The impacts of top management team characteristics on entrepreneurial strategic orientation The moderating effects of industrial environment and corporate ownership Lin Yang School of Management, Nanjing University of Finance & Economics, Nanjing, China, and Danni Wang W.P. Carey School of Business, Arizona State University, Tempe, Arizona, USA Abstract Purpose – The paper aims to empirically examine the questions of how top management team (TMT) characteristics, including TMT heterogeneity and vertical dyads differences between TMT and Board Director, influence entrepreneurial strategic orientation, as well as how industry environment and corporate ownership moderate those relationships. Design/methodology/approach – The paper designs the panel data on the listed companies of China’s Small and Medium-sized Enterprises Board for the period 2006-2010, and uses hierarchical regression analysis and grouping regression analysis when examining the relationships among variables involved. Findings – The paper provides empirical insights about how top management team (TMT) characteristics, including TMT heterogeneity and vertical dyads differences between TMT and Board Director, influence entrepreneurial strategic orientation, as well as how industry environment and corporate ownership moderate those relationships. It suggests that, except for TMT educational background, the heterogeneity of TMT age, gender, functional experience, and the vertical dyad differences between TMT and board chairperson significantly and positively impact ESO. Furthermore, industry environment and corporate ownership will moderate the relationship between TMT characteristics and ESO. Originality/value – This paper fulfills an identified need to study how top management team characteristics influence entrepreneurial strategic orientation, as well as how industry environment and corporate ownership moderate those relationships. Keywords Entrepreneurship, Corporate governance, Business strategy Paper type Research paper The current issue and full text archive of this journal is available at www.emeraldinsight.com/0025-1747.htm The authors are very grateful to receive the valuable suggestions and comments from Anne S. Tsui, Gerry Keim, Brian Boyd, Wei Shen, and David Zhu, Professors of W.P. Carey School of Business at Arizona State University. The authors also thank this journal’s two anonymous reviewers for their valuable comments and suggestions. The research was supported by the projects of the National Natural Science Foundation of China (Grant No. 70802016), the Ministry of Education of China (Grant No. 09YJC630114) and the Priority Academic Development of Jiangsu Higher Education Institutions (PAPD). All remaining errors, however, are solely the responsibility of the authors. MD 52,2 378 Management Decision Vol. 52 No. 2, 2014 pp. 378-409 q Emerald Group Publishing Limited 0025-1747 DOI 10.1108/MD-03-2013-0140
Transcript
The impacts of top managementteam characteristics onentrepreneurial strategic
orientationThe moderating effects of industrialenvironment and corporate ownership
Lin YangSchool of Management, Nanjing University of Finance & Economics,
Nanjing, China, and
Danni WangW.P. Carey School of Business, Arizona State University, Tempe, Arizona, USA
Abstract
Purpose – The paper aims to empirically examine the questions of how top management team(TMT) characteristics, including TMT heterogeneity and vertical dyads differences between TMT andBoard Director, influence entrepreneurial strategic orientation, as well as how industry environmentand corporate ownership moderate those relationships.
Design/methodology/approach – The paper designs the panel data on the listed companies of China’sSmall and Medium-sized Enterprises Board for the period 2006-2010, and uses hierarchical regressionanalysis and grouping regression analysis when examining the relationships among variables involved.
Findings – The paper provides empirical insights about how top management team (TMT)characteristics, including TMT heterogeneity and vertical dyads differences between TMT and BoardDirector, influence entrepreneurial strategic orientation, as well as how industry environment andcorporate ownership moderate those relationships. It suggests that, except for TMT educationalbackground, the heterogeneity of TMT age, gender, functional experience, and the vertical dyaddifferences between TMT and board chairperson significantly and positively impact ESO.Furthermore, industry environment and corporate ownership will moderate the relationshipbetween TMT characteristics and ESO.
Originality/value – This paper fulfills an identified need to study how top management teamcharacteristics influence entrepreneurial strategic orientation, as well as how industry environmentand corporate ownership moderate those relationships.
Keywords Entrepreneurship, Corporate governance, Business strategy
Paper type Research paper
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/0025-1747.htm
The authors are very grateful to receive the valuable suggestions and comments from Anne S. Tsui,Gerry Keim, Brian Boyd, Wei Shen, and David Zhu, Professors of W.P. Carey School of Business atArizona State University. The authors also thank this journal’s two anonymous reviewers for theirvaluable comments and suggestions. The research was supported by the projects of the NationalNatural Science Foundation of China (Grant No. 70802016), the Ministry of Education of China(Grant No. 09YJC630114) and the Priority Academic Development of Jiangsu Higher EducationInstitutions (PAPD). All remaining errors, however, are solely the responsibility of the authors.
IntroductionSince the 1970s, entrepreneurial strategic orientation (ESO) has become a centralconcept in the domain of corporate entrepreneurship, and received substantialconceptual and empirical attention (e.g. Covin and Mile, 1999; Rauch et al., 2009). ESOrefers to a firm’s strategic orientation, capturing specific entrepreneurial aspects ofdecision-making styles, methods, and practices (Wiklund and Shepherd, 2005). Assuch, it can represent how a firm operates rather than what it does (Lumpkin and Dess,1996). Thus, as the initiators and leaders of corporate strategic decision-making, topmanagers will undoubtedly play a dominant role during the formulation andimplementation of ESO. Extant research, based primarily on the perspective ofindividual top manager rather than top management team (TMT), has examined theeffect of individual decision maker on ESO during a certain particular time(e.g. Chaston and Sadler-Smith, 2012; Foo et al., 2006; Guo and Xue, 2011; Poon et al.,2006; Richard et al., 2009; Simske et al., 2010; Tarabishy, 2006). Further, even though afew piece of literature discussed the relationship between top management andentrepreneurial strategy, they dealt with the top management as a whole, and didn’tdeeply explore the effect of TMTs’ internal compositions and functioning. For example,Ling et al. (2008) examined the effect of TMT characteristics (including behavioralintegration, risk propensity, decentralization of responsibilities, and long-termcompensation) on corporate entrepreneurship (rather than ESO).
However, both entrepreneurship theory and business practices have shown that, toa great extent corporate entrepreneurship is not an individual activity but a complexdynamic system with the participation of many people, which will produce differentialeffects of different team compositions on entrepreneurial strategic activities. Forinstance, O’Reilly et al.(1993) pointed out that top teams, rather than top person, havethe greatest effects on organizational functioning. Gartner et al. (1994) observed thatthe field of entrepreneurship needs to account for the reality that “the entrepreneur inentrepreneurship is more likely to be plural,” and that “those individuals who mighthave a significant involvement in the venture” be included in theory development andresearch. West (2007) stated that new venture success often depends on how thefounding team collectively understands its world, estimates effects of possible actions,makes decisions, and allocates appropriate resources. On a practical level, academicswho teach entrepreneurship often stress the importance of the team in the start-upprocess, an emphasis that is also prominent in venture capitalists’ assessments of anew venture’s potential (Cyr et al., 2000; Zacharakis and Meyer, 1998). Furthermore,Microsoft’s leadership consists of an office of the president which not only includes theCEO and VPs but also some long-term employees as well and Martha Stewart’sOmnimedia has an all-female TMT consisting of the VPs for publishing, selling,merchandise and TV (Klenke, 2003).
Therefore, collective cognition in new ventures is fundamentally different fromindividual cognition or from the aggregation of individual cognitions, and becomes animportant research area yet to explore. Thus, entrepreneurship research shouldrecognize that entrepreneurs are likely to be many individuals rather than a singleindividual, and a focus on the characteristics of TMT rather than on the individual topexecutive (e.g. CEO) will yield stronger explanations of organizational outcomes inentrepreneurship. More importantly, what effects of TMT characteristics will have onthe entrepreneurial strategic activities and ESO in particular? Knippenberg and
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Schippers (2007) stated that, work group diversity, the degree to which there aredifferences between different group members may affect group process andperformance positively as well as negatively, yet much is still unclear about theeffects of diversity. Thus, it is very necessary to pay more theoretical and empiricalattention to the processes that are assumed to underlie the effects of diversity on ESOand the contingency factors of these relationships.
