Araştırma Makalesi
BibTex RIS Kaynak Göster

Türk Tüketicilerinin Satın Alma Niyetlerinin, Omni-Kanallı Mağazalar ve Birleştirilmiş Teknolojinin Kabul ve Kullanımı Teorisi (Utaut-2) Bağlamında İncelenmesi Üzerine Bir Araştırma

Yıl 2024, , 281 - 299, 31.12.2024
https://doi.org/10.54821/uiecd.1549197

Öz

Bu makalenin amacı, Türk Tüketicilerinin omnikanal mağazalardan satın alma sürecindeki davranışlarının altında yatan motivasyon faktörlerini, teknolojinin mevcut rolüne ilişkin daha derin ve daha geniş bir bakış açısıyla incelemektir. Araştırmada nicel araştırma yöntemi kullanılmıştır. Türkiye'de yerleşik 456 kişi ankete katılarak, son 12 aylık dönem içinde, satın alma işlemlerine yönelik davranışlarını belirtmişlerdir. Araştırmadan elde edilen verilerin analizinde, Smart Pls ve IBM SPSS-25 istatistik yazılım paketlerinden yararlanılmıştır. Araştırmanın hipotez analizi kısmı, aşağıda belirtilen faktörlerin satın alma davranışı üzerinde olumlu etkiye sahip olduğunu ileri sürmektedir. Bu faktörler algılanan güven, yenilik, fiyatlandırma değeri ve satın alma niyetidir. Çalışmanın bulgularına göre, Omnikanaldan hizmet veya ürün satın alan Türk Tüketiciler kullandıkları teknolojik cihazlar aracılığıyla reklam mesajlarını alma, bu cihazlarla ürün ve fiyatları karşılaştırma olanağına sahiptirler. Bu nedenle, satın alma işlemlerini tamamlamak ve ayrıca satış sonrası teslimatlarını izlemek için kişiselleştirilmiş kampanyaları da takip etmektedirler.

