Determinantsofinvolvementin mobilecommerce.Themoderating ... · [69 ] 12 69...

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january · april 2012 · esic market

Determinants of involvement inmobile commerce. The moderatingrole of gender1

San Martín-Gutiérrez2, S., López-Catalán3, B. and Ramón-Jerónimo4, M.A., 2012, “Deter-minants of involvement in mobile commerce. The moderating role of gender”. EsicMarket,Vol. 141, pp. 69-101.

AbstractMobile phones are one of the latest marketing tools that consumers areusing to make their purchases, a fact that entails a revolution in the wayfirms are relating to their clients. It therefore becomes essential to under-stand the driving forces behind consumer involvement in this purchasechannel; an aspect that has not been previously studied in the context ofmobile commerce. In this pioneering work, we analyze the role that isplayed by perceived risk in mobile purchasing, permission marketing andconsumer propensity towards new technologies as antecedents of con-sumer involvement. Based on the information gathered from a sample of674 mobile users, our work highlights the importance of these variables asfacilitators of involvement, as well as the need for firms to consider genderdifferences in the development of their strategies.

Key words: Mobile Commerce; Involvement; Risk; Permission-based Mar-keting; Personal innovativeness in the domain of information technologyinnovativeness; Gender.

JEL code: M31.

Sonia San Martín-GutiérrezUniversity of Burgos

Blanca López-Catalán and M. Ángeles Ramón-JerónimoUniversity Pablo de Olavide

(1) This work was

supported in part by

the Consejería de

Educación from Junta

de Castilla y León

(Spain) under Grant

V02H.03.

(2) Universidad de

Burgos. Departamento

de Economía y

Administración de

Empresas. Facultad de

Ciencias Económicas.

E-mail:

[email protected]

(3) Universidad Pablo

de Olavide, Sevilla.

Departamento de

Organización de

Empresas. Facultad de

Ciencias

Empresariales. E-mail:

[email protected]

(4) Universidad Pablo

de Olavide, Sevilla.

Departamento de

Comercialización e

Investigación de

Mercados. Facultad de

Ciencias

Empresariales. E-mail:

[email protected]

1. IntroductionOne of today’s commercial challenges is the possibility of mobile commerce,now that Internet commerce has to some extent consolidated its presence inour society. Even though communication is the primary function of themobile phone, in recent years firms have added numerous functions, as theyare aware of its marketing potential, thanks to its ubiquitous, interactivequalities, ease of personalization and convenience. The penetration of mobilephones in society is undeniable, borne out by the constant increase in thenumbers of mobile phone users in the world and their growth forecast.

The development of the mobile phone as a new marketing tool is recentand it presents enormous possibilities as a purchasing channel. As thischannel is at an early stage of development, it is essential that firms under-stand the factors that might involve consumers in its expansion: in otherwords, a classification of the determinants of their involvement. Alongthese lines, Bloch (1981) and Houston and Rothschild (1978) proposegrouping the determinants of involvement into: personal characteristics ofthe consumer (personal innovativeness with information technology);attributes of the product (which reflect the perceived risk) and the contextof the purchasing situation (permission marketing).

We are aware of studies that have analyzed the moderating role of gen-der in the use of new technologies and in the context of on-line sales (Mit-tal and Kamakura, 2001; Floh and Treiblmaier, 2006) and of some worksthat treat the moderating role of gender in the context of mobile commerce(Jayawardhena et al. 2010). Thus, we present a parsimonious model thatincludes three determinants of involvement in mobile commerce and ofgender as a moderating factor.

Our work has a two-fold general objective: on the one hand, we wishto determine the roles played by perceived risk, permission marketing andpersonal innovativeness with information technology and their influenceon involvement in mobile commerce and, on the other hand, the extent towhich gender differences are present in the role played by these three deter-minants in involvement, underlining their moderating role.

To achieve our objective, the second section describes a theoreticalframework using the model’s variables: involvement as the dependent vari-


determinants of involvement in mobile commerce.the moderating role of gender

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able, and perceived risk, permission marketing and personal innovative-ness with information technology as the independent variables. Likewise,the third section is concerned with studying the moderating role exercisedby gender in the relations between the aforementioned variables. Havingproposed the hypotheses and laid out the global model, we move on to thefourth section that centres on the details of the empirical study. Finally, thefifth section contains the principal conclusions, professional implications,limitations and future lines of research.

2. Involvement in mobile commerce. Conceptualizationand determinants

2.1. Involvement in mobile commerceIn recent decades, involvement has been considered one of the explanato-ry variables of individual behaviour. In a transactional context, individualsfacing the same purchase decision are expected to behave in different waysaccording to the degree of their involvement (Dholakia, 2001). For exam-ple, an implicated consumer gathers information beforehand and evaluatesthe available information in a more critical way (Celsi and Olson, 1988;Clarke and Belk, 1979). Equally, individual involvement determines theduration, the intensity and the complexity of the purchasing decision-mak-ing process (Howard and Shet, 1969) and the purchasing experience(Wakefield and Baker, 1998).

