows10 Pro, 6 cores CPU and 24 Gigabytes RAMcomputer2.

A general summarization is the observationof a different in the behaviour of price volatilitybetween the long and short runs in all threefinancial markets. It is to be noted that thevolatility seems to be more persistence in thelong run than the short run. However as arguedby De Bondt (2000), the evidence seem tosuggest that the market is reverting back tothe fundamental value in the long run. A keyexplanation is persistency in market volatilitycan only be observed in the long-run, since thepersistent is based on long memory behaviouras hinted by Engle and Lee (1999). However,the markets seem to be highly reactive in theshort run. This appears to be in accordancewith the accepted wisdom of volatility beinggreater in the short run than the long run asargued by Engle and Lee (1999) and Pastorand Stambaugh (2012). This is to be expected,since behavioural theories dictate that marketparticipants react with greater intensity to newsin the short run as hinted by Engle and Lee(1999). In effect this means that the effect of thereaction of the German market participants onfinancial market volatility is deviating with timeas suggested by Engle and Lee (1999), De Bondt(2000) and Pastor and Stambaugh (2012).

2We tested on a different environment got slightly different estimation results.


Tab. 1: Major German Financial Markets Indices

Market Equity Foreign Exchange Sovereign Debt GoldIndex DAX Effective Exchange

Rate Index, EuroGerman allMaturities Index

Gold Price Index, Euro

Source investing.com Bank of England Barclay Risk Analytics& Index Solutions Ltd.∗)

World Gold Council

Period from 02/01/1981to 31/12/2016

from 02/01/1975to 31/12/2016

from 31/12/1997to 31/12/2016

from 29/12/1978to 30/12/2016

Observations 6,783 10,957 4,958 9,916Note: ∗) It must be noted that on the 24th August 2016 the Barclay Risk Analytics and Index Solutions Ltd. was takenover by Bloomberg. So, the product is now known as Bloomberg Government bonds.

Fig. 1: German Financial Markets Volatility Components

The observed period is interesting because ithighlights the different impact of major eventson the long and short run volatility. Essentially,Fig. 1 highlights the impact from two key eventson the German financial market, financial crisesof late 2007 to 2016. Whichever way you look atit, the financial crises seem to have a strong ef-fect on the three observed markets. Conversely,the Brexit vote on 23rd June 2016 extendedthe volatile period. Of cause the introduction

of the Euro on 1st January 1999 is of significantinterest to the German financial market, yetthe evident from Fig. 1 seem to hint at a slightimpact on the equity and FX markets butnone on the sovereign debt and gold markets.However, it is worth remembering that thesetwo markets are regarded as safe havens andthe introduction of the euro was not regardedas a risk. Another possible explanation is due tothe large impact of the financial and sovereign


debt crises on these two markets, the volatilityin these two markets deviated away. Remembera key theory of the GARCH/ARCH modelsas intended by Engle (1982) and Bollerslev(1986) is that volatility deviates over time, soa highly volatile event in the past becomes lessinfluential with time on the observed dataset.The other major event is the aftermath of there-unification of Germany in 1990 which seemto be highlighted in the FX market but not inthe equity and gold markets. However, a keyfactor during that period could be the impactfrom Black Wednesday on 16th September 1992and the effect it had on the European ExchangeRate Mechanism (ERM).

The high ρ coefficients in Tab. 2 seem tobe indicating the presence of highly persistentpermanent volatility in the equity and FXmarkets. On close inspection of Fig. 1, thereasoning becomes clear, both markets were atthe heart of periods of constant highly volatileenvironment as illustrated in the previous para-graph. Market participants are highly reactiveto events such as these. The second factor isthe long-run effects of the introduction of theEuro and the recent financial and sovereign debtcrises which contributed to the high persistentof volatility. It would seem that the recentcrises were also a relevant contributory for thehigh persistency in the gold market. Conversely,Fig. 1 also explains the low volatility persistencein the sovereign debt market as illustratedby the ρ coefficient of the market in Tab. 3.In comparison to the other three observedmarkets, the sovereign debt market seemed tobe relatively stable until the recent crises withonly a few minor hikes in volatility. A possibleexplanation is generally during a period ofeconomic and financial market upturn like theearly to mid-2000s, market participants areless reactive and thus market volatility is lesspersistent. This leads to another explanation,during a period of increasing asset prices,market participants look for high return riskymarkets, in simple terms acting irrationallyleading to a bubbled market. The sovereign debtmarket is generally regarded as a risk-free lowearning market, especially the German market.As explained earlier, the short run volatility

persistent tends to be generally low, a pointin case are the observed β coefficients of allfour markets in Tab. 3. The coefficients seem tobe hinting at very low volatility persistency inall four markets with coefficients of not greaterthan 0.708.

As implied by Engle and Lee (1999), theorydictates over a long-time horizon market shockstend to decay in ferocity. Thus, meaning thatin the long run the effect of any event inducinghigh market shocks on prices become lessrelevant. This is observed in the equity, goldand FX markets as illustrated by Tab. 3 withthe φ coefficients pointing to a lower marketshock in the long run. In effect the φ coefficientsare under 0.1 for all three markets hintingat a low sensitivity to market shocks. AsFig. 1 illustrates, all three markets suffered asignificant hike in price volatility during therecent crises period plus the Brexit vote andthe � coefficients, greater than 0.2, seem to bereflecting this hike. Mainly due to the timingand severity of a combination of events (i.e.the recent Eurozone sovereign debt crises andBrexit vote) and the German sovereign debtmarket status as the safe haven and liquidmarket in the Eurozone, the long run effect ofthe shocks in the sovereign debt market did notdecay away given the time horizon as illustratedby the φ coefficient at 0.186334. In the shortrun, the high � coefficient of 0.312428 is a signof the market during the crises period.

A key observation made in Fakhry andRichter (2016a, 2016b) is that the asymmetricaleffect has an impact on the efficiency of themarket. As illustrated by Tab. 3, we observeda low γ coefficient for all four markets withabsolute value of no greater than 0.09 observedin the gold market. This does mean that thereis a limited asymmetrical effect in each of themarkets. The equity and gold markets display anegative γ coefficient which means that negativeshocks to the market have greater impact thanpositives shocks in the short run. As hinted byBlack (1976), a key observation often made inthe equity market is the negative correlationbetween returns and volatility. The limitedleverage effect is a hint of this observation.The key word in there being limited, for an


Tab. 3: Statistics for Variance Bound Test using Asymmetrical C-GARCH model

Equations:(6) mt = ω + ρpmt−1 + φq(kt−1 − ht−1)

(9) (ht −mt) = σ2 + (αpkt−1 −mt−1) + (βqht−1 −mt−1) + γ(kt−1 −mt−1)I

(10, 11) EMH Test =∑

coefficients− 1

std. dev. (var(Price))

Market Equity Foreign Exchange Sovereign Debt GoldMean Equationa 0.071782* 0.009607* 0.020584* 0.005543*

(0.002136) (0.000192) (0.000678) (8.41E-06)b 0.716483* 0.736035* 0.691017* 0.719573*

(0.006919) (0.003483) (0.006640) (0.001878)µ 0.507201* 0.306194* 0.377432* 0.375839*

(0.013024) (0.006653) (0.015129) (0.000891)Volatility Equationω 7.480590* 0.029847 0.026859 −2.37E-05

(0.384085) (0.033685) (0.003366) (2.16E-06)Long-run Price Volatilityρ 0.999998* 0.998977* 0.847473* 0.987450*

(6.43E-08) (0.001167) (0.023697) (9.24E-04)φ 0.039161* 0.087957* 0.186334* 0.008243*

(0.000976) (0.022952) (0.022307) (0.002056)Short-run Price Volatilityα 0.213435* 0.359580* 0.312428* 0.453493*

(0.003626) (0.019467) (0.017036) (0.020139)γ −0.019528* 0.062521* 0.012089* −0.092895*

(0.005517) (0.007920) (0.001591) (0.015680)β 0.707345* 0.577842* 0.675722* 0.646091*

(0.005470) (0.025604) (0.017817) (0.008971)Model StatisticsLog Likelihood 1,374.877 20,161.730 7,075.928 28,617.290R2 0.719687 0.712889 0.725742 0.751854DW-Statistics 2.156971 1.625504 1.575250 1.686794ARCH Effects 0.339560 0.028096 0.018395 0.526407Jarque-Bera 434,325.400 22,946,634.000 491,035.900 3,280,997.000σ2 1.193893 0.166384 0.317139 0.233287Efficiency TestsLong-run EfficiencyEMH Statistics 0.032799 0.522490 0.106600 0.018462Efficiency Accept Accept Accept AcceptShort-run EfficiencyEMH Statistics 0.082711 0.000343 0.000754 0.028673Efficiency Accept Accept Accept Accept

Notes: The numbers in brackets are standard errors, *** indicated 10% significance level, ** is 5% and * is 1%.


explanation we need to look at the observedGerman equity and gold markets. It is highlypossible that during the period before the on-slaught of the recent global financial crises, bothmarkets experienced one type of asymmetricaleffect. However, the onslaught of the recentglobal financial crises changed the asymmetriceffect. The positive and negative effects mayhave counter-balanced each other, hence leadingto the near zero impact. Conversely, due to thetiming and ferocity of the negative impact onthe markets during the recent global financialcrises, there is a limited leverage effect. The tworemaining markets point to a limited positiveasymmetrical effect hinting at positive shocks tothe market having a greater impact than neg-ative shocks in the short run. An explanationfor the observations of positive asymmetricaleffects could be found in a combination of theglobal status of both markets and the recentglobal financial environment. This added to thereversed of the combination effect underpinningthe explanation of the observed limited leverageeffect in the equity and gold markets meansthat the FX and sovereign debt markets exhibitslight positive asymmetrical effects.

A key measure of risk factors in the marketis the standard deviation, essentially defined asthe dispersion of the observed market pricesaround the expected market price. The stan-dard deviation statistics from Tab. 3 seem to behinting at a large dispersion from the expectedprice variance in the equity market with a σ2 ofapproximately 1.194. A clue is in Fig. 1, boththe long and short run volatilities hint at alarge hike in the equity market during the recentfinancial crises which gives the impression ofa large dispersion in the equity market. TheFX market has a low standard deviation ofapproximately 0.166, this is to be expected since

the euro did not deviate from the expectedvalue by much. Even during the Eurozonecrises, the movement against the benchmarkcurrencies was not that great in both thelong and short runs, as hinted by Fig. 1. Thesovereign debt market suffered from spikes inthe volatility during the Eurozone crises whichis indicated by the low standard deviation of0.317 and the level of volatility in Fig. 1. Itmust be noted that the German sovereign debtmarket is regarded as the risk-free benchmarkmarket in the Eurozone, so the movement inthe market was mainly due to runs in theEurozone markets leading to upward pressureson the German sovereign debt market. Andas the age old saying by Isaac Newton goes:“what goes up must come down” eventually,hence the normalisation of the sovereign debtmarket towards the fundamental long run valuemay have also been a factor in the moderatestandard deviation. The same could be saidabout the gold market, remember the goldmarket is the global safe haven market. Inessence, the gold market, similar to many othercommodity markets, suffered a bubble reactionduring the global financial crises. However, thelow dispersion is a sign that the impact of theglobal financial crises did not impact the overallobservation.

Essentially, our variance bound test is sayingthat for a market to be efficient it mustbe efficient in the short and long runs. Asillustrated by Tab. 3, the significant of thevariance bound test is the results seem tobe hinting at the acceptance of the EMH inall the observed markets in both the shortand long runs. The statistics are damming forbehavioural finance with EMH statistics notgreater than 0.6, it must be remembered thatthese are well within the bound of 1.96.

6 CONCLUSION

In this paper, we extended the work done byFakhry and Richter in recent years to analysethe efficiency of the German financial marketin the short and long runs. We differed fromprevious work by Fakhry and Richter in using a

five-day variance calculation and the key indicesof the German market. We used a ComponentGARCH including a threshold to obtain theshort and long runs’ volatility and coefficientsfor our EMH tests.


Our results show that the German financialmarket is efficient in both the short and longruns. The results seem to be a dammingrejection of the behavioural finance theory andan endorsement of the court ruling. However,as is the case with any test there are a numberof factors to account for. The first and foremostis the observational period in all the market,if the period was based around the financialand sovereign debt crises then the results mayhave been different. The second is the volatilitymodel, i.e. Component GARCH, underpinningour volatility tests could be a key factor in theacceptance of the EMH. It would be interestingto see if the German financial market wasefficient around the crises period of the late2000s to early 2010s. Given that the resultsof Fakhry and Richter (2015, 2016a, 2016b)

did found that the German market is generallyinefficient during the crisis period.

Our main contribution, the methodology,is relevant in analysing the long and shortrun efficiency of the market and thereforemaking the optimal investment decision be itin an asset or as part of a portfolio. Theresults of our empirical study are important forresearchers in the fields of applied finance andportfolio management. Additionally, the papercan be useful for portfolio managers and marketparticipants in making investment decisions orportfolio optimisation.

In concluding, the results seem to suggestthat the court case was right to endorse theEMH. However, we urge caution on rejectingthe behavioural finance theory due to pastempirical evidence suggesting that the Germanmarket is not always efficient.

7 REFERENCES

Adrian, T. and Rosenberg, J. 2008. Stock Returnsand Volatility: Pricing the Short-Run and Long-Run Components of Market Risk. The Journal ofFinance, 63 (6), 2997–3030.

Ahmad, R., Rhee, S. G. and Wong, Y. M. 2012.Foreign Exchange Market Efficiency under RecentCrises: Asia-Pacific Focus. Journal of InternationalMoney and Finance, 31 (6), 1574–1592.

Ball, R. 2009. The Global Financial Crisis and theEfficient Market Hypothesis: What Have WeLearnt? Journal of Applied Corporate Finance,21 (4), 8–16.

Barlevy, G. 2007. Economic Theory and AssetBubbles. Economic Perspectives, 31 (3), 44–59.

Black, F. 1976. Studies of Stock Market VolatilityChanges. In Proceedings of the 1976 Meeting ofthe Business and Economic Statistics Section,American Statistical Association, pp. 177–181.

Blanchard, O. J. and Watson, M. W. 1982. Bubbles,Rational Expectations and Financial Markets.National Bureau of Economic Research, WorkingPaper No. 945.

Boboc, I.-A. and Dinică, M.-C. 2013. An Algorithmfor Testing the Efficient Market Hypothesis. PLoSONE, 8 (10).

Bollerslev, T. 1986. Generalized AutoregressiveConditional Heteroskedasticity. Journal ofEconometrics, 31 (3), 307–327.

Borges, M. R. 2010. Efficient Market Hypothesis inEuropean Stock Markets. The European Journalof Finance, 16 (7), 711–726.

Brunnermeier, M. K. 2009. Deciphering the Liquidityand Credit Crunch 2007–2008. The Journal ofEconomic Perspectives, 23 (1), 77–100.

Colacito, R., Engle, R. F. and Ghysels, E. 2011.A Component Model for Dynamic Correlations.Journal of Econometrics, 164 (1), 45–59.

Du, D. and Hu, O. 2014. The Long-Run Componentof Foreign Exchange Volatility and Stock Returns.Journal of International Financial MarketsInstitutions and Money, 31 (1), 268–284.

De Bondt, W. F. M. 2000. The Psychology ofUnderreaction and Overreaction in World EquityMarkets. In Keim, D. B. and Ziemba, W. T. (eds.).Security Market Imperfections in World WideEquity Markets, pp. 65–89. Cambridge: CambridgeUniversity Press.

Economou, F., Kostakis, A. and Philippas, N.2011. Cross-Country Effects in Herding Behaviour:Evidence from Four South European Markets.Journal of International Financial Markets,Institutions and Money, 21 (3), 443–460.

Engle, R. F. 1982. Autoregressive ConditionalHeteroscedasticity with Estimates of the Varianceof United Kingdom Inflation. Econometrica, 50 (4),987–1007.


Engle, R. F. and Lee, G. G. J. 1999. A Long-Runand Short-Run Component Model of Stock ReturnVolatility. In Engle, R. F. and White, H. (eds.).Cointegration, Causality and Forecasting – AFestschrift in Honour of Clive W. J. Granger.Oxford: Oxford University Press.

Engle, R. F. and Patton, A. J. 2001. What Good isa Volatility Model? Quantitative Finance, 1 (2),237–245.

Fakhry, B. 2016. A Literature Review of the EfficientMarket Hypothesis. Turkish Economic Review,3 (3), 431–442.

Fakhry, B. 2018. Impact of the Crises on the Efficiencyof the Financial Market: Evidence from the SDM.KSP Books.

Fakhry, B. and Richter, C. 2015. Is the SovereignDebt Market Efficient? Evidence from the US andGerman Sovereign Debt Markets. InternationalEconomics and Economic Policy, 12 (3), 339–357.

Fakhry, B. and Richter, C. 2016a. Testing theEfficiency of the Sovereign Debt Market usingan Asymmetrical Volatility Test. Journal ofManagement and Training for Industries, 3 (2),1–15.

Fakhry, B. and Richter, C. 2016b. Testing theEfficiency of the GIPS Sovereign Debt Marketsusing an Asymmetrical Volatility Test. Journal ofEconomics and Political Economy, 3 (3), 524–535.

Fakhry, B., Masood, O. and Bellalah, M. 2017. Arethe GIPS Sovereign Debt Markets Efficient Duringa Crisis? Journal of Risk, 19 (S1), 27–39.

Fama, E. F. 1965. Random Walk in Stock MarketPrices. Financial Analyst Journal, 21 (5), 55–59.

Ferreira, S. and Karali, B. 2015. Do EarthquakesShake Stock Markets? PLoS ONE, 10 (7).

Gerlach, J.-C., Demos, G. and Sornette, D. 2018.Dissection of Bitcoin’s Multiscale Bubble Historyfrom January 2012 to February 2018 [online].Available at: https://arxiv.org/abs/1804.06261[Accessed 2018, October 1].

Guo, H. and Neely, C. J. 2006. Investigatingthe Intertemporal Risk-Return Relation inInternational Stock Markets with the ComponentGARCH Model. Economics Letters, 99 (2),371–374.

Jiang, Z.-Q., Zhou, W.-X., Sornette, D.,Woodard, R., Bastiaensen, K. and Cauwels, P.2010. Bubble Diagnosis and Prediction of the2005–2007 and 2008–2009 Chinese Stock MarketBubbles. Journal of Economic Behavior andOrganization, 74 (3), 149–162.

Lee, H. and Sodoikhuu, K. 2012. Efficiency Test inForeign Exchange Market. International Journalof Economics and Financial Issues, 2 (2), 216–224.

Lee, W. Y., Jiang, C. X. and Indro, D. C. 2002.Stock Market Volatility, Excess Returns and theRole of Investor Sentiment. Journal of Banking &Finance, 26 (12), 2277–2299.

Luo, N. 2012. The Impact of Natural Disasters onGlobal Stock Market: the Case of the Japanese2011 Earthquake [online]. Available at: http://library2.smu.ca/handle/01/24714#.WWYR_YjysuU[Accessed 2018, February 19].

Maierhofer, S. 2011. 5 Worst Disasters –How Did the Stock Market React? [online].Available at: http://www.nasdaq.com/article/5-worst-disasters-how-did-the-stock-market--react-cm68124 [Accessed 2018, February 15].

Malkiel, B. G. 1962. Expectations, Bond Prices,and the Term Structure of Interest Rates. TheQuarterly Journal of Economics, 76 (2), 197–218.

Malkiel, B. G. and Fama, E. F. 1970. Efficient CapitalMarket: A Review of Theory and Empirical Work.The Journal of Finance, 25 (2), 383–417.

Mali, P. and Mukhopadhyay, A. 2014. MultifractalCharacterization of Gold Market: A MultifractalDetrended Fluctuation Analysis. Physica A:Statistical Mechanics and its Applications, 413,361–372.

Masood, O., Aktan, B., Gavurová, B., Fakhry, B.,Tvaronavičienė, M. and Martinkutė-Kaulienė, R. 2018. The Impact of Regime-Switching Behaviour of Price Volatility onEfficiency of the US Sovereign Debt Market.Economic Research (Ekonomska Istraživanja),30 (1), 1865–1881.

Mele, M. 2015. On the Inefficient Markets Hypothesis:Arbitrage on the Forex Market. InternationalJournal of Economics, 9 (2), 111–122.

Narayan, P. K., Narayan, S. and Zheng, X. 2010.Gold and Oil Markets: Are Markets Efficient.Applied Energy, 87 (10), 3299–3303.

Nofsinger, J. R. and Sias, R. W. 1999. Herding andFeedback Trading by Institutional and IndividualInvestors. Journal of Finance, 54 (6), 2263–2295.

Onali, E. and Goddard, J. 2011. Are EuropeanEquity Markets Efficient? New Evidence fromFractal Analysis. International Review of FinancialAnalysis, 20 (2), 59–67.

Panagiotidis, T. 2010. Market Efficiency and theEuro: the Case of Athens Stock Exchange.Empirica, 37 (3), 237–251.

Parker, M. and Steenkamp, D. 2012. The EconomicImpact of the Canterbury Earthquakes. ReserveBank of New Zealand Bulletin, 70 (3), 13–25.

Pastor, L. and Stambaugh, R. F. 2012. Are StocksReally Less Volatile in the Long Run? The Journalof Finance, 67 (2), 431–478.


Sensoy, A. and Tabak, B. M. 2015. Time-varyingLong Term Memory in the European Union StockMarkets. Physic A, 436, 147–158.

Shiller, R. J. 1979. The Volatility of Long-TermInterest Rates and Expectations Models of theTerm Structure. The Journal of Political Economy,87 (6), 1190–1219.

Shiller, R. J. 1981. The Use of Volatility Measuresin Assessing Market Efficiency. The Journal ofFinance, 36 (2), 291–304.

Singh, P., Deepak, C. A. and Kumar, A. 2015.Revisiting Weak Form Efficiency of Major EquityMarkets in Light of Global Financial Crisis: APanel Data Approach. Asia-Pacific Finance andAccounting Review, 3 (1), 17–44.

Sornette, D. and Cauwels, P. 2015. FinancialBubbles: Mechanisms and Diagnostic. Reviews ofBehavioral Economics, 2 (3), 279–305.

Sosvilla-Rivero, S. and Morales-Zumaquero, A.2012. Volatility in EMU Sovereign Bond Yields:Permanent and Transitory Components. AppliedFinancial Economics, 22 (17), 1453–1464.

Thaler, R. H. 2015. Misbehaving: The Making ofBehavioural Economics. Penguin Random House.

Todea, A. and Lazar, D. 2012. Global Crisis andRelative Efficiency: Empirical Evidence fromCentral and Eastern European Stock Markets. TheReview of Finance and Banking, 4 (1), 45–53.

Wang, Y., Wei, Y. and Wu, C. 2011. Analysis of theEfficiency and Multifractality of Gold MarketsBased on Multifractal Detrended FluctuationAnalysis. Physica A: Statistical Mechanics and itsApplications, 390 (5), 817–827.

Winkler, A. 2014. Rescues Violating the GermanConstitution: The Federal Court Decides on aTheory of Finance. LSE Financial Markets GroupSpecial Paper Series, SP No. 231.

Zakoian, J.-M. 1994. Threshold HeteroskedasticModels. Journal of Economic Dynamics andControl, 18 (5), 931–955.

Zhang, Y. and Wei, Y. 2010. The Crude Oil Marketand the Gold Market: Evidence for Cointegration,Causality and Price Discovery. Resources Policy,35 (3), 168–177.

AUTHOR’S ADDRESSBachar Fakhry, The University of Lahore, School of Accountancy and Finance, Lahore,Pakistan, e-mail: [email protected]

Christian Richter, German University in Cairo, Faculty of Management Technology,Department of Economics, New Cairo City, Egypt, e-mail: [email protected]


www.ejobsat.com

READY FOR CHANGES?THE INFLUENCE OF GENERALSELF-EFFICACY AND RESISTANCETO CHANGE ON MANAGERS’ FUTURECOMPETENCE REQUIREMENTSJürgen Mühlbacher1, Tom Siebenaler11Vienna University of Economics and Business, Austria

MÜHLBACHER, Jürgen, and SIEBENALER, Tom. 2018. Ready for Changes? The Influence of GeneralSelf-Efficacy and Resistance to Change on Managers’ Future Competence Requirements. European Journal ofBusiness Science and Technology, 4 (2): 126–142. ISSN 2336-6494,DOI http://dx.doi.org/10.11118/ejobsat.v4i2.131.

ABSTRACT

With this study, we will test the interrelations between the psychological concept of self-efficacyof managers and its influences on the resistance to change. The results show that it makes aqualitative difference, if change in competences occurs in a positive or a negative direction andthat there is a clear predisposition of managers concerning change. Both results have to be takeninto account in designing changes processes.

KEY WORDS

competence management, self-efficacy, resistance to change

JEL CODES

M100, O100

1 INTRODUCTION

For more than a hundred years, the topic ofwhat tasks a manger has to fulfil and whatthe manager of the future will look like hasbeen much reflected on. While in earlier daysthe main emphasis was on the analysis of thejob and functional aspects such as planning,coordinating and organising, management dis-course changed drastically with the introduc-tion of post-bureaucratic reforms and the rise ofthe competence movement (McClelland, 1973).Instead of the workplace, the focus is now onthe persons themselves as well as their abili-

ties, knowledge and skills. Subsequent studiesproposed several competences managers shouldpossess, including interacting with people, pre-senting, organizing and executing. Because ofcurrent trends such as globalisation and theincreasing amalgamation of occupational andprivate life (Ford and Collinson, 2011), man-agers are furthermore expected to act effectivelyin unforeseeable and complex situations. Inother words, managers should have a rangeof competences that enables them to act ina self-organised manner (Erpenbeck and von

Ready for Changes? The Influence of General Self-Efficacy and Resistance to Change on … 127

Rosenstiel, 2003) – even in a rapidly changingbusiness environment. As a direct consequenceof these new changes, companies were more andmore looking for “managers of the future, notof the present” (Woodruffe, 1993, p. 34).

However, despite their importance, future-oriented competences in competence researchhave been greatly neglected (e.g. Robinson etal., 2007). A main reason is that competence as-sessment methods such as the critical behaviourinterview largely focused on a manger’s pastperformance. Competence requirements werethus in the best case present-oriented and inthe worst case derived from past events. Onlyrecently, both past and future competenceshave been analysed to a greater extent (e.g.Campion et al., 2011; Mühlbacher, 2007). Schol-ars such as Robinson et al. (2007) proposedseveral methodological principles (e.g., includ-ing a time horizont) and more recent studiesempirically examined the future significance ofmanagerial competences required by healthcareexecutives and commercial kitchen chefs (e.g.Giousmpasoglou et al., 2016).

According to Woodruffe (1993), there are twooptions for looking into “the future”: the focusof analysis is either on change competences,which are required in order to deal withunforeseeable situations, or on changing com-petences, which represent future competencerequirements. The former group – competencesof “changeability” (Woodruffe, 1993, p. 35) –has been extensively studied (e.g., Paton andMcCalman, 2008) and often presented in theform of lists. On the other hand, previous workson “competency life cycles” (e.g., Sparrowand Boam, 1992) clearly differentiate betweenemerging and maturing competencies and pointtoward the changing nature of competences. Re-cent developments such as constantly changingrequirements at work, high expectations frommanagers, and increasing competition (Tripathiand Agrawal, 2014) strengthen the demand fora better understanding of future competencerequirements which are therefore the subject ofthis study.

Empirically, it can be shown that managersgreatly differ in their competence requirements(e.g., Lakshminarayanan et al., 2016). Some

perceive an increasing demand for competencesof a particular class, while others detect a fall.In other words, not all managers respond in thesame way to the idea of changing competences(e.g., Boyatzis and Saatcioglu, 2008; Dierdorffet al., 2009). The question why managers seedifferent requirements and what factors explainthis difference in perception has not beenaddressed in the literature so far. Thus, thisstudy aims at closing this research gap and atidentifying potential predictors that explain therise and fall in competence requirements.

It can be argued that the concept of theself is the starting point for every changeprocess that affects a person’s actions, habitsor competences (Boyatzis, 2006; Taylor, 2006).Besides competence research, the psychology ofthe self hence is a theoretical basis for thisstudy. Competences are seen as prerequisites forself-organised behaviour, which allow managersto act even in unforeseeable situations (Er-penbeck, 2011; Erpenbeck and von Rosenstiel,2003). Knowledge of one’s own self is oftenformulated in a so-called theory of the self whichassumes that people aim for a better under-standing for themselves and rely on their self-knowledge when making decisions (Oysermanet al., 2012). The best known such theory is thetheory of cognitive dissonance (Festinger, 1957),which postulates that people generally strive tobe consistent in their behaviour and act in linewith their self-concept. In case of a discrepancy,on the other hand, people experience discomfortand a certain state of tension, also calleddissonance. They are subsequently motivatedto either change their attitude or behaviour inorder to appear reasonable in their decisions.

A further important component is the dis-positional perspective. It presumes that peoplehave certain psychological predispositions to-wards changes (Holt et al., 2010). Accordingly,personal characteristics should play a crucialrole in the perception of a change as a benefit ora threat (Vakola et al., 2013). More specifically,several authors argue that the perceived abilityas well as a person’s will to accept changes havea strong influence on how changes are dealt with(e.g. Holt et al., 2010). In the following study,the perceived ability is operationalised through

128 Jürgen Mühlbacher and Tom Siebenaler

the use of the personality trait of general self-efficacy (Judge et al., 1998), which captures thegeneralized belief of individuals to possess theresources required to fulfil task demands (Chenet al., 2001). On the other hand, the willingnessto accept changes is operationalised by meansof a person’s resistance to change (Oreg, 2003),which can be defined as a predisposed inclina-tion of an individual to avoid change. Studieshave shown that both personality traits areconnected with how changes are dealt with (e.g.Judge et al., 1999; Oreg, 2006). For this reason,these were then tested as predictors of rising orfalling competence requirements.

The research model suggested can thus beseen as an answer to the criticism of compe-

tence research to neglect future-oriented compe-tences. By including not only current and futurecompetences, but also potential predictors ofcompetence requirements, the study addition-ally aims to find an answer to the question ofwhat factors predict a rise or fall in competencerequirements. Competence research, the theoryof the self, and the dispositional perspective ofchange management thus build the theoreticalfoundation to answer the following researchquestion: what influence do personality traits –in the form of general self-efficacy and resistanceto change – have on the increase and decreasein competence requirements?

2 THEORETICAL BACKGROUND

The theoretical background of this study isbased on competence research, the theory of theself and the dispositional perspective in changemanagement.

2.1 Competence Research

The most important objectives of occupationalcompetence development are the establishmentand promotion of professional behavioural com-petence. The main focus is put on the in-tegration of cognitive, emotional-motivational,volitional and social aspects of human be-haviour in work situations (Heyse, 1997, p. 6).An early differentiation was provided by Jacobs(1989, p. 36), who distinguishes between “hardand soft competencies”. Hard competences referto, for instance, analytical and organisationalabilities, while creativity and sensitivity arepart of soft competences. From this, Jacobsderives the assumption that hard competencesresult in observable behaviour and, at thesame time, the invisible but controlling softcompetences are underlying elements.

This distinction was later differentiated intofour types of competence, which meet boththeoretical and pragmatic requirements (Heyse,1997, p. 6). A concise overview of these fourcompetence classes can be found in Sonntag

and Schaper (1999, p. 411ff). They includeprofessional competence, method competence,social competence as well as self- and personalcompetence. This classification was then re-worked itself. In more recent classifications, par-ticularly professional and method competenceshave been fused, due to their similarities anda desired construction of a general competencemodel, while self- and personal competence aresub-divided further. The aim is to enable adifferentiated observation of dispositions andself-organised behaviour.

The concept by Erpenbeck and von Rosen-stiel (2003) – though working on a moreabstract level – provides a current classifica-tion. It also comprises four general competenceclasses, but their differentiation is based onthe idea that mental or physical behaviouralways represents subject-object or subject-subject relationships. Self-organised behaviourcan (1) reflexively relate to the acting personitself or (2) relate to the professional-methodicalrecognition and change of the concrete environ-ment. It can be (3) oriented towards the socialenvironment and thus to other persons andgroups or it (4) more closely characterises theactivity and willingness component of the actor(Erpenbeck and von Rosenstiel, 2003, p. XV).From this, generally the following competence


classes can be derived (Erpenbeck and vonRosenstiel, 2003, p. XVI): (1) personal com-petences, (2) professional-methodical compe-tences, (3) social-communicative competencesand (4) activity- and implementation-orientedcompetences.

Although this classification is a general tax-onomy, the authors themselves remark thatallocating individual and sub-competences tothese classes might lead to problems. This holdsparticularly true for the difficult demarcationof the class of activity- and implementation-oriented competences, which in fact only refersa person’s ability to implement – and thusa combination of his or her professional-methodical and social-communicative compe-tences. Further problems might arise in allo-cating traits (such as ambition, diligence orpersistence) that might belong to either thefirst or the fourth class (Erpenbeck and vonRosenstiel, 2003, p. XVI).

Therefore, this study mainly focuses on thegeneral differentiation between professional andmethod competences on the one hand and socialcompetences on the other. Although the stateof the art is reduced, this makes a connectionto the central leader-manager differentiationpossible (Bennis, 1989). According to this,“managers” are executives, who put an empha-sis on control, prefer orderly proceedings andare rather professionally competent. “Leaders”,in contrast, think for the long term, want toconvey a vision and have social-communicativecompetences (Bennis, 1989).

2.2 Theory of the Self

As it can be argued that individuals cannotevaluate their own competences and futurecompetence requirements without taking re-course to their own self-concept (Crocker andCanevello, 2012, p. 263), the self plays animportant part. A person’s self influences alltheir behaviour, habits and competences andcan be interpreted both as the starting point(e.g. Boyatzis, 2006, p. 613; Taylor, 2006) andthe subject of change processes. In addition,the self, in the form of self-organisation theory,is closely connected with competence research

(Erpenbeck and Heyse, 1999; Erpenbeck andvon Rosenstiel, 2003). Psychological theories ofthe self can therefore bring new insights regard-ing rising and falling competence requirements.

The theory of cognitive dissonance (Fes-tinger, 1957) is regarded as one of the mostinfluential theories of the self (e.g. Nail et al.,2004) and postulates that people strive to actconsistently and to make rational decisions vis-à-vis the outside world. If there is a discrep-ancy between one’s own values (e.g. healthylifestyle), cognition (e.g. seeing oneself as asportsperson) and behaviour (e.g. smoking),individuals experience an inner tension, alsocalled dissonance. The greater the discrepancy,the stronger the desire to release this tension.The self-affirmation theory (Steele, 1988), avariant of dissonance theory, assumes thatpeople generally are motivated to maintaina positive image of self-integrity. Thoughts,events or behaviour that threaten this imageof self-integrity are perceived as a psychologicalthreat (Cohen and Sherman, 2014).

In order to counter this threat, people tendto emphasise their individual strengths andthus to newly define success. An importantmechanism is to have access to several existingidentities and therefore have different sources ofintegrity available (Steele, 1988). By means ofself-affirmation it is thus possible to compensatefor perceived mistakes by being successful inother areas relevant for the self (e.g. a spe-cific competence, a certain hobby). In otherwords, self-affirmation allows for a constant re-interpretation of events that are important tomaintain one’s own self-image by placing thefocus of attention on successful characteristics.

2.3 Dispositional Perspective inChange Management

As rising and falling competence requirementscan be perceived as either a positive or negativechange by the managers (e.g. Bouckenooghe,2010), the research field of change manage-ment also is a theoretical foundation for thisstudy. The dispositional perspective in changemanagement is particularly important in thiscontext, as a number of studies have pointed


out the influence of personality traits in thechange process (e.g. Herold et al., 2007). Judgeet al. (1999), for instance, identified a totalof seven personality traits (e.g. general self-efficacy, locus of control) that are related totackling changes. The dispositional perspectivethus assumes that individuals are predisposedto react to changes in a certain manner andregard these as either threatening or useful (e.g.Oreg et al., 2011; Vakola et al., 2013). It isfurther argued that the willingness to changerequires both the will to accept changes and acertain degree of self-confidence or self-efficacyto successfully cope with the changes to come.

General self-efficacy was conceived on thebasis of Bandura’s (1977) concept of self-efficacy, which describes a person’s convictionto be able to deal successfully with even difficultsituations in their own right (Łuszczyńska etal., 2005). Originally conceived as a situation-specific construct, self-efficacy includes a per-ceived feeling of control with which peoplecan change their behaviour. Also empirically,a connection between persons’ self-efficacy andtheir willingness to accept changes has beenfound (e.g. Amiot et al., 2006).

In order to record the influence of howconvinced people are of their own self-efficacyirrespective of the situation, Bandura’s originalconcept was conceived as a personality trait(Judge et al., 1998). The concept of generalself-efficacy developed from this describes thepersonal assessment of one’s own competencesto tackle challenges in various situations. Sev-eral studies have shown that people evalu-ate changes depending on their general self-efficacy (e.g. Hornung and Rousseau, 2007).One explanation for this connection is theexistence of a self-reinforcing mechanism (Judgeet al., 1998). Persons with a high general self-efficacy, for example, increase their chances forsuccess, which in turn reinforces them in theircompetences. On the other hand, it is arguedthat a high degree of general self-efficacy indifferent situations tempts people into actingproactively and flexibly. For these reasons,it is presumed that general self-efficacy has

an influence on rising and falling competencerequirements:

H1: General self-efficacy influences rising andfalling competence requirements.

