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YAPAY ZEKANIN YEŞİL ÜRÜN SATIN ALMA DAVRANIŞINA ETKİSİ

Year 2023, Volume: 3 Issue: 2, 39 - 54, 30.10.2023

Abstract

Son yıllarda, çevresel sürdürülebilirlik konusunda artan bir endişenin olması ve tüketicilerin artan çevre bilinci, tüketicilerin
satın alma davranışlarını değiştirmektedir. Bu durum son yıllarda tüketicilerin yeşil ürünlere olan talebini artırmış ve
işletmelere ve hükümetlere yeşil üretimi benimseme konusunda baskı yapmasına neden olmuştur. Bu açıdan yapılan bu
çalışma, yapay zekanın tüketicilerin yeşil ürün satın alma davranışı üzerindeki etkisine odaklanmaktadır. Uyaran-organizma tepki modeline dayanan bu çalışma, yapay zekanın tüketicilerin yeşil ürün satın alma davranışları üzerindeki etkisini yapay
zeka pazarlama çabaları (bilgi, erişilebilirlik ve özelleştirme) ile incelemektedir. Ayrıca çalışma kapsamında yapay zeka
pazarlama çabalarının marka deneyimine olan etkisi de araştırılmıştır. Bu kapsamda katılımcılardan yüz yüze anket
yöntemiyle toplanan veriler Smart PLS4 ve SPSS 26 programları kullanılarak analiz edilmiştir. Yapılan analiz sonuçlarına
göre yapay zeka pazarlama çabaları (bilgi, erişilebilirlik, etkileşim ve özelleştirme) unsurlarının tümünün marka deneyimi ve
satın alma niyetleri üzerinde etkili olduğunu göstermektedir. Ayrıca çalışma kapsamında tespit edilen bir diğer önemli bulgu
ise marka deneyiminin tüketicilerin satın alma niyetlerini olumlu olarak etkilediği bulgusudur.

