Araştırma Makalesi
BibTex RIS Kaynak Göster

Z KUŞAĞI TÜKETİCİLERİN ÇEVRİMİÇİ ALIŞVERİŞ DAVRANIŞLARININ ÇEVRİMİÇİ DEĞERLENDİRME PUANI VE ÇEVRİMİÇİ YORUM SAYISI BAĞLAMINDA İNCELENMESİ

Yıl 2024, Cilt: 7 Sayı: 2, 125 - 140, 31.12.2024
https://doi.org/10.46238/jobda.1586205

Öz

Dijital teknolojilerden, sosyal medyadan ve çevrimiçi alışverişten büyük ölçüde etkilenen önemli bir tüketici demografisini temsil eden Z Kuşağı, satın alma kararlarını verirken sosyal etkiye ve akran görüşlerine önem verdiği bilinmektedir. Bu nedenle, bandwagon etkisinin (sürü psikolojisi) ve çevrimiçi derecelendirmelerinin Z Kuşağının çevrimiçi satın alma davranışını nasıl etkilediğini anlamak, tüketici davranışı çalışmalarında önemli bir araştırma alanı haline gelmiştir. Bu araştırmanın amacı da, Z Kuşağı dijital tüketicilerinin, ürünlerin çevrimiçi inceleme sayısı ve çevrimiçi değerlendirme puanı bilgileri bağlamında, bandwagon, satın alma isteği ve satın almaya yönelik tutumu açısından farklılıklarını incelemektir. Bu doğrultuda Z Kuşağı dijital tüketicisi olan 181 kişiye çevrimiçi anketler uygulanmış ve bandwagon, satın alma isteği ve satın almaya yönelik tutumları ölçülmüştür. Elde edilen verilere 2X2 ANCOVA uygulanmıştır. Yapılan analizin sonuçlarına göre çevrimiçi inceleme sayısı ve değerlendirme puanı grupları bağlamında satın alma isteği ve satın almaya yönelik tutumu açısından istatistiksel olarak anlamlı farklılıkların olduğu tespit edilmiştir.

