Alboqami, H. (2023). Trust me, I'm an influencer! -Causal recipes for customer trust in artificial intelligence influencers in the retail industry. Journal of Retailing and Consumer Services, 72, 103242, https://doi.org/10.1016/j.jretconser.2022.103242
Anica-Popa, I., Anica-Popa, L., Rădulescu, C., & Vrîncianu, M. (2021). The integration of artificial intelligence in retail: benefits, challenges and a dedicated conceptual framework. Amfiteatru Economic, 23(56), 120-136.
doi:10.24818/EA/2021/56/120
Aw, E. C. X., Tan, G. W. H., Cham, T. H., Raman, R., & Ooi, K. B. (2022). Alexa, what's on my shopping list? Transforming customer experience with digital voice assistants. Technological Forecasting and Social Change, 180, 121711. https://doi.org/10.1016/j.techfore.2022.121711
Bae, J., Lee, S., Kim, S., & Lee, Y. H. (2019). An automatic logistics system using artificial intelligence. International Journal of Recent Technology and Engineering, 8(2), 2277-3878.
https://DOI:10.35940/ijrte.B1183.0782S419
Bottani, E., Centobelli, P., Gallo, M., Kaviani, M. A., Jain, V., & Murino, T. (2019). Modelling wholesale distribution operations: an artificial intelligence framework. Industrial Management & Data Systems, 119(4), 698-718. https://doi.org/10.1108/IMDS-04-2018-0164
Brau, R. I., Sanders, N. R., Aloysius, J., & Williams, D. (2024). Utilizing people, analytics, and AI for decision making in the digitalized retail supply chain. Journal of Business Logistics, 45(1), e12355. https://doi.org/10.1111/jbl.12355
Bienhaus, F., & Haddud, A. (2018). Procurement 4.0: factors influencing the digitisation of procurement and supply chains. Business Process Management Journal, 24(4), 965-984. https://doi.org/10.1108/BPMJ-06-2017-0139
Burakhanova, A., Baizhaxynova, G., Duisebayeva, A., Davletova, M., & Nurakhova, B. (2023). Using Artificial Intelligence for Retail Value Chain. International Journal of Service Science, Management, Engineering, and Technology (IJSSMET), 14(1), 1-21. DOI: 10.4018/IJSSMET.330018
Calvo, A. V., Franco, A. D., & Frasquet, M. (2023). The role of artificial intelligence in improving the omnichannel customer experience. International Journal of Retail & Distribution Management, 51(9/10), 1174-1194. https://doi.org/10.1108/IJRDM-12-2022-0493
Cao, L. (2021). Artificial intelligence in retail: applications and value creation logics. International Journal of Retail & Distribution Management, 49(7), 958-976. https://doi.org/10.1108/IJRDM-09-2020-0350
Chavoshi, Seyyed Kazem; Khamoui, Farshid; Shokrullah Tabar, His Holiness (1402). Factors affecting the acceptance of Islamic banking by customers with Aras approach. Human resource management research, 12(2), 139-163. [In persian] http://dorl.net/dor/20.1001.1.22286977.1402.13.2.5.4
Chen, Y., Biswas, M. I., & Talukder, M. S. (2023). The role of artificial intelligence in effective business operations during COVID-19. International Journal of Emerging Markets, 18(12), 6368-6387. https://doi.org/10.1108/IJOEM-11-2021-1666
Chien, C. F., Lin, Y. S., & Lin, S. K. (2020). Deep reinforcement learning for selecting demand forecast models to empower Industry 3.5 and an empirical study for a semiconductor component distributor. International Journal of Production Research, 58(9), 2784-2804. https://doi.org/10.1080/00207543.2020.1733125
Chinchanachokchai, S., Thontirawong, P., & Chinchanachokchai, P. (2021). A tale of two recommender systems: The moderating role of consumer expertise on artificial intelligence based product recommendations. Journal of Retailing and Consumer Services, 61, 102528. https://doi.org/10.1016/j.jretconser.2021.102528
Chung, S. H. (2021). Applications of smart technologies in logistics and transport: A review. Transportation Research Part E: Logistics and Transportation Review, 153, 102455. https://doi.org/10.1016/j.tre.2021.102455
Čirjevskis, A. (2022). Exploring Coupled Open Innovation for Digital Servitization in Grocery Retail: From Digital Dynamic Capabilities Perspective. Journal of Risk and Financial Management, 15(9), 411. oduct recommendations. Journal of Retailing and Consumer Services, 61,102528. https://doi.org/10.3390/jrfm15090411
De Bellis, E., & Johar, G. V. (2020). Autonomous shopping systems: Identifying and overcoming barriers to consumer adoption. Journal of Retailing, 96(1), 74-87. https://doi.org/10.1016/j.jretai.2019.12.004