The component of willingness is opera-tionalised using the concept of resistance tochange. Research into the question why certainpeople are negatively disposed towards changesand actively resist them goes back all the wayto the year 1948, when Coch and French (1948)analysed the phenomenon empirically. Overthe years, a multitude of definitions emergedwith a common negative focus on changes(Bouckenooghe, 2010). This traditional point ofview, which generally related changes to stress,was more and more criticised at the beginningof the 2000s (e.g. Piderit, 2000). The argumentwas that the majority of studies on this topicrelied too much on the behavioural level (whatdo people do to resist changes) and, in turn,the cognitive (what do people think of changes)and emotional (what do people feel in view ofchanges) components were neglected.

Responding to this criticism, Oreg (2003) hassuggested conceptualising resistance to changeas a personality trait that includes cognitive,affective and behavioural elements. Resistanceto change in this sense is described as a pre-disposed tendency to avoid changes. A personwith a high level of resistance to change thusperceives changes as rather negative, more fre-quently associates them with negative feelingsand generally integrates fewer changes in hisor her daily life. In a comprehensive surveyarticle on the subject of reactions to changescovering a period of 60 years, Oreg et al. (2011)describe resistance to change as a predictorof changes. Similarly, several authors arguethat resistance to change is one of the mainreasons for differences in people’s willingnessto change (e.g., Oreg and Sverdlik, 2011). Forthese reasons it is assumed that resistance tochange also has an influence on rising and fallingcompetence requirements:

H2: Resistance to change influences risingand falling competence requirements.


3 METHODOLOGY AND DATA

Constructs that cannot be measured directly– such as personality traits or competence re-quirements – often manifest in a culture-specificform (e.g., Fischer and Schwartz, 2011). As areview of several guidelines for cross-culturaladaptation “could not bring out a consensus”(Epstein et al., 2015, p. 435) on how to limitpossible cultural biases, the following studywas conducted in a culturally diverse environ-ment: The Grand Duchy of Luxembourg. Asa founder member of the European EconomicCommunity (EEC), the tranquil Grand Duchyis the seat of several EU institutions (e.g.European Court of Justice, European Courtof Auditors, European Investment Bank) andis seen, besides Brussels and Strasbourg, asan EU capital. Its international orientationis also reflected in its population figures: in2016, the percentage of foreigners living inLuxembourg was 46.71% (STATEC, 2016).Resident foreigners also account for 71% of theworking population (Luxembourg for Financeand Luxembourg for Business, 2015). The morethan 170 nationalities, numerous commutersand the phenomenon of multilingualism furthercharacterise Luxembourg’s cultural diversity.Moreover, with a growth rate consistentlyabove the EU average and a public debt atonly 23.20% of the gross domestic product(Luxembourg for Finance and Luxembourgfor Business, 2015), Luxembourg will remainattractive for foreigners from all over the world.For this reason, Luxembourg lends itself fora study of competence requirements, whichare also needed internationally. The empiricalsurvey was thus based on a self-selective sampleof 274 Luxembourgish managers. The followingmethod section provides more detail on thesample of participants, the variables collected,and data collection and analysis.

3.1 Sample

Data were collected between June 2015 andFebruary 2016. In this stage, a total of 2,226managers working in various sectors in Lux-embourg with at least one direct employee

were contacted. Of these, 274 managers replied,which is a response rate of 12.31%. Accordingto Tabachnick and Fidell (2007) as well as Field(2013), this is a sufficient sample to calculate arobust regression model. During data collection,the participants were asked to state whetherthey were active in top, upper or middle man-agement. The sample turned out to include 104participants (37.96%) from top management,75 (27.37%) from upper management, and 95(34.67%) from middle management.

Of the 274 managers, 39 were women(14.23%) and 235 men (85.77%). The averageage was 49 years (SD = 7.15), with 24 managersbetween 30 and 39 years (8.76), 100 between40 and 49 years (36.50%), 135 between 50and 59 (49.27%) and 15 older than 60 years(5.47%). In the sample, altogether 17 nation-alities were represented, with a majority of themanagers stating to be Luxembourg nationals(48.18%). Other large groups of managers wereBelgian (16.79%), French (16.42%) and Germannationals (8.03%). The sample thus reflectsthe multicultural environment of Luxembourgand underlines the influence of cross-borderworkers (Thewes, 2008). When asked for theirmother tongue, most managers replied Lux-embourgish (44.53%), French (34.31%) andGerman (10.58%). Regarding their education,167 managers stated to have a master’s degree(60.95%) and 54 a bachelor’s degree (19.71%).A further 36 managers stated to have finishedhigh school (13.14%) and 17 had a Ph.D.(6.20%). The majority of the managers studiedbusiness and economics (33.21%), followed byIT (25.91%) and engineering (24.09%).

On average, the managers participating had15 years of work experience (SD = 8.02). Theyworked in organisations with an average of 727employees (SD = 1010.27), with 71 managers(25.91%) working in small enterprises (1 to 49employees), 99 (36.13%) in medium enterprises(50 to 499 employees) and 104 (37.96%) inlarge enterprises (more than 500 employees).The majority of the managers stated to workin Finance (34.31%), followed by telecommuni-cations (25.91%) and the public sector (8.76%).


3.2 Variables Collected

In this section, all variables (criterion vari-ables, predictors and demographic variables)are explained that were collected for testingthe hypotheses. Because of Luxembourg’s mul-ticultural environment, where more than 170nationalities can be found (Luxembourg forFinance and Luxembourg for Business, 2015),all measuring instruments were available inGerman, English and French.

3.2.1 Rising and falling competencerequirements

The rising and falling competence requirementswere calculated for the classes of professional-methodical and social-communicative compe-tences. In a first step, the participants wereasked to answer the following open questions:what competences do you need in your po-sition today in order to meet the currentrequirements? What competences will be nec-essary in your position in the future to suc-cessfully meet the demand for adaptation inthe next 3–5 years? In addition, participantswere to weight the importance of the namedcompetences using a percentage rate so thatthe sum adds up to 100%. The participants’answers represent competence manifestations(e.g. learning Chinese), which were allocatedto competences (e.g. multilingualism) using acoding scheme (Mühlbacher, 2007), which inturn were grouped into competence classes(e.g. social-communicative). In order to ad-dress the basal leader-manager differentiation(Toor, 2011) properly, this study mainly fo-cuses on the professional-methodical and social-communicative competences.

Subsequently, the competence requirementswere determined through the difference betweencurrent and future competences. For calculatingrising demand for professional-methodical orsocial-communicative competences, exclusivelypositive values (0 to 100) were then used, whilefor calculating falling demand only negative val-ues (−100 to 0) were taken into consideration.The advantage of this open approach is thatparticipants were able to answer freely and thussheltered from potential interference throughpre-formulated answering options. Due to the

open approach, a reliability analysis by meansof Cronbach’s Alpha was not possible. Descrip-tive statistics showed the following means andstandard deviations for the criterion variables:• rising demand for professional-methodical

competences: M = 16.71; SD = 17.36;• falling demand for professional-methodical

competences: M = −21.87; SD = 20.85;• rising demand for social-communicative

competences: M = 7.15; SD = 10.52;• falling demand for social-communicative

competences: M = −10.47; SD = 12.59.

3.2.2 General self-efficacyIn order to measure general self-efficacy, a ques-tionnaire designed by Schwarzer and Jerusalem(1995) was used. This is a well-establishedmeasuring instrument with 10 items, whichhad already been tested in several countriesand cultural spheres (e.g. Scholz et al., 2002).The items include statements relating to thesuccessful accomplishment of general tasks,such as “If a problem approaches, I usually haveseveral ideas how to solve it” or “Whateverhappens, I will manage”. It is a 4-point Likertscale with a Cronbach Alpha of α = 0.85,which is satisfactory (Bortz and Döring, 2006).The participants achieved a mean of 3.36 (SD= 0.38) and the test values were in a rangefrom 2.40 to 4. The questionnaire had alreadybeen translated into German (Schwarzer andJerusalem, 1999) and French (Dumont et al.,2000).

3.2.3 Resistance to changeIn order to measure resistance to change, aquestionnaire designed by Oreg (2003) wasused. This is a well-established measuring in-strument with 17 items, which had been testedin a large-scale study in more than 19 countries(e.g., Oreg et al., 2008). The items includestatements on the perception of changes suchas “I generally think changes are negative” or“If I am informed about changes to plans, Ifeel more tension”. It is a 6-point Likert scalewith a Cronbach Alpha of α = 0.81, whichis satisfactory (Bortz and Döring, 2006). Theparticipants achieved a mean of 2.71 (SD =0.52) and the test values were in a range from1.35 to 4. The questionnaire had already been


translated into German (Oreg et al., 2008).For translation into French, an experiencedtranslator was hired.

3.2.4 Demographic variablesData on the industry (e.g. finance, publicsector) and relating to the number of employeesin the organisation were recorded. As in otherstudies (e.g. Schminke et al., 2002), the figuresgiven on the number of employees were log-transformed in order to reduce skewness. More-over, the participants’ age, sex, nationality,mother tongue, educational achievement, fieldof studies, position in the organisation andcurrent line of work were recorded.

3.3 Data Collection and Analysis

The data were collected by means of an onlinesurvey, which is a typical approach for quanti-tative research designs (Frippiat and Marquis,2010, p. 285). The survey was compiled usingLimeSurvey 1.92 (www.limesurvey.org), an

open-source survey tool, and included the twoopen questions for recording competences, thetwo standardised measuring instruments torecord general self-efficacy and resistance tochange, as well as the demographic variables.The questionnaire was offered in German, En-glish and French and it took 15–20 minutes tofill in. After completion, the data were importedinto an Excel file and analysed using IBM SPSSStatistics 20.

For testing the hypotheses, multiple re-gression models (Cohen et al., 2013) werecalculated. The influence of the demographicvariables of age, sex, educational achievementand experience as a manager was controlled.As Type I and Type II errors become moreprobable if certain requirements of regressionanalyses are violated (e.g. Williams et al., 2013),these were tested in the present study. As allrequirements were met (e.g. suitable samplesize, outliers, multicollinearity), the multipleregression models were calculated without prob-lems.

4 EMPIRICAL RESULTS

The results section consists of two parts. In afirst step, the results of the coding procedure(Mühlbacher, 2007) will be displayed in theform of a competence profile encompassingthe identified competences. Then, the resultof the multiple regression model is presented,by means of which the influence of personalitytraits on falling and rising competence require-ments was tested.

4.1 Professional-methodical andSocial-communicativeCompetences

The participants in the study were asked intwo open questions to list competences thatare on the one hand relevant for their currentjob and on the other hand will become soin the future. The participants’ answers werethen allocated to a total of 14 professional-methodical and 9 social-communicative com-petences. The class of professional-methodical

competences includes solution-oriented and job-related behaviours and abilities. In Tab. 1, themeans of all current and future professional-methodical competences are shown.

The class of social-communicative compe-tences refers to abilities that are requiredfor social interaction. In Tab. 2, the meansof all current and future social-communicativecompetences are shown.

Calculating the difference between cur-rent and future professional-methodical com-petences gives the individual demand forprofessional-methodical competences for eachparticipant. For calculating the individual ris-ing demand for professional-methodical com-petences, only positive values (0 to 65) aretaken into account. Similarly, for calculatingthe individual falling demand for professional-methodical competences, only the negativevalues (−85 to 0) are used. The averagedvalues then become the criterion variables ofthe rising demand for professional-methodical


competences (M = 16.71; SD = 17.36) andthe falling demand for professional-methodicalcompetences (M = −21.87; SD = 20.85). Forthe social-communicative competence class therising (M = 7.15; SD = 10.52) and falling (M =−10.47; SD = 12.59) demand was calculated inthe same manner.

4.2 Testing the Hypotheses

In this part of the results section, all the mainresults that are required to find an answer tothe hypotheses are listed. The correlation table(Tab. 5 in the annex) contains all variables rele-vant to the study and points out any significantconnections. A significantly negative correla-tion can be found between the rising demandfor professional-methodical competences andthe falling demand for social-communicativecompetences (r = −0.42, p < 0.01). Atthe same time, it can be seen that a risingdemand for social-communicative competencesshows a significantly negative correlation withthe falling demand for professional-methodicalcompetences (r = −0.38, p < 0.01). Bothfindings suggest that managers who reporteda high demand for change in one of thetwo competence classes also perceived a highdemand for change in the other.

It also becomes apparent that general self-efficacy positively correlates with a falling de-mand for professional-methodical competences(r = 0.16, p < 0.05). This proves a connectionbetween a personality trait and the competencerequirements. As expected, there is furthermorea negative correlation between the two person-ality traits general self-efficacy and resistance tochange (r = 0.39, p < 0.01), which has also beendetected in earlier studies (e.g. Armenakis et al.,1993). As regards the demographic variables, itcan be seen that age is negatively correlatedwith general self-efficacy (r = −0.19, p < 0.01).Thus, the younger a manager is, the higher hisdegree of general self-efficacy tends to be.

Tab. 1: Professional-methodical competences identified

Competences Time M SDAccounting / Current 5.43 11.01Financial management Future 2.93 9.04

Analytical thinking Current 3.11 8.48Future 1.82 6.72

Corporate development Current 2.86 7.34Future 2.95 8.13

Change management Current 2.23 7.13Future 4.39 12.24

Decision-making ability Current 1.80 6.40Future 1.35 5.75

Personnel management Current 1.26 5.44Future 1.13 4.82

IT knowledge Current 6.88 15.58Future 8.47 18.13

Legal competence Current 2.61 8.70Future 1.86 7.41

Marketing / Sales Current 2.95 8.01Future 2.97 9.69

Professional knowledge Current 4.08 10.84Future 2.47 10.06

Project management Current 2.17 6.29Future 1.24 5.99

Risk management Current 1.03 3.99Future 0.55 3.56

Strategic management Current 5.32 9.74Future 6.52 13.35

Technical understanding Current 3.45 9.48Future 3.03 10.79

Tab. 2: Social-communicative competences identified

Competences Time M SDCommunication Current 3.46 7.29

Future 3.13 8.15Conflict management Current 0.89 3.82

Future 0.95 4.69Customer relationship Current 1.81 6.53

management Future 1.93 7.59Active listening Current 1.05 3.98

Future 0.53 3.19Multilingualism Current 5.52 9.23

Future 2.76 6.95Negotiating skills Current 1.81 6.11

Future 1.65 6.45Network skills Current 1.73 5.99

Future 1.66 6.42Teamwork Current 1.00 4.91

Future 0.90 4.20Reporting Current 1.15 4.39

Future 0.76 4.95


As expected, the age of the managers cor-relates positively with their experience (r =0.67, p < 0.01). In addition, the number ofemployees in the organisation shows a positivecorrelation with the falling demand for social-communicative competences (r = 0.16, p <0.05) and a negative correlation with the risingdemand for social-communicative competences(r = −0.22, p < 0.01). In larger organisa-tions, therefore, social-communicative compe-tences were rated as less important. Moreover,a negative correlation between the number ofemployees and general self-efficacy (r = −0.15,p < 0.05) was detected.

Tab. 3: Multiple regression model to predict rising andfalling demand for professional-methodical competences

Rising demandfor professional-

methodicalcompetencesa

Falling demandfor professional-

methodicalcompetencesb

Predictors β R2 ∆R2 β R2 ∆R2

Step 1: 0.01 0.01 0.03 0.03Age in years −0.11 −0.16Sex −0.01 0.04Educationalachievement −0.06 −0.07

Experienceas a managerin years

0.12 −0.03

Step 2: 0.01 0.00 0.09 0.06**Age in years −0.10 −0.12Sex −0.01 0.07Educationalachievement −0.06 −0.11


0.12 −0.08

Generalself-efficacy 0.02 0.26**

Resistanceto change 0.01 0.21*

Notes: an = 150, bn = 161, *p < 0.05, **p < 0.01.

Calculating the multiple regression modelshowed that general self-efficacy (β = 0.26,p < 0.01) and resistance to change (β =0.21, p < 0.05), with an R2 of 0.09, aresignificant predictors of the falling demand forprofessional-methodical competences (Tab. 3).In contrast, it can be seen that the rising de-mand for professional-methodical competences

cannot significantly be predicted by eithergeneral self-efficacy (β = 0.02, p = 0.88) orresistance to change (β = 0.01, p = 0.90).The control variables of age, sex, educationalachievement and experience as a manager donot play any role at all.

Tab. 4: Multiple regression model to predict the rising andfalling demand for social-communicative competences

Rising demandfor social-

communicativecompetencesa

Falling demandfor social-

communicativecompetencesb

Predictors β R2 ∆R2 β R2 ∆R2

Step 1: 0.04 0.04 0.01 0.01Age in years −0.16 0.02Sex −0.09 0.05Educationalachievement −0.09 0.10


0.21 −0.03

Step 2: 0.04 0.01 0.05 0.04*Age in years −0.19 −0.03Sex −0.11 0.06Educationalachievement −0.09 0.11


0.23* −0.01

Generalself-efficacy −0.08 −0.20*

Resistanceto change −0.07 −0.19*

Notes: an = 155, bn = 200, *p < 0.05.

A similar result emerged when calculating theregression model to predict rising and fallingdemand for social-communicative competences(Tab. 4). Again, it becomes apparent thatgeneral self-efficacy (β = −0.20, p < 0.05) andresistance to change (β = −0.19, p < 0.05),with an R2 of 0.05, are significant predictorsof the falling demand for social-communicativecompetences. In contrast, it can be seen thatthe rising demand for social-communicativecompetences cannot significantly be predictedby either general self-efficacy (β = −0.08, p =0.37) or resistance to change (β = −0.07, p =0.41). Only experience as a manager predictsthe rising demand for social-communicative


competences (β = 0.23, p < 0.05). A possi-ble explanation might be that managers withincreasing work experience are more likely tobe found in top or upper management andin this position have to communicate witha larger number of stakeholders. The othercontrol variables – age, sex, and educationalachievement – remained immaterial.

It thus becomes apparent that both inthe case of professional-methodical and social-

communicative competences it is falling com-petence requirements that are predicted by thetwo personality traits. This suggests that thetwo changes here are very different, with differ-ent underlying dispositions, and the quality ofthe change therefore plays an important part.The falling demand for professional-methodicaland social-communicative competences is inaddition influenced by the exact opposite formof general self-efficacy and resistance to change.

5 DISCUSSION

It was the aim of this study to identifypredictors of rising and falling demandfor professional-methodical and social-communicative competences – especiallyagainst the background of the much-usedleader-manager differentiation. Based on theliterature, particularly the influence of twopersonality traits, general self-efficacy andresistance to change, was analysed. The resultsof the multiple regression models have shownthat the two personality traits predict thecompetence requirements, but always onlyfalling and not rising demand for professional-methodical and social-communicative com-petences. Therefore, hypotheses 1 and 2were only confirmed for falling competencerequirements. Furthermore, it was shown thatthe predictors influenced the falling demand forthe two competence classes in exactly oppositedirections. On the one hand, executives (=leaders) with a high level of general self-efficacy and resistance to change perceivea falling demand for professional-methodicalcompetences. On the other hand, executives(= managers) with a low level of general self-efficacy and resistance to change report fallingdemand for social-communicative competences.

As falling and rising competence require-ments rest on different personality traits, it canbe argued that there are two different formsor types of change connected to two differentchange personalities, leaders and managers(Yukl and Lepsinger, 2005, p. 361). Accord-ing to this, fundamental differences betweenmanagers and leaders can be found deep in

their psyche or personality (Zaleznik, 1977).This underlines the complexity of the many-faceted phenomenon of “change”, much coveredin the literature, which the people involved canperceive very differently depending on very dif-ferent characteristics. Caldwell et al. (2004), forinstance, in their study discuss the importanceof the extent of changes and whether theseare to be interpreted as useful or threatening.Compared to a change in small steps, a massivechange has a much greater potential to disturbthe sensitive balance between the requirementsand one’s own competences. The expected risks(e.g. loss of control) compared to the desiredadvantages of a change (e.g. better chances inthe labour market) thus reflect a negative anda positive focus (Oreg et al., 2011).

Rising and falling competence requirementscan also be evaluated according to differentcharacteristics. This indicates that the qualityof changes is very important and that peoplecontemplate what consequences change mighthave for them (Brockner and Wiesenfeld, 1996).Assessing changes such as the future compe-tence requirements can have both work-related(e.g. for work performance or behaviour) andpersonal consequences (e.g. for personal devel-opment or health) (an overview of potentialconsequences can be found in Oreg et al., 2011).

How changes are perceived is hence a verysubjective assessment and strongly dependson one’s own self-concept. Some authors evenargue that the self-concept is always involvedwhen people assess their own competencesor a future scenario (Crocker and Canevello,


2012). In order to be able to interpret one’sown environment better, people take recourseto their experiences and knowledge aboutthemselves, which are often formulated in atheory of the self (Oyserman et al., 2012).As the variables collected are self-appraisalsand therefore cognitive variables, the theoryof cognitive dissonance (Festinger, 1957), withits focus on cognitive aspects of the self, andparticularly the self-affirmation theory (Steele,1988) can be used for interpreting the results.

If a manager has the impression that his orher current competences strongly diverge fromthe competences required in the future, this canresult in cognitive dissonance. In this specificcase, this implies a departure from professional-methodical competences of leaders (Lunenburg,2011), who, although they are trying to breaknew ground, run the risk of getting lost inunknown territory due to a lack of pertinentknowledge. On the other hand, managers unfor-tunately often deal with crises by perceivablyreducing the social-communicative component(Daft, 2014), which results in additional uncer-tainty and disorientation of the employees. Acertain change, such as rising or falling com-petence requirements and their consequences,can so be perceived as negative, damaging orthreatening, depending on the extent of thecognitive dissonance produced. The theory ofcognitive dissonance, however, also postulatesthat people do not simply passively remain ina state of cognitive dissonance, but attempt toresolve it (Silvia and Gendolla, 2001). Managers

that assess their own competences as unsuitableto tackle future challenges are therefore eager tomaintain a positive self-image and to reduce thedissonance they feel (Nail et al., 2004).

Self-affirmation is a mechanism to reducedissonance which is intended to re-interpretchanges that otherwise are a psychologicalthreat assailing a person’s identity (Cohenand Sherman, 2014). Reporting future com-petences that do not match his or her ownwould endanger the self-image of an effectivemanager. In order to protect themselves, itis therefore conceivable that managers whoexcel in professional-methodical competencessee a falling demand for social-communicativecompetences. By focusing on one’s own existingstrengths, self-affirmation thus acts as a bufferagainst a potential threat to the self-image. Byexplicitly devaluing a certain competence class(falling competence requirements), managersare able to newly define success and orientatethis towards their own strengths. Consequently,managers who have problems in communicatingwith clients will possibly rather emphasise theirprofessional competences in order to compen-sate for this perceived weakness. This perceivedinconsistency is trivialised (Wakslak and Trope,2009) by explicitly devaluating a certain com-petence class and so separating the threat fromthe self-image. Rising and falling competencerequirements can thus be interpreted as theresult of a self-affirmation technique with theaim to reduce dissonance.

6 CONCLUSION AND OUTLOOK

This paper combines competence research withpsychological literature and adds further in-sights into future competence requirements.The insight that personality traits, which arealso reflected in the self-selected role perception,are connected with the assessment of com-petence requirements, however, also has sev-eral practical implications. First, organizationshave a strong interest in accurately identifyingcompetences that enable their executives tobe successful in the future and act in a

self-organised manner, even in unforeseeablesituations. A comprehensive competence man-agement system often serves as the “basis for ef-fective recruitment, selection, and developmentof high-performing managers and employees”(Bücker and Poutsma, 2010, p. 832). However,as the findings of this work show, factors suchas personality traits might affect the accuracyof competence assessments. Especially as thecritical incident technique, which aims to iden-tify critical situations in the past from which


competences can be inferred, is still one of themost commonly employed approaches to anal-yse competences. To create competence profilesfor core staff employees, managers, experts andproject managers (in case of a professionaland project management career path) HR orLearning and Development experts are thusoften interviewing a handful of higher rankedmanagers. However, the perception of managersregarding their competence requirements can bedistorted in the way that their level of generalself-efficacy and resistance to change result in adevaluation of either professional-methodical orsocial-communicative competences. Personalitytraits should thus be taken into account whenassessing competences by selecting a variety ofdifferent managers. As an example, to createthe competence profile of a vice president, HRshould not only conduct interviews with extro-vert, HR-friendly vice presidents but also withthe more reserved ones. In this sense, it can beargued that the inclusion of personality traitsmay increase the objectivity of competenceassessment methods.

Second, the findings underpinning themanager-leader distinction in terms of psycho-logical dispositions and preferred competenceclasses can be interesting for the design of acareer path model and appropriate trainingmeasures. As the role of a leader includeschallenging the status quo, innovating, andfocusing on people and is thus fundamentallydifferent from the role of a manager whorelies on control, creates rules, and usesformal authority (Bennis, 1989), it could beargued that HR experts should design separatecareer paths. In the career path for managers,participants receive the opportunity to furtherdevelop competences such as time management,project management, and organizational skills.Instead, the career path for leaders couldinclude topics such as strategic thinking andtransformational leadership style. As both rolesincorporate opposite responsibilities and skillsthey could act as a team with complementarycompetences.

As a third practical implication, the findingsreflect the difficulty to identify so called “changeleaders”. Some scholars argue that organiza-tions, which are planning to undergo change,

should rely on dispositional factors such asresistance to change in order to create readinessprofiles and identify change agents (Vakola,2013). However, the current study showedthat, independently of their level of resistanceto change, both – leaders and managers –perceived competence requirements to change.The quality of the perceived change (fallingdemand of social-communicative or methodical-professional competences) played an importantrole to them. On the other hand, the conclusionthat executives with a high level of resistanceto change are not perceiving any change wouldbe incorrect. Therefore, individual readinessprofiles based on dispositional traits should notbe used as a decision making tool or basis for atraining programme.

The present study has identified two predic-tors of future competence requirements and inseveral respects shows the limits of rationaldecision-making. On the one hand, it wasshown that the quality of change plays anessential part, as rising or falling competencerequirements are determined by different per-sonality traits. The subjective assessment ofrisks and advantages of changes, as well as theirexpected consequences, are taken into accountin decision-making, as is people’s own self-concept. Self-affirmation in the form of explicitdevaluation of certain competence classes istherefore used to release the tension inducedby cognitive dissonance. More importantly, thepresent study has discovered a new path forfuture research by demonstrating that the per-ception of which competences will be relevantin the future does not exist in a “void”, but ispartly based on psychological predispositions.

Future studies could test the influence of ad-ditional personality traits, such as internal locusof control (Judge et al., 1998), as predictors ofcompetence requirements. Another objective offurther research might be to identify specificpredictors of rising competence requirements.Using a qualitative research design, it could beanalysed what exactly the difference betweenthe assessment of rising and falling competencerequirements is and which main characteristics(Oreg et al., 2011) play the most importantpart.


7 REFERENCES

Amiot, C. E., Terry, D. J., Jimmieson, N. L. andCallan, V. J. 2006. A Longitudinal Investigationof Coping Processes During a Merger: Implicationsfor Job Satisfaction and OrganizationalIdentification. Journal of Management, 32 (2),552–574.

Armenakis, A. A., Harris, S. G. and Mossholder,K. W. 1993. Creating Readiness for OrganizationalChange. Human Relations, 46 (2), 681–703.

Bandura, A. 1977. Self-efficacy: Toward a UnifyingTheory of Behavioral Change. PsychologicalReview, 84 (1), 191–215.

Bennis, W. 1989. Managing the Dream: Leadershipin the 21st Century. Journal of OrganizationalChange Management, 2 (1), 6–10.

Bortz, J. and Döring, N. 2006. Forschungsmethodenund Evaluation für Human- undSozialwissenschaftler. Berlin: Springer-Verlag.

Bouckenooghe, D. 2010. Positioning ChangeRecipients’ Attitudes Toward Change in theOrganizational Change Literature. The Journal ofApplied Behavioral Science, 46 (3), 500–531.

Boyatzis, R. E. 2006. An Overview of IntentionalChange from a Complexity Perspective. Journal ofManagement Development, 25 (3), 607–623.

Boyatzis, R. E. and Saatcioglu, A. 2008. A 20-yearView of Trying to Develop Emotional, Social andCognitive Intelligence Competencies in GraduateManagement Education. Journal of ManagementDevelopment, 27 (1), 92–108.

Brockner, J. and Wiesenfeld, B. M. 1996. AnIntegrative Framework for Explaining Reactionsto Decisions: Interactive Effects of Outcomesand Procedures. Psychological Bulletin, 120 (2),189–208.

Bücker, J. and Poutsma, E. 2010. Global ManagementCompetencies: A Theoretical Foundation. Journalof Managerial Psychology, 25 (4), 829–844.

Caldwell, S. D., Herold, D. M. and Fedor,D. B. 2004. Toward an Understanding of theRelationships Among Organizational Change,Individual Differences, and Changes in Person-Environment Fit: A Cross-Level Study. Journal ofApplied Psychology, 89 (3), 868–882.

Campion, M. A., Fink, A. A., Ruggeberg, B. J.,Carr, L., Phillips, G. M. and Odman, R. B.2011. Doing Competencies Well: Best Practicesin Competency Modeling. Personnel Psychology,64 (2), 225–262.

Chen, G., Gully, S. M. and Eden, D. 2001. Validationof a New General Self-efficacy Scale. OrganizationalResearch Methods, 4 (1), 62–83.

Coch, L. and French, J. R. P. 1948. OvercomingResistance to Change. Human Relations, 1 (2),512–532.

Cohen, J., Cohen, P., West, S. G. and Aiken, L. S.2013. Applied Multiple Regression/CorrelationAnalysis for the Behavioral Sciences. New Jersey:Routledge.

Cohen, G. L. and Sherman, D. K. 2014. ThePsychology of Change: Self-affirmation and SocialPsychological Intervention. Annual Review ofPsychology, 65 (2), 333–371.

Crocker, J. and Canevello, A. 2012. Self andIdentity: Dynamics of Persons and TheirSituations. In Deaux, K. and Snyder, M. (eds.).The Oxford Handbook of Personality and SocialPsychology. New York: Oxford University Press,pp. 263–286.

Daft, R. L. 2014. The Leadership Experience.Stamford: Cengage Learning.

Dierdorff, E. C., Rubin, R. S. and Morgeson,F. P. 2009. The Milieu of Managerial Work: AnIntegrative Framework Linking Work Context toRole Requirements. Journal of Applied Psychology,94 (4), 972–988.

Dumont, M., Schwarzer, R. and Jerusalem, M.2000. French Adaptation of the General Self-Efficacy Scale: Auto-efficacité généralisée [online].Berlin: Freie Universität Berlin. Available at:http://userpage.fu-berlin.de/health/french.[Accessed 2018, October 3].

Epstein, J., Santo, R. M. and Guillemin, F.2015. A Review of Guidelines for Cross-CulturalAdaptation of Questionnaires Could Not Bring Outa Consensus. Journal of Clinical Epidemiology,68 (3), 435–441.

Erpenbeck, J. 2011. Der Königsweg zurKompetenz: Grundlagen qualitativ-quantitativerKompetenzerfassung. Münster: Waxmann Verlag.

Erpenbeck, J. and Heyse, V. 1999. DieKompetenzbiographie. Münster: WaxmannVerlag.

Erpenbeck, J. and von Rosenstiel, L.2003. Einführung. In Erpenbeck, J. andvon Rosenstiel, L. (eds.). HandbuchKompetenzmessung. Erkennen, verstehen undbewerten von Kompetenzen in der betrieblichen,pädagogischen und psychologischen Praxis.Stuttgart: Schäffer-Poeschel, IX–XL.

Festinger, L. 1957. Cognitive Dissonance Theory:Psychological Approaches. Newbury Park: SagePublications.


Field, A. 2013. Discovering Statistics Using IBMSPSS Statistics. London: Sage Publications.

Fischer, R. and Schwartz, S. 2011. WhenceDifferences in Value Priorities? Individual,Cultural, or Artifactual Sources. Journal ofCross-Cultural Psychology, 42 (7), 1127–1144.

Ford, J. and Collinson, D. 2011. In Search ofthe Perfect Manager? Work-life Balance andManagerial Work. Work, Employment and Society,25 (3), 257–273.

Frippiat, D. and Marquis, N. 2010. Web Surveys inthe Social Sciences: An Overview. Population-E,65 (3), 252–285.

Giousmpasoglou, C., Marinakou, E. and Cooper, J.2016. Chefs’ Future Competencies Needs in theUK: The Stakeholders’ Perspectives [online].Dorset: Bournemouth University. Available at:http://eprints.bournemouth.ac.uk/24935/1/abstract156.pdf. [Accessed 2018, October 3].

Herold, D. M., Fedor, D. B. and Caldwell, S. D.2007. Beyond Change Management: A MultilevelInvestigation of Contextual and Personal Influenceson Employees’ Commitment to Change. Journal ofApplied Psychology, 92 (7), 942–951.

Heyse, V. 1997. Vorbemerkung: Ziele undHauptaussagen der Studie. In Heyse, V. (ed.).Kundenbetreuung im Banken- und Finanzwesen– Praxisbeiträge zur Kompetenzentwicklung.Münster: Waxmann Verlag, pp. 1–11.

Holt, D. T., Helfrich, C. D., Hall, C. G. andWeiner, B. J. 2010. Are You Ready? How HealthProfessionals Can Comprehensively ConceptualizeReadiness for Change. Journal of General InternalMedicine, 25 (1), 50–55.

Hornung, S. and Rousseau, D. M. 2007. Active onthe Job – Proactive in Change How Autonomyat Work Contributes to Employee Support forOrganizational Change. The Journal of AppliedBehavioral Science, 43 (3), 401–426.

Jacobs, R. 1989. Getting the Measure of ManagerialCompetence. Personnel Management, 6 (1), 32–37.

Judge, T. A., Erez, A. and Bono, J. E. 1998. ThePower of Being Positive: The Relation BetweenPositive Self-concept and Job Performance. HumanPerformance, 11 (2), 167–187.

Judge, T. A., Thoresen, C. J., Pucik, V. andWelbourne, T. M. 1999. Managerial Copingwith Organizational Change: A DispositionalPerspective. Journal of Applied Psychology, 84 (1),107–122.

Lakshminarayanan, S., Pai, Y. P. and Ramaprasad,B. S. 2016. Competency Need Assessment: A GapAnalytic Approach. Industrial and CommercialTraining, 48 (4), 423–430.

Lunenburg, F. C. 2011. Leadership versusManagement: A Key Distinction – at Leastin Theory. International Journal of Management,Business, and Administration, 14 (1), 1–4.

Łuszczyńska, A., Scholz, U. and Schwarzer, R.2005. The General Self-efficacy Scale: MulticulturalValidation Studies. The Journal of Psychology,139 (4), 439–457.

Luxembourg for Finance and Luxembourg forBusiness. 2015. SurprisingLux: Look Closer forOpportunities Beyond Borders [online]. Availableat: http://www.surprisinglux.com/asset/download/LFFI_SURPRISINGLUX_ENG_WEB.pdf.[Accessed 2018, October 3].

McClelland, D. C. 1973. Testing for CompetenceRather than for “Intelligence”. AmericanPsychologist, 28 (1), 1–14.

Mühlbacher, J. M. 2007. Kompetenzmanagementals Grundlage strategischer Wettbewerbsvorteile.Wien: Linde Verlag.

Nail, P. R., Misak, J. E., Davis, R. M. 2004.Self-affirmation versus Self-consistency: AComparison of Two Competing Self-theories ofDissonance Phenomena. Personality and IndividualDifferences, 36 (10), 1893–1905.

Oreg, S. 2003. Resistance to Change: Developing anIndividual Differences Measure. Journal of AppliedPsychology, 88 (6), 680–693.

Oreg, S. 2006. Personality, Context, and Resistance toOrganizational Change. European Journal of Workand Organizational Psychology, 15 (1), 73–101.

Oreg, S., Bayazit, M., Vakola, M., Arciniega, L. M.,Armenakis, A. A., Barkauskienė, R.,Bozionelos, N., Fujimoto, Y., González, L.,Han, J., Hřebíčková, M., Jimmieson, N.,Kordačová, J., Mitsuhashi, H., Mlačić, B.,Ferić, I., Topić, M. K., Ohly, S., Saksvik, P. Ø.,Hetland, H., Saksvik, I. and van Dam, K. 2008.Dispositional Resistance to Change: MeasurementEquivalence and the Link to Personal ValuesAcross 17 Nations. Journal of Applied Psychology,93 (4), 935–944.

Oreg, S. and Sverdlik, N. 2011. Ambivalencetoward Imposed Change: The Conflict betweenDispositional Resistance to Change and theOrientation toward the Change Agent. Journal ofApplied Psychology, 96 (3), 337–349.

Oreg, S., Vakola, M. and Armenakis, A. 2011.Change Recipients’ Reactions to OrganizationalChange: A 60-year Review of Quantitative Studies.The Journal of Applied Behavioral Science, 47 (3),461–524.


Oyserman, D., Elmore, K. and Smith, G. 2012.Self, Self-concept, and Identity. In Leary, M. R.and Tangney, J. P. (eds.). Handbook of Selfand Identity. New York: The Guilford Press,pp. 69–104.

Paton, R. A. and McCalman, J. 2008. ChangeManagement: A Guide to Effective Implementation.London: Sage Publications.

Piderit, S. K. 2000. Rethinking Resistance andRecognizing Ambivalence: A MultidimensionalView of Attitudes toward an OrganizationalChange. Academy of Management Review, 25 (3),783–794.

Robinson, M. A., Sparrow, P. R., Clegg, C. andBirdi, K. 2007. Forecasting Future CompetencyRequirements: A Three-phase Methodology.Personnel Review, 36 (1), 65–90.

