GELENEKSEL, DİJİTAL VE FİJİTAL PAZARLAMA BAĞLAMINDA AMPİRİK ÇALIŞMALARIN BİBLİYOMETRİK VERİ KAYNAKLARININ KARŞILAŞTIRMALI ANALİZİ

Öz

Bu çalışmanın amacı, 1960-1979 (geleneksel pazarlama) 1980-2006 (dijital pazarlama) 2007-2021 (fijital pazarlama) dönemini kapsayan pazarlama alanlarında ampirik tüketici davranışları araştırmalarındaki son gelişmeleri değerlendirmek ve karşılaştırmalı olarak incelemektir. Çalışma kapsamında geleneksel, dijital ve fijital pazarlama alanındaki ampirik çalışmalar yayın kaynağı türü, temel özellikleri, çalışma konusu, teorik altyapı, araştırma değişkenleri açısından 5 adımda incelenmiştir. Veri analizinde VOSviewer programı ile gerçekleştirilen bibliyometrik analiz kullanılmıştır. Çalışma sonucunda farklı pazarlama alanlarına yönelik farklı dergilerin yayın sürecine dahil edildiği ve fijital pazarlama çalışmalarında yazar sayısının arttığı tespit edilmiştir. Karma yöntemlerin ön plana çıktığı, anketin en çok kullanılan veri toplama aracı olduğu ve YEM analizinin son zamanlarda daha fazla kullanılmaya başlandığı sonucuna varılmıştır. Geleneksel pazarlamada marka satın alma niyeti, karar verme süreci, memnuniyetsizlik/memnuniyet konuları ön plana çıkarken, dijital pazarlamada TAM teorisi temelinde online incelemeler önem kazanırken, fijital pazarlamada AR ve VR teknolojileri konuları öne çıkmıştır. Araştırma değişkenleri açısından niyet, tutum ve memnuniyet temaları tüm dönemlerde motor temalar olarak ön plana çıkmıştır.

Anahtar Kelimeler

• Geleneksel Pazarlama
• Dijital Pazarlama
• Fijital Pazarlama
• Bibliyometrik Veri
• Karşılaştırmalı Analiz

COMPARATIVE ANALYSIS OF BIBLIOMETRIC DATA SOURCES OF EMPIRICAL STUDIES IN THE CONTEXT OF TRADITIONAL, DIGITAL AND PHYGITAL MARKETING

Öz

The aim of this study is to evaluate and comparatively examine the latest developments of empirical consumer behavior research in the field of marketing, covering the period 1960-1979 (traditional marketing) 1980-2006 (digital marketing) 2007-2021 (phygital marketing). Within the scope of the study, empirical studies in the field of traditional, digital and phygital marketing were examined in 5 steps in terms of publication source type, basic characteristics, study subject, theoretical background, research variables. In data analysis, bibliometric analysis was used with VOSviewer program. As a result of the study, it has been determined that different journals for different marketing fields are included in the publication production process, and the number of authors has increased in phygital marketing studies. It was concluded that mixed methods came to the fore, the questionnaire was the most used data collection tool, and SEM analysis started to be used more recently. While brand purchase intention, decision making process, dissatisfaction/satisfaction subjects come to the fore in traditional marketing, online reviews have gained importance on the basis of TAM theory in digital marketing, AR and VR technologies are concentrated in phygital marketing. In terms of research variables, intention, attitude and satisfaction themes came to the fore as motor themes in all periods.