The conceptualization of involvement has been an important and con-troversial theme in marketing research (Andrews et al. 1990) and we canfind multiple definitions (see Chérif, 2001). Zaichkowsky (1985, p. 32)defines involvement as “a person’s perceived relevance of the object basedupon inherent needs, values, and interests”; for Celsi and Olson (1988, pp.211) “involvement is said to reflect the degree of personal relevance of thedecision for an individual in terms of basic values, goals and self-con-cepts”. Taking the proposals of Celsi and Olson (1988) and Zaichkowsky(1985) as a reference, we define individual involvement in mobile pur-chasing in this research as a stable and long-lasting state of personal rele-vance and interest in the (mobile) channel used for the purchase. As a

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result, we do not consider so-called situational involvement applicable asdefined by Bloch (1981), given that it refers to a concrete, time-bound sit-uation, applied to a specific context, the character of which is provisionaland that will diminish when the objective of purchasing a particular prod-uct or service has been achieved.

Nuns (2005) highlights the importance of involvement in the manage-ment of on-line client relations, arguing that the level of client involvementin the purchase will have a considerable effect on the client’s desires toestablish communication with the firm, which will benefit from such com-munication to the extent that it is able to identify each client’s level ofinvolvement and adapt the conversation accordingly.

Once involvement in the mobile purchase is defined and its importanceunderlined, we then centre on the study of its three key determinants: per-ceived risk related to the product and the channel; marketing permissionrelated to the firm; and personal innovativeness in the domain of informationtechnology related to the personality of the consumer. Thus, with regard tothe individual, we will consider two internal determinants –risk and propen-sity to use technologies – and another external one –permission marketing.

2.2. Determinants of involvement in mobile commerceAndrews et al. (1990) propose the existence of factors that are situationalor associated with the purchase decision, and personal factors asantecedents to involvement. In line with this proposition, and in accordancewith the objectives of this research, we focus on the study of risk in mobilepurchasing as a determinant of involvement, and we also analyze how indi-vidual profiles affect the involvement of purchasers in mobile commercethrough their personal innovativeness with information technology. Like-wise, we include permission marketing as a further determinant that refersto the selling firm. Our proposal follows the classification of determinantsof involvement that were previously suggested by Bloch (1981) and Hous-ton and Rothschild (1978) grouping the determinants of involvement intoindividual consumer characteristics (personal innovativeness with informa-tion technology); product attributes (reflected in perceived risk) and thecontext of the purchasing situation (permission marketing).

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Perceived risk in mobile commerceThe theory of perceived risk has been used to explain the behaviour of theconsumer ever since the 1960s (Taylor, 1974). Since the first investigationsinto risk, it is normal to use the probability of obtaining a negative resultto conceptualize risk (Bauer, 1960; Taylor, 1974; Peter and Ryan, 1976).Perceived risk, seen as uncertainty with regard to results and the costs ofthe purchasing decision, is already used in the context of distance com-merce (Campbell and Goodstein, 2001; Featherman and Fuller, 2002;Gefen et al., 2002).

It is acknowledged that consumers associate more risk with distancepurchasing decisions than with purchases from a physical outlet (Tan,1999; Cunningham et al., 2005). In the context of mobile marketing, it isalso suggested that risk perception is greater in mobile banking than in tra-ditional banking based on personal interaction (Kim et al., 2009; Koenig-Lewis et al., 2010). Distance purchasing entails greater negative resultsthan traditional selling, because the difficulty of evaluating a product orservice is greater, there are no tangible clues about product quality or face-to-face interaction and the purchase is affected by problems of security andprivacy (Ha, 2004; Laroche et al., 2005; Li and Yeh, 2010).

One of the fields in which risk in mobile purchasing has been studiedmore than any other is banking. Its main types of risk are those related toprivacy and security, the reliability of the tool used for the purchase(mobile telephone) and the control perceived by the individual when nego-tiating the use of a new technology (Laukkanen and Kiviniemi, 2010). Fur-thermore and in relation to mobile commerce, it has also been found thatif a technology fails to provide the expected result, it will result in a lossfor the consumer (Im et al. 2008; Laukkanen and Kiviniemi, 2010).

It should be pointed out that many works studying perceived risk in thecontext of mobile marketing treat it essentially as a fear of providing per-sonal or banking data to a firm and of loss of privacy (Bauer et al., 2005;Gao et al., 2010; Riquelme and Ríos, 2010). However, we believe that theconceptualization of risk, based on concerns over privacy and security,made more sense at the start of electronic marketing, and for data trans-ferred through impersonal mediums such as a computer. Risk considera-

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tion, therefore, has changed since on-line transactions have become morepopular, moving from greater concern over fraud to other types of riskrelated both to cognitive and to affective factors (Wu and Wang, 2005) andderived from product quality. In fact, the proliferation of social networksis an indicator of diminished concerns over privacy and security (Gao etal., 2010). Therefore, in this work we shall treat the risk that is related tothe anxiety that a mobile purchase produces in the consumer jointly withthe risk that the mobile purchase will not turn out as expected.