Schminke, M., Cropanzano, R. and Rupp, D. E. 2002.Organization Structure and Fairness Perceptions:The Moderating Effects of Organizational Level.Organizational Behavior and Human DecisionProcesses, 89 (4), 881–905.

Scholz, U., Gutiérrez-Doña, B., Sud, S. andSchwarzer, R. 2002. Is General Self-efficacy anUniversal Construct? Psychometric Findings from25 Countries. European Journal of PsychologicalAssessment, 18 (2), 242–251.

Schwarzer, R. and Jerusalem, M. 1995. GeneralizedSelf-efficacy Scale. In Weinmann, J., Wright, S.and Johnston, M. (eds.). Measures in HealthPsychology: A User’s Portfolio. Causal andControl Beliefs. Windsor: Nefer-Nelson, pp. 35–37.

Schwarzer, R. and Jerusalem, M. 1999. Skalen zurErfassung von Lehrer- und Schülermerkmalen:Dokumentation der psychometrischen Verfahrenim Rahmen der wissenschaftlichen Begleitung desModellversuchs Selbstwirksame Schulen. Berlin:Freie Universität Berlin.

Silvia, P. J. and Gendolla, G. H. 2001. OnIntrospection and Self-perception: Does SelfFocused Attention Enable Accurate Self-knowledge? Review of General Psychology, 5 (2),241–269.

Sonntag, K. and Schaper, N. 1999. Förderungberuflicher Handlungskompetenz. In Sonntag, K.(ed.). Personalentwicklung in Organisationen.Göttingen: Hogrefe, pp. 211–244.

Sparrow, P. and Boam, R. 1992. Designing andAchieving Competency: A Competency-basedApproach to Developing People and Organizations.London: McGraw-Hill.

STATEC. 2016. Luxembourg in Figures 2016 [online].Available at:http://www.luxembourg.public.lu/en/publications/c/statec-luxchiffres2016/index.html. [Accessed 2018, October 3].

Steele, C. M. 1988. The Psychology of Self-affirmation:Sustaining the Integrity of the Self. Advances inExperimental Social Psychology, 21 (3), 261–302.

Tabachnick, B. G. and Fidell, L. S. 2007. UsingMultivariate Statistics. Boston: Pearson Education.

Taylor, S. N. 2006. Why the Real Self is Fundamentalto Intentional Change. Journal of ManagementDevelopment, 25 (4), 643–656.

Thewes, G. 2008. About, History of theGrand Duchy of Luxembourg [online].Luxembourg: Information and Press Serviceof the Government. Available at: http://www.luxembourg.public.lu/en/publications/b/ap-histoire/ap-histoire-2008-EN.pdf.[Accessed 2018, October 3].

Toor, S. R. 2011. Differentiating Leadership fromManagement: An Empirical Investigationof Leaders and Managers. Leadership andManagement in Engineering, 11 (3), 310–320.

Tripathi, K. and Agrawal, M. 2014. CompetencyBased Management in Organizational Context: ALiterature Review. Global Journal of Finance andManagement, 6 (4), 349–356.

Vakola, M. 2013. Multilevel Readiness toOrganizational Change: A Conceptual Approach.Journal of Change Management, 13 (2), 96–109.

Vakola, M., Oreg, S. and Armenakis, A. 2013.Reactions to Organizational Change from anIndividual Differences Perspective: A Review ofEmpirical Research. In Oreg, S., Michel, A. andBy, R. T. (eds.). The Psychology of OrganizationalChange: Viewing Change from the Employee’sPerspective. Cambridge: Cambridge UniversityPress, pp. 95–122.

Wakslak, C. J. and Trope, Y. 2009. CognitiveConsequences of Affirming the Self: TheRelationship between Self-affirmation and ObjectConstrual. Journal of Experimental SocialPsychology, 45 (6), 927–932.

Williams, M. N., Grajales, C. A. G. andKurkiewicz, D. 2013. Assumptions of MultipleRegression: Correcting Two Misconceptions.Practical Assessment, Research and Evaluation,18 (1), 1–14.

Woodruffe, C. 1993. What is Meant by aCompetency? Leadership and OrganizationDevelopment Journal, 14 (1), 29–36.

Yukl, G. and Lepsinger, R. 2005. Why Integratingthe Leading and Managing Roles is Essentialfor Organizational Effectiveness. OrganizationalDynamics, 34 (3), 361–375.

Zaleznik, A. J. 1977. Managers and Leaders: Are TheyDifferent? Harvard Business Review, 55 (3), 1–9.


8 ANNEX

Tab. 5: Descriptive statistics and intercorrelations of study variables

Variables M SD 1. 2. 3. 4. 5. 6. 7. 8. 9.1. Fd. p-m −21.87 20.85 12. Rd. p-m 16.71 17.36 a 13. Fd. s-c −10.47 12.59 0.15 −0.42** 14. Rd. s-c 7.15 10.52 −0.38** 0.13 a 15. GS 3.36 0.38 0.16* 0.03 −0.11 0.00 16. RtC 2.71 0.52 0.09 0.00 −0.10 −0.05 −0.39** 17. Age 49.30 6.99 −0.15 −0.04 0.00 −0.04 −0.19** 0.05 18. Exp 15.36 7.87 −0.13 0.04 0.00 0.07 −0.04 −0.02 0.67** 19. Emp 5.26 2.02 0.10 −0.10 0.16* −0.22** −0.15* 0.11 −0.03 −0.12 1Notes: *p < 0.05, **p < 0.01, a = can not be computed, Fd. p-m = Falling demand for professional-methodicalcompetences, Rd. p-m = Rising demand for professional-methodical competences, Fd. s-c = Falling demand forsocial-communicative competences, Rd. s-c = Rising demand for social-communicative competences, GS = Generalself-efficacy, RtC = Resistance to change, Age = Age in years, Exp = Experience as a manager in years, Emp =Number of employees (log-transformed).

AUTHOR’S ADDRESSJürgen Mühlbacher, Vienna University of Economics and Business, Institute of ChangeManagement and Management Development, Department of Management, Vienna, Austria,e-mail: [email protected]

Tom Siebenaler, Vienna University of Economics and Business, Institute of ChangeManagement and Management Development, Department of Management, Vienna, Austria,e-mail: [email protected]


www.ejobsat.com

THE FINANCIAL ACCELERATOR IN EUROPEAFTER THE FINANCIAL CRISISKlára Baková11Mendel University in Brno, Czech Republic

BAKOVÁ, Klára. 2018. The Financial Accelerator in Europe after the Financial Crisis. European Journal ofBusiness Science and Technology, 4 (2): 143–155. ISSN 2336-6494,DOI http://dx.doi.org/10.11118/ejobsat.v4i2.136.

ABSTRACT

This paper investigates the mechanism of a financial accelerator. In particular, it examines theprocyclicality of credit margins in Europe after the financial crisis, with an additional split intosmall, medium and large-sized banks. The empirical analysis is in contrast with contemporaryauthors because it approves that the financial accelerator is not present on the European marketafter the financial crisis. It could be caused by multiple factors, for example structural changesduring the financial crisis, a change in the behaviour of commercial banks or extremely low interestrates. We tested our hypothesis on a dataset that consists of a data panel with annual data forthe period 1998–2015 and includes 2,489 banks from 36 European countries from the Bankscopedatabase. We also provide robust empirical proof that such behaviour was not occurring duringthe financial crisis or after the financial crisis in the European banking system.

KEY WORDS

credit cycle, financial accelerator, interest margin

JEL CODES

C23, E51, G21

1 INTRODUCTION

The financial accelerator theory, which origi-nated in the 1990s, was described in the studiesof Bernanke and Gertler (1989) and Bernankeet al. (1996). Kiyotaki and Moore (1997) alsocontributed to the financial accelerator theoryand procyclical change in the value of collateralassets. The financial accelerator was empirically

tested before the financial crisis and aftera financial crisis and confirmed in the USA(Aliaga-Díaz and Olivero, 2010), in Turkey(Turgutlu, 2010) and in Europe (Altunbaş etal., 2016). There is general agreement thatthe financial accelerator does not exist after afinancial crisis. Our paper follows these studies

144 Klára Baková

and contributes to the current theory of thefinancial accelerator, which helps to explain thescale and persistence of the business cycle.

The methodology was based on the studyof the behaviour of banks’ price-cost marginsas a proxy for the external finance premiumthat banks charge to firms. They identified theprocyclical impact of credit margins in theirresults. Procyclical margins make bank loansmore expensive during economic downturns andcan cause the deepening of the business cycle.

The contribution of this paper is to identifythe varied functioning of the financial accelera-tor after the financial crisis, with an additionalsplit into small, large and medium-sized banks.The research is focused on the procyclical

behaviour of interest margins on the Europeanmarket. It influences the ability of borrowersto obtain loans from external sources. Thispaper provides robust empirical proof that suchbehaviour was not occurring in the Europeanbanking market during the financial crisis orafter the financial crisis. In particular, it ex-amines the relationship between credit margins,the economic cycle and other determinants.

The paper is organised as follows. Section2 contains the literature review. A detailedoverview of methods and data is provided inSections 3. Section 4 presents the results of theeconometric models and Section 5 presents arobustness analysis. Section 6 offers concludingremarks.

2 LITERATURE REVIEW

There is an extensive review of literature onthe FA, especially during the 1990s. A financialaccelerator can be described as a mechanismeffect when the effect of relatively small im-pulses could lead to a persistent fluctuation inthe economy due to the role of an endogenouslyprocyclical credit margin in financial markets(Bernanke et al., 1996 and 1998). Due toimperfections in the credit market, the ability ofborrowers to obtain credit from external sourcesis procyclically affected if the economy is hit bya shock that affects the net worth of borrowers(Bernanke and Gertler, 1989; Bernanke et al.,1996 and 1998). The effect may also haveprocyclical interaction between credit limitsand asset prices. Durable assets are presentedas factors of production, but also as collateralfor loans (Kiyotaki and Moore, 1997).

We follow studies of the financial acceleratorin the USA (Aliaga-Díaz and Olivero, 2010),in Turkey (Turgutlu, 2010) and in Europe(Altunbaş et al., 2016). These studies testedthe existence of the financial accelerator on thecase of cyclical banks’ price-cost margins asthe dependent variable. Therefore, we provide abrief overview about the history of the financialaccelerator as well as the determinants of bankmargins.

2.1 History of the FinancialAccelerator

The financial accelerator theory is part ofthe theoretical and empirical literature aboutcredit-market imperfections. The origin of thetheory was in 1989 when Bernanke and Gertler(1989) and then Bernanke et al. (1996) studiedhow shocks may be amplified by endogenous de-velopments in the financial markets. Bernankeand Gertler (1989) identified a condition ofthe borrower’s balance sheet as a source ofoutput dynamics. Their concept analyses themechanism of net worth, which has an impacton agency costs. In short, when, for example, apositive shock occurs, the higher borrower networth reduces the agency costs, so he can pay alower premium on external finance because therisk of bankruptcy is lower. It causes an increasein investment. This mechanism amplifies theupturn and a relatively small shock could leadto a persistent shock in the economy.

The question of how credit constraints in-teract with aggregate economic activity overthe business cycle was also studied by Kiyotakiand Moore (1997). They focused on amplifyingshocks, the transfer through other sectors andtheir persistence. As an amplifier of businessfluctuations, they identified the prices of the

The Financial Accelerator in Europe after the Financial Crisis 145

assets used as collateral. It interacts with anendogenously defined credit limit and can leadto a large and persistent shock. The theoryis basically similar to that of Bernanke andGertler (1989), but in this case, the change innet worth is due to the availability of credit, notthe cost of credit.

In the paper “flight to quality”, Bernanke etal. (1996), focused on the beginning positionof borrowers. They suggest that borrowersfacing relatively high agency costs in creditmarkets will bear the brunt of an economicdownturn. When a shock occurs, they reducespending, production, and investment and itworsens the effects of recessionary shocks. Forhigh-agency-cost borrowers, small and medium-sized firms with a worse balance sheet aremainly considered. Their procyclical variabilityis higher and they should react earlier.

The financial accelerator has been studiedin recent empirical works. Some of them werefocused on the development of the bank inter-est margin. They assumed the Bernanke andGertler hypothesis (1989), that the bank creditmargin is a proxy for premium external funds, akey element of the model. This margin behavesprocyclically and makes bank loans more ex-pensive during economic downturns comparedto an economy with constant margins.

The financial accelerator hypothesis was con-firmed by Aliaga-Díaz and Olivero (2010) forUS banks in the period 1984–2005. Turgutlu(2010) tested the theory in Turkey in theperiod 2001–2008. The impact of the financialaccelerator has also been confirmed. Altunbaşet al. (2016) then studied the European bankingsystem in the period 1989–2012. They foundthat margins in the European banking systemare cyclical with respect to the output gap andtotal bank loans. Pancrazi et al. (2016) con-firmed the existence of the financial acceleratormechanism, but with the addition that it isstronger than originally assessed.

The financial accelerator could be changedafter the financial crisis. The impact of a lackof liquidity and a change in asset quality wasdifferent because of the heterogeneity in Europe(Fratzscher, 2012). The impact of the bankingmarket structure was also explored by Brissimis

and Delis (2010), who provided evidence thatheterogeneity observed on the bank level canaffect the response to changes in monetarypolicy. The heterogeneity can be observedthrough the banking channel before a financialcrisis and after a financial crisis (Heryán andTzeremes, 2017). The changing conditions inthe economy also brought changes in monetarypolicy. The ECB decreased interest rates toa historical minimum. They also respondedby increasing credit support and quantitativeeasing (ECB, 2010).

2.2 Determinants ofInterest Margins

There are many studies focused on interestmargins and their determinants. For example,Kapounek et al. (2017) present the develop-ment of interest margins spread as the mostimportant indicator of credit growth. Higherinterest rates are therefore associated with alower supply of loans. Models for the interestmargin spread are based on a model proposedby Ho and Saunders (1981). The model assumesbanks to be risk averse and that their maincontribution is to collect deposits and provideloans. The bank margin is influenced by theuncertainty of the transaction, the structure ofthe banking market, the degree of banking cap-italization and the volatility of interest rates.The model was subsequently modified andsupplemented, for example, by the possibilityof portfolio diversification on the performanceof the banking market (McShane and Sharpe,1985) or the role of operating costs (Maudosand de Guevara, 2004).

Differences in interest margins and bank prof-itability are reflected in varying determinants,such as bank characteristics, macroeconomicconditions, regulation, and several legal andinstitutional indicators, as shown by Demirgüç-Kunt and Huizinga (1999) in their study.

The evolution of interest margins is dividedaccording to the influence of monetary policyand banking regulation, the risks of firms thatact as current or potential borrowers and thecharacteristics of the bank.

146 Klára Baková

The influence of monetary policy and bankingregulation is important to mention because thefinancial crisis and its consequences have ledto changes in regulatory policy because theregulatory framework then proved to be inad-equate for achieving financial stability. It wasnecessary to include unrecovered dimensionslike liquidity and the risk of the transmission ofshock resulting from various sources (Bank ofEngland, 2011). The existing regulatory frame-work was also inadequate because it failed toprevent banks from over-risking (Dewatripontet al., 2010). Many central banks have notpreviously embedded the banking system intotheir models. They have not seen it as apotential source of friction in the transmissionmechanism of monetary policy (Gambacortaand Marques-Ibanez, 2011). A new regulatoryframework has been introduced, which is aset of macroprudential regulations to reducesystemic risks. A key element is the creation of areserve for the accumulation of capital at a timewhen banks are doing well and the economy isgrowing and vice versa (Cincotti et al., 2012).

In case of a tightening of monetary policy,banks should respond by reducing the volumeof credit, which also affects the amount ofthe credit margin. This mechanism and itsfunctioning are influenced by the central bank’stransmission mechanisms, which can operatein different ways. The change in the marketinterest rate due to the change in official in-terest rates is influenced by the confidence andexpectations of future developments (Bank ofEngland, 1999), the transparency of the centralbank’s monetary policy (Papadamou et al.,2015), credibility which increases the efficiencyof the transmission mechanism (Levieuge etal., 2018), and the bank’s access to alternativefinancing (Fungáčová et al., 2014). Access toalternative sources is determined by the char-acteristics of banks such as capital, capitaliza-tion and liquidity, but also the structure ofthe banking sector and the market power ofindividual financial institutions (Gambacorta,2005; Matousek and Sarantis, 2009). Sanfilippo-Azofra et al. (2018) show that banks do notrespond to monetary policy in countries witha less developed financial system. In countries

with developed financial systems, the efficiencyof the banking channel is proven after thefinancial crisis.

During the financial crisis, interest rates werealmost zero and it caused the low efficiencyof the banking channel in the transmissionof monetary policy. The ability of monetarypolicy to affect banks’ lending activity becamevery ineffective. At low-interest rates, a bank’sexpectations about future interest rates arechanging significantly (Swanson and Williams,2014; Apergis and Christou, 2015). Other stud-ies suggest that the banking channel is lessefficient in banking systems with large, moreliquid and more profitable banks (Matousekand Sarantis, 2009; Gunji and Yuan, 2010; Houand Wang, 2013). The negative impact of verylow-interest rates on the profitability of banks’credit assets by reducing interest rate marginswas also confirmed by Borio and Gambacorta(2017). Then Dell’Ariccia and Marquez (2013)also warn that it may have a negative impacton the bank’s risk.

The literature bears witness to many papersdefining factors which could influence a bank’sactivities and therefore bank loans. Kučerováand Kapounek (2015) identified the main de-terminants of bank lending activities in thesample of EU countries. They confirmed thesignificant impact of macroeconomic shocks,banking controls and institutional variables onEuropean lending activities. Chakraborty andRay (2006) also show similar results – the levelof per capita GDP and investments is higherunder the bank-based system compared to themarket-based system.

Interest rate margins are also affected by thecredit cycle. The lower willingness of banks toborrow during a crisis is caused by higher eco-nomic uncertainty, lower liquidity availabilityon interbank markets, and lower solvency dueto weaker balances (Adams-Kane et al., 2015).Changes in credit capacity affect the activityof firms dependent on external financing. Asmentioned above, banks also respond to thetightening of monetary policy (Kashyap andStein (1995). Especially small and less liquidbanks with low securities are more responsiveto monetary policy shocks (Kashyap and Stein,


2000). This effect is amplified by endogenouschanges in optimism and pessimism (animalspirits; see De Grauwe and Macchiarelli, 2015).Based on these changes, it is possible to ob-serve the paradox of financial instability whichwas first presented by Borio and Drehmann(2009) and Borio (2011). The instability ofthe economy is paradoxically growing the mostwhen an economy is at its peak. It’s causedby the procyclicality of bank lending and firms’access to funds. Banks reduce credit standardsin times of economic growth (Jiménez andSaurina, 2006).

Banks can also be influenced by asset pricedevelopments, which are used as collateral, andtheir reduction is accompanied by a reductionin the availability of credit to those usingassets in this way (Jiménez and Saurina, 2006).Carvalho et al. (2015) identified bank distressin connection with a fall in share valuation andsubsequent losses. These lead to a reduction inthe investments of borrowers with the strongestcredit relations with banks.

When examining the determinants of interestmargins, the impact of the risk channel and theriskiness of the companies cannot be omitted.There were also changes in this sector afterthe financial crisis. A new risk channel hasbeen defined which suggests that monetarypolicy can determine the level of risk in theeconomy. Too low-interest rates for a longtime can cause systemic risk accumulation inthe financial sector. This results in financialimbalances caused by reduced aversion to riskfrom banks and other investors (Borio and Zhu,2012). Knowledge about the risk channel isstill limited, but evidence of the risk channelhas been proven in the Eurozone (Maddaloniand Peydró, 2011; Cappiello et al., 2010) orin the US investment-banking sector (Adrianand Shin, 2010). Altunbaş et al. (2010) alsoconsider bank risk with the classic indicators(size, liquidity and capitalization) used to assessthe ability and willingness of the bank toprovide loans. In particular, it found that bankscharacterized by lower expected default ratesare able to offer a larger amount of credit and tobetter isolate the supply of loans from monetarypolicy changes. Banks that include corporate

risk are also affected by information asymme-tries (Duran and Lozano-Vivas, 2015) followedby moral hazard (Antzoulatos and Tsoumas,2014). Cincotti et al. (2012) confirmed that thestate of affairs also affected the level of interestrates.

The last part of credit margins determinantsincludes bank characteristics. Gambacorta andMarques-Ibanez (2011) identified the character-istics of banks that have a significant impacton banks’ credit activity. According to theirresults, the decline in credit activity duringthe crisis was strongest in banks with lowercore capital, increased dependence on mar-ket liquidity and non-interest income sources.Markovic (2006) includes bank capital becausemore capitalized banks are more isolated fromchanges in monetary policy or other shocks,without changing credit activity. Similar resultswere shown by Borio and Gambacorta (2017).

Important determinants of interest rates andthe ability to provide loans also include size,capitalization, efficiency and the liquidity ofthe bank (Guiso et al., 2002). Altunbaş et al.(2009) and Apergis and Christou (2015) placeemphasis on characteristics such as liquidityand capitalization. The assumption that large,liquid and well-capitalized banks have moreopportunities to expand their loan portfolio andare less sensitive to monetary policy shocks andpolicy changes to the interest rate has been con-firmed by several other authors (Gambacortaand Mistrulli, 2004; Gambacorta, 2005; Jorge,2009). We can also mention determinants likemanagement efficiency, which can reduce costs,followed by interest margins (Angbazo, 1997;Hawtrey and Liang, 2008).

We include bank liquidity in our modelbecause holding more liquid assets increases ad-ditional costs (Ho and Saunders, 1981). We alsoinclude bank specialization because we assumethat banks more specialized in deposit react in arelatively less elastic manner and banks are ableto separate money from exogenous economicshocks (Berlin and Mester, 1999). As anotherdeterminant, we include credit quality. If thereis a higher credit default, banks need to increasetheir credit margins to compensate for theloss (Maudos and de Guevara, 2004). The last

148 Klára Baková

banking characteristic is capital because morecapitalized banks can charge a higher margin,if we assume that liabilities are cheaper than

equity. It can be caused due to tax optimization(Lown and Peristiani, 1996; Jorge, 2009; Adrianand Shin, 2010).

3 DATA AND METHODS

We use annual data from Bureau van Dijk– Bankscope for 2,489 banks across 36 Euro-pean countries in the period 1998–2015. TheBankscope database provides detailed data in-cluding balance sheets and financial indicatorsof the banks. We mostly focus on bank marginand bank characteristics. We obtained data onmacroeconomic fundamentals from the publiclyavailable Eurostat database (Eurostat, 2017).The macroeconomics and institutional data setis merged with individual bank data.

Data are transformed using a chain indexwith a base period in 2007. The data arefurther adjusted for outliers in the 1% and99% percentile. To eliminate the obliquity andaccuracy of data, all data are transformedusing logs. Descriptive statistics and a cross-correlation matrix are in Annex.

The financial accelerator was tested beforethe financial crisis and after the financial crisis,

especially using interest margins. Changes inthe financial market during the period 1998–2015 can have an impact on the financialaccelerator, so we divide the period and thenwe will analyse the financial accelerator beforethe financial crisis and after the financial crisis.Specifically, this paper examines the relation-ship between interest margins, the economiccycle and other determinants. We focus on theEuropean banking sector. Therefore, we dealwith the determinants of interest margins in theeconomy dependent on the banking sector.

In the analysis, the panel regression modelis used. Because of the specific conditionsof a particular bank, a fixed-effects model isused. These specifics are not captured in themodel and cannot be considered as random.Parameter estimates are calculated using theOLS method.

We assume the following regression:

IRmarginsi,t = c+

M∑m=1

β1 mshocksc,t +B∑

n=1

β2 bcontrolsi,t +S∑

s=1

β3 insti + θt + µi + εi,t (1)

In the equation (1), i and t are banks andtime, IRmarginsi,t is the bank’s net interestmargin, mshocksc,t are macroeconomics shocksin the country c and time t. It measuresthe business cycle through the development ofGDP. GDP is the main explanatory variable, sowe include it in the main model and in everysub-model. The set of variables bcontrolsi,trepresents selected banking characteristics, in-cluding bank liquidity measured as a ratio ofliquidity assets to total bank assets and bankspecialization measured as the ratio of bankdeposits to total bank assets. An additionalbanking characteristic is credit quality mea-sured as a ratio of loan loss provisions to totalloans. The last one is capital measured as theratio of capital to total bank assets. The last set

of variables, insti, includes determinants of theinstitutional environment. Finally, we includethe time dummy variable, θt, bank fixed effects,µi (special characteristics with different impactfor each bank), and a residual, εi,t.

The mechanism of the financial acceleratorstarts with a relatively small shock that causesa change in economic activity. Changes ineconomic activity are included in the modelby GDP. When an adverse shock occurs, GDPdecreases, it causes a slowdown in sales, adecline in cash flows and internal funds, increas-ing the amount that a firm must obtain fromexternal financial resources to finance invest-ment projects. Changes that have caused thedecline in the net worth of the borrower furtherexert an external financial premium due to the


asymmetry of information. An increase in theexternal financial premium due to the deteriora-tion of the borrower’s financial situation and theincrease in its risk disrupts the access of busi-nesses and households to credit. In addition,there is a reduction in the value of guarantees.It further reduces debtors’ balance sheets, in-creases their risk, and thus reduces their abilityto obtain credit. Firms are forced to reduce theirinvestment, resulting in a negative impact onperformance. The changes will also cause fluc-tuations in banks’ credit activity, which againaffects investment, expenditure and production,which in turn affects GDP. The result is anincrease in the persistence of the original shockand the further deepening of the business cycle.

In the robustness analysis, we check thesensitivity of our analysis in two ways. Firstly,we included bank size criteria. Bank size, liq-uidity, and capitalization are the main criteria,which determine the interest margin (Guiso etal., 2002). Kapounek et al. (2017) show thatthe loans of large banks also depend stronglyon demand factors like GDP, consumption orunemployment.

We analyse small, large and medium-sizedbanks (see Tab. 3) separately. We divided themodel into these groups according to the per-centile. The distinguishing criterion used is theindicator of the total assets of banks modifiedwith respect to GDP to eliminate the impact ofthe size of the economy.

4 RESULTS

Tab. 1 presents OLS results for the bank in-terest margin. Our main model focuses on theinterest margin, which is determined by theeconomic cycle, bank liquidity, specialization,bank equity and credit quality.

The results present the significant and nega-tive effect of GDP on the interest margin. Thus,higher GDP is associated with a lower interestrate. In other words, the interest margins arehigher during an economic downturn. This hasa negative impact on firms, because it reducestheir ability to obtain loans. It further deepenthe economic downturn. We can conclude thatinterest margins are procyclical, so we can con-firm the financial accelerator in the Europeanbanking system. Tab. 1 also presents the signif-icant and negative effect of bank liquidity. Thisconfirms our hypothesis of declining interestmargins in liquidity growth due to the increasein the cost of holding liquid portfolios. Thepositive impact of capital (equity to assets)confirms the hypothesis that more capitalizedbanks can set higher interest margins.

On the contrary, an insignificant variable isthe credit quality (loans loss reserve to grossloans), so we do not include it in further models.

In the second step, we divided the model bythe period before the financial crisis (column2), during the financial crisis (column 3) and

after the financial crisis (column 4). Column1 presents the undivided model, similarly toTab. 1. As we mentioned, credit quality isomitted because it is not significant in the firstmodel.

Our results show the financial acceleratoris in the European banking system only untilthe financial crisis. Column (3) and (4) inTab. 2 shows interest margins are determinedby the business cycle, but the financial crisischanged their direction. After the financialcrisis, the business cycle had a positive impacton bank interest margins. The business cycleis represented by GDP. Thus, the positiveimpact on bank interest margins means thatwhen GDP grows, interest margins also increaseand loans become more expensive for firms.It could reduce the growth of GDP. This isthe main different between Tab. 1, where thebusiness cycle is deepened by the negativeimpact of the business cycle, known as thefinancial accelerator.

When we compare the results of the modelfocusing on the period of the financial crisis(column 3) to the model after the financial crisis(column 4), we can see that the impact of GDPis higher during the financial crisis.

When we compare the results of the undi-vided model (column 1) to the divided model

150 Klára Baková

Tab. 1: Analysis of interest margin determinants

1 2 3 4 5 6GDP −0.183*** −0.225*** −0.195*** −0.106 −0.118 −0.131*

(0.068) (0.072) (0.070) (0.065) (0.081) (0.078)Liquid assets −0.030*** −0.033***to total assets (0.009) (0.008)Deposits to assets 0.220*** 0.045*

(0.032) (0.024)Equity to assets 0.272*** 0.228***

(0.025) (0.027)Loans loss reserve 0.003 0.006to gross loans (0.008) (0.008)Constant 0.849*** 0.785*** 0.643*** 1.649*** 1.021*** 1.527***

(0.026) (0.033) (0.021) (0.078) (0.051) (0.087)Observations 26,654 24,098 23,856 24,105 12,240 10,635R2 0.065 0.068 0.071 0.122 0.102 0.160Number of banks 2,453 2,250 2,230 2,245 1,805 1,663ll −10,345 −7,975 −6,766 −7,615 −1,720 −741.9

Tab. 2: Financial accelerator analysed based on the period

1998–2015 1998–2007 2007–2010 2008–2015GDP −0.120* −0.240*** 1.302*** 0.476***

(0.062) (0.079) (0.253) (0.130)Liquid assets to total assets −0.029*** −0.011 −0.030 −0.022*

(0.008) (0.014) (0.020) (0.012)Deposits to assets 0.070** 0.014 −0.120* 0.087

(0.033) (0.049) (0.063) (0.069)Equity to assets 0.310*** 0.342*** 0.012 0.189***

(0.023) (0.036) (0.049) (0.032)Constant 1.728*** 1.792*** 0.657*** 0.974***

(0.075) (0.126) (0.135) (0.087)Observations 23,748 9,597 3,044 11,217R2 0.148 0.148 0.058 0.034Number of banks 2,219 1,560 1,612 2,061ll −5,488 655.3 930.6 −1,334

(columns 2–4 according to period), we cansee that the impact of liquid assets and spe-cialization is not significant throughout the

period. However, the impact of bank liquidityis approximately similar to that of the originalmodel.

5 ROBUSTNESS ANALYSIS

The results of the robustness analysis by thesize of the banks shows that interest marginsare procyclical only in the case of a large bank.The results are in line with the literature – largebanks can better diversify, it leads to lowercredit default and then lower credit costs and

margins. Our robustness analysis results alsoconfirm our previous results about liquid assetsand capital, especially in the case of large banks.

Moreover, the impact of capital (equity toassets) is significant before the financial crisisand after the financial crisis and for all bank


Tab. 3: Results of robustness analysis by the size of the banks

All banks Small banks Medium banks Large banksGDP −0.120* −0.275 −0.082 −0.187**

(0.062) (0.169) (0.106) (0.089)Liquid assets to total assets −0.029*** −0.009 −0.027** −0.048***

(0.008) (0.014) (0.012) (0.014)Deposits to assets 0.070** 0.015 0.045 0.034

(0.033) (0.043) (0.043) (0.022)Equity to assets 0.310*** 0.267*** 0.352*** 0.293***

(0.023) (0.045) (0.037) (0.037)Constant 1.728*** 1.295*** 1.489*** 1.232***

(0.075) (0.121) (0.094) (0.100)Observations 23,748 5,860 8,818 7,438R2 0.148 0.161 0.157 0.175Number of banks 2,219 632 695 595ll −5,488 −1,332 −2,085 −511.9

Tab. 4: Robustness analysis by country

EU 36 CEES Eurozone EU 5GDP −0.120* −0.058 0.467*** 0.327**

(0.062) (0.160) (0.063) (0.157)Liquid assets to total assets −0.029*** −0.009 −0.044*** −0.046***

(0.008) (0.017) (0.013) (0.011)Deposits to assets 0.070** −0.073** 0.168** 0.130**

(0.033) (0.035) (0.065) (0.053)Equity to assets 0.310*** 0.259*** 0.288*** 0.279***

(0.023) (0.051) (0.055) (0.031)Constant 1.728*** 2.297*** 1.294*** 1.734***

(0.075) (0.194) (0.152) (0.101)Observations 23,748 2,194 9,585 14,911R2 0.148 0.302 0.143 0.112Number of banks 2,219 223 684 1,266ll −5,488 −456.8 374.1 −3,674

sizes. Thus, we can confirm the hypothesisthat banks which are more capitalized can sethigher interest margins for all banks almostindependently of the size. The positive impactof bank capital is unchanged throughout.

Secondly, we check the sensitivity of ouranalysis according to the different groups ofEuropean countries – Central and EasternEuropean countries (CEES), the euro area and

the 5 biggest countries (EU 5) in Europeaccording to GDP. Column 1 presents the un-divided model, similarly to Tab. 1. The resultsof the robustness analysis by country confirmour previous results of the divided model. Inthe euro area and the 5 biggest countries,the economic cycle has a positive impact oninterest margins. Therefore, we cannot provethe effectiveness of the financial accelerator.

152 Klára Baková

6 DISCUSSION AND CONCLUSIONS

The contribution of this paper is to identify thevaried functioning of the financial acceleratorbefore the financial crisis and after the financialcrisis and subsequently for the different sizesof banks. The paper is mainly focused onthe relationship between interest margins, theeconomic cycle and other determinants such asbank liquidity or bank capital.

We show that our results of the first undi-vided model are in line with the current litera-ture and confirm the presence of the financialaccelerator in the European banking system.This means procyclical interest margins, whichdeepen the economic cycle. We also dividedour model into 3 periods and according tothis model, the financial accelerator is presentin the European banking system only untilthe year 2007, when the financial crisis began.Consequently, economic activity has no pro-cyclical impact on the interest margins after thefinancial crisis.

There are several reasons why the financialaccelerator has not been proven in the Euro-pean market since the financial crisis. Duringthe crisis, there were many structural changesthat led to changes in the instruments used bycentral banks, but also changes in the behaviourof commercial banks due to increased risk.Extremely low interest rates could have hadan important impact. Banks and businesses

could have played their role during the crisis.Besides the financial crisis, the banking systemalso weakened the transmission mechanism,due to deregulation, financial innovations andchanges in bank business models. The effectson the financial accelerator may also havechanges in the focus on macro-prudential policyor greater emphasis on risk measurement andunderstanding in the financial sector. In thecontext of risk control, several new institutionsare also involved in monitoring systemic riskand issuing recommendations.

Finally, we presented a robustness analysisto identify the significant impact of the banksize on the financial accelerator in the Europeanmarket. Our results show the presence of thefinancial accelerator in the European bankingsystem only in the case of large banks. Wealso examined other characteristics and, forexample, we can confirm the hypothesis thatmore capitalized banks can set higher interestmargins for all banks almost independently ofthe size.

Then we examined the presence of the finan-cial accelerator in different groups of countries –CEES, the euro area and the 5 biggest countriesin Europe. We found a significant result in thecase of the euro area and the 5 biggest countriesin Europe and we did not find a procyclicalimpact of interest margins.

7 REFERENCES

Adams-Kane, J., Jia, Y. and Lim, J. J. 2015. GlobalTransmission Channels for International BankLending in the 2007–09 Financial Crisis. Journalof International Money and Finance, 56, 97–113.

Adrian, T. and Shin, H. S. 2010. Liquidity andLeverage. Journal of Financial Intermediation,19 (3), 418–437.

Aliaga-Díaz, R. and Olivero, M. P. 2010. Is Therea Financial Accelerator in US Banking? Evidencefrom the Cyclicality of Banks’ Price–cost Margins.Economics Letters, 108 (2), 167–171.

Altunbaş, Y., di Tommaso, C. and Thornton, J.2016. Is There a Financial Accelerator in EuropeanBanking? Finance Research Letters, 17, 218–221.

Altunbaş, Y., Gambacorta, L. and Marques-Ibanez, D. 2009. Securitisation and the BankLending Channel. European Economic Review,53 (8), 996–1009.

Altunbaş, Y., Gambacorta, L. and Marques-Ibanez, D. 2010. Bank Risk and Monetary Policy.Journal of Financial Stability, 6 (3), 121–129.

Angbazo, L. 1997. Commercial Bank Net InterestMargins, Default Risk, Interest Rate Risk andOff-balance Sheet Banking. Journal of Banking &Finance, 21 (1), 55–87.


Antzoulatos, A. A. and Tsoumas, C. 2014.Institutions, Moral Hazard and ExpectedGovernment Support of Banks. Journal ofFinancial Stability, 15, 161–171.

Apergis, N., Christou, C. 2015. The Behaviour ofthe Bank Lending Channel when Interest RatesApproach the Zero Lower Bound: Evidence fromQuantile Regressions. Economic Modelling, 49,296–307.

Bank of England. 1999. The TransmissionMechanism of Monetary Policy. Bank ofEngland Quarterly Bulletin [online]. Availableat: https://www.bankofengland.co.uk/-/media/boe/files/quarterly-bulletin/1999/the-transmission-mechanism-of-monetary-policy.

Bank of England. 2011. Instruments of MacroprudentialPolicy. Bank of England Discussion Paper.

Berlin, M. and Mester, L. J. 1999. Deposits andRelationship Lending. Review of Financial Studies,12 (3), 579–607.

Bernanke, B. and Gertler, M. 1989. Agency Costs,Net Worth and Business Fluctuations. AmericanEconomic Review, 79 (1), 14–31.

Bernanke, B., Gertler, M. and Gilchrist, S.1996. The Financial Accelerator and the Flight toQuality. The Review of Economics and Statistics,78 (1), 1–15.

Bernanke, B., Gertler, M. and Gilchrist, S. 1998.The Financial Accelerator in a QuantitativeBusiness Cycle Framework. NBER Working PaperNo. 6455.