Anahtar Kelimeler

• Traditional Marketing
• Digital Marketing
• Phygital Marketing
• Bibliometric Data
• Comparative Analysis

Kaynakça

1. Accenture, (2020) Banking consumer study: making digital more human. Available at: https://www. accenture.com/us-en/insights/banking/consumer-study-making-digital-banking-more-human [Accessed 19 April 2022].
2. Ajzen, I. (1991). The theory of planned behavior. Organizational behavior and human decision processes, 50(2), 179-211.
3. Anderson, R. E. (1973). Consumer dissatisfaction: The effect of disconfirmed expectancy on perceived product performance. Journal of Marketing Research, 10(1), 38–44.
4. Aronson, E., & Carlsmith, J. M. (1963). Effect of the severity of threat on the devaluation of forbidden behavior. The Journal of Abnormal and Social Psychology, 66(6), 584-588.
5. Azis, N., Amin, M., Chan, S., & Aprilia, C. (2020). How smart tourism technologies affect tourist destination loyalty. Journal of Hospitality and Tourism Technology, 11(4), 603-625.
6. Baek, E., Choo, H. J., Wei, X. & Yoon, S. Y. (2020). Understanding the virtual tours of retail stores: how can store brand experience promote visit intentions?. International Journal of Retail & Distribution Management, 8(7), 1-18.
7. Balaji, M. S., & Roy, S. K. (2017). Value co-creation with Internet of things technology in the retail industry. Journal of Marketing Management, 33(1-2), 7-31.
8. Ballina, F. J., Valdes, L. & Valle, E. D. (2019). The phygital experience in the smart tourism destination. International Journal of Tourism Cities, 5(4), 656-671.

