SOCIAL BEHAVIOR AND PERSONALITY, 2010, 38(3), 415-426 Society for Personality Research (Inc.) DOI 10.2224/sbp.2010.38.3.415 User Acceptance of Mobile Internet Based on THE UNIFIED THEORY OF ACCEPTANCE AND USE OF TECHNOLOGY: Investigating the Determinants and Gender Differences Hsiu-Yuan Wang Chung Hua University, Hsinchu, Taiwan, ROC Shwu-Huey Wang Far East University, Tainan, Taiwan, ROC Based on the Unified Theory of Acceptance and Use of Technology Model (UTAUT; Venkatesh, Morris, Davis, & Davis, 2003), the purpose of this study was to investigate the determinants of mobile Internet (m-internet) acceptance and to understand whether or not there are gender differences in the acceptance of m-internet. Data collected online from 343 respondents in Taiwan were tested against the research model, using the structural equation modeling approach. The proposed model was mostly supported by the empirical data. The findings of this study provide several crucial implications for m-internet service practitioners and researchers. Keywords: mobile Internet, Unified Theory of Acceptance and Use of Technology, determinants, gender differences. Mobile Internet (m-internet) refers to accessing wireless Internet anytime and anywhere via palm-sized mobile devices including mobile phones, personal digital assistants (PDAs), and smart phones. With the rapid growth of demand for mobile phones, and the advent of third-generation technology, accessing Hsiu-Yuan Wang, PhD, Assistant Professor, Department of Hospitality Management, Chung Hua University, Hsinchu, Taiwan, ROC; Shwu-Huey Wang, Lecturer, Department of Business Administration, Far East University, Tainan, Taiwan, ROC. Appreciation is due to reviewers including: Ju-ling Yu, 63, Alley 26, Lane 442, Kai-Yuan Rd., Tainan City, Taiwan, ROC. Please address correspondence and reprint requests to: Hsiu-Yuan Wang, Department of Hospitality Management, Chung Hua University, No. 707, Sec. 2, WuFu Rd., Hsinchu, Taiwan 300, ROC. Phone: +886-3-5374281~5-6873; Fax: +886-3-518-6569; Email: hywang@chu.edu.tw 415
416 USER ACCEPTANCE OF MOBILE INTERNET the Internet via a mobile phone to conduct mobile-related activities is likely to become a widespread and popular trend. Mobile activities basically denote any electronic activities performed in a wireless environment, through a mobile device, and via the Internet (Turban, Cohen, Copi, & King, 2003). As an example, the major differences between m-commerce and other forms of e-commerce are mobility and accessibility. Users can create real-time contact with commercial systems at any time (accessibility) and anywhere (mobility) through the use of wireless Internet and mobile devices. Accordingly, m-internet is an enabling technology for all kinds of mobile activities. As the growth of mobile activities is closely related to m-internet, a clear understanding of m-internet adoption is very important. However, there is a lack of literature that is focused on exploring factors influencing the individual decision to adopt m-internet, and also very little has been written on exploring the moderating effects of gender on the adoption of m-internet. Therefore, to better understand what motivates individuals to use m-internet, there is a need to identify the factors underlying the process leading to their adoption of this technology. Thus, the purpose in this study was to investigate the determinants, and also the gender differences, in the acceptance of m-internet based on the Unified Theory of Acceptance and Use of Technology (UTAUT) proposed by Venkatesh, Morris, Davis, and Davis (2003). THEORETICAL FOUNDATIONS UTAUT Grounded on eight famous models in the field of information technology acceptance research, Venkatesh et al. (2003) conducted an empirical study and proposed a unified model, called UTAUT. This model combines components across the eight models which include the Theory of Reasoned Action (TRA; Fishbein & Ajzen, 1975), the Technology Acceptance Model (TAM; Davis, 1989), the Motivational Model (MM; Davis, Bagozzi, & Warshaw, 1992), the Theory of Planned Behavior (TPB; Ajzen, 1991), the Combined TAM and TPB (C-TAM-TPB; Taylor & Todd, 1995), the Model of PC Utilization (MPCU; Thompson, Higgins, & Howell, 1991), the Innovation Diffusion Theory (IDT; Moore & Benbasat, 1991; Rogers, 1995), and the Social Cognitive Theory (SCT; Bandura, 1986). UTAUT consists of four core determinants of intention and usage, and four moderators of key relationships. Venkatesh et al. (2003) posit that performance expectancy, effort expectancy, social influence, and facilitating conditions are determinants of behavioral intention or use behavior, and that gender, age, experience, and voluntariness of use have moderating effects in the acceptance of information technology (IT).