The literature indicates that perceived risk is a factor that affects in asignificant and negative way the intention to use or the acceptance ofmobile-telephone purchasing (Bauer et al., 2005; Meuter et al., 2005; Wuand Wang, 2005; Wessels and Drennan, 2010; Riquelme and Ríos, 2010);however, we have to point out that we are unaware of any study that meas-ures and relates perceived risk with involvement in mobile-telephone pur-chasing.

Risk relates to variations in the intensity of involvement, especially inthe case of innovations or immature technologies, where consumers haveno prior experience with the new product, service or type of purchase andperceive a high-risk situation (Wu and Wang, 2005; Laukkanen andKiviniemi, 2010). Thus, the outcome of the adoption process can result inthe rejection of innovation (Bauer et al., 2005). Consequently, in this workour first hypothesis proposes a negative relation between risk and involve-ment:

H1: Perceived risk has a negative influence on consumer involvement inmobile commerce.

Permission marketingNot all advertising sent to the consumer is desired or voluntarily receivedand, in consequence, the concept of permission marketing is essential toachieve positive consumer attitudes towards the selling firm, which finallyleads to a greater distance-purchasing intention (Reutterer and Walter,2009). Permission marketing consists in stimulating bidirectional commu-nications between the consumer and the marketing personnel of a firm

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(Jayawardhena et al., 2009; Barwise and Strong, 2002). It implies the per-sonalization of messages in the timing, localization and content of theinformation. In Europe, marketing managers have to request the expressconsent of the consumer, before they may be included in a programme ofmobile marketing (Kautonen et al., 2007, cited in Jayawardhena et al.,2009). Specifically, in Spain, Law 29/2009, which entered into force onMarch 1, 2010, amended the legal regulations on advertising to improvethe protection offered to consumers and users. This law regulates practicesof “aggressive harassment”: “making unsolicited and repeated proposi-tions by telephone, fax, electronic mail or other means of distance com-munication«. It is especially opportune at this time to observe how per-mission marketing can benefit firms through the involvement ofconsumers.

The literature relating to privacy in the use of mobile telephones hasstudied “spam” and the invasion of privacy as central themes connected tothe willingness of the consumer to accept mobile advertising (Barnes andScornavacca, 2004; Grant and O’Donohoe, 2007; Leppaniemi and Kar-jaluoto, 2005; Gao et al., 2010). There are few empirical works on per-mission marketing, and even fewer that examine the context of mobilemarketing (Jayawardhena et al., 2009). Hirose and Okazaki (2009) findthat attitude towards mobile-telephone advertising influences the intentionto ignore or delete messages, but that more favourable attitudes do indeedarise from permission marketing. In fact, we are unaware of any work thattests the relation between permission marketing and involvement. Even so,we consider that it is likely that permission marketing will produce a pos-itive effect on the relevance given to the mobile telephone as the purchasechannel. We therefore propose the second hypothesis:

H2: Permission marketing positively influences consumer involvement inmobile commerce.

Innovativeness in the field of information technologyFiore et al. (2003) point out that purchasing experiences are individual andby nature subjective, and are determined by personal characteristics that

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include the personality of the purchaser. This concept is defined as “a rel-ative and durable set of psychological traits that people use to interact withtheir surroundings” (Scarr and Zanden, 1987:420).

Al–Gahtani et al. (2007) show that the attitude towards the use of tech-nologies is a forerunner of the intention to use that technology and the lit-erature indicates that greater personal exposure to new technologies entailsa greater predisposition to purchase (Dholakia and Usitalo, 2002; Lohse etal., 2000). This will facilitate learning and the take up of new technologies.Besides, Goldsmith (2000) showed that the frequency of on-line purchas-es, as well as future purchasing intentions could be predicted by individualinnovativeness and by a personal involvement in the Internet as a purchasechannel.

Various studies have examined the impact of innovativeness in theacceptance of mobile services (June et al., 2003; Jong et al., 2006). In thecontext of mobile commerce, the idea of “personal innovativeness in thedomain of information technologies” is considered a variable of individualpersonalities that reflect a favourable and proactive attitude towards theuse of information technologies. This concept was introduced by Agarwaland Prassad (1998), who contend that a person whose personality har-bours the characteristic of innovativeness in the field of new technologieswill respond positively to the knowledge of those technologies, will seek toexperiment with them when made aware of their existence, is usually thefirst of their reference group to try out such technologies, and will enjoyexperimenting with them.

Jeong et al. (2009) demonstrated in the field of Radio Frequency Iden-tification (RFID) purchases that personal innovativeness with informationtechnology behaved as a moderating variable between perceived need andpurchase intention. Thus, mobile users with high innovativeness in thefield of information technology may need to experience less purchasenecessity to reach the same level of purchase intention.