Kaynakça

  • Ahn, H., & Park, E. (2024). The impact of consumers' sustainable electronic-word-of-mouth in purchasing sustainable mobility: An analysis from online review comments of e-commerce, Research in Transportation Business & Management, 52, 101086.
  • Anantharaman, R., Prashar, S., & Vijay, T. S. (2023). Uncovering the role of consumer trust and bandwagon effect influencing purchase intention: an empirical investigation in social commerce platforms. Journal of Strategic Marketing, 31(6), 1199-1219.
  • Akcan, B. (2021). Tüketimi teşvik etmek için kıtlık satmak, In: Reklama “yeni”den bakmak, 215-247, EfeAkademi.
  • Atılgan, K. Ö. ve Koç, O. (2020). İndirim düzeyleri ve sosyal sınıflar açısından tüketici fiyat algısındaki farklılıkların incelenmesi, Mehmet Akif Ersoy Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 7(Özel Sayı), 1075-1103.
  • Baek, H., Ahn, J., & Choi, Y. (2012). Helpfulness of online consumer reviews: Readers’ objectives and review cues, International Journal of Electronic Commerce, 17(2), 99-126.
  • Bickart, B., & Schindler, R. M. (2001). Internet forums as influential sources of consumer information, Journal of Interactive Marketing, 15(3), 31-40.
  • Bindra, S., Sharma, D., Parameswar, N., Dhir, S., & Paul, J. (2022). Bandwagon effect revisited: A systematic review to develop future research agenda, Journal of Business Research, 143, 305-317.
  • Cameron, A.C. (2004). “Kurtosis”, in Lewis-Beck, M., Bryman, A. and Liao, T.F. (Eds.): The Sage Encyclopedia of Social Science Research, p.545, Sage, Thousand Oaks.
  • Campbell, D. T., & Fiske, D. W. (1959). Convergent and discriminant validation by the multitrait-multimethod matrix. Psychological Bulletin, 56(2), 81-105.
  • Cao, X., Liu, Y., Zhu, Z., Hu, J., & Chen, X. (2017). Online selection of a physician by patients: Empirical study from elaboration likelihood perspective. Computers in Human Behavior, 73, 403-412.
  • Chakraborty, T., & Balakrishnan, J. (2017). Exploratory tendencies in consumer behaviour in online buying across gen X, gen Y and baby boomers, International journal of value chain management, 8(2), 135-150.
  • Chang, Y., & Thorson, E. (2004). Television and web advertising synergies, Journal of Advertising, 33(2), 75–84.
  • Chen, Y., & Jinhong, X. (2004). Online consumer review: A new element of marketing communications mix (Working Paper). Gainesville: Department of Marketing, University of Florida.
  • Chen, Y., Lu, Y., Wang, B., & Pan, Z. (2019). How do product recommendations affect impulse buying? An empirical study on WeChat social commerce. Information & Management, 56(2), 236-248.
  • Chetioui, Y., & El Bouzidi, L. (2023). An investigation of the nexus between online impulsive buying and cognitive dissonance among gen Z shoppers: are female shoppers different?, Young Consumers, 24(4), 406-426.
  • Chew, S. S., & Leng, H. K. (2016). The role of social influence in purchasing sports apparel. Athens Journal of Sports, 3(4), 276-284.
  • Cho, E., Kim-Vick, J., & Yu, U. J. (2022). Unveiling motivation for luxury fashion purchase among Gen Z consumers: need for uniqueness versus bandwagon effect. International Journal of Fashion Design, Technology and Education, 15(1), 24-34.
  • Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, Lawrence Erlbaum Associates.
  • De Pelsmacker, P., Dens, N., & Kolomiiets, A. (2018). The impact of text valence, star rating and rated usefulness in online reviews, International Journal of Advertising, 37(3), 340-359.
  • Dodds, W. B., Monroe, K. B., & Grewal, D. (1991). Effects of price, brand, and store information on buyers’ product evaluations, Journal of Marketing Research, 28(3), 307-319.