USER ACCEPTANCE OF MOBILE INTERNET 417 However, the m-internet context is to some degree different from the traditional IT context. Pedersen and Ling (2003) suggested in their paper that the traditional adoption models in IT research may be modified and extended when they are applied to the adoption of new technology such as m-internet. After considering the m-internet context and user factors, these researchers added three additional constructs, perceived playfulness, perceived value, and palm-sized computer self-efficacy, to the UTAUT to explore m-internet acceptance. However, since the rate of regular usage of mobile value-added services through m-internet is still very low, in the current study, we also chose behavioral intention as a dependent variable. Thus, three constructs that were originally in UTAUT, namely use behavior, facilitating conditions, and experience, were omitted in our study. Further, we investigated the acceptance of m-internet in a voluntary usage context, and found that most m-internet adopters in Taiwan are aged between 20 and 35 (Liang, 2006) so that the moderators of voluntariness of use and age were also omitted from our study. RESEARCH MODEL AND HYPOTHESES The research model tested in this study is shown in Figure 1. In this model, performance expectancy, effort expectancy, social influence, perceived playfulness, perceived value and palm-sized computer self-efficacy were hypothesized to be determinants of behavioral intention to use m-internet. The proposed constructs and hypotheses are supported by findings gained in previous studies. Performance Expectancy Venkatesh et al. (2003) define performance expectancy as the extent to which an individual believes that utilizing the information system will assist him/her to attain benefits in job performance. Performance expectancy has been justified as a predictor of behavioral intention to use IT (Venkatesh et al., 2003). Adapting performance expectancy to an m-internet context implies that mobile users will think m-internet beneficial because it enables them to accomplish their daily jobs faster and with more flexibility, or even helps increase their work productivity. Based on the findings of previous researchers (Venkatesh & Morris, 2000; Venkatesh et al., 2003), gender has been theorized to play a moderating role on the influence of performance expectancy on behavioral intention, such that the effect will be stronger for men. Therefore, in our study the following hypotheses were tested: H1. Performance expectancy will have a positive effect on behavioral intention to use m-internet. H2. Performance expectancy will influence behavioral intention to use m- Internet more strongly for men than for women.
418 USER ACCEPTANCE OF MOBILE INTERNET Effort Expectancy The definition of effort expectancy is the extent of ease concerning the use of the information system (Venkatesh et al., 2003). Based on the UTAUT, it is thought that individual acceptance of m-internet will depend on whether or not the accessibility of m-internet is easy and effortless. In addition, prior researchers have shown that constructs associated with effort expectancy will be stronger determinants of personal intention about using IT for women than they are for men (Venkatesh & Morris, 2000; Venkatesh et al., 2003). Thus, we proposed that the influence of effort expectancy on m-internet acceptance might be moderated by gender. Therefore, the following hypotheses were tested: H3. Effort expectancy will have a positive effect on behavioral intention to use m-internet. H4. Effort expectancy will influence behavioral intention to use m-internet more strongly for women than for men. Social Influence Social influence is defined as the extent to which a person perceives that important others believe he or she should use a new information system (Venkatesh et al., 2003). Prior researchers have claimed that social influence is significant in shaping personal intention to use new technology (Moore & Benbasat, 1991; Venkatesh & Davis, 2000). Furthermore, it has been suggested that women tend to be more sensitive to the influence of others and therefore social influence will be more salient when women form an intention to use new technology (Venkatesh, Morris, & Ackerman, 2000; Venkatesh et al., 2003). Hence, the following hypotheses were proposed: H5. Social influence will have a positive effect on behavioral intention to use m-internet. H6. Social influence will influence behavioral intention to use m-internet more strongly for women than for men. Perceived Playfulness Based on the definition of Moon and Kim (2001), perceived playfulness in this study is defined as a state of mind that contains three dimensions: the degree to which the individual (1) finds that his/her attention is focused on the interaction with the m-internet, (2) is curious during the interaction, and (3) perceives the interaction as intrinsically enjoyable. Moon and Kim found that perceived playfulness has a significant positive influence on behavioral intention to use the World Wide Web and m-internet can be considered as a kind of wireless World Wide Web. By applying the findings of Moon and Kim to m-internet we predicted that an individual s intention to use m-internet would be influenced by his/her perceptions of playfulness. Prior researchers have indicated that there are
