THE ROLE OF INDIVIDUAL FACTORS ON ONLINE SHOPPING BEHAVIOR

Yıl 2017, Cilt: 6 Sayı: 3, 200 - 215, 30.09.2017

Alev Kocak Alan Ebru Tumer Kabadayı Selen Bakis Sabina Ibrahimovic Ildokuz

https://doi.org/10.17261/Pressacademia.2017.680

Öz

Purpose: Based on the rapid growth of e-commerce and online shopping,
this study explores behavioral intention of consumers of online shopping
websites. 

Methodology: Consumer’s individual factors’ effect on consumer
perceived usefulness of online shopping and user satisfaction are modelled and
examined in terms of effects on behavioral and purchase intention toward online
shopping websites. Data were collected via Internet survey and 318 usable
surveys of consumers were gathered.

Findings: The results suggest that consumer’s relationship proneness
of online shopping websites among individual factors has the strongest effect
on consumer purchase/behavioral intention of online shopping websites. Besides,
consumer perceived usefulness has the strongest effect on consumer’s purchase
intention.

Conclusion: The effect of
relationship proneness of consumers with online shopping firms on consumers’
purchase intentions can be used to draw consumer attention. Likewise, firms can
plan their marketing communications such as advertising strategies and
promotional strategies in a way that appeal to their target customers’
personality. 

Anahtar Kelimeler

Online shopping, online purchase intention, relationship proneness, perceived usefulness, self-efficacy