Furthermore, a striking feature of upper echelon studies in entrepreneurship thathave sought an explanation for corporate ESO is the tendency to decontextualize topmanagement teams – that is, not account for the idiosyncratic nature of each firm’sstrategy and the outside environment of the TMT. So far, little research on TMTcharacteristics and organizational outcomes has focused on transitional economiessuch as China in which environmental attributes are a large extent different from thewestern developed economies. As is well known, China is currently transforming fromcentrally planned to market-orientated economy, from a traditional to an informationaleconomy, and from monopolies to competitive industries, which no doubt willcontinuously promote the degree of economic activities of China’s inherent elements(Chow, 2005). It represents an important setting to examine the applicability of priorfindings in Western societies where individualism is widely accepted. China’s rapidpolitical, economic, and institutional changes accompanied by relativelyunderdeveloped factor and product markets yield a very suitable context forexploring the role of outside and inside environments. First, empirically examining themoderating effects of industry environment. In the 1980 s, industry and strategyscholars turned their attention to the research of Harvard Business School professorMichael Porter (1980, 1981) who applied the theories of industrial organization to thefield of strategic management. Industrial organizational models require companies tofind the most attractive industries to compete against (Backmann, 2002). Since mostfirms have similar strategic resources for moving between the different industries, theymust find the industries that offer the greatest potential for profits and learn how to usethose resources to implement entrepreneurial strategies determined by the industrialstructures (Feldman et al., 2005). Nowadays, China is adjusting, restructuring, andupgrading its industrial structures. Since different industries greatly vary in theireconomic features, competitive environments, and potential profits, the relationshipbetween TMT characteristics and ESO will be significantly influenced by theindustrial structures. Second, empirically examining the moderating effects ofcorporate ownership. Extant research has shown that corporate ownership is one of theimportant differences among different companies in China (Peng and Luo, 2000). Withthe deepening of economic reform, China has already formed the coexistence ofmultiple corporate ownerships including state-owned, private, and foreign-fundedenterprises, which vary greatly in their values and philosophies, decision-makingstyles, and management methods. Such omissions of moderating variables in priorwork create opportunities for further research. Thus, it is important to consider howcorporate ownership moderates the relationship between TMT characteristics andESO. Recognizing the above insufficiencies, this study was designed to furtherinvestigate the influence of a firm’s industry environment and corporate ownership onthe linkages between TMT characteristics and ESO in a transitional economy of China.
The article proceeds as follows. In the next section, we explain our theoreticalanalysis and assumptions, analyze the relational modes of TMT characteristics and
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ESO, and the moderating effects of industry environment and corporate ownership.Next, we delineate the research methodology and design, including sample selectioncriteria, data sources, variable measurement indicators, and analytical methods.Finally, we report our findings, discuss their implications, and point out the avenuesfor future research.
Theoretical background and hypothesesThis study mainly builds on the theories of upper echelons theory (Hambrick andMason, 1984), similarity-attraction paradigm, and self-categorization theory. Bysynthesizing the previously fragmented literatures, Hambrick and Mason (1984)proposed a more general “upper echelons perspective”. The basic assumption of thisperspective is that an individual’s demographic characteristics are indicators of thatperson’s underlying experiences, training, cognitive orientation, attitudes andopinions, which constitute the mental driving force that supports his or her strategicdecisions. Thus, the values and cognitive bases of TMTs greatly impact strategicdecision making, and executive team demographic characteristics can indicate theircognition and social psychology (Hambrick, 1992; Jackson et al., 1992; Mael, 1991). Thelatter two perspectives suggest that individuals classify everyone (includingthemselves) along salient dimensions such as age, sex, race, and education etc.Based on these classifications, others are deemed either similar (i.e. in-group members)or dissimilar (i.e. out-group members) to oneself and individuals typically exhibit biasin favor of the former. Demographic characteristics of individuals like age, gender,tenure, education and function have long been considered important variables inpsychological research[1]. To summarize, there are two kinds of demography: simpledemography and relational demography. Among which, Tsui and O’Reilly (1989)coined the term relational demography to refer to “the comparative demographiccharacteristics of members of dyads or groups who are in a position to engage inregular interactions”. This approach estimates the degree to which a person differsfrom another individual or a larger group with respect to demographic variables(e.g. gender, age, race, tenure) and examines how this dissimilarity influencesindividual attitudes and behaviors. Relational demography builds onsimilarity-attraction paradigm and self-categorization theory. Among which,self-categorization theory proposes that people may use social characteristics suchas age, gender, race, education, or organizational membership to define psychologicalgroups and to promote a positive self-identity. In this study, we explore therelationship between TMT characteristics and ESO from both simple demography andrelational demography, specifically including four indicators of age, gender,educational background and functional experience. Next, we analyze the impact ofeach indicator on ESO and further propose the related hypotheses.
Simple demography of TMT and ESOTMT age. Age is an important demographic variable in that it helps to predict anindividual’s non-work-related experiences. People of a similar age have suchexperiences in common, which leads to shared attitudes and beliefs (Rhodes, 1983).Diversity of age is expected to increase the variety of perspectives on strategic issues offacing a firm, thus stimulating the consideration of change, including ESO. Thus, anindividual’s age is expected to influence strategic decision-making perspectives and
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choices (Wiersema and Bantel, 1992). For TMT, different ages of their members haveexperienced different social, political, and economic environments and events, whichformed various attitudes, values, and visions that greatly influence their strategy,innovation, adjustment, and direction. In uncertain environments, a variety of attitudesand values can promote team creativity; thus teams with members of different ages aremore innovative (Bantel and Jackson, 1989). Age influences the formation of socialrelation contexts (Sessa and Jackson, 1995), so team members of different ages canform broader social relations. Since age heterogeneity increases the diversity of viewson strategic issues, diverse enterprises will be more encouraged to consider future ESO.Considering that ESO means to turn the business toward differently or even entirelynew fields, more uncertain business environments require more diverse informationand perspectives. Thus, the broader social relation context caused by age heterogeneitymay induce the enterprise to take a more proactive ESO. Therefore, we propose thefollowing hypothesis:
H1a. The greater the TMT age heterogeneity, the more aggressively the firm willadopt ESO.
TMT gender. Management and social psychology literatures have suggested that maleand female senior managers behave differently, and can influence corporate strategydifferently (Klenke, 2003). In fact, there are many differences between male and femaleexecutives concerning his/her entrepreneurial intentions as well as characteristics andbehaviors. The characteristics and performance of their ventures in a transitional contextdistinguish between direct and indirect gender effects (Mueller, 2004). Gender differencesamong executive teams should affect agency costs because companies with a higherproportion of male executives need more cash flow for investment strategic decisions(Jurkus et al., 2011). That is, the higher the agency costs, the more active expansionenterprises will prefer to act, which means the greater probability of adopting aggressiveESO. This positive correlation is more significant in highly competitive markets andwith imperfect external governance. Furthermore, male and female executives perceiverisk differently, and specifically male executives were more proactive, more attracted torisk, and more likely to show overconfidence (Peng and Wei, 2007). Thus, maleexecutives are more adventurous and implement relatively more aggressiveentrepreneurial strategic activities. Therefore, we propose the following hypothesis:
H1b. The higher the TMT proportion of male members, the more aggressively thefirm will adopt ESO.