Kaynakça

  • Agarwal, R., & Prasad, J. (1998). A conceptual and operational definition of personal innovativeness in the domain of information technology. Information Systems Research, 9(2), 204–215.
  • Ajzen. I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50 (2), 179- 211.
  • Apostolova, E., & Gehrt, K. (2000). Credit card use and abuse by today's and tomorrow's elderly. Journal of Nonprofit & Public Sector Marketing, 7(1), 25-49.
  • Ayensa, E.J., Mosquera, A., & Murillo, Y. S. (2016). Omnichannel customer behavior: key drivers of technology acceptance and use and their effects on purchase intention. Frontiers in Psychology, 7, 1-11.
  • Bakan, D. (1966). The test of significance in psychological research. Psychological Bulletin, 66(6), 423–437.
  • Brown, S. A., & Venkatesh, V. (2005). Model of adoption of technology in the household: A baseline model test and extension incorporating household life cycle. Management Information System Quarterly, 29, 399-426.
  • Chang, A. (2012). UTAUT and UTAUT 2: A rewiev and agenda for future research. Journal the Winners. 13(2), 106-114.
  • Chau, P., & Hui, K. L. (1998). Identifying early adopters of new IT products: A case of Windows 95. Information & Management, 33(5), 225-233.
  • Chellappa, R.K. and Pavlou, P.A. (2002). Perceived information security, financial liability and consumer trust in electronic commerce transactions. Logistics Information Management, 15(5-6), 358-368.
  • Childers, T., Carr, C., Peck, J., & Carson, P. (2001). Hedonic and utilitarian motivations for online retail shopping behavior. Journal of Retailing, 77(4), 511-535.
  • Chin, W., & Marcoulides, G. (1998). The Partial least squares approach to structural equation modeling. Advances in Hospitality and Leisure, 8(2).
  • Citrin, V. A., 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.
  • Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum Associates, Publishers.
  • Coskun, T., & Marangoz, M. (2019). Hedonik ve faydacı tüketim davranışları ölçeğinin geliştirilmesi: güvenirlik ve geçerlik çalışması. Business and Economics Research Journal, 10(2), 517-540.
  • Davis, F. D., & Cosenza R. M. (1985). Business research for decision making, Boston: Kent Publishing Company.
  • Deaux, K., & Kite, M. E. (1987). Thinking about gender. In B. B. Hess & M. M. Ferree (Eds.), Analyzing gender: A handbook of social science research (pp. 92–117). Sage Publications, Inc.
  • Deaux, K., & Lewis, L. L. (1984). Structure of gender stereotypes: Interrelationships among components and gender label. Journal of Personality and Social Psychology, 46(5), 991–1004.
  • Dodds, William B., Monroe, Kent, B., & Grewal, D. (1991). Effects of price, brand, and store information on buyers' product evaluations. JMR, Journal of Marketing Research, 23(3), 307-321.
  • Faqih, K. (2015). An empirical analysis of factors predicting the behavioral intention to adopt Internet shopping technology among non-shoppers in a developing country context: Does gender matter? Journal of Retailing and Consumer Service, 30, 140-164.
  • Fishbein M., & Ajzen I. (1975). Beliefs, attitude, intention and behavior: An introduction to theory and research. Boston: Addison-Wesley.
  • Fishbein, M., & Ajzen, I. (2010). Predicting and changing behavior: The reasoned action approach. New York, NY: Psychology Press.
  • Frasquet, M., Molina, M. & Descals, A. (2015). The role of the brand in driving online loyalty for multichannel retailers. The International Review of Retail, Distribution and Consumer Research, 25(5), The 18th International Conference on Research in the Distributive Trades – EAERCD.
  • Gensler, S., Neslin, S. A., & Verhoef, P. C. (2017). The showrooming phenomenon: It’s more than just about price. Journal of Interactive Marketing, 38(1), 29-43.
  • Goldsmith, R., & Hofacer, C. (1991). Measuring consumer innovativeness, Journal of the Academy of Marketing Science 19(3), 209-221.
  • Grohmann, M. Z., Battistella, L., & Velter, A. N. (2011). The impact of the sales approach in the acceptance on technologically innovative products. Journal of Information Systems and Technology Management, 10(1), 177-197.
  • Hair, J. F. (2009). Multivariate data analysis, 2. Edition, Pearson Prentice Hall, New Jersey.
  • Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis. 7th ed., Pearson Prentice Hall, New Jersey.
  • Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2014) Multivariate data analysis. 7th Edition, Pearson Education, Upper Saddle River.
  • Hair, J. F., Sarsted, M., Ringle, C. M., & Gudergan, S. P. (2017). Advanced issues in partial least squares structural equation modeling. Sage Publication Inc.
  • Hair, J. F., Sarstedt, M., Ringle, C. M., & Mena, J. A. (2012). An assessment of the use of partial least squares structural equation modeling in marketing research. Journal of the Academy of Marketing Science, 40(3), 414-433.
  • Hall, D.T., & Mansfield, R. (1975). Relationships of age and seniority with career variables of engineers and scientists. Journal of Applied Psychology, 60(2), 201–210.
  • Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43, 115-135.