  • Fornell, C. ve Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
  • Ganguly, B., Dash, S. B., Cyr, D., & 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.
  • Gössling, S., Hall, C. M., & Andersson, A. C. (2018). The manager’s dilemma: a conceptualization of online review manipulation strategies, Current issues in Tourism, 21(5), 484-503.
  • Hlee, S., Lee, H., & Koo, C. (2018). Hospitality and tourism online review research: A systematic analysis and heuristic-systematic model, Sustainability, 10(4), 1141.
  • Hong, S., & Pittman, M. (2020). eWOM anatomy of online product reviews: Interaction effects of review number, valence, and star ratings on perceived credibility. International Journal of Advertising, 39(7), 892-920.
  • Hu, Y. (2022, December). The influence of online web reviews on consumers’ purchase intention. In 2022 2nd International Conference on Economic Development and Business Culture (ICEDBC 2022) (276-282). Atlantis Press.
  • Kastanakis, M. N., & Balabanis, G. (2012). Between the mass and the class: Antecedents of the “bandwagon” luxury consumption behavior, Journal of Business Research, 65(10), 1399-1407.
  • Kim, H. S. (1995). Consumer response toward apparel products in advertisements containing environmental claims. Doktora tezi, Iowa State University.
  • Lazim, N. A. M., Sulaiman, Z., Zakuan, N., Mas’od, A., Chin, T. A., & Awang, S. R. (2020, March). Measuring post-purchase regret and impulse buying in online shopping experience from cognitive dissonance theory perspective. In 2020 6th International Conference on Information Management (ICIM) (7-13). IEEE.
  • Lee, E. J., & Shin, S. Y. (2014). When do consumers buy online product reviews? Effects of review quality, product type, and reviewer’s photo, Computers in Human Behavior, 31, 356-366.
  • Lee, S., & Choeh, J. Y. (2018). The interactive impact of online word-of-mouth and review helpfulness on box office revenue. Management Decision, 56(4), 849-866.
  • Leibenstein, H. (1950). Bandwagon, snob, and Veblen effects in the theory of consumers' demand, The Quarterly Journal of Economics, 64(2), 183-207.
  • Liu, W., Wu, F., & Awan, T. M. (2023). Does product touch affect consumer attitude toward a product? Meta‐analysis of effect sizes, moderators, and mediators. Psychology & Marketing, 40(4), 674-689.
  • Lovett, M. J., Peres, R., & Shachar, R. (2013). On brands and word of mouth. Journal of Marketing Research, 50(4), 427-444.
  • Lu, X., Li, Y., Zhang, Z., & Rai, B. (2014). Consumer learning embedded in electronic word of mouth. Journal of Electronic Commerce Research, 15(4), 300-316.
  • Lusianingrum, F. P. W., Pertiwi, W. N. B., & Zelliana, D. (2023, December). Online treveler reviews: How to build the ıntention of generation Z travelers. In International Conference on Sustainability in Technological, Environmental, Law, Management, Social and Economic Matters (ICOSTELM 2022) (117-127). Atlantis Press.
  • Marangoz, M. (2007). Ağızdan ağıza iletişimin müşterilerin satın alma davranışlarına etkileri: Cep telefonu pazarına yönelik bir araştırma. Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 16(2), 395-412.
  • McKnight, H., & Kacmar, C. (2006, January). Factors of information credibility for an internet advice site. In Proceedings of the 39th Annual Hawaii International Conference on System Sciences (HICSS'06) (Vol. 6, 113b-113b). IEEE.
  • Meydiawati, M., Pebrianti, W., Afifah, N., & Listiana, E. (2024). Pengaruh need for uniqueness dan bandwagon effect terhadap purchase intention melalui value-expressive function of attitude sebagai variabel intervening: studi empiris pada hijab buttonscarves. Reslaj Religion Education Social Laa Roiba Journal, 6(3), 1892-1903. https://doi.org/10.47467/reslaj.v6i3.5816.