TMT educational background. The upper echelon perspective suggests that formaleducational background may reflect the manager’s ability and skills base (Hambrick andMason, 1984). Prior studies have suggested a unique influence associated with an eliteeducation. That is, educational background influences strategic decision makingprocesses and outcomes (Hitt and Tyler, 1991). In our study, we focus on theheterogeneity of educational specialization to consider the influence of education.Wiersema and Bantel (1992) found that curriculum choices were associated withindividual personalities, attitudes and cognitive styles. Specifically, managers educatedin engineering generally can be expected to have a somewhat different cognitive basefrom someone educated in history or law (Tihanyi et al., 2000). Goll et al. (2008) statedthat there was a positive relationship between education level and a differentiation
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strategy and a negative relationship between education level and a low cost strategy.Also in dynamic uncertain environments, TMT educational background heterogeneitywill have more positive impact on differentiation strategies and more actively broadenthe strategic boundaries of the firm into new business areas. In considering a complexissue such as ESO, a top management team with executives representing a broad anddiverse educational base may be better equipped to deal with the wide range of relevantissues that must be considered. Therefore, we propose the following hypothesis:
H1c. The greater the TMT educational background heterogeneity, the moreaggressively the firm will adopt ESO.
TMT functional experience. Although the relationship between the functionalbackgrounds of top executives and organizational direction has not been established,empirical evidence validates the existence of patterns of associations betweenfunctional background backgrounds and business-level strategies (Peyrefitte et al.,2002). Miles and Snow (1978) originally proposed that the dominant coalitions ofefficiency-orientated “defender” firms would be comprised primarily of managers withthroughput-orientated backgrounds such as finance and production, functions mostcritical to reducing costs; while marketing-seeking “prospectors” would be led byexecutives with expertise in output-orientated skill such as marketing and productdevelopment, competencies necessary for market expansion. Subsequently, empiricalresearch has also found functional background heterogeneity or diversity in functionalexperiences to be positively associated with adaptation and change (Bluedorn et al.,1994). Functional background heterogeneity can bring the TMT technical, legal, andmanagement skills and the ability to form new perspectives and diversifiedinformation (Simons et al., 1999). The combination of functional backgroundheterogeneity brings new ideas to prevent short-sighted thinking, enhance innovativeproblem-solving ability, and solve nonstandard and non-routine complex problems(Jehn et al., 1999). The executive team can be seen as an information processing device(Harrison and Klein, 2007). TMT functional experience heterogeneity can increase therichness of information and views and thus prompt more proactive entrepreneurialorientations. Also, according to Contingency theory (Knockaert et al., 2011),homogeneous teams can better resolve routine problems, while heterogeneous teamsare more suitable for unconventional and new problems of uncertainty. Broad-basedfunctional experience may be necessary to handle the complexities of entrepreneurialactivities, so we expect to find that as a firm’s entrepreneurial activity increases, itsTMT will possess a wide variety of functional expertise. We expect that greater levelsof ESO will place more demands on executive skills, and that these skill requirementswill reflect diverse TMT functional experiences, regardless of the means a firm uses tocompete. Therefore, we propose the following hypothesis:
H1d. The greater the TMT functional experience heterogeneity, the moreaggressively the firm will adopt ESO.
Relational demography of TMT and ESOConceptually, it appears that relational demography can affect work perceptions andattitudes through both interpersonal attraction and the frequency of interactions.These effects are postulated to account for variance above and beyond that accountedfor by simple demographics (Tsui and O’Reilly, 1989). Thus, knowing the comparative
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similarity or dissimilarity in given demographic attributes of a superior and asubordinate or of the members of an interacting work team may provide additionalinformation about the members’ characteristics, attitudes and behaviors, and moreimportant, insight into the processes through which demography affects job outcomes.In China, during the power allocation of the listed companies, board of directors has thelargest decision-making power, and Chairperson is the highest representative of thedecision-making power of Board of Directors (Wong et al., 2004). Moreover, accordingto the relevant provisions of Chinese Company Act, Chairperson of the board is thelegal representative of China’s listed company and hold the real decision-makingpower. Thus, the difference between TMT and Chairperson of the board is one kind oftypical vertical dyad, and can reflect the internal composition and functioning of TMT.Therefore, this study further discusses the direct effect of TMTs’ vertical dyaddifferences on ESO from the perspective of relational demography.
To date, there are some research examining the vertical dyad of team or workinggroup. For instance, Tsui and O’Reilly (1989) found that both similarities and differencesmay have a positive effect in the superior-subordinate dyads of working group.Specifically, for working group in general, the greater the dissimilarity ofsuperior-subordinate dyads demographic characteristics, the more negative will be joboutcomes such as performance, affect expressed by the superior toward the subordinate,and role ambiguity and conflict as experienced by the subordinate. Further studies havestated that, the greater the dissimilarity in age, the higher the level of education, and thelonger the tenure between a superior-subordinate dyad, the higher will be the evaluationof the subordinate’s basic task and additional role activities (Tsui and Gutek, 1999; Tsuiet al., 2002). Then, Green et al. (1996) found that there was significantly positiverelationship between gender differences and leader-member exchange (LMX),specifically, the quality of LMX decreased when there were gender difference betweena supervisor and subordinates dyad. Epitropaki and Martin (1999) indicated that thegreater the tenure difference of manager-employee dyad, the lower will be thepsychological attachment of members of the working group. Bedi (2000) found thatdemographic differences had a significant effect on LMX. That is, both race and genderwere found to significantly impact the quality of exchange relationship in the dyadsobserved. Werbel and Henriques (1992) showed that status differences betweensupervisors and subordinates appear to influence conditions of trust. Specifically,supervisors are more concerned about conditions of trust that deal with supervisorydelegation, and subordinates are more concerned about the conditions of trust based oninteractional justice. In Chinese companies, the vertical dyad differences of TMTdemographic characteristics impacted corporate executives’ defections (Zhang and Liu,2009). Gender and age differences between the TMT and board chairperson significantlyand positively impacted financial restatement (He and Liu, 2010).
Usually, the vertical dyad differences between TMT and board chairperson may leadto some important consequences including role ambiguity and role conflict. That is, ifdissimilarities in demographic characteristics lead to low communication between themembers of TMT vertical dyad, role ambiguity should also be high. If dissimilarities indemographic background lead to differences in attitudes, values, and beliefs, role conflictshould also be high because the TMT vertical dyad members may have differentconceptions of the subordinate’s role requirements. Although the effects of demographicdifferences on role ambiguity and conflict may be observed with referents other than an
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organizational superior, we suspect the effects will be most salient in TMTs’ verticaldyads because board chairperson are the primary referent for defining performanceexpectations and standards for subordinates. Moreover, as stated above, BoardChairperson is the highest level in the company, which has more or better informationthan the other, and thus holds the advantages of asymmetric information. Theasymmetric information or information advantage of Board Chairperson can influencethe selection, appointment and dismissal of other top managers (including CEO), andfurther impact the corporate strategic behavior (Zhang, 2008). Especially, in differentinstitutional environment and management situations, the effect of TMT vertical dyaddifferences will be not the same size or even be amplified. Specifically, in relatively equalenvironments, people are less vulnerable to the impact of social status, but in Chinesesociety they are very sensitive to hierarchy and authority (Brew and David, 2004).Currently, China is still in a period of economic and institutional transformation, andChinese companies do not select their executives for market-oriented reasons only. Forexample, state-controlled listed companies have not fundamentally changed theirtraditional methods selecting and appointing administrative channel executives. That is,a large proportion of executives in state-controlled listed companies still occupy theadministrative level; in non-state-controlled listed companies, executives are oftenappointed by the willingness of the actual controller rather than through market-orientedselection. Therefore, the company’s institutional background may be more prominent inthe impact of executive position and demographic differences: the greater the typicalvertical dyad differences between the TMT and board chairperson, the more likely thechairperson will show arbitrariness and risk propensity in entrepreneurial strategicdecision making. Official positions within the organization can determine the formal roleof individuals in organizations, which play a key role on individual interactions. In termsof the relational demography, individuals at various positions show differentsignificances even if their sizes are equal, particularly in Chinese contexts, where theinfluence is subject to power distance (Hofstede, 2001). Therefore, the effects ofdifferences in executive positions and demographic characteristics may be moreprominent in the Chinese institutional background. That is, the greater the TMT verticaldyads differences of age, gender, educational background and functional experiences, thestronger the Chairperson’s information advantage, authority and influence will be.Therefore, we propose the following hypotheses:
H2a. The greater the vertical dyad difference of age between TMT and BoardChairperson, the more aggressively the firm will adopt ESO.
