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Electronic Commerce Research
Published in: Electronic Commerce Research 2/2021

22-09-2019

Four generational cohorts and hedonic m-shopping: association between personality traits and purchase intention

Authors: Sabina Lissitsa, Ofrit Kol

Published in: Electronic Commerce Research | Issue 2/2021

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Abstract

In retailing, it is recognized that prominent differences exist between generational cohorts. As such, analysis of varying patterns of personality traits and their effects between generations is essential for understanding consumer behaviors. This research focuses on the association between the Big Five personality traits and m-shopping intentions of hedonic products among four generational cohorts: baby boomers and Generations X, Y, and Z. Generational cohort theory, the Big Five Personality Model, and resistance to innovations theory are integrated in a theoretical framework. The research was conducted by online survey of 1241 Internet users aged 14–72. Different patterns of effects of personality traits between generations were found. For baby boomers and Generation X, a positive association between openness to experience and m-shopping intention was found. Moreover, in these generations, personality traits were more powerful in predicting m-shopping intention, compared to younger generations. Among Generation Y, extraversion was positively correlated with m-shopping intention. Among Generation Z, a negative correlation between agreeableness and m-shopping intention was found. Based on our findings, we propose a generational approach to marketing strategy and suggest specific practical implications.
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Appendix
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Literature
1.
Dhar, R., & Wertenbroch, K. (2000). Consumer choice between hedonic and utilitarian goods. Journal of Marketing Research, 37(1), 60–71.
2.
Hansen, T., & Møller Jensen, J. (2009). Shopping orientation and online clothing purchases: The role of gender and purchase situation. European Journal of Marketing, 43(9/10), 1154–1170.
3.
Strang, K. D. (2018). Consumer behavior in online risky purchase decisions: Exploring trustworthiness across culture. International Journal of Online Marketing (IJOM), 8(2), 1–26.
4.
Aldás-Manzano, J., Ruiz-Mafé, C., & Sanz-Blas, S. (2009). Exploring individual personality factors as drivers of M-shopping acceptance. Industrial Management & Data Systems, 109(6), 739–757.
5.
Lee, S., & Park, S. (2006). Improving accessibility and security for mobile phone shopping. Journal of Computer Information Systems, 46(3), 124–133.
6.
Zhou, T., & Lu, Y. (2011). The effects of personality traits on user acceptance of mobile commerce. International Journal of Human–Computer Interaction, 27(6), 545–561.
7.
8.
Taipale, S., Wilska, T.-A., & Gilleard, C. (2017). Digital technologies and generational identity: ICT usage across the life course. London: Routledge.
9.
Colucci, M., & Scarpi, D. (2013). Generation Y: Evidences from the fast-fashion market and implications for targeting. Journal of Business Theory and Practice, 1(1), 1.
10.
Lian, J.-W., & Yen, D. C. (2014). Online shopping drivers and barriers for older adults: Age and gender differences. Computers in Human Behavior, 37, 133–143.
11.
Parment, A. (2013). Generation Y vs. baby boomers: Shopping behavior, buyer involvement and implications for retailing. Journal of Retailing and Consumer Services, 20(2), 189–199.
12.
Rahulan, M., Troynikov, O., Watson, C., Janta, M., & Senner, V. (2015). Consumer behavior of generational cohorts for compression sportswear. Journal of Fashion Marketing and Management, 19(1), 87–104.
13.
Eastman, J. K., & Liu, J. (2012). The impact of generational cohorts on status consumption: An exploratory look at generational cohort and demographics on status consumption. Journal of Consumer Marketing, 29(2), 93–102.
14.
Brosdahl, D. J. C., & Carpenter, J. M. (2011). Shopping orientations of US males: A generational cohort comparison. Journal of Retailing and Consumer Services, 18(6), 548–554.
15.
Jackson, V., Stoel, L., & Brantley, A. (2011). Mall attributes and shopping value: Differences by gender and generational cohort. Journal of Retailing and Consumer Services, 18(1), 1–9.
16.
Wu, W.-Y., & Ke, C.-C. (2015). An online shopping behavior model integrating personality traits, perceived risk, and technology acceptance. Social Behavior and Personality: An International Journal, 43(1), 85–97.
17.