Borio, C. 2011. Rediscovering the MacroeconomicRoots of Financial Stability Policy: Journey,Challenges and a Way Forward. BIS WorkingPaper No. 354.

Borio, C. and Drehmann, M. 2009. Towards anOperational Framework for Financial Stability:‘Fuzzy’ Measurement and Its Consequences. BISWorking Papers No. 284.

Borio, C. and Gambacorta, L. 2017. MonetaryPolicy and Bank Lending in a Low Interest RateEnvironment: Diminishing Effectiveness? Journalof Macroeconomics, 54 (B), 217–231.

Borio, C. and Zhu, H. 2012. Capital Regulation,Risk-taking and Monetary Policy: A MissingLink in the Transmission Mechanism? Journal ofFinancial Stability, 8 (4), 236–251.

Brissimis, S. N. and Delis, M. D. 2010. BankHeterogeneity and Monetary Policy Transmission.ECB Working Paper No. 1233.

Cappielo, L., Kadareja, A., Sørensen, C. K. andProtopapa, M. 2010. Do Bank Loans and CreditStandards Have an Effect on Output? A PanelApproach for the Euro Area. ECB Working PaperNo. 1150.

Carvalho, M., Ferreira, M. A. and Matos, P. 2015.Lending Relationships and the Effect of BankDistress: Evidence from the 2007–2009 FinancialCrisis. Journal of Financial and QuantitativeAnalysis, 50 (6), 1165–1197.

Chakraborty, S. and Ray, T. 2006. Bank-Basedversus Market-Based Financial Systems: AGrowth-Theoretic Analysis. Journal of MonetaryEconomics, 53 (2), 329–350.

Cincotti, S., Raberto, M. and Teglio, A. 2012.Macroprudential Policies in an Agent-BasedArtificial Economy. Revue de l’OFCE, 124 (5),205–234.

De Grauwe, P. and Macchiarelli, C. 2015. AnimalSpirits and Credit Cycles. Journal of EconomicDynamics and Control, 59, 95–117.

Dell’Ariccia, G. and Marquez, R. 2013. InterestRates and the Bank Risk Taking Channel. AnnualReview of Financial Economics, 5 (1), 123–141.

Demirgüç-Kunt, A. and Huizinga, H. 1999.Determinants of Commercial Interest Margins andProfitability: Some International Evidence. WorldBank Economic Review, 13 (2), 379–408.

Dewatripont, M., Rochet, J.-C. and Tirole, J.2010. Balancing the Banks: Global Lessons fromthe Financial Crisis. Princeton University Press,Princeton, Oxford. ISBN 978-0-691-14523-5.

Duran, M. A. and Lozano-Vivas, A. 2015. MoralHazard and the Financial Structure of Banks.Journal of International Financial Markets,Institutions and Money, 34, 28–40.

ECB. 2010. The ECB’s Response to the FinancialCrisis. ECB Monthly Bulletin, 10, 59–74 [online].Available at: https://www.ecb.europa.eu/pub/pdf/other/art1_mb201010en_pp59-74en.pdf.

Eurostat. 2017. Data [online]. Available at:http://ec.europa.eu/eurostat/data/database.[Accessed 2017, November 9].

Fratzscher, M. 2012. Capital Flows, Push versus PullFactors and the Global Financial Crisis. Journal ofInternational Economics, 88 (2), 341–356.

Fungáčová, Z., Solanko, L. and Weill, L. 2014.Does Competition Influence the Bank LendingChannel in the Euro Area? Journal of Banking &Finance, 49, 356–366.

Gambacorta, L. and Marques-Ibanez, D. 2011. TheBank Lending Channel: Lessons from the Crisis.Economic Policy, 26 (66), 135–182.

Gambacorta, L. 2005. Inside the Bank LendingChannel. European Economics Review, 49 (7),1737–1759.

Gambacorta, L. and Mistrulli, P. E. 2004. DoesBank Capital Affect Lending Behavior? Journal ofFinancial Intermediation, 13 (4), 436–457.

154 Klára Baková

Gunji, H. and Yuan, Y. 2010. Bank Profitability andthe Bank Lending Channel: Evidence from China.Journal of Asian Economics, 21 (2), 129–141.

Guiso, L., Kashyap, A. K., Panetta, F. andTerlizzese, D. 2002. How Interest Sensitiveis Investment? Very (When the Data AreWell Measured). Presented at the NBERSummer Institute, Capital Markets in theEconomy Workshop. Available at: http://www.nber.org/~confer/2002/si2002/guiso.pdf.

Hawtrey, K. and Liang, H. 2008. Bank InterestMargins in OECD Countries. North AmericanJournal of Economics and Finance, 19 (3),249–260.

Heryán, T. and Tzeremes, P. G. 2017. The BankLending Channel of Monetary Policy in EUCountries During the Global Financial Crisis.Economic Modelling, 67, 10–22.

Ho, T. S. Y. and Saunders, A. 1981. The Determinantsof Bank Interest Margins: Theory and EmpiricalEvidence. Journal of Financial and QuantitativeAnalysis, 16 (4), 581–600.

Hou, X. and Wang, Q. 2013. Implications of BankingMarketization for the Lending Channel of MonetaryPolicy Transmission: Evidence from China. Journalof Macroeconomics, 38 (B), 442–451.

Jiménez, G. and Saurina, J. 2006. Credit Cycles,Credit Risk, and Prudential Regulation.International Journal of Central Banking, 2 (2),65–98.

Jorge, J. 2009. Why Do Bank Loans React with aDelay to Shifts in Interest Rates? A Bank CapitalExplanation. Economic Modelling, 26 (5), 799–806.

Kapounek, S., Kučerová, Z. and Fidrmuc, J. 2017.Lending Conditions in EU: The Role of CreditDemand and Supply. Economic Modelling, 67,285–293.

Kashyap, A. K. and Stein, J. C. 1995. The Impactof Monetary Policy on Bank Balance Sheets.Carnegie-Rochester Conference Series on PublicPolicy, 42, 151–195.

Kashyap, A. K. and Stein, J. C. 2000. What Do aMillion Banks Have to Say About the Transmissionof Monetary Policy? The American EconomicReview, 90 (3), 407–428.

Kučerová, Z. and Kapounek, S. 2015. Determinantsof Bank Lending Activities in the EuropeanUnion Countries: Is There Any Difference betweenBank-Based and Market-Based Systems? InEconomic Policy in the European Union MemberCountries, pp. 315–326. ISBN 978-80-248-3796-3.

Kiyotaki, N. and Moore, J. 1997. Credit Cycles.Journal of Political Economy, 105 (2), 211–248.

Levieuge, G., Lucotte, Y. and Ringuedé, S. 2018.Central Bank Credibility and the ExpectationsChannel: Evidence Based on a New CredibilityIndex. Review of World Economics, 154 (3),493–535.

Lown, C. and Peristiani, S. 1996. The Behavior ofConsumer Loan Rates During the 1990 CreditSlowdown. Journal of Banking & Finance, 20 (10),1673–1694.

Maddaloni, A. and Peydró, J.-L. 2011. BankRisk-Taking, Securitization, Supervision and LowInterest: Rates Evidence from the Euro Area andthe U.S. Lending Standards. Review of FinancialStudies, 24 (6), 2121–2165.

Markovic, B. 2006. Bank Capital Channels in theMonetary Transmission Mechanism. Bank ofEngland Working Paper No. 313.

Matousek, R. and Sarantis, N. 2009. The BankLending Channel and Monetary Transmission inCentral and Eastern European Countries. Journalof Comparative Economics, 37 (2), 321–334.

Maudos, J. and de Guevara, J. F. 2004. FactorsExplaining the Interest Margin in the BankingSectors of the European Union. Journal of Banking& Finance, 28 (9), 2259–2281.

McShane, R. W. and Sharpe, I. G. 1985. A TimeSeries/Cross Section Analysis of the Determinantsof Australian Trading Bank Loan/Deposit InterestMargins. Journal of Banking & Finance, 9 (1),115–136.

Pancrazi, R., Seoane, H. D. and Vukotic, M. 2016.The Price of Capital and the Financial Accelerator.Economics Letters, 149, 86–89.

Papadamou, S., Sidiropoulos, M. and Spyromitros,E. 2015. Central Bank Transparency and theInterest Rate Channel: Evidence from EmergingEconomies. Economic Modelling, 48, 167–174.

Sanfilippo-Azofra, S. S., Torre-Olmo, B.,Cantero-Saiz, M. and López-Gutiérrez, C.2018. Financial Development and the BankLending Channel in Developing Countries. Journalof Macroeconomics, 55, 215–234.

Swanson, E. T. and Williams, J. C. 2014. Measuringthe Effect of the Zero Lower Bound on Medium-and Longer-Term Interest Rates. AmericanEconomic Review, 104 (10), 3154–3185.

Turgutlu, E. 2010. Cyclical Behavior of Price-costMargins in the Turkish Banking Industry.Economic Modelling, 27, 368–374.


8 ANNEX

Tab. 5: Descriptive statistics

Variable Observations Mean Std. deviation Min. Max.Interest margin 27,190 2.7265 10.128 −353.53 812.50GDP 44,784 0.9242 0.1742 0.2706 1.6108Liquid assets to total assets 24,685 0.2311 0.2233 −0.0509 1.0000Deposits to assets 24,409 0.7981 0.1875 0.0000 1.8684Equity to assets 24,741 0.1028 0.1204 −2.5062 1.0000Loan loss reserve to gross loans 12,468 4.2432 6.7056 −0.3880 100.00

Tab. 6: Cross-correlation matrix

Variable Interestmargin GD Liquid assets

to total assetsDepositsto assets

Equityto assets

Loan loss reserveto gross loans

Interest margin 1.000GDP −0.131 1.000Liquid assets to total assets −0.188 −0.098 1.000Deposits to assets 0.183 0.009 0.046 1.000Equity to assets 0.346 0.064 0.022 −0.130 1.000Loan loss reserve to gross loans 0.341 −0.039 0.130 0.053 0.162 1.000

AUTHOR’S ADDRESSKlára Baková, Mendel University in Brno, Faculty of Business and Economics, Zemědělská 1,613 00 Brno, Czech Republic, e-mail: [email protected]


www.ejobsat.com

FACTORS INFLUENCINGDIVIDEND POLICY IN BANGLADESH:SURVEY EVIDENCE FROM LISTEDMANUFACTURING COMPANIES INDHAKA STOCK EXCHANGEMohammad Shahidul Islam1, ATM Adnan1

1BGMEA University of Fashion & Technology, Dhaka, Bangladesh

ISLAM, Mohammad Shahidul, and ADNAN, ATM. 2018. Factors Influencing Dividend Policy in Bangladesh:Survey Evidence from Listed Manufacturing Companies in Dhaka Stock Exchange. European Journal of BusinessScience and Technology, 4 (2): 156–173. ISSN 2336-6494, DOI http://dx.doi.org/10.11118/ejobsat.v4i2.132.

ABSTRACT

A firm considers various factors when approaching a dividend policy decision. To analyze thedeterminants of dividend policy in the context of Bangladesh, questionnaire survey has been donefrom financial decision makers of sample companies. The nonparametric test and factor analysisis used for interpreting results. The research finding exhibits that in the first stage, the economicrelated factor, legal constraint factor, capital market related factor, residual policy factor, capitalsource factor and clientele factors are considered in dividend decision making. Then in the secondstage, the companies follow the preceding years’ pattern of dividend payment. In the next stage,dividend decision is made mainly on the level of earnings and liquidity. The observed result revealsthat present earnings and liquidity are the most likely factors for the firm in deciding the payoutpolicy.

KEY WORDS

factor analysis, EPS, DPR, MM model, Lintner model

JEL CODES

A100, A110

1 INTRODUCTION

Over the past half-century, numerous re-searchers have attempted to identify differentfactors influencing the payment of dividends.For example, in his seminal study, Lintner(1956) reports that past dividends and currentearnings are the primary determinants of cur-rent dividends and managers prefer to maintain

stable dividends and make periodic adjustmentstoward a target payout ratio. In a recent study,Brav et al. (2005) benchmark their findings toLintner. They found that the perceived stabilityof future earnings still affects dividend policybut the link between dividends and earnings isweaker. They also found that managers contin-

Factors Influencing Dividend Policy in Bangladesh: Survey Evidence … 157

ued to make dividend decisions conservativelybut that the importance of targeting the payoutratio was not as high. Dividend payers alsotend to smooth dividends from year to year andalter the amount of dividends in response topermanent changes in earnings. In their reviewof the literature on dividend determinants sinceLintner, Baker and Nofsinger (2010) concludedthat managers tend to share some commonly-held beliefs about the factors that affect div-idend policy. The evidence suggests that thekey determinants that influence dividend policyappear to have remained fairly stable over morethan 50 years. Some of the more importantand consistent determinants of payout policyare the pattern of past dividends, stability ofearnings or cash flows, and the level of currentand expected future earnings. Such firm-specificfactors appear to be first-order determinants inmaking dividend decisions.

Since Black (1976b) referred to the interestin dividends by shareholders and the practiceof firms paying dividends as the ‘dividendpuzzle,’ researchers have tried to understandthe determinants of dividend policy. Dividendpolicy remains a topic of ongoing debate amongfinancial economists (Baker and Wurgler, 2002).Although most studies focus on US firms, agrowing body of evidences exists on dividendpolicy outside of the US. These studies generallyrely on economic modeling approaches insteadof obtaining direct evidence about how in-vestors and managers behave and perceive divi-dends. Researchers cannot fully identify factorsinfluencing dividend policy by merely modelingmarket data, but must also use interactive toolssuch as interviews and surveys. To resolve thedividend puzzle, Chiang et al. (2006) concludedthat the cardinal thrust of academic researchmust turn toward learning about the motivationfor making managerial decisions and the percep-tions upon which this motivation is based.

The board of directors takes the dividenddecision along with other financial decision. So,their consideration about dividend decision isimportant. The opinion of dividend decisionmakers is taken with survey. The survey find-ings reveal the factors which are consideredin dividend decision. The choice of influencing

factors for questionnaire survey is based on theprevious studies and opinion of the corporatetop level managers. We conducted this studyseparately (financial sector and nonfinancialsector) to identify the factors in respectivesectors.

In first world economies, the payout deci-sion has been taken very cautiously by bothinvestors and the administration of the businessentity (Glen et al., 1995). Many prominentresearch works such as Lintner (1956), Millerand Modigliani (1961), Baker and Powell (2000)on the subject of the payout policy has beencarried out with pragmatic proof concerning thedeterminants of payout strategy. Still, there isabsence of uniform and cohesive clarificationon what factors stimulate the dividend policy.This is known as the dividend puzzle in financeliterature (Black, 1976a). Many hypotheseshave been developed to solve this dilemma butthe challenge still exists.

The most key question regarding dividendpolicy is: what are the determining factors ofdividend policy? Researchers have come outwith several findings regarding the determi-nants such as Kania and Bacon (2005), Al-Malkawi (2007), Gill et al. (2012) exhibits firm’sprofitability, while Anil and Kapoor (2008)shows Liquidity position as a significant de-terminants. In reality, determining the suitabledividend policy it is often a strenuous taskof harmonizing many contradictory forces. Thevital elements are not complicated to recognizebut the relations involving those elements aremultifaceted and complex to explain (Rosset al., 2008). Researchers have mostly con-centrated on developed economies; however,further focus into the payout policy debatecan be gained momentum by an assessmentof developing countries, like Bangladesh. Thisresearch planned to identify the determinantsof dividends payout policy for manufacturinglisted companies in Dhaka stock exchange(DSE) and to verify whether the potentialdeterminants identified in the literature appliesin an emergent stock exchange like DSE.

In developing countries like Bangladesh, in-tensive research in this area is rare. So, this gapinspires us to conduct the primary survey for

158 Mohammad Shahidul Islam and ATM Adnan

identifying the factors which are considered inthe time of dividend decision.

A number of prior studies have exhibits thatdividend expenditure decision is subjective tovarious factors; it is sensible for the majorstakeholders of a company to understand fac-tors that influence company’s dividend payoutdecisions. This research is projected to enhanceconception of the stimulators of dividend pay-out within the manufacturing firms operatingwithin the Bangladesh corporate environment.

In spite of ample amount of study, we stilldo not have any conclusive suggestion to thedividend dilemma (Baker et al., 2002).

There are considerable number of researchescarried on the area of payout policy in contextof different geography and industry but thedefinite driving force of dividend choice stillremains inexplicable in corporate finance andadvance investigation is essential to enhance theunderstanding of the subject (Baker and Pow-ell, 1999). Hence lack of conclusive consensusresolution for the subject of dividend policy,result many researchers continuing to conductinvestigate on this field in order to obtain astrong theoretical and pragmatic investigationon payout and solve this payout Dilemma.

Dividend distribution strategies for manu-facturing companies listed at DSE differ sig-nificantly while operating under same business

atmosphere. The questions how do the manu-facturing companies decide on the rationalityand rate of their payout impose the dilemma individend payout in Bangladesh context. Theseexpose that there is no unified picture regardingdividend payout policy. Moreover it would alsoreasonable to argue that there are so manyfactors influence dividend policy and there is nocertain rule of thumb for companies to decideon the rate of payout. In addition to that whenpointing to the earlier experiential researches ondividend policy, most of them have been carriedmainly on U. S. firms, developed countries,emerged market, Asia and western Africa butscarcely there is any proof has been recognizedfrom Bangladesh perspective. So there is aneed to observe the factors which determinethe dividend payout policy for manufacturingcompanies listed at DSE, which may presentadditional insights for noteworthy factors to beevaluated.

The paper is structured as follow; the firstsection introduces about the dividend policyand its determinants. The second section rep-resent the literature review (the contributionof previous researchers). The research method-ology is clearly explained in Section 3. In theSection 4, analysis and its result are interpreted.The Section 5 and 6 represent conclusion andreferences respectively.

2 LITERATURE REVIEW

2.1 Empirical Evidence ofDeveloped Countries

Lintner (1956) in his pioneering work on div-idend policy interviewed managers from 28enterprises and based on findings concludedthat dividends are sticky, tied to long-term sus-tainable earnings, paid by mature enterprises,smoothed from year to year, and targeteda long-term payout ratio when determiningdividend policy.

Baker et al. (1985) survey revealed that thefirst highly ranked determinant was the antic-ipated level of an enterprise’s future earnings,the second factor was the pattern of past divi-

dends and the third factor cited as important indetermining dividend policy was the availabilityof cash. In particular, respondents were highlyconcerned with dividend continuity, and the re-spondents believed that dividend policy affectsshare value and dividend payments provide asignaling device of enterprise future prospects.Baker (2009) surveyed managements’ views onstock dividends. The analysis was based onthe responses of 121 responding enterprises.The major findings of the survey were thatmanagers strongly agree on stock dividendswhich have a positive psychological impact,managers believe stock dividends enable themto express their confidence in the enterprise’s


future prospects, and the dominant motivefor paying stock dividends is to maintain theenterprise’s historical practice.

Baker and Powell (2000) investigated theviews of corporate managers of major US en-terprises about the factors influencing dividendpolicy. They concluded that the most importantdeterminants of an enterprise’s dividend policywere the level of current and expected futureearnings and the pattern or continuity of pastdividends.

Dalmácio and Corrar (2007) surveyed onmanagement views on corporate dividend pol-icy in Portugal. This paper focuses on thedividend policy of the companies listed on theLisbon Stock Exchange (LSE), from the view-point of their managers. It takes as its startingpoint the results obtained from a questionnaireanswered by the Chief Executive Office andthe Chief Financial Officer. Following Lintner(1956), which were later confirmed by theempirical studies of Fama and Babiak (1968),Baker et al. (1985) and Partington (1989), theycame to the conclusion that the most significantfactors were the dividend stability and theshareholders’ satisfaction. The importance ofsignaling and clientele effects was also signif-icant. By using the factorial analysis and theprincipal component analysis in their study,they tried to identify new variables, whichpresented positive correlation with the dividendpolicy. Two factors, which explain about 56%of the total variance, were found. The resultssuggest that the managers of the listed com-panies determine the respective dividend policyas passive residual, though they show concernabout the signaling of the prospective profit, thequotation stability and taxes. Besides that, theyseem to be worried about the dividend stabilityand alterations, which can be reversible, and,also, with the current practice in the sector towhich the company belongs. Also, the relativeimportance of the amount of shares in thehands of managers and controlling groups isrelevant, which can be associated with thedegree of capital concentration. Finally, theycan say that the fact that it is easy to obtainexternal capital in the future also conditions thedividend policy.

Brav et al. (2005) surveyed 384 chief fi-nancial officers and treasurers to determinekey factors that drive dividend and repurchasepolicy. The survey unveiled that, except underextraordinary circumstances, managers have astrong desire not to cut dividends. As a result,for enterprises that pay dividends tend to besmoothed from year to year and linked tosustainable long-run changes in profitability.

Baker et al. (2006) reported the results ofa 2004 survey from managers of dividend-paying Norwegian firms listed on the Oslo StockExchange about their views on dividend policy.Specifically, they identified the most importantfactors in making dividend policy decisions andmanagers’ views about various dividend-relatedissues. The most important determinants of afirm’s dividend policy are the level of currentand expected future earnings, stability of earn-ings, current degree of financial leverage, andliquidity constraints. No significant correlationexists between the overall rankings of factorsinfluencing dividend policy between Norwe-gian and U. S. managers. Norwegian managersexpress mixed views about whether a firm’sdividend policy affects firm value. Respondentspoint to the possible role of dividend policyas a signaling mechanism. No support existsfor the tax-preference explanation for payingdividends.

Mizuno (2007) surveyed the views of corpo-rate managers on payout policy of Japaneseenterprises listed in Tokyo Stock Exchange.The analysis of the responses obtained from69 enterprises revealed that on payout policyenterprises put higher emphasis on dividendsthan on share repurchases, enterprises attachmore importance to stable dividends than toperformance linked dividends, and corporatemanagers recognized the relationship betweendividends and an enterprise’s value.

Vieira (2011b), Archbold and Vieira (2010)and Vieira (2011a) reported the empirical re-sults of a questionnaire survey about corporatedividend policy addressed to finance directorsof UK and Portuguese listed firms. Similar toother studies for example, Brav et al. (2005)in the US and Dhanani (2005) in the UK,they surveyed 313 finance directors in the UK


and 48 in Portugal to examine their views ofand understanding about the dividend decisionin order to compare practice with theoreticalpropositions to be found in the literature.Their survey results demonstrate similaritiesin the responses from the UK and Portugal,but also substantive differences, particularlyin respect of the interaction between dividendand investment decisions and views about thesignaling consequences of dividends.

Baker et al. (2011) surveyed on managersof firms listed on the Toronto Stock Exchangeabout their views on dividends. They found theperceptions of factors that influence dividendpolicy differ between managers of financialand nonfinancial firms. Industry classificationalso affects how managers view statementsabout the dividend pattern, dividend settingprocess, dividend policy and firm value, residualdividend theory, and explanations for payingdividends. However, they found weak, if any,multinational operations effect on managerperception of dividends. They concluded thatresearchers investigating dividends should par-tition the data by industry type and perhapsother firm characteristics to better understandthe dividend puzzle.

2.2 Empirical Evidence ofDeveloping Countries

Khurana (1985) surveyed the corporate divi-dend policy in India mailing structured ques-tionnaire to the 215 enterprises. The surveyand personal interviews, among others, revealedthat dividend decision of enterprises was pri-marily governed by net profits and dividendpaid in the previous year.

Manandhar (2002) surveyed the views ofcorporate executives on dividend policy andpractice of corporate enterprises in Nepal. Themajor findings of the survey were that dividenddecision was considered as discretionary deci-sion, and lack of timely disclosure of relevantfinancial information and low rate of dividendpayment were the major causes to the declininginvestors’ confidence in the stock market.

Pradhan and Adhikari (2003) surveyed theviews of financial executives of 50 large Nepalese

enterprises. The survey findings, among others,revealed that major motive for paying cash div-idends is to convey information to shareholdersabout favorable prospects of the enterprise anddividend decision is not a residual decision.

Deshmukh et al. (2013) analyzed the resultsof 2001 survey of 81 CFOs of bt-500 companiesin India to find out the determinants of thedividend policy decisions of the corporate India.It uses factor analytic framework on the CFOs’responses to capture the determinants of thedividend policy of corporate India. Most ofthe firms have target dividend payout ratioand dividend changes follow shift in the long-term sustainable earnings. The findings ondividend policy are in agreement with Lintner’sstudy on dividend policy. The dividend policyis used as a signaling mechanism to conveyinformation on the present and future prospectsof the firm and thus affects its market value.The dividend policy is designed after takinginto consideration the investors’ preference fordividends and clientele effect.

Basnet (2007) surveyed the views of man-agers on dividend policy of Nepalese enterpriseslisted at Nepal Stock Exchange Ltd. (NEPSE).The survey revealed that level of current andexpected future earnings, liquidity constraints,projection about future state of the economy arethe important factors in setting the enterprise’sdividend policy in Nepal.

Adeyemi and Adewale (2010) studied ondividend policy. It is a pivot around which otherfinancial policies rotate, hence central to theperformance and valuation of listed firms. Thisis more because managers as decision makersare often confronted with the “dividend puzzle”– the problem of reconciling observed dividendbehavior with economic incentives. This paperis motivated by the apparent dearth of empiricalworks on dividend policies and practices inNigeria and hence aims to evaluate such policiesand practices among selected Nigerian quotedfirms. The result of the survey questionnairesshows that Nigerian investors’ attitudes areconsistent with those of the bird-in-the-handtheorists. Hence, Nigerian managers’ beliefs arethat dividend payouts have significant signalingeffect both on share price and future prospects


of a firm. Consequently, they strive to maintaina consistent and uninterrupted dividend payoutpolicy.

Asghar et al. (2011) surveyed the views of60 financial executives on practices of dividendpolicy in Nepal. The results revealed thatamong others, stability of earnings, level ofcurrent earnings, and pattern of past dividendswere the three important factors in order oftheir importance determining dividend policyof corporate sector.

Adhikari (2013) analyzed the perceptionsof managers on dividend policy by surveyingthe views of 125 Managers of 66 companieslisted at Nepal Stock Exchange. This surveyis motivated by the observation that much ofdividend policy theory is implicitly based ona capital market perspective. Out of 66 listedenterprises surveyed, 16 were from banks and50 were from nonbanks. To examine whetherviews of managers on dividend policy differbetween banking group and nonbanking group,chi-square analysis was used. Spearman’s rankcorrelation coefficient was calculated to findout the degree of relationship between theresponses of banking group and nonbankinggroup and it was tested for significance at 5percent level of significance. Median value ofresponses for each statement of observationon dividend policy was computed to highlightthe significance of observation. The results ofthis study indicate that the most importantdeterminants of dividend policy in order aregrowth rate of enterprise’s earnings, patternsof past dividends, availability of investmentopportunities; managers have more emphasis onthe stable dividend policy; and dividend policyinfluences the value of the enterprise in Nepal.

Haleem et al. (2011) examined the percep-tions of managers of dividend-paying firmslisted on Karachi Stock Exchange (KSE) on fac-tors influencing dividend policy, issues relatingdividend policy and the corporate governancepractices. The survey shows that the mostimportant factors that affect dividend policyare: the level of current earnings, the projectionabout the future state of the economy, thestockholders characteristics, concerns about thestock prices, need of current stockholders. From

a practical perspective, there is little discrimi-nation among the top ranked factors. All thesurveyed firms formulate their dividend policiesaccording to the theoretical model of Lintner(1956). The survey also shows that there isno difference in responses about these factorswith respect to various titles of the respondentssuch as chief financial officer or Chief ExceptiveOfficer. The survey also finds strong supportfor the life cycling theory followed by agencytheory, signaling theory and the catering theoryrespectively. The survey also shows the pres-ence of corporate governance practices in thesurveyed firms.

Khan et al. (2011b) surveyed the opinions offinance directors of 60 foreign listed companiesout of 105 foreign listed companies on Karachistock exchange in order to visualize theirview about the dividend decision. The surveyresulted into some very important points to benoted that include: the firms give importanceto the dividend as it was in past and thegrowth is considered at time of declaration ofdividend; the dividend decision is influenced bythe competitor policy and the fear of signalingof shortage of profitable investment; and the re-sults demonstrate that foreign listed companiesare more concerned with dividend policy.

Alshammari (2012) surveyed the corporatemanagers of 123 Kuwaiti firms listed in theKuwait Stock Exchange (KSE) in order tolook into what affects dividend policies inKuwait. The questionnaire based survey with52.58 percent response rate led some importantfindings. The major findings of the surveywere that future earnings was a paramountfactor that affects the level of current dividendsand the level of current liquidity is anotherimportant factor affecting dividends in Kuwaitilisted firms.

Baker and Powell (2012) surveyed managersof dividend-paying firms listed on the Indone-sian Stock Exchange (IDX) to learn their viewsabout the factors influencing dividend policy,dividend issues, and explanations for payingdividends. Of the 163 firms surveyed, 52 firmsresponded, resulting in a response rate of 31.9per cent. The evidence showed that managersview the most important determinants of div-


idends is the stability of earnings and thelevel of current and expected future earnings.The evidence also showed that managers ofIndonesian firms perceive that dividend policyaffects firm value.

Naser et al. (2013) surveyed the managers ofthe companies listed on Abu Dhabi SecuritiesExchange. The survey based on the responsesobtained through 34 filled up questionnairesrevealed, among others, that external factorsrelated to the economic conditions togetherwith the state of the capital market and lendingconditions are all important factors in formulat-ing dividend policy, and restrictions imposed onthem by debt providers together with currentfinancial market crises are the most importantfactors that affect their dividend policy.

Abor and Fiador (2013) surveyed the opin-ions of managers on factors influencing div-idends decision in Nigerian listed firms. Thesurvey revealed, among others, that pattern ofpast dividends, the level of current earnings,current degree of financial leverage, availabil-ity of alternative source of capital, liquidityconstraints such as availability of cash, growthand investment opportunities have a significantinfluence on dividend decision in Nigerian firms.

John (2018) studied to examine the opinionsof managers on factors influencing dividendsdecision in Nigerian listed firms. The studyemploys survey research design and obtainedprimary data from selected managers throughthe administration of questionnaire. The resultof the study reveals that pattern of past divi-dends, level of current earnings, current degreeof financial leverage, availability of alternativesource of capital, liquidity constraints suchas availability of cash, growth and invest-ment opportunities have significant influenceon dividend decision in Nigeria. The studyrecommends that future researchers shouldinvestigate the relationship between dividendpayment and firms’ value.

Naser et al. (2013) studied to explore the per-ception of managers of companies listed on AbuDhabi exchange about dividend policy. Thirty-four out of fifty-nine managers of companieslisted on Abu Dhabi Securities Exchange wereasked to reflect their experience about different

aspects of dividend policy. The bird-in-the-hand theory received the highest support. Thestudy extends limited previous research basedon questionnaire and survey related dividendpolicy. It thus provides new evidence from anemerging and fast growing economy.

The reviews of aforementioned surveys ex-pose that there are various surveys on dividendpolicy mostly in the context of developed coun-tries, and there are very few and less compre-hensive surveys of managers with inconclusiveresults on dividend policy conducted in thecontext of Bangladesh. Thus, there is a need ofconducting another survey of managers’ viewscovering the divergent aspects of dividend pol-icy in Bangladesh. Thus, there is a need of con-ducting another survey of managers’ views cov-ering the divergent aspects of dividend policy inBangladesh. The important factors of dividendpolicy are past dividend, earnings, competitors’dividend, types of shareholders, liquidity level,tax, availability of external fund, legal rules andregulations, economic volatility etc.

2.3 Research Gap

In above paragraphs, review of literaturesillustrate that the payout determinants havebeen well investigated and acknowledged infirst world economies, emerging markets likeMalaysia, India, Pakistan and Saudi Arabiaand few in Africa like Nigeria, south Africaand Ghana but there is scarcity of experien-tial studies in Bangladesh context. Thereforethe research essential to fill the knowledgegap sustaining by practically identifying thesignificant factors concerning payout policy inBangladesh for the manufacturing companieslisted at DSE. Besides, a range of researchfrom different country, economy and businesscontext have been carried out to sort out thedividend dilemma. But due to the difference inlegal, the tax and the accounting policy amongthe countries and across industries with mixedcharacteristics, there is no cohesive means to setout dividend payout strategy. These implyingthat dividend dilemma still exist and requireresearch regarding determinants of dividendpayout policy for the manufacturing companies


listed at DSE in Bangladesh. thus this study ismodest input to resolve dividend dilemma.

At long last, most of existing research usemultiple regressions but not panel data (crosssectional)/time series multiple regression. Thisstudy adopts panel data regression as wellfactor analysis in identifying the determinantsof dividend payout policy for the manufacturingcompanies listed at DSE in Bangladesh.

This research has got substantial contribu-tion in a number of ways. To begin with, itfocuses on the decisive factors of managerswhile deciding on the dividend policy. The topic

payout policy is very imperative as a lucrativeand frequent corporate dividend policy followedby higher management would establish yard-stick of the wellbeing of the firms thus moredividends can be dispersed to the equity holderswhile sustaining the inclusive wellbeing of thecorporation. Secondly, the research exhibits amajor part to existing academic and experi-ential facts concerning determinants of payoutpolicy. Finally, the research may provide as anorientation and foundation for advance studyon determinants of dividend payout policyactions in developing countries.

3 RESEARCH DESIGN

The present research is based on an empiri-cal study of 108 listed firms from the DSE(Dhaka Stock Exchange) with the objective ofidentifying the determinants of dividend policy.The data have been collected through theprimary mode using a structured questionnairecontaining 28 statements based on 5 pointlikert scale where not important = 0, lowimportant = 1, moderate = 2, important =3, very important = 4. The respondents areasked to indicate the level of importance ofthe factors for determining their firm’s dividendpolicy. The questionnaire has been preparedafter reviewing the prior studies on dividendpractices by decision maker. The survey followsthe literature of Baker and Powell (2000), Bravet al. (2005), Baker et al. (1985) etc.

We have mailed the survey instruments tothe chief financial officer (CFO) and Managingdirector, Chairman, Board of directors of eachfirm in September 2015. The mail included acover letter and a stamped return envelope.The cover letter assured recipients that theiranswers would be confidential and released onlyin summary form. But we did not find satis-factory response. So, later, we went personallyto the respondents of each firm. Finally, we

have collected 108 respondents’ opinion throughquestionnaire.

We have used a nonparametric test (χ2 test)to determine whether the mean response foreach of the 28 factors involving dividend policydiffers significantly from 0 (not important).This study follows the test of Baker and Powell(2000), Baker et al. (1985) etc.

The factor analysis has been used to an-alyze the dividend determinants by decisionmaker. The Principal Components Analysis hasbeen used to explore and confirm the inter-relatedness between the occurrences of variablespertaining to dividend. The number of principalcomponents to be retained has been decidedbased on Kaiser’s criterion of Eigen value >1 and Bartlett’s test. The Bartlett’s test ofsignificance led to acceptance of significantprincipal components. The PCA with varimaxrotation method has been used to maximize thesum of squared loading of each factor extractedin turn. It explained more variance than theloadings obtained from any other method of fac-toring. The factors loaded by variables havingsignificant loadings of the magnitude of 0.5 andabove have been interpreted.


Tab. 1: Variables used in the study

No. Factors No. Factors

X1 Pattern of past dividend X15Preference for dividends rather thanrisky reinvestment

X2 Desire to maintain a constant payout ratio X16 Cost of raising external funds

X3The dividend policies of competitorsor other companies in the same industry X17

Availability of profitable investmentopportunities for the firm

X4 Stability of earnings X18 Availability of alternative source of capital

X5 Level of current earnings X19Investors opportunities for investingin another projects

X6 Anticipated level of future earnings X20Concern that a dividend change mayprovide a wrong signal to investors

X7 A sustainable change in earnings X21 The future state of the economy

X8Attracting institutional investorsto purchase the stock X22 Inflationary Consideration

X9 The influence of institutional shareholders X23Concern about maintaining a targetcapital structure

X10Attracting individual investorsto purchase the stock X24 Legal rules and constraints

X11 Concern about the stock price X25Contractual constraints such as dividendrestriction in debt contracts

X12 Liquidity level X26 Accessibility to capital marketX13 Tax positions of shareholders X27 Dilution of control & dilution of earnings

X14 Category of shareholders and their expectations X28Internal rate of return considerationi.e. reinvestment rate

4 RESULTS AND DISCUSSIONS

4.1 Nonparametric Test

From the Tab. 2, it is seen that the variable 3(the dividend policies of competitors or othercompanies in the same industry) and variable 19(investors opportunities for investing in anotherprojects) are statistically insignificant at χ2

test and the more than 40 percent respondentsgave their opinion as not important and lowimportant variables on dividend determinants.

Among the significant variables, the variables5 (level of current earnings), 12 (liquidity level),1 (pattern of past dividend), 4 (stability of earn-ings), 2 (desire to maintain a constant payoutratio) are the top five significant determinantsin dividend decision. These reveal the pictureof dividend determinants in our country. Thecompanies mainly consider the current earningsand liquidity position of the company. Theyalso maintain to follow the pattern of previousyears dividend payment by paying stable divi-dend payout ratio. Others factors are relevant

but the managers mainly consider the earlier tomost significant factors. The results support thefindings of Mizuno (2007), Khan et al. (2011b),Alshammari (2012), Baker and Powell (2012),Naser et al. (2013), John (2018), Manandhar(2002), Shah et al. (2010), Baker et al. (2011),Archbold and Vieira (2010).

We have conducted the factor analysis withthe significant variables for identifying therelevant determinants of dividend decision.

4.2 Factor Analysis

The scale of measurement was tested usingCronbach α reliability test. It was found to be0.810 which is considered a satisfactory level ofreliability.