References

  • Abou-Zahra, S., Brewer, J. and Cooper, M. (2018). Artificial intelligence (AI) for web accessibility: Is conformance evaluation a way forward? [Paper presentation]. Proceedings of the 15th International Web for All Conference, 1–4, Lyon, France. https://doi.org/10.1145/3192714.3192834
  • Akyılmaz, B. (2022). Yapay Zekâ ve Tüketici Davranışı Alanındaki Yayınların Bibliyometrik Analizi. İşletme Araştırmaları Dergisi,14(1), 947-963.
  • Angeles, R. (2014). Attrıbutes Of Consumers Most Lıkely To Use Goodguıde.Com Sustaınabılıty Informatıon About “Green” Household Products. In L. Mola, A. Carugati, A. Kokkinaki, & N. Pouloudi (Eds.), Proceedings of the 8th Mediterranean Conference on Information Systems (CD-ROM), Verona, Italy, September 03-05. Retrieved from http://aisel.aisnet.org/mcis2014/50
  • Anshu, K., L. Gaur, and G. Singh. 2022. Impact of customer experience on attitude and repurchase intention in online grocery retailing: A moderation mechanism of value Co-creation. Journal of Retailing and Consumer Services 64: 102798.
  • Armağan, V. (2018). Dijital Dönüşüm Sürecinde Akıllı Şehirler ve E-Devlet Platformu. Journal of Communication Theory & Research / Iletisim Kuram ve Arastirma Dergisi, 46, 387–413.
  • Armutcu, B., Ramadani, V., Zeqiri, J. and Dana, L.-P. (2023). The role of social media in consumers’ intentions to buy green food: evidence from Türkiye. British Food Journal, Vol. ahead-of-print No. https://doi.org/10.1108/BFJ-11-2022-0988.
  • Armutcu, B., Zuferi, R., Tan, A. (2023). Green product consumption behaviour, green economic growth and sustainable development: unveiling the main determinants. Journal of Enterprising Communities: People and Places in the Global Economy, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/JEC-05-2023-0074.
  • Asker, J., Fershtman, C. and Pakes, A. (2021). Artificial Intelligence and Pricing: The Impact of Algorithm Design. SSRN Electronic Journal. Working Paper, 28535, 1-52. https://doi.org/10.3386/w28535 Aylak, B. L., Oral, O., & Yazıcı, K. (2021). Yapay Zeka ve Makine Öğrenmesi Tekniklerinin Lojistik Sektöründe Kullanımı. El-Cezeri, 8(1), 74-93. doi: 10.31202/ecjse.776314.
  • Bashar, A., & Rabbani, M. R. (2021). Exploring the Role of Web Personalization in Consumer Green Purchasing Behavior: A Conceptual Framework. In 2021 Third International Sustainability and Resilience Conference: Climate Change (pp. 23-28). Sakheer, Bahrain. https://doi.org/10.1109/IEEECONF53624.2021.9668110
  • Beyari, H., & Garamoun, H. (2022). The Effect of Artificial Intelligence on End-User Online Purchasing Decisions: Toward an Integrated Conceptual Framework. Sustainability, 14(15), 9637. https://doi.org/10.3390/su14159637
  • Bhagat, R., Chauhan, V. and Bhagat, P. (2023), "Investigating the impact of artificial intelligence on consumer’s purchase intention in e-retailing", Foresight, Vol. 25 No. 2, pp. 249-263. https://doi.org/10.1108/FS-10-2021-0218 20.07.2023
  • Cha, N., Cho, H., Lee, S., & Hwang, J. (2019). Effect of AI Recommendation System on the Consumer Preference Structure in e-Commerce: Based on Two types of Preference. 2019 21st International Conference on Advanced Communication Technology (ICACT), 77-80. https://doi.org/10.23919/ICACT.2019.8701967.
  • Cheng, Y., and Jiang, H. (2021). Customer–brand relationship in the era of artificial intelligence: understanding the role of chatbot marketinefforts. The Journal of Product & Brand Management, aheadof-print (ahead-ofprint). Demir, Ç. (2021). Konaklama İşletmelerinin İş Süreçlerinde Yapay Zekâ Teknolojileri ve Akıllı Otel Uygulamaları: Avantajlar ve Dezavantajlar. Journal of Tourism & Gastronomy Studies, 9(1), 203-219.