  • Hirschman, E. (1980). Innovativeness, novelty seeking, and consumer creativity. Journal of Consumer Research 7(3). 283-295.
  • Hirschman, E., & Holbrook, M. (1982). Hedonic consumption: emerging concepts, methods and propositions. Journal of Marketing, 46(3), 92-101.
  • Ho Cheong, J., & Park, M. (2005). Mobile internet acceptance in Korea. Internet Research, 15(2), 125-140.
  • Karahanna, E., Straub, D., & Chervany, N. (1999). Information technology acceptance across time: a cross-sectional comparison of pre-adoption and post-adoption beliefs. MIS Quarterly, 23, 183-213.
  • Kim, H. W., Chan, H. C., & Gupta, S. (2007). Value-Based Adoption of Mobile Internet: An Empirical Investigation," Decision Support Systems, 43(1), 111-126.
  • Kim,J., Forsythe, S. (2008). Hedonic usage of product virtualization technologies in online apparel shopping. International Journal of Retail & Distribution Management, 35(6), 502-514.
  • Kothari, C. R. (2004) Research methodology: Methods and techniques. 2nd Edition, New Age International Publishers, New Delhi.
  • Lazaris, C., Vrechopoulos, A., Katerina, F., & Doukidis, G. (2014). Exploring the “Omnichannel” shopper behavior. in AMA SERVSIG, International Service Research Conference, 1–15.
  • Lee, H., & Leonas, K. (2018). Consumer experiences, the key to survive in an omni-channel environment: Use of virtual technology. Journal of Textile and Apparel, Technology and Management, 10(3), 1-23.
  • Malthora, N. (2004). Review of marketing research, M.E. Sharpe Armonk Inc.
  • Marangoz, M., & Aydin, A. E. (2017). Tüketicilerin değişen alışveriş alışkanlıkları ve perakendecilikte bütünleşik dağıtım kanalı yaklaşımı. Journal of Consumer and Consumption Research, 9(1), 71-93.
  • Menz, H. B., Morris, M. E., & Lord, S. R. (2005). Foot and ankle characteristics associated with impaired balance and functional ability in older people. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, 60(12), 1546-1552.
  • Midgley, D. F., & Dowling, G. R. (1978). Innovativeness: The concept and its measurement. Journal of consumer research, 4(4), 229-242.
  • Mosquera, A., Pascual, C. O., & Ayensa, E. J. (2017). Understanding the customer experience in the age of omni-channel shopping. Icono14, 15(2), 235-255.
  • Neslin, S. A., Grewal, D., Leghorn, R., Shankar, V., Teerling, M. L., Thomas, J. S., & Verhoef, P. C. (2006). Challenges and opportunities in multichannel customer management. Journal of service research, 9(2), 95-112.
  • Pantano, E., & Viassone, M. (2015). Engaging consumers on new integrated multichannel retail settings: Challenges for retailers. Journal of Retailing and Consumer Services, 25, 106-114.
  • Pantano, E., & Viassone, M. (2015). Engaging consumers on new integrated multichannel retail settings: Challenges for retailers. Journal of Retailing and Consumer Services, 25, 106-114.
  • Pieri, M., & Diamantinir, D. (2010). Young people, elderly and ICT. Procedia-Social and Behavioral Sciences, 2(2), 2422-2426.
  • Plude, D. J., & Hoyer, W. J. (1986). Age and the selectivity of visual information processing. Psychology and Aging, 1(1), 4-10.
  • Posner, E. A. (1996). Law, economics, and inefficient norms. University of Pennsylvania Law Review, 144(5), 1697-1744.
  • Salisbury, W. D., Pearson, R. A., Pearson, A. W., & Miller, D. W. (2001). Perceived security and World Wide Web purchase intention. Industrial Management & Data Systems, 101(4), 165-177.
  • Salmones, M. D. M. G. D. L., Crespo, A. H., & Bosque, I. R. D. (2005). Influence of corporate social responsibility on loyalty and valuation of services. Journal of business ethics, 61(4), 369-385.
  • Sivakumar, B., Jayawardena, A. W., & Fernando, T. M. K. G. (2002). River flow forecasting: use of phase-space reconstruction and artificial neural networks approaches. Journal of Hydrology, 265(1-4), 225-245.
  • Slama, M. E., & Tashchian, A. (1985). Selected socioeconomic and demographic characteristics associated with purchasing involvement. Journal of Marketing, 49(1), 72-82.
  • Thong, J. Y., Hong, S. J., & Tam, K. Y. (2006). The effects of post-adoption beliefs on the expectation-confirmation model for information technology continuance. International Journal of Human-Computer Studies, 64(9), 799-810.
  • Uyar, A. (2019). Evaluation of consumers’ perception about mobile applications according to the technology acceptance model. Journal of Business Research-Turk, 11(1), 687-705.
  • Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 27(3), 425-478.
  • Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information: extending the unified theory of acceptance and use of technology. MIS Quarterly 36(1), 150-178.
  • Verhoef, P. C., Kannan, P. K., & Inman, J. J. (2015). From multi-channel retailing to omni-channel retailing: introduction to the special issue on multi-channel retailing. Journal of retailing, 91(2), 174-181.
  • Winch, G., & Joyce, P. (2006). Exploring the dynamics of building, and losing, consumer trust in B2C eBusiness. International Journal of Retail & Distribution Management, 34(7), 541-555.
  • Zeithaml, V. A. (1988). Consumer perceptions of price, quality, and value: a means-end model and synthesis of evidence. Journal of Marketing, 52(3), 2-22.