H2b. The greater the vertical dyad difference of gender between TMT and BoardChairperson, the more aggressively the firm will adopt ESO.
H2c. The greater the vertical dyad difference of educational background betweenTMT and Board Chairperson, the more aggressively the firm will adopt ESO.
H2d. The greater the vertical dyad difference of functional experience betweenTMT and Board Chairperson, the more aggressively the firm will adopt ESO.
Moderating effect of industry environmentExtant research indicated that the different properties of industry environment havebecome an important moderating factor for the relationships between some variables,
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including both the linkage between TMT heterogeneity and performance and thelinkage between leadership behavior and performance (Hmieleski and Ensley, 2007). Ingeneral, industry environment can be divided into two dimensions composed of stableand dynamic industrial environments, and the different types of industryenvironments have its own unique intrinsic properties. In a dynamic industryenvironment, opportunity is fleeting and it will be very crucial to rapidly formulate astrategic decision-making. Past research has indicated that the speed with whichstrategic decisions are made can affect various organizational outcomes (Judge andMiller, 1991). Decision speed can be especially important to new ventures, whichfrequently occupy dynamic environments and seek to exploit the nimbleness conferredby their relative smallness (Chen and Hambrick, 1995). For instance, Lumpkin andDess (1995) found simple strategy making, a decision-making outcome commonlyassociated with homogeneous teams, to be most effective in stable rather than dynamicenvironments. Goll et al. (2008) examined the relationships between managementcharacteristics and business strategy before and after airline deregulation. They foundthat there were significant management demographics-business strategy relationshipsin the deregulatory period. Generally, the regulatory environment simplifiesenvironmental contingencies and limits the number of possible strategic factors tobe considered. With deregulation, companies face new competitive pressures thatrequire a change in strategy as it disrupts the established behavior patterns andincreases managerial discretion (Kim and Prescott, 2005). Moreover, althoughheterogeneous teams are particularly effective in considering various options andunderstanding uncertainties, it will take a longer time for them to reach consensusbecause their different points-of-view may produce more conflict and slow thedecision-making process (Amason, 1996). Drawing on life course theory and humancapital theory, Forbes (2005) showed that entrepreneur’s individual characteristicscould determine the decision speed of new ventures. Specifically, the greater ofentrepreneurial TMT heterogeneity, the longer time it will be taken to search,communicate and integrate information between the members of TMT in thedecision-making process. Thus, the decision speed become relatively more slow andfurther the effect of such TMT will be greater in stable industry environment than indynamic industry environment.
However, under the current economic, social and cultural situation of China, peopleoften remains very sensitive to rank and authority figures. When vertical dyaddifferences of TMT become increasingly greater, Board Chairperson will have higherseniority and authority and play a more significant impact in strategicdecision-making process, which can reduce decision’s communication and discussionwithin TMT. Obviously, the effect of vertical dyad differences will be greater indynamic industry environment than in stable industry environment. Moreover, atearly stages of emerging industries, such as high-tech and pharmaceutical industries,product innovation and first-move are critical to competitive advantage (Lumpkin andDess, 2001). Emerging industries are more likely to have radical entrepreneurialorientations compared with the mature or declining industries such as food, beverage,and tobacco. In addition, the industries in early growth stages more commonly developand use new knowledge (William and Lee, 2009). Therefore, industry environment willaffect the intensity of ESO, which ultimately can be attributed to the size of industryenvironment uncertainties. Specifically, the greater enterprises face uncertain
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industrial environments, the more likely enterprises formulate ESO. On the contrary, inmore stable and predictable industry environments, the formulation of ESO isrelatively more difficult. Therefore, we propose the following hypothesis:
H3. Industrial environments will moderate the relationship between thecharacteristics of TMT and ESO. Specifically, TMT characteristics will bemore strongly associated with ESO in stable industry environment than indynamic industry environment.
Moderating effect of corporate ownershipWith the deepening of reform and opening to the outside world, China is experiencinggreater social and economic transformation, which gradually forms the coexistence ofmultiple economic compositions, including state-owned, private, and foreignindustries. By comparatively examining the background differences of ESO inChina’s transitional economies, Tan (2001) found that there are different thinking andaction tendencies of innovation and risk-taking between managers of state-ownedenterprises and private sector entrepreneurs when facing the identical environments.Peng et al. (2004) analyzed the relationship between corporate ownership structuresand strategic portfolios, which found that state-owned and private enterprises tend touse defensive and tentative strategies; collectively owned and foreign enterprises tendto adopt analysis-oriented strategies. Li (2007), adopting the enterprises of China’sBohai Rim Region as the sample, showed that there were different ESO amongstate-owned, private, and foreign-owned enterprises. Taken as a whole, state-ownedenterprises have lower ESO, especially in the dimension of risk taking when comparedwith foreign-owned enterprises and private-holding enterprises. Xu and Zhang (2008)found a big difference in the knowledge absorption and development between Chinesestate-owned and non-state-owned enterprises, so it is necessary to consider the natureof corporate ownership when considering knowledge innovation strategies. Martin(2008) studied 28,000 enterprises of 12 European countries and found thatforeign-funded enterprises are more innovative than local enterprises, and thisphenomenon is more pronounced in the newly joined member states of EU whereforeign-funded enterprises have a positive and important role in the flow of newproducts.
Currently, China is still in transition from a planned economy to a market-orientedeconomy. As fair resource distribution is not guaranteed in the market systems, firmsoften need the support of administrative institutions through nonmarket channels, andpersonal connections with governmental officials are often decisive in determiningwhich firms receive such support (Yang, 1994). Although the governments at all levelsare gradually transforming their functions, there’s no denying that the governmentsstill hold a large number of social resources and strong powers of resources allocation.For instance, in China, not only state-owned banks remain absolute monopoly forindirect financing channels of enterprises, direct financing channels by capital marketmust also go through strict check and approval of the China Securities RegulatoryCommission. Thus, many of the top leaders of private enterprises have to get somekind of political identities to ensure the necessary funds (Hu, 2006). Given the fact thattop management with political backgrounds can provide many conveniences for theirenterprises in the area of government procurement, tax incentives, and so forth, such
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enterprises tend to use the relational channels as part of business strategies ((Luo andTang, 2009). Therefore, we propose the following hypothesis:
H4. Corporate ownership will moderate the relationship between thecharacteristics of TMT and ESO. Specifically, TMT characteristics will bemore strongly associated with ESO in non-state-owned corporate ownershipthan in state-owned corporate ownership.
Data and research methodSample selection and data collectionExtant research has failed to provide a strictly uniform standard for defining the age ofentrepreneurial firms. For example, Forbes (2005) defined new venture to beindependent firms that had been in business ten years or less. Amason et al. (2006)suggested that entrepreneurial firms are those that have existed for fewer than sixyears; Zhang and Li (2010) identified eight years as an appropriate measure.Combining the extant literature with the nature of the research sample, we defineentrepreneurial firms as having been established no more than ten years. BecauseChina’s Small and Medium-sized Enterprises Board (CSMEB) was officially opened onJune 25, 2004, we selected the companies listed from 2006 to 2010 and establishedbefore December 31, 2005 in CSMEB. And the listed companies established before 1998were removed to ensure the samples to fit the entrepreneurial period. Our research dataare mainly from the Chinese WIND database. Since the data issued in this databasemust be checked and approved by China’s legal institution including China SecuritiesRegulatory Commission and its authorized agencies, the data quality to the greatextent has been guaranteed. Moreover, there were also some other research gatheringdata from a single database, for example COMPUSTAT (e.g. Wiersema and Zhang,2001). Thus, the data source of our study from WIND database is reasonable.