Chen, Y., & Lan, Y. (2018). An empirical study of the factors affecting mobile shopping in Taiwan. International Journal of Technology and Human Interaction, 10(1), 19–30.
18.
Groß, M. (2015). Mobile shopping: A classification framework and literature review. International Journal of Retail & Distribution Management, 43(3), 221–241.
19.
Hung, M.-C., Yang, S.-T., & Hsieh, T.-C. (2012). An examination of the determinants of mobile shopping continuance. International Journal of Electronic Business Management, 10(1), 29.
20.
Wong, C. H., Lee, H. S., Lim, Y. H., Chua, B. H., & Tan, G. W. H. (2012). Predicting the consumers’ intention to adopt mobile shopping: An emerging market perspective. International Journal of Network and Mobile Technologies, 3(3), 24–39.
21.
Faulds, D. J., Mangold, W. G., Raju, P. S., & Valsalan, S. (2018). The mobile shopping revolution: Redefining the consumer decision process. Business Horizons, 61(2), 323–338.
22.
Kim, C., Li, W., & Kim, D. J. (2015). An empirical analysis of factors influencing M-shopping use. International Journal of Human–Computer Interaction, 31(12), 974–994.
23.
24.
Kourouthanassis, P. E., & Giaglis, G. M. (2012). Introduction to the special issue mobile commerce: The past, present, and future of mobile commerce research. International Journal of Electronic Commerce, 16(4), 5–18.
25.
Yang, K., & Kim, H.-Y. (2012). Mobile shopping motivation: An application of multiple discriminant analysis. International Journal of Retail & Distribution Management, 40(10), 778–789.
26.
Lustigová, L., & Šálková, D. (2018). Shopping via mobile phones in the Central European Czech Republic Market. AGRIS On-line Papers in Economics and Informatics, 10(665–2019–279), 49.
27.
Madan, K., & Yadav, R. (2018). Understanding and predicting antecedents of mobile shopping adoption: A developing country perspective. Asia Pacific Journal of Marketing and Logistics, 30(1), 139–162.
28.
Ozok, A. A., & Wei, J. (2010). An empirical comparison of consumer usability preferences in online shopping using stationary and mobile devices: Results from a college student population. Electronic Commerce Research, 10(2), 111–137.
29.
Ajzen, I. (2005). Attitudes, personality, and behavior. New York: McGraw-Hill Education.
30.
Chen, T. (2011). Personality traits hierarchy of online shoppers. International Journal of Marketing Studies, 3(4), 23.
31.
Huang, J.-H., & Yang, Y.-C. (2010). The relationship between personality traits and online shopping motivations. Social Behavior and Personality: An International Journal, 38(5), 673–679.
32.
Bosnjak, M., Galesic, M., & Tuten, T. (2007). Personality determinants of online shopping: Explaining online purchase intentions using a hierarchical approach. Journal of Business Research, 60(6), 597–605.
33.
McCrae, R. R., & John, O. P. (1992). An introduction to the five-factor model and its applications. Journal of Personality, 60(2), 175–215.
34.
Gosling, S. D., Rentfrow, P. J., & Swann, W. B., Jr. (2003). A very brief measure of the Big-Five personality domains. Journal of Research in Personality, 37(6), 504–528.
35.
George, J. M., & Zhou, J. (2001). When openness to experience and conscientiousness are related to creative behavior: An interactional approach. Journal of Applied Psychology, 86(3), 513.
36.
Jeronimus, B. F., Riese, H., Sanderman, R., & Ormel, J. (2014). Mutual reinforcement between neuroticism and life experiences: A five-wave, 16-year study to test reciprocal causation. Journal of Personality and Social Psychology, 107(4), 751.
37.
John, O. P., Robins, R. W. & Pervin, L. A. (2008). Handbook of personality: Theory and research (3rd ed.). New York: Guilford.
38.
Straughan, R. D., & Roberts, J. A. (1999). Environmental segmentation alternatives: A look at green consumer behavior in the new millennium. Journal of Consumer Marketing, 16(6), 558–575.
39.
Fitzgerald Bone, P. (1991). Identifying mature segments. Journal of Consumer Marketing, 8(4), 19–32.
40.
Chaney, D., Touzani, M., & Ben Slimane, K. (2017). Marketing to the (new) generations: Summary and perspectives. London: Taylor & Francis.
41.