Ellefsen, A. P. T., Oleśków-Szłapka, J., Pawłowski, G., & Toboła, A. (2019). Striving for excellence in AI implementation: AI maturity model framework and preliminary research results. LogForum, 15(3). http://dx.doi.org/10.17270/J.LOG.2019.354
Flavián, C., Akdim, K., & Casaló, L. V. (2023). Effects of voice assistant recommendations on consumer behavior. Psychology & Marketing, 40(2), 328-346. https://doi.org/10.1002/mar.21765
García-Reyes, H., Avilés-González, J., & Avilés-Sacoto, S. V. (2022). A model to become a supply chain 4.0 based on a digital maturity perspective. Procedia Computer Science, 200, 1058-1067. https://doi.org/10.1016/j.procs.2022.01.305
Gately, C. (2017). Vekia: pioneering machine learning in retail supply chain. Small Enterprise Research, 24(3), 326-332. https://doi.org/10.1080/13215906.2017.1396243
Giroux, M., Kim, J., Lee, J. C., & Park, J. (2022). Artificial intelligence and declined guilt: Retailing morality comparison between human and AI. Journal of Business Ethics, 178(4), 1027-1041. https://doi.org/10.1007/s10551-022-05056-7
Har, L. L., Rashid, U. K., Te Chuan, L., Sen, S. C., & Xia, L. Y. (2022). Revolution of retail industry: from perspective of retail 1.0 to 4.0. Procedia Computer Science, 200, 1615-1625. https://doi.org/10.1016/j.procs.2022.01.362
Hasija, A., & Esper, T. L. (2022). In artificial intelligence (AI) we trust: A qualitative investigation of AI technology acceptance. Journal of Business Logistics, 43(3), 388-412. https://doi.org/10.1111/jbl.12301
Hassel, A., & Özkiziltan, D. (2023). Governing the work-related risks of AI: implications for the German government and trade unions. Transfer: European Review of Labour and Research, 29(1),71-86. https://doi.org/10.1177/10242589221147228
Hejazi, M., Alrusaini, O., & Beyari, H. (2022). The effect of artificial intelligence and payment flexibility on operational performance: The enabling role of supply chain risk management. Uncertain Supply Chain Management, 10(4), 1117-1130. http://dx.doi.org/10.5267/j.uscm.2022.8.015
Hendriksen, C. (2023). AI for Supply Chain Management: Disruptive Innovation or Innovative Disruption?. Journal of Supply Chain Management. https://doi.org/10.1111/jscm.12304
Hosseini Dahshiri, Seyyed Jalaluddin; Aghaei, Mojtabi (2019). Identification and prioritization of human resources risks using the integrated method of Suara and Aras Seghi. Journal of Human Resource Studies, 10(1), 53-78. [In persian] https://doi.org/10.22034/jhrs.2020.105969
Hu, S. K., Lu, M. T., & Tzeng, G. H. (2015). Improving mobile commerce adoption using a new hybrid fuzzy MADM model. International Journal of Fuzzy Systems, 17, 399-413. https://doi.org/10.1007/s40815-015-0054-z
Jackson, I., Jesus Saenz, M., & Ivanov, D. (2024). From natural language to simulations: applying AI to automate simulation modelling of logistics systems. International Journal of Production Research, 62(4), 1434-1457. https://doi.org/10.1080/00207543.2023.2276811
Jagtap, S., Bader, F., Garcia-Garcia, G., Trollman, H., Fadiji, T., & Salonitis, K. (2020). Food logistics 4.0: Opportunities and challenges. Logistics, 5(1), 2. https://doi.org/10.3390/logistics5010002
Jan, I. U., Ji, S., & Kim, C. (2023). What (de) motivates customers to use AI-powered conversational agents for shopping? The extended behavioral reasoning perspective. Journal of Retailing and Consumer Services, 75, 103440. https://doi.org/10.1016/j.jretconser.2023.103440
Karabašević, D. M., Maksimović, M. V., Stanujkić, D. M., Jocić, G. B., & Rajčević, D. P. (2018). Selection of software testing method by using ARAS method. Tehnika, 73(5), 724-729. https://doi.org/10.5937/tehnika1805724K
Kaur, J., Arora, V., & Bali, S. (2020). Influence of technological advances and change in marketing strategies using analytics in retail industry. International journal of system assurance engineering and management, 11(5), 953-961. https://doi.org/10.1007/s13198-020-01023-5
Kayani, Mehrdad; Andalib Ardakani, Daud; Zare Ahmad Abadi, Habib, Mir Fakhr al-Dini, Seyyed Haider (1402). An analysis of the enablers effective on the implementation of the circular economy and Industry 4.0 in the supply chain of glass factories. Journal of Industrial Studies, 70 (21), 1-43. [In persian] https://doi.org/10.48308/jimp.13.4.9
