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COVİD-19 TÜRKİYE'DE TÜKETİCİ DAVRANIŞI EĞİLİMLERİNİ NASIL DEĞİŞTİRDİ?

Year 2024, Volume: 26 Issue: 2, 915 - 945, 15.06.2024
https://doi.org/10.16953/deusosbil.1375618

Abstract

COVİD-19, günlük yaşamın birçok yönünü etkilemiş özellikle de alışveriş yöntemlerini değiştirmiştir. Bu çalışma, tüketici davranışı eğilimlerinin nasıl etkilediğini norm duyarlılığı, risk algısı ve dijital reklamları odağına alarak incelemektedir. Bu araştırmanın amacı, COVİD-19 ile tüketici davranışı eğilimlerindeki değişiklikler arasındaki ilişkide norm duyarlılığı, risk algısı ve dijital reklamların aracı rolünü anlamaktır. Bu bağlamda nitel veriler, 19 ile 52 yaş arasındaki 41 katılımcıdan çevrimiçi olarak toplanmış ve MAXQDA programı kullanılarak analiz edilmiştir. Bu çalışmanın özgün yanı konuyu nitel olarak ele alması ve nitel bir çalışmaya göre yüksek bir örneklem büyüklüğüne sahip olmasıdır. Bulgular, COVİD-19 döneminde çevrimiçi alışverişe karşı artan duyarlılık olduğunu, geleneksel yüz yüze alışverişi virüs bulaşma riski nedeniyle genellikle riskli olarak algılandığını, dijital kanallara artan güveni, dijital reklamların satın almaya olan tartışmasız etkilerini ve alışveriş öncesi araştırma yapmanın önemini göstermektedir. Ayrıca, bulgular, alışveriş yöntemlerinin COVİD-19’un erken dönemlerinde bile geleneksel yüz yüze alışverişten çevrimiçi alışverişe kaydığını ortaya koymuştur. Bu bulgulara dayanarak, işletmelerin çevrimiçi alışveriş deneyimlerini iyileştirerek web sitesi kullanılabilirliğini ve güvenlik önlemlerini artırmasının faydalı olabileceği düşünülmektedir. Ayrıca, tüketicilerin endişelerini hafifletmek için fiziksel mağazalarda güvenlik protokolleri uygulayabilir ve sürdürebilirler. Dijital reklam stratejilerini kullanmak ve tüketici araştırmasına yatırım yapmak, işletmelerin değişen tüketici tercihlerine ve davranışlarına uyum sağlamasına yardımcı olabilir.