The personal characteristics of consumers determine their level ofinvolvement towards the medium (Andrews et al., 1990). Consequently,and taking earlier works as a reference, we consider that personal innova-tiveness in the domain of information technology is an important person-

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ality trait to win consumer involvement in mobile-phone purchasing, hencewe propose such a relation in the following hypothesis:

H3: Personal innovativeness in the domain of information technology hasa positive influence on consumer involvement in mobile commerce.

3. The role of gender as a moderator of mobile purchasingEarlier studies have considered that certain socio-demographic and con-textual characteristics such as age (Yalch and Spangenberg, 1990), educa-tion (Gattiker et al., 2000; Tamimi and Sebastianelli, 2007), income level(Dawson et al., 1990), gender (Zhang et al., 2007; Kolsaker and Payne,2002), purchase motivations (Eroglu and Machleit, 1990), knowledge (Sir-gy et al., 2000), cultural values (Overby et al., 2004) and other people’sopinions are factors that influence the purchasing experience. Gattiker etal. (2000) affirmed that personal characteristics influence and interact withmental processes such as perception, reasoning, making judgments anddecision taking. Socio-demographic characteristics can be moderators ofvariables that influence distance purchasing behaviour and the acceptanceand implementation of new information technologies (Zhang et al., 2007).The literature therefore considers personal characteristics as variables thatmoderate the relation between a stimulus and a response. Thus, Goldsmithand Flynn (2004) found that neither age nor income but gender is relatedto on-line purchasing of clothes (women buy more clothes on-line thanmen).

Gender differences have been investigated in various empirical studiesrelated to the acceptance of Internet purchasing technology, the use of elec-tronic mail and on-line banking (Lichtenstein and Williamson, 2006;Chang and Samuel, 2004; Rodgers and Harris, 2003; Luo et al., 2006;Flavián et al., 2011). Gefen and Straub (1997) affirmed that, althoughtechnology such as electronic mail may be used to a similar extent by bothsexes, the perception of service is different between men and women. It isinteresting to highlight this point, as it should be taken into account in theadvertising models that firms apply, adding this variable to other aspectssuch as cultural variables, for example.

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In the context of mobile-telephone commerce, works have been pub-lished that study the role of gender in its acceptance. Yang (2005) affirmsthat gender as a variable measures the relation between the perceived util-ity of purchases by mobile telephone and ease of use, in such a way thatthis relation is stronger for men. Jun Zhang (2009) also analyzes the influ-ence of gender in the two key variables of the Technology AcceptanceModel (TAM) (usefulness and ease of use) and ratifies the greater effect ofthese variables in the acceptance of mobile commerce in China. However,Ha (2007) shows that ease of use, in the specific case of mobile games, ismore important with regard to enjoyment in the case of women ratherthan men. For communication tools such as mobile chat, Nysveen et al.(2005) proved that the intention to use chat revealed, in the case of men,motives such as usefulness and, surprisingly, expressivity. In the case offemale users, they highlighted social norms and perceived enjoyment to agreater extent.

Divergent evidence exists on the importance of gender in the use ofinformation technologies as the purchasing channel. In fact, various authorshave defended the utility of inquiring into behavioural differences of thebuyer according to gender (Bauer et al., 2005; Gao et al., 2010). Some stud-ies affirm that as penetration and acceptance of technologies increase, themoderating effect of gender will diminish (Zhou et al., 2007). Other stud-ies have demonstrated that men and women respond in different ways ineither an on-line (Gattiker et al., 2000) or in a mobile context (Jayaward-hena et al., 2010). Thus, Ranganathan et al. (2006) found that faced withthe same circumstances, men experienced a greater propensity to changemobile service providers than women. All of the above, linked to the pre-dominantly male profile of the Mobile Internet user in Spain (62%)(Nielsen, 2010), leads us to think that possible differences have to be con-templated in the marketing strategies of the firms that wish to enter thischannel. Thus, implicit in the earlier affirmations is the need to conduct in-depth studies that examine the true value of gender as a moderating vari-able of various stimuli or factors linked to mobile purchasing decisions.

Previous studies mention specific differences, establishing that womenare usually more implicated in purchase activities (Slama and Tashlian,

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1985), pay more attention to sellers (Gilbert and Warren, 1995), showmore concern over risk and privacy, and place greater value on relationsand personal contact (Citrin et al., 2003). Men show greater interest in theinformation and the personalization of the product, whereas women placea higher value on purchase delivery and post-sales services (Burke, 2002).In the context of mobile commerce, men take purchasing decisions in amore decisive way (Denis et al., 2005) and their enjoyment of the mobile-telephone marketing experience will be guided by the desire to satisfy cer-tain expectations of experiences. Jayawardhena et al. (2009) even go so faras to suggest that mobile marketing is a functional activity destined morefor men, allowing them to be more decisive and increasing their perceivedcontrol.