USER ACCEPTANCE OF MOBILE INTERNET 419 significant gender differences in attitudes toward computers (Mitra et al., 2000), with men showing a more positive attitude towards using computers than women did. So, it may be inferred that perceived playfulness would be more salient in determining behavioral intention to use m-internet for men, than for women. Thus, the following hypotheses were tested: H7. Perceived playfulness will have a positive effect on behavioral intention to use m-internet. H8. Perceived playfulness will influence behavioral intention to use m-internet more strongly for men than for women. Perceived Value Perceived value is defined as the consumer s overall assessment of the utility of a product based on perceptions of what is received and what is given (Zeithaml, 1988). In the case of m-internet, potential users would probably compare all the attributes of m-internet usage with prices of previous mobile phone calls and stationary Internet access. Urbany, Bearden, Kaicker, and Smith-de Borrero (1997) argued that transaction advantage is a predictor of purchase intention and behavior; hence, we believed that higher perceived value would lead to greater willingness to adopt the new technology. Moreover, gender is a vital factor in regard to differences in consumer perceived value (Hall, Shaw, Lascheit, & Robertson, 2000). So, the following hypotheses were examined: H9. Perceived value will have a positive effect on behavioral intention to use m-internet. H10. Perceived value will influence intention to use m-internet more strongly for women than for men. Palm-sized Computer Self-efficacy Palm-sized computer self-efficacy is defined as a summary judgment of one s capability to engage in some specific computer-related activities through a palmsized computer. Computer self-efficacy has been found to be a significant direct determinant of individual response to IT (Agarwal, Sambamurthy, & Stair, 2000; Johnson & Marakas, 2000). Venkatesh et al. (2003) encouraged other researchers to integrate the UTAUT with previously examined determinants, such as selfefficacy or computer self-efficacy, to provide a greater understanding of adoption of IT. In the situation of m-internet, the individual who is competent at using a palm-sized computer is very likely to have an intention to use m-internet. Some researchers have indicated that women display less self-efficacy with computers or the Internet (Durndell & Hagg, 2002). M-Internet could be considered to be a natural extension of computer use. Therefore, the following hypotheses were tested:
420 USER ACCEPTANCE OF MOBILE INTERNET Performance Expectancy 0.243 *** Effort Expectancy Social Influence Perceived Playfulness 0.299 ** 0.179 * -0.138 R 2 = 0.650 Behavioral Intention to use m-internet (BI) Perceived Value Palm-sized Computer Self-efficacy 0.198 ** 0.201 ** Figure 1. Research model and standardized path coefficients for all respondents. * p < 0.05, ** p < 0.01, *** p < 0.001 Performance Expectancy Effort Expectancy Social Influence Perceived Playfulness Perceived Value Palm-sized Computer Self-efficacy 0.672 *** -0.059 0.281 *** 0.871 *** -0.012 0.058 0.001-0.040 0.208 * 0.107 0.376 *** -0.031 R 2 = 0.650 Behavioral Intention to use m-internet (BI) Figure 2. Standardized path coefficients for males and females. Coefficients for males are in the shaded boxes. * p < 0.05, ** p < 0.01, *** p < 0.001
USER ACCEPTANCE OF MOBILE INTERNET 421 H11. Palm-sized computer self-efficacy will have a positive effect on behavioral intention to use m-internet. H12. Palm-sized computer self-efficacy will influence intention to use m- Internet more strongly for men than for women. MEASURES AND DATA COLLECTION Items for the constructs of interest were taken from the previously validated inventory (Hsu & Chiu, 2004; Moon & Kim, 2001; Sirdeshmukh, Singh, & Sabol, 2002; Venkatesh et al., 2003) and modified to fit the m-internet being studied. Likert scales (1 to 7), with anchors ranging from strongly disagree to strongly agree were used for all items. Data used to test the research model were gathered from an online sample in Taiwan of 343 respondents who volunteered; 58.9% of the respondents were male. RESULTS The measurement model exhibited a fairly good fit with the data collected (χ 2 /df = 1.58, GFI = 0.93, AGFI = 0.90, NFI = 0.95, CFI = 0.98, and RMSEA = 0.04) and had acceptable psychometric properties in terms of reliability, convergent validity, and discriminant validity. The structural model also provided evidence of a good model-data fit (χ 2 /df = 