Kaynakça

• Ahn, J. and Rho, T. (2016). Influence of customer–firm relationships on customer participation in the service industry. Service Business, 10, 1, 113–133.
• Akar, E. and Nasir, V. A. (2015). A review of literature on consumers' online purchase intentions. Journal of Customer Behavior, 14(3), 215233.
• Alkailani, M. and Kumar, R. (2016). Impacting innovativeness: The role of interpersonal influences and cultural dimensions on consumer innovativeness. Journal of Strategic Innovation and Sustainability, 11(1), 62.
• Amin, H. (2007). Internet banking adoption among young intellectuals. Journal of Internet Banking and Commerce, 12(3), 1-13.
• Amin, H. (2008). Factors affecting the intentions of customers in Malaysia to use mobile phone credit cards. Management Research News, 31(7), 493-503.
• Amoako-Gyampah, K. (2007). Perceived usefulness, user involvement and behavioral intention: an empirical study of ERP implementation. Computers in Human Behavior, 23(3), 1232-1248. doi:10.1016/j.chb.2004.12.002
• Bailey, A. A. (2015). Factors promoting social CRM: A conceptual model of the impact of personality and social media characteristics. International Journal of Customer Relationship Marketing and Management (IJCRMM), 6(3), 48-69.
• Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood. Englewoods Cliffs: Prentice Hall.
• Barrick, M. R., and Mount, M. K. (1991). The big five personality dimensions and job performance: a meta‐analysis. Personnel psychology, 44(1), 1-26.
• Barrick, M. R., Stewart, G. L., and Piotrowski, M. (2002). Personality and job performance: test of the mediating effects of motivation among sales representatives. Journal of Applied Psychology, 87(1), 43.
• Bearden, W. O., Netemeyer, R. G. and Teel, J. E. (1989). Measurement of consumer susceptibility to interpersonal influence. Journal of Consumer Research, 15(4), 473-481.
• Bearden, W. O. and Rose, R. L. (1990). Attention to social comparison information: an individual difference factor affecting consumer conformity. Journal of Consumer Research, 16, 461-471.
• Blazevic,V., Wiertz, C., Cotte, J., de Ruyter, K. and Keeling, I. D. (2014). GOSIP in cyberspace: Conceptualization and scale development for general online social interaction propensity. Journal of Interactive Marketing, 28(2), pp. 87–100
• Bloch, P.H. and Richins, M.L. (1983). Shopping without purchase: an investigation of consumer browsing behavior. NA-Advances in Consumer Research, 10, 389-393.
• Bloemer, J. and Odekerken-Schroder, G. (2002). Store satisfaction and store loyalty explained by customer-and store-related factors. Journal of Consumer Satisfaction, Dissatisfaction and Complaining Behavior, 15, 68-80.
• Bloemer, J. and Odekerken-Schröder, G. (2006). The role of employee relationship proneness in creating employee loyalty. International Journal of Bank Marketing, 24(4), 252 – 264.
• Bloemer, J., Odekerken-Schröder, G. and Kestens, L. (2003). The impact of need for social affiliation and consumer relationship proneness on behavioral intentions: an empirical study in a hairdresser's context. Journal of Retailing and Consumer Services,10, 231–240.
• Brandstätter, H. (1997). Becoming an entrepreneur—a question of personality structure?. Journal of economic psychology, 18(2), 157-177.
• Brandstätter, H. (2011). Personality aspects of entrepreneurship: A look at five meta-analyses. Personality and individual differences, 51(3), 222-230.
• Chang, S.H. (2015). The influence of green viral communications on green purchase intentions: The mediating role of consumers’ susceptibility to interpersonal influences. Sustainability, 7(5), 4829-4849; doi:10.3390/su7054829.
• Chang, H. H. and Chen, S. W. (2008). The impact of online store environment cues on purchase intention: Trust and perceived risk as a mediator. Online information review, 32(6), 818-841.
• Chen, C. W. D. and Cheng, C. Y. J. (2009). Understanding consumer intention in online shopping: a respecification and validation of the DeLone and McLean model. Behavior and Information Technology, 28(4), 335-345.
• Childers, T. L., Carr, C. L., Peck, J. and Carson, S. (2001). Hedonic and utilitarian motivations for online retail shopping behavior. Journal of Retailing, 77(4), 511-535.
• Chiu, C. M., Lin, H. Y., Sun, S. Y. and Hsu, M. H. (2009). Understanding customers' loyalty intentions towards online shopping: an integration of technology acceptance model and fairness theory. Behavior and Information Technology, 28(4), 347-360.
• Collier, J. E. and Bienstock, C. C. (2006). Measuring service quality in e-retailing. Journal of Service Research, 8(3), 260-275.
• Compeau, D. R. and Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS quarterly, 189-211.
• Davis Jr, F. D. (1986). A technology acceptance model for empirically testing new end-user information systems: Theory and results. (Doctoral dissertation, Massachusetts Institute of Technology).
• Davis, D. F. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319340.
• del Río-Lanza, A. B., Vázquez-Casielles, R. and Díaz-Martín, A. M. (2009). Satisfaction with service recovery: Perceived justice and emotional responses. Journal of Business Research, 62(8), 775-781.
• Fernandes, T. M. and Proença, J. F. (2008). The blind spot of relationships in consumer markets: the consumer proneness to engage in relationships. Journal of Marketing Management, 24(1-2), 153-168.
• Lee, S. Y. (2015). Interpersonal influence on online game choices. Computers in Human Behavior, 45, 129-136.
• Fishbein, M. and Ajzen, I. (1977). Belief, attitude, intention, and behavior: An introduction to theory and research.