With regard to the impact of gender on the determinants of involve-ment that are contemplated in our work, perceived risk has a greater effecton mobile-phone purchasing for the female gender. Igbara and Chakrabar-ti (1990) and Chiu et al. (2005) defend the idea that women show higherlevels of anxiety and value the convenience of physical purchases morethan men. The study carried out by Luo et al. (2006) suggests that womenseek elements that help them to reduce risk in on-line purchasing. Tamimiand Sebastianelli (2007) also analyze the differences between groups seg-mented by gender, age, income level and education in the perception oftrust in Internet and find that women attach greater relevance to the ele-ments that mitigate privacy and security in the use of new informationtechnology (Garbarino and Strahilevitz, 2004; Bartel-Sheehan, 1999). Forall those reasons, the studies suggest that women experience greater psy-chological and functional risk in mobile-telephone purchasing, and weunderstand that risk will reduce involvement even more in the case of men.As involvement is more important for women than for men (Slama andTashlian, 1985), it is expected that the negative determinant that we con-sider in our work (risk) will reduce their involvement even more than inthe case of men. In consequence:

H4. In the case of women, the effect of perceived risk on involvement inmobile commerce is greater than it is in the case of men.

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Gurau and Ranchhod (2009) find gender differences with respect to theintention to accept mobile marketing, because women react in a more emo-tional way if there is an abuse of privacy, whereas men are more mistrust-ing towards the mobile-telephone marketing environment; they do notwish to participate in promotional programmes or want to control the useof personal information in detail.

Jayawardhena et al. (2009) find significant differences between menand women with respect to permission marketing because women give per-mission according to their previous experience with mobile marketingcampaigns, whereas permission marketing influences perceived control toa greater extent in men. According to these authors, men will not link theirdecision to give marketing permission to their past experience, owing totheir impatience when taking decisions with the mobile. These authorspropose that the better the experience of mobile marketing, the better thereceptivity to permission marketing. Likewise, women value personal con-tact more, whereas permission marketing is more impersonal (Gilbert andWarren, 1995; Citrin et al., 2003).

Okazaki (2004) found no relation between gender and attitudestowards advertising on mobile web-sites. However, Karjaluoto et al.(2006) showed that although no gender differences were noted in mobile-“push” marketing, women are more active in mobile “pull” marketing.

In our case, it is to be expected that men will be more receptive to per-mission marketing, as we are considering a type of purchase that is notvery consolidated in Spain, where men have more experience of purchas-ing with new technology. We therefore propose that permission marketingwill be more important in the case of men than it will in the case of womento achieve involvement in mobile commerce.

H5. In the case of men, the effect of permission marketing on involvementin mobile commerce is greater than it is in the case of women.

Venkatesh and Morris (2000) observed that men value perceived util-ity more for decision-taking, whereas women value perceived ease morewhen accepting a technology. Pijpers et al. (2001) also found that demo-

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graphic characteristics predicted the acceptance of information tech-nologies.

Bouwman et al. (2008) demonstrated, through a longitudinal study onthe use of mobile-telephone services in Finland, that the use of those serv-ices differed in accordance with gender and attitudes towards innovation,and as a consequence of the latter, the possession of advanced mobiledevices. This effect is indirectly made clear through the use of mobile Inter-net. Men are more frequent users than women and this slows down thepossibility of familiarizing themselves with the latest advantages of mobileInternet. Additionally, Bowman affirms that women with a greater per-sonal propensity towards innovation are also more inclined to use themobile services on offer, which leads us to think that they will developgreater levels of involvement than men. In consequence, we propose thefollowing hypothesis:

H6. In the case of women, the effect of personal innovativeness in thedomain of information technology is greater than it is in the case ofmen.

At this point, we move on to test the model presented below in Figure1, which summarizes in graphic form all the hypotheses: H1, H2 and H3for the three determinants of involvement in mobile commerce and H4, H5and H6 on the moderating effect of gender in relation to these determi-nants of involvement in mobile commerce.

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ANTECEDENTS OF INVOLVEMENT IN MOBILEPURCHASING

INVOLVEMENT INMOBILE PURCHASING

PROPENSITY TO USE NEW INFORMATIONTECHNOLOGIES

PERMISSION MARKETING

PERCEIVED RISK

GENDER

Figure 1. Proposed model and moderating hypotheses



4. Empirical studyAn empirical study was conducted to test the proposed hypotheses on anempirical basis, the results of which we shall discuss in the present section.In the first place, we detail the scope of the study and characterize the sam-ple selected for analysis; subsequently, we present the scales of measure-ment for each of the variables and their validation and, finally, we com-ment on the results of the estimation of the proposed models.

4.1. Study scope and sampleThe data were collected through personal interviews during February2010. The interviewees were selected by considering the representation ofeach group in the population using data from the Instituto Nacional deEstadistica (Spain’s National Institute of Statistics). Finally, a sample wasgathered of 674 individuals from the Spanish population. Insofar as thepurpose of this work was to conduct correlation-based analyses, a variedsample was gathered in which all the groups of individuals that describethe population were present, as proposed by Blair and Zinkhan (2006).The descriptives of the demographic variables in the sample may be foundin table 1.