1.43, GFI = 0.94, AGFI = 0.91, NFI = 0.96, CFI = 0.99, and RMSEA = 0.04). Properties of the causal paths, including standardized path coefficients for both male and female respondents as well as significance levels, are shown in Figures 1 and 2. Hypotheses H1, H2, H3, H4, H5, H9, H11, and H12 were supported. However, H6, H7, H8, and H10 were not supported. Altogether, the proposed model accounted for 65% of the variance in behavioral intention. For males the total variance was 74% while for females the model accounted for 82% of the variance of behavioral intention. DISCUSSION AND CONCLUSION Determinants of m-internet Acceptance Coinciding with the findings of Venkatesh et al. (2003), the three constructs derived from UTAUT (performance expectancy, effort expectancy, and social influence) had a significant positive influence on behavioral intention to use m- Internet. Among the three constructs, performance expectancy was shown to be strongly related to behavioral intention to use m-internet. To boost the usage of m-internet, m-internet practitioners should make an effort to develop valuable functions and variety services that could help to fulfill potential users needs. For example, m-internet can facilitate many services that are already provided
422 USER ACCEPTANCE OF MOBILE INTERNET by stationary Internet. Potential functions like enabling people to do away with tickets, keys, remote controls, and even business cards may be considered by mobile solution providers. In the near future, if these sorts of functions could increasingly be added to m-internet, then mobile devices operated via the Internet could take the place of these items and adopters would increase radically. The results reveal that effort expectancy also had a significant influence on individual intention to use m-internet. This means that the majority of users are concerned about the amount of time and effort needed to learn about and use it. If its usage entails complex user interfaces, slow response, and/or inconvenient connecting procedures, then its benefits would be greatly decreased. Thus, m- Internet providers should improve the user friendliness and ease of use of m- Internet systems so as to attract more users. Social influence was found to have a significant impact on usage intention of m-internet. M-Internet practitioners should be aware of the importance of social influences. Once individuals start using and become familiar with m-internet, they may begin to persuade their colleagues and friends to adopt it. Thus, m- Internet service providers can promote m-internet to potential early adopters who are inclined to have a higher level of personal innovation in IT (Rogers, 2003). When the number of m-internet users reaches a critical mass point, the number of later m-internet adopters is likely to rise rapidly (Rogers). In line with our hypothesis, we found that one of the newly added constructs, perceived value, has a significant influence on adoption intention in the context of m-internet. This means that perceived value can reflect customers beliefs about adoption intention, which conforms to the findings of earlier research in economics and marketing (Lee & Overby, 2004; Soltani & Gharbi; 2008). Accordingly, to attract more potential adopters, m-internet providers still need to strive to decrease the usage fee of m-internet so as to enhance potential adopters perception that the use of m-internet offers value for money. As predicted, another newly added variable, palm-sized computer self-efficacy, was also found to play a critical role in predicting m-internet acceptance, and this result is in line with the findings of previous research on IT acceptance (Hong, Thong, Wong, & Tam, 2002). This finding can help m-internet practitioners target the early adopters of m-internet systems and promote the advanced technology to them. Contrary to our expectation, perceived playfulness did not have a strong influence on behavioral intention, and this is not in accordance with the findings of prior research (Moon & Kim, 2001). At this early stage of development of m- Internet, it might be that the perceived service or network communication quality of m-internet is not good enough, since feedback and speed have been identified as possible antecedents of perceived playfulness (Chung & Tan, 2004). If our potential users did not get the feeling that the feedback and speed of m-internet