  • Duarte, D., Ståhl, N. (2019). Machine Learning: A Concise Overview. In: Said, A., Torra, V. (eds) Data Science in Practice. Studies in Big Data, vol 46. Springer, Cham. https://doi.org/10.1007/978-3-319-97556-6_3 Durumaz, Y., & Kılıç, Y. (2023). A Theoretical Approach to Artificial Intelligence in Consumer Behavior. International Business &Economics Studies, 5(2).
  • Ebrahim, R., A. Ghoneim, Z. Irani, and Y. Fan. 2016. A brand preference and repurchase intention model: The role of consumer experience. Journal of Marketing Management 32 (13–14): 1230–1259.
  • Ever, D. & Demircioğlu, E. N. (2022). Yapay Zekâ Teknolojilerinin Kalite Maliyetleri Üzerine Etkisi . Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 31 (1), 59-72 . DOI: 10.35379/cusosbil.1023004
  • Fornell, C., and D.F. Larcker. 1981. Evaluation structural equality models with unobserved variables and measurement error. Journal of Marketing Research 18 (1): 39–50.
  • Frank, B. (2021). Artificial intelligence-enabled environmental sustainability of products: Marketing benefits and their variation by consumer, location, and product types. Journal of Cleaner Production, 285, 125242. https://doi.org/10.1016/j.jclepro.2020.125242.
  • FuiYeng, W., & Yazdanifard, R. (2015). Green marketing: A study of consumers’ buying behavior in relation to green products. Global Journal of Management and Business Research: E Marketing, 15(5), 16-23.
  • Ghosh, S., & Singh, A. (2020). The scope of Artificial Intelligence in mankind: A detailed review. Journal of Physics: Conference Series, 1531(012045). https://doi.org/10.1088/1742-6596/1531/1/012045
  • Godey, B., A. Manthiou, D. Pederzoli, J. Rokka, G. Aiello, R. Donvito, and R. Singh. 2016. Social media marketing efforts of luxury brands: Influence on brand equity and consumer behavior. Journal of Business Research 69 (12): 5833–5841
  • Guha, A., Grewal, D., Kopalle, P., Haenlein, M., Schneider, M., Jung, H., Moustafa, R., Hegde, D., & Hawkins, G. (2021). How artificial intelligence will affect the future of retailing. Journal of Retailing, 97, 28-41.
  • Gülleroğlu, H. D. (2021). Yapay Zekanın Tarih İçindeki Gelişimi ve Eğitimde Kullanılması. Ankara Universitesi Egitim Bilimleri Fakultesi Dergisi. https://doi.org/10.30964/auebfd.916220 Gülsen, I. (2019). İşletmelerde yapay zeka uygulamaları ve faydaları: perakende sektöründe bir derleme. Tüketici ve Tüketim Araştırmaları Dergisi= Journal of Consumer and Consumption Research, 11(2), 407-436.
  • Habil, S., El-Deeb, S., & El-Bassiouny, N. (2023). AI-Based Recommendation Systems: The Ultimate Solution for Market Prediction and Targeting. In The Palgrave Handbook of Interactive Marketing (pp. 683-704). Cham: Springer International Publishing.
  • Hair, J.F., Jr, Sarstedt, M., Ringle, C.M. and Gudergan, S.P. (2017), Advanced _Issues in Partial Least Squares Structural Equation Modeling, Sage Publications, London, ISBN: 9781483377391.
  • İnce, H., İmamoğlu, S. E., & İmamoğlu, S. Z. (2021). Yapay zeka uygulamalarının karar verme üzerine etkileri: Kavramsal birçalışma [The effects of artificial intelligence applications on decision-making: A conceptual study]. International Review ofEconomics and Management, 9(1), 50-63.
  • Jiang, Y., Li, X., Luo, H., Yin, S., & Kaynak, O. (2022). Quo vadis artificial intelligence?. Discover Artificial Intelligence, 2(1), 4. 10.17010/ijom/2013/v43/i12/80511