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Gender Age Education Monthly income

Men 45.9% < 18 1.8% Unqualified 1.8% < €900 49.6%

Women 54.1% 18-24 47.3%PrimarySchool

10.68% €901-1200 24.3%

25-34 24.%SecondarySchool

39.02% €1201-1500 11.28%

35-44 16.2%Graduate andDiplomas

42.28% €1501-2000 8.01%

45-54 5.93% Postgraduate 6,23% €2001-3000 3.26%

> 54 3.71% €3001-4000 1.34%

> €4000 1.93%

Table 1. Sample description



4.2. Measurement of the research variablesFive-point Likert scales were used for the measurement of the proposedvariables. These scales were adapted to the context of the study, on thebasis of the indicators proposed in the literature. The design process andthe references used for the scales are detailed below.

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Item Description C. E. (t-value) F.C. V.E.

Permission Marketing (MP)

MP1- I wish to share my mobile telephone number with firms that carryout mobile marketing.

0.86

MP2- I don’t mind sharing personal information with firms that carry outmobile marketing.

0.792 (15.01)***

MP3 - I wish to participate in mobile marketing activities. 0.798 (16.47)***

Risk (R)

R4I am concerned that the product /service that I buy will not turn outas expected

0.877

R5 The idea gives me a feeling of anxiety 0.739 (5.48)***

Personal Innovativeness in the domain of Information Technology (PIIT)

PNT1If I hear about a new information technology, I will look for ways ofexperimenting with it

0.678

PNT2Among my friends, I am usually the first to try out new informationtechnologies

0.69 (10.52)***

PNT4 I like to experiment with new information technologies 0.675 (9.41)***

Involvement in Mobile Purchasing (IMP)

IMP1I think that I would be the first of my friends/family to know where/how to buy by mobile telephone

0.765

IMP2I think that I would be the first of my friends/family to buy by mobile-telephone

0.854 (17.78)***

IMP3I think that I know more about mobile commerce than my circle offriends

0.725 (14.40)***

IMP4I would buy by mobile telephone even though I do not know anybodythat has done so.

0.53 (10.56)***

Table 2. Reliability and validity of the measures

S.L.= Standardized Loading C.R.= Composite Reliability; V.E. = Variance Extracted.*** Significant to 1%.Measures of goodness of fit of the measurement model: χ2= 97.297 degrees of freedom = 48p-value < 0.01;S-B χ2= 80.5946 p-value < 0.01; CFI= 0.982; NFI= 0.957; IFI=0.982; GFI=0.968; AGFI=0.948; RMSEA= 0.038; RMR= 0.046; RMR standardized= 0,037.



We took the scales used by Stone and Gronhaug (1993) and Laroche etal. (2005) and Cunningham et al. (2005) for the measurement of perceivedrisk, considering functional risk (the product did not turn out as expected)and psychological risk (anxiety perceived in the purchase) (Jacoby andKaplan, 1972). Thus, we should point out that it is difficult to differenti-ate in an effective way between the dimensions of risk from the consumer’spoint of view (Koenig-Lewis et al., 2010), especially when there is limitedexperience, as is the case for mobile purchases. Other works on mobile-phone marketing have used one or two general indicators to measure risk(Wu and Wang, 2005).

Involvement was measured through the scale proposed by Keaveneyand Parthsarathy (2001) and Zinkhan and Locander (2001) and is consid-ered especially appropriate for technology-related areas, such as the mobiletelephone. This scale includes specific items of involvement, interest andskill or capability in relation to the product or situation.

The permission marketing scale was prepared with reference to Baueret al. (2005) and Reutterer and Walter (2009). Finally, the scales ofRodriguez et al. (2009) and Goldsmith and Hofacker (1991) were used forthe measurement of information technology innovativeness.

4.3. Validation of the measurement scalesThe first step was to guarantee the validity and reliability of the scales, forwhich purpose we used the EQS 6.1 statistical software package. It wasnecessary to eliminate some items, in order to guarantee the convergentvalidity shown in the Confirmatory Factorial Analysis (CFA) goodness-of-fit measurements for each of the proposed factors. The standardized load-ings of the indicators that were finally used to test the hypotheses areshown in table 2. As may be seen in that table, all the standardized load-ings present values of over 0.6, the only exception being the fourth indica-tor of involvement that was maintained as it presented a significantly dif-ferent value from zero and so as not to lose content validity. Maintainingthis indicator, the Variance Extracted (V.E.) continued to be above 0.5,guaranteeing its convergent validity. Furthermore, personal innovativenesswith information technology presented a lower V.E. value of 0.464, which

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may be considered sufficient to guarantee the convergent validity. In con-sequence, considering the measures of goodness of fit of the measurementmodel, the standardized values of the factorial loadings and the V.E. (allthis information can be found in table 2), we may consider the convergentvalidity of the measurements acceptable. The measurements also presentreliability, given that the values of composite reliability are above the rec-ommended value of 0.7.