Ingelhart, R. (1977). The silent revolution. Changing values and political style among western publics. Princeton: Princeton University Press.
42.
Meredith, G., & Schewe, C. (1994). The power of cohorts. American Demographics, 16(12), 22–28.
43.
Strauss, W., & Howe, N. (1991). Generations: The history of America's future, 1584–2069. New York: William Morrow.
44.
Strauss, W., Howe, N. (1997). The fourth turning: What the cycles of history tell us abut America’s next rendezvous with destiny. New York: Broadway Books.
45.
Egri, C. P., & Ralston, D. A. (2004). Generation cohorts and personal values: A comparison of China and the United States. Organization Science, 15(2), 210–220.
46.
Hung, K. H., Gu, F. F., & Yim, C. K. B. (2007). A social institutional approach to identifying generation cohorts in China with a comparison with American consumers. Journal of International Business Studies, 38(5), 836–853.
47.
Pekerti, A. A., & Arli, D. (2017). Do cultural and generational cohorts matter to ideologies and consumer ethics? A comparative study of Australians, Indonesians, and Indonesian migrants in Australia. Journal of Business Ethics, 143(2), 387–404.
48.
Arli, D., & Pekerti, A. (2016). Investigating the influence of religion, ethical ideologies and generational cohorts toward consumer ethics: Which one matters? Social Responsibility Journal, 12(4), 770–785.
49.
Parment, A. (2011). Generation Y in consumer and labour markets (Vol. 15). London: Routledge.
50.
Moore, M., & Carpenter, J. M. (2008). Intergenerational perceptions of market cues among US apparel consumers. Journal of Fashion Marketing and Management: An International Journal, 12(3), 323–337.
51.
Schewe, C. D., & Noble, S. M. (2000). Market segmentation by cohorts: The value and validity of cohorts in America and abroad. Journal of Marketing Management, 16(1–3), 129–142.
52.
Markert, J. (2004). Demographics of age: Generational and cohort confusion. Journal of Current Issues & Research in Advertising, 26(2), 11–25.
53.
Norum, P. S. (2003). Examination of generational differences in household apparel expenditures. Family and Consumer Sciences Research Journal, 32(1), 52–75.
54.
Kumar, V., Lahiri, A., & Dogan, O. B. (2018). A strategic framework for a profitable business model in the sharing economy. Industrial Marketing Management, 69, 147–160.
55.
Rosen, L. D. (2011). Teaching the iGeneration. Educational Leadership, 68(5), 10–15.
56.
Stewart, A. J. & Torges, C. M. (2006). Social, historical, and developmental influences on the psychology of the baby boom at midlife. The baby boomers grow up. Contemporary Perspectives on Midlife, 23, 44.
57.
Willetts, D. (2011). Pinch: How the baby boomers took their children's future-and why they should give it back. London: Atlantic Books.
58.
Guerrieri, P., & Bentivegna, S. (2011). The economic impact of digital technologies: Measuring inclusion and diffusion in Europe. Cheltenham: Edward Elgar Publishing.
59.
Yusof, A. A., Mokhtar, N. F., & Set, K. (2019). Cost, security and features influencing baby boomers behavioral intention on adopting Whatsapp application. International Journal of Accounting, 4(18), 67–77.
60.
Kuoppamäki, S.-M., Taipale, S., & Wilska, T.-A. (2017). The use of mobile technology for online shopping and entertainment among older adults in Finland. Telematics and Informatics, 34(4), 110–117.
61.
Berraies, S., Ben Yahia, K., & Hannachi, M. (2017). Identifying the effects of perceived values of mobile banking applications on customers: Comparative study between baby boomers, generation X and generation Y. International Journal of Bank Marketing, 35(6), 1018–1038.
62.
Keller, S. L., & Leslie, P. (2017). Aging in place: Baby boomers and what we can learn from Japan. Perspectives of the ASHA Special Interest Groups, 2(15), 53–59.
63.
Dhanapal, S., Vashu, D., & Subramaniam, T. (2015). Perceptions on the challenges of online purchasing: A study from “baby boomers”, generation “X” and generation “Y” point of views. Contaduría y Administración, 60, 107–132.
64.
65.
Atkins, K. G., & Hyun, S.-Y. J. (2016). Smart shoppers’ purchasing experiences: Functions of product type, gender, and generation. International Journal of Marketing Studies, 8(2), 1.