  • Moe, W. W. ve Schweidel, D. A. (2012). Online product opinions: Incidence, evaluation, and evolution, Marketing Science, 31(3), 372-386.
  • Nadroo, Z. M., Lim, W. M., & Naqshbandi, M. A. (2024). Domino effect of parasocial interaction: Of vicarious expression, electronic word-of-mouth, and bandwagon effect in online shopping. Journal of Retailing and Consumer Services, 78, 103746.
  • Ngo, T. T. A., Nguyen, H. L. T., Nguyen, H. P., Mai, H. T. A., Mai, T. H. T., & Hoang, P. L. (2024). A comprehensive study on factors influencing online impulse buying behavior: Evidence from Shopee video platform. Heliyon, 10(15). e35743.
  • Nunnally, J. C. (1978). Introduction to psychological measurement. New York: McGraw-Hill.
  • Pallant, J. (2005). SPSS survival manual: A step by step guide to data analysis using SPSS for Windows (Version 12). Allen and Unwin, Crow’s Nest NSW.
  • Park, D. H., & Lee, J. (2008). eWOM overload and its effect on consumer behavioral intention depending on consumer involvement, Electronic Commerce Research and Applications, 7(4), 386-398.
  • Park, D. H., Lee, J., & Han, I. (2007). The effect of on-line consumer reviews on consumer purchasing intention: The moderating role of involvement. International Journal Of Electronic Commerce, 11(4), 125-148.
  • Perez-Aranda, J., Tolkach, D., & Panchal, J. H. (2024). Reputation and eWOM in accommodation decision-making: insights from generation Z users. Tourism Review. DOI 10.1108/TR-03-2024-0185.
  • Priporas, C. V., Stylos, N., & Fotiadis, A. K. (2017). Generation Z consumers' expectations of interactions in smart retailing: A future agenda, Computers in Human Behavior, 77, 374-381.
  • Priporas, C. V. (2020). Smart Consumers and Decision-making Process in the Smart Retailing Context through Generation Z Eyes, Pantano, E. (Ed.) Retail Futures, Emerald Publishing Limited, Leeds, 147-162. https://doi.org/10.1108/978-1-83867-663-620201017.
  • Rikkers, L. F. (2002). The bandwagon effect, Journal of Gastro Intestinal Surgery, 6(6), 787-794. Rook, L. (2006). An economic psychological approach to herd behavior, Journal of Economic Issues, 40(1), 75-95.
  • Ros, M. (2016). The effects of ratio of reviews and product type, Master’s thesis, University of Twente.
  • Schermelleh-Engel, K., Moosbrugger, H., & Müller, H. (2003). Evaluating the fit of structural equation models: Tests of significance and descriptive goodness-of-fit measures. Methods of psychological research online, 8(2), 23-74.
  • Shao, Z., Zhang, L., Pan, Z., & Benitez, J. (2023). Uncovering the dual influence processes for click-through intention in the mobile social platform: An elaboration likelihood model perspective. Information & Management, 60(5), 103799.
  • Shi, D., Maydeu-Olivares, A., & Rosseel, Y. (2020). Assessing fit in ordinal factor analysis models: SRMR vs. RMSEA, Structural Equation Modeling: A Multidisciplinary Journal, 27(1), 1-15.
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  • Xu, Q. (2013). Social recommendation, source credibility, and recency: Effects of news cues in a social bookmarking website, Journalism & Mass Communication Quarterly, 90(4), 757-775.
  • Yang, J., Sarathy, R., & Lee, J. (2016). The effect of product review balance and volume on online Shoppers’ risk perception and purchase intention, Decision Support Systems, 89, 66-76.
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EXAMINING THE ONLINE SHOPPING BEHAVIORS OF GENERATION Z CONSUMERS IN THE CONTEXT OF ONLINE RATINGS AND NUMBER OF REVIEWS