9. Banik, S. (2021). Exploring the involvement-patronage link in the phygital retail experiences. Journal of Retailing and Consumer Services, 63, 1-12.
10. Baytar, F., Chung, T., & Shin, E. (2020). Evaluating garments in augmented reality when shopping online. Journal of Fashion Marketing and Management, 24(4), 667-683.
11. Becker, G. S. (1965). A Theory of the Allocation of Time. The Economic Journal, 75(299), 493–517.
12. Bell, G. D. (1967). The automobile buyer after the purchase. Journal of Marketing, 31(3), 12–16.
13. Bhatnagar, A., Misra, S. and Rao, H.R. (2000) On risk, convenience, and internet shopping behavior. Communications of the ACM, 43, 98-105.
14. Bird, M., & Ehrenberg, A. S. C. (1966). Intentions-to-buy and claimed brand usage. OR, 17(1), 27–46.
15. Bird, M., Channon, C., & Ehrenberg, A. S. C. (1970). Brand image and brand usage. Journal of Marketing Research, 7(3), 307–314.
16. Birdwell, A. E. (1968). A study of the ınfluence of image congruence on consumer choice. The Journal of Business, 41(1), 76–88.
17. Bonera, M., & Corvi, E. (2014), The relevance of visual merchandising for online retailers, Journal of Applied Behavioral Economics (IJABE), 3(4),1-16.
18. Bonfield, E. H. (1974). Attitude, social influence, personal norm, and intention interactions as related to brand purchase behavior. Journal of Marketing Research, 11(4), 379–389.
19. Cardozo, R. N. (1965). An experimental study of customer effort, expectation, and satisfaction. Journal of Marketing Research, 2(3), 244–249.
20. Chang, S.H., Chih, W.H., Liou, D.K., & Yang, Y.T. (2016), The mediation of cognitive attitude for online shopping, Information Technology and People, 29(3),618-646.
21. Chang, Y. W. & Chen, J. (2021). What motivates customers to shop in smart shops? The impacts of smart technology and technology readiness. Journal of Retailing and Consumer Services, 58, 1-11.
22. Chau, P. Y. K., Au, G., & Tam, K. Y. (2000) Impact of information presentation modes on online shopping: An empirical evaluation of a broadband interactive shopping service. Journal of Organizational Computing and Electronic Commerce, 10(1), 1-20.
23. Childers, T. L., Carr, L. C., Peck, J., & Carson, S. (2001). Hedonic and utilitarian motivations for online retail shopping behavior. Journal of Retailing, 77(4), 511-535.
24. Chu, W., Choi, B., & Song, M. R. (2005). The role of on-line retailer brand and infomediary reputation in increasing consumer purchase intention. International Journal of Electronic Commerce, 9(3), 115–127.
25. Citrin, A. V., Sprott, D. E., Silverman, S. N., & Stem, D. E. (2000). Adoption of internet shopping: the role of consumer innovativeness. Industrial Management & Data Systems, 100(7), 294-300.
26. Clarke, K. & Belk, R. W. (1979). The effects of product involvement and task definition on anticipated consumer effort. in NA - Advances in Consumer Research Vol. 6, eds. Wilkie, W. L., & Abor, A. Association for Consumer Research, 313-318.
27. Cruz-Cárdenas, J., Zabelina, E., Guadalupe-Lanas, J., Palacio-Fierro, A., & Ramos-Galarza, C. (2021). COVID-19, consumer behavior, technology, and society: A literature review and bibliometric analysis. Technological Forecasting and Social Change, 173, 121179.
28. Csikszentmihalyi, M. (1990). Flow: The psychology of optimal experience. Journal of Leisure Research, 24(1), 93-94.
29. Çakın, Ö., & Yaman, D. (2020). Fijital (Phygital) Pazarlama Uygulamaları Üzerine Bir İnceleme: Amazon Go Örneği. Middle Black Sea Journal of Communication Studies, 5(1), 1-10.
30. Davis, H. L. (1971). Measurement of husband-wife influence in consumer purchase decisions. Journal of Marketing Research, 8(3), 305–312.
31. Davis, F. D. (1985). A Technology Acceptance Model for empirically testing new end-user information systems: Theory and results. Massachusetts Institute of Technology.
32. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 13(3), 319-340.
33. Duhan, P., & Singh, A. (Eds.). (2019). M-Commerce: Experiencing the phygital retail. CRC Press.
34. Dunakhe, K. & Panse, C. (2021), Impact of digital marketing – a bibliometric review, International Journal of Innovation Science, Vol. ahead-of-print No. ahead-of-print.
35. Faruk, M., Rahman, M., & Hasan, S. (2021). How digital marketing evolved over time: A bibliometric analysis on scopus database, Heliyon, 7(2), 1-9.
36. Fireworker, R.B., & Friedman, H.H. (1977). The effects of endorsements on product evaluatıon. Decision Sciences, 8, 576-583.
37. Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research, Addison-Wesley: Reading MA.
38. Forsythe, S. M., & Shi, B. (2003). Consumer patronage and risk perceptions in internet shopping. Journal of Business Research, 56(11), 867-875.
39. Foxall, G. R. (1975). Social factors in consumer choice: Replication and extension. Journal of Consumer Research, 2(1), 60–64.
40. Gefen, D., Karahanna, E., & Straub, D.W. (2003). Inexperience and experience with online stores: the importance of TAM and trust. IEEE Transactions on Engineering Management, 50, 307-321.
41. Gefen, D., & Straub, D. W. (2000). The relative importance of perceived ease of use in IS adoption: A study of e-commerce adoption. Journal of the Association for Information Systems, 1(8), 1-30.
42. Gill, J., Johnson, P. & Clark, M. (2010). Research Methods for Managers, SAGE Publications
43. Ghorbani, Z., Kargaran, S., Saberi, A., Haghighinasab, M., Jamali, S. M., & Ale Ebrahim, N. (2021). Trends and patterns in digital marketing research: bibliometric analysis. Journal of Marketing Analytics, 10, 158-172.
44. Golgeci, I., Ali, I., Ritala, P., & Arslan, A. (2022), A bibliometric review of service ecosystems research: current status and future directions, Journal of Business & Industrial Marketing, 37(4), 841-858.
45. Granbois, D. H., & Summers, J. O. (1972). On the predictive accuracy of subjective purchase probabilities, in SV- Proceedings of the Third Annual Conference of the Association for Consumer Research, eds. Venkatesan, M. Chicago, IL: Association for Consumer Research, 502-511.
46. Grewal, D., Roggeveen, A.L., & Nordfält, J. (2017), The future of retailing, Journal of Retailing, 93(1), 1-6.
47. Ha, H. (2004). Factors influencing consumer perceptions of brand trust online. Journal of Product & Brand Management, 13(5), 329-342.
48. Ha, Y. H., & Perks H. (2005). Effects of consumer perceptions of brand experience on the web: Brand familiarity, satisfaction and brand trust. Journal of Consumer Behaviour, 4(6), 438-442.
49. Han, S. L., An, M., Han, J. J., & Lee, J. (2020). Telepresence, time distortion, and consumer traits of virtual reality shopping. Journal of Business Research, 118, 311-320.
50. Hansen, F. (1969). Consumer choice behavior: An experimental approach. Journal of Marketing Research, 6(4), 436–443.
51. Hayes, A. F. (2013). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. New York, London: The Guilford Press
52. Holbrook, M.B. & Hirschman, E.C. (1982), The experiential aspects of consumption: consumer fantasies, feelings, and fun, Journal of Consumer Research, 9(2), 132-140.
53. Holloway, R. J. (1967). An experiment on consumer dissonance. Journal of Marketing, 31(1), 39–43.
54. Hovland, C. I., Harvey, O. J., & Sherif, M. (1957). Assimilation and contrast effects in reactions to communication and attitude change. The Journal of Abnormal and Social Psychology, 55(2), 244–252.
55. Huang, T., & Liao, S. (2015). A model of acceptance of augmented-reality interactive technology: The moderating role of cognitive innovativeness. Electronic Commerce Research, 15(2), 269-295.
56. Huang, W., Schrank, H. & Dubinsky, A. J. (2004). Effect of brand name on consumers' risk perceptions of online shopping. Journal of Consumer Behaviour: An International Research Review, 4(1), 40-50.
57. Hutton, J.G. (1996), Integrated marketing communications and the evolution of marketing thought, Journal of Business Research, 37(3),155-162.
58. Jacoby, J., & Kyner, D. B. (1973). Brand loyalty vs. repeat purchasing behavior. Journal of Marketing Research, 10(1), 1–9.
59. Jarvenpaa, S.L., Tractinsky, N., & Vitale, M.R. (2000). Consumer trust in an internet store. Information Technology and Management, 1(1), 45-71.
60. Jarvenpaa, S.L., & Todd, P. A. (1996) Consumer reactions to electronic shopping on the world wide web, International Journal of Electronic Commerce, 1(2), 59-88.
61. Jin, B., Kim, G., Moore, M., & Rothenberg, L. (2021). Consumer store experience through virtual reality: its effect on emotional states and perceived store attractiveness. Fashion and Textiles, 8(1), 1-21.
62. Jıang. Z. & Benbasat, I. (2004). Virtual product experience: Effects of visual and functional control of products on perceived diagnosticity and flow in electronic shopping. Journal of Management Information Systems, 21(3), 111-147.
63. Kim, D., & Ammeter, A.P. (2018), Shifts in online consumer behavior: a preliminary investigation of the net generation, Journal of Theoretical and Applied Electronic Commerce Research, 13(1), 1-25.
