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The role of perceived risk and trust in the effect of artificial intelligence marketing technology on online purchase intention

Yıl 2024, Cilt: 26 Sayı: Özel Sayı, 1 - 16, 21.10.2024
https://doi.org/10.33707/akuiibfd.1403109

Öz

Artificial intelligence marketing technology provides online consumers with a personalized purchasing experience and businesses the opportunity to effectively meet customer needs. This study was conducted to reveal the role of trust in the relevant technology and perceived risk in the effect of artificial intelligence marketing technology experience on online purchasing intention. In this context, the experiential elements of artificial intelligence marketing technology are discussed in three dimensions: accuracy, insight, and interaction. A conceptual model based on the SOR model was developed, including trust, perceived risk, and purchase intention. Then, a quantitative study was conducted with a sample size of 480 people using an online survey method for people with online shopping history. Data collected by snowball sampling method were analyzed by Partial Least Squares Variance Based Structural Equation Modeling (PLS-SEM) using the SmartPLS 4 program. The results showed that the experience of insight and interaction positively affected trust in technology, while the experience of accuracy had no effect on trust. It has been determined that all the experiential elements of artificial intelligence marketing technology have a positive effect on reducing consumers' risk perceptions. Reduced perceived risk due to trust and experiential factors positively and significantly affects online purchase intention. In addition, it was found that trust and perceived risk variables had a serial mediating effect on the relationship between artificial intelligence marketing technology experiential elements and online purchasing intention.

Kaynakça

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  • Aini, Q., Sembiring, I., Setiawan, A., Setiawan, I., & Rahardja, U. (2023). Perceived accuracy and user behavior: Exploring the impact of AI-based air quality detection application (AIKU). Indonesian Journal of Applied Research (IJAR), 4(3), 209-218. https://doi.org/10.30997/ijar.v4i3.356
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Yapay zekâ pazarlama teknolojisinin çevrimiçi satın alma niyetine etkisinde algılanan risk ve güvenin rolü

Yıl 2024, Cilt: 26 Sayı: Özel Sayı, 1 - 16, 21.10.2024
https://doi.org/10.33707/akuiibfd.1403109

Öz

Yapay zekâ pazarlama teknolojisi, çevrimiçi alışveriş yapan tüketicilere kişiselleştirilmiş satın alma deneyimi, işletmelere ise müşteri ihtiyaçlarını etkin bir şekilde karşılama imkânı tanımaktadır. Bu çalışma, yapay zekâ pazarlama teknolojisi deneyiminin, çevrimiçi satın alma niyeti üzerindeki etkisinde ilgili teknolojiye olan güvenin ve algılanan riskin rolünü ortaya koymak amacıyla yapılmıştır. Bu bağlamda yapay zekâ pazarlama teknolojisinin deneyimsel unsurları doğruluk, içgörü ve etkileşim olmak üzere üç boyutta ele alınmış; güven, algılanan risk ve satın alma niyetinin de dahil olduğu SOR modeline dayanan kavramsal bir model geliştirilmiştir. Ardından çevrimiçi alışveriş geçmişi bulunan kişilere çevrimiçi anket yöntemi ile 480 örnek hacimli nicel bir çalışma gerçekleştirilmiştir. Kartopu örnekleme yöntemi ile toplanan veriler, SmartPLS 4 programı kullanılarak Kısmi En Küçük Kareler Varyans Temelli Yapısal Eşitlik Modellemesi (PLS-SEM) ile analiz edilmiştir. Sonuçlar, içgörü ve etkileşim deneyiminin teknolojiye olan güveni pozitif bir şekilde etkilediğini, doğruluk deneyiminin ise güven üzerinde herhangi bir etkisi olmadığını göstermiştir. Tüketicilerin risk algılarının azalmasında yapay zekâ pazarlama teknolojisinin deneyimsel unsurlarının tamamının pozitif bir etkisi olduğu tespit edilmiştir. Güven ve deneyimsel unsurlar dolayısıyla azalan algılanan risk, çevrimiçi satın alma niyetini pozitif ve anlamlı bir şekilde etkilemektedir. Ayıca yapay zekâ pazarlama teknolojisi deneyim unsurları ile çevrimiçi satın alma niyeti arasındaki ilişkide güven ve algılanan risk değişkenlerinin seri aracı etkisi olduğu bulunmuştur.