References

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  • Andrews, M., Goehring, J., Hui, S., Pancras, J., & Thornswood, L. (2016). Mobile promotions: A framework and research priorities. Journal of Interactive Marketing. 34, 15–24.
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  • Bicchieri, C. (2016). Norms in the wild: How to diagnose, measure, and change social norms. Oxford University Press.
  • Bicchieri, C., & Mercier, H. (2014). Norms and beliefs: How change occurs. In The complexity of social norms (pp. 37-54). Springer, Cham.
  • Bilgilier, H. A. (2019). Y Kuşağının İnternetten Alışverişe Yönelik Tutumları: Nicel Bir Araştırma. Erciyes İletişim Dergisi, 6 (1), 487-512.
  • Caine, S. (2020, May 1). As coronavirus pandemic pushes more grocery shoppers online, stores struggle to keep up with demand. Bain. https://www.bain.com/about/media-center/bain-in-the-news/2020/covid-19-pushes-more-grocery-shoppers-online-stores-struggle-to-keep-up-with-demand/
  • Celik, B. & Dane, S. (2020). The effects of COVID - 19 Pandemic Outbreak on Food Consumption Preferences and Their Causes. Journal of Research in Medical and Dental Science, 8 (3), 169-173.
  • Clemes, M. D., Gan, C., & Zhang, J. (2014). An empirical analysis of online shopping adoption in Beijing, China. Journal of Retailing and Consumer Services, 21 (3), 364-375.
  • Cox, D. F., & Rich, S. U. (1964). Perceived risk and consumer decision making: The case of telephone shopping. Journal of Marketing Research, 1 (4), 32-39.
  • Danışmaz, A. T. (2020). Covid-19 Salgınının Tüketicilerin Online Alışveriş Tercihine Etkisi. Sosyal Bilimler Araştırma Dergisi, 9 (2), 83-90.
  • Davranova, M. D. (2019). Internet Advertising: Perceptions of the Users. International Journal of Marketing & Business Communication, 8 (2&3), 25-36.
  • Dwivedi, N., & Kumar, R. (2021). Analysis on the Impact of Social Media Advertisement on the Consumer Buying Behaviour of Women for Cosmetic Goods in NCR Region. Turkish Online Journal of Qualitative Inquiry, 12 (6). 5476-5485.
  • Duong, H., Nguyen, L., & Vu, H. (2020). With whom do consumers interact?: Effects of online comments and perceived similarity on source credibility, content credibility, and personal risk perception. Journal of Social Marketing, 10 (1), 18–37.
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  • Fulgoni, G. M., & Lipsman, A. (2017). The downside of digital word of mouth and the pursuit of media quality: How social sharing is disrupting digital advertising models and metrics. Journal of Advertising Research, 57 (2), 127-131.
  • Giamanco, B., & Gregoire, K. (2012). Tweet me, friend me, make me buy. Harvard Business Review, 90 (7), 89-93.
  • Gibbs, J. P. (1965). Norms: The problem of definition and classification. American Journal of Sociology, 70 (5), 586-594.
  • Guru, S., Nenavani, J., Patel, V., & Bhatt, N. (2020). Ranking of perceived risks in online shopping. DECISION: Official Journal of Indian Institute of Management Calcutta, 47 (2), 137. https://ezproxy.etu.edu.tr:2262/10.1007/s40622-020-00241-x
  • Hesham, F., Riadh, H., & Sihem, N. K. (2021). What have we learned about the effects of the COVID-19 pandemic on consumer behavior?. Sustainability, 13 (8), 1-23. https://doi.org/10.3390/su13084304
  • Hille, P., Walsh, G., & Cleveland, M. (2015). Consumer Fear of Online Identity Theft: Scale Development and Validation. Journal of Interactive Marketing, 30, 1–19. https://ezproxy.etu.edu.tr:2262/10.1016/j.intmar.2014.10.001
  • Holmes, E. A., O’Connor, R. C., Perry, V. H., Tracey, I., Wessely, S., Arseneault, L., Ballard, C., Christensen, H., Silver, R. C., Everall, I., Ford, T., John, A., Kabir, T., King, K., Madan, I., Michie, S., Przybylski, A. K., Shafran, R., Sweeney, A., … Bullmore, E. (2020). Multidisciplinary research priorities for the COVID-19 pandemic: a call for action for mental health science. Lancet Psychiatry, 7 (6), 547–560.
  • Homburg, C., Wieseke, J., & Kuehnl, C. (2010). Social influence on salespeople’s adoption of sales technology: a multilevel analysis. Journal of the Academy of Marketing Science, 38, 159-168. https://doi.org/10.1007/s11747-009-0157-x
  • Hong, L. M., Che Nawi, N., & Zulkifli, W. F. W. (2019). Online store image towards perceived risks in online shopping. Journal of Entrepreneurship and Business, 7 (1), 1-9. https://doi.org/10.17687/JEB.0701.01
  • IBIS World 2016. IBIS World’s industry research reports. https://www.ibisworld.com/industrytrends/ (accessed May 29, 2019).
  • Ivanovic, D., & Antonijevic, M. (2020). The Role of Online Shopping in the Republic of Serbia During COVID-19. Economic Analysis, 53 (1), 28-41.
  • Jacoby, J. (1976). Consumer psychology: An octennium. Annual review of psychology, 27 (1), 331-358.