64. Kim, J. H., Kim, M., Park, M., & Yoo, J. (2021). How interactivity and vividness influence consumer virtual reality shopping experience: the mediating role of telepresence. Journal of Research in Interactive Marketing, 15(3), 502-525.
65. Kollat, D. T., & Willett, R. P. (1967). Customer ımpulse purchasing behavior. Journal of Marketing Research, 4(1), 21–31.
66. Korzaan, M. L. (2003). Going with the Flow: Predicting online purchase ıntentions. Journal of Computer Information Systems, 43(4), 25-31.
67. Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behavior. Information Systems Research, 13(2), 205–223.
68. Kulviwat, S. & Guo, C. & Engchanil, N. (2004). Determinants of online information search: a critical review and assessment. Internet Research, 14(3), 245–253.
69. Kumar, B., Sharma, A., Vatavwalaa, S. & Kumar, P. (2020), Digital mediation in business-to-business marketing: a bibliometric analysis, Industrial Marketing Management, 85(2),126-140.
70. Kwon, W. S., & Lennon S. J. (2009). Reciprocal effects between multichannel retailers’ offline and online brand images. Journal of Retailing, 85(3), 376–390.
71. Lambert, Z. V. (1970). Marketing notes and communications: Product perception: An ımportant variable in price strategy. Journal of Marketing, 34(4), 68–71.
72. Lamberton, C., & Stephen, A.T. (2016), A thematic exploration of digital, social media, and mobile marketing: research evolution from 2000 to 2015 and an agenda for future inquiry, Journal of Marketing, 80(6), 146-172.
73. Lee, M. K. O., & Turban, E. (2001). A trust model for consumer internet shopping. International Journal of Electronic Commerce, 6(1), 75–91.
74. Li, N. & Zhang, P. (2002). Consumer Online Shopping Attitudes and Behavior: An assessment of research. Proceedings of the Americas Conference on Information Systems (AMCIS’2002), Dallas, 9-11.
75. Littell, J. H., Corcoran, J., & Pillai, V. (2008). Systematic reviews and meta-analysis. Oxford University Press.
76. Locander, W. B., & Hermann, P. W. (1979). The effect of self-confidence and anxiety on information seeking in consumer risk reduction. Journal of Marketing Research, 16(2), 268–274.
77. Luarn, P. & Lin, H. H. (2005). Toward an understanding of the behavioral intention to use mobile banking, Computers in Human Behavior, 21(6), 873-891.
78. Mazis, M. B., Olli T. A., & Eugène R. K. (1975). A Comparison of Four MultiAttribute Models in the Prediction of Consumer Attitudes, Journal of Consumer Research, 2(1), 38-52.
79. McConnell, J. D. (1968). The development of brand loyalty: An experimental study. Journal of Marketing Research, 5(1), 13-19.
80. McDougall, G. H. G. (1978) Comparative advertising: The effect of claim type and brand loyalty. Current Issues and Research in Advertising, 1(1), 39-52.
81. McLean, G. & Wilson, A. (2019). Shopping in the digital world: Examining customer engagement through augmented reality mobile applications. Computers in Human Behavior, 101, 210–224.
82. Mehrabian, A., & Russell, J. A. (1974). An approach to environmental psychology. The MIT Press.
83. Miyazaki, A. D., & Fernandez, A. (2001). Consumer perceptions of privacy and security risks for online shopping. The Journal of Consumer Affairs, 35(1), 27–44.
84. Muñoz-Leiva, F., Rodríguez López, M.E., Liebana-Cabanillas, F., & Moro, S. (2021), Past, present, and future research on self-service merchandising: a co-word and text mining approach, European Journal of Marketing, 55(8), 2269-2307.
85. Nakazawa, J., & Tokuda, H. (2007). Phygital map: Accessing digital multimedia from physical map. In 21st International Conference on Advanced Information Networking and Applications Workshops (AINAW'07). IEEE.
86. Namias, J. (1960). Intentions to purchase related to consumer characteristics. Journal of Marketing, 25(1), 32–36.
87. Nusair, K. (2020), Developing a comprehensive life cycle framework for social media research in hospitality and tourism: A bibliometric method 2002-2018, International Journal of Contemporary Hospitality Management, 32(3), 1041-1066.
88. O'Cass, A., & Fenech, T. (2003). Web retailing adoption: Exploring the nature of internet users Web retailing behaviour. Journal of Retailing and Consumer Services, 10, 81-94.
89. Oliver, R. L. (1977). Effect of expectation and disconfirmation on postexposure product evaluations: An alternative interpretation. Journal of Applied Psychology, 62(4), 480–486.