Collecting procedures of the data are as follows. First, we identified the sample listof the CSMEB issued before December 31, 2006 from WIND database, a total of 102.Second, using the time interval of year 2006-2010, we obtained 510 annual reports ofthe sample companies. Third, according to the nature of this study, we screened thesample companies and removed those with annual reports lacking R&D expendituredata and those that changed the Board Chairperson. The eligible sample included 88companies, a total of 352 with valid data. Finally, we acquired the sample data from theannual reports to measure the variables including TMT characteristics, ESO, industryenvironment, corporate ownership, and the related control variables. Furthermore, toexamine the dynamic effects and causal relationship of TMT characteristics on ESO,we constructed a panel data structure. Specifically, we used one-year lag period (yeart 2 1 to t) for the dependent variable to the other variables. That is, the dependentvariable ESO (year 2007-2010) lags one year behind the independent variables (TMTcharacteristics), moderating variables (industry environment and corporate ownership)and the other control variables (TMT size, organizational size, asset-liability ratio andpercentage of outside directors).
Measurement of variablesIndependent variables: TMT characteristics. In this study, we measure TMTcharacteristics from two aspects including TMT heterogeneity and vertical dyaddifferences between TMT and Board Chairperson. So far, no one has provided a
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uniform standard to define TMT members. Combining the generally accepted methods(Wiersema and Bantel, 1992; Fraser and Greene, 2006; Adams and Ferreira, 2009) withthe nature of sample firms, we defined the TMT as chairpersons, general managers,vice general managers, vice presidents, chief accountants/chief financial officers, andother top-two tiers of executives, and specifically designed four measurementindicators including TMT age, gender, educational background, and functionalexperience. Among which, the codification of the TMT educational background andfunctional experience is shown in Table I.
TMT heterogeneity was measured following the method recommended inupper-echelon research (Wiersema and Bantel, 1992; Hambrick et al., 1996). Given thecategorical variables of gender, educational background, and functional experience, weadopted Blau’s (1977) classification index. The computing formula is as follows: Blau’sCategorical Index ¼ 1 2 SPijt
2. Among which, Pijt represents the percentage of the i classof TMT members for t year in j company. For each categorical variable, the values ofTMT heterogeneity range from 0 (complete homogeneity) to 1 (complete heterogeneity).Following the previous research (Murray, 1989; Richard and Shelor, 2002; Tihanyi et al.,2000; Zimmerman, 2008), we measure age diversity and organizational tenure diversity bythe coefficient of variation, defined as the standard deviation divided by the mean, wherea high score indicates greater heterogeneity and a low score means greater homogeneity.
In addition, according to the aforementioned hypothesis, the effects of TMTheterogeneity and TMT vertical dyad differences on ESO have the consistent direction.Thus, when examining the moderating effect of industry environment and corporateownership, we sum up the Blau’s classification values of TMT heterogeneity variables,and construct a composite index of TMT heterogeneity ranging from 0 (completehomogeneity) to 4 (complete heterogeneity) by drawing on Hmieleski and Ensley’s (2007)method. The smaller value indicates the lower TMT heterogeneity, and vice versa.
Categories Value
TMT educational backgroundScience (science, agronomy, and medicine) 1Engineering 2Economics (theoretical and applied) 3Management (accounting, business and tourism management) 4Literature and art (philosophy, literature, history) 5Science of law (law) 6Other (education, military science, and non-education professionals) 7
TMT functional experienceProduction operations/manufacturing 1R&D 2Finance and accounting 3Marketing and public relations 4Legal 5Business management 6Administration (government staff, party, trade unions, etc.) 7
Sources: Hambrick et al. (1996), Zhang (2006), Tihanyi et al. (2000)
Table I.Codification of TMT
educational backgroundand functional experience
The impacts oftop management
389
When measuring the vertical dyad differences between TMT and Board Chairperson,we draw from the research of He and Liu (2010) and Zhang and Liu (2009) to designfour vertical dyad indicators composed of age, gender, educational background, andfunctional experience. Because of the inconsistency of coding scale standards oneducational background and functional experience in calculating the value of verticaldyad differences, we respectively standardized (Z-value) the code value of TMT’s(excluding chairperson board) average educational background and functionalexperience as well as Board Chairperson’ educational background and functionalexperience. Then we subtracte TMT’s standardized score from chairperson board’sstandardized score to count the value of vertical dyad differences. The smaller valuemeans the lower vertical dyad differences, and vice versa.
Dependent variables: ESO intensity. Drawing on Williams and Lee’s (2009) method,we calculate a composite measure of ESO intensity through two indicators includingthe proportion of company’s annual R&D expenditure for sales revenue and theproportion of company’s annual investment activities net cash flows for sales revenue.Those two indicators form four kind of different combinations in the two-dimensionalspace, and each point in the space reflects different status of ESO. First, we use xit torepresent the ration of R&D expenditure to sales revenue of the i company in year t, yit
represents the ratio of net cash flows from investing activities to sales income of the icompany in year t. Thus, the coordinate (xit, yit) reflects the status of ESO of the icompany in year t. Second, we calculate the Euclidean distance from the coordinate (xit,yit) to coordinate (0, 0), which means the intensity of ESO. The computing formula is asfollows:
Generally, the smaller values indicate weaker intensity of ESO, and the greater valuesmean stronger intensity of ESO. That is, the closer the ESO location is to (0, 0) intwo-dimensional space, the more conservative it is; the further the ESO is to the (0, 0),the more aggressive it is.
Moderators. Industry environment. According to the Listed Company IndustrialClassification Guidelines of China issued by Chinese Securities Regulatory Commissionin April 2001, the sample companies of our study are assigned to 15 differentindustries[2] based on the two-digital Standard Industrial Classification (SIC) code.Combining the research of Arthur (1996), Hmieleski and Ensley (2007), and Williamand Lee (2009) with the nature of the sample’s core business, the industry environmentwas divided into two dimensions composed of stable and dynamic environment. Thefirst includes A, C0, C1, C2, C4, C7, E, F, H, K, and M, a total of 65, and 55 companies areeligible. Thus, the valid sample data is 55 plus 4 ¼ 220:The latter includes C5, C6, C8,and G, a total of 37, and the qualified samples are 33 companies. Thus, the final validsample data is 33 plus 4 ¼ 132:
Corporate ownership. The company annual reports of the sample show that thetypes of controlling shareholder mainly include state-owned, private, foreign,collective, social groups, or the Employee Stock Ownership Plan Association. Onone hand, China is currently transforming from centrally planned to market-orientatedeconomy, which leads to the change of enterprise institutions from state-ownedinstitution to non-stated-owned institution. On the other hand, considering the number
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of samples and the basic requirements of statistical analysis, we divide corporateownership into two different types including state-owned and non-state-ownedenterprises. Among which, the government-controlled sample are classified asstate-owned enterprises (coded as the value “1”), and the sample controlled byorganizations or individuals (such as private, foreign, collective, social groups, ESOPAssociation) are classified as non-state-owned enterprises (coded as the value “0”).
Control variables. We added four control variables including TMT size,organizational size, asset-liability ratio and percentage of outside directors in ourstudy. First, TMT size, measured by the number of TMT members at the end of theprior year, was included as a control variable for two reasons: it has a strong influenceon the group’s level of diversity (Blau, 1977; Boone and Hendriks, 2009), since largerTMTs have more potential for dissimilarity (Wiersema and Bantel, 1992, p. 100); teamsize can be directly linked to group process and the organizational outcomes (Hambrickand D’Aveni, 1992). Second, organizational size was measured by the natural logarithmof total assets (Carpenter and Fredrickson, 2001; Richard et al., 2004). Third,Asset-Liability Ratio is a financial ratio that indicates the percentage of a company’sassets that are provided via debt. The higher the ratio, the greater risk it will beassociated with the firm’s operation. In addition, high debt to assets ratio may indicatelow borrowing capacity of a firm, which in turn will lower the firm’s financialflexibility and may influence the firm’s ability to allocate resource. Fourth, percentageof outside directors is another commonly used proxy for boards’ ability to perform thecontrol task effectively, measured by the number of directors not being executivemanagers (whether employed by the firm or not) divided by the total number ofdirectors on the board. This definition corresponds to previous studies of non-executivedirector (Fiegener et al., 2000). Corporate governance standards require publiccompanies to have a certain number or percentage of outside directors on their boardsas they are more likely to provide unbiased opinions and even monitor management[3](Byrd and Hickman, 1992). The general assumption is that the more outside directorswho are present on the board, the more involved is the board in monitoring managerialand company performance (Daily et al., 2002). Thus, the percentage of outside directorsmay negatively influence the intensity of ESO. That is, the higher the percentage ofoutside directors, the lower the intensity of ESO will be.