66.
Valkeneers, G., & Vanhoomissen, T. (2012). Generations living their own life: The differences in lifestyle and consumer behaviour between busters and baby boomers. Journal of Customer Behaviour, 11(1), 53–68.
67.
Lyons, S. T., Duxbury, L., & Higgins, C. (2007). An empirical assessment of generational differences in basic human values. Psychological Reports, 101(2), 339–352.
68.
Barford, I. N., & Hester, P. T. (2011). Analysis of generation Y workforce motivation using multiattribute utility theory. Defense Acquisition Univ FT Belvoir VA.
69.
Eisner, S. P. (2005). Managing generation Y. SAM Advanced Management Journal, 70(4), 4.
70.
Shaw, S., & Fairhurst D. (2008). Engaging a new generation of graduates. Education + Training, 50(5), 366–378.
71.
Bennett, S., Maton, K., & Kervin, L. (2008). The ‘digital natives’ debate: A critical review of the evidence. British Journal of Educational Technology, 39(5), 775–786.
72.
Ahn, J., & Jung, Y. (2016). The common sense of dependence on smartphone: A comparison between digital natives and digital immigrants. New Media & Society, 18(7), 1236–1256.
73.
Acar, A. B. (2014). Do intrinsic and extrinsic motivation factors differ for Generation X and Generation Y. International Journal of Business and Social Science, 5(5), 12–20.
74.
Williams, K. C., & Page, R. A. (2011). Marketing to the generations. Journal of Behavioral Studies in Business, 3, 1.
75.
Gursoy, D., Maier, T. A., & Chi, C. G. (2008). Generational differences: An examination of work values and generational gaps in the hospitality workforce. International Journal of Hospitality Management, 27(3), 448–458.
76.
Crumpacker, M., & Crumpacker, J. M. (2007). Succession planning and generational stereotypes: Should HR consider age-based values and attitudes a relevant factor or a passing fad? Public Personnel Management, 36(4), 349–369.
77.
Reisenwitz, T. H., & Iyer, R. (2009). Differences in Generation X and Generation Y: Implications for the organization and marketers. The Marketing Management Journal, 19(2), 91–103.
78.
79.
Bencsik, A., Horváth-Csikós, G., & Juhász, T. (2016). Y and Z generations at workplaces. Journal of Competitiveness, 8(3), 90–106.
80.
Bilgihan, A. (2016). Gen Y customer loyalty in online shopping: An integrated model of trust, user experience and branding. Computers in Human Behavior, 61, 103–113.
81.
82.
Seounmi Y., & Seunghyun K. (2019). Newsfeed native advertising on Facebook: young millennials’ knowledge, pet peeves, reactance and ad avoidance. International Journal of Advertising, 38(5), 651–683.
83.
Liu, H., Wu, L., & Li, X. (2019). Social media envy: How experience sharing on social networking sites drives millennials’ aspirational tourism consumption. Journal of Travel Research, 58(3), 355–369.
84.
Wood, S. (2013). Generation Z as consumers: Trends and innovation. Institute for Emerging Issues: NC State University (pp. 1–3).
85.
Smith, K. T. (2019). Mobile advertising to digital natives: Preferences on content, style, personalization, and functionality. Journal of Strategic Marketing, 27(1), 67–80.
86.
Özkan, A. P. P. M. (2017). Generation Z—The global market’s new consumers-and their consumption habits: Generation Z consumption scale. European Journal of Multidisciplinary Studies, 5(1), 150–157.
87.
Smits, I. A. M., Dolan, C. V., Vorst, H., Wicherts, J. M., & Timmerman, M. E. (2011). Cohort differences in Big Five personality factors over a period of 25 years. Journal of Personality and Social Psychology, 100(6), 1124.
88.
Goldsmith, R. (2016). The Big Five, happiness, and shopping. Journal of Retailing and Consumer Services, 31, 52–61.
89.
Mroczek, D. K., & Spiro Iii, A. (2003). Modeling intraindividual change in personality traits: Findings from the Normative Aging Study. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 58(3), P153–P165.
90.
Twenge, J. M. (2001). Birth cohort changes in extraversion: A cross-temporal meta-analysis, 1966–1993. Personality and Individual Differences, 30(5), 735–748.