  • Jung, H., Park, M., Hong, K., & Hyun, E. (2016). The impact of an epidemic outbreak on consumer expenditures: An empirical assessment for MERS Korea. Sustainability, 8 (5), 454.
  • Kaplan, L. B., Szybillo, G. J., & Jacoby, J. (1974). Components of perceived risk in product purchase: A cross-validation. Journal of Applied Psychology, 59 (3), 287-291. https://doi.org/10.1037/h0036657
  • Keeney, R. L. (1999). The Value of Internet Commerce to the Customer. Management Science, 45 (4), 533-542.
  • Khattar, A., Jain, P. R., & Quadri, S. M. K. (2020). Effects of the Disastrous Pandemic COVID 19 on Learning Styles, Activities and Mental Health of Young Indian Students-A Machine Learning Approach. In 2020 4th International Conference on Intelligent Computing and Control Systems (ICICCS) (pp. 1190-1195). IEEE.
  • Kim, H., Lee, E. J., & Hur, W. M. (2012). The normative social influence on eco-friendly consumer behavior: The moderating effect of environmental marketing claims. Clothing and Textiles Research Journal, 30 (1), 4-18. https://doi.org/10.1177/0887302X12440875
  • Kostring, J. C. (2012). Eight trends shaping digital marketing in the auto industry. McKinsey & Company.
  • Lee, H., & Cho, C. H. (2019). An empirical investigation on the antecedents of consumers’ cognitions of and attitudes towards digital signage advertising. International Journal of Advertising 38 (1), 97–115.
  • Lee, H. & Cho, C. H. (2020). Digital advertising: present and future prospects. International Journal of Advertising, 39 (3), 332-341.
  • Leigh, A. (2020). How COVID-19 Will Change Consumer Behavior Long-Term. Accessed April 27, 2020; Retrieved from www.chaindrugreview.com/how-covid-19-will-change-consumer-behavior-long-term/
  • Li, J., Hallsworth, A. G., & Coca-Stefaniak, J. A. (2020). The changing grocery shopping behavior of Chinese consumers at the outset of the COVID-19 Outbreak. Age, 6 (53), 574-583.
  • Li, K. J., & Li, X. (2020). COVID-19 Pandemic: Social Distancing, Public Policy, and Market Response. Available at http://dx.doi.org/10.2139/ssrn.3593813
  • Lobschat, L., Osinga, E. C., & Reinartz, W. J. (2017). What happens online stays online? Segment-specific online and offline effects of banner advertisements. Journal of Marketing Research, 54 (6), 901-913.
  • Ludwig, S., De Ruyter, K., Friedman, M., Brüggen, E. C., Wetzels, M., & Pfann, G. (2013). More than words: The influence of affective content and linguistic style matches in online reviews on conversion rates. Journal of Marketing, 77 (1), 87-103. https://doi.org/10.1509%2Fjm.11.0560
  • MAXQDA Standart [Computer Software]. (2020). https://www.maxqda.com/
  • Melnyk, V., Carrillat, F. A., & Melnyk, V. (2022). The influence of social norms on consumer behavior: A meta-analysis. Journal of Marketing, 86 (3), 98-120. https://doi.org/10.1177/00222429211029199
  • Mwencha, P. M., & Muathe, S. M. (2019). A principal component analysis of customers’ perceived risks for online retailing services: Evidence from Kenya. Journal of Customer Behaviour, 18 (3), 167–190.
  • Naiyi, Y. E. (2004). Dimensions of consumer’s perceived risk in online shopping. Journal of Electronic Science and Technology of China, 2 (3), 177-182.
  • Netcomm Suisse Observatory & United Nations Conference on Trade and Development (2020). COVID-19 and E-commerce: Findings from a survey of online consumers in 9 countries. https://unctad.org/system/files/official-document/dtlstictinf2020d1_en.pdf
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  • Pliner, P., & Mann, N. (2004). Influence of social norms and palatability on amount consumed and food choice. Appetite, 42 (2), 227-237. https://doi.org/10.1016/j.appet.2003.12.001
  • Shaikh, A. (2020). Effective factors in changing the buying behavior of consumer due to Covid-19. Studies in Indian Place Names, 40 (68), 408-414.
  • Spencer, T. (2016). Risk Perception: Theories and Approaches. Nova Science Publishers, Inc.
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  • Stone R. N., & Grønhaug K. (1993). Perceived Risk; Further Considerations for the Marketing Discipline. European Journal of Marketing, 27 (3), 39–50.
  • Swinyard, W. R., & Smith, S. M. (2003). Why people (don't) shop online: A lifestyle study of the internet consumer. Psychology & marketing, 20 (7), 567-597.
  • Tan, S. J. (1999). Strategies for reducing consumers’ risk aversion in internet shopping. Journal of Consumer Marketing, 16 (2), 163-180.
  • Tetteh, V. A. (2019). Consumer Behavior. Salem Press Encyclopedia.
  • Turkish Statistical Institute (2019), “Information Society Statistics, Households with access to the Internet”, Accessed July 29, 2019; available at http://www.tuik.gov.tr/UstMenu.do?metod=temelist.
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HOW COVID-19 CHANGED CONSUMER BEHAVIOR TRENDS IN TÜRKİYE?