Yıl 2024, Cilt: 7 Sayı: 2, 125 - 140, 31.12.2024
https://doi.org/10.46238/jobda.1586205

Öz

Representing an important consumer demographic that is greatly affected by digital technologies, social media, and online shopping, Generation Z is known to value social influence and peer opinions when making purchasing decisions. Therefore, understanding how the bandwagon effect and online ratings affect the online purchasing behavior of Generation Z has become an important area of research in consumer behavior studies. The aim of this research is to examine the differences of Generation Z digital consumers in terms of bandwagon effect, willingness to buy, and attitude toward purchasing in the context of the number of online reviews and online rating score information of products. In this context, online surveys were applied to 181 Generation Z digital consumers and their bandwagon effect, willingness to buy, and attitude toward purchasing were measured. 2X2 ANCOVA was applied to the obtained data. According to the results, it was determined that there were statistically significant differences in terms of willingness to buy and attitude toward purchasing in the context of the number of online reviews and evaluation score groups.

Kaynakça

  • Ahn, H., & Park, E. (2024). The impact of consumers' sustainable electronic-word-of-mouth in purchasing sustainable mobility: An analysis from online review comments of e-commerce, Research in Transportation Business & Management, 52, 101086.
  • Anantharaman, R., Prashar, S., & Vijay, T. S. (2023). Uncovering the role of consumer trust and bandwagon effect influencing purchase intention: an empirical investigation in social commerce platforms. Journal of Strategic Marketing, 31(6), 1199-1219.
  • Akcan, B. (2021). Tüketimi teşvik etmek için kıtlık satmak, In: Reklama “yeni”den bakmak, 215-247, EfeAkademi.
  • Atılgan, K. Ö. ve Koç, O. (2020). İndirim düzeyleri ve sosyal sınıflar açısından tüketici fiyat algısındaki farklılıkların incelenmesi, Mehmet Akif Ersoy Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 7(Özel Sayı), 1075-1103.
  • Baek, H., Ahn, J., & Choi, Y. (2012). Helpfulness of online consumer reviews: Readers’ objectives and review cues, International Journal of Electronic Commerce, 17(2), 99-126.
  • Bickart, B., & Schindler, R. M. (2001). Internet forums as influential sources of consumer information, Journal of Interactive Marketing, 15(3), 31-40.
  • Bindra, S., Sharma, D., Parameswar, N., Dhir, S., & Paul, J. (2022). Bandwagon effect revisited: A systematic review to develop future research agenda, Journal of Business Research, 143, 305-317.
  • Cameron, A.C. (2004). “Kurtosis”, in Lewis-Beck, M., Bryman, A. and Liao, T.F. (Eds.): The Sage Encyclopedia of Social Science Research, p.545, Sage, Thousand Oaks.
  • Campbell, D. T., & Fiske, D. W. (1959). Convergent and discriminant validation by the multitrait-multimethod matrix. Psychological Bulletin, 56(2), 81-105.
  • Cao, X., Liu, Y., Zhu, Z., Hu, J., & Chen, X. (2017). Online selection of a physician by patients: Empirical study from elaboration likelihood perspective. Computers in Human Behavior, 73, 403-412.
  • Chakraborty, T., & Balakrishnan, J. (2017). Exploratory tendencies in consumer behaviour in online buying across gen X, gen Y and baby boomers, International journal of value chain management, 8(2), 135-150.
  • Chang, Y., & Thorson, E. (2004). Television and web advertising synergies, Journal of Advertising, 33(2), 75–84.
  • Chen, Y., & Jinhong, X. (2004). Online consumer review: A new element of marketing communications mix (Working Paper). Gainesville: Department of Marketing, University of Florida.
  • Chen, Y., Lu, Y., Wang, B., & Pan, Z. (2019). How do product recommendations affect impulse buying? An empirical study on WeChat social commerce. Information & Management, 56(2), 236-248.
  • Chetioui, Y., & El Bouzidi, L. (2023). An investigation of the nexus between online impulsive buying and cognitive dissonance among gen Z shoppers: are female shoppers different?, Young Consumers, 24(4), 406-426.
  • Chew, S. S., & Leng, H. K. (2016). The role of social influence in purchasing sports apparel. Athens Journal of Sports, 3(4), 276-284.
  • Cho, E., Kim-Vick, J., & Yu, U. J. (2022). Unveiling motivation for luxury fashion purchase among Gen Z consumers: need for uniqueness versus bandwagon effect. International Journal of Fashion Design, Technology and Education, 15(1), 24-34.
  • Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, Lawrence Erlbaum Associates.
  • De Pelsmacker, P., Dens, N., & Kolomiiets, A. (2018). The impact of text valence, star rating and rated usefulness in online reviews, International Journal of Advertising, 37(3), 340-359.
  • Dodds, W. B., Monroe, K. B., & Grewal, D. (1991). Effects of price, brand, and store information on buyers’ product evaluations, Journal of Marketing Research, 28(3), 307-319.