Analytical methodsFirst, we used Hausman statistics to test whether the individual random-effectsregression model or individual fixed-effects regression model should be constructed inthe study. The null and alternative hypotheses are as follows: H0: individual effects hadno significant relationship with regression variables (individual random-effectsregression model); H1: individual effects had significant relationship with regressionvariables (individual fixed-effects regression model). The test results showed that thevalue of Hausman statistics was 14.27 and the corresponding probability was 0.22,which was not significant at the 10 percent level; and the probability corresponded tothe comparative value of the intermediate results of Hausman test, both falling into the10 percent level, which was not significant. This indicated that the test results rejectedthe individual fixed-effects model and should establish individual random-effectsregression model.
The impacts oftop management
391
Second, we constructed a panel data random effects regression model, and usedhierarchical regression analysis to verify the direct effect of TMT characteristics onESO.
Finally, we used grouping regression analysis to verify the moderating effect of theindustry environment and corporate ownership. There are two reasons for adoptingthe grouping regression analysis. On one hand, the independent variables of TMTheterogeneity and the vertical dyad differences between TMT and Board Chairpersonare continuous variables, yet the moderators are categorical variables. Thus, whenverifying moderating effects, we should use grouping regression method rather thanthe usual multiplication of independent variables and moderators (Wen et al., 2005). Onthe other hand, we run the test on the grouping sample including stable industryenvironment vs dynamic industry environment and state-owned enterprises vsnon-state-owned enterprises, and the results indicated that the betas of the twoequations differ significantly.
Analysis and resultsDescriptive statistics and correlative analysisTable II shows the mean value, standard deviation, and Pearson correlation coefficientof the main variables. It shows that TMT age, gender, and functional experience werepositively related to the ESO intensity. However, education background showed nosignificant effect. The vertical dyad differences of age, gender, and professionalexperience between TMT and Board Chairperson were positively related to ESO.Moreover, the correlation coefficient between the independent or control variables wereless than 0.40; the eigenvalues of independent variables were not equal to 0, the valuesof condition index were less than 30, and the inflation factor (VIF) was less than 10.Those findings suggest no multicollinearity between the independent variables in thisstudy, and also show that TMT characteristics will influence ESO.
TMT characteristics and ESOTMT heterogeneity effects on ESO were analyzed by six models:
(1) Model 1 contains only control variables.
(2) Model 2 includes control variables and the TMT age heterogeneity variables.
(3) Model 3 includes the control variables and the TMT gender heterogeneityvariables.
(4) Model 4 includes control variables and the TMT educational backgroundheterogeneity variables.
(5) Model 5 contains control variables and the TMT functional experienceheterogeneity variables.
(6) Model 6 includes the significant variables that removed the non-significantvariables.
Using those models helped to compare the effect of each variable on the explainedvariance, and also the relative effect of the independent variables and the controlvariables on the dependent variable. Table III shows the results of the six regressionanalysis models.
MD52,2
392
Var
iab
les
Mea
nS
D1
23
45
67
89
1011
1213
14
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SO
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nsi
ty0.
176
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149
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212
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et2
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tra
tio
0.40
00.
170
20.
165
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0.06
42
0.01
70.
100
20.
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20.
007
20.
177
**
20.
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0.07
00.
186
**
0.36
3*
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13.
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cen
tag
eof
outs
ide
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rs0.
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92
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12
0.03
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20.
137
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0.08
62
0.08
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0.07
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ner
ship
0.27
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0.14
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0.16
3*
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20.
140
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22
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0.48
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20.
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0.17
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Notes
:n¼
352;
* p,
0.05
,** p
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01(t
wo-
tail
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st)
Table II.Means, standard
deviations, andcorrelations among
variables
The impacts oftop management
393
Var
iab
les
Mod
el1
Mod
el2
Mod
el3
Mod
el4
Mod
el5
Mod
el6
(Constant)
0.38
0(0
.168
)**
0.14
6(0
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)0.
126
(0.1
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2(0
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(0.1
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ze0.
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(0.0
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20.
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(0.0
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(0.0
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)A
sset
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tra
tio
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156
(0.0
65)*
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170
(0.0
65)*
**
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(0.0
62)*
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outs
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(0.1
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ner
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tyof
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nct
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5(0
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the
par
amet
ers
inb
rack
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are
Std
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rror
Table III.Results of regressionanalysis for TMTheterogeneity and ESO
MD52,2
394
From the Table III, for the control variables, the ratio of asset to liability hadsignificantly negative impact on ESO in all models. That is, the higher the debt ratio,the lower was the ESO intensity. Assets size in Models 3, 4, and 5 had a significantnegative impact; TMT size had no significant impact. Second, the results of maineffects regression analysis from Models 2 to 6 show that among the four indexes ofTMT heterogeneity, except for the heterogeneity of educational background, theheterogeneities of TMT age, gender, and functional experience had a significantlypositive impact on ESO. Also the indicators of R 2, DR 2 and the F-value and theirsignificant level showed that these regression models had an overall ideal effect. Theseresults verified H1a, H1b, and H1d.
According to the above analytical methods, we tested the effect of vertical dyaddifferences between TMT and Board Chairperson on ESO. Table IV shows theregression analysis results.
From the Table III, for the three control variables, except for TMT size, theorganizational size and debt ratio had a significant negative impact on ESO. That is,the greater the scale of organizational size and the higher the debt ratio, the lower wasthe ESO intensity. The regression analysis results of the main effect of Models 2 to 6show that, except for educational background, the other three vertical dyad differencesbetween TMT characteristics and Board Chairperson had a significant positive impacton ESO, and the model indicators of R 2, DR 2 and the F and their significant level showthese regression models had ideal overall effect. These results verify H2a, H2b, andH2d.
Moderating effect of the industry environmentWe used grouping regression analysis to respectively test the moderating effect ofindustrial environment on the relationship between TMT characteristics and ESO.Furthermore, when testing each group sample, we used hierarchical regressionanalysis. The first step included the control variables, and the second step was maineffects of the independent variables. Table V shows the main results of regressionanalysis of two group samples of stable and dynamic industrial environments.
In grouping the stable industrial environment sample, the regression modelexplained a variance of 19.0 percent of ESO ðF ¼ 38:016; p ,0.001), indicating thatthis model has ideal effect. Adding the variables of TMT heterogeneity to theregression equation, the explanatory power variance of the model on the ESO increasedby 14.4 percent ðDF ¼ 35:95; p ,0.001); adding the vertical dyad differences betweenTMT and Board Chairperson to the regression equation, the explanatory powervariance of the model on ESO increased by 2.8 percent ðF ¼ 4:362; p ,0.01).
In grouping the dynamic industrial environment sample, the regression modelexplained a variance of 10.9 percent of ESO ðF ¼ 4:817; p ,0.01), indicating idealeffect of this model. Adding the variables of TMT heterogeneity to the regressionequation, the explanatory power variance of the model on the ESO increased by 3.4percent ðDF ¼ 2:799; p ,0.01); adding the vertical differences between TMT andBoard Chairperson to the regression equation, the explanatory power variance of themodel on ESO increased by 8.7 percent ðDF ¼ 10:883; p ,0.001).