Year 2024, Volume: 26 Issue: 2, 915 - 945, 15.06.2024
https://doi.org/10.16953/deusosbil.1375618

Abstract

COVID-19 has altered many aspects of daily life, notably impacting shopping methods. This study examines how these changes affect consumer behavior, focusing on norm sensitivity, risk perception, and digital advertising. The purpose of this research is to understand the role of norm sensitivity, risk perception, and digital advertising as mediators in the relationship between COVID-19 and changes in consumer behavior. Qualitative data is collected from online meetings with 41 participants aged between 19 and 52 and it is analyzed by using MAXQDA. The unique aspect of this study is its qualitative approach and having a relatively large sample size compared to typical qualitative studies. The findings indicate higher sensitivity towards online shopping during COVID-19, perceiving traditional face-to-face shopping as risky mostly due to virus transmission, increased trust in digital channels, the undeniable effects of digital advertisements on purchasing, and the importance of making research before shopping. Furthermore, the findings revealed that shopping methods shifted from traditional face-to-face to online shopping during COVID-19 even in the early times of the pandemic. Based on these findings, businesses should prioritize enhancing their online shopping experiences by improving website usability and security measures. They may also implement safety protocols in physical stores to alleviate consumer concerns. Leveraging targeted digital advertising strategies and investing in consumer research can help businesses adapt to evolving consumer preferences and behaviors.