  • Kamran, H. (2021). Pazarlamada Yapay Zekânın Kullanımı: Yapay Zekâ Pazarlama Araçlarının Tüketici Kabulüne Ilişkin Bir Araştırma (Doctoral dissertation, Bursa Uludag University (Turkey)).
  • Karataş, S. (2021). Yapay zeka ve açık inovasyon etkileşiminin işletmeler üzerine etkileri (Master's thesis, Aydın Adnan Menderes Üniversitesi Sosyal Bilimler Enstitüsü).
  • Khan, S. I. (2022). Impact of artificial intelligence on consumer buying behaviors: Study about the online retail purchase. International Journal of Health Sciences, 8121-8129. https://doi.org/10.53730/ijhs.v6nS2.7025 Kim, J., Kang, S., & Bae, J. (2022). The effects of customer consumption goals on artificial intelligence driven recommendation agents: evidence from Stitch Fix. International Journal of Advertising, 41(6), 997-1016. https://doi.org/10.1080/02650487.2021.1963098
  • Kock, N. (2015), “Common method bias in PLS-SEM: a full collinearity assessment approach”, International Journal of e-Collaboration, Vol. 11 No. 4, pp. 1-10.
  • Lacom, P., & Sagot, S. (2022). A Research Framework for B2B Green Marketing Innovation: the Design of Sustainable Websites. In 2022 IEEE 28th International Conference on Engineering, Technology and Innovation (ICE/ITMC) & 31st International Association For Management of Technology (IAMOT) Joint Conference, pp. 1-9. Nancy, France. doi:10.1109/ICE/ITMC-IAMOT55089.2022.10033239.
  • Lake, B., Ullman, T., Tenenbaum, J., & Gershman, S. (2017). Building machines that learn and think like people. Behavioral and Brain Sciences, 40, E253. doi:10.1017/S0140525X16001837
  • Lee, Y. L., & Huang, F. H. (2011). Recommender system architecture for adaptive green marketing. Expert Systems with Applications, 38(8), 9696-9703.
  • Li, Y., Zhong, Z., Zhang, F., & Zhao, X. (2022). Artificial Intelligence-Based Human-Computer Interaction Technology Applied inConsumer Behavior Analysis and Experiential Education. Frontiers in Psychology, 13, 784311. doi: 10.3389/fpsyg.2022.784311.
  • Malik, R., Jindal, T., & Sharma, A. (2022). Role of Artificial Intelligence in Reshaping Retail. In 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE) (pp. 660-664). Greater Noida, India. doi: 10.1109/ICACITE53722.2022.9823675.
  • Nguyen, T., S. Quach, and P. Thaichon. 2021. The effect of AI quality on customer experience and brand relationship. Journal of Consumer Behavior. https:// doi. org/ 10. 1002/ cb. 1974.
  • Ribeiro De Oliveira, T., Biancardi Rodrigues, B., Moura Da Silva, M., Antonio N. Spinassé, R., Giesen Ludke, G., Ruy Soares Gaudio, M., Iglesias Rocha Gomes, G., Guio Cotini, L., Da Silva Vargens, D., Queiroz Schimidt, M., Varejão Andreão, R., & Mestria, M. (2022). Virtual Reality Solutions Employing Artificial Intelligence Methods: A Systematic Literature Review. ACM Computing Surveys, 55, 1 - 29. https://doi.org/10.1145/3565020
  • Schermelleh-Engel, K., Moosbrugger, H. and Müller, H. (2003), “Evaluating the fit of structural equation models: tests of significance and descriptive goodness-of-fit measures”, Methods of Psychological Research Online, Vol. 8 No. 2, pp. 23-74.
  • Schumacker, R.E. and Lomax, R.G. (1996), A Beginner’s Guide to Structural Equation Modelling, Lawrence Erlbaum Associates, NJ, Publishers.
  • Tiautrakul, J., & Jindakul, J. (2019). The Artificial Intelligence (AI) with the Future of Digital Marketing. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3405184.
  • Yang, X., Li, H., Ni, L., & Li, T. (2021). Application of Artificial Intelligence in Precision Marketing. J. Organ. End User Comput., 33, 209-219. https://doi.org/10.4018/JOEUC.20210701.OA10.
Year 2023, Volume: 3 Issue: 2, 39 - 54, 30.10.2023