91.
Gentile, B., Campbell, W. K., & Twenge, J. M. (2013). Generational cultures. In Cohen A. B.(Ed.). Culture reexamined: Broadening our understanding of social and evolutionary influences (pp. 31–48). Washington, DC: American Psychological Association.
92.
Twenge, J. M., & Campbell, S. M. (2011). Generational differences in psychological traits and their impact on the workplace. IEEE Engineering Management Review, 39(2), 72–84.
93.
Ram, S. (1987). A model of innovation resistance. Advances in Consumer Research, 14(1), 208–212.
94.
yRogers, E. (2003). Diffusion of innovations (5th Ed.). New York, NY: Free Press.
95.
Laukkanen, T., Sinkkonen, S., Kivijärvi, M., & Laukkanen, P. (2007). Innovation resistance among mature consumers. Journal of Consumer Marketing, 24(7), 419–427.
96.
Ram, S., & Sheth, J. N. (1989). Consumer resistance to innovations: The marketing problem and its solutions. Journal of Consumer Marketing, 6(2), 5–14.
97.
Rogers, E. M. (2003). Elements of diffusion. Diffusion of Innovations, 5, 1–38.
98.
Lissitsa, S., & Kol, O. (2016). Generation X vs. Generation Y—A decade of online shopping. Journal of Retailing and Consumer Services, 31, 304–312.
99.
Quazi, A., & Talukder, M. (2011). Demographic determinants of adoption of technological innovation. Journal of Computer Information Systems, 52(1), 34–42.
100.
Zhang, R., Chen, J. Q., & Lee, C. J. (2013). Mobile commerce and consumer privacy concerns. Journal of Computer Information Systems, 53(4), 31–38.
101.
Mou, J., Shin, D.-H., & Cohen, J. F. (2017). Trust and risk in consumer acceptance of e-services. Electronic Commerce Research, 17(2), 255–288.
102.
Cozzarin, B. P., & Dimitrov, S. (2016). Mobile commerce and device specific perceived risk. Electronic Commerce Research, 16(3), 335–354.
103.
Hetts, J. J., Boninger, D. S., Armor, D. A., Gleicher, F., & Nathanson, A. (2000). The influence of anticipated counterfactual regret on behavior. Psychology & Marketing, 17(4), 345–368.
104.
Heidenreich, S., & Handrich, M. (2015). What about passive innovation resistance? Investigating adoption-related behavior from a resistance perspective. Journal of Product Innovation Management, 32(6), 878–903.
105.
Bagozzi, R. P. (1999). Consumer resistance to, and acceptance of, innovations. Advances in Consumer Research, 26, 218–225.
106.
Adams, D., & Hess, M. (2010). Social innovation and why it has policy significance. London: SAGE Publications.
107.
Devaraj, S., Easley, R. F., & Crant, J. M. (2008). Research note—How does personality matter? Relating the five-factor model to technology acceptance and use. Information Systems Research, 19(1), 93–105.
108.
Badowska, S., Zamojska, A., & Rogala, A. (2015). Baby boomers’ attitudes toward innovations: Empirical research in Poland. Procedia-Social and Behavioral Sciences, 213, 1050–1056.
109.
Lau, U. H., Lee, L. E., Lew, D. K., Loo, L. S., & Ooi, S. X. (2018). The awakening frontier: Barriers repelling baby boomers from adopting mobile payment in Malaysia.
110.
Olver, J. M., & Mooradian, T. A. (2003). Personality traits and personal values: A conceptual and empirical integration. Personality and Individual Differences, 35(1), 109–125.
111.
Hendrawan, D., & Nugroho, D. A. (2018). Influence of personality on impulsive buying behaviour among Indonesian young consumers. International Journal of Trade and Global Markets, 11(1–2), 31–39.
112.
Barrick, M. R., & Mount, M. K. (1991). The Big Five personality dimensions and job performance: A meta-analysis. Personnel Psychology, 44(1), 1–26.
113.
Rautio, A.-M. (2018). The role of personality traits and advertisement characteristics in social shopping. An experimental study of personality and Instagram marketing. Finland: BA thesis, School of Business, Aalto University.
114.
Babin, B. J., Darden, W. R., & Griffin, M. (1994). Work and/or fun: Measuring hedonic and utilitarian shopping value. Journal of Consumer Research, 20(4), 644–656.