References

  • Alaimo, L. S., Fiore, M., & Galati, A. (2020). How the COVID-19 pandemic is changing online food shopping human behaviour in Italy. Sustainability, 12 (22), 1-18. https://doi.org/10.3390/su12229594
  • Andrews, M., Goehring, J., Hui, S., Pancras, J., & Thornswood, L. (2016). Mobile promotions: A framework and research priorities. Journal of Interactive Marketing. 34, 15–24.
  • Bhatnagar, A., Misra, S., & Rao, H. R. (2000). On Risk, Convenience, and Internet Shopping Behavior. Communications of the ACM, 43 (11), 98–105.
  • Bicchieri, C. (2006). The grammar of society: The nature and dynamics of social norms. Cambridge University Press.
  • Bicchieri, C. (2016). Norms in the wild: How to diagnose, measure, and change social norms. Oxford University Press.
  • Bicchieri, C., & Mercier, H. (2014). Norms and beliefs: How change occurs. In The complexity of social norms (pp. 37-54). Springer, Cham.
  • Bilgilier, H. A. (2019). Y Kuşağının İnternetten Alışverişe Yönelik Tutumları: Nicel Bir Araştırma. Erciyes İletişim Dergisi, 6 (1), 487-512.
  • Caine, S. (2020, May 1). As coronavirus pandemic pushes more grocery shoppers online, stores struggle to keep up with demand. Bain. https://www.bain.com/about/media-center/bain-in-the-news/2020/covid-19-pushes-more-grocery-shoppers-online-stores-struggle-to-keep-up-with-demand/
  • Celik, B. & Dane, S. (2020). The effects of COVID - 19 Pandemic Outbreak on Food Consumption Preferences and Their Causes. Journal of Research in Medical and Dental Science, 8 (3), 169-173.
  • Clemes, M. D., Gan, C., & Zhang, J. (2014). An empirical analysis of online shopping adoption in Beijing, China. Journal of Retailing and Consumer Services, 21 (3), 364-375.
  • Cox, D. F., & Rich, S. U. (1964). Perceived risk and consumer decision making: The case of telephone shopping. Journal of Marketing Research, 1 (4), 32-39.
  • Danışmaz, A. T. (2020). Covid-19 Salgınının Tüketicilerin Online Alışveriş Tercihine Etkisi. Sosyal Bilimler Araştırma Dergisi, 9 (2), 83-90.
  • Davranova, M. D. (2019). Internet Advertising: Perceptions of the Users. International Journal of Marketing & Business Communication, 8 (2&3), 25-36.
  • Dwivedi, N., & Kumar, R. (2021). Analysis on the Impact of Social Media Advertisement on the Consumer Buying Behaviour of Women for Cosmetic Goods in NCR Region. Turkish Online Journal of Qualitative Inquiry, 12 (6). 5476-5485.
  • Duong, H., Nguyen, L., & Vu, H. (2020). With whom do consumers interact?: Effects of online comments and perceived similarity on source credibility, content credibility, and personal risk perception. Journal of Social Marketing, 10 (1), 18–37.
  • Forster, P. W., & Tang, Y. (2005, January). The role of online shopping and fulfillment in the Hong Kong SARS crisis. In Proceedings of the 38th Annual Hawaii International Conference on System Sciences (pp. 271a-271a). IEEE.
  • Fulgoni, G. M., & Lipsman, A. (2017). The downside of digital word of mouth and the pursuit of media quality: How social sharing is disrupting digital advertising models and metrics. Journal of Advertising Research, 57 (2), 127-131.
  • Giamanco, B., & Gregoire, K. (2012). Tweet me, friend me, make me buy. Harvard Business Review, 90 (7), 89-93.
  • Gibbs, J. P. (1965). Norms: The problem of definition and classification. American Journal of Sociology, 70 (5), 586-594.
  • Guru, S., Nenavani, J., Patel, V., & Bhatt, N. (2020). Ranking of perceived risks in online shopping. DECISION: Official Journal of Indian Institute of Management Calcutta, 47 (2), 137. https://ezproxy.etu.edu.tr:2262/10.1007/s40622-020-00241-x
  • Hesham, F., Riadh, H., & Sihem, N. K. (2021). What have we learned about the effects of the COVID-19 pandemic on consumer behavior?. Sustainability, 13 (8), 1-23. https://doi.org/10.3390/su13084304