The tests have been conducted to know thatwhether the sample is adequate or not. Thesampling adequacy is depicted in Tab. 4.


Tab. 2: Test of significance

Level of importance (%)Very

important Important Moderate Lowimportant

Notimportant Mean Rank χ2 value Asymp. Sig.

X1 32.56 48.84 15.12 1.16 2.33 3.0706 3 72.25 0.000X2 16.28 26.74 47.67 19.77 0.00 2.9765 5 62.60 0.000X3 12.79 23.26 27.91 23.26 15.12 1.9294 23 5.51 0.239X4 40.70 41.86 13.95 2.33 1.16 3.1882 4 69.23 0.000X5 46.51 37.21 13.95 2.33 0.00 3.2941 1 42.93 0.000X6 15.12 39.53 30.23 13.95 1.16 2.5294 7 38.76 0.000X7 13.95 39.95 32.56 10.47 2.33 2.4941 9 41.20 0.000X8 4.65 12.79 38.37 30.23 13.95 1.6588 26 32.98 0.000X9 2.33 12.79 43.02 29.07 12.79 1.6353 28 44.23 0.000X10 12.79 24.42 33.72 15.12 13.95 2.0941 18 13.76 0.008X11 36.05 33.72 17.44 9.30 3.49 2.8824 6 36.09 0.000X12 50.00 34.88 8.14 5.81 1.16 3.2588 2 78.18 0.000X13 10.47 22.09 29.07 31.40 6.98 1.9647 21 20.51 0.000X14 11.63 22.09 34.88 24.42 6.98 2.0706 19 20.86 0.000X15 3.49 20.93 33.72 32.56 9.30 1.7529 25 31.55 0.000X16 6.98 19.77 39.53 25.58 8.14 1.9059 22 31.09 0.000X17 16.28 38.37 26.74 13.95 4.65 2.5059 8 30.70 0.000X18 10.47 37.21 29.07 18.60 4.65 2.2941 15 30.39 0.000X19 10.47 17.44 24.42 22.09 25.58 1.6471 27 6.55 0.161X20 12.79 37.21 30.23 15.12 4.65 2.3765 12 30.62 0.000X21 10.47 39.53 24.42 22.09 3.49 2.3412 14 33.07 0.000X22 6.98 29.07 32.56 23.26 8.14 2.0588 20 24.11 0.000X23 9.30 38.37 36.05 10.47 5.81 2.3765 13 43.07 0.000X24 20.93 26.74 26.74 20.93 4.65 2.4118 11 14.11 0.007X25 4.65 13.95 40.70 23.26 17.44 1.8588 24 27.37 0.000X26 6.98 31.40 41.86 12.79 6.98 2.1647 16 68.04 0.000X27 12.79 41.86 31.40 9.30 4.65 2.1412 17 42.83 0.000X28 12.79 41.86 31.40 9.30 4.65 2.4824 10 43.41 0.000

Tab. 3: Reliability statistics

Cronbach’sAlpha

Cronbach’s Alpha Basedon Standardized Items

Number ofitems

0.810 0.809 26

Tab. 4: KMO and Bartlett’s test

Kaiser-Meyer-Olkin Measureof Sampling Adequacy 0.632

Bartlett’s Test of Sphericity:Approx. χ2 940.922df 378Sig. 0.000

KMO recommends accepting value greaterthan 0.5 as barely acceptable and Bartlettrecommends the accepting value less than0.05. Since the accepting value for variables is0.632 (more than 0.5) for KMO and 0.000 forBartlett’s test (less than 0.05), these measuresindicate that the set of variables is appropriatefor factor analysis and the analysis can proceedfor next stage.

Factor analysis procedure is based on initialcomputation of a table of correlations amongthe variables that is, correlation matrix. Thismatrix is then transformed through estimation


Tab. 5: Total variance explained

Initial Eigen values Extraction sumsof squared loadings

Rotation sumsof squared loadings

Com-ponent Total % of

varianceCumulative

% Total % ofvariance

Cumulative% Total % of

varianceCumulative

%1 5.122 18.294 18.294 5.122 18.294 18.294 3.004 10.729 10.7292 3.123 11.153 29.447 3.123 11.153 29.447 2.688 9.601 20.3313 2.421 8.648 38.095 2.421 8.648 38.095 2.620 9.358 29.6884 2.217 7.917 46.012 2.217 7.917 46.012 2.270 8.108 37.7965 1.568 5.601 51.613 1.568 5.601 51.613 2.023 7.226 45.0226 1.462 5.220 56.833 1.462 5.220 56.833 1.797 6.417 51.4407 1.410 5.035 61.869 1.410 5.035 61.869 1.777 6.347 57.7868 1.261 4.503 66.372 1.261 4.503 66.372 1.628 5.815 63.6019 1.124 4.015 70.387 1.124 4.015 70.387 1.514 5.407 69.00810 1.014 3.623 74.009 1.014 3.623 74.009 1.400 5.001 74.00911 0.790 2.821 76.83012 0.676 2.414 79.24513 0.652 2.329 81.57414 0.615 2.197 83.77115 0.579 2.068 85.83916 0.502 1.792 87.63017 0.445 1.590 89.22118 0.435 1.555 90.77519 0.415 1.484 92.25920 0.387 1.381 93.64021 0.328 1.171 94.81222 0.300 1.071 95.88323 0.274 0.980 96.86224 0.241 0.860 97.72325 0.216 0.772 98.49526 0.167 0.595 99.09027 0.138 0.492 99.58228 0.117 0.418 100.000

Note: Extraction Method – Principal Component Analysis.

of a factor model to obtain the factor matrixcontaining the loadings for each variable oneach derived factor. The Tab. 5 contains theinformation regarding the factors and the rel-ative explanatory power as expressed by theireigen values. As per the latent root criteriaof retaining the factors, those factors shouldbe retained that have eigen value > 1. TheEigen values, the percentage of total variance,and rotated sum of squared loadings havebeen shown in Tab. 5. The factor matrix asobtained in the principal component analysis

has also been further subjected to VarimaxRotation. An examination of Eigen values hasled to the retention of ten factors. These factorshave accumulated for 10.72%, 9.60%, 9.35%,8.10%, 7.22%, 6.41%, 6.34%, 5.815%, 5.40%,and 5.00%of variation. This implies that thetotal variance accumulated for by all ten factorsis 74.00% and remaining variance is explainedby other factors.

The application of Cattell (1966) Scree test(Fig. 1) resulted in acceptance of Factors. TheScree plot shows the factor eigen values in


Tab. 6: Rotated component matrix

1 2 3 4 5 6 7 8 9 10X14 0.782 −0.048 0.152 0.166 0.080 −0.119 0.153 −0.032 0.179 −0.111X13 0.753 −0.044 0.022 0.019 0.192 0.008 −0.246 0.173 0.060 −0.010X8 0.609 0.098 0.045 0.200 −0.059 0.236 0.453 −0.192 −0.234 0.099X9 0.543 −0.113 0.119 0.086 0.183 0.526 0.100 0.108 −0.219 0.225X15 0.482 0.101 0.471 −0.026 0.254 0.001 0.163 −0.160 −0.075 0.251X4 0.090 0.800 0.000 0.062 −0.044 −0.101 −0.063 −0.225 0.023 0.023X5 −0.159 0.728 −0.171 0.130 0.040 −0.108 0.253 0.175 0.018 0.015X6 0.021 0.677 0.399 −0.066 0.059 0.162 0.107 0.106 −0.201 0.051X7 0.003 0.585 0.324 0.026 0.138 0.329 −0.022 0.216 0.210 −0.247X12 0.090 0.453 0.017 0.252 0.375 −0.445 −0.153 0.228 −0.155 −0.093X21 0.089 0.076 0.876 0.045 −0.037 0.007 0.010 0.108 0.029 0.040X22 0.132 0.026 0.658 0.362 −0.123 0.050 0.282 −0.135 −0.080 −0.095X24 −0.015 0.157 0.580 0.075 −0.034 0.248 0.209 0.162 0.146 −0.430X26 0.166 −0.117 0.100 0.803 0.054 0.118 0.102 0.201 0.058 −0.212X27 0.067 0.218 0.150 0.767 0.041 0.141 −0.060 −0.055 0.095 0.214X28 −0.241 0.330 0.169 0.468 0.077 0.150 0.088 0.266 0.273 −0.034X10 0.215 −0.078 0.053 −0.084 0.778 −0.011 0.270 −0.016 −0.133 −0.058X2 −0.057 0.138 −0.092 0.065 0.704 0.122 −0.244 −0.053 0.399 0.008X11 0.022 0.112 −0.137 0.471 0.644 −0.116 0.025 −0.150 −0.125 0.144X25 0.085 0.025 0.094 0.297 −0.024 0.835 0.018 0.085 −0.085 0.049X16 0.177 0.039 0.269 −0.001 0.146 0.162 0.742 −0.005 0.054 0.100X17 −0.084 0.207 0.063 0.088 −0.078 −0.195 0.629 0.495 0.062 −0.002X18 0.124 0.037 0.070 0.086 −0.088 0.119 0.052 0.643 0.096 0.085X1 0.074 −0.017 −0.014 0.104 −0.036 −0.124 0.035 0.096 0.857 0.134X23 −0.014 −0.312 0.374 0.332 0.131 0.243 0.282 0.075 0.481 0.126X20 −0.093 0.004 −0.008 0.019 −0.006 0.149 0.132 0.126 0.191 0.780

Notes: Extraction Method – Principal Component Analysis, Rotation Method – Varimax with Kaiser Normalization.Rotation converged in 14 iterations.

descending order. The eigen values of a fac-tor represents the variance explained by eachfactor. An elbow in the Scree plot occursat Factor 10, which indicates the point atwhich the inclusion of additional factors doesnot contribute significantly in explaining thevariance of the data set. The results of theanalysis are presented in the form of factorpattern matrix. Factors above the elbow of theplot are retained. A set of 10 Factors thatwere chosen accounts for about 74.009% of thevariations in the data.

After studying the Eigen values for thecomponents, the next step is to study the factormatrix and the respective factors loadings. The

loadings above 0.45 have been considered forthis study. For obtaining the rotated factormatrix, orthogonal rotation method (Varimaxrotation) has been used. The results are dis-played in Tab. 6.

After identifying the significant factor load-ings, next step is to study the communalitiesof the variables, representing the amount ofvariance accounted for by the factor solutionfor each variable. It is generally assumed thatvariable with communalities > 0.5 should beretained for the study, the communalities of thevariables have been shown in the Tab. 7.


Fig. 1: Scree plot

Tab. 7: Communalities

Initial Extraction Initial ExtractionX1 1.000 0.796 X15 1.000 0.650X2 1.000 0.767 X16 1.000 0.716X4 1.000 0.720 X17 1.000 0.750X5 1.000 0.711 X18 1.000 0.813X6 1.000 0.717 X20 1.000 0.817X7 1.000 0.727 X21 1.000 0.799X8 1.000 0.789 X22 1.000 0.712X9 1.000 0.759 X23 1.000 0.669X10 1.000 0.762 X24 1.000 0.706X11 1.000 0.742 X25 1.000 0.820X12 1.000 0.724 X26 1.000 0.812X13 1.000 0.701 X27 1.000 0.746X14 1.000 0.753 X28 1.000 0.598Note: Extraction Method – Principal ComponentAnalysis.

The principal component analysis using vari-max rotation of twenty six variables has led tothe extraction of ten factors. Tab. 8 representsthe final results of the study and reflects theextraction of the factors that are consideredmore influential by the respondents.

The rotated factor matrix has been shown inTab. 6. This shows that variables understudyhave constituted ten groups factors. These havebeen discussed in the following paragraphs.

Factor-I: Clientele factor. Factor-I explains10.72% of the total variations existing in thevariable set. This includes variables X14, X13,X8, X9 and X15. This factor has significantfactor loadings on these variables which haveformed this major cluster. So, this factorprovides a basis for conceptualization of adimension, which may be identified as ‘clientelefactor’.

Factor-II: Earnings and liquidity factor.Factor-II explains 9.6% of the total variationsexisting in the variable set. This includesvariables X4, X5, X6, X7 and X12. Thisfactor has significant factor loadings on thesevariables which have formed second importantcluster. So, this factor provides a basis forconceptualization of a dimension, which may beidentified as ‘earnings and liquidity factor’.

Factor-III: Economic related factor. Factor-III explains 9.35% of the total variations exist-ing in the variable set. This includes variablesX21, X22 and X24. This factor has significant


factor loadings on these variables which haveformed third cluster. So, this factor provides abasis for conceptualization of a dimension whichmay be identified as ‘economic related factor’.

Factor-IV: Capital market related factor.Factor-IV explains 8.1% of the total variationsexisting in the variable set. This includesvariables X26, X27 and X28. This factor hassignificant factor loadings on these variableswhich have formed fourth cluster. So, this factorprovides a basis for conceptualization of adimension, which may be identified as ‘capitalmarket related factor’.

Factor-V: Market price related factor. Factor-V explains 7.22% of the total variations existingin the variable set. This includes variables X10,X2 and X11. This factor has significant factorloadings on these variables which have formedfifth cluster. So, this factor provides a basis forconceptualization of a dimension which may beidentified as ‘market price related factor’.

Factor-VI: Legal constraint factor. Factor-VIexplains 6.41% of the total variations existingin the variable set. This includes variableX25. This factor has significant factor loadingson these variables which have formed sixthcluster. So, this factor provides a basis forconceptualization of a dimension which may beidentified as ‘legal constraint factor’.

Factor-VII: Residual policy factor. Factor-VII explains 6.34% of the total variations exist-ing in the variable set. This includes variablesX16 and X17. This factor has significant factorloadings on these variables which have formedseventh cluster. So, this factor provides a basisfor conceptualization of a dimension which maybe identified as ‘residual policy factor’.

Factor-VIII: Capital source factor. Factor-VIII explains 5.81% of the total variationsexisting in the variable set. This includesvariable X18. This factor has significant factorloadings on these variables which have formedeighth cluster. So, this factor provides a basisfor conceptualization of a dimension which maybe identified as ‘capital source factor’.

Factor-IX: Pattern of past dividend issuefactor. Factor-IX explains 5.4% of the totalvariations existing in the variable set. Thisincludes variables X1 and X23. This factor has

significant factor loadings on these variableswhich have formed ninth cluster. So, this factorprovides a basis for conceptualization of adimension which may be identified as ‘patternof past dividend issue factor’.

Factor-X: Signaling factor. Factor-X explains5.00% of the total variations existing in thevariable set. This includes variable X20. Thisfactor has significant factor loadings on thesevariables which have formed tenth clusters. So,this factor provides a basis for conceptualiza-tion of a dimension which may be identified as‘signaling factor’.

Finally, the rankings obtained on the basis offactor wise scores are shown in the Tab. 8.

Tab. 8: Rankings of the factors

Factor Averagescore Rank

I Clientele 1.16 10II Earnings and liquidity 1.91 1III Economic related 1.59 5IV Capital market related 1.51 7V Market price related 1.85 3VI Legal constraint 1.54 6VII Residual policy 1.49 8VIII Capital source 1.47 9IX Pattern of past dividend issue 1.88 2X Signaling 1.84 4Note: Data have been compiled by the researcher.

The ranking shows that Factor-II (earningsand liquidity) is most important factor thatleads the dividend decision in Bangladesh.This factor includes variables X4 (stability ofearnings), X5 (level of current earnings), X6

(anticipated level of future earnings), X7 (asustainable change in earnings) and X12 (liquid-ity level). This implies that the managementsof a company concern about the earnings andliquidity position of the company.

The second important factor is the ‘patternof past dividend issue’ which indicates thatthe companies follow the previous trend ofdividend payment in dividend decision. Thethird important factor is ‘market price relatedfactor’ which implies that the companies takethe dividend decision to maximize the market


Capital market related factor (7)Legal constraint factor (6)Economic related factor (5)Residual policy factor (8)Capital source factor (9)

Clientele factor (10)

Pattern of pastdividend issue

factor (2)

Earningsand liquidity

factor (1)Dividenddecision

- - -

Market pricerelated factor (3)

Signallingfactor (4)

6?

6

Fig. 2: Theoretical model framework

price of share. The other important factors aresignaling factor and economic related factor.

But it is a great concern that the clienteleissue is lowest position (10th) in ranking. Thecompany has less concern about the categoriesof investors and they do not set the dividendpolicy to attract the specific group of investors.

On the basis of findings from χ2 test andfactor analysis, we have developed a theoreticalframework which is discussed below.

We have developed this model frameworkon the basis of importance of the factors indetermining the dividend decision. In the first

stage, the factors – economic related factor,legal constraint factor, capital market relatedfactor, residual policy factor, capital source fac-tor, clientele factors are considered in dividenddecision making. Then in the second stage, thecompanies follow the previous years’ pattern ofdividend payment. In the next stage, dividenddecision is made mainly on the level of earningsand liquidity. On the other hand, dividenddecision is closely related to market price ofshare. The market price of share is influencedby the signaling impact of dividend payment.

5 CONCLUSION

This study presents the factors of dividenddecision which are considered before takingdividend policy. The companies mainly considerthe current earnings and liquidity position ofthe company for dividend decision. They alsomaintain to follow the pattern of previous yearsdividend payment and stable dividend payoutratio. The findings support the findings of Bakeret al. (1985), Baker (2009), Baker and Powell(2000), Deshmukh et al. (2013), Mizuno (2007),Khan et al. (2011a) and Alshammari (2012).

The broad literature on dividend payoutstrategy the US or European listed firms.But this research tries to observe whether thechosen factors have momentous roles to identify

dividend payout policy for manufacturing firmslisted in DSE or not. The result can beuseful to other industries and have suitablerecommendation for the managers.

Even though the paper uses a thorough paneldata analysis for determining the variableseffect payout policy, the existing factors andthe number of samples entities can be furtherextended to other industries listed in the DSEand CSE in Bangladesh and can have newviewpoint to determine key determinants ofdividend payout policy. Also, investigating theimpact of other variables such as size of thefirm, degree of leverage (both operating andfinancial), market risk and regulation may have


fascinating recommendations for policy makers.Thus, it requires profound analysis of DSElisted firms to decide what factors, in exact,have considerable roles and can be compre-hensive for further study. In addition to that,the study conducted by using primary surveydata from received from the chief financialofficers of the selected firms and statistically an-alyzed. The primary data will more inclusivelyreveals the determinants of listed company’spayout policy to their shareholders rather thansecondary data which examine the variationof high or low dividend payout. Finally, theresearch did not include service, financial andforeign firms listed at DSE, this implies thatthe findings can only be generalized to firmssimilar to those who participated to the researchand not fully reflected the dividend policy to alllisted firms at DSE.

The outcome and the investigation haverevealed some additional insights which needto be analyzed in future research. More firmrelated variables/factors than the ones incorpo-rated in the research should have an impact onthe payout rate. Hence it would be fascinatingto carry out a similar research with diverse com-pany chosen factors. For example the impactsof firm’s age, business risk, ownership status,tax policy and structure formation on payoutspolicy. On the basis of the practical result inthis study, it can be concluded that further re-lated research would be desirable; further studyincluding dividend paying and nondividendpaying firm using other a regression techniquessuch as Tobit and Probit models to observethe determinant variables of dividend paymentdecisions of the manufacturing industry listedat DSE with using primary data from interviewand questionnaires approach.

6 REFERENCES

Abor, J. and Fiador, V. 2013. Does CorporateGovernance Explain Dividend Policy in Sub-Saharan Africa? International Journal of Law andManagement, 55 (3), 201–225.

Adeyemi, S. L. and Adewale, A. A. 2010. Evaluationof the Dividend Practices among Selected NigerianQuoted Firms. Maiduguri Journal of Accountancyand Finance, 8 (1).

Adhikari, B. K. 2013. Peer Influence on DividendPolicies. Presented at the 2013 FMA Meetings.

Al-Malkawi, H.-A. N. 2007. Determinants ofCorporate Dividend Policy in Jordan: AnApplication of the Tobit Model. Journal ofEconomic and Administrative Sciences, 23 (2),44–70.

Alshammari, T. Dividend Policies in Kuwait. InProceedings of the Las Vegas InternationalAcademic Conference, pp. 356–361.

Anil, K. and Kapoor, S. 2008. Determinants ofDividend Payout Ratios: A Study of IndianInformation Technology Sector. InternationalResearch Journal of Finance and Economics, 15,55–63.

Archbold, S. and Vieira, E. F. S. 2010. CorporateDividend Policies in Bank-based and Market-basedSystems: Survey Evidence from UK and Portugal.Portuguese Journal of Management Studies,15 (1), 35–64.

Asghar, M., Shah, S. Z. A., Hamid, K. and Suleman,M. T. 2011. Impact of Dividend Policy on StockPrice Risk: Empirical Evidence from Equity Marketof Pakistan. Far East Journal of Psychology andBusiness, 4 (1), 45–52.

Baker, H. K. 2009. Dividends and Dividend Policy.John Wiley and Sons.

Baker, H. K., Dutta, S. and Saadi, S. 2011.Management Views on Real Options in CapitalBudgeting. Journal of Applied Finance, 21 (1),18–29.

Baker, H. K., Farrelly, G. E. and Edelman, R. B.1985. A Survey of Management Views on DividendPolicy. Financial Management, 14 (3), 78–84.

Baker, H. K., Mukherjee, T. K. and Paskelian,O. G. 2006. How Norwegian Managers ViewDividend Policy. Global Finance Journal, 17 (1),155–176.

Baker, H. K. and Nofsinger, J. R. (eds.). 2010.Behavioral Finance: Investors, Corporations, andMarkets. John Wiley and Sons.

Baker, H. K. and Powell, G. E. 1999. How CorporateManagers View Dividend Policy. Quarterly Journalof Business and Economics, 38 (2), 17–35.

Baker, H. K. and Powell, G. E. 2000. Determinantsof Corporate Dividend Policy: A Survey of NYSEfirms. Financial Practice and Education, 10, 29–40.


Baker, H. K. and Powell, G. E. 2012. DividendPolicy in Indonesia: Survey Evidence fromExecutives. Journal of Asia Business Studies,6 (1), 79–92.

Baker, H. K., Powell, G. E. and Veit, E. T. 2002.Revisiting the Dividend Puzzle: Do All of thePieces Now Fit? Review of Financial Economics,11 (4), 241–261.

Baker, M. and Wurgler, J. 2002. Market Timingand Capital Structure. The Journal of Finance,57 (1), 1–32.

Basnet, S. K. 2007. Dividend, Earnings and StockPrices: A Case of Nepal. PhD Dissertation,Tribhuvan University, Kathmandu.

Black, F. 1976a. The Dividend Puzzle. Journal ofPortfolio Management, 2 (2), 5–8.

Black, F. 1976b. Studies of Stock Price VolatilityChanges. In Proceedings of the 1976 Meeting ofthe Business and Economic Statistics Section,pp. 177–181.

Brav, A., Graham, J. R., Harvey, C. R. andMichaely, R. 2005. Payout Policy in the 21stCentury. Journal of Financial Economics, 77 (3),483–527.

Cattell, R. B. 1966. The Scree Test for the Numberof Factors. Multivariate Behavioral Research, 1 (2),245–276.

Chiang, K., Frankfurter, G. M., Kosedag, A. andWood, B. G. 2006. The Perception of Dividendsby Professional Investors. Managerial Finance,32 (1), 60–81.

Dalmácio, F. Z. and Corrar, L. J. 2007. Aconcentração do controle acionário e a política dedividendos das empresas listadas na Bovespa: umaabordagem exploratória à luz da teoria de agência.Revista de Contabilidade e Organizações, 1 (1),16–29.

Deshmukh, S., Goel, A. M. and Howe, K. M. 2013.CEO Overconfidence and Dividend Policy. Journalof Financial Intermediation, 22 (3), 440–463.

Dhanani, A. 2005. Corporate Dividend Policy: TheViews of British Financial Managers. Journalof Business Finance and Accounting, 32 (7–8),1625–1672.

Fama, E. F. and Babiak, H. 1968. Dividend Policy:An Empirical Analysis. Journal of the AmericanStatistical Association, 63 (324), 1132–1161.

Gill, A., Biger, N. and Mathur, N. 2012.Determinants of Equity Share Prices: Evidencefrom American Firms. International ResearchJournal of Finance and Economics, 90, 176–192.

Glen, J. D., Karmokolias, Y., Miller, R. R. andShah, S. 1995. Dividend Policy and Behavior inEmerging Markets: To Pay or Not to Pay. IFCDiscussion Paper No. 26.

Haleem, F., Ijaz-ur-Rehman and Javid, A. Y. 2011.The Dividend Policy in Manufacturing Sector ofPakistan: The Perception of Corporate Managers.Journal of Economics and Behavioral Studies,3 (1), 63–75.

John, A. O. 2018. Managers’ Perception of FactorsInfluencing Dividends Decision in Nigeria.International Journal of Advances in Managementand Economics, 2 (2), 135–140.

Kania, S. L. and Bacon, F. W. 2005. What FactorsMotivate the Corporate Dividend Decision?ASBBS E-Journal, 1 (1), 97–107.

Khan, K. I., Aamir, M., Qayyum, A., Nasir, A.and Khan, M. I. 2011a. Can Dividend DecisionsAffect the Stock Prices: A Case of Dividend PayingCompanies of KSE. International Research Journalof Finance and Economics, 76, 69–74.

Khan, N. U., Burton, B. M. and Power, D. M.2011b. Managerial Views About Dividend Policyin Pakistan. Managerial Finance, 37 (10), 953–970.

Khurana, P. K. 1985. Corporate Dividend Policy inIndia. Panchsheel Publishers.

Lintner, J. 1956. Distribution of Incomes ofCorporations Among Dividends, RetainedEarnings, and Taxes. The American EconomicReview, 46 (2), 97–113.

Manandhar, K. D. 2002. Corporate DividendPolicy and Practice in Nepal. PhD Dissertation,Tribhuvan University, Kathmandu.

Miller, M. H. and Modigliani, F. 1961. DividendPolicy, Growth, and the Valuation of Shares. TheJournal of Business, 34 (4), 411–433.

Mizuno, M. 2007. Payout Policy of Japanese Firms:Analysis on the Survey of Four Industries Listedon the Tokyo Stock Exchange. Pacific EconomicReview, 12 (5), 631–650.

Naser, K., Nuseibeh, R. and Rashed, W. 2013.Managers’ Perception of Dividend Policy: Evidencefrom Companies Listed on Abu Dhabi SecuritiesExchange. Issues in Business Management andEconomics, 1 (1), 1–12.

Partington, G. H. 1989. Variables InfluencingDividend Policy in Australia: Survey Results.Journal of Business Finance and Accounting,16 (2), 165–182.

Pradhan, R. S. and Adhikari, N. 2003. A Surveyof Dividend Policy and Practices of NepaleseEnterprises. In Pradhan, R. S. Research inNepalese Finance, pp. 220–250. Buddha AcademicPub.

Ross, S. A., Westerfield, R. and Jordan, B. D.2008. Fundamentals of Corporate Finance. TataMcGraw-Hill Education.


Shah, S. Z. A., Yuan, H. and Zafar, N. 2010. EarningsManagement and Dividend Policy: An EmpiricalComparison between Pakistani Listed Companiesand Chinese Listed Companies. InternationalResearch Journal of Finance and Economics, 35,51–60.

Vieira, E. F. S. 2011a. Investor Sentiment and theMarket Reaction to Dividend News: EuropeanEvidence. Managerial Finance, 37 (12), 1213–1245.

Vieira, E. F. S. 2011b. Firm-Specific Factors andthe Market Reaction to Dividend ChangeAnnouncements: Evidence from Europe. MarmaraJournal of European Studies, 19 (1), 1–25.

AUTHOR’S ADDRESSMohammad Shahidul Islam, Department of Business Administration, BGMEA University ofFashion & Technology (BUFT), Nishatnagar, Turag, Dhaka-1230, e-mail:[email protected]

ATM Adnan, Department of Business Administration, BGMEA University of Fashion &Technology (BUFT), Nishatnagar, Turag, Dhaka-1230, e-mail: [email protected]


www.ejobsat.com

DIFFERENCES OF DIVERSITYATTITUDES BETWEEN EMPLOYEESWITH AND WITHOUT AN IMMIGRATIONBACKGROUND: THE CASE OF GERMANYPetia Genkova1, Pia Keysers11Osnabrück University of Applied Sciences, Germany

GENKOVA, Petia, and KEYSERS, Pia. 2018. Differences of Diversity Attitudes between Employees with andwithout an Immigration Background: The Case of Germany. European Journal of Business Science andTechnology, 4 (2): 174–186. ISSN 2336-6494, DOI http://dx.doi.org/10.11118/ejobsat.v4i2.115.

ABSTRACT

The demographic shift in the age structure has the effects that many ageing employees work inorganisations. Migration can slow down the ageing of population but could not stop it. Moreand more people with immigration background work in organisations. Therefore, the questionis whether diversity sensitive attitudes count for all diversity aspects. The central aim of thestudy is to deal with the problem fields of multicultural teamwork. Thereby, the focus is onthe collaboration of employees with and without immigration background. The interviews withemployees with and without an immigration background of various company branches wereconducted. The results show that employees with an immigration background have more contactand feel comfortable with persons from different cultures than employees without an immigrationbackground. The qualitative analysis indicates that there is a high need of competence develop-ment, especially intercultural and social competences in organisations. The results of the studyreveal that personality traits and characteristics of employees play a role to what extent theyaccept diversity and are willing to work with persons from another culture. Age is not importantregarding intercultural competence development.

KEY WORDS

diversity attitudes, multicultural teamwork, migration

JEL CODES

O15

1 INTRODUCTION

The demographic trend of Europe had changedtremendous in the last decades. New challengeshave arisen – started from an ageing population

to an intensive immigration. Especially Ger-many is concerned by this development. Ageingpeople define increasingly the social image in

Differences of Diversity Attitudes between Employees with and without an Immigration … 175

Europe. More than 127 million people are over60 years old in Europe. This represents a popu-lation share of 25% (German Federal StatisticalOffice, 2016). The demographical change isfarthest advanced in Germany, compared toother European countries (German FederalStatistical Office, 2016). Based on demographicchanges and the high number of immigrationin the years of 2015 and 2016, the society isgetting more and more cultural heterogeneousin Europe (German Federal Statistical Office,2016).

This trends changed the attitudes towardsdiversity significantly. Thus, the interest inthe issue diversity by politics, societies andorganisations has risen greatly in the last years.Diversity has become a more important topicin Germany as well as in other Europeancountries. Women as well as people with animmigration background and ageing employeesgain more importance at the labour market.For one thing the demographic change is achallenge for organisations. For the other thingit provides an opportunity for groups like

ageing people and people with an immigrationbackground (German Federal Statistical Office,2016). Diverse teams in organisations are oneof the consequences of the demographic change(Kunze and Goecke, 2016).

Migration is not only a challenge for or-ganisations and societies, but generate newopportunities for the social progress, economicproductivity and innovative capability throughheterogeneity and diversity (Pitts, 2009). Re-search shows that a diverse workplace improvesthe satisfaction and compliance of employeesas well as the performance and communicationin teams (Pitts, 2009). However, the researchhad shown that diversity is primarily associ-ated with stress and difficulties but less withthe positive opportunities for innovation anddevelopment.

The demand for qualified professionals willfurther increase in the next years. Women,ageing employees and employees with an immi-gration background are getting more importantfor companies to counteract the demographicalchanges (Adenauer, 2015).

2 DIVERSITY ATTITUDES

Diversity in organisations support the build-ing of personnel diversity (Becker, 2006) anddescribes the commonalities and differences ofpeople (Krell, 2003). Diversity indicates boththe obvious and barely perceived and salientcharacters like for example age, religion, sexualorientation, cultural values as well as barelyobviously changing characters like language andcompetence (Miliken and Martin, 1996).

Diversity Management includes the values ofequal opportunity and fairness. It contributessignificantly to the expectations of employeesregarding the respect of different individualsthat can be satisfied by the company (Magoshiand Chang, 2009). When employees have thefeeling of equal opportunity and fair treatment,the fluctuation can be reduced (Chrobot-Masonand Aramovich, 2013).

The presentation of diversity within theorganisation has an impact on how employeesand leaders accept diversity guidelines. This

perception affects the performance of employ-ees and, therefore, the business performance(Groeneveld and Verbeek, 2012; Nishii et al.,2008). It is important that diversity actions arein accordance with the corporate culture andthe business model. This means that diversityactions should fit to the organisation and donot feel like foreign matter. Research had shownthat diversity management is only successfulif it was implemented as a top-down-process.Therefore, it is important that the leadership aswell as every company level support diversity.The success of diversity depends highly onwhether and to what extent leaders support theprocess and are a role model for their employees(Groeneveld and Verbeek, 2012; Nishii et al.,2008). Cultural diversity remains to be one ofthe hardest challenges even if every organisationis already grappling with gender mainstreamand elderly staff. Hereby considerably moreproblems and conflicts are expected than with

176 Petia Genkova and Pia Keysers

the integration of women and elderly staff intoestablished working processes. The implemen-tation of cultural diversity requires especiallyculturally sensitive actions, a complex culturalenvironment as well as intercultural compe-tences and diversity management (Lanfranchi,2013).

Cultural diversity can set impulses in anumber of society areas, economic sectors andareas of life. Nevertheless, the research showsthat individuals can see diversity as a threat(van Knippenberg et al., 2013).

Diversity can be enriching for organisationsand individuals, when they engage in perspec-tive change (Page, 2007). Studies have shownthat people with pro-diversity beliefs describegroups as good, precisely by the fact that thatgroups are diverse. This accords to the socialidentity. People with a pro-diversity belief iden-tify themselves stronger with the group (vanDick et al., 2008). Wolf and van Dick (2008)pointed out in their study, that people, who seemigrants as enrichment, have more contacts tothem and express less xenophobia, compared tothose, who do not see migrants as enrichmentfor the society. Stegman (2011) illustrated in hisMeta-Analysis that pro-diversity beliefs as wellas a positive diversity culture result in beneficialresults for groups and individuals and increasethe job performance.

Diversity Management includes the values ofequal opportunity and fairness. It contributessignificantly to the expectations of employeesregarding the respect of different individualsthat can be satisfied by the company (Magoshiand Chang, 2009). When employees have thefeeling of equal opportunity and fair treatment,the fluctuation can be reduced (Chrobot-Masonand Aramovich, 2013).

The development of diversity in organisationsreduces the fluctuation rate of employees. As aresult, costs for organisations will be reduced(Armstrong et al., 2010; Roland Berger Study,2012; Evans, 2014). Furthermore, the produc-tivity as well as the innovation capability ofemployees increase when organisations developthe individual competences of their employees(Evans, 2014; Armstrong et al., 2010). A diverseteam has a positive impact on new aspects and

ideas of employees. The diversity and differ-ences of competences produces new approachesfor problem solving as well as suggestions forimprovement (Pitts, 2009).

Which parameter do promote and supportdiversity? Are there difference in handling withdiversity?

Appropriate knowledge, intercultural abili-ties and competences have to be generatedand transferred to implement a successful di-versity management. The culture-comparativeand intercultural research shows (Berry et al.,2012; Genkova, 2012; Segall et al., 1999) thatculturally conditioned fault lines can arise basedon cultural differences, especially, in connectionwith acculturation processes or forms of eco-nomic cooperation (Asbrock et al., 2012; Homanet al., 2007).

Studies have shown that acculturative indi-viduals can adapt better to the society andprefer to keep their own origin culture andintegrate in the bigger national society. Thus,they prefer to connect both cultures. Mostcountries have introduced multicultural rulesand guidelines for integration, which includeonly assimilation, segregation or marginaliza-tion, instead of integration (Berry et al., 2011).

The perception of intergroup difference is animportant influence factor in culturally diversesocieties. This is examined inter alia by vanOsch and Breugelmans (2012). They analysedthe perceived group difference as organisationalprinciple of intercultural attitudes and accul-turation attitudes.

Minority groups, who were perceived asbeing more different from themselves by themajority members, received less support formulticulturalism. Furthermore, they were seenas a threat and less competent by the majoritygroup.

Majority members assumed that minoritygroups did not want to adapt the culture of themajority group to maintain their own ethnicalculture.

Minorities, who perceived themselves as dif-ferent to the majority group, could betteradapt to multiculturalism. They adopted themainstream culture less and maintained theirown culture more. Van Osch and Breugelmans


(2012) showed that intergroup differences arean important aspect of intergroup relationshipsin culturally diverse societies.

Diversity can also lead to rejection by indi-viduals. This demarcation attitude can lead tothe fact that diversity is perceived as threatand stress, not only by employees with animmigration background but also by employeeswithout an immigration background.

Stereotypes and prejudices can disturb di-verse teamwork. Negative stereotypes can re-duce the performance of group members. Theseaspects are examined by a number of studies(Stereotype Threat, cf. Blascovich et al., 2001;Stelle and Aronson, 1995). Negative stereo-types can increase the probability of internalattribution of failure (Koch et al., 2008) andcan lead to the fact that individuals dissociatefrom the domain group, which confront themwith negative stereotypes (von Hippel et al.,2005). Thereby, the experience of StereotypeThreat has direct effects on the job performanceof individuals as well as on the motivation(Martiny et al., 2013).

The research illustrates a diverse manage-ment guidance exerts positive influence onthe performance of the organisation (Talke etal., 2010; Nielsen and Nielsen, 2013; Baixauli-Soler et al., 2015). The perception of diversityclimate affects significantly the extent to whichemployees have the feeling to be themselvesat work. This encourages employees to developinnovative solutions and to identify themselveswith the organisation (Chrobot-Mason andAramovich, 2013).