Finally, the model’s discriminant validity was tested using the consider-ations of Fornell and Larcker (1991): none of its constructs presented aV.E. below the table of correlations (see correlations in table 3). Therefore,it may be concluded that the proposed model is sufficiently robust.

4.4. ResultsThe hypotheses were proven thanks to a structural model in whichinvolvement was the dependent factor that was related with three exoge-nous factors, permission, risk and personal innovativeness with informa-tion technology. Thus, as may be observed from the coefficients shown intable 4, the three proposed hypotheses in our study are upheld, as the threeparameters are significant and present the expected sign. Equally, the mod-el presents an acceptable fit, all of which leads us to consider that theresults are valid.

D.E. Medias MP R PNT IMP

MP .904 1.758 --

R .956 3.775 -.210 --

PNT .687 3.161 .157 0.123 --

IMP .879 2.439 .519 -.122 .519 --

Table 3. Measurements, deviations and correlations

S.D. = Standard Deviation.



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It was necessary to divide the sample into two groups in order to testthe hypotheses referring to gender differences: group 1 was made up of310 men while group 2 was made up of 364 women. The difference ofmeans and the correlations matrices were tested in both groups, as well ascompliance with the conditions of metric invariance (Steenkamp andBaumgartner, 1998) and the convergent and the discriminant validity (For-nell and Larcker 1991) necessary to validate the measurements. The resultsof the structural model are presented in table 5. As we may see from thattable, the coefficients corresponding to each of the hypotheses in themajority of cases present the expected values, fulfilling the two firsthypotheses but not the third, where significant differences do not existbetween both parameters.

Independent /Dependent Involvement R2=,329Coefficient (t-value)

Hypothesis

Risk -.138 (-2.382)*** H1 Accepted

Permission Marketing .159 (3,297)*** H2 Accepted

Personal Information TechnologyInnovativeness

.654 (6.96)*** H3 Accepted

Table 4. Structural model, hypothesis

NB: Non-standardized coefficients are used.*** Significant to 1%.Measures of goodness of fit: χ2= 97,297 degrees of freedom = 48 p-value < 0.01;S-B χ2=80.5946 p-value < 0.01; CFI= 0.982; NFI= 0.957; IFI=0.982; GFI= 0.968; AGFI=0.948;RMSEA= 0.038; RMR= 0.046; standardized RMR = 0.037.



Different hypotheses were proposed. The first three make reference tothe effect of the variables proposed for involvement. The followinghypotheses are upheld: the greater the perceived risk, the lesser the involve-ment (H1); the more the individual is willing to participate in mobile-mar-keting campaigns and the greater the propensity to accept new technolo-gies (H2 and H3 respectively), the greater the individual’s involvement. Asexpected, this process of generating involvement presents gender differ-ences. In the case of men, permission marketing has a greater impact oninvolvement than it does on women (for whom it is not even significant, afinding which in consequence supports H4). Risk, for its part, acts as aninhibitor in the appearance of involvement for women and not for men,thereby providing support for hypothesis 5. Finally, contrary to what wasproposed in hypothesis 6, personal information technology innovativenessin men and women has a similar effect on involvement.

5. ConclusionsWe can point to the different contributions of this study within this frame-work. Firstly, our work is pioneering in the study of involvement in mobilepurchasing, a key variable in the establishment and maintenance of rela-tions with the client, which has not been extensively studied in this con-

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Independent /Dependent InvolvementCoefficient (t-value)

Hypothesis

Hombres R2=.241 Women R2=.372

Risk -.124 (-1.588) -.152 (-2.099)** H4 Accepted

Permission Marketing .211 (3.133)*** .095 (1.332) H5 Accepted

Personal information technologyinnovativeness

.671 (3.894)*** .692 (6.258)*** H6 Rejected

Table 5. Structural model, hypotheses on gender differences

NB: Non-standardized coefficients are shown.** Significant to 1%, **significant to 5%.Measurements of goodness of fit: χ2=163, 515 degrees of freedom = 104 p-value < 0.01;S-B χ2= 137.4767 p-value =0.016; CFI= 0.982; NFI= 0.930; IFI=0.982 GFI= 0.949; AGFI=0.923; RMSEA= 0.037; RMR= 0.062; standardizedRMR = 0.050.



text. We have proposed a model in the course of the study that seeks toexplain the formation of involvement in mobile purchasing by consideringthree aspects: individual characteristics of the consumer (personal infor-mation technology innovativeness); attributes of the product (which arereflected in perceived risk) and the context of the purchasing circumstances(permission marketing) that is intended to gather individual attitudestowards mobile marketing and the way in which consent is given to formpart of the mobile-marketing programme.

The second contribution is the analysis of the model, taking the mod-erating effect of gender into account. As Broderick and Mueller (1999)suggest, involvement is a complex construct that requires continuous crit-ical analysis to be understood. Wessels and Drennan (2010) maintain thatfirms involved in mobile sales should try to modify the attitudes of poten-tial mobile consumers and to do so it is necessary to increase their involve-ment in this type of purchase/purchase channel.