A Research on the Investigation of Turkish Consumers' Purchase Intentions in the Context of Omni-Channel Shops and Unified Theory of Acceptance and Use of Technology (Utaut-2)

Yıl 2024, , 281 - 299, 31.12.2024
https://doi.org/10.54821/uiecd.1549197

Öz

The particular aim of this paper is to examine the motivational factors underlying Turkish consumers' behavior during the process of their purchasing from omnichannel shops, with a deeper and broader perspective on the current role of technology. The Quantitative research method was used to achieve the adopted research objective. A total of 456 respondents shared their actions regarding their last purchase in the 12 months prior to data collection in Turkey. The hypothesis analysis part of this article suggests that the following elements have a favourable impact on purchasing behaviour: perceived trust, innovation, pricing value, and purchase intention. According to the study's findings, Turkish omni-channel shoppers value the ability to receive advertising messages through the technological devices they use, compare products and prices with these devices, and thus expect personalised campaigns to complete their purchases and track post-sale deliveries.

Kaynakça

  • Agarwal, R., & Prasad, J. (1998). A conceptual and operational definition of personal innovativeness in the domain of information technology. Information Systems Research, 9(2), 204–215.
  • Ajzen. I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50 (2), 179- 211.
  • Apostolova, E., & Gehrt, K. (2000). Credit card use and abuse by today's and tomorrow's elderly. Journal of Nonprofit & Public Sector Marketing, 7(1), 25-49.
  • Ayensa, E.J., Mosquera, A., & Murillo, Y. S. (2016). Omnichannel customer behavior: key drivers of technology acceptance and use and their effects on purchase intention. Frontiers in Psychology, 7, 1-11.
  • Bakan, D. (1966). The test of significance in psychological research. Psychological Bulletin, 66(6), 423–437.
  • Brown, S. A., & Venkatesh, V. (2005). Model of adoption of technology in the household: A baseline model test and extension incorporating household life cycle. Management Information System Quarterly, 29, 399-426.
  • Chang, A. (2012). UTAUT and UTAUT 2: A rewiev and agenda for future research. Journal the Winners. 13(2), 106-114.
  • Chau, P., & Hui, K. L. (1998). Identifying early adopters of new IT products: A case of Windows 95. Information & Management, 33(5), 225-233.
  • Chellappa, R.K. and Pavlou, P.A. (2002). Perceived information security, financial liability and consumer trust in electronic commerce transactions. Logistics Information Management, 15(5-6), 358-368.
  • Childers, T., Carr, C., Peck, J., & Carson, P. (2001). Hedonic and utilitarian motivations for online retail shopping behavior. Journal of Retailing, 77(4), 511-535.
  • Chin, W., & Marcoulides, G. (1998). The Partial least squares approach to structural equation modeling. Advances in Hospitality and Leisure, 8(2).
  • Citrin, V. A., 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.
  • Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum Associates, Publishers.
  • Coskun, T., & Marangoz, M. (2019). Hedonik ve faydacı tüketim davranışları ölçeğinin geliştirilmesi: güvenirlik ve geçerlik çalışması. Business and Economics Research Journal, 10(2), 517-540.
  • Davis, F. D., & Cosenza R. M. (1985). Business research for decision making, Boston: Kent Publishing Company.
  • Deaux, K., & Kite, M. E. (1987). Thinking about gender. In B. B. Hess & M. M. Ferree (Eds.), Analyzing gender: A handbook of social science research (pp. 92–117). Sage Publications, Inc.
  • Deaux, K., & Lewis, L. L. (1984). Structure of gender stereotypes: Interrelationships among components and gender label. Journal of Personality and Social Psychology, 46(5), 991–1004.
  • Dodds, William B., Monroe, Kent, B., & Grewal, D. (1991). Effects of price, brand, and store information on buyers' product evaluations. JMR, Journal of Marketing Research, 23(3), 307-321.
