Document Type : Research Paper

Authors

1 Assistant Professor, Department of Business Administration, Payame Noor University, Tehran, Iran y.shirmohammadi@pnu.ac.ir

2 MSc in Master of Business Management, Payame Noor University

Abstract

Using artificial intelligence technology, smart stores transfer a lot of customer and product information (big data) including facial recognition, smart sensors, smart shelves, automatic payment and interactive displays at high speed based on the fifth generation (5G) internet. Since the spread of the corona virus has changed the way of life and business today, that's why marketers have used new strategies based on artificial intelligence to advance. This research analyzed the hedonic factors of customers' purchases based on the Hedonic Information Systems Acceptance Model (HISAM). The sampling method of this research was simple random and its number was 404 people. The measurement tool in this research is a questionnaire. Statistical analysis was done using structural equation method and using SPSS and Amos software. To determine the causal relationship between the variables using the structural equation model method and significance levels in order to test the hypotheses, a p_value smaller than 0. 05 was considered. The results of this research showed that the perceived ease of use, perceived benefit and perceived enjoyment have a positive and significant effect on the purchase intention due to the technology readiness of customers. Also, the results of the research indicated that the mediating variable of technology readiness was effective from optimism, innovation, discomfort and insecurity, and perceived ease of use, perceived enjoyment, and perceived benefit had a positive effect on customers' purchase intentions from smart stores in the era of Corona.