• Frederick, F. R. and Thomas, T. E. A. L. (1996). The loyalty effect: the hidden force behind growth, profits, and lasting value. Harvard Business School Press, Boston, Massachusetts.
• Ganguly, B., Dash, S. B., Cyr, D., and Head, M. (2010). The effects of website design on purchase intention in online shopping: the mediating role of trust and the moderating role of culture. International Journal of Electronic Business, 8(4-5), 302-330.
• Gefen, D., Karahanna, E., and Straub, D. W. (2003). Trust and TAM in online shopping: An integrated model. MIS quarterly, 27(1), 51-90.
• Gu, B. and Ye, Q. (2012). First step in social media: measuring the influence of online management responses on customer satisfaction. Production and Operations Management, 23(4), 570-582. doi:10.1111/poms.12043
• Hair, J. F., Anderson, R. E., Babin, B. J. and Black, W. C. (2010). Multivariate data analysis: A global perspective (Vol. 7). Upper Saddle River, NJ: Pearson.
• Häubl, G. and Trifts, V. (2000). Consumer decision making in online shopping environments: The effects of interactive decision aids. Marketing science, 19(1), 4-21.
• Hayashi, A., Chen, C., Ryan, T. and Wu, J. (2004). The role of social presence and moderating role of computer self-efficacy in predicting the continuance usage of e-learning systems. Journal of Information Systems Education, 15(2), 139-154.
• Humphreys, M. S., and Revelle, W. (1984). Personality, motivation, and performance: a theory of the relationship between individual differences and information processing. Psychological review, 91(2), 153.
• Jensen, M. L., Dunbar, N. E., Connelly, M. S., Taylor, W. D., Hughes, M., Adame, B. and Rozzell, B. (2014). Organizational balancing of website interactivity and control: An examination of ideological groups and the duality of goals. Computers in Human Behavior, 38, 43-54. doi:10.1016=j.chb.2014.05.015.
• Jones, M. A. (1999). Entertaining shopping experiences: An exploratory investigation. Journal of Retailing and Consumer Services, 6(3), 129139.
• Kim, Y. H. and Kim, D. J. (2005, January). A study of online transaction self-efficacy, consumer trust, and uncertainty reduction in electronic commerce transaction. In System Sciences, 2005. HICSS'05. Proceedings of the 38th Annual Hawaii International Conference on (pp. 170c170c). IEEE.
• Kim, H. Y., Kang, J. Y. M., and Johnson, K. K. (2012). Effect of consumer relationship proneness on perceived loyalty program attributes and resistance to change. International Journal of Retail and Distribution Management, 40(5), 376-387.
• Krishen, A. S., Trembaht, L. and Muthaly, S. (2015). From liking to loyalty: the impact of network affinity in the social media digital space. ACM SIGMIS Database: the DATABASE for Advances in Information Systems, 46(2), 30-42.
• Kuo, Y. F., Hu, T. L. and Yang, S. C. (2013). Effects of inertia and satisfaction in female online shoppers on repeat-purchase intention: The moderating roles of word-of-mouth and alternative attraction. Managing Service Quality: An International Journal, 23(3), 168-187.
• Lalwani A. K. (2002) Interpersonal orientation of spouses and household purchase decisions: the case of restaurants. The Service Industries Journal, 22(1), 184-200. DOI: 10.1080/714005064
• Lee, G. G. and Lin, H. F. (2005). Customer perceptions of e-service quality in online shopping. International Journal of Retail and Distribution Management, 33(2), 161-176.
• Liang, T.P., Ho Y.T., Li Y.W. and Turban E. (2011). What drives social commerce: the role of social support and relationship quality. International Journal Of Electronic Commerce, 16(2),69-90.
• Libai, B., Bolton, R., Bügel, M.S., de Ruyter, K., Götz, O., Risselada, H. and Stephen, A.T. (2010). Customer-to-customer interactions: Broadening the scope of word of mouth research. Journal of Service Research, 13(3), 267–282.
• Limayem, M., Khalifa, M., and Frini, A. (2000). What makes consumers buy from Internet? A longitudinal study of online shopping. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, 30(4), 421-432.
• Liu, Y. and Shrum, L.J. (2002). What is interactivity and is it always such a good thing? Implications of definition, person, and situation for the influence of interactivity on advertising effectiveness. Journal of Advertising, 31(4), pp. 53–64
• Lin, S. Y. (2013). The influence of relational selling behavior on relationship quality: The moderating effect of perceived price and customers’ relationship proneness. Journal of Relationship Marketing, 12(3), 204-222.
• Littunen, H. (2000). Entrepreneurship and the characteristics of the entrepreneurial personality. International Journal of Entrepreneurial Behavior and Research, 6(6), 295-310.
• Mann, R. D. (1959). A review of the relationships between personality and performance in small groups. Psychological Bulletin, 56(4), 241.
• Martin, B. A., Wentzel, D. and Tomczak, T. (2008). Effects of susceptibility to normative influence and type of testimonial on attitudes toward print advertising. Journal of Advertising, 37(1), 29-43. DOI: 10.2753/JOA0091-3367370103
• Matute, J., Polo-Redondo, Y. and Utrillas, A. (2016). The influence of EWOM characteristics on online repurchase intention. Mediating roles of trust and perceived usefulness. Online Information Review, 40(7), 1090-1110. doi:10.1108/OIR-11-2015-0373
• McCollough, M. A. and Bharadwaj, S. G. (1992). The recovery paradox: an examination of consumer satisfaction in relation to disconfirmation, service quality, and attribution based theories. Marketing Theory and Applications, 119.
• Mishra, V. and Vaithianathan, S. (2015). Customer personality and relationship satisfaction: Empirical evidence from Indian banking sector. International Journal of Bank Marketing, 33(2), 122-142.