Abstract

References

  • Abou-Zahra, S., Brewer, J. and Cooper, M. (2018). Artificial intelligence (AI) for web accessibility: Is conformance evaluation a way forward? [Paper presentation]. Proceedings of the 15th International Web for All Conference, 1–4, Lyon, France. https://doi.org/10.1145/3192714.3192834
  • Akyılmaz, B. (2022). Yapay Zekâ ve Tüketici Davranışı Alanındaki Yayınların Bibliyometrik Analizi. İşletme Araştırmaları Dergisi,14(1), 947-963.
  • Angeles, R. (2014). Attrıbutes Of Consumers Most Lıkely To Use Goodguıde.Com Sustaınabılıty Informatıon About “Green” Household Products. In L. Mola, A. Carugati, A. Kokkinaki, & N. Pouloudi (Eds.), Proceedings of the 8th Mediterranean Conference on Information Systems (CD-ROM), Verona, Italy, September 03-05. Retrieved from http://aisel.aisnet.org/mcis2014/50
  • Anshu, K., L. Gaur, and G. Singh. 2022. Impact of customer experience on attitude and repurchase intention in online grocery retailing: A moderation mechanism of value Co-creation. Journal of Retailing and Consumer Services 64: 102798.
  • Armağan, V. (2018). Dijital Dönüşüm Sürecinde Akıllı Şehirler ve E-Devlet Platformu. Journal of Communication Theory & Research / Iletisim Kuram ve Arastirma Dergisi, 46, 387–413.
  • Armutcu, B., Ramadani, V., Zeqiri, J. and Dana, L.-P. (2023). The role of social media in consumers’ intentions to buy green food: evidence from Türkiye. British Food Journal, Vol. ahead-of-print No. https://doi.org/10.1108/BFJ-11-2022-0988.
  • Armutcu, B., Zuferi, R., Tan, A. (2023). Green product consumption behaviour, green economic growth and sustainable development: unveiling the main determinants. Journal of Enterprising Communities: People and Places in the Global Economy, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/JEC-05-2023-0074.
  • Asker, J., Fershtman, C. and Pakes, A. (2021). Artificial Intelligence and Pricing: The Impact of Algorithm Design. SSRN Electronic Journal. Working Paper, 28535, 1-52. https://doi.org/10.3386/w28535 Aylak, B. L., Oral, O., & Yazıcı, K. (2021). Yapay Zeka ve Makine Öğrenmesi Tekniklerinin Lojistik Sektöründe Kullanımı. El-Cezeri, 8(1), 74-93. doi: 10.31202/ecjse.776314.
  • Bashar, A., & Rabbani, M. R. (2021). Exploring the Role of Web Personalization in Consumer Green Purchasing Behavior: A Conceptual Framework. In 2021 Third International Sustainability and Resilience Conference: Climate Change (pp. 23-28). Sakheer, Bahrain. https://doi.org/10.1109/IEEECONF53624.2021.9668110
  • Beyari, H., & Garamoun, H. (2022). The Effect of Artificial Intelligence on End-User Online Purchasing Decisions: Toward an Integrated Conceptual Framework. Sustainability, 14(15), 9637. https://doi.org/10.3390/su14159637
  • Bhagat, R., Chauhan, V. and Bhagat, P. (2023), "Investigating the impact of artificial intelligence on consumer’s purchase intention in e-retailing", Foresight, Vol. 25 No. 2, pp. 249-263. https://doi.org/10.1108/FS-10-2021-0218 20.07.2023
  • Cha, N., Cho, H., Lee, S., & Hwang, J. (2019). Effect of AI Recommendation System on the Consumer Preference Structure in e-Commerce: Based on Two types of Preference. 2019 21st International Conference on Advanced Communication Technology (ICACT), 77-80. https://doi.org/10.23919/ICACT.2019.8701967.
  • Cheng, Y., and Jiang, H. (2021). Customer–brand relationship in the era of artificial intelligence: understanding the role of chatbot marketinefforts. The Journal of Product & Brand Management, aheadof-print (ahead-ofprint). Demir, Ç. (2021). Konaklama İşletmelerinin İş Süreçlerinde Yapay Zekâ Teknolojileri ve Akıllı Otel Uygulamaları: Avantajlar ve Dezavantajlar. Journal of Tourism & Gastronomy Studies, 9(1), 203-219.