Keywords

بخشنده، قاسم، قشقایی، سمیرا. (1399). مدل عوامل موثر بر تمایل بانوان به خرید پوشاک از فروشگاه‌های آنلاین. مطالعات مدیریت کسب و کار هوشمند، 8 (31)، ۲۰۴- ۱۸۵.
رحیمی اقدم، صمد، فضل زاده، علیرضا، ابراهیمی اقدم، نوشین. (1399). تاثیر استراتژی‌های تضمین بر قصد خرید اینترنتی با میانجی‌گری اعتماد در فروشگاه‌های آنلاین. مطالعات مدیریت کسب و کار هوشمند، 8 (32)، ۱۴۶-۱۱۷. http://dx. doi. org/10. 22054/IMS. 2020. 45974. 1580
محمدی، فاطمه، یزدانی، حمید رضا، ادیب زاده، مرضیه. (1399). فراتحلیل مطالعات خرید آنلاین، بررسی و ترکیب نتایج تحقیقات انجام شده در زمینه خرید آنلاین. مطالعات مدیریت کسب و کار هوشمند,8 (33)، ۱۴۲-۱۰۱.
Adapa, S. , Fazal-e-Hasan, S. M. , Makam, S. B. , Azeem, M. M. , Mortimer, G. (2020). Examining the antecedents and consequences of perceived shopping value through smart retail technology. Journal of Retailing and Consumer Services. 52-10190. https://doi. org/10. 1016/j. jretconser.
Budak, M. C. & Onar, S. C. (2021). Analyzing Online Shopping Behaviors via a New Data-Driven Hesitant Fuzzy Approach. International Journal of Computational Intelligence Systems. 1875-6883. https://doi. org/10. 2991/ijcis. d. 210205. 003.
Caffaro, F. , Cremasco, M. M. , Roccato, M. , Cavallo, E. (2020). Drivers of farmers’ intention to adopt technological innovations in Italy: The role of information sources, perceived usefulness, and perceived ease of use. Journal of Rural Studies. 264271. https://doi. org/10. 1016/j. jrurstud. 2020. 04. 028.
Cardenas, J. C. , Lanas, J. G. , Galarza, C. R. (2021). Drivers of technology readiness and motivations for consumption in explaining the tendency of consumers to use technology-based services. Journal of Business Research. 122-217225. https://doi. org/10. 1016/j. jbusres. 2020. 08. 054.
Chang, Y. , Chen, J. (2021). What motivates customers to shop in smart shops? The impacts of smart technology and technology readiness. Journal of Retailing and Consumer Services. 58-102325. https://doi. org/10. 1016/j. jretconser. 2020. 102325.
Chen, C. , White, C. , Hsieh, Y. (2020). The role of consumer participation readiness in automated parcel station usage intentions. Journal of Retailing and Consumer Services. 54-102063. https://doi. org/10. 1016/j. jretconser. 2020. 102063.
Davis, F. D. (1989). Perceived Usefulness, Perceived Ease to Use, and User Acceptance of Information Technology. Management Information Systems Research Center, University of Minnesota. 319-340. https://doi. org/10. 2307/249008.
Davis, F. D. , Bagozzi, R. P. , Warshaw, P. R. (1992). Extrinsic and Intrinsic Motivation to Use Computers in the Workplace. Journal of Applied Social Psychology. 1111-1132. https://doi. org/10. 1111/j. 1559-1816. 1992. tb00945.
Do, H. , Shih, W. , Ha, Q. (2020). Effects of mobile augmented reality apps on impulse buying behavior: An investigation in the tourism field. Heliyon. 6-e04667. https://doi. org/101016/j. heliyon. 2020. e04667.
Fazal-e-Hasan, S. M. , Amrollahi, A. , Mortimer, G. , Adapa, S. , Makam, S. B. (2021). Computer in Human Behavior. 117-106622. https://doi. org/10. 1016/j. chb. 2020. 106622.
Fu (Fred), J. R. , Lu, I. W. , Chen, J. H. F. , Farn, C. K. (2020). the willingness to accept suggestions and recommendations from social media members before making purchase decisions. International Journal of Information Management. 54-102189. https://doi. org/10. 1016/j. ijinfomgt. 2020. 102189.
Gong, T. , Wang, C. Y. , Lee, K. (2021). Effects of characteristics of in-store retail technology on customer citizenship behavior. Journal of Retailing and Consumer Services. 102488. https://doi. org/10. 1016/j. jretconser. 2021. 102488.
Holdack, E. , Stoyanov, K. L. , Fromme, H. F. (2020). The role of perceived enjoyment and perceived in formativeness in assessing the acceptance of AR wearables. Journal of Retailing and Consumer Services. 102259. https://doi. org/10. 1016/j. jretconser. 2020. 102259.
 Izuagbe, R. , Ibrahim, N. A. , Ogiamien, L. O. , Olawoyin, O. R. , Nwokeoma, N. M. , Ilo, P. I. , Osayande, O. (2019). Effect of perceived ease of use on librarians' e-skills: Basis for library technology acceptance intention. Library and Information Science Research. 100969. https://doi. org/10. 1016/j. lisr. 2019. 100969.
Jabeen, G. , Ahmad, M. , Zhang, Q. (2021). Perceived critical factors affecting consumers’ intention to purchase renewable generation technologies: Rural-urban heterogeneity. Energy. 218-119494. https://doi. org/10. 1016/j. energy. 2020. 119494.
Jain, N. , K. , Gajjar, H. , Shah, B. J. (2020). Electronic logistics service quality and repurchase intention in e-tailing: Catalytic role of shopping satisfaction, payment options, gender and returning experience. Journal of Retailing and Consumer Services. 102360. https://doi. org/10. 1016/j. jretconser. 2020. 102360.
Li, X. , Zhao, X. , Xu, W. , Pu, W. (2020). Measuring ease of use of mobile applications in e-commerce retailing from the perspective of consumer online shopping behavior patterns. Journal of Retailing and Consumer Services 55-102093. https://doi. org/10. 1016/j. jretconser. 2020. 102093.
Ling, H. C. , Chen, H. R. , Ho, K. K. W. , Hsiao, K. L. (2020). Exploring the factors affecting customers’ intention to purchase a smart speaker. Journal of Retailing and Consumer Services. 102331. https://doi. org/10. 1016/j. jretconser. 2020. 102331.