  • Faqih, K. (2015). An empirical analysis of factors predicting the behavioral intention to adopt Internet shopping technology among non-shoppers in a developing country context: Does gender matter? Journal of Retailing and Consumer Service, 30, 140-164.
  • Fishbein M., & Ajzen I. (1975). Beliefs, attitude, intention and behavior: An introduction to theory and research. Boston: Addison-Wesley.
  • Fishbein, M., & Ajzen, I. (2010). Predicting and changing behavior: The reasoned action approach. New York, NY: Psychology Press.
  • Frasquet, M., Molina, M. & Descals, A. (2015). The role of the brand in driving online loyalty for multichannel retailers. The International Review of Retail, Distribution and Consumer Research, 25(5), The 18th International Conference on Research in the Distributive Trades – EAERCD.
  • Gensler, S., Neslin, S. A., & Verhoef, P. C. (2017). The showrooming phenomenon: It’s more than just about price. Journal of Interactive Marketing, 38(1), 29-43.
  • Goldsmith, R., & Hofacer, C. (1991). Measuring consumer innovativeness, Journal of the Academy of Marketing Science 19(3), 209-221.
  • Grohmann, M. Z., Battistella, L., & Velter, A. N. (2011). The impact of the sales approach in the acceptance on technologically innovative products. Journal of Information Systems and Technology Management, 10(1), 177-197.
  • Hair, J. F. (2009). Multivariate data analysis, 2. Edition, Pearson Prentice Hall, New Jersey.
  • Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis. 7th ed., Pearson Prentice Hall, New Jersey.
  • Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2014) Multivariate data analysis. 7th Edition, Pearson Education, Upper Saddle River.
  • Hair, J. F., Sarsted, M., Ringle, C. M., & Gudergan, S. P. (2017). Advanced issues in partial least squares structural equation modeling. Sage Publication Inc.
  • Hair, J. F., Sarstedt, M., Ringle, C. M., & Mena, J. A. (2012). An assessment of the use of partial least squares structural equation modeling in marketing research. Journal of the Academy of Marketing Science, 40(3), 414-433.
  • Hall, D.T., & Mansfield, R. (1975). Relationships of age and seniority with career variables of engineers and scientists. Journal of Applied Psychology, 60(2), 201–210.
  • Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43, 115-135.
  • Hirschman, E. (1980). Innovativeness, novelty seeking, and consumer creativity. Journal of Consumer Research 7(3). 283-295.
  • Hirschman, E., & Holbrook, M. (1982). Hedonic consumption: emerging concepts, methods and propositions. Journal of Marketing, 46(3), 92-101.
  • Ho Cheong, J., & Park, M. (2005). Mobile internet acceptance in Korea. Internet Research, 15(2), 125-140.
  • Karahanna, E., Straub, D., & Chervany, N. (1999). Information technology acceptance across time: a cross-sectional comparison of pre-adoption and post-adoption beliefs. MIS Quarterly, 23, 183-213.
  • Kim, H. W., Chan, H. C., & Gupta, S. (2007). Value-Based Adoption of Mobile Internet: An Empirical Investigation," Decision Support Systems, 43(1), 111-126.
  • Kim,J., Forsythe, S. (2008). Hedonic usage of product virtualization technologies in online apparel shopping. International Journal of Retail & Distribution Management, 35(6), 502-514.
  • Kothari, C. R. (2004) Research methodology: Methods and techniques. 2nd Edition, New Age International Publishers, New Delhi.
  • Lazaris, C., Vrechopoulos, A., Katerina, F., & Doukidis, G. (2014). Exploring the “Omnichannel” shopper behavior. in AMA SERVSIG, International Service Research Conference, 1–15.
  • Lee, H., & Leonas, K. (2018). Consumer experiences, the key to survive in an omni-channel environment: Use of virtual technology. Journal of Textile and Apparel, Technology and Management, 10(3), 1-23.
  • Malthora, N. (2004). Review of marketing research, M.E. Sharpe Armonk Inc.
  • Marangoz, M., & Aydin, A. E. (2017). Tüketicilerin değişen alışveriş alışkanlıkları ve perakendecilikte bütünleşik dağıtım kanalı yaklaşımı. Journal of Consumer and Consumption Research, 9(1), 71-93.
  • Menz, H. B., Morris, M. E., & Lord, S. R. (2005). Foot and ankle characteristics associated with impaired balance and functional ability in older people. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, 60(12), 1546-1552.