  • Fornell, C. ve Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
  • Ganguly, B., Dash, S. B., Cyr, D., & 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.
  • Gössling, S., Hall, C. M., & Andersson, A. C. (2018). The manager’s dilemma: a conceptualization of online review manipulation strategies, Current issues in Tourism, 21(5), 484-503.
  • Hlee, S., Lee, H., & Koo, C. (2018). Hospitality and tourism online review research: A systematic analysis and heuristic-systematic model, Sustainability, 10(4), 1141.
  • Hong, S., & Pittman, M. (2020). eWOM anatomy of online product reviews: Interaction effects of review number, valence, and star ratings on perceived credibility. International Journal of Advertising, 39(7), 892-920.
  • Hu, Y. (2022, December). The influence of online web reviews on consumers’ purchase intention. In 2022 2nd International Conference on Economic Development and Business Culture (ICEDBC 2022) (276-282). Atlantis Press.
  • Kastanakis, M. N., & Balabanis, G. (2012). Between the mass and the class: Antecedents of the “bandwagon” luxury consumption behavior, Journal of Business Research, 65(10), 1399-1407.
  • Kim, H. S. (1995). Consumer response toward apparel products in advertisements containing environmental claims. Doktora tezi, Iowa State University.
  • Lazim, N. A. M., Sulaiman, Z., Zakuan, N., Mas’od, A., Chin, T. A., & Awang, S. R. (2020, March). Measuring post-purchase regret and impulse buying in online shopping experience from cognitive dissonance theory perspective. In 2020 6th International Conference on Information Management (ICIM) (7-13). IEEE.
  • Lee, E. J., & Shin, S. Y. (2014). When do consumers buy online product reviews? Effects of review quality, product type, and reviewer’s photo, Computers in Human Behavior, 31, 356-366.
  • Lee, S., & Choeh, J. Y. (2018). The interactive impact of online word-of-mouth and review helpfulness on box office revenue. Management Decision, 56(4), 849-866.
  • Leibenstein, H. (1950). Bandwagon, snob, and Veblen effects in the theory of consumers' demand, The Quarterly Journal of Economics, 64(2), 183-207.
  • Liu, W., Wu, F., & Awan, T. M. (2023). Does product touch affect consumer attitude toward a product? Meta‐analysis of effect sizes, moderators, and mediators. Psychology & Marketing, 40(4), 674-689.
  • Lovett, M. J., Peres, R., & Shachar, R. (2013). On brands and word of mouth. Journal of Marketing Research, 50(4), 427-444.
  • Lu, X., Li, Y., Zhang, Z., & Rai, B. (2014). Consumer learning embedded in electronic word of mouth. Journal of Electronic Commerce Research, 15(4), 300-316.
  • Lusianingrum, F. P. W., Pertiwi, W. N. B., & Zelliana, D. (2023, December). Online treveler reviews: How to build the ıntention of generation Z travelers. In International Conference on Sustainability in Technological, Environmental, Law, Management, Social and Economic Matters (ICOSTELM 2022) (117-127). Atlantis Press.
  • Marangoz, M. (2007). Ağızdan ağıza iletişimin müşterilerin satın alma davranışlarına etkileri: Cep telefonu pazarına yönelik bir araştırma. Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 16(2), 395-412.
  • McKnight, H., & Kacmar, C. (2006, January). Factors of information credibility for an internet advice site. In Proceedings of the 39th Annual Hawaii International Conference on System Sciences (HICSS'06) (Vol. 6, 113b-113b). IEEE.
  • Meydiawati, M., Pebrianti, W., Afifah, N., & Listiana, E. (2024). Pengaruh need for uniqueness dan bandwagon effect terhadap purchase intention melalui value-expressive function of attitude sebagai variabel intervening: studi empiris pada hijab buttonscarves. Reslaj Religion Education Social Laa Roiba Journal, 6(3), 1892-1903. https://doi.org/10.47467/reslaj.v6i3.5816.
  • Moe, W. W. ve Schweidel, D. A. (2012). Online product opinions: Incidence, evaluation, and evolution, Marketing Science, 31(3), 372-386.
  • Nadroo, Z. M., Lim, W. M., & Naqshbandi, M. A. (2024). Domino effect of parasocial interaction: Of vicarious expression, electronic word-of-mouth, and bandwagon effect in online shopping. Journal of Retailing and Consumer Services, 78, 103746.
  • Ngo, T. T. A., Nguyen, H. L. T., Nguyen, H. P., Mai, H. T. A., Mai, T. H. T., & Hoang, P. L. (2024). A comprehensive study on factors influencing online impulse buying behavior: Evidence from Shopee video platform. Heliyon, 10(15). e35743.
  • Nunnally, J. C. (1978). Introduction to psychological measurement. New York: McGraw-Hill.
  • Pallant, J. (2005). SPSS survival manual: A step by step guide to data analysis using SPSS for Windows (Version 12). Allen and Unwin, Crow’s Nest NSW.
  • Park, D. H., & Lee, J. (2008). eWOM overload and its effect on consumer behavioral intention depending on consumer involvement, Electronic Commerce Research and Applications, 7(4), 386-398.