Diversity has not only benefits on the individ-ual level, but also on the organisational level aswell as the team level. The implementation ofdiversity management creates a positive imageamong employees and customers. To use the po-tential of diversity, the dominant diversity hasto be organised and be consciously integratedin the particular organisation. Then, everyoneexperiences positive aspects by interculturalcooperation (Thomas, 2006; Franken, 2015).

However, in practice, it often turns out adifferent picture. One culture dominates theother. This leads to a differentiation between

non-dominant groups and dominant groups(Berry et al., 2011).

Diversity can also have a number of disad-vantages for individuals, for persons with animmigration background as well as for personswithout an immigration background. Ward(1996) examined that the acculturation processis more difficult, when the differences betweentwo cultures are larger. When the culturaldistance is too big, behavioural changes are abigger challenge for individuals because a largeramount of changes are demanded by the group,dominant or non-dominant group. However, thechange of the non-dominant group is greater.When the challenge of changing is a seriousthreat for the individual, this phenomenon iscalled acculturative stress (Ward, 1996).

Multicultural societies promote two culturalidentities and characteristics of ethno-culturalgroups and accept the contact and participationof groups in the bigger pluralistic society(Berry et al., 2011). It is the knowledge ofstereotypes about the own minority as wellas eventual discrimination by others that canlead to stress at employees with an immi-gration background (Meyer, 2003). Discrimi-nation causes a significant emotional stress ofindividuals in the stress-coping-research. ByJetten and Branscombe (2009), it is helpfulfor individuals to cope with discrimination byidentifying themselves with the minority andby emphasizing the difference between otherminorities or to the majority group (Jetten andBranscombe, 2009).

Factors like lack of autonomy, role ambiguityor stressful working conditions as well as theculture influence the stress level of employees atthe workplace (Jetten and Branscombe, 2009).These factors can have an impact on personswith an immigration background as well as onageing employees. Ageing employees are oftenunderestimated in terms of flexibility comparedto younger employees, innovative capacity andhandling with stress.

The research shows that diverse managementguidance can influence the organisation’s per-formance in a positive way and, therefore, diver-sity management is important for organisations.


3 METHODOLOGY AND DATA

This study is part of a bigger project, whichgrabbles with individual and organisationalconditions for successful diversity. Especiallythe implicit attitudes of the employees in Ger-many are examined to determine the barriers ofthe implementation of diversity.

The explicit attitude pictures that diversityis desirable in Germany. But the attitudes ofinitiating an acting show clearly that peoplerather associate stress and reserves with diver-sity. For that reason the project is constructedas a two-stage study – a qualitative surveywere conducted for generating hypothesis firstand a quantitative study was following forreviewing these hypothesis. In this article theimplicit attitudes of employees with and with-out migrant background are examined andcompared. 18 employees with an immigrationbackground and 15 employees without an immi-gration background from different organisationswere interviewed by telephone regarding theirattitude to cultural diversity, diversity andmulticultural teamwork. The questions wereasked in a direct an in an indirect way to verifythe attitudes and to generate the hypothesis ofresearch nearby reality and praxis. People ofbig organisations were asked because diversitymanagement is existing rather in big Germanorganisations. Also the number of people withmigrant background is adequate to answer theresearch questions by the own results and notin a hypothetic way.

The explorative interviews enable to presentthe backgrounds and relationships betweencultural diversity from the view of involvedemployees from different industries.

Thereby, it was analysed whether differencesbetween employees with and without an immi-gration background and between younger andageing employees exist.

The qualitative investigation is part of abig project to generate hypotheses for a quan-titative investigation and to obtain specificmeasurements for a quantitative questionnaire.Therefore explorative questions wer asked,which were answered with the interviews.

A qualitative structured interview was se-lected as survey method. It allows to un-derstand and analyse the diversity aspects ofculture and age and its challenges. Furthermore,not-considered aspects from the research canbe figured out. In this case e.g. how employeeswith and without an immigration backgroundperceive multicultural teamwork and how im-portant competences are in the present workingworld.

The anonymised interviews were analysed byapplying the quantitative content analysis byMayring (2015). Therefore, the material willbe transcribed, categorised and generalised andanalysed by Excel. The interviews were alsoanalysed by the frequency analysis with theaim to count the elements of the material andcompare their frequency with other elements(Mayring, 2015). The structured interviews donot include response categories except of someclosed items and contains predominantly openquestions. The structured interview is basedon an interview guideline, which is formulateddeductive, thus, theory-based.

The interview questions primary pertain tothe handling with cultural ambivalent situa-tions. The handling and communication withcolleagues with the same and with other cul-tural background is focused. Other questionsinquire which diversity measures are known bythe employees – here it is important to mentionthat the data collection took place only inorganisations that have diversity managementconcepts. But only the measurement of theimplementation of a concept can verify if theseconcepts are successful or not. The employeeswere also asked about challenges with diversityand the relevance of diversity to get somehints for an implicit approval or disapprovalof diversity. This shall be integrated into thequantitative study.

It is also important to evaluate the role ofmanagement and leadership for the handlingwith diversity and the assessment of the role ofpersons with immigration background for theorganisation.


The interview guideline is structured as fol-lows: The first partpart has asked the employeesabout their demographic data, e.g. age, gen-der, immigration background, business sectorsand internationality of the company. Anotherpart has related to questions about the issuesof diversity, especially equal opportunities ofpersons with an immigration background, e.g.:“What do you associate with the term diver-sity?”, “Which aspects does the term diversityinclude in your opinion?”.

Furthermore, the employees were asked aboutthe issue prejudices, discrimination and multi-cultural teamwork. The employees were askedwhether discrimination exists in companies.Finally, employees with an immigration back-ground were additionally asked whether theyperceived discrimination in their private life orwork life and to which area their statementsreferred. They could answer this question vol-untarily.

The first explorative hypothesis is: Employeeswithout an immigration background see moredisadvantages in the multicultural teamworkthan employees with an immigration back-ground.

The base of the self-assessment is a Likert-scale. The closed questions were answered on a5-Point Likert Scale, 1 = strongly disagree to 5= strongly agree, by the respondents and derivefrom English-speaking questionnaires, whichwere translated into Germany by the methodof retranslation, e.g. ‘I would judge myself asbeing open to people of different cultures.’

In addition, the interview focused on the issuecompetence. Thereby, diversity competenceswere examined in detail. Another part of theinterviews was the stress level and stressors ofemployees with and without an immigrationbackground regarding diversity. Furthermore,the employees were asked about the effective-ness of diversity actions, inter alia diversityconcepts that reduce prejudices against personswith an immigration background.

The aim of the interview’s questions wereto obtain knowledge about how employees andmanagers live and promote diversity, especiallythe equal opportunities of employees withan immigration background. Furthermore, it

can be examined how effective and successfuldiversity actions are in practice. Thereby, thefocus is especially on diversity competences anddiversity attitudes of employees.

To verify hints for the second survey theclosed questions were also evaluated. Thereforethree hypotheses were tested:• Hypothesis 1: Employees with an immigra-

tion background feel more comfortable towork with people from different culturesthan employees without an immigrationbackground.

• Hypothesis 2: Employees with an immi-gration background feel more familiar indealing with persons from different culturesthan employees without an immigrationbackground.

• Hypothesis 3: Younger employees feel morefamiliar in dealing with persons from differ-ent cultures than ageing employees.

A qualitative structured interview was se-lected as survey method. It allows to un-derstand and analyse the diversity aspects ofculture and age and its challenges. Furthermore,not-considered aspects from the research canbe figured out. In this case e.g. how employeeswith and without an immigration backgroundperceive multicultural teamwork and how im-portant competences are in the present workingworld.

The anonymised interviews were analysed byapplying the quantitative content analysis byMayring (2015). Therefore, the material willbe transcribed, categorised and generalised andanalysed by Excel. The interviews were alsoanalysed by the frequency analysis with theaim to count the elements of the material andcompare their frequency with other elements(Mayring, 2015). The structured interviews donot include response categories except of someclosed items and contains predominantly openquestions. The structured interview is basedon an interview guideline, which is formulateddeductive, thus, theory-based.

The closed questions were answered on a 5-Point Likert Scale, 1 = strongly disagree to5 = strongly agree, by the respondents andderive from English-speaking questionnaires,which were translated into Germany by the


method of retranslation, e.g. “I am open topeople from different cultures”.

The interview guideline is structured asfollows. One part has asked the employeesabout their demographic data, e.g. age, gender,immigration background, business sectors, in-ternationality of the company. Another part hasrelated to questions about the issues of diver-sity, especially equal opportunities of personswith an immigration background, e.g. “Whatdo you associate with the term diversity?”,“Which aspects does the term diversity includein your opinion?”. Furthermore, the employeeswere asked about the issue prejudices, dis-crimination and multicultural teamwork. The

employees were asked whether discriminationexists in companies. Finally, employees withan immigration background were additionallyasked whether they perceived discrimination intheir private life or work life and to which areatheir statements referred. They could answerthis question voluntarily.

The sample of the qualitative investigationconsists of 18 employees with an immigrationbackground and 15 employees without an immi-gration background. Thirteen of all are femaleand 20 are male. The average age of the sampleis M = 35.48 (N = 33; SD = 9.99). Therespondents work about M = 9.29 years (N =33; SD = 9.37) in their organisations.

4 RESULTS

In the following, the results of the explorativesurvey will be presented: Employees withoutan immigration background see more disad-vantages in the multicultural teamwork thanemployees with an immigration background.

The results show that both groups recognisethe challenges of multicultural teams. However,employees without an immigration backgroundsee more disadvantages than advantages inmulticultural teams compared to employeeswith an immigration background. Accordingto the statements of both groups, particularchallenges regarding the cooperation of personswith an immigration background are potentiallanguage barriers like “especially difficulties inunderstanding different languages as problem-atic”. Different languages can lead to misun-derstandings. Employees with an immigrationbackground additionally mentioned followingproblem fields: cultural working methods andattitudes (“Well, I think that sensitivities inevery culture are different and also what isimportant for the people. There are cultures,which need very strong confirmation by oth-ers. This is what I have been experiencingThey have different hierarchical concepts.”)Employees without an immigration backgroundmentioned a different understanding of teamculture and capacity of teamwork as well associal interaction as problems in multicultural

teams. One employee without an immigrationbackground said e.g. “I believe that everyculture deals differently with a subject. Somepeople from other cultures are temperamentaland have different approaches and values.”

The results do not surprise although peoplewith immigration background are also natives.Obviously, it is a wide spread negative stereo-type to join cultural differences and divergent orinsufficient language skills. This is also reportedby people with immigration background. Peopleassume those people with immigration back-ground to have inferior languages skills even ifthis is not right.

The analysis of biculturalism of employeeswith an immigration background supports theresults of the qualitative investigation. They an-swered the closed questions on a 5-point LikertScale, 1 = strongly disagree to 5 = stronglyagree. Employees have a strong connection totheir ethnical group (N = 16; M = 3.75;SD = 1.34). Furthermore, they have a strongerconnection to their ethnical group. But mostof their friends are from Germany and theirethnical group (N = 16; M = 4.44; SD = 1.03).It is to be mentioned that the closest friendsof employees with an immigration backgrounddo not have necessarily the same culturalbackground like themselves (N = 15; M = 2.33;SD = 1.45). In this sample, the employees with


an immigration background are integrated inboth cultures and feel mostly integrated (N =18; M = 4.44; SD = 1.19).

This results are also verified in internationalresearch. The relation of acculturation andsocio-cognitive functions is tested in the studyof Tadmor et al. (2009). Bicultural personswere more integrative complex than adaptedpersons. One reason for this is that biculturalpersons have better skills and can differentiatebetween competing cultural perspectives. Theyare able to integrate themselves to adaptedindividuals and separated individuals.

Employees with an immigration backgroundlist up following aspects as difficulties inthe multicultural teamwork: social interaction,leadership, cultural conflicts, language deficits,intercultural perspective and work attitudesand different personalities. Employees with-out an immigration background point outthat intercultural interaction, personality andgenerational differences are difficulties in themulticultural teamwork.

Apart from immigration background youcan explain this behaviour with the classicallytheories of social psychology.

The theory of social identity indicates thatmembers of within groups are evaluated morefavourable than members of the foreign group.Positive successes are related to the withingroup. Negative behaviour is attributed internalto the members of foreign groups. Comparativecultural studies confirm that negative behaviouris attributed external in the within group.Negative expectations are established againstmembers of the foreign group (Hewstone, 1988).This may explain why employees without animmigration background assess multiculturalteamwork more negative and attribute theproblems to employees with an immigrationbackground.

An interesting aspect was mentioned in theinterviews. It was the issue of envy towardsemployees with an immigration background.Employees without an immigration backgroundpartly regard employees with an immigrationbackground with envy because they take theview that employees with an immigration back-

ground are preferred and get more support thanothers.

Employees without an immigration back-ground mentioned the aspect of envy as well.One employee with an immigration backgroundreasoned “envy […] is a big factor and plays ahuge role. Envy and fame as well as respectare important facts. Some people with animmigration background feel vulnerable whenother people with an immigration backgroundare around them because they felt as a uniquebefore. When other people with an immigrationbackground work with other people with animmigration background together, they feelenvy and confronted by the other people withan immigration background because they mighthave the same qualifications as them. Envy isthe biggest problem. Envy, respect and fame.”Employees without an immigration backgroundmentioned, furthermore, the aspect of feargetting in contact with employees with animmigration background. Prejudices and socialcategorisation can lead to distance betweenemployees and can have an impact on themulticultural teamwork for half of the respon-dents. Uncertainty, ignorance and fear towardsother cultures can also create distance betweenemployees because the own culture can beswamped by the other culture and can lead toloss of identity.

The concept of envy is explored in the USresearch in relation to conflicts between whiteand colored people as well as between Latin-American immigrants and native population. Itis verified with the theories of social dominance(Sidanius and Pratto, 2001) and realistic groupconflicts. Through the explorative questions itbecomes clear that the concept of envy loomslarge and so it should be considered for anexamination of the quantitative issues.

Overall the respondents were largely satisfiedwith the multicultural teamwork (N = 11;M = 4.73; SD = 0.65).

In the following, the results of the quantita-tive hypotheses are presented.

Hypothesis 1: Employees with an immigrationbackground feel more comfortable to work withpeople from different cultures than employeeswithout an immigration background.


The results do not show significant differ-ences. This is an indication that diversity isnot perceived as a threat by employees or thatthe expression of intercultural competence isvery high. This indication will be examinedin the further quantitative research. The t-testconfirmed the non-significant differences (T =1.24; df 1; 21; p = 0.068).

Hypothesis 2: Employees with an immigrationbackground feel more familiar in dealing withpersons from different cultures than employeeswithout an immigration background.

A t-test was conducted to verify this hy-pothesis. The results show high significantdifferences (Employees without an immigrationbackground M = 3.47; SD = 0.83; Employeeswith an immigration background M = 4.67;SD = 0.49; T = 5.157; df 1; 31; p = 0.000).The differences indicate that the growth ofintercultural competences is due to personnelbackground and experience. The quantitativeresults are supported by the evaluations ofthe qualitative investigation. E.g. quote of an

employee with an immigration background: “[…]people with an immigration background havegrown up at least with two cultures and differ-ent perspectives and competences. Therefore,we have a better understanding other peoplebetter.”; “People, who have not experiencedintercultural experiences, are also able to makeperspective change by their seniority. […] But Ibelieve that experience is the most importantthing in this context, e.g. experiences abroad orto know different contexts and cultures.”

Hypothesis 3: Younger employees feel morefamiliar in dealing with persons from differentcultures than ageing employees. This hypoth-esis was refuted because there is no significantdifference between both groups (T = −1.462; df1; 31; p = 0.154). The assumption that youngerpersons are more open for new experiencesand, therefore, are more flexible and unprej-udiced could not be confirmed. Interculturalcompetences are not influenced by age, but bypersonality traits.


The results show that the significance of self-awareness and exchange of experience andthe expression of intercultural competence in-creases. There are differences regarding thefamiliarity in dealing with other cultures be-tween persons with and without an immigra-tion background. Persons with an immigrationbackground have more experiences with personsfrom other cultures. They often grow up with atleast two cultures and, therefore, learned earlyto adapt to other cultures and to engage init. The qualitative investigation clarifies thatit is important for organisations to promotetheir employees and managers regarding inter-cultural competences. The age does not play arole regarding intercultural competences.

In this study it can be positively pointedout that a quite high diversification could bereached with a sample of 33 employees withand without an immigration background. Therespondents work in small, medium-sized andlarge organisations where, on the one hand,

diversity has already been implemented and,on the other hand, no diversity actions havebeen implemented. Furthermore, the employeeswere from different business areas through-out Germany. Based on the small sample,a large overview about the issue of diver-sity management could be given in Germany.Considering the importance of diversity anddiversity attitudes of employees, especially theequal opportunities of persons with an immi-gration background and ageing people, allowto analyse disregarded aspects from involvedpersons. Bigger questionnaires can build uponthe results of this qualitative study and examinethe results in detail. The interview guidelinegives a large overview of the different factorsand the importance and attitudes of diversityin companies. However, the interview guidelineshould be extended on the basis of the resultsof the study and more detailed questions shouldbe asked. Furthermore, the results should beexamined by a quantitative study.


The interview guideline has covered manyissues of diversity management. The combina-tion of closed and open questions has increasedthe comparability of the interviews comparedto interviews with only open questions. Butthe results of structured interviews are lesscomparable, inter alia based due to open ques-tions, whereby the analysis is more difficult.The results would be more comparable, if astandardised, quantitative questionnaire wasused and a higher sample could be asked. Never-theless, the results would not be so diverse andmultifaceted as with the selected interviews.The study could consider and differentiatethe problem fields and diversity attitudes ofemployees with and without an immigrationbackground in detail. The qualitative inves-tigation was predominantly used for generat-ing hypotheses. Therefore, the differences ofthe groups were only measured to generatehypotheses for a quantitative investigation. Itprovides approaches which have to be examinedin detail in subsequent studies.

The following has to be criticised regardingthe survey method: The interview guidelinedeals partly superficial with some topics of di-versity. It could have been asked more, e.g. whatkind of discrimination exist in organisations andwhich actions could help to reduce discrimina-tion? The respondents are even though from dif-ferent business areas and sizes. However, othercompanies can differentiate from the sampledue to other characteristics, e. g. size, structure,implementation of a diversity department.

It is necessary to investigate the categorysystems of the interviews regarding their qualitycriteria. The interviews of the study were usedfor generating hypotheses for a quantitativequestionnaire. Therefore, additional aspects re-garding diversity, especially equal opportunitiesof persons with an immigration background,which are represented in the conventional quan-titative research, could be measured.

The sample is evenly distributed regardingthe persons with and without an immigrationbackground. The following has to be criti-cised regarding the sample. There were morewomen than men who conducted the interview.Furthermore, the results only give approaches

regarding diversity attitudes of employees withand without an immigration background. Thereis a strong East-West gap concerning theemployment of migrants in organisations inGermany. This fact is reflected in the in-terviews. Not every respondent has been incontact with migrants in their work routine,when the interview was conducted. To get arepresentative sample, a more comprehensivesample should be made with employees inGermany. Furthermore, it should be examinedhow effective diversity actions are and towhat extent diversity concepts should takea higher priority in personnel actions. Theresults showed that the priority depends onthe business areas, size and the location of thecompany as well as the diversity of the staff.

It has to be considered, whether the an-swers were given due to social desirabilityor deliberate misrepresentation because thesurvey method was an interview. Some of thequestions have been very personal and referredto perceived discrimination of employees withan immigration background in working and inprivate life. According to the statements of em-ployees, around one third of the employees withan immigration background have perceived dis-crimination in their private life. The discrimina-tion referred to outward appearances and theirorigin culture. The interviewed employees withan immigration background have not perceiveddiscrimination in their work life according to theresults of the qualitative investigation. Groupspecific development concepts help to reducediscrimination in companies according to theresults.

The data of the interviews were anonymised.Therefore, the effects of social desirability couldbe minimised but it could still occur due to thesocial interaction during the interviews. Thiscould lead to a distortion of the results becausee.g. the individual responsibility or the skills ofthe own person were presented more positive.Therefore, the results have to be discussedcritically. A deliberate misrepresentation can beexcluded because the respondents participatedvoluntarily at the interview and did not have toexpect any negative effects due to giving specificstatements.


The qualitative results show a tendency toregional differences regarding the importance ofdiversity and that diversity attitudes of employ-ees exist. The results can occur to what extentemployees are grown up in a multiculturalcontext and how open the environment is. Prej-udices against persons from another culture canbe partly reduced by implementing diversityconcepts. The results of the interviews indicatethat such concepts are generation-dependentand location-dependent. The younger genera-tion grows up in a multicultural society inGermany and in Europe. Therefore, they bringcertain intercultural competences into theirwork life. Diversity plays a more important rolefor organisations. But there can be the risk ofnegative connotation. The interviews showedthat in the western part of Germany, e.g. in theRuhr area, such a diversity concept for equalopportunities of migrants would be superfluous

because there is a high proportion of migrantsand it is normal to work with different culturestogether.

In summary, there is a high demand of com-petence development, especially regarding in-tercultural competence and social competence.Social competence facilitates the collaborationwith persons with an immigration backgroundand employees learn to experience a changeof perspective. The results of the study showthat personality traits and characteristics ofemployees play a role to what extent employeesaccept diversity and are willing to work withpersons from another culture. Age does not playa role regarding intercultural competence devel-opment. This means for organisations to offertrainings and seminars for the issues of culture,stereotypes and intercultural competences andto support as well as experience abroad andforeign assignment.

6 REFERENCES

Adenauer, S. 2015. Leistungsfähigkeit im Betrieb.In Adenauer, S. (ed.). Kompendium fürden Betriebspraktiker zur Bewältigung desdemografischen Wandels. Wiesbaden: Springer,pp. 9–25.

Armstrong, C., Flood, P. C., Guthrie, J. P.,Liu, W., MacCurtain, S. and Mkamwa, T. 2010.The Impact of Diversity and Equality Managementon Firm Performance: Beyond High PerformanceWork Systems. Human Resource Management,49 (6), 977–998.

Asbrock, F., Christ, O., Duckitt, J. and Sibley,C. G. 2012. Differential Effects of IntergroupContact for Authoritarians and Social Dominators:A Dual Process Model Perspective. Personalityand Social Psychology Bulletin, 38 (4), 477–490.

Baixauli-Soler, J. S., Belda-Ruiz, M. and Sanchez-Marin, G. 2015. Executive Stock Options, GenderDiversity in the Top Management Team, and FirmRisk Taking. Journal of Business Research, 68 (2),451–463.

Becker, M. 2006. WissenschaftstheoretischeGrundlagen des Diversity Management.In Becker, M. and Seidel, A. DiversityManagement – Unternehmens- und Personalpolitikder Vielfalt. Stuttgart: Poeschel, pp. 3–48.

Berry, J. B., Poortinga, Y. H., Breugelmans, S. M.,Chasiotis, A. and Sam, D. L. 2011. Cross-CulturalPsychology: Research and Applications. New York:Cambridge University Press.

Berry, J. W., Poortinga, Y. H., Segall, M. H. andDasen, P. R. 2012. Cross-Cultural Psychology.Research and Applications. 3rd Edition.Cambridge: University Press.

Blascovich, J., Spencer, S. J., Quinn, D. andSteele, C. 2001. African Americans and HighBlood Pressure: The Role of Stereotype Threat.Psychological Science, 12 (3), 225–229.

Chrobot-Mason, D. and Aramovich, N. P. 2013. ThePsychological Benefits of Creating an AffirmingClimate for Workplace Diversity. Group andOrganization Management, 38 (6), 659–689.

Evans, C. 2014. Diversity Management andOrganizational Change. Equality, Diversity andInclusion: An International Journal, 33 (6),482–493.

Franken, S. 2015. Personal: Diversity Management.6th ed. Wiesbaden: Gabler.

Genkova, P. 2012. Lehrbuch KulturvergleichendePsychologie: Ein Forschungsleitfaden. Wiesbaden:Springer.


German Federal Statistical Office. 2016.Ältere Menschen in Deutschlandund der EU [online]. Available at:https://www.destatis.de/DE/Publikationen/Thematisch/Bevoelkerung/Bevoelkerungsstand/BroschuereAeltereMenschen0010020169004.pdf?__blob=publicationFile. [Accessed 2018,February 6].

Groeneveld, S. and Verbeek, S. 2012. DiversityPolicies in Public and Private Sector Organizations.An Empirical Comparison of Incidence andEffectiveness. Review of Public PersonnelAdministration, 32, 353–381.

Hewstone, M. 1988. Attributional Basis of IntergroupConflict. In Stroebe, W., Kruglanski, A. W.,Bar-Tal, D. and Hewstone, M. (eds.). TheSocial Psychology of Intergroup Conflict. Berlin:Springer, pp. 47–71.

Homan, A. C., van Knippenberg, D., Van Kleef,G. A. and De Dreu, C. K. W. 2007. BridgingFaultlines by Valuing Diversity: Diversity Beliefs,Information Elaboration, and Performancein Diverse Work Groups. Journal of AppliedPsychology, 92 (5), 1189–1199.

Jetten, J. and Branscombe, N. R. 2009. Minority-Group Identification: Reponses to Discriminationwhen Group Membership is Controllable. InButera, F. and Levine, J. L. (eds.). Coping withMinority Status. Cambridge University Press,pp. 155–176.

Koch, S., Müller, S. and Sieverding, M. 2008.Women and Computers: Effects of StereotypeThreat on Attribution of Failure. Computers andEducation, 51 (4), 1795–1803.

Krell, G. 2003. Personelle Vielfalt in Organisationenals Herausforderung für die Praxis. InWächter, H., Vedder, G. and Führing, M.(eds.). Personelle Vielfalt in Organisationen.München: Hampp, pp. 219–232.

Kunze, F. and Goecke, T. 2016. Altersdiversitätals Organisationskompetenz: Chancen undHerausforderungen. In Genkova, P. andRingeisen, T. (eds.). Handbuch DiversityKompetenz. Band 2: Gegenstandsbereiche.Wiesbaden: Springer, pp. 183–196.

Lanfranchi, A. 2013. Interkulturelle Kompetenzals Element pädagogischer Professionalität-Schlussfolgerungen für die Lehrerausbildung. InAuernheimer, G. (ed.). Interkulturelle Kompetenzund pädagogische Professionalität. Wiesbaden: VSVerlag für Sozialwissenschaften, pp. 231–260.

Magoshi, E. and Chang, E. 2009. DiversityManagement and the Effects on Employees’Organizational Commitment: Evidence from Japanand Korea. Journal of World Business, 44 (1),31–40.

Martiny, S. E., Götz, T. and Keller, M. 2013.Emotionsregulation im Kontext von StereotypenThreat: Die Reduzierung der Effekte negativerStereotype bei ethnischen Minderheiten. InGenkova, P. and Ringeisen, T. (eds.).Handbuch Stress und Kultur: Interkulturelle undkulturvergleichende Perspektiven. Wiesbaden:Springer, pp. 397–416.

Mayring, P. 2015. Qualitative Inhaltsanalyse:Grundlagen und Techniken. 12th ed. Weinheim:Beltz.

Meyer, I. H. 2003. Prejudice, Social Stress, andMental Health in Lesbian, Gay, and BisexualPopulations: Conceptual Issues and ResearchEvidence. Psychological Bulletin, 129 (5), 674–697.

Miliken, F. J. and Martin, L. L. 1996. Searching forCommon Threads: Understanding the MultipleEffects of Diversity in Organizational Groups.Academy of Management, 21 (2), 402–433.

Nielsen, B. B. and Nielsen, S. 2013. Top ManagementTeam Nationality Diversity and Firm Performance:A Multilevel Study. Strategic ManagementJournal, 34 (3), 373–382.

Nishii, L. H., Lepak, D. P. and Schneider, B. 2008.Employee Attributions of the “Why” of HRPractices: Their Effects on Employee Attitudes andBehaviors, and Customer Satisfaction. PersonnelPsychology, 61, 503–545.

Page, S. E. 2007. The Difference: How the Power ofDiversity Creates Better Groups, Firms, Schools,and Societies. Princeton: Princeton UniversityPress.

Pitts, D. 2009. Diversity Management, JobSatisfaction, and Performance: Evidence from USFederal Agencies. Public Administration Review,69 (2), 328–338.

Roland Berger. 2012. Diversity and Inclusion:Eine betriebswirtschaftliche Investition [online].Available at: http://www.cssa-wiesbaden.de/fileadmin/Dokumente/Demografischer_Wandel/Dokumente/Diversity/Diversity_and_Inclusion_Roland_Berger_D_20120716.pdf. [Accessed 2017,November 20].

Segall, M. H., Dasen, P. R., Berry, J. W. andPoortinga, Y. H. 1999. Human Behavior in GlobalPerspective: An Introduction to Cross-CulturalPsychology. Boston: Allyn and Bacon.

Sidanius, J. and Pratto, F. 2001. Social Dominance:An Intergroup Theory of Social Hierarchy andOppression. Cambridge: Cambridge UniversityPress.

Steele, C. and Aronson, J. 1995. Stereotype Threatand the Intellectual Test Performance of AfricanAmericans. Journal of Personality and SocialPsychology, 69 (5), 797–811.


Stegmann, S. 2011. Engaging with Diversityof Social Units – A Social IdentityPerspective on Diversity in Organizations[online]. Doctoral Dissertation. GoetheUniversity, Frankfurt am Main. Available at:http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hebis:30-111582. [Accessed 2018,February 6].

Tadmor, C. T., Tetlock, P. E. and Peng, K.2009. Acculturation Strategies and IntegrativeComplexity: The Cognitive Implications ofBiculturalism. Journal of Cross-CulturalPsychology, 40 (1), 105–139.

Talke, K., Salomo, S. and Rost, K. 2010. HowTop Management Team Diversity AffectsInnovativeness and Performance via the StrategicChoice to Focus on Innovation Fields. ResearchPolicy, 39 (7), 907–918.

Thomas, A. 2006. An Action- and Learning-Theoretical Concept of Intercultural Competence.In Helfrich, H., Zillekens, M. and Hölter, E.(eds.). Culture and Development in Japan andGermany. Münster: Daedalus Verlag, pp. 191–216.

van Dick, R., van Knippenberg, D., Hägele, S.,Guillaume, Y. R. F. and Brodbeck, F. C. 2008.Group Diversity and Group Identification: TheModerating Role of Diversity Beliefs. HumanRelations, 61 (10), 1463–1492.

van Knippenberg, D., van Ginkel, W. P. andHoman, A. C. 2013. Diversity Mindsets and thePerfomance of Diverse Teams. OrganizationalBehavior and Human Decision Processes, 121 (2),183–193.

van Osch, Y. M. J. and Breugelmans, S. M.2012. Perceived Intergroup Difference as anOrganizing Principle of Intercultural Attitudes andAcculturation Attitudes. Journal of Cross-CulturalPsychology, 43 (5), 801–821.

von Hippel, W., von Hippel, C., Conway,L., Preacher, K. J., Schooler, J. W. andRadvansky, G. A. 2005. Coping with StereotypeThreat: Denial as an Impression ManagementStrategy. Journal of Personality and SocialPsychology, 89 (1), 22–35.

Ward, C. 1996. Acculturation. In Landis, D. andBhagat, R. S. (eds.). Handbook of InterculturalTraining. 2nd ed. Thousand Oaks, CA: Sage,pp. 124–147.

Wolf, C. and van Dick, R. 2008. Wenn andersnicht schlechter bedeutet – Wertschätzung vonVielfalt fördert Gleichwertigkeit der Gruppen.In Heitmeyer, W. (ed.). Deutsche Zustände.Frankfurt: Suhrkamp, pp. 137–153.

AUTHOR’S ADDRESSPetia Genkova, Faculty of Business Management and Social Sciences Economics, OsnabrückUniversity of Applied Sciences, Caprivistr. 30 A, 49076 Osnabrück, Germany, e-mail:[email protected]

Pia Keysers, Faculty of Business Management and Social Sciences Economics, OsnabrückUniversity of Applied Sciences, Caprivistr. 30 A, 49076 Osnabrück, Germany, e-mail:[email protected]


www.ejobsat.com

CYBERSEXUAL HARASSMENT ASICTS DEVELOPMENT CONSEQUENCES:A REVIEWJūratė Kuklytė11Vytautas Magnus University, Kaunas, Lithuania

KUKLYTĖ, Jūratė. 2018. Cybersexual Harassment as ICTs Development Consequences: A Review. EuropeanJournal of Business Science and Technology, 4 (2): 187–195. ISSN 2336-6494,DOI http://dx.doi.org/10.11118/ejobsat.v4i2.137.

ABSTRACT

Rapid progress of information and communication technologies (ICTs) affected the evolution ofsexual harassment. Cybersexual harassment can be exposed via social media but as well might be atool for harassers to attack or stalk individuals after anonysmously. This evolution of phenomenonenter to virtual reality require changes in differenr levels: individual, enterprise and state tocounter the hybrid threats. The proposed conceptual framework reflects the main vulnerablegroups, consequences. These main aspects trigger for the development of ICTs in order to changeorganizational policies, political and security regulations.

KEY WORDS

cybersexual harassment, cyberbullying, cybercrime, hybrid threats

JEL CODES

M1, D8, D74

1 INTRODUCTION

A rise of social media and networking hasmade faster access to information and engage tocommunicate through tweet, post, Instagram,sharing various content on Facebook, makingTumblr blogs or Youtube videos. Individualshave the voice to tell their story in a mas-sive scale via different mobile applications bymaking digital messages more personal andintimate. Also and broadcast specific momentslive.

However, the viral spread of informationleads to power imbalance of specific individ-uals who are targeted against social normsand express revolutionary ideas, attitudes andinsights. The scholars highlighted that thereis a need of cybersexual harassment preven-tion among adolescence (Pereira et al., 2016)and university students (Moafa et al., 2018).Mainiero and Jones (2013) develop new com-munication ethics in order to prevent work-

188 Jūratė Kuklytė

place romances that may subsequently turninto workplace sexual harassment through theuse of social networks and other forms ofdigital communication between employees. Theinterest among academicians is growing. Kuemet al. (2017) tested what different aspectswhich may have significant effect and maylead to prosocial behaviour in social networkingservices. Misbehaviour in social networks hasgained public attention and encourage to reportof cybersexual harassment to legal instutitions.

Furthermore, cybersexual harassment, in-cluding cyber-porn, obscenity, sharing sexuallyexpressive illegal content or activities, areidentified as a cybercrime (Holt, 2018). Theseactions play a key role to digital diplomacy.According to Surma (2016) international con-flicts may be started by using “Factories of

Trolls” in order to use provocation strategy tomanipulate public opinion of specific country.Hybrid threats are complex like cyberattacks,alienation, extortion of confidential informa-tion, cyberbullying, cybersexual harassmentand others.

This research aims to broaden the under-standing what are the major threats and conse-quences of cyber sexual harassment in differentlevels. Following the aim of this research themain attention was gained, how cybersexualharassment perception evolved and changed indifferent level. By intending to investigate a re-search gap, following questions were formulated:

RQ1: How cybersexual sexual harassmentevolve?

RQ2: What are the main vulnerable groupsand consequences in different levels?

2 BACKGROUND OF CYBERSEXUAL HARASSMENT

Sexual harassment became an important is-sue and throroughly analysed as face-to-faceactions. Interpretive way reveal multiple re-alities, which are socially constructed by dif-ferent workplace environments – academia(Carstensen, 2004), military (Matheson andLyle, 2017), private sector organizations (Sar-potdar, 2013).

Moreover, hermenautical delectical analysiscould be employed based by the concept ofGramsci hegemony that social practice con-struct the actions and desires excluding per-sonal interests and values by analyzing thenature of sexual harassment and cybersexualharassment (see e.g. Hatch and Cunliffe, 2006).Dialectical perspective reveal that deviant be-haviors can be seen as mimicry. Accordingto Bhabha (1997), “mimicry emerges as therepresentation of a difference that itself aprocess of disavowal.” Also mimicry is definedas “the sign of a double articulation, a complexstrategy of reform, regulation and discipline,which “appropriates” the Other as it visualizespower”. Such complex nature is shown in someresearches. Lindberg et al. (2012) revealed thatthe Finnish adolescents who “expressed theirmassacre threats online as cybersexual harass-

ment could be considered a riskier group thanthe group who expressed the threats offline”.

Cybersexual harassment involves destruc-tive electronic means mediated communica-tion such as e-mail spoofing, stalking, cybersexual defamation, cyber flirting, hacking, cy-ber pornography, and cyberbullying. Moreover,similarities, differences and interrelationshipof cyberbullyinh and cyber sexual harass-ment were exposed. Akbulut and Eristi (2011)highlight that cyberbullying can be expressedthrough flaming, sexual harassment and stalk-ing. Also it includes verbal and visual social andrelational aggression like harassment, denigra-tion, sexting, posting embarrassing photos ormemes (Ballard and Welch, 2015). Vveinhardtand Kuklytė (2017) online misbehaviors inthree types: violent and pornographic content,threats and vulgar language, and grooming.Thus, both phenomena are tend to refer ascybercrime by having tripple nature – could beexpressed in a direct, indirect and mixed ways.Thus, extensive literature review and synthesisrequired in order to identify the targetedgroups, possible threats, and consequences indifferent levels.

Cybersexual Harassment as ICTs Development Consequences: A Review 189

3 CONCEPTUAL FRAMEWORK

The use of various social networks and onlinetechnology is increase and transform the phe-nomena of sexual harassment in various per-spectives. The provided model of cybersexualharassment aims to contribute conceptual un-derstanding what are vulnerable groups, whatcould be consequences in different level (Fig. 1).