In the above two models, TMT characteristics have a somewhat differentlyexplanatory power on ESO. The explanatory power variance of TMT heterogeneity inthe stable industrial environment group (19.0 percent) is greater than in the dynamic
The impacts oftop management
395
Var
iab
les
Mod
el1
Mod
el2
Mod
el3
Mod
el4
Mod
el5
Mod
el6
(Constant)
0.38
0(0
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)**
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(0.1
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(0.1
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(0.1
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4(0
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)**
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(0.0
15)
20.
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(0.0
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et-D
ebt
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0.15
6(0
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)**
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.065
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.064
)*2
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6(0
.065
)2
0.17
0(0
.064
)**
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)**
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cen
tag
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outs
ide
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)2
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.E
rror
Table IV.Results of regressionanalysis for vertical dyaddifferences and ESO
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industrial environment group (10.9 percent), and the explanatory power variance ofvertical dyads differences between TMT and Board Chairperson in the dynamicindustrial environment group (16.1 percent) is greater than in the stable industrialenvironment group (7.4 percent). Table V also shows that in the two groups ofenterprises, the vertical differences characteristics between TMT and BoardChairperson have a significantly positive impact on ESO. The standardizedregression coefficient b of the TMT heterogeneity are 0.398 ( p ,0.001) and 0.200(p , 0:01) respectively, and the standardized regression coefficient b of the verticaldifferences between TMT and Board Chairperson are 0.171 ( p ,0.01) and 0.310(p , 0:001) respectively. Obviously, the regression coefficients b of TMTheterogeneity in the stable industrial environment group are greater than in thedynamic industry, and the regression coefficients b of the vertical difference betweenTMT and Board Chairperson in the dynamic industrial environment group are greaterthan in the stable industry. The above results verify H3.
Moderating effect of corporate ownershipBecause the moderator of corporate ownership is a categorical variable, and theindependent variable is a continuous variable, the analytical methods and proceduresof the moderator are the same as the above industrial environment. Table VI shows themain results of regression analysis on two groups of samples of state-owned andnon-state-owned enterprises.
In the group of state-owned enterprises, the regression model explained a varianceof 22.6 percent of the ESO ðF ¼ 21:304; p,0.001), indicating ideal effect of this model.Adding the variables of TMT heterogeneity to the regression equation, the explanatorypower variance of the model on the ESO increased by 18.5 percent ðDF ¼ 20:549;
TMT characteristicsStable
industryenvironment
Dynamicindustry
environment
Number of grouping sample 220 132
Step 1: Control variablesR-squared for explanatory variables 0.046 * 0.074 *
Step 2: Heterogeneity of TMTR-squared for explanatory variables 0.190 * * * 0.109 * *
Step 2:Vertical dyad difference between TMT and Board ChairpersonR-squared for explanatory variables 0.069 * 0.128 *
F-value of explanatory variables 5.778 * 8.979 *
DR 2 of explanatory variables 0.022 * 0.088 *
DF of explanatory variables 3.279 * 8.224 *
Standardized regression coefficientb of explanatory variables 0.148 * 0.357 *
Note: n ¼ 352; *p , 0.01, * *p , 0.001
Table VI.Results of moderatedregression analysis forcorporate ownership
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Discussion and implicationsThe impact of TMT characteristicsBased on the collective perspective (top management team), we build a theoreticalmodel of TMT characteristics and ESO, together integrating the moderating effects ofindustry environments and corporate ownership. We further use the sample data of theChina’s SME board-listed companies from 2006 to 2010 to test the research hypotheses.The results of regression analysis show that except for TMT educationalheterogeneity, all other TMT measurement indicators including age, gender, andfunctional experience, as well as the vertical dyad differences between TMT and BoardChairperson have a significantly positive effect on ESO. The results of this studybasically echo the conclusions of some extant research. For instance, Bedi (2000) foundthat the level of formal education for both supervisor and subordinates did notsignificantly affect the quality of exchange relationship. Klenke (2003) postulated thatit is not gender per se that accounts for differences in decision making among seniorfemale and male executives, but that four constructs, namely power, political savvy,conflict management and trust mediate the hypothesized relationships. He and Liu(2010) indicated that TMT educational heterogeneity in China’s listed companies hadno significant effect on organizational outcomes because the internal and externalgovernance environment determines the efficacy of executive education. But thefinding of this study had some difference with the result of Goll et al. (2008), whichindicated that TMT demographics had different impact on education level in regulatedand deregulated environments. Specially, TMT demographics have no significantrelationship to differentiation strategy under regulation, but differentiation strategyhas a significant positive relationship to mean education level in the deregulatedenvironment.
We argue that there are maybe two main reasons for the above results. On one hand,China is currently experiencing the transition from centrally planned economy to amarket-orientated economy, which will lead to great changes in economic and socialinstitutions. Institutional transitions can be defined as ‘fundamental andcomprehensive changes introduced to the rules of the game that affect organizationsas players’ (Peng, 2003). Thus, the current transformation of different institutions inChina can lead to many imperfections of the internal governance structure of Chinesecompanies controlled by large shareholders. For instance, the legitimacy-seekingimperatives highlighted by institutional theory are well documented by thenorm-formation processes during which various firms appoint outside directors.What is interesting and perhaps unique is that these processes, which took severaldecades in the US to unfold, took place in a short span of five years in China. Therefore,the internal supervision and coordination institutions of corporate governance shouldbe further improved. On the other hand, under the influence of traditional and uniqueChinese culture, people usually are very sensitive to rank and authority (Brew andDavid, 2004), and also companies have yet not formed a high quality of corporategovernance culture. Obviously, all of those factors may constrain TMT educationalbackground from playing a key role in the process of entrepreneurial strategicdecision-making.
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Moderating effect of the industry environmentThe empirical results of this study support the hypothesis that industry environmentwill moderate the relationship between TMT characteristics and ESO. Morespecifically, the moderating effect of TMT heterogeneity in stable industryenvironments ðb ¼ 0:398; p ,0.001) is greater than in the dynamic industryenvironment ðb ¼ 0:200; p ,0.01), and the moderating effect of vertical dyaddifferences between TMT and Board Chairperson in the dynamic industryenvironment ðb ¼ 0:310; p ,0.001) is greater than in the stable industryenvironment ðb ¼ 0:171; p ,0.01). The findings of this study to a certain extentechoed the research conclusions of Goll et al. (2008), which indicated that TMTdemographics have no significant relationship with differentiation strategy underregulation, but in the deregulated environment, differentiation strategy has amarginally significant negative relationship with mean age/tenure. Generally, thederegulated environment allows top managers more options to make choices than theregulated environment (Goll et al., 2008). Therefore, different natures of the industrycan influence or even determine the corporate strategic-making behavior. In China,during the current economic and institutional transition period, many industries haveor are going through the transition from regulation to deregulation, which makes thesample enterprises of this study in different industrial environments including bothregulatory and deregulatory industries, and thus have not completely been consistentwith the Goll et al.’s (2008) research. Moreover, in dynamic industry environments, thespeed of strategic decision-making will be particularly important because businessopportunity is fleeting. Strategic decisions must be made rapidly before businessopportunities disappear or competitors can outpace them in applying new technologies(Stevenson and Gumpert, 2001). Generally, greater TMT heterogeneity means that itwill take more time and effort to gather, communicate, and integrate informationduring the process of strategic decision-making, which indicates that heterogeneousTMT can be more effective in stable industry environments than in dynamic industryenvironments. Furthermore, under the current economic and socio-cultural context ofChina’s transitional period, rank and authority figures are still very sensitive[4]. Sowhen TMT and Board Chairpersons have greater vertical dyad differences, BoardChairperson generally hold stronger power of strategic decision-making, which canreduce the time for internal communication and discussion during the process ofdecision-making. Therefore, the vertical dyad differences have a stronger moderatingeffect in dynamic industry environments than in stable industry environments.