  • Duarte, D., Ståhl, N. (2019). Machine Learning: A Concise Overview. In: Said, A., Torra, V. (eds) Data Science in Practice. Studies in Big Data, vol 46. Springer, Cham. https://doi.org/10.1007/978-3-319-97556-6_3 Durumaz, Y., & Kılıç, Y. (2023). A Theoretical Approach to Artificial Intelligence in Consumer Behavior. International Business &Economics Studies, 5(2).
  • Ebrahim, R., A. Ghoneim, Z. Irani, and Y. Fan. 2016. A brand preference and repurchase intention model: The role of consumer experience. Journal of Marketing Management 32 (13–14): 1230–1259.
  • Ever, D. & Demircioğlu, E. N. (2022). Yapay Zekâ Teknolojilerinin Kalite Maliyetleri Üzerine Etkisi . Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 31 (1), 59-72 . DOI: 10.35379/cusosbil.1023004
  • Fornell, C., and D.F. Larcker. 1981. Evaluation structural equality models with unobserved variables and measurement error. Journal of Marketing Research 18 (1): 39–50.
  • Frank, B. (2021). Artificial intelligence-enabled environmental sustainability of products: Marketing benefits and their variation by consumer, location, and product types. Journal of Cleaner Production, 285, 125242. https://doi.org/10.1016/j.jclepro.2020.125242.
  • FuiYeng, W., & Yazdanifard, R. (2015). Green marketing: A study of consumers’ buying behavior in relation to green products. Global Journal of Management and Business Research: E Marketing, 15(5), 16-23.
  • Ghosh, S., & Singh, A. (2020). The scope of Artificial Intelligence in mankind: A detailed review. Journal of Physics: Conference Series, 1531(012045). https://doi.org/10.1088/1742-6596/1531/1/012045
  • Godey, B., A. Manthiou, D. Pederzoli, J. Rokka, G. Aiello, R. Donvito, and R. Singh. 2016. Social media marketing efforts of luxury brands: Influence on brand equity and consumer behavior. Journal of Business Research 69 (12): 5833–5841
  • Guha, A., Grewal, D., Kopalle, P., Haenlein, M., Schneider, M., Jung, H., Moustafa, R., Hegde, D., & Hawkins, G. (2021). How artificial intelligence will affect the future of retailing. Journal of Retailing, 97, 28-41.
  • Gülleroğlu, H. D. (2021). Yapay Zekanın Tarih İçindeki Gelişimi ve Eğitimde Kullanılması. Ankara Universitesi Egitim Bilimleri Fakultesi Dergisi. https://doi.org/10.30964/auebfd.916220 Gülsen, I. (2019). İşletmelerde yapay zeka uygulamaları ve faydaları: perakende sektöründe bir derleme. Tüketici ve Tüketim Araştırmaları Dergisi= Journal of Consumer and Consumption Research, 11(2), 407-436.
  • Habil, S., El-Deeb, S., & El-Bassiouny, N. (2023). AI-Based Recommendation Systems: The Ultimate Solution for Market Prediction and Targeting. In The Palgrave Handbook of Interactive Marketing (pp. 683-704). Cham: Springer International Publishing.
  • Hair, J.F., Jr, Sarstedt, M., Ringle, C.M. and Gudergan, S.P. (2017), Advanced _Issues in Partial Least Squares Structural Equation Modeling, Sage Publications, London, ISBN: 9781483377391.
  • İnce, H., İmamoğlu, S. E., & İmamoğlu, S. Z. (2021). Yapay zeka uygulamalarının karar verme üzerine etkileri: Kavramsal birçalışma [The effects of artificial intelligence applications on decision-making: A conceptual study]. International Review ofEconomics and Management, 9(1), 50-63.
  • Jiang, Y., Li, X., Luo, H., Yin, S., & Kaynak, O. (2022). Quo vadis artificial intelligence?. Discover Artificial Intelligence, 2(1), 4. 10.17010/ijom/2013/v43/i12/80511
  • Kamran, H. (2021). Pazarlamada Yapay Zekânın Kullanımı: Yapay Zekâ Pazarlama Araçlarının Tüketici Kabulüne Ilişkin Bir Araştırma (Doctoral dissertation, Bursa Uludag University (Turkey)).
  • Karataş, S. (2021). Yapay zeka ve açık inovasyon etkileşiminin işletmeler üzerine etkileri (Master's thesis, Aydın Adnan Menderes Üniversitesi Sosyal Bilimler Enstitüsü).