115.
Mohamed, N., Hussein, R., Hidayah Ahmad Zamzuri, N., & Haghshenas, H. (2014). Insights into individual's online shopping continuance intention. Industrial Management & Data Systems, 114(9), 1453-1476.
116.
McCrae, R. R., & Costa, P. T. (2003). Personality in adulthood: A five-factor theory perspective. New York: Guilford Press.
117.
Ackerman, R. A., Witt, E. A., Donnellan, M. B., Trzesniewski, K. H., Robins, R. W., & Kashy, D. A. (2011). What does the narcissistic personality inventory really measure? Assessment, 18(1), 67–87.
118.
119.
Sedikides, C., Cisek, S., & Hart, C. M. (2011). Narcissism and brand name consumerism. The handbook of narcissism and narcissistic personality disorder: Theoretical approaches, empirical findings, and treatments, 382–392.
120.
Cisek, S. Z., Sedikides, C., Hart, C. M., Godwin, H. J., Benson, V., & Liversedge, S. P. (2014). Narcissism and consumer behaviour: A review and preliminary findings. Frontiers in Psychology, 5, 232.
121.
Westlake, E. J. (2008). Friend me if you Facebook: Generation Y and performative surveillance. The Drama Review, 52(4), 21–40.
122.
Rothstein, M. G., Paunonen, S. V., Rush, J. C., & King, G. A. (1994). Personality and cognitive ability predictors of performance in graduate business school. Journal of Educational Psychology, 86(4), 516.
123.
John, O. P., & Srivastava, S. (1999). The Big Five trait taxonomy: History, measurement, and theoretical perspectives. Handbook of Personality: Theory and Research, 2(1999), 102–138.
124.
Li, N., & Zhang, P. (2002). Consumer online shopping attitudes and behavior: An assessment of research. In AMCIS 2002 proceedings (Vol. 74).
125.
Chiu, W., Kim, T., & Won, D. (2018). Predicting consumers’ intention to purchase sporting goods online: an application of the model of goal-directed behavior. Asia Pacific Journal of Marketing and Logistics, 30(2), 333–351.
126.
Hernández, B., Jiménez, J., & José Martín, M. (2011). Age, gender and income: Do they really moderate online shopping behaviour? Online Information Review, 35(1), 113–133.
127.
Gupta, A., & Arora, N. (2017). Understanding determinants and barriers of mobile shopping adoption using behavioral reasoning theory. Journal of Retailing and Consumer Services, 36, 1–7.
128.
Bigne, E., Ruiz, C., & Sanz, S. (2005). The impact of internet user shopping patterns and demographics on consumer mobile buying behaviour. Journal of Electronic Commerce Research, 6(3), 193.
129.
Katz-Gerro, T., Raz, S., & Yaish, M. (2009). How do class, status, ethnicity, and religiosity shape cultural omnivorousness in Israel? Journal of Cultural Economics, 33(1), 1–17.
130.
Lissitsa, S., & Lev-On, A. (2014). Gaps close, gaps open: A repeated cross-sectional study of the scope and determinants of the ethnic digital divide. International Journal of Electronic Governance, 7(1), 56–71.
131.
Lissitsa, S., & Roth Cohen, O. (2018). The decade of online shopping in the Jewish uUltra-orthodox community. Journal of Media and Religion, 17(2), 74–89.
132.
Farag, S., Schwanen, T., Dijst, M., & Faber, J. (2007). Shopping online and/or in-store? A structural equation model of the relationships between e-shopping and in-store shopping. Transportation Research Part A: Policy and Practice, 41(2), 125–141.
133.
McManus, I., & Furnham, A. (2010). “Fun, fun, fun”: Types of fun, attitudes to fun, and their relation to personality and biographical factors. Psychology, 1(03), 159.
Metadata
Title
Four generational cohorts and hedonic m-shopping: association between personality traits and purchase intention
Authors
Sabina Lissitsa
Ofrit Kol
Publication date
22-09-2019
Publisher
Springer US
Published in
Electronic Commerce Research / Issue 2/2021
Print ISSN: 1389-5753
Electronic ISSN: 1572-9362
DOI
https://doi.org/10.1007/s10660-019-09381-4

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