• Mou, J., Shin, D.-S. and Cohen, J. (2017). Understanding trust and perceived usefulness in the consumer acceptance of an e service a longitudinal investigation. Behavior and Information Technology, 36(2), 125-139. doi:10.1080/0144929X.2016.1203024
• Mount, M. K., Barrick, M. R., and Stewart, G. L. (1998). Five-factor model of personality and performance in jobs involving interpersonal interactions. Human performance, 11(2-3), 145-165.
• Nga, J. K. H., and Shamuganathan, G. (2010). The influence of personality traits and demographic factors on social entrepreneurship start up intentions. Journal of Business Ethics, 95(2), 259-282.
• Noyan, F. and Simsek, G. G. (2011). Structural determinants of customer satisfaction in loyalty models: Turkish retail supermarkets. Procedia-Social and Behavioral Sciences, 30, 2134-2138.
• Odekerken-Schroder, G., Wulf, K.D. and Schumacher, P. (2003). Strengthening outcomes of retailer consumer relationships: the dual impact of relationship marketing tactics and consumer personality. Journal of Business Research, 56, 177-190.
• Ogonowski, A., Montandon, A., Botha, E. and Reyneke, M. (2014). Should new online stores invest in social presence elements? The effects of social presence on initial trust formation. Journal of Retailing and Consumer Services, 21(4), 482–491.
• Oliver R. L. (1997). Satisfaction: A behavioral perspective on the consumer. New York: McGraw-Hill.
• Palmer, J. W. (2002). Web site usability, design, and performance metrics. Information Systems Research, 13(2), 151–67.
• Park, C. H., and Kim, Y. G. (2003). Identifying key factors affecting consumer purchase behavior in an online shopping context. International Journal of Retail and Distribution Management, 31(1), 16-29.
• Park, C. and Lee, T. M. (2009). Antecedents of online reviews’ usage and purchase influence: An empirical comparison of US and Korean consumers. Journal of Interactive Marketing, 23(4), 332–340. doi:10.1016/j. intmar.2009.07.001
• Park, Y. A. and Gretzel, U. (2010). Influence of consumers' online decision-making style on comparison shopping proneness and perceived usefulness of comparison shopping tools. Journal of Electronic Commerce Research, 11(4), 342-354.
• Park, Y. and Chen, J. V. (2007). Acceptance and adoption of the innovative use of smartphone. Industrial Management and Data Systems, 107(9), 1349-1365.
• Parish, J. T. and Holloway, B. B. (2010). Consumer relationship proneness: a reexamination and extension across service exchanges. Journal of Services Marketing, 24(1), 61 – 73.
• Perea y Monsuwé, T., Dellaert, B. G., and De Ruyter, K. (2004). What drives consumers to shop online? A literature review. International Journal of Service Industry Management, 15(1), 102-121.
• Ramayah, T., and Ignatius, J. (2005). Impact of perceived usefulness, perceived ease of use and perceived enjoyment on intention to shop online. ICFAI Journal of Systems Management (IJSM), 3(3), 36-51.
• Rauch, A., and Frese, M. (2007). Let's put the person back into entrepreneurship research: A meta-analysis on the relationship between business owners' personality traits, business creation, and success. European Journal of Work and Organizational Psychology, 16(4), 353385.
• Rodgers, S. and Thorson, E. (2000). The interactive advertising model: How users perceive and process online ads. Journal of Interactive Advertising, 1(1), 41-60.
• Rouibah, K., Ramayah, T. and May, O.S. (2009). User acceptance of Internet banking in Malaysia: test of three competing models. International Journal of E-Adoption,1(1), 1-19.
• Saade, R. and Bahli, B. (2004). The impact of cognitive absorption on perceived usefulness and perceived ease of use in on-line learning: an extension of the technology acceptance model. Information and Management, 42, 317-327.
• Salgado, J. F. (1997). The Five Factor Model of personality and job performance in the European Community. Journal of Applied Psychology, 82(1), 30-43.
• Trapnell, P. D., and Campbell, J. D. (1999). Private self-consciousness and the five-factor model of personality: distinguishing rumination from reflection. Journal of Personality and Social Psychology, 76(2), 284.
• Weinstein, L. and Mullins, R. (2012). Technology usage and sales teams: a multilevel analysis of the antecedents of usage. Journal of Personal Selling and Sales Management, 32(2), 245-259.
• Wu, W. Y., Lee, C. L., Fu, C. S., and Wang, H. C. (2013). How can online store layout design and atmosphere influence consumer shopping intention on a website?. International Journal of Retail and Distribution Management, 42(1), 4-24.
• Wulf, K. D., Odekerken-Schröder, G. and Iacobucci, D. (2001). Investments in consumer relationships: A cross-country and cross-industry exploration. Journal of Marketing, 65(4), 33-50.
• Yang, K. (2010). The effects of technology self-efficacy and innovativeness on consumer mobile data service adoption between American and Korean consumers. Journal of International Consumer Marketing, 22(2), 117-127.
• Yeh, R. K.-J. and Teng, J. T. C. (2012). Extended conceptualisation of perceived usefulness empirical test in the context of information system use continuance. Behavior and Information Technology, 31(5), 525-540. doi:10.1080/0144929X.2010.517272
• Zhao, H., and Seibert, S. E. (2006). The big five personality dimensions and entrepreneurial status: a meta-analytical review. Journal of Applied Psychology, 91(2), 259-271.
• Zhou, L., Dai, L. and Zhang, D. (2007). Online shopping acceptance model-A critical survey of consumer factors in online shopping. Journal of Electronic Commerce Research, 8(1), 41.