State level showed the incidents of cybersex-ual harassment operating at digital diplomacylevel as a hybrid conflict – massive cyber at-tacks against minorities (children, adolescents,women) to cause socio-demographic problemsand influence political issues without use ofarmy force (Maurer and Janz, 2014).

Interpersonal level defines cyber sexual abuseamong non-related individuals. Innapropriatedissemination and gender discrimination mayappear among children, adolescents, studentsand virtual agents in different electronic en-vironment – social networks and video games.The main intention is to initiate and engagea video connection or face-to-face meetingwith the victim. Furthermore, the high levelanonymity and power imbalance enable longlasting destructive communication which maycause psychological damage.

Enterprise level represents analysis of em-ployees’ misbehaviour in social networks. Theseoffensive actions targeted against gender issuesare analysed as deviant behaviors in computer-mediated communication (Ritter, 2014). Cyberincivility and online sexual harassment amongemployees has been analysed by Giumetti et al.(2016), Park et al. (2018) and others. Such anextent of spread of cybersexual harassment maycause financial and non-financial damage, alsoharm the well-being of employees.

According to Lewis et al. (2017), cybersexualharassment is an extention of offline sexual vi-olence against women. Cyber-aggression amongadolescents tend to have a sexual nature regard-ing the gender such as getting an unwantedsexual message from somebody or receivingsexual request by an adult may cause social-emotional consequences (Shapka and Magh-soudi, 2017). Several researchers argued thatcybersexual harassment can adversely affect

the organization (Ritter, 2008) and has anegative professional and economic outcomesfor victims. Gamergate’s misogynist scandalhave revealed that social networking may playa key role of online abuse in conflicts thatenable to gain a public and technologicalpower (Salter, 2018). Moreover, massive attacksof cybersexual harassment messages targetedagainst minorities can be used as political toolto start hybrid or information warfare. Thus,cybersexual harassment is analysed in differentcontexts by using various keywords.

The scientific literature review enable todivide victims: women, adolescents, students,virtual agents, employees.

Tab. 1 represents cybersexual harassmentamong individuals who are not subordinated byspecific job agreements. On the other hand, onegroup of victims – university students – hasan intimate relationships with a perpetrator.These online actions affect interpersonal level.

Cybersexual harassment activities conductedin social networks during leisure time or ona daily basis may evolve to on-duty activitiesin different organizations (Maneiro and Jones,2013). Although, outcomes of individual onlinemisbehaviour may have negative impact onsocio-demographic factors.

The most vulnerable victims group is ado-lescents (Tab. 1). Malicious online activitiesmay defined as “online sexual solicitation”,“Internet-initiated offense”, and “online sexualgrooming”. Sklenarova et al. (2018) analysed2238 adolescents (14–17 years) in Germany andfound that some participants (24.7%) reportedabout online sexual experiences with peersand/or adults, 43.3% reported of exchangingpictures and 6.2% had engaged in cybersex.

Another group of victims are women. A con-siderable evidence shown that women experi-ence cybersexual harassment and interpersonalmisbehaviour is more often observed in indi-vidual level (Vitis and Gilmour, 2017; Ritter,2014; Ritter, 2008). Women tend to experienceonline misbehaviour in various environment likeblogs (Eckert, 2018), video games (Ballard andWelch, 2017) and other.


Fig. 1: The model of cybersexual harassment in different level

Less common online misbehaviour is virtualrape in a two or three dimentional environment.The first virtual rape case LambdaMOO wasdiscussed in 1992. Spence (2012, p. 125) arguedthat “an avatar as virtual representation of anindividual in reality can and must be perceivedas a virtual purposive agent that have moralrights and obligations similar to those of theirreal counterparts. With regard to agency thoserights are merely prima facie but with regard topersonhood framed around the notion of self-respect those rights are absolute.” Accordingto Wolfendale (2007) virtual world is based toperformative utterances and have illocutionaryforce (intentional virtual agents actions) andperlocutionary force (virtual agents have signif-icant social effect). Warren and Palmer (2010)mentioned in Australian Institute of Crimi-nology report that a female user of “SecondLife” (3D game) informed Belgian police thather avatar had been raped in May, 2007. Itis affirmed that “the rape of an avatar mayproduce some real-world physical discomfortor shock among unsuspecting or novice users”(Boellstorff, 2008). On the contrary, Fox et al.(2015) assert that virtual rape is understud-ied phenomena and claim that women’s self-objectification lead to increases of rape mythacceptance.

Enterprise level represents organizationalcontext. Online communication such as cyber-bullying among adults (Lowry et al., 2016),cyber sexual harassment (Choi and Lee, 2017)among employees during working hours can

be identified as on-duty deviance and off-duty deviance (Lyons et al., 2016). Moreover,cyber incivility through e-mail messages tendto have a double-edge sword effect (Lim andTeo, 2009). It can be illustrated by the caseof women bloggers when they response with ahumour creating memes and posts after onlineabuse (Eckert, 2018). This coping strategy isgiving the same online abuse response to theperpetrator. Thus, a victim switches the rolesand becomes a harasser.

Also online sexual aggression as an expressionof misogynistic culture after GamerGate hatespeech campaigns when female game devel-oper Zoe Quinn was receiving death threats,threats of rape, and many harassing commentsafter an accusation of her ex-boyfriend thatshe had been given sexual favors for positivegame reviews (Kaplan, 2014). Misogyny andhomophobia may have impact on online aggres-sion among massively multiplayer online gameplayers (Ballard and Welch, 2017).

Cyber incivility and job subordination ex-pressed in “not safe for work” (NSFW) blogslike tumblr.com may jeopardise the status ofemployees. Tiidenberg (2014) presented a casestudy of male sexual dominance by using theimage of suit – tie combination and focusingon crotch area adding a caption: “I think it’stime you took some dictation. Clearly, I need asecretary to assist me.”

Louderback and Antonaccio (2017) extendedtypology of online misbehaviour by addinghuman and computer interaction issue –


Tab. 1: Conceptual analysis of cybersexual harassment in interpersonal level

Keywords Definition Victims SourceOnlineobsessiverelationalintrusion

“The use of social networking sites, blogs, and othertechnologies to gain greater information, awareness, andknowledge of their partner’s online and offline activities.”

Universitystudents

Marganski andMelander, 2018

Online sexualaggression

An online actions when males use various coercive strategiesto engage the women in consensual sexual activities.

Women Strikwerda, 2015

Online sexualharassment

“Number of manifestation like revenge pornography,non-consensual sexting, cyberstalking, sending unsolicitednude images and sexually violent threats and harassment overonline platforms such as gender-based hate speech.”

Women Vitis and Gilmour,2017

Onlineaggression

A systematic abuse of power using electronic technology. Itincludes verbal and visual social and relational aggression likename-calling, sexting, posting embarrassing photos or memes,stalking and impersonation.

Gamers Ballard and Welch,2017

Online sexualsolicitation

“Online risk behaviors like sexting, relating to strangersthrough the Internet, time using internet, using chat rooms,and adding strangers to social network friend lists.”

Adoles-cents

Gámez-Guadix etal., 2018

Internet-initiatedoffense

Offensive actions that consist of enticing child into a sexualrelationship or sexual gratification by using Internetcommunication platforms and fantasy-enhancing items likeweb camera and others.

Adoles-cents

Kloess et al., 2017

Cyber-interpersonalviolance

Online harassment that consists of spreading of rumors,unwanted sexual photos without consent, and/or threateningindividuals, and cyber impersonation.

Collegestudents

Choi and Lee, 2017

Technology-facilitatedabuse (cyberviolence)

Online actions enable abusers to overcome geographic andspatial boundaries that would have otherwise prevented themfrom contacting victims. Forms of domestic violence inelectronic environment like cyber-stalking, non-consensualsexting and cyberbullying.

Adults Al-Alosi, 2017

Virtual rape “Virtual act of forcing sex upon an unwilling person invirtual environment.”

Virtualagent

Strikwerda, 2015

Virtual rape An unwanted sexual intercourse in order to harm the avatarin virtual environment.

Virtualagent

Young andWhitty, 2010

Online sexualgrooming

An online manipulation process when offender createscircumstances to sexually abuse or exploit a child by earningthe trust and initiating intimate physical contact with thevictim.

Adoles-cents

Shannon, 2008

computer-focused digital deviance that is a con-sequence of a lack of technological mindfulness(Maier et al., 2017).

Another important aspect is that initi-ated massive cybersexual harassment attacksthrough social networks may work as a toolof digital diplomacy to seek control and powerin state level. According to the EuropeanParliamentary Research Service Blog, hybridthreat can be defined as “a phenomenon re-sulting from convergence and interconnectionof different elements, which together form a

more complex and multidimensional threat”. Itis very complex in terms of nature of challenges,multiplicity of actors involved and diversityof (un)conventional means used (i.e. military,diplomatic, technological). Thus, hybrid threatsinvolve the cyber incidents and actions. TheEuropean Centre of Excellence for CounteringHybrid Threats categorize hybrid threats basedby three aspects. Firstly, hybrid threats are“coordinated and synchronised action, thatdeliberately targets democratic states’ and in-stitutions systemic vulnerabilities, through a


Tab. 2: Conceptual analysis of cybersexual harassment in enterprise level

Keywords Definition Victims SourceOnline abuse “A crime that include intertwined online-offline

communication and gendered, raced constructions ofwho is privileged to speak publicly in which way.”

Womenbloggers

Eckert, 2018

Cyber incivility Widespread and discourteous treatment amongemployees that occurs via information andcommunication technologies. E-mail and text messagesrefer as uncivil behaviors.

Employess Giumetti et al.,2016

Cyber incivility “A day-level incivility via work e-mail.” Employess Park et al., 2018Cyber incivility “A communicative behaviour exhibited in computer

mediated interactions that violate workplace norms ofmutual respect.”

Employess Lim and Teo, 2009

Cyber sexism A phenomenon when women are putting off careers. Women Foster, 2015Computer-focuseddigital deviance

It includes cybercrimes such as cyber offending,damaging sensitive data and online malware.

Employees Louderback andAntonaccio, 2017

wide range of means”. Secondly, it is relatedto the activities that exploit the thresholdsof detection and attribution. Thirdly, differentforms that may effect decision making at thestate, or institutional level to realize the agent’sstrategic goals in order to undermine the target.

The increasing interests of hybrid conflictwhen interested parties may use technologicalmeans to exploit social, economic or politicalvulnerabilities leads to the main question how

to counter the hybrid threat (Maurer and Janz,2014). What if cybersexual harassment couldbe seen as a social vulnerability. The cyberperpetrators may use bots, specific algorithmsor “factory of trolls” to spread massive panicand increase level of suicide in specific country.

In addition, cybersexual harassment is inter-pretated differently in various levels and mayhave different antecedents, outcomes to pursuespecific objectives of perpetrator.


The analysis and synthesis of scientific liter-ature review provides a specific discource ofcybersexual harassment in different levels byspecifying victims and targeted groups. Thispaper contributes to the conceptual develop-ment of cybersexual harassment and expressesa deeper research interest, motivation andpractical implications in public and privatesectors.

The developed model broaden the conceptualunderstanding if we defining it to the multi-level framework of interpersonal mistreatment(Cunningham et al., 2007). This methodologicalapproach is extended in different contexts– daily cyber aggression among non-relatedindividuals, job relationship subordinated in-dividuals and specific country level in termsof hybrid threat to harm the marginalized or

the weakest group of individuals. According toArcos (2018), target audience segmentation andpreliminary research and analysis play a keyrole in order to identify targeted publics, thatis important to overt and covert disinformationand propaganda campaigns. The constructedmodel showed three unique perspectives ofcybersexual harassment: interpersonal level,enterprise level and state level. The presentedconceptual framework is important for furtherinvestigations in order to prevent negativeoutcomes in terms of countering the hybridthreats (Bachmann, 2011).

ICTs, Internet of Things, Big Data and cyber-physical systems are influenced major changesin the context of Industry 4.0 by consideringtechnical aspects, human interactions and de-velopment of new business models (Navickas et


al., 2017). Cyber-physical systems are used byhackers in order to reach sensitive data or rawinformation of individuals or fully automatatedenterprises. Moreover, it could be used as atool to start a hybrid warfare. The provided

conceptual framework of cybersexual harass-ment could be useful to maintain organizationalpolicies, security strategies, technological solu-tions for development of counter-measures andbuilding resistance.

5 REFERENCES

Akbulut, Y. and Eristi, B. 2011. Cyberbullying andVictimisation among Turkish University Students.Australasian Journal of Educational Technology,27 (7), 1155–1170.

Al-Alosi, H. 2017. Technology-FacilitatedAbuse: The New Breed of DomesticViolence. The Conversation [online].Available at: https://theconversation.com/technology-facilitated-abuse-the-new-breed-of-domestic-violence-74683.

Arcos, R. 2018. Post-Event Analysis of the HybridThreat Security Environment: Assessmentof Influence Communication Operations.Strategic Analysis [online]. Available at: https://www.hybridcoe.fi/wp-content/uploads/2018/11/Strategic-Analysis-2018-10-Arcos.pdf.[Accessed 2018, November 25].

Bachmann, S.-D. 2011. Hybrid Threats, CyberWarfare and NATO’s Comprehensive Approachfor Countering 21st Century Threats – Mappingthe New Frontier of Global Risk and SecurityManagement. Amicus Curiae, 88, 14–17.

Ballard, M. E. and Welch, K. M. 2017. VirtualWarfare: Cyberbullying and Cyber-Victimizationin MMOG Play. Games and Culture, 12 (5),466–491.

Boellstorff, T. 2011. Placing the Virtual Body:Avatar, Chora, Cypherg. In Mascia-Lees, F. E.(ed.). A Companion to the Anthropology of theBody and Embodiment, pp. 504–520.

Bhabha, H. 1997. Of Mimicry and Man: TheAmbivalence of Colonial Discourse. In Cooper, F.and Stoler, A. L. (eds.). Tensions of Empire:Colonial Cultures in a Bourgeois World, Part I(Framings), Chapter 3, pp. 152–160.

Carstensen, G. 2004. Sexuella trakasserier finns nogi en annan värld: Konstruktioner av ett (o)giltigtproblem. PhD Thesis. Förlags AB Gondolin.

Choi, K.-S. and Lee, J. R. 2017. Theoretical Analysisof Cyber-interpersonal Violence Victimization andOffending using Cyber-routine Activities Theory.Computers in Human Behavior, 73, 394–402.

Cunningham, W. A., Zelazo, P. D., Packer,D. J. and Van Bavel, J. J. 2007. The IterativeReprocessing Model: A Multilevel Framework forAttitudes and Evaluation. Social Cognition, 25 (5),736–760.

Eckert, S. 2018. Fighting for Recognition: OnlineAbuse of Women Bloggers in Germany,Switzerland, the United Kingdom, and the UnitedStates. New Media & Society, 20 (4), 1282–1302.

Foster, D. 2015. Five Proposals on Homophobia.In Expanding the Circle: Creating an InclusiveEnvironment in Higher Education for LGBTQStudents and Studies, pp. 225–235.

Fox, J., Ralston, R. A., Cooper, C. K. and Jones,K. A. 2015. Sexualized Avatars Lead to Women’sSelf-Objectification and Acceptance of RapeMyths. Psychology of Women Quarterly, 39 (3),349–362.

Gámez-Guadix, M. De Santisteban, P. andAlcazar, M. Á. 2018. The Construction andPsychometric Properties of the Questionnairefor Online Sexual Solicitation and Interaction ofMinors with Adults. Sexual Abuse, 30 (8), 975–991.

Giumetti, G. W., Saunders, L. A., Brunette, J. P.,DiFrancesco, F. M. and Graham, P. G. 2016.Linking Cyber Incivility With Job PerformanceThrough Job Satisfaction: The Buffering Role ofPositive Affect. Psi Chi Journal of PsychologicalResearch, 21 (4), 230–240.

Hatch, M. J. and Cunliffe, A. L. 2006. OrganizationTheory: Modern, Symbolic, and PostmodernPerspectives. 2nd ed. New York: Oxford UniversityPress.

Holt, T. J. 2018. Regulating Cybercrime throughLaw Enforcement and Industry Mechanisms. TheANNALS of the American Academy of Politicaland Social Science, 679 (1), 140–157.

Kaplan, S. 2014. With #GamerGate, the Video-game Industry’s Growing Pains go Viral.The Washington Post [online]. Available at:https://www.washingtonpost.com/news/morning-mix/wp/2014/09/12/with-gamergate-the-video-game-industrys-growing-pains-go-viral/?noredirect=on&utm_term=.957ef0c3defd.[Accessed 2018, September 29].


Kloess, J. A., Seymour-Smith, S., Hamilton-Giachritsis, C. E., Long, M. L., Shipley, D.and Beech, A. R. 2017. A Qualitative Analysisof Offenders’ Modus Operandi in SexuallyExploitative Interactions with Children Online.Sexual Abuse, 29 (6), 563–591.

Kuem, J., Ray, S., Siponen M. and Kim, S. S. 2017.What Leads to Prosocial Behaviors on SocialNetworking Services: A Tripartite Model. Journalof Management Information Systems, 34 (1),40–70.

Lewis, R., Rowe, M. and Wiper, C. 2017. OnlineAbuse of Feminists as An Emerging form ofViolence Against Women and Girls. The BritishJournal of Criminology, 57 (6), 1462–1481.

Lim, V. K. G. and Teo, T. S. H. 2009. Mind Your E-manners: Impact of Cyber Incivility on Employees’Work Attitude and Behavior. Information &Management, 46 (8), 419–425.

Lindberg, N., Sailas, E. and Kaltiala-Heino, R.2012. The Copycat Phenomenon after Two FinnishSchool Shootings: An Adolescent PsychiatricPerspective. BMC Psychiatry, 12, 91–106.

Louderback, E. R. and Antonaccio, O. P. 2017.Exploring Cognitive Decision-Making Processes,Computer-focused Cyber Deviance Involvementand Victimization: The Role of ThoughtfullyReflective Decision-Making. Journal of Research inCrime and Delinquency, 54 (5), 639–679.

Lowry, P. B., Zhang, J., Wang, C. and Siponen, M.2016. Why Do Adults Engage in Cyberbullyingon Social Media? An Integration of OnlineDisinhibition and Deindividuation Effects withthe Social Structure and Social Learning Model.Information Systems Research, 27 (4), 962–986.

Lyons, B. D., Hoffman, B. J., Bommer, W. H.,Kennedy, C. L. and Hetrick, A. L. 2016. Off-dutyDeviance: Organizational Policies and Evidencefor Two Prevention Strategies. Journal of AppliedPsychology, 101 (4), 463–483.

Maier, C., Wirth, J., Laumer, S. and Weitzel, T.2017. Personality and Technostress: Theorizingthe Influence of IT Mindfulness. In ICIS2017 Proceedings [online]. Available at:https://aisel.aisnet.org/icis2017/Security/Presentations/10/. [Accessed 2018, September 15].

Mainiero, L. A. and Jones, K. J. 2013. WorkplaceRomance 2.0: Developing a Communication EthicsModel to Address Potential Sexual Harassmentfrom Inappropriate Social Media Contacts BetweenCoworkers. Journal of Business Ethics, 114 (2),367–379.

Marganski, A. and Melander, L. 2018. IntimatePartner Violence Victimization in the Cyberand Real World: Examining the Extent of CyberAggression Experiences and Its Associationwith In-person Dating Violence. Journal ofInterpersonal Violence, 33 (7), 1071–1095.

Matheson, L. C. I. and Lyle, E. 2017. Gender Bias inCanadian Military Leadership Training. Journalof Ethnographic & Qualitative Research, 12 (1),18–28.

Maurer, T. and Janz, S. 2014. The Russia-UkraineConflict: Cyber and Information Warfare in aRegional Context. The International Relations andSecurity Network, 17, 277–293.

Moafa, F. A., Ahmad, K., Al-Rahmi, W. M.,Yahaya, N., Kamin, Y. B. and Alamri, M. M.2018. Cyber Harassment Prevention Through UserBehavior Analysis Online in Kingdom of SaudiArabia (KSA). Journal of Theoretical and AppliedInformation Technology, 96 (6), 1732–1746.

Navickas, V., Kuznetsova, S. A. and Gruzauskas, V.2017. Cyber–Physical Systems Expression inIndustry 4.0 Context. Financial and CreditActivity: Problems of Theory and Practice, 2 (23),188–197.

Park, Y. A., Fritz, C. and Jex, S. M. 2018. DailyCyber Incivility and Distress: The ModeratingRoles of Resources at Work and Home. Journal ofManagement, 44 (7), 2535–2557.

Pereira, F., Spitzberg, B. H. and Matos, M. 2016.Cyber-harassment Victimization in Portugal:Prevalence, Fear and Help-seeking amongAdolescents. Computers in Human Behavior, 62,136–146.

Ritter, B. A. 2008. Cybersexual Harassment:Development and Validation of a Measure ofthe Online Environment and Online SexualHarassment. Academy of Management AnnualMeeting Proceedings, 1, 1–6.

Ritter, B. A. 2014. Deviant Behavior in Computer-Mediated Communication: Development andValidation of a Measure of CybersexualHarassment. Journal of Computer-MediatedCommunication, 19 (2), 197–214.

Salter, M. 2018. Publicising Privacy, WeaponisingPublicity: The Dialectic of Online Abuse on SocialMedia. In Dobson, A. S., Robards, B. andCarah, N. (eds.). Digital Intimate Publics andSocial Media, pp. 29–43.

Sarpotdar, A. 2013. Sexual Harassment of Women:Reflections on the Private Sector. Economic &Political Weekly, 48 (40).


Shannon, D. 2008. Online Sexual Grooming in Sweden– Online and Offline Sex Offences against Childrenas Described in Swedish Police Ddata. Journal ofScandinavian Studies in Criminology and CrimePrevention, 9 (2), 160–180.

Shapka, J. D. and Maghsoudi, R. 2017. Examining theValidity and Reliability of the Cyber-Aggressionand Cyber-Victimization Scale. Computers inHuman Behavior, 69, 10–17.

Sklenarova, H., Schulz, A., Schuhmann, P.,Osterheider, M. and Neutze, J. 2018. OnlineSexual Solicitation by Adults and Peers – Resultsfrom a Population Based German Sample. ChildAbuse & Neglect, 76, 225–236.

Spence, E. H. 2012. Virtual Rape, Real Dignity:Meta-Ethics for Virtual Worlds. In Sageng,J. R., Fossheim, H. J. and Larsen, T. M. (eds.).Philosophy of Computer Games, Chapter 9,pp. 125–142.

Strikwerda, L. 2015. Present and Future Instancesof Virtual Rape in Light of Three Categories ofLegal Philosophical Theories on Rape. Philosophy& Technology, 28 (4), 491–510.

Surma, I. 2016. Pushing the Boundaries of DigitalDiplomacy: The International Experience and theRussian Practice. In Zlateva, T. and Greiman,V. A. (eds.). International Conference on CyberWarfare and Security, pp. 304–311.

Tiidenberg, K. 2014. Bringing Sexy Back:Reclaiming the Body Aesthetic via Self-Shooting.Cyberpsychology: Journal of Psychosocial Researchon Cyberspace, 8 (1).

Vitis, L. and Gilmour, F. 2017. Dick Pics on Blast: AWoman’s Resistance to Online Sexual HarassmentUsing Humour, Art and Instagram. Crime, Media,Culture: An International Journal, 13 (3), 335–355.

Vveinhardt, J. and Kuklytė, J. 2017. The SideEffect of Cyberbullying. In Kuzmin, S. V. (ed.).XLIX Международная научно-практическаяконференция «Теория и практика мировогонаучного знания в ХХ веке», pp. 8–10. ISBN978-5-9500243-0-6.

Warren, I. and Palmer, D. 2010. Crime Risks ofThree-Dimensional Virtual Environments. Trends& Issues in Crime and Criminal Justice, 388, 1–6.

Wolfendale, J. 2007. My Avatar My Self: VirtualHarm and Attachment. Ethics and InformationTechnology, 9 (2), 111–119.

Young, G. and Whitty, M. T. 2010. Games WithoutFrontiers: On the Moral and PsychologicalImplications of Violating Taboos within Multi-Player Virtual Spaces. Computers in HumanBehavior, 26 (6), 1228–1236.

AUTHOR’S ADDRESSJūratė Kuklytė, Faculty of Economics and Management, Vytautas Magnus University,S. Daukanto str. 28, Kaunas, 44246 Lithuania, e-mail: [email protected]


www.ejobsat.com

AN ANALYSIS OF EXPECTATIONSIN INDUSTRIAL VALUEENGINEERING PROJECTSErhard Teschl11Mendel University in Brno, Czech Republic

TESCHL, Erhard. 2018. An Analysis of Expectations in Industrial Value Engineering Projects. European Journalof Business Science and Technology, 4 (2): 196–215. ISSN 2336-6494,DOI http://dx.doi.org/10.11118/ejobsat.v4i2.139.

ABSTRACT

This exploratory study addresses the need to identify specific and holistic upfront expectationsinto industrial value engineering projects for best tailored preparation of an efficient projectexecution. The analysis includes a total base population of 90 projects, which were conductedbetween 2010 and 2018 in 16 different industries. Out of those, 63 projects had a narrower valueengineering context and have been analyzed with the support of a CAQDAS tool (ComputerAssisted Qualitative Data Analysis Software). Analytical results show that participants’ expec-tations in value engineering projects vary depending on their industrial environments, but copewith existing studies on critical success factors for project management. Based on the findings theauthor recommends further research on fast project execution, closing the gap between training-and project content as well as emphasizing the necessity of rigor with regards to the utilizationand application of terminology, which includes sharpening the correct interpretation of valueengineering, its tools and contents.

KEY WORDS

value engineering, project expectations, content analysis, CAQDAS

JEL CODES

O310, L230

1 INTRODUCTION

This introduction covers three aspects. First, inorder to avoid and prevent misunderstandingand to foster a common clear understandingof the origin and the potential impact, the

term ‘value engineering’ is elaborated in theliterature review.

Second, as this analysis’ driving force, theauthor’s personal practical experience and ar-bitrary observations let one assume that a

An Analysis of Expectations in Industrial Value Engineering Projects 197

high degree of freedom rules practitioners’ andstakeholders’ interpretations and expectationsin value engineering projects. On the samepage, not all past projects have been closedwith full satisfaction. But the analysis withinthis environment seems to show repetitivepatterns. The consecutive question arises, if theproject setup and planning preventively couldhave been prepared a better way upfront. Astrong alignment of value engineering projectsalong project management’s basic principles isevident.

Third, this analysis is based on a datacollection, which was gathered during the last

decade by the author as unique source. Thegeneral validity, its restrictions and limitationsof this base require careful consideration. Onthe other side, the given set of data allows anal-ysis, understanding and comparison of differentindustrial environments.

Therefore, this analysis provides insightsinto contemporary and subjective environment-dependent interpretations as well as improve-ment proposals for future value engineeringprojects’ setup and upfront planning, includingthe consideration of participants’ expectationsin terms of potential goals, procedures andexecution.

2 RESEARCH OBJECTIVE AND RELEVANCE

This research’s relevance is based on threedistinctive aspects. Generally, it aims to ex-plore practical interpretation and applicationof value engineering projects in the industrialenvironment. The guiding idea is to analyzeand understand upfront expectations into valueengineering projects, in order to address themthe earliest possible moment. This shall raisesatisfaction with the projects and its results.

The first detailed supportive aspect of thisstudy’s relevance deals with the necessaryprecision of wording and terminology in orderto enable exact and correct interpretation. It isrelevant to embrace the contemporarily inter-preted identity of any term, in this particularcase the term “value engineering”, in order toenable oneself to talk about this term with anyother person without creating misunderstand-ings. One main force behind this research wasthe author’s experienced increase of projects,which were labelled “value engineering”, butpursued other non-value-engineering objectivesas any other random project following loose,unclear and unbinding definitions. Any wronglyor imprecisely labelled project might lead tomisconception and disappointment, if the labelis used as a generic “one-for-all umbrella-term”. This paper shall support sharpeningthe use and interpretation of the terminologyby understanding contemporary interpretationsand project expectations.

The second underlying aspect of relevanceconsecutively derives from the first one anddeals about the best possible upfront prepa-ration to potential expectations in upcomingprojects. It is about the awareness of thespoken and unspoken objectives, goals andexpectations, within and beyond imaginationof all participants and stakeholders. One couldargue, that it finally would not matter fromthe viewpoint of project success, which labelsthe assigned projects finally are given or whichtools are being applied, as long as the projectfocal point, objectives and expectations aredefined thoroughly and precisely for the sake ofmost efficient and successful project execution.Projecting this aspect even on to externalinfluences, value engineering projects hypothet-ically and theoretically could be influenced bynew trends or collateral effects, which werenot covered back in the time, when valueengineering was defined. There might be a newmainstream, which is worth being detected ascollateral benefit of this work.

The third underlying aspect of relevancedeals with general difficulties to compare differ-ent industrial project environments within onestudy due to restricted data access. This paperoffers a unique opportunity to do that (in alimited way, and to compare different industrialproject environments and uncover differences.

198 Erhard Teschl

3 LITERATURE REVIEW

The idea of Value Engineering (VE) was ini-tiated and formulated during the 1940s byLawrence D. Miles (Lawrence D. Miles ValueFoundation, 2016). Now it is manifested asa norm and as an internationally recognizedstandard in the European Community (DIN –Deutsches Institut für Normung, 2002) as wellas on the American continent (SAVE Inter-national, 2018). The underlying core principleof the VA technique, as explained in thesefundamental documents, is based on methods ofthe technical value- and functionprinciple andinterprets the term “Value” as function-cost-ratio (SAVE International, 2018), a trade-offbetween utilization of a part and its cost ofcreation.

Value Management (VM), according to DINEN 12973 (DIN – Deutsches Institut für Nor-mung, 2002), is manifested in an internationalnormative. There, it is defined as a managementstyle, which has been developed from methodsbased on the value- and function-principle.Nowadays the utilization of the terms ValueManagement (VM), Value Analysis (VA) andValue Engineering (VE) is based on the sameconcept and applies the same toolset. Accordingto Springer Gabler Verlag (2016a), the tech-niques VA and VE are being applied at differentstages of a product’s life cycle. VE is beingapplied during the early concept-, development-and engineering phase, where the majority ofthe cost still can be influenced before theirallocation. In contrast, VA rather analyses andoptimizes products, which are already readilydeveloped, launched and produced on existingfacilities with lower savings-impact and atcostly design changes.

The main distinctive characteristics of theVE approach from other approaches is astrong primary focus on the customer, thecustomer requirements, the customer expec-tations (translated into customer functions)and an overall cost-optimization-thought. Miles(Lawrence D. Miles Value Foundation, 2016)quoted the challenges and core thoughts forVE as follow: “All cost is for Function” and“Instead of thinking and talking in terms of

‘things,’ Value Analysis changes the thinkingprocess to ‘functions’.” From a practitioners’tool perspective, the VE-approach technicallytakes advantage of thinking in higher levels ofabstraction by neutrally defining a product’sfunctions and thinking in those.

In its very beginnings, VE aimed on improv-ing the value of existing products, in termsof reducing and eliminating unnecessary cost.Later, it shifted its focus additionally towardsfunctional improvement of a product, simplysaid: making its features better. Nowadays, VEis being applied on products, services, projectsand administrative processes, regardless of theirdevelopment maturity along the entire productlife cycle.

VE is defined as an organized, systematicand cross-functional team approach with theobjective to provide the required functions atlowest overall cost (DIN – Deutsches Institut fürNormung, 2002). VE pursues a holistic integra-tive solution system. The required quality, per-formance, reliability, performance and marketacceptance of a product are not being sacrificedfor the sake of cutting cost or cheapening aproduct only.

With cross-reference to product development,Ibusuki and Kaminski (2007) as well as Ungerand Eppinger (2011) and Ho and Lin (2009)recommend utilizing VE, together with theprinciples of target costing, concurrent functiondeployment and concurrent engineering forproduct development processes.

In the United States and Canada, the appli-cation of VE shows a long mandatory projecttrack in private, federal and governmentalorganizations (SAVE International, 2018). ThePublic Law 104–106 (104th Congress, UnitedStates of America, 1996) even mandates theapplication of VE for public procurementprojects, for instance on construction, traffic,road construction, defense, security and spaceflights.

VE has a long history on its transition frompure cost optimization towards standardizationand application in various industries, products,services and along the entire product life cycle.


Fig. 1: Development of influence for change, cost of changes and information level along the innovation process progress(source based on Jahn, 2010; Herstatt and Verworn, 2004; von Hippel, 1993; modified by the author)

During the early innovation phase (see Fig. 1,“Influence” zone “fuzzy front end” duringthe very early phase of product development,sources stated below) design changes can beimplemented relatively easy at lower changecost in comparison to design changes at a laterpoint of time, where change cost are higherdue to already allocated cost, such as alreadyinvested design-labor, material, machines, jigs,fixtures or tools among others – compareJahn (2010), modified from and referenced toHerstatt and Verworn (2004), itself based onvon Hippel (1993), see also Fig. 1.

Even though not stated anywhere explicitlywithin the standard, it is obvious, that the workplan of a value study (DIN – Deutsches Institutfür Normung, 2002, p. 22ff) fulfils the definitionof a project (Springer Gabler Verlag, 2016b).Any VE project is built on a clear projectmanagement setup.

Timewise on parallel to VE, Project Man-agement has been developed as a generic man-agement model (Atkinson, 1999; Müller andJugdev, 2012) on its transition towards formal-ization and institutionalized standardization(Garel, 2013). This development path ever sincewas paired with the search for critical successfactors, as elaborated by Müller and Jugdev

(2012), who have analyzed and summarized thecontribution of Pinto, Slevin and Prescot as(in their view) popular and dominant authorsin the field of Project Management. In theirsummary on research referring to project man-agement success factors, they have identified“impact on customers” and “business success”among others, which refer back on key featuresof VE, themselves. Lim and Mohamed (1999)reconfirm in their exploratory studies, thatproject success mainly depends on stakeholders’perspectives and has different meanings to dif-ferent stakeholders. This copes with the abovestated author’s personal experience. Frefer etal. (2018) compare the findings of Pinto andSlevin (1988) on projects’ critical success factorswith other researchers’ conclusion (Freemanand Beale, 1992; Khosravi and Afshari, 2011;Bryde and Robinson, 2005; Bahia and de FariasFilho, 2010; Al-Tmeemy et al., 2010; Mukhtarand Amirudin, 2016; Gomes and Romão, 2016;Omer, 2017), shown in adapted Fig. 2. “Time”,“Cost”, “Customer Satisfaction”, “Effectiveness& Efficiency”, “Requirements & Specifications”,“Quality” and “Health, Safety, Environment”were identified as critical success factors bymore than half of the researchers.

200 Erhard Teschl

Fig. 2: Quantitative summary of success factors in projects (source based on Frefer et al., 2018; modified by the author)

4 RESEARCH DESIGN

The main goal of this analysis is to explore dif-ferent aspects of project expectations and theirimpact direction for industrial value engineeringprojects.

Under the assumption, that project expecta-tions of one specific project environment canbe transferred from past and projected onfuture projects in a similar project environmentand setup, also conclusions from past can betransferred and may be verified with futureprojects.

The analysis of this (past) information shallserve as improvement base for future valueengineering projects’ setup. This includes theconsideration of participants’ “ex ante” expec-tations (in the meaning of “original, beforethe project was started and not influenced byexternal factors”) in terms of potential goalsand on top of the hard project content goals,procedures and execution of the projects itself.

It is the goal of this analysis to identify thedifferent aspects of upfront expectations intoprojects, which is linked to project satisfaction.

Therefore, this analysis’ research questionis: “What was past industrial VE projectsparticipants’ real upfront comprehensive, con-temporary and particular expectation in thoseprojects?”

This research has an exploratory character.There is no upfront knowledge available, there

are no given parameters nor variables to ex-amine (Creswell, 2009, p. 18). Creswell (2009,p. 194) takes reference to Locke et al. (2013):“The intent of qualitative research is to under-stand a particular social situation, group, …”.Based on the given subjective baseline, theinductive constructionist research approach waschosen. Silverman (2017) defines it as focusingon social processes and constructing the realitysocially by applying “How?” questions.

This is supported by the specific characteris-tics of the given research environment, whichcalls for qualitative research (Creswell, 2009,pp. 175 and 195). There is a natural setting,in which the author shall experience the issuewhen collecting input. The author is activepart and a key instrument of research himselfby observing behavior and interpreting whencollecting data. With regards to VE projects,there are multiple sources of data, which needto be compared. By organizing the identifieddata from bottom-up, an inductive process isinstalled with working back and forth betweensources, codes and the levels of abstraction.The research design is emergent and beingdeveloped during the research itself. It is notdescribed a detailed way before beginning. Theresearch topic demands a holistic view in termsof combining and comparing the findings of eachsingle project stream.


For reaching the research objective, it is moreimportant to fully understand the research field,opened by the various cases, than to focuson and apply methodologies (Creswell, 2009,p. 10). The author wants to identify and under-stand the dependencies, connections and exclu-sions between these different projects/cases andits expectations. This research objective doesnot require providing a post positivistic proof ofa hypothesis, which cannot be identified basedon the given starting base line.

Qualitative research has gained importanceand application within social science, psychol-ogy and medical research in general duringthe last decade, where quantitative researchwas dominant and preferred before. Malterud(2001) underlines the importance of ‘interpre-tive action’ to be included in medical research,while Lamnek (1995) sees the advantage, thatthe interpretive procedure allows the reader orobserver to uncover background information,which would not be possible with a quantitativeapproach. The content analysis as a forerun-ner of qualitative research comes from com-munication science and provides a procedureto analyze big amounts of textual material(Mayring, 2010). According to Mayring (2010),the qualitative content analysis combines thetechnical knowhow of, how to deal with lots oftextual material, with the capability to performinterpretive and verifiable text analysis.