  • Hille, P., Walsh, G., & Cleveland, M. (2015). Consumer Fear of Online Identity Theft: Scale Development and Validation. Journal of Interactive Marketing, 30, 1–19. https://ezproxy.etu.edu.tr:2262/10.1016/j.intmar.2014.10.001
  • Holmes, E. A., O’Connor, R. C., Perry, V. H., Tracey, I., Wessely, S., Arseneault, L., Ballard, C., Christensen, H., Silver, R. C., Everall, I., Ford, T., John, A., Kabir, T., King, K., Madan, I., Michie, S., Przybylski, A. K., Shafran, R., Sweeney, A., … Bullmore, E. (2020). Multidisciplinary research priorities for the COVID-19 pandemic: a call for action for mental health science. Lancet Psychiatry, 7 (6), 547–560.
  • Homburg, C., Wieseke, J., & Kuehnl, C. (2010). Social influence on salespeople’s adoption of sales technology: a multilevel analysis. Journal of the Academy of Marketing Science, 38, 159-168. https://doi.org/10.1007/s11747-009-0157-x
  • Hong, L. M., Che Nawi, N., & Zulkifli, W. F. W. (2019). Online store image towards perceived risks in online shopping. Journal of Entrepreneurship and Business, 7 (1), 1-9. https://doi.org/10.17687/JEB.0701.01
  • IBIS World 2016. IBIS World’s industry research reports. https://www.ibisworld.com/industrytrends/ (accessed May 29, 2019).
  • Ivanovic, D., & Antonijevic, M. (2020). The Role of Online Shopping in the Republic of Serbia During COVID-19. Economic Analysis, 53 (1), 28-41.
  • Jacoby, J. (1976). Consumer psychology: An octennium. Annual review of psychology, 27 (1), 331-358.
  • Jung, H., Park, M., Hong, K., & Hyun, E. (2016). The impact of an epidemic outbreak on consumer expenditures: An empirical assessment for MERS Korea. Sustainability, 8 (5), 454.
  • Kaplan, L. B., Szybillo, G. J., & Jacoby, J. (1974). Components of perceived risk in product purchase: A cross-validation. Journal of Applied Psychology, 59 (3), 287-291. https://doi.org/10.1037/h0036657
  • Keeney, R. L. (1999). The Value of Internet Commerce to the Customer. Management Science, 45 (4), 533-542.
  • Khattar, A., Jain, P. R., & Quadri, S. M. K. (2020). Effects of the Disastrous Pandemic COVID 19 on Learning Styles, Activities and Mental Health of Young Indian Students-A Machine Learning Approach. In 2020 4th International Conference on Intelligent Computing and Control Systems (ICICCS) (pp. 1190-1195). IEEE.
  • Kim, H., Lee, E. J., & Hur, W. M. (2012). The normative social influence on eco-friendly consumer behavior: The moderating effect of environmental marketing claims. Clothing and Textiles Research Journal, 30 (1), 4-18. https://doi.org/10.1177/0887302X12440875
  • Kostring, J. C. (2012). Eight trends shaping digital marketing in the auto industry. McKinsey & Company.
  • Lee, H., & Cho, C. H. (2019). An empirical investigation on the antecedents of consumers’ cognitions of and attitudes towards digital signage advertising. International Journal of Advertising 38 (1), 97–115.
  • Lee, H. & Cho, C. H. (2020). Digital advertising: present and future prospects. International Journal of Advertising, 39 (3), 332-341.
  • Leigh, A. (2020). How COVID-19 Will Change Consumer Behavior Long-Term. Accessed April 27, 2020; Retrieved from www.chaindrugreview.com/how-covid-19-will-change-consumer-behavior-long-term/
  • Li, J., Hallsworth, A. G., & Coca-Stefaniak, J. A. (2020). The changing grocery shopping behavior of Chinese consumers at the outset of the COVID-19 Outbreak. Age, 6 (53), 574-583.
  • Li, K. J., & Li, X. (2020). COVID-19 Pandemic: Social Distancing, Public Policy, and Market Response. Available at http://dx.doi.org/10.2139/ssrn.3593813
  • Lobschat, L., Osinga, E. C., & Reinartz, W. J. (2017). What happens online stays online? Segment-specific online and offline effects of banner advertisements. Journal of Marketing Research, 54 (6), 901-913.