  • Park, D. H., Lee, J., & Han, I. (2007). The effect of on-line consumer reviews on consumer purchasing intention: The moderating role of involvement. International Journal Of Electronic Commerce, 11(4), 125-148.
  • Perez-Aranda, J., Tolkach, D., & Panchal, J. H. (2024). Reputation and eWOM in accommodation decision-making: insights from generation Z users. Tourism Review. DOI 10.1108/TR-03-2024-0185.
  • Priporas, C. V., Stylos, N., & Fotiadis, A. K. (2017). Generation Z consumers' expectations of interactions in smart retailing: A future agenda, Computers in Human Behavior, 77, 374-381.
  • Priporas, C. V. (2020). Smart Consumers and Decision-making Process in the Smart Retailing Context through Generation Z Eyes, Pantano, E. (Ed.) Retail Futures, Emerald Publishing Limited, Leeds, 147-162. https://doi.org/10.1108/978-1-83867-663-620201017.
  • Rikkers, L. F. (2002). The bandwagon effect, Journal of Gastro Intestinal Surgery, 6(6), 787-794. Rook, L. (2006). An economic psychological approach to herd behavior, Journal of Economic Issues, 40(1), 75-95.
  • Ros, M. (2016). The effects of ratio of reviews and product type, Master’s thesis, University of Twente.
  • Schermelleh-Engel, K., Moosbrugger, H., & Müller, H. (2003). Evaluating the fit of structural equation models: Tests of significance and descriptive goodness-of-fit measures. Methods of psychological research online, 8(2), 23-74.
  • Shao, Z., Zhang, L., Pan, Z., & Benitez, J. (2023). Uncovering the dual influence processes for click-through intention in the mobile social platform: An elaboration likelihood model perspective. Information & Management, 60(5), 103799.
  • Shi, D., Maydeu-Olivares, A., & Rosseel, Y. (2020). Assessing fit in ordinal factor analysis models: SRMR vs. RMSEA, Structural Equation Modeling: A Multidisciplinary Journal, 27(1), 1-15.
  • Shin, D., & Darpy, D. (2020). Rating, review and reputation: how to unlock the hidden value of luxury consumers from digital commerce?. Journal of Business & Industrial Marketing, 35(10), 1553-1561.
  • Singh, P. (2024). What drives or decelerates generation z? An empirical study navigating consumer buying ıntentions in online shopping. SAGE Open, 14(3), 21582440241263173.
  • Smith, K. T. (2019). Mobile advertising to Digital Natives: preferences on content, style, personalization, and functionality, Journal of Strategic Marketing, 27(1), 67-80.
  • Sparks, B. A., Perkins, H. E., & Buckley, R. (2013). Online travel reviews as persuasive communication: The effects of content type, source, and certification logos on consumer behavior, Tourism Management, 39, 1-9.
  • Sundar, S. S. (2008). The MAIN Model: A Heuristic Approach to Understanding Technology Effects on Credibility (73-100). Cambridge, MA: MacArthur Foundation Digital Media and Learning Initiative.
  • Sundar, S. S., & Nass, C. (2001). Conceptualizing sources in online news, Journal of Communication, 51(1), 52-72.
  • Sundar, S. S., Oeldorf-Hirsch, A., & Xu, Q. (2008). The bandwagon effect of collaborative filtering technology. In CHI08 extended abstracts on Human factors in computing systems (3453-3458).
  • Sung, E., Chung, W. Y., & Lee, D. (2023). Factors that affect consumer trust in product quality: a focus on online reviews and shopping platforms. Humanities and Social Sciences Communications, 10(1), 1-10.
  • Wu, T. Y., & Lin, C. A. (2017). Predicting the effects of eWOM and online brand messaging: Source trust, bandwagon effect and innovation adoption factors, Telematics and Informatics, 34(2), 470-480.
  • Xu, Q. (2013). Social recommendation, source credibility, and recency: Effects of news cues in a social bookmarking website, Journalism & Mass Communication Quarterly, 90(4), 757-775.
  • Yang, J., Sarathy, R., & Lee, J. (2016). The effect of product review balance and volume on online Shoppers’ risk perception and purchase intention, Decision Support Systems, 89, 66-76.
  • Zhang, K. Z., Zhao, S. J., Cheung, C. M., & Lee, M. K. (2014). Examining the influence of online reviews on consumers' decision-making: A heuristic–systematic model. Decision Support Systems, 67, 78-89.
Toplam 66 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Dijital Pazarlama
Bölüm Özgün Bilimsel Makaleler
Yazarlar

Kalender Özcan Atılgan 0000-0003-1482-4505

Yayımlanma Tarihi 31 Aralık 2024
Gönderilme Tarihi 15 Kasım 2024
Kabul Tarihi 12 Aralık 2024
Yayımlandığı Sayı Yıl 2024 Cilt: 7 Sayı: 2

Kaynak Göster

APA Atılgan, K. Ö. (2024). Z KUŞAĞI TÜKETİCİLERİN ÇEVRİMİÇİ ALIŞVERİŞ DAVRANIŞLARININ ÇEVRİMİÇİ DEĞERLENDİRME PUANI VE ÇEVRİMİÇİ YORUM SAYISI BAĞLAMINDA İNCELENMESİ. Journal of Business in The Digital Age, 7(2), 125-140. https://doi.org/10.46238/jobda.1586205

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