Mustak, M. , Salminen, J. , Ple, L. , Wirtz, J. (2020). Artificial intelligence in marketing: Topic modeling, scientometric analysis, and research agenda. Journal of Business Research. 389404. https://doi. org/10. 1016/j. jbusres. 2020. 10. 044.
Nayal, P. , Pandey, N. , Paul, J. (2021). Examining m-coupon redemption intention among consumers: A moderated moderated-mediation and conditional model. International Journal of Information Management. 57-102288. https://doi. org/10. 1016/j. ijinfomgt. 2020. 102288.
Pal, D. & Vanijja, V. (2020). Perceived Usability Evaluation of Microsoft Teams as an Online Learning Platform During COVID-19 using System Usability Scale and Technology Acceptance Model in India. Children and Youth Services Review. 105535. https://doi. org/10. 1016/j. childyouth. 2020. 105535.
Pantano, E. & Pizzi, G. (2020). Forecasting artificial intelligence on online customer assistance: Evidence from chatbot patents analysis. Journal of Retailing and Consumer Services. 55-102096. https://doi. org/10. 1016/j. jretconser. 2020. 102096.
Parasuraman, A. & Colby, C. L. (2014). An Updated and Streamlined Technology Readiness Index: TRI 2. 0. 2014. Journal of Service Research. https://doi. org/10. 1177/1094670514539730.
Pillai, R. , Sivathanu, B. , Dwivedi, Y. K. (2020). Shopping intention at AI-powered automated retail stores (AIPARS). Journal of Retailing and Consumer Services. 57-102207. https://doi. org/10. 1016/j. jretconser. 2020. 102207.
Plumed, F. M. , Gomez, E. , Orallo, J. H. (2021). Futures of artificial intelligence through technology readiness levels. Telematics and Informatics. 58-101525. https://doi. org/10. 1016/j. tele. 2020. 101525.
Qasem, Z. (2021). The effect of positive TRI traits on centennials adoption of try-on technology in the context of E-fashion retailing. International Journal of Information Management. 56-102254. https://doi. org/10. 1016/j. ijinfomgt. 2020. 102254.
Ratan, R. , Earle, K. , Rosenthal, S. , Chen, V. H. H. , Andrew, G. , Goggin, G. , Stevens, H. , Li, B. , Lee, K. M. (2021). The (digital) medium of mobility is the message: Examining the influence of e-scooter mobile app perceptions on e-scooter use intent. Computers in Human Behavior Reports. 3-100076. https://doi. org/10. 1016/j. chbr. 2021. 100076.
Roy, S. K. , Balaji, M. S. , Nguyen, B. (2020). Consumer-computer interaction and in-store smart technology (IST) in the retail industry: the role of motivation, opportunity, and ability. Journal of Marketing Management. 1472-1376. https://www. tandfonline. com/loi/rjmm20.
Shankar, V. , Douglass, T. Hennessey, J. , Kalyanam, K. , Setia, P. , Golmohammadi, A. , Tirunillai, S. , Bull, J. S. , Waddoups, R. (2020). How Technology is Changing Retail. Journal of Retailing. https://doi. org/10. 1016/j. jretai. 2020. 10. 006.
Sicari, S. , Rizzardi, A. , Porisini, A. C. (2020). 5G in the internet of things era: An overview on security and privacy. Journal of Computer Networks. 179-107345. https://doi. org/10. 1016/j. comnet. 2020. 107345.
Singh, S. , Singh, N. , Kalinic, Z. , Francisco J. , Cabanillas, L. (2020). Assessing determinants influencing continued use of live streaming services:an extended perceived value theory of streaming addiction. Expert Systems with Applications. 114211. https://doi. org/10. 1016/j. eswa. 2020. 11424.
Todisco, L. , Tomo, A. , Canonico, P. , Mangia, G. , Sarnacchiaro, P. (2020). Exploring social media usage in the public sector: Public employees' perceptions of ICT's usefulness in delivering value added. Socio-Economic Planning Sciences. 102404. https://doi. org/10. 1016/j. seps. 2020. 10085.
Van der Heijden, H. (2004). User Acceptance of Hedonic Information Systems. MIS Quarterly. Vol. 28. No. 4. 695-704. https://doi. org/10. 2307/25148660.
Van Esch, P. , Cui, Y. , Jain, S. P. (2020). Stimulating or Intimidating: The Effect of AI-Enabled In-Store Communication on Consumer Patronage Likelihood. Journal of Advertizing. https://doi. org/10. 1080/00913367. 2020. 1832939.
Venkatesh, V. , Morris, M. G. , Davis, G. B. , Davis, F. D. (2003). User Acceptance of Information Technology: Toward A Unified View. MIS Quarterly. 425-478. https://doi. org/10. 2307/30036540.
Yan, L. Y. , Tan, G. W. H, Loh, X. M. , Hew, J. J. , Ooi, K. B. (2021). QR code and mobile payment: The disruptive forces in retail. Journal of Retailing and Consumer Services. 58-102300. https://doi. org/10. 1016/j. jretconser. 2020. 102300.
You, Y. , He, Y. , Chen, Q. , Hu, M. (2021). The interplay between brand relationship norms and ease of sharing on electronic word-of-mouth and willingness to pay. Information & Management. 58-103410. https://doi. org/10. 1016/j. im. 2020. 103410.
References [In Persian]
Bakhshandeh, G. , Ghashghayi, S. (2020). TheModel of theInfluential factors on the Intention of Women toPurchaseClothing from Online Stores. BI Management Studies. 8 (31), 185-204. http://dx. doi. org/10. 22054/IMS. 2019. 45327. 1568 [In Persian]
Rahimiaghdam, S. , Fazlzadeh, A. , Ebrahimiaghdam, N. (2020). The Impact of Assurance Strategies on Online Purchase Intonation by Mediating Role of Trust in online Stores. BI Management Studies. 8 (32), 117-146. http://dx. doi. org/10. 22054/IMS. 2020. 45974. 1580. [In Persian]
Mohammadi, F. , Yazdani, H. , Adibzadeh, M. (2020). A Meta-Analysis of Online Shopping Studies: Review and Synthesis Online sShopping Studies Results. BI Management Studies. 8 (33), 101-142. http://dx. doi. org/10. 22054/IMS. 2020. 47090. 1606 [In Persian]