  • Ludwig, S., De Ruyter, K., Friedman, M., Brüggen, E. C., Wetzels, M., & Pfann, G. (2013). More than words: The influence of affective content and linguistic style matches in online reviews on conversion rates. Journal of Marketing, 77 (1), 87-103. https://doi.org/10.1509%2Fjm.11.0560
  • MAXQDA Standart [Computer Software]. (2020). https://www.maxqda.com/
  • Melnyk, V., Carrillat, F. A., & Melnyk, V. (2022). The influence of social norms on consumer behavior: A meta-analysis. Journal of Marketing, 86 (3), 98-120. https://doi.org/10.1177/00222429211029199
  • Mwencha, P. M., & Muathe, S. M. (2019). A principal component analysis of customers’ perceived risks for online retailing services: Evidence from Kenya. Journal of Customer Behaviour, 18 (3), 167–190.
  • Naiyi, Y. E. (2004). Dimensions of consumer’s perceived risk in online shopping. Journal of Electronic Science and Technology of China, 2 (3), 177-182.
  • Netcomm Suisse Observatory & United Nations Conference on Trade and Development (2020). COVID-19 and E-commerce: Findings from a survey of online consumers in 9 countries. https://unctad.org/system/files/official-document/dtlstictinf2020d1_en.pdf
  • Nielsen Media Research and Interactive Advertising Bureau (2012), “A Comprehensive Picture of Digital Video and TV Advertising: Viewing, Budget Share Shift and Effectiveness,” Accessed January 20, 2013; retrieved from http://www.iab.net/media/file/Digital-Video-and-TV-Advertising-ViewingBudget-Share-Shift-and-Effectiveness.pdf.
  • Özcan, S. O. (2010). İnternet pazarlama faaliyetlerinde tüketici satın alma karar süreci. İnternet Uygulamaları ve Yönetimi Dergisi, 1 (2), 29-39.
  • Pliner, P., & Mann, N. (2004). Influence of social norms and palatability on amount consumed and food choice. Appetite, 42 (2), 227-237. https://doi.org/10.1016/j.appet.2003.12.001
  • Shaikh, A. (2020). Effective factors in changing the buying behavior of consumer due to Covid-19. Studies in Indian Place Names, 40 (68), 408-414.
  • Spencer, T. (2016). Risk Perception: Theories and Approaches. Nova Science Publishers, Inc.
  • Statista (2021). Number of social network users worldwide from 2017 to 2025(in billions). Retrieved from: https://www.statista.com/statistics/278414/number-of-worldwide-social-network-users/
  • Stone R. N., & Grønhaug K. (1993). Perceived Risk; Further Considerations for the Marketing Discipline. European Journal of Marketing, 27 (3), 39–50.
  • Swinyard, W. R., & Smith, S. M. (2003). Why people (don't) shop online: A lifestyle study of the internet consumer. Psychology & marketing, 20 (7), 567-597.
  • Tan, S. J. (1999). Strategies for reducing consumers’ risk aversion in internet shopping. Journal of Consumer Marketing, 16 (2), 163-180.
  • Tetteh, V. A. (2019). Consumer Behavior. Salem Press Encyclopedia.
  • Turkish Statistical Institute (2019), “Information Society Statistics, Households with access to the Internet”, Accessed July 29, 2019; available at http://www.tuik.gov.tr/UstMenu.do?metod=temelist.
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There are 60 citations in total.

Details

Primary Language English
Subjects Microeconomics (Other)
Journal Section Articles
Authors

Cansu Kaya 0000-0001-6084-0747

Sinem Gemalmaz 0000-0002-3557-6187

Yeşim Üzümcüoğlu Zihni 0000-0002-4905-5518

Merve Kartal 0000-0001-5223-1925

Suzan Ceylan-batur 0000-0003-2073-7598

Publication Date June 15, 2024
Submission Date October 13, 2023
Acceptance Date April 30, 2024
Published in Issue Year 2024 Volume: 26 Issue: 2

Cite

APA Kaya, C., Gemalmaz, S., Üzümcüoğlu Zihni, Y., Kartal, M., et al. (2024). HOW COVID-19 CHANGED CONSUMER BEHAVIOR TRENDS IN TÜRKİYE?. Dokuz Eylül Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 26(2), 915-945. https://doi.org/10.16953/deusosbil.1375618