The results are supported by a detailed sample carried out through per-sonal surveys, the objective of which is to achieve greater control over thecomposition of the sample. A large number of responses and the composi-tion of the sample that is broken down by age, educational level, and pro-fession reflects the universe of mobile users, redressing a recurrent weaknessof many of the existing studies in the literature (Wessels and Drennan, 2010).

The results provide insight into the importance of perceived risk as aninhibitor of involvement, a question previously envisaged by Laukkanenand Kiviniemi (2010) when proposing perceived risk as a resistant barrierto the acceptance of mobile-telephone marketing, which is difficult tobreakdown even when the firm provides information.

Marketing permission behaves as a facilitator of involvement, makingit clear that, by providing consent, the consumer is expressing some sort offavourable attitude towards the channel (consents to provide the request-ing firm personal data, such as a telephone number, or even other more pri-vate information), and in addition, feels involved in the relation insofar asthere is some acceptance to participate in mobile-phone activities.

As may be expected, the results suggest that personal innovativenesswith information technology positively influences the appearance of

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involvement. This is explained because the propensity to accept new tech-nologies in the field of mobile commerce facilitates perceived utility andease of use, which will lead to greater individual interest towards the chan-nel that, maintained over time, will generate involvement in mobile com-merce.

Consideration of gender differences has made the need to treat men andwomen in different ways quite clear, if the intention is to involve them inmobile commerce. This is because, on the basis of their gender, individualswill respond in different ways due to external stimuli. In the case of per-mission marketing as an external stimulus, men present greater sensitivitythan women, which may be because they wish to exercise more detailedcontrol over the use of personal information and may lead us to think thatmale consent will be more likely to develop involvement than the consentof a woman. Likewise, perceived risk acts as an inhibitor of the emergenceof involvement in the case of women and shows no significant effect formen. In the case of women, this perceived risk translates into greateruncertainty in the purchasing process, and greater anxiety towards themedium, as they value the convenience of physical purchasing more thanmen, based on the greater tangibility of the conventional channel.

Personal information technology innovativeness is shown to be a rele-vant factor for the formation of involvement regardless of the gender of theconsumer, forming a specific characteristic of the individual involved inmobile purchasing.

There are more than a few implications for management that may bedrawn from our study. It is worth highlighting, in the first place, the grow-ing volume of mobile purchases in Spain, which implies a sales channelwith a future, the size of which should be the subject of theoretical andempirical study, with the aim of gathering useful knowledge for firms.

Initially, and as a consequence of this study, we propose the followingindications that relate to the three dimensions under study: firms thatdecide to enter mobile commerce should bear in mind that a reduction inperceived risk is an important way of winning individual involvement, andit can contribute to mitigate perceived risk through signals of reliability inthe purchase process and security in the channel, to diminish anxiety.

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Moreover, the firm should use permission marketing in compliance withlegal provisions in Spain, but has to bear in mind that it is an opportunityto personalize communication with its target population and to encourageparticipation in the channel. This too, if well used, can become a differen-tiating feature in the face of competition and a strategy that manages tosatisfy consumers, by adapting itself to their preferences.

With reference to purchaser profiles, it is also important for firms togenerate a climate that fosters the acceptance of new technologies by theirclients, participating in communication campaigns that try to explain tothe client the advantages of the channel (perceived utility) and its ease ofuse, to attract clients that are less inclined to use new technologies.

In an effective segmentation, firms have to contemplate gender differ-ences insisting on those attributes that facilitate permission marketing inthe case of products targeted at men, and on those aspects that help to mit-igate perceived risk for marketing campaigns that target women.

With regard to the limitations of this work, the fact should be men-tioned that the information was only collected in Spain, which prevents thegeneralization of the model to other geographical and cultural areas.Besides, we have centred on mobile users without distinguishing the degreeof experience that they have with mobile purchasing.

Finally, there are various future research lines now open to us. It wouldbe interesting to study the influence of culture and geographic scopebecause of the differences they produce in individual perceptions, attitudesand behaviours with regard to mobile purchasing (Gurau and Ranchhod,2009). For example, Gurau and Ranchhod (2009) found that consumersfrom different countries are more or less receptive to intrusive, unsolicitedpublicity. It would also be convenient to inquire into the possibilities ofcomparing the model for individuals that purchase with the mobile-tele-phone and those that abstain or for those that make mobile purchases andthose that use the Internet or even in relation to offline purchasers. Bydoing so, it would be possible to speculate on the complementaritiesbetween both sales contexts. There are authors that indicate that it is riskyto reproduce off-line strategies in virtual environments (Vrechopoulos etal. 2004). Although we have especially centred on three variables in this

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work as determinants of involvement in mobile commerce, there are otheraspects that could be analyzed, such as trust and seller reputation. Equal-ly, it would be interesting to include the influence of the group in theinvolvement of potential purchasers through variables such as social riskand the subjective norm (Riquelme and Ríos, 2010). Moreover, we con-sider that research needs to continue into involvement in mobile commerceand the role that involvement plays in individual behaviour.

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