90. Olshavsky, R. W., & Miller, J. A. (1972). Consumer expectations, product performance, and perceived product quality. Journal of Marketing Research, 9(1), 19–21.
91. Oshikawa, S. (1968). The theory of cognitive dissonance and experimental research. Journal of Marketing Research, 5(4), 429–430.
92. Park, J. S., Ha, S., & Jeong, S. W. (2020). Consumer acceptance of self-service technologies in fashion retail stores. Journal of Fashion Marketing and Management: An International Journal, 25(2), 371-388.
93. Paul, J., Lim, W.M., O’Cass, A., Hao, A.W., & Bresciani, S. (2021), Systematic procedures and rationales for systematic literature reviews (SPAR-4-SLR). International Journal of Consumer Studies, 45(3),1-16.
94. Petit, O., Velasco, C., & Spence, C. (2019), Digital sensory marketing: integrating new technologies into multisensory online experience, Journal of Interactive Marketing, 45, 42-61.
95. Pikkarainen, T., Pikkarainen, K., Karjaluoto, H., Pahnila, S. (2004). Consumer acceptance of online banking: An extension of the technology acceptance model. Internet Research, 14, 224-235.
96. Pine, B.J., & Gilmore, J.H. (1999), The Experience Economy: Work is Theatre and Every Business a Stage, Harvard Business School Press, Boston, MA.
97. Qin, H., Peak., A., & Prybutok, V. (2021). A virtual market in your pocket: How does mobile augmented reality (MAR) influence consumer decision making?, Journal of Retailing and Consumer Services, 58, 102337.
98. Rauschnabel, P. A. (2021). Augmented reality is eating the real-world! The substitution of physical products by holograms. International Journal of Information Management, 57, 102279.
99. Reibstein, D. J., Youngblood, S. A., & Fromkin, H. L. (1975). Number of choices and perceived decision freedom as a determinant of satisfaction and consumer behavior. Journal of Applied Psychology, 60(4), 434–437.
100. Rese, A., Baier, D., Geyer-Schulz, A., & Schreiber, S. (2017). How augmented reality apps are accepted by consumers: A comparative analysis using scales and opinions. Technological Forecasting and Social Change, 124, 306-319.
101. Rich, S. U., & Jain, S. C. (1968). Social class and life cycle as predictors of shopping behavior. Journal of Marketing Research, 5(1), 41–49.
102. Roy, S. K., Balaji, M. S., Nguyen, B., & Melewar, T. C. (2017). Constituents and consequences of smart customer experience in retailing. Technological Forecasting & Social Change, 124, 257-270.
103. Scammon, D. L. (1977). Information load and consumers. Journal of Consumer Research, 4(3), 148–155,
104. Senecal, S., Kalczynski, P. J. & Nantel, J. (2005). Consumers' decision-making process and their online shopping behavior: A clickstream analysis. Journal of Business Research, 58(11), 1599-1608.
105. Senyo, P. K., Liu, K., & Effah, J. (2019). Digital business ecosystem: Literature review and a framework for future research. International Journal of Information Management, 47, 52-64.
106. Shaffer, J. D. (1960). The influence of "impulse buying" or in-the-store decisions on consumers' food purchases. Journal of Farm Economics, 42(2), 317-324.
107. Sharma, P., Ueno, A., & Kingshott, R. (2021). Self-service technology in supermarkets – Do frontline staff still matter?, Journal of Retailing and Consumer Services, 59, 102356,
108. Snyder, H. (2019). Literature review as a research methodology: An overview and guidelines. Journal of Business Research, 104, 333-339.
109. Szymanski, D. M., & Hise, R. T. (2000). E-satisfaction: An initial examination. Journal of Retailing, 76(3), 309-322,
110. Woodside, A. G., & Davenport, J. W. (1974). The effect of salesman similarity and expertise on consumer purchasing behavior. Journal of Marketing Research, 11(2), 198–202.
111. Wright, P. (1975). Consumer choice strategies: Simplifying vs. optimizing. Journal of Marketing Research, 12(1), 60–67.
112. Wright, P.L. (1974). Analyzing media effects on advertising responses. Public Opinion Quarterly, 38, 192-205.
113. Van Eck, N., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523-538.
114. Yaoyuneyong, G., Foster, J., & Flynn, L. (2014), Factors impacting the efficacy of augmented reality virtual dressing room technology as a tool for online visual merchandising, Journal of Global Fashion Marketing, 5(4),283-296.
115. Yim, M. Y. C, Chu, S. C., & Sauer, P. L. (2017). Is augmented reality technology an effective tool for E-commerce? An interactivity and vividness perspective. Journal of Interactive Marketing, 39, 89-103.