Moderating effect of corporate ownershipOur results also support the hypothesis that different corporate ownerships willmoderate the relationship between TMT characteristics and ESO. When examiningTMT characteristics and ESO relationship, we find that state-owned enterprises have agreater moderating effect ðb ¼ 0:447; p ,0.001) than non-state-owned enterprisesðb ¼ 0:270; p ,0.001). Also, when examining the relationship between vertical dyaddifferences and ESO, we find that state-owned enterprises have a greater moderatingeffect ðb ¼ 0:357; p ,0.01) than non-state enterprise systems ðb ¼ 0:148; p ,0.01).We argue that the unique Chinese context of transforming from a planned economy toa market-orientated economy may account for those results. That is, although theChinese governments at all levels are gradually changing or reducing their functions,
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undeniably they still hold a large number of social resources and much power. Forexample, finance is important for the development of entrepreneurship, but in Chinastate-owned banks still absolutely monopolize indirect financing channels, and theChina Securities Regulatory Commission and other related regulatory departmentsmust scrutinize all direct financing through the capital market. Therefore, manyprivate enterprises have to hold some political identity if they are to obtain the fundsthey need for their enterprise development (Hu, 2006; Zhang and Zhan, 2006).Considering the lack of sound legal systems and expensive transaction costs,enterprises tend to use relational channels as part of their business strategy (Luo andTang, 2009). Wu et al.’s (2008) empirical studies reached similar conclusions, whichshowed that top managers of state-owned enterprises may diversify the relativelyweak corporate governance structure to make corporate management more complex tohighlight their value, and thus obtain higher remuneration and internal managementauthority. Executives of state-owned enterprises have a stronger political network andplay a weak role in promoting the business and geographic diversification strategies.Therefore, higher entrepreneurial TMT heterogeneity and typical vertical dyaddifference may form a broader “key factors influencing diversification or specializationstrategy – management resources” (Perry et al., 2005) or political networks. The moreextensively corporate executives manage resources or political networks, the strongerwill be the political status of the network members and the greater the social impact.Compared with private enterprises, state-owned enterprises are more likely to breakthrough various barriers and venture into new industries and new areas, and have agreater impact on ESO.
Contribution, limitations and future directionFour aspects of theoretical contributions can be derived from our review and analyses.First, we empirically explore the role of the TMT characteristics on ESO. Extantentrepreneurship research is predominantly focusing on one top owner/founder/manager of the firm rather than the team (e.g. Chaston and Sadler-Smith, 2012), whichis indeed inappropriate because most entrepreneurial companies are founded by teams(e.g. West, 2007; Leary and DeVaughn, 2009). Given the fact that different TMTs’characteristics, including the degree of team heterogeneity and vertical dyaddifferences, will have different efficacy on ESO in different context, this study canimprove the understanding of the influence of entrepreneurial strategic decisionmaking, and further broaden the theoretical research depth of ESO. Second, althoughthere are three common perspectives or methods of measuring a firm’s ESO, includingmanagement perceptions regarding entrepreneurial processes; entrepreneurial firmbehavior; and archival data denoting prior resource allocations as indicators of anentrepreneurial posture, and each one has its benefits and drawbacks[5], researchevidence to date mainly focused on the first two perspectives. However, Mintzberg(1978) defined strategy as the pattern in a firm’s resource allocation. Zhang andRajagopalan (2010) conceptualized strategic change (reflecting the nature of ESO) asthe variation over time in a firm’s pattern of resource allocation in key strategicdimensions that goes beyond industry-wide changes in these dimensions. In essence,strategic variation (including ESO) refers to the extent to which a firm’s patterns ofresource allocation in key strategic dimensions change over time (Carpenter, 2000).There is no doubt that it will be high value to explore ESO from the perspective of
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resource allocation. Third, consistent with the concept of “fit” in the moderationperspective, the impact that a predictor variable has on a criterion variable isdependent on the level of a third variable called the moderator (Venkatraman, 1989).Specifically, the role of “fit” in explaining the extent to which the relationship of TMTcharacteristics to ESO is contingent on the business context in which these processesoccur. Therefore, the study, combing the features of entrepreneurial activities withChina’s unique context, constructs two important moderators of industry environmentand corporate ownership and empirically examines their moderating effects, which canform more specific and valuable conclusions in different context. Finally, althoughdepartures from entrepreneurial TMT often reflect the difficulty teams have in comingto agreement when differing points-of-view are present (Ucbasaran et al., 2003), theaddition of team members can inject novel experience and new understandings into theteam’s collective deliberations. Thus, the study also discusses “time” as an importantcontextual factor in ESO research since entrepreneurial TMTs do not remain staticover time. More specifically, this study designs the panel data (rather thancross-sectional data like many other similar researches) to analyze the relationshipamong the related variables, which to some extent reflects the dynamic effects andcausal relationships between the variables involved.
As with any study, there are also some limitations that should be recognized. First,we test the related hypotheses by adopting secondary data from the listed companiesof Chinese Small and Medium-Sized Enterprises Board. Although the research samplebasically belong to the nature of entrepreneurial period by using strict controllingrequirements and methods, future research can further adopt primary data bydesigning appropriate questionnaires. Second, researchers might consider othermeasurements of variables. For example, drawing on social psychology,questionnaires can also be used to probe entrepreneurial TMT characteristics.Again, to measure industry environment, we chose the Chinese Listed CompanyIndustrial Classification Guidelines issued by the China Securities RegulatoryCommission in April 2001. Future research can draw on the methods of otherresearch (e.g. Rueda-Manzanares et al., 2008) to measure the construct.
Notes
1. Although there were also some critiques against using demographic indicators as proxies forbehavior (Gabrielsson and Huse, 2004; Gabrielsson, 2007), Hambrick and Mason’s (1984)suggestion that demographic characteristics serve as proxies for the beliefs, values, andcognitions of managers paved the way for a large number of subsequent empirical studies.While not perfect substitutes for the underlying constructs, demographic variables offer theadvantage of being objective, testable, and comprehensive (Hambrick and Mason, 1984;Pfeffer, 1983).
2. Specifically, the 15 different industries include: a agriculture, forestry, animal husbandry,fisheries; C0 food, materials; C1 textile, services, fur; C2 materials, furniture; C4 petroleum,chemical, plastics, plastic; C5 electronics; C6 metal, nonmetal; C7 machinery, equipment,instruments; C8 medicine, biological products; E construction industry; F transportationindustry; G industry; H wholesale and retail trade; K social services; and M comprehensive.
3. For example, according to the Guidelines for Introducing Independent Directors to the Boardof Directors of Listed Companies enacted by China Securities Regulatory Commission (CSRC)in 2001, all listed companies are required to introduce independent (outside) Directors to the
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Board, and by 30 June 2003, at least one-third of the Board should be independent directors(per Guidelines, see CSRC, 2001).
4. More specifically, being older in a group dominated by younger members will lead to anincreased propensity to leave among older individuals, and within top management teams itis the relative difference in ages within groups that predicate individuals’ leaving, not theindividuals’ ages per se.
5. See Lyon et al. (2000) for the definition and detailed review of each perspective.
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Further reading
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Teng, B.S. (2007), “Corporate entrepreneurship activities through strategic alliances:a resource-based approach toward competitive advantage”, Journal of ManagementStudies, Vol. 44 No. 1, pp. 119-142.
About the authorsLin Yang is an Associate Professor in the School of Management at Nanjing University ofFinance & Economics, Nanjing, P.R. China. He gained his PhD from Nanjing University in 2006,and finished his post-doctoral research at FuDan University in 2010. He was a one-year visitingscholar of the W.P. Carey School of Business at Arizona State University from March, 2011 toMarch, 2012. His research interests focus on managerial cognition, enterprise strategic changeand entrepreneurship management in the context of transitional economy. Lin Yang is thecorresponding author and can be contacted at: [email protected]
Danni Wang is a Research Associate and PhD student of Management Department of W.P.Carey School of Business at Arizona State University, USA. She gained her Masters’ degree fromGuanghua School of Management at Peking University, Beijing, China in 2009. Her researchinterests mainly include leadership process; team and group, etc.
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