  • Khan, S. I. (2022). Impact of artificial intelligence on consumer buying behaviors: Study about the online retail purchase. International Journal of Health Sciences, 8121-8129. https://doi.org/10.53730/ijhs.v6nS2.7025 Kim, J., Kang, S., & Bae, J. (2022). The effects of customer consumption goals on artificial intelligence driven recommendation agents: evidence from Stitch Fix. International Journal of Advertising, 41(6), 997-1016. https://doi.org/10.1080/02650487.2021.1963098
  • Kock, N. (2015), “Common method bias in PLS-SEM: a full collinearity assessment approach”, International Journal of e-Collaboration, Vol. 11 No. 4, pp. 1-10.
  • Lacom, P., & Sagot, S. (2022). A Research Framework for B2B Green Marketing Innovation: the Design of Sustainable Websites. In 2022 IEEE 28th International Conference on Engineering, Technology and Innovation (ICE/ITMC) & 31st International Association For Management of Technology (IAMOT) Joint Conference, pp. 1-9. Nancy, France. doi:10.1109/ICE/ITMC-IAMOT55089.2022.10033239.
  • Lake, B., Ullman, T., Tenenbaum, J., & Gershman, S. (2017). Building machines that learn and think like people. Behavioral and Brain Sciences, 40, E253. doi:10.1017/S0140525X16001837
  • Lee, Y. L., & Huang, F. H. (2011). Recommender system architecture for adaptive green marketing. Expert Systems with Applications, 38(8), 9696-9703.
  • Li, Y., Zhong, Z., Zhang, F., & Zhao, X. (2022). Artificial Intelligence-Based Human-Computer Interaction Technology Applied inConsumer Behavior Analysis and Experiential Education. Frontiers in Psychology, 13, 784311. doi: 10.3389/fpsyg.2022.784311.
  • Malik, R., Jindal, T., & Sharma, A. (2022). Role of Artificial Intelligence in Reshaping Retail. In 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE) (pp. 660-664). Greater Noida, India. doi: 10.1109/ICACITE53722.2022.9823675.
  • Nguyen, T., S. Quach, and P. Thaichon. 2021. The effect of AI quality on customer experience and brand relationship. Journal of Consumer Behavior. https:// doi. org/ 10. 1002/ cb. 1974.
  • Ribeiro De Oliveira, T., Biancardi Rodrigues, B., Moura Da Silva, M., Antonio N. Spinassé, R., Giesen Ludke, G., Ruy Soares Gaudio, M., Iglesias Rocha Gomes, G., Guio Cotini, L., Da Silva Vargens, D., Queiroz Schimidt, M., Varejão Andreão, R., & Mestria, M. (2022). Virtual Reality Solutions Employing Artificial Intelligence Methods: A Systematic Literature Review. ACM Computing Surveys, 55, 1 - 29. https://doi.org/10.1145/3565020
  • Schermelleh-Engel, K., Moosbrugger, H. and Müller, H. (2003), “Evaluating the fit of structural equation models: tests of significance and descriptive goodness-of-fit measures”, Methods of Psychological Research Online, Vol. 8 No. 2, pp. 23-74.
  • Schumacker, R.E. and Lomax, R.G. (1996), A Beginner’s Guide to Structural Equation Modelling, Lawrence Erlbaum Associates, NJ, Publishers.
  • Tiautrakul, J., & Jindakul, J. (2019). The Artificial Intelligence (AI) with the Future of Digital Marketing. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3405184.
  • Yang, X., Li, H., Ni, L., & Li, T. (2021). Application of Artificial Intelligence in Precision Marketing. J. Organ. End User Comput., 33, 209-219. https://doi.org/10.4018/JOEUC.20210701.OA10.
There are 42 citations in total.

Details

Primary Language Turkish
Subjects Behavioural Finance
Journal Section Research Articles
Authors

Mustafa Cesur This is me

Barış Armutcu

Publication Date October 30, 2023
Published in Issue Year 2023 Volume: 3 Issue: 2

Cite

APA Cesur, M., & Armutcu, B. (2023). YAPAY ZEKANIN YEŞİL ÜRÜN SATIN ALMA DAVRANIŞINA ETKİSİ. Kamu Ekonomisi Ve Kamu Mali Yönetimi Dergisi, 3(2), 39-54.