USER ACCEPTANCE OF MOBILE INTERNET 423 was acceptable, then they would not perceive m-internet as playful. However, our explanations/propositions need further investigations in future studies to provide justification and validation. Gender Differences We observed that the main effects of perceived value and social influence on behavioral intention were significant, but we found no gender differences. That is, no matter whether an individual was male or female, those with a perception of high value about using m-internet had a greater intention to use m-internet than those with a perception of less value. Also, compared to all others, those whose friends, relatives, or parents had adopted m-internet had a greater intention to use m-internet. Thus, m-internet providers can cooperate with each other to deliver a perception of more value to potential customers in order to persuade more people to adopt it. It is evident that the results indicate that there are some significant gender differences in terms of the effects of the determinants on behavioral intention. First, we predicted correctly that the effect of performance expectancy on behavioral intention was significant for men, but nonsignificant for women, and this is in accordance with the findings of prior research (Venkatesh et al., 2000, 2003). Therefore, when service providers are planning to promote to the public some new services or functions developed through m-internet related technologies they should aim firstly at the male users. Once male users perceive m-internet technology as beneficial and decide to adopt it, they may use their social influence to encourage their friends to use m-internet, thus facilitating the extension of m-internet. As expected, effort expectancy was found to be a stronger determinant of intention for women than for men, and this result is in line with the findings of previous studies (Venkatesh & Morris, 2000; Venkatesh et al., 2000, 2003). In those studies it was found that women tend to care much more about technological effort expended in the early stages of a new behavior. Therefore, m-internet developers should offer a user-friendly interface with a touch screen and even a voice recognition mechanism to connect to m-internet. This could make women perceive m-internet as easier to use and thus they would be more likely to adopt it in the future. Finally, we found that gender difference moderates the effect of palm-sized computer self-efficacy on behavioral intention because men with high palmsized computer self-efficacy tend to have a greater behavioral intention to use m-internet than those with less palm-sized computer self-efficacy, but women with high palm-sized computer self-efficacy do not have greater intention to use m-internet than those with less palm-sized computer self-efficacy. This finding is the same as was recorded in previous studies (Agarwal et al., 2000; Hong et
424 USER ACCEPTANCE OF MOBILE INTERNET al., 2002). Thus, m-internet practitioners can increase men s, but not women s, palm-sized computer self-efficacy by providing them with education in various mobile computer technologies, which, in turn, will help them develop greater behavioral intention to use m-internet. By extension and modification of UTAUT, in this study we examined the determinants of m-internet usage intention and explored how gender differences moderate the influence of these determinants on usage intention. The contributions of this study are: Firstly, we have extended and validated the UTAUT for the m-internet context through empirical data in Taiwan; secondly, two of the three variables we added in this study were found to have significant influence on behavioral intention (i.e., perceived value and palm-sized computer self-efficacy); thirdly, the results show that the effects of social influence and perceived value on behavioral intention were significant, but no gender differences were found; fourthly, the effects of performance expectancy and palm-sized computer self-efficacy on usage intention were moderated by gender, such that they were significant for men, but not significant for women; finally, the effect of effort expectancy on intention was significant across both male and female groups, but it was moderated by gender so that it was more significant for women than for men. The findings of this study will not only help m-internet practitioners in understanding the perceptions of potential adopters, but also provide new insights on m-internet acceptance. REFERENCES Agarwal, R., Sambamurthy, V., & Stair, R. M. (2000). Research report: The evolving relationship between general and specific computer self-efficacy-an empirical assessment. Information Systems Research, 11(4), 418-430. Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211. Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice-Hall. Chung, J., & Tan, F. B. (2004). Antecedents of perceived playfulness: An exploratory study on user acceptance of general information-searching websites. Information and Management, 41(7), 869-881. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-339. Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace. Journal of Applied Social Psychology, 22(14), 1111-1132. Durndell, A., & Hagg, Z. (2002). Computer self efficacy, computer anxiety, attitudes towards the Internet and reported experience with the Internet, by gender, in an East European sample. Computers in Human Behavior, 18(5), 521-535. Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.