  • Midgley, D. F., & Dowling, G. R. (1978). Innovativeness: The concept and its measurement. Journal of consumer research, 4(4), 229-242.
  • Mosquera, A., Pascual, C. O., & Ayensa, E. J. (2017). Understanding the customer experience in the age of omni-channel shopping. Icono14, 15(2), 235-255.
  • Neslin, S. A., Grewal, D., Leghorn, R., Shankar, V., Teerling, M. L., Thomas, J. S., & Verhoef, P. C. (2006). Challenges and opportunities in multichannel customer management. Journal of service research, 9(2), 95-112.
  • Pantano, E., & Viassone, M. (2015). Engaging consumers on new integrated multichannel retail settings: Challenges for retailers. Journal of Retailing and Consumer Services, 25, 106-114.
  • Pantano, E., & Viassone, M. (2015). Engaging consumers on new integrated multichannel retail settings: Challenges for retailers. Journal of Retailing and Consumer Services, 25, 106-114.
  • Pieri, M., & Diamantinir, D. (2010). Young people, elderly and ICT. Procedia-Social and Behavioral Sciences, 2(2), 2422-2426.
  • Plude, D. J., & Hoyer, W. J. (1986). Age and the selectivity of visual information processing. Psychology and Aging, 1(1), 4-10.
  • Posner, E. A. (1996). Law, economics, and inefficient norms. University of Pennsylvania Law Review, 144(5), 1697-1744.
  • Salisbury, W. D., Pearson, R. A., Pearson, A. W., & Miller, D. W. (2001). Perceived security and World Wide Web purchase intention. Industrial Management & Data Systems, 101(4), 165-177.
  • Salmones, M. D. M. G. D. L., Crespo, A. H., & Bosque, I. R. D. (2005). Influence of corporate social responsibility on loyalty and valuation of services. Journal of business ethics, 61(4), 369-385.
  • Sivakumar, B., Jayawardena, A. W., & Fernando, T. M. K. G. (2002). River flow forecasting: use of phase-space reconstruction and artificial neural networks approaches. Journal of Hydrology, 265(1-4), 225-245.
  • Slama, M. E., & Tashchian, A. (1985). Selected socioeconomic and demographic characteristics associated with purchasing involvement. Journal of Marketing, 49(1), 72-82.
  • Thong, J. Y., Hong, S. J., & Tam, K. Y. (2006). The effects of post-adoption beliefs on the expectation-confirmation model for information technology continuance. International Journal of Human-Computer Studies, 64(9), 799-810.
  • Uyar, A. (2019). Evaluation of consumers’ perception about mobile applications according to the technology acceptance model. Journal of Business Research-Turk, 11(1), 687-705.
  • Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 27(3), 425-478.
  • Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information: extending the unified theory of acceptance and use of technology. MIS Quarterly 36(1), 150-178.
  • Verhoef, P. C., Kannan, P. K., & Inman, J. J. (2015). From multi-channel retailing to omni-channel retailing: introduction to the special issue on multi-channel retailing. Journal of retailing, 91(2), 174-181.
  • Winch, G., & Joyce, P. (2006). Exploring the dynamics of building, and losing, consumer trust in B2C eBusiness. International Journal of Retail & Distribution Management, 34(7), 541-555.
  • Zeithaml, V. A. (1988). Consumer perceptions of price, quality, and value: a means-end model and synthesis of evidence. Journal of Marketing, 52(3), 2-22.
Toplam 63 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular İşletme , Pazarlama (Diğer)
Bölüm Araştırma Makaleleri
Yazarlar

A. Cüneyd Deniz 0000-0002-1318-5660

İge Pırnar 0000-0002-8068-1736

Hüseyin Ozan Altın

Yayımlanma Tarihi 31 Aralık 2024
Gönderilme Tarihi 12 Eylül 2024
Kabul Tarihi 30 Aralık 2024
Yayımlandığı Sayı Yıl 2024

Kaynak Göster

APA Deniz, A. C., Pırnar, İ., & Altın, H. O. (2024). A Research on the Investigation of Turkish Consumers’ Purchase Intentions in the Context of Omni-Channel Shops and Unified Theory of Acceptance and Use of Technology (Utaut-2). International Journal of Business and Economic Studies, 6(4), 281-299. https://doi.org/10.54821/uiecd.1549197

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