Creswell (2009, pp. 185–191) summarizes thekey points for qualitative data analysis andinterpretation as an ongoing process with con-tinual reflection about open ended data, whichhas to be collected, organized, analyzed andstructured by “coding” (which means to cate-gorize), arrange the codes within a frameworkto start to form a theory and interpret thefindings. The continual reflection from differentperspectives is the base for triangulation ofdifferent data in order to provide validity.

In her introduction to Grounded Theory,Charmaz (1996) describes the means and pro-cedures of qualitative studies as “… a set ofinductive strategies for analysing data. Thatmeans you start with individual cases, incidentsor experiences and develop progressively moreabstract conceptual categories to synthesize, to

explain and to understand your data and toidentify patterned relationships within it. Youbegin with an area to study. Then, you buildyour theoretical analysis on what you discoveris relevant in the actual worlds that you studywithin this area.”

Following Silverman (2017, p. 326), the re-search strategy follows 4 steps: (1) focus onhigh quality date with easy access; (2) focus onone process within that data only; (3) narrowdown to one part of that process; (4) comparedifferent sub-samples of the population.

The only focal point for the research at handwas set within the above mentioned researchquestion. Other potential areas of interestfor studies, as for instance, success factors,success rates, and financial benefits of projects,organizational setups, and hierarchical supportamong others were not followed and specificallyexcluded. The only topic of interest was anypotential upfront expectation into the project.

The inductive approach of qualitative contentanalysis was mixed with quantitative insights,in order to enlarge to a mixed methods ap-proach. Silverman (2017) and Saldana (2016)underline the useful support of a CAQDAS(Computer Aided Qualitative Data AnalysisSoftware) for such studies. The chosen softwarefor this study is MAXQDA.

Applying triangulation supports this researchin different ways. First, by analyzing the re-search question from different viewpoints, newknowledge is created (Flick, 2008). Data trian-gulation supports the research validity: “… bycombining methods and investigators in thesame study, observers can partially overcomethe deficiencies that flow from one investigatorand/or method. (…) In this respect triangulationof method, investigator, theory, and data re-mains the soundest strategy of theory construc-tion.” (Denzin, 1970). In this research, multiplecases from multiple industries and multipledifferent projects serve as subjects for this studyand provide “rich data” (Silverman, 2017).

Fig. 3 demonstrates the study’s design. Itcombines Silverman’s (2017) 4-step approachand Charmaz’s (1996) procedures. In a firststep, appropriate projects from the author’sprofessional past practice were identified, which

202 Erhard Teschl

Fig. 3: Design of study

potentially could contribute to the researchquestion. Filters were applied to focus on themost appropriate set of project data (see nextsub chapter below). Then a Qualitative ContentAnalysis with first cycle coding according toSilverman (2017), Miles et al. (2014), andSaldana (2016) was applied by searching eachsingle case by case for any potential hint on con-tribution to analyzing or answering the researchquestion. Any identified information fragmentwas marked with codes. These codes emergedfrom the content and describe and summa-rize the content of the identified informationfragments by descriptive notes. The MAXQDAsoftware facilitates cross comparing the contentof all identified information fragments of onecode. Doing so, the coding was refined andconsolidated in a second cycle coding, loopby loop. The software also supports crosscomparison of the results of different documentgroups. Different combinations of documentgroups with codes finally were visualized aqualitative and quantitative way.

4.1 Sampling Technique

Due to the exploratory character of the studythe author has applied purposive convenience

sampling technique (compare Arber, 2001; Bry-man, 2012; Denzin and Lincoln, 1994; Silver-man, 2017). The samples conveniently werealready available and accessible, which favoredthe examination of a larger population due tothe timeadvantage. The selected base popula-tion for this study is all available cases, they are“naturally occurring data” (Miles et al., 2014),as most comprehensive and representative pop-ulation (Arber, 2001).

According to Silverman (2017), the choice ofcases for qualitative research should always betheoretically guided. Yin (2014) concludes thatqualitative research (case studies in particular)can be generalized to theoretical propositions,but not to populations. According to Silverman(2017), the goal much rather is to “expandand generalize theories (analytic generaliza-tion) and not to enumerate frequencies (statis-tical generalization).” Hence for this particularstudy, generalization of the findings is of lessimportance than creating a first qualitativeknowledge on one single and narrow focalpoint, which is the upfront expectation intoVE projects (Bryman, 2012), (Silverman, 2017).Gobo (2007) proposes to apply “interactive,progressive, and iterative sampling”, in order toachieve representativeness.


5 DATA BASE OF CASES

The author is a trained, certified and practicingvalue engineer. As industrial consultant, he hasparticipated in a 100+ projects across severalindustries for different companies over the lastdecade. The author’s experience as consultantin industrial projects has facilitated the accessto projects from several diverse industries. Themajority of these projects were settled within aparticular VE context but yet showed differentVE-coverage, -relevance and -density.

These projects’ technical content has toobey strict confidentiality. But keeping thisresearch’s subjects focused on upfront expecta-tions into the projects only, does not violateany confidentiality restriction. Neither technicalproject content nor its particular hard goalsare being discussed and distributed. Choosingthe approach at hands, anonymous informationis protected as required, but still can beanalyzed and then shared. The large numberof projects itself and its diversity with regardsof industries, companies, participants and par-ticipants’ functional roles supports anonymity,do not allow any reference conclusion back onsingle projects and provides biggest possibleand representative diversity within the settled,limited environment.

The author’s entire professional project trackwith more than 100 projects and cases wasscreened as first step (compare to “Project DataBase with VE Context” in Fig. 3). Applying afirst upfront filter on the entire data base re-sulted in 90 remaining cases as initial data baseline fulfilling all of the following characteristics:they were real projects, trainings or conferences;they were no concepts only, nor fragments; theytook place during the last 10 years with theauthor’s current work environment and work–scope as VE practitioner; they were embeddedwithin a particular VE context; they potentiallycan contribute in answering the research ques-tion.

5.1 Filtering & Structuringthe Project Data Base

As next procedure, a second, more specific filterwas applied (compare step “Filter, Selection+ Classification” in Fig. 3) on the pre-selected90 cases. As result, 63 cases remained relevantfor the study. 27 cases had to be excludedas not relevant for the study. Reason forexclusion could be any one of the followingones: referring to the research question, theydid not contain any stated expectations in VEprojects and, hence they could not contributeto answer the research question; they had noclear and specific value engineering referenceon second view (“borderline cases”) – thatcould be either one or both of the followingcases: they did not have a clear focal pointon functional improvement; they did not havea clear focal point on cost improvement; theywere of repetitive character, had same or verysimilar content as other cases and, hence couldnot add additional contribution; they were ofrather conceptual character, as for instancetheoretic papers, which had been designed fromone single party without reflection or discussionby other different parties; they lacked crossfunctional cooperation during creation.

Fig. 4 and 5 provide an overview of the cases’base population’s classification after applyingthe first filters.

The vertical axis of Fig. 4 lists the indus-tries, where the projects were nested in. Thehorizontal axis divides them a twofold way.The primary selection criterion is “relevant foranalysis”/“not relevant for analysis” (secondline in Fig. 4) for the further analysis as resultedafter structuring as described in this chapterabove. The secondary criterion (line three)describes the type of each single case. The initial“Project Data Base with VE Context” consistsof a total number of 90 cases identified after thefirst selection, which reduced the original over100 cases to 90 cases, as shown in Fig. 5.

Those 90 cases were later split into 3 sub-categories as a consequence of the emergingdifferences during the later applied first-cycle

204 Erhard Teschl

Fig. 4: Data base characteristics for analysis

coding process throughout the qualitative anal-ysis. For the ease of reading, these later emergedsub-categories are already shown at this point oftime as anticipation. They split into 66 projects,13 trainings and 11 conferences. All of those areassigned to 16 different industries, which areshown on the vertical axis of Fig. 4.

While the category “projects” refers to realpractical industrial project work on technicalcases, the categories “training” and “confer-ences” refer to a theoretical, conceptual framewith less interaction and rather one-directionalinformation flow. The category “training” con-tains cases with theoretical VE education of theparticipants. The category “conferences” con-tains cases, where information was shared anddiscussed with an audience. This informationcould for instance refer to cutting edge projectresults, new approaches or lessons learned. In“conference” cases, new theoretical information,which had derived from real practical cases, wasspread.

These three categories later showed differentresponse behavior during the course of theanalysis of the research question. Summarizing,Fig. 4 and 5 provide an imagination of the cases’

diversity, even though they were obtained fromone single source only.

Those were screened in a second filter, se-lected and classified (compare “Filter, Selection+ Classification”). A total of 27 cases did notmeet the four criterions of the second filter(group “Not relevant for Analysis” in Figure 4,they were “without clearly stated expectations”in Fig. 5). 63 cases remained “Relevant forAnalysis” in Fig. 4 (labeled “Relevant Cases” inFig. 5), with potential contribution to answerthe research question. The “Qualitative Anal-ysis with CAQDAS; Coding first Loop” wasapplied on those 63 cases.

The major share of projects or cases in Fig. 4was conducted in the closely related industriesof “valve”, “compressor” and “Oil & Gas”.But they were complemented with projectsfrom very distinctive other industries, such asrailway, marine, farming vehicles, automotive,semi-conductor and theoretical knowledge fromconsulting and training expertise.

An even closer look on the project category“projects” (compare waterfall diagram of the46 “Industrial Projects” in Fig. 5) in a thirdanalysis loop, which also has emerged during


Fig. 5: Cases, their characteristics and timely development

the later second cycle coding process, hasuncovered another interesting side effect.

The 46 Industrial projects later were evenfurther split according to their functional envi-ronment. More than half of the projects wereNew Product Development (NPD) projects.Ten projects supported purchasing, mainly forpreparation of vendor negotiations in terms offunctional- or cost levers. The remaining 11projects were settled in the production envi-ronment for supporting their efficiency at theinterface to product improvements, which referto changes of product functions, -dimensions or-specifications.

The bold dark grey arrows above the right3 columns in the chart of Fig. 5 indicate thetimely and numerous tendencies of projectsper category. Despite of best and strongestVE-impact during early new product devel-opment projects (NPD) (compare “influencezone” in Fig. 1), the number of NPD projectswas decreasing along the timeline. Projects inpurchasing environment remained stable, whileprojects in production surroundings were evenincreasing along the same time period.

The decrease of NPD projects per time periodin the current environment can be explainedwith the fact of limited number of real newproduct development projects per year. Thehigher share of NPD projects is a result of the

chosen VE strategy in the current setting. Inthat the first focal point was set in the optimiza-tion of the new products in the developmentphase. It was then followed by stronger focalpoint shift to purchasing and production, onceVE resources became released, when the NPDproject backlog has ceased.

Fig. 4 and 5 proof, that the application ofVE is not limited to NPD projects during earlyproduct life cycle phases only, but also offersgood impact on cases, which – with regardsto their development- and product-maturity –have reached already a later and more maturephase of their life cycle, as for instance inpurchasing- or production cases.

5.2 Participants

Fig. 6 provides an overview of the recordedproject participants including their functionaland industrial background. The total number ofparticipants, including the non-recorded ones,exceeds the recorded one. The vertical axis ofFig. 6 provides an overview on the 185 recorded-only participants’ professional role and theiroccupation. They are aggregated to reasonablemain professional role clusters. The horizontalaxis of Fig. 6 indicates the industry the projectswere nested in. If a participant has participatedin more than 1 Project, only the main project

206 Erhard Teschl

Fig. 6: Industries of projects and participants’ functional roles

(in terms of largest project) was counted (nodouble count).

The table shows, that the majority of par-ticipants are engaged in production- and en-gineering roles. But they are well spread overdifferent industries and very well represent allfunctional scopes, specifically contributing tothe new product development process in anearly stage (compare to the ‘influence zone ofthe “fuzzy front end”’, compare to Fig. 1), butequally also during the later phases of productlife cycle.

From the data diversity viewpoint, the avail-able data can be considered sufficient for theanalysis. The matrix, which is opened by theproject sourcing industries and the concernedparticipants occupation and functional roles,has points with higher density, but generallyis well balanced. In return, this research’sanalysis shall serve as input for the functionalroles of the last participant group of “GenericFunctions” in similar industrial environments.However, other environments from contraryindustries might require a similar approach,which could result in different analysis results.

6 QUALITATIVE CONTENT ANALYSIS

Throughout the course of the analysis differentdocument sets have been formed. The firstdifferentiation was chosen after first and duringsecond cycle coding. The sets have changedbased on the emerged findings and accordingthe business environments of the author’s cur-rent and past occupation environment. Withinthe current environment a second differentia-

tion was drawn in order to distinguish practicalindustrial projects from theory-oriented train-ings and conferences.

The qualitative content analysis was donewith MAXQDA software for facilitating theprocessing and examination of large numbersof data and documents.


One single and leading question for theexamination was defined before the start. Thiswas a simplified version of the research question:“Which were the upfront expectations in theprojects?”

Each single case of the entire case popula-tion was examined for any comment, whichpotentially contributes to answer the leadingquestion. Each of these identified informationfragments was marked with a code, which itselfrepresented its content. The specific contentdescription was formulated in a memo, whichwas attached to each code. This procedurewas applied case by case. The codes werecreated inductively, they emerged from thecontent. Wherever it was appropriate, alreadyexisting codes from prior definitions on otherinformation fragments were applied.

37 different codes existed after at the end ofthe first cycle coding process.

Some of the 37 codes seemed to be verysimilar, being redundant, or at least aiminginto a similar direction. During comparing andcontrasting the codes’ description was refinedand made more precise. Some very similarcodes were combined and aggregated into onecommon code. An accordingly refined codedescription in the memos was adapted.

Five preliminary Groups of similar or com-plementing codes then were established, consol-idated and defined during this procedure: (1)“Procedural Aspects”, (2) “Hidden ParticipantAgenda”, (3) “New Opportunities”, (4) “Orga-nizational Aspects”, and (5) “Product Related”.

In the second cycle coding phase, all textfragments of each single code were cross-compared and contrasted with the MAXQDAsoftware. The subject of examination changedfrom the cases (in first cycle) to the codes,which were compared from the view of theidentified information fragments in the cases.The focal point was set on the applicability ofthe newly defined groups of codes, the properqualitative description of the codes for allmarked information fragments and the generalfit of the code.

Finally, 18 consolidated, different codesemerged from the initial 37 ones. The reduction

was carried out by combining similar codes intoaggregated ones.

Data was considered saturated, when findingsbecame repetitive and no new idea emergedduring the iterative loops (Czarniawska, 2014).

Fig. 7 shows the 18 resulting codes sorted indescending order of their absolute nominationquantity over all cases. 615 information frag-ments throughout all 63 analyzed documentshave been coded in total. “Cost Transparency”is the pre-dominant expectation set in VEprojects.

The prior upfront classification of cases(compare Fig. 4) also was re-structured as anemerging side-effect during second cycle cod-ing. The former document groups “projects”,“conferences” and “trainings” were re-arranged.“Trainings” and “conferences” both had arather theoretical character and were mergedinto “Conferences and Trainings”. One casefrom the preliminary group “projects” movedto “Conferences and Trainings” as well. The re-maining “projects” were split according to theirindustrial environment into “Current ProjectEnvironment” and “Former External Environ-ment”. This split makes more sense, since dif-ferences between these two environments couldbe detected during second cycle coding, andboth are settled within a practical applicationenvironment compared to the theoretical groupof “conferences and training”.

Fig. 8 provides an overview of the code fre-quency as the percentage of documents, whichhave been coded with each particular code inthe four new document-sets. Multiply appliedcodes within one document are not considered.The codes are sorted in descending order oftheir frequency on the set “all documents” inFig. 8.

The patterns of the frequency barcodes inFig. 8 obviously varies between the 4 differentabove-mentioned document sets. These differ-ent environments apparently have a differentimportance in between the codes and a differentsequence of upfront expectations. The highcontribution share of the document set “currentproject environment” explains the similarity ofthe barcode patterns between the two groups

208 Erhard Teschl

Fig. 7: Codes for expectations with absolute nominated quantity

Fig. 8: Code frequency for expectations – sorted in descending order on all documents

“all documents” and “current project environ-ment”.

Interestingly, two gaps between the categories“Current Project Portfolio” and “Conferences& Trainings” become evident, even though thetrainings particularly shall prepare and supportthe application of VE projects in the currentenvironment. The Expectations “Fast ProjectExecution” and “New Market” are nominatedin the current project environment, but werenever nominated during any conference andtraining. See also Fig. 9.

During the second cycle coding process thecodes were re-structured and re-grouped withupdated and better meaning and fit. Themeanings of the new structure of document

groups also were taken into account. The 7 newgroups have emerged during the second cyclecoding and are shown in Tab. 1 and 2. Theiremergence was not influenced by any other priorstudy or theory, their structure and sorting wasformed an uninfluenced way through comparingand contrasting. They formed the new fine-tuned thematic focal points of the expectations.In Tab. 1, they are already sorted in descendingorder on an overall view on all 63 cases.They are (1) “Cost”, (2) “Time Management& Efficiency”, (3) Organizational Aspects”,(4) “Quality-, Risk & Maturity Management”,(5) “Function Analysis”, (6) “New businessOpportunities”, and (7) “Hidden Agenda”.


Fig. 9: Two case comparison between trainings and applied projects

7 INTERPRETATION OF SINGLE ANDGROUPED EXPECTATIONS

7.1 Single Expectations

In both Fig. 7 and 8 the code “cost trans-parency” is the most cited code and outweighsall others. Also, in the other 2 documents sets“current project environment” and “conferencesand trainings” it is the dominating code, whilethe emphasis on “information exchange” and“Structured approach” is higher for the formerexternal business environment in a differentindustry.

A remarkable gap between the theoreticallydriven “conferences & trainings” and the prac-tical “current project environment” can befound. The codes “fast project execution” and“new market” have a significant role within

the practical projects (“current project envi-ronment”), while they were not mentioned atall during “trainings and conferences”. Fig. 8and 9 visualize this gap. The two codes on thefigure’s right end are only mentioned in thedocument set “current project environment”(quite frequently), while all other codes werecited in both document sets. Future trainingshould take care for this fact. Rethinking thefuture training focal points towards a moreapplication-tailored content makes sense.

Even though all selected projects were set-tled in a Value Engineering environment, thespecific VE aspect of “function analysis” onlyis represented at the bottom of the currentprojects’ importance in expectations (compare

210 Erhard Teschl

Tab. 1: Expectation groups with absolute frequencies

Thematic groupsof expectations

Current projectenvironment

(38 cases)

Training &conferences(18 cases)

Former projectenvironment

(7 cases)All cases(63 cases)

Cost 78 28 37 143Time Management & Efficiency 73 26 25 124Organizational Aspects 40 39 45 124Quality, Risk- & Maturity Management 29 13 54 96Function Analysis 37 22 16 75New Business Opportunities 28 2 3 33Hidden Agenda 19 1 0 20

Fig. 8), while it had a much more dominant rolefor the projects in the former external projectenvironment.

Surprisingly, in this specific given VE en-vironment, not even one expectation referredinto a fundamental VE focal point, namely thecustomer, and the customer behavior. This is aremarkable gap between theoretic VE from VE-practitioners’ view and applied or interpretedVE from participants’ or stakeholders’ view.

Based on finding these differences betweendifferent sets of documents, the author adaptedhis research strategy from “finding any hint onan expectations into projects” to “identifyingcommons and differences” between differentsets of cases on expectation group level, asexplained in the following text.

7.2 Expectation Groups

Tab. 1 shows the newly formed groups ofexpectations in a descending order on all 63cases. In an overall view (far right column), cost,time, organizational aspects and quality werethe driving expectation groups ahead of VE’score distinctive element, the function analysis.New business opportunities and hidden agendaswere least important expectations.

Expectation Group “Cost”. The most predom-inant group of expectations with 143 nomina-tions was basically defined by 3 main thoughts:(1) Create product knowledge by gaining in-sights and understanding of the product’sfeatures, characteristics, functions, advantagefor the customer and manufacturability. (2)Create cost transparency on a systematic and

detailed level and a feeling for the cost driversand -levers. Consider influence options on costsand create plausibility. Develop strategies toencounter implausibility or to optimize coststructure. (3) Think in total cost of ownership.Include thoughts on logistics chains, landed costview, value chain depth, distribution cost and -time, as well tradeoffs as for instance expeditingvs. on-time-delivery.

Expectation Group “Time Management &Efficiency”. The second most nominated expec-tation group with 124 nominations is dealingwith the time constraint and is defined withthe following thoughts: (1) Ensure fast projectexecution. (2) Consider product creation di-mensions: on-time-delivery, throughput time,lead time. Include most efficient and reasonableuse of capacities and resources.

Expectation Group “Organizational Aspects”.The other second most nominated expectationgroup with also 124 nominations is dealingwith the tactical issues of organizational aspectsand is defined with the following thoughts:(1) Apply cross functional setups in orderto ensure efficient processes and best possibleinformation exchange. (2) Ensure a structuredapproach. Consider capacity and competency.(3) Ensure information- and data integrity anddata completeness.

Expectation Group “Quality, Risk- & Ma-turity Management”. This expectation groupis risk-oriented. It was nominated 96 timesand is defined with the following thoughts:(1) Consider complexity in terms of productvariants, geography or restrictions. (2) Applyrisk mitigation strategies on technology, time,


Tab. 2: Themes of expectations (normalized on number of cases)

Thematic groupsof expectations

Current projectenvironment

(38 cases)

Training &conferences(18 cases)

Former projectenvironment

(7 cases)All cases(63 cases)

Cost 2.05 1.56 5.29 2.27Time Management & Efficiency 1.92 1.44 3.57 1.97Organizational Aspects 1.05 2.17 6.43 1.97Quality. Risk- & Maturity Management 0.76 0.72 7.71 1.52Function Analysis 0.97 1.22 2.29 1.19New Business Opportunities 0.74 0.11 0.43 0.52Hidden Agenda 0.50 0.06 0.00 0.32

quality, finance, procedures, processes and cost.(3) Consider application of maturity-levels withregards to project, product, production pro-cesses, vendors, customer acceptance, on timemarket-release, on-time product-development.

Expectation Group “Function Analysis”. Thisexpectation group with 75 nominations is thecore of any VE project. Within a given VE-project-environment, it is placed on fifth po-sition in terms of expectation frequency only.It is defined according to VE approach (com-pare Chapter 3), including function-fulfillment.This includes product functionality, productcharacteristics and requirements, and productperformance improvement.

Expectation Group “New Business Oppor-tunities”. This expectation group with 33nominations is challenge-oriented and definedwith the following thoughts: (1) New mar-ket: benchmarks, competitive analysis, marketrequirement definition, customer expectations.(2) Competitive advantage: clear leadershipon technology or cost, product performance,impact of optimized product creation processesor supply chain variants.

Expectation Group “Hidden Agenda”. Theleast, but still nominated expectation groupwith 20 nominations is dealing with mainly in-terpersonal and emotional issues, such as powergames or personal preferences. This could be forinstance: (1) Wishful thinking or self-fulfillingprophecies. (2) Reconfirmation of opinions. (3)“Who is better? Who is right?” in termsof negotiations, as technician, as purchasing,manufacturer, process specialist. (4) Defense oracquisition of area of influence.

7.3 Normalized View onthe Same Set of Data

Referring to Fig. 8, the huge influence of thelargest document group on the overall resultsbecame evident. In order to overcome thatshortcoming from the viewpoint of comparabil-ity between document sets, the author applieda simple form of normalization, as shown inTab. 2.

The normalization was conducted easily andstraight forward by dividing each frequency bycases per set, for instance “cost” on “currentproject environment”: 78/38 = 2.05. Theresult expresses the average frequency per case.Considering the different number of cases inthe new classification shifts the importance andtheir emphasis clearly, especially in between thedistinctive document sets.

This view results in higher amplitudes on thebandwidth of each document set. “Cost” still isthe dominant expectation group in the practicalgroups, while “organizational aspects” shapethe expectations and are of higher concernin the conferences and trainings. This gapindicates a mismatch in content between train-ings and practical applications. Future trainingdesign should take care for this gap.

With regards to the document set of “formerproject environment”, the amplitudes of thesingle nodes are much more spread (0.00 to7.71) than with the other sets (0.06 to 2.17). It isevident, that the group with the largest numberof cases is more leveled and shows a band widthof 0.50 to 2.05 only. The Question arises, wherethis effect might derive from? Is this influencedby the higher number of cases, are they “leveled

212 Erhard Teschl

out”? Future studies could consider this ideaand analyze accordingly. This question mightbe a fact to consider for future study-updates.

The first 3 expectation groups in the “formerproject environment”, quality, cost, and organi-zational aspects outweigh the remaining groups

by far. Only the expectation-group “time” staysin reach. The conclusion is, that in that givenenvironment a very strong emphasis was setinto these 4 expectation groups in literally everyproject. That could depend on the personalitiesof the project participants in that environment.

8 DISCUSSION

The analysis at hands is a first attempt todescribe upfront expectations into industrialVE projects. This study’s research question wasformulated as: “What was past industrial VEprojects participants’ real upfront comprehen-sive, contemporary and particular expectationin those projects?”

Answering this research question, this studyhas elaborated 7 groups of expectations and18 coded expectations along the course of thisqualitative content analysis as outlined in theChapters 6 and 7. They can serve as a prelim-inary checklist for future searches of spoken –and more important – unspoken expectations.

All selected projects serve as “naturallyoccurring data” (compare to Miles et al.,2014; Silverman, 2017; Saldana, 2016) for thequalitative part of this analysis. The initialbase population consists of 90 projects. Theyare settled in 16 different industries and ensurerichness (Silverman, 2017) and diversity of thedata base (Holstein and Gubrium, 2016).

In total, 185 recorded participants from var-ious functional backgrounds have contributedto the single cases. They cover nearly allfacets of functional areas and can truly beconsidered cross-functional. Some of them havecontributed to multiple cases. A larger non-replicable number of participants on top werenot recorded participants. They were partic-ipating on demand and on specific occasionsor questions, contributing from their functionalpoint of expertise.

Summarizing, both, data richness and datadiversity can be considered sufficient for thisresearch at hand.

VE as a cross-functional approach supportsdiversity. The diversity of this analysis’ inputdata was granted through the large number

of projects, covered industries and the diversefunctional and personal backgrounds of allparticipants. They span over a large arrayof rich and diverse viewpoints, inputs andinterests.

But there is a constraint on the data-set.The projects source is a restricted collectionfrom one source’s environment only: the author.Further research and analysis would need totestify this analysis’ conclusion on other inputdata from other environments, sources andindustries.

The findings of Fig. 8 and Tab. 1 and 2demonstrate that projects, which are settledwithin different industrial environments, mightresult in different upfront project expectations.Nevertheless, “cost”, “time”, “quality” and“organizational aspects” are of nearly sameimportance for either environment.

The findings of this study at hands cover uplargely with the findings of Frefer et al. (2018)on general project management critical successfactors. Also they see “time” and “cost” on mostfrequent positions with regards to demandedsuccess factors, and quality on position 4.

The assumption can be drawn, that expec-tations in projects and their critical successfactors are widely the same. On the otherhand, the nature of VE projects is mainlyproject management, as outlined in Chapter 3.Considering that, one should not be surprisedby this high degree of cope between the re-sults of those two studies – regardless of thedifferent environments, industries, participants,and their experiences and preferences. Thenature of VE projects demands generic projectmanagement as fundament. Hence the samecritical success factor can be applied, andtranslated into upfront expectations.


It also became evident, that the expecta-tions and content of training does not copewith real projects’ expectations. The identifiedgaps should be addressed and considered infuture training designs. Those gaps specificallyreferred to the absence of an exact customerdefinition and explanation of expected customer

behavior, but also in the expectation of “fastproject execution” and “new markets”. Whilethe author sees connection between exact cus-tomer definition and new markets, the “needfor project speed” remains a necessity, whichshould be analyzed in future research.

9 CONCLUSION

Summarizing, the author recommends fourmain further analysis directions and workpackages to address this research’s findings.First, the training content should expectation-wise be tailored to the practical needs. Second,further investigation would be needed to iden-tify ways to address the expectations in theproject speed factor. Exactness and rigor indefinition and usage of terminology has to beemphasized. VE projects are mainly projects.

But they offer their main distinctive factor: thefunction analysis, which strongly works with theimpact of abstraction and requires a proper andmost exact definition of customers and theirenvironment (market). Apply the identifiedexpectation codes, groups of expectations andtheir detailed description mandatorily in futureprojects. Refine the descriptions and checklistswith any new perspective in continuous im-provement loops.

10 REFERENCES

104th Congress, United States of America. 1996. PublicLaw 104–106; Title XLIII, Sec. 4306.

Al-Tmeemy, S. M. H., Abdul-Rahman, H. andHarun, Z. 2010. Future Criteria for Successof Building Projects in Malaysia. InternationalJournal of Project Management, 29 (3), 337–348.

Arber, S. 2001. Designing Samples. In Gilbert, N.(ed.). Researching Social Life, Chapter 5,pp. 58–82.

Atkinson, R. 1999. Project Management: Cost, Time,and Quality, Two Best Guesses and a Phenomenon,Its Time to Accept Other Success Criteria.International Journal of Project Management,17 (6), 337–342.

Bahia, F. D. and de Farias Filho, J. R. 2010. Analysisof Success Criteria in Engineering, Supplies andConstruction (EPC) Projects. Journal of Businessand Projects, 1, 49–67.

Bryde, D. J. and Robinson, L. 2005. Client VersusContractor Perspectives on Project SuccessCriteria. International Journal of ProjectManagement, 23 (8), 622–629.

Bryman, A. 2012. Social Research Methods. 4th ed.Oxford University Press.

Charmaz, K. 1996. The Search for Meanings –Grounded Theory. In Smith, J. A., Harré, R. andVan Langenhove, L. (eds.). Rethinking Methodsin Psychology, Chapter 3, 27–49.

Creswell, J. W. 2009. Research Design: Qualitative,Quantitative, and Mixed Methods Approaches. 3rded. Thousand Oaks, CA: SAGE Publications.

Czarniawska, B. 2014. Social Science Research –From Field to Desk. London: SAGE Publications.

Denzin, N. K. 1970. The Research Act: A TheoreticalIntroduction Sociological Methods Chicago: AldineTransaction.

Denzin, N. K. and Lincoln, Y. S. 1994. Handbookof Qualitative Research. 3rd ed. Thousand Oaks:SAGE Publications.

DIN – Deutsches Institut für Normung. 2002. EuropeanStandard. Berlin: Beuth.

Flick, U. 2008. Triangulation. 2nd ed. Wiesbaden: VSVerlag für Sozialwissenschaften.

Freeman, M. A. and Beale, P. 1992. MeasuringProject Success. Project Management Journal,23 (1), 8–17.

214 Erhard Teschl

Frefer, A. A., Mahmoud, M., Haleema, H.and Almamlook, R. 2018. Overview SuccessCriteria and Critical Success Factors inProject Management. Industrial Engineering &Management, 7 (1), 244.

Garel, G. 2013. A History of Project ManagementModels: From Pre-models to the Standard Models.International Journal of Project Management,31 (5), 663–669.

Gobo, G. 2007. Re-Conceptualizing Generalization:Old Issues in a New Frame. In Alasuutari, P.,Bickman, L. and Brannen, J. (eds.). The SAGEHandbook of Social Research Methods, Chapter 12,pp. 193–213.

Gomes, J. and Romão, M. 2016. Improving ProjectSuccess: A Case Study Using Benefits and ProjectManagement. Procedia Computer Science, 100,489–497.

Herstatt, C. and Verworn, B. 2004. The ‘FuzzyFront End’ of Innovation. In Bringing Technologyand Innovation into the Boardroom: Strategy,Innovation and Competences for Business Value,pp. 347–372.

Holstein, J. A. and Gubrium, J. F. 2016.Narrative Practice and the Active Interview. InSilverman, D. (ed.). Qualitative Research, Part II(Interviews and Focus Groups), pp. 67–82. 4th ed.London: Sage.

Ho, Y.-C. and Lin, C.-H. 2009. A ConcurrentFunction Deployment-based and ConcurrentEngineering-based Product Development Methodfor Original Design Manufacturing Companies.Journal of Engineering Design, 20 (1), 21–55.

Ibusuki, U. and Kaminski, P. C. 2007. ProductDevelopment Process with Focus on ValueEngineering and Target-Costing: A Case Study inan Automotive Company. International Journal ofProduction Economics, 105 (2), 459–474.

Jahn, T. 2010. Portfolio- und Reifegradmanagementfür Innovationsprojekte zur Multiprojektsteuerungin der frühen Phase der Produktentwicklung. PhDThessis, Universität Stuttgart.

Khosravi, S. and Afshari, H. 2011. A SuccessMeasurement Model for Construction Projects.In International Proceedings of EconomicsDevelopment and Research, 11, pp. 186–190.

Lamnek, S. 1995. Qualitative Sozialforschung: Band2 – Methoden und Techniken. 3rd ed. Weinheim:Beltz.

Lawrence D. Miles Value Foundation. 2016. Who WasLarry D. Miles? [online]. Available at: http://www.valuefoundation.org/Innovate-VM-Miles.htm[Accessed 2016, March 22].

Lim, C. S. and Mohamed, M. Z. 1999. Criteria ofProject Success: An Exploratory Re-examination.International Journal of Project Management,17 (4), 243–248.

Locke, L. F., Spirduso, W. W. and Silverman,S. J. 2013. Proposals That Work: A Guide forPlanning Dissertations and Grant Proposals. 6thed. Thousand Oaks: SAGE Publications.

Malterud, K. 2001. Qualitative Reserach: Standards,Challenges, and Guidelines. The Lancet, 358 (9280),483–488.

Mayring, P. 2010. Qualitative Inhaltsanalyse. InMey, G. and Mruck, K. (eds.). HandbuchQualitative Forschung in der Psychologie,pp. 601–613. Wiesbaden: VS Verlag fürSozialwissenschaften.

Miles, M. B., Huberman, A. M. and Saldana, J.2014. Qualitative Data Analysis: A MethodsSourcebook. 3rd ed. Thousand Oaks: SAGEPublications.

Mukhtar, M. M. and Amirudin, R. 2016. The SuccessCriteria of Public Housing Project in Nigeria.International Journal of Built Environment andSustainability, 3 (2), 102–110.

Müller, R. and Jugdev, K. 2012. Critical SuccessFactors in Projects: Pinto, Slevin, and Prescott –the Elucidation of Project Success. InternationalJournal of Managing Projects in Business, 5 (4),757–775.

Omer, H. H. 2017. Assessment of Projects UsingKey Performance Indicators in Oil and GasCompanies. MSc Thesis, University of Tripoli.

Pinto, J. K. and Slevin, D. P. 1988. Project Success:Definitions and Measurement Techniques. ProjectManagement Journal, 19 (1), 67–72.

Saldana, J. 2016. The Coding Manual for QualitativeResearchers. 3rd ed. London: SAGE Publications.

SAVE International. 2018. SAVE: AboutValue Engineering [online]. Available at:http://www.value-eng.org/page/AboutVE[Accessed 2018, March 30].

Silverman, D. 2017. Doing Qualitative Research. 5thed. London: SAGE Publications.

Springer Gabler Verlag. 2016a. GablerWirtschaftslexikon: Wertanalyse [online].Available at: http://wirtschaftslexikon.gabler.de/Archiv/54964/wertanalyse-v5.html[Accessed 2016, March 17].

Springer Gabler Verlag. 2016b. GablerWirtschaftslexikon: Projekt [online]. Available at:http://wirtschaftslexikon.gabler.de/Archiv/13507/projekt-v7.html [Accessed 2016, March 23].


Unger, D. and Eppinger, S. 2011. Improving ProductDevelopment Process Design: A Method forManaging Information Flow, Risks, and Iterations.Journal of Engineering Design, 22 (10), 689–699.

von Hippel, E. 1993. Wettbewerbsfaktor Zeit. ModerneIndustrie.

Yin, R. K. 2014. Case Study Research and Applications:Design and Method. 6th ed. Thousand Oaks:SAGE Publications.

AUTHOR’S ADDRESSErhard Teschl, Department of Economics, Faculty of Business and Economics, MendelUniversity in Brno, Zemědělská 1, 613 00 Brno, Czech Republic, e-mail:[email protected].

216

CALL FOR PAPERS

Your opportunity to publish research papers.

Open access journal for researchers and specialists from around the world.

European Journal of Business Science and Technology is an English-language, open access,double-blind refereed, multidisciplinary journal published by Mendel University in Brno,Faculty of Business and Economics.

The journal crosses traditional discipline boundaries, publishing original research papers in thefields of economics, business and technology.

The journal aids the application of theory developed from economics to the real business world.

The EJOBSAT aims primarily at economic policymakers, academic researchers, universityteachers and students, economists working in the public and private sectors.

Subjects covered by EJOBSAT

• Economics• Finance and Public Finance• Public Policy and Administration• Business, Management and Accounting• Marketing and Trade• Statistics and Econometrics• Business Law and Ethics• Information & Communication Technology• Research Methods in Economy• Public & Nonprofit Management• Tourism, Hospitality and Events• Entrepreneurship and Small Business Management

Journal information

• ISSN 2336-6494• Online submission, open access, double blind referred• Special offer – no publishing fees for current issues• EJOBSAT is published twice a year (submissions are accepted throughout the year)• Registered members are informed about new papers• Liberal copyright policy• Submissions are accepted in English, in Word and TEX/LATEX

www.ejobsat.cz

Date post:	28-Apr-2023
Category:	Documents
Upload:	khangminh22
View:	0 times
Download:	0 times

Does the Federal Constitutional Court Ruling Mean

Documents