USER ACCEPTANCE OF MOBILE INTERNET 425 Hall, J. E., Shaw, M., Lascheit, J., & Robertson, N. (2000). Gender differences in a modified perceived value construct for intangible products. Australian and New Zealand Marketing Academy Conference Proceedings, Gold Coast, Queensland, Australia. CD-Rom, 457-462. Hong, W., Thong, J. Y. L., Wong, W., & Tam, K. (2002). Determinants of user acceptance of digital libraries: An empirical examination of individual differences and system characteristics. Journal of Management Information Systems, 18(3), 97-124. Hsu, M. H., & Chiu, C. M. (2004). Internet self-efficacy and electronic service acceptance. Decision Support Systems, 38(3), 369-381. Johnson, R. D., & Marakas, G. M. (2000). Research report: The role of behavioral modeling in computer skills acquisition toward refinement of the model. Information Systems Research, 11(4), 402-417. Lee, E. J., & Overby, J. W. (2004). Creating value for online shoppers: Implications for satisfaction and loyalty. Journal of Consumer Satisfaction, Dissatisfaction and Complaining Behavior, 17, 54-67. Liang, T. H. (2006, August). Internet broadband usage adoption in Taiwan: An overview report. Proceedings of the 3rd Asia Pacific Internet Research Alliance (APIRA) International Conference, Taipei, Taiwan. Mitra, A., Lenzmeier, S., Steffensmeier, T., Avon, R., Qu, N., & Hazen, M. (2000). Gender and computer use in an academic institution: Report from a longitudinal study. Journal of Educational Computing Research, 23(1), 67-84. Moon, J., & Kim, Y. (2001). Extending the TAM for a world-wide-web context. Information and Management, 38(4), 217-230. Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2(3), 192-222. Pedersen, P. E., & Ling, R. (2003, January). Modifying adoption research for mobile Internet service adoption: Cross-disciplinary interactions. Proceedings of the 36th Hawaii International Conference on System Sciences (HICSS-36), Big Island, Hawaii, Los Alamitos, CA: IEEE Computer Society Press. Rogers, E. (1995). Diffusion of innovations. New York: Free Press. Rogers, E. (2003). Diffusion of innovations (5th Ed.). New York: Free Press. Sirdeshmukh, D., Singh, J., & Sabol, B. (2002). Consumer trust, value, and loyalty in relational exchanges. Journal of Marketing, 66(1), 15-37. Soltani, I., & Gharbi, J-E. (2008). Determinants and consequences of the website perceived value. Journal of Internet Banking and Commerce, 13(1), 1-13. Taylor, S., & Todd, P. A. (1995). Assessing IT usage: The role of prior experience. MIS Quarterly, 19(4), 561-570. Thompson, R. L., Higgins, C. A., & Howell, J. M. (1991). Personal computing: Toward a conceptual model of utilization. MIS Quarterly, 15(1), 125-143. Turban, E., Cohen, C., Copi, I. M., & King, D. R. (2003). Introduction to e-commerce. New Jersey: Prentice-Hall. Urbany, J. E., Bearden, W. O., Kaicker, A., & Smith-de Borrero, M. (1997). Transaction utility effects when quality is uncertain. Journal of the Academy of Marketing Science, 25(1), 45-55. Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204. Venkatesh, V., & Morris, M. G. (2000). Why don t men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior. MIS Quarterly, 24(1), 115-139.
426 USER ACCEPTANCE OF MOBILE INTERNET Venkatesh, V., Morris, M. G., & Ackerman, P. L. (2000). A longitudinal field investigation of gender differences in individual technology adoption decision-making processes. Organizational Behavior and Human Decision Processes, 83(1), 33-60. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478. Zeithaml, V. A. (1988). Consumer perceptions of price, quality and value: A means-end model and synthesis of evidence. Journal of Marketing, 52(3), 2-22.
Copyright of Social Behavior & Personality: An International Journal is the property of Society for Personality Research and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use.