Kaynakça

  • Abu-Shamaa, R., Abu-Shanab, E., & Khasawneh, R. (2016). Payment methods and purchase intention from online stores: An empirical study in Jordan. International Journal of E-Business Research (IJEBR), 12(2), 31-44. https://doi.org/10.4018/IJEBR.2016040103
  • Aini, Q., Sembiring, I., Setiawan, A., Setiawan, I., & Rahardja, U. (2023). Perceived accuracy and user behavior: Exploring the impact of AI-based air quality detection application (AIKU). Indonesian Journal of Applied Research (IJAR), 4(3), 209-218. https://doi.org/10.30997/ijar.v4i3.356
  • Ajenaghughrure, I. B., da Costa Sousa, S. C., & Lamas, D. (2020). Risk and trust in artificial intelligence technologies: A case study of autonomous vehicles. 13th International Conference on Human System Interaction, Tokyo, Japan. https://doi.org/10.1109/HSI49210.2020.9142686
  • Aksay, B., & Ünal, A. Y. (2016). Yapısal Eşitlik Modellemesi Kapsamında Formatif Ve Reflektif Ölçüm. Cag University Journal of Social Sciences, 13(2), 1-21. https://dergipark.org.tr/en/download/article-file/696237
  • Alam, S. S., Masukujjaman, M., Mohamed Makhbul, Z. K., Helmi Ali, M., Ahmad, I., & Al Mamun, A. (2023). Experience, Trust, eWOM Engagement and Usage Intention of AI Enabled Services in Hospitality and Tourism Industry: Moderating Mediating Analysis. Journal of Quality Assurance in Hospitality & Tourism, 1-29. https://doi.org/10.1080/1528008X.2023.2167762
  • Ameen, N., Tarhini, A., Reppel, A., & Anand, A. (2021). Customer experiences in the age of artificial intelligence. Computers in Human Behavior, 114, 106548. 1-14. https://doi.org/10.1016/j.chb.2020.106548
  • Antony, S., Lin, Z., & Xu, B. (2006). Determinants of escrow service adoption in consumer-to-consumer online auction market: an experimental study. Decision Support Systems, 42(3), 1889-1900. https://doi.org/10.1016/j.dss.2006.04.012
  • Baber, R., & Baber, P. (2022). Influence of social media marketing efforts, e-reputation and destination image on intention to visit among tourists: application of SOR model. Journal of Hospitality and Tourism Insights, 6(5), 2298-2316. https://doi.org/10.1108/JHTI-06-2022-0270
  • Bashir, S., Anwar, S., Awan, Z., Qureshi, T. W., & Memon, A. B. (2018). A holistic understanding of the prospects of financial loss to enhance shopper's trust to search, recommend, speak positive and frequently visit an online shop. Journal of Retailing and Consumer Services, 42, 169-174. https://doi.org/10.1016/j.jretconser.2018.02.004
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  • Lăzăroiu, G., Neguriţă, O., Grecu, I., Grecu, G., & Mitran, P. C. (2020). Consumers’ decision-making process on social commerce platforms: Online trust, perceived risk, and purchase intentions. Frontiers in Psychology, 11, 890, 1-7. https://doi.org/10.3389/fpsyg.2020.00890
  • Ling, K. C., Daud, D. B., Piew, T. H., Keoy, K. H., & Hassan, P. (2011). Perceived risk, perceived technology, online trust for the online purchase intention in Malaysia. International Journal of Business and Management, 6(6), 167-182. https://doi.org/10.5539/ijbm.v6n6p167
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  • Mohseni, S., Jayashree, S., Rezaei, S., Kasim, A., & Okumus, F. (2018). Attracting tourists to travel companies’ websites: the structural relationship between website brand, personal value, shopping experience, perceived risk and purchase intention. Current Issues in Tourism, 21(6), 616-645. https://doi.org/10.1080/13683500.2016.1200539
  • Munikrishnan, U. T., Huang, K., Mamun, A. A., & Hayat, N. (2023). Perceived risk, trust, and online food purchase intention among Malaysians. Business Perspectives and Research, 11(1), 28-43. https://doi.org/10.1177/22785337211043968
  • Naiyi, Y. E. (2004). Dimensions of consumer's perceived risk in online shopping. Journal of Electronic Science and Technology, 2(3), 177-182.
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  • Overgoor, G., Chica, M., Rand, W., & Weishampel, A. (2019). Letting the computers take over: Using AI to solve marketing problems. California Management Review, 61(4), 156-185. https://doi.org/10.1177/0008125619859318
  • Özbek, A., & Sırakaya, Ö. (2022). Türkiye’de kullanılan e-ticaret platformlarının performanslarının karşılaştırılması. Kırıkkale Üniversitesi Sosyal Bilimler Dergisi, 12(2), 469-492. https://dergipark.org.tr/en/download/article-file/2218809
  • Peng, C., & Kim, Y. G. (2014). Application of the stimuli-organism-response (SOR) framework to online shopping behavior. Journal of Internet Commerce, 13(3-4), 159-176. https://doi.org/10.1080/15332861.2014.944437
  • Pires, G., Stanton, J., & Eckford, A. (2004). Influences on the perceived risk of purchasing online. Journal of Consumer Behaviour: An International Research Review, 4(2), 118-131. https://doi.org/10.1002/cb.163
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  • Qalati, S. A., Vela, E. G., Li, W., Dakhan, S. A., Hong Thuy, T. T., & Merani, S. H. (2021). Effects of perceived service quality, website quality, and reputation on purchase intention: The mediating and moderating roles of trust and perceived risk in online shopping. Cogent Business & Management, 8(1), 1-20. https://doi.org/10.1080/23311975.2020.1869363
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  • Rooij, S. V. (2022). Taking it personally? A study on the effects of trust and privacy in the context of AI-enabled personalization. Master Thesis, MSc Marketing, Radboud University.
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Toplam 74 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Yapay Zeka (Diğer), Pazarlama (Diğer)
Bölüm Araştırma Makaleleri
Yazarlar

Ceylan Bozpolat 0000-0002-9672-8308

Erken Görünüm Tarihi 9 Şubat 2024
Yayımlanma Tarihi 21 Ekim 2024
Gönderilme Tarihi 11 Aralık 2023
Kabul Tarihi 5 Şubat 2024
Yayımlandığı Sayı Yıl 2024 Cilt: 26 Sayı: Özel Sayı

Kaynak Göster

APA Bozpolat, C. (2024). Yapay zekâ pazarlama teknolojisinin çevrimiçi satın alma niyetine etkisinde algılanan risk ve güvenin rolü. Afyon Kocatepe Üniversitesi İktisadi Ve İdari Bilimler Fakültesi Dergisi, 26(Özel Sayı), 1-16. https://doi.org/10.33707/akuiibfd.1403109

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