Klaus, P., & Zaichkowsky, J. L. (2022). The convenience of shopping via voice AI: Introducing AIDM. Journal of Retailing and Consumer Services, 65, 102490. https://doi.org/10.1016/j.jretconser.2021.102490
Kokina, J., & Davenport, T. H. (2017). The emergence of artificial intelligence: How automation is changing auditing. Journal of emerging technologies in accounting, 14(1),115-122. https://doi.org/10.2308/jeta-51730
Kumar, A., Gupta, N., & Bapat, G. (2023). Who is making the decisions? How retail managers can use the power of ChatGPT. Journal of Business Strategy. https://doi.org/10.1108/JBS-04-2023-0067
Lee, Y. I., & Trim, P. R. (2022). Enhancing marketing provision through increased online safety that imbues consumer confidence: coupling AI and ML with the AIDA Model. Big Data and Cognitive Computing, 6(3), 78. https://doi.org/10.3390/bdcc6030078
Leoni, L., Ardolino, M., El Baz, J., Gueli, G., & Bacchetti, A. (2022). The mediating role of knowledge management processes in the effective use of artificial intelligence in manufacturing firms. International Journal of Operations & Production Management, 42(13), 411-437. https://doi.org/10.1108/IJOPM-05-2022-0282
Li, J., Wu, L., Qi, J., Zhang, Y., Wu, Z., & Hu, S. (2023). Determinants affecting consumer trust in communication with AI chatbots: the moderating effect of privacy concerns. Journal of Organizational and End User Computing (JOEUC), 35(1), 1-24. DOI: 10.4018/JOEUC.328089
Li, M., & Li, T. (2022). AI automation and retailer regret in supply chains. Production and Operations Management, 31(1), 83-97. https://doi.org/10.1111/poms.13498
Li, M., & Wang, R. (2023). Chatbots in e-commerce: The effect of chatbot language style on customers’ continuance usage intention and attitude toward brand. Journal of Retailing and Consumer Services, 71, 103209. https://doi.org/10.1016/j.jretconser.2022.103209
Martins, F. D. C., Simon, A. T., & Campos, R. S. D. (2020). Supply chain 4.0 challenges. Gestão & Produção, 27, e5427. https://www.scielo.br/j/gp/a/tfYDLqyzChwgqDbZ6McTW3p/?lang=en
Merhi, M. I., & Harfouche, A. (2023). Enablers of artificial intelligence adoption and implementation in production systems. International Journal of Production Research, 1-15. https://doi.org/10.1080/00207543.2023.2167014
Mithas, S., Chen, Z. L., Saldanha, T. J., & De Oliveira Silveira, A. (2022). How will artificial intelligence and Industry 4.0 emerging technologies transform operations management?. Production and Operations Management, 31(12), 4475-4487. https://doi.org/10.1111/poms.13864
Mohammadian, Ayoub; Heydari Dahoui, Jalil; Vashqani, Fatemeh and Rafiei, Mahmoud (1401). Identifying and prioritizing the challenges and applications of big data in the retail industry using multi-criteria decision-making methods. Information Technology Management, 8(1), 225-244. [In persian] https://doi.org/ 10.22034/aimj.2022.170983
Nguyen, H. M., & Khoa, B. T. (2019). The relationship between the perceived mental benefits, online trust, and personal information disclosure in online shopping. The Journal of Asian Finance, Economics and Business (JAFEB), 6(4), 261-270. doi:10.13106/jafeb.2019.vol6.no4.261
Nowzari, Hamed; Sadeghi, Mohammad Ibrahim; The heroism of Nahar, Javid and Najafi, Seyyed Ismail (1400). Quantitative analysis of the challenge of implementing a digital supply chain based on Internet of Things technology (Supply Chain 4.0). Scientific Journal of Standard and Quality Management, 11(3), 63-94. [In persian] https://doi.org/10.22034/jsqm.2022.314683.1380
Núñez-Merino, M., Maqueira-Marín, J. M., Moyano-Fuentes, J., & Castaño-Moraga, C. A. (2022). Industry 4.0 and supply chain. A Systematic Science Mapping analysis. Technological Forecasting and Social Change, 181, 121788. https://doi.org/10.1016/j.techfore.2022.121788
Olan, F., Liu, S., Suklan, J., Jayawickrama, U., & Arakpogun, E. O. (2022). The role of Artificial Intelligence networks in sustainable supply chain finance for food and drink industry. International Journal of Production Research, 60(14), 4418-4433. https://doi.org/10.1080/00207543.2021.1915510
Padilla-Vega, R., Sanchez-Rivero, C., & Ojeda-Castro, A. (2023). Navigating the business landscape: challenges and opportunities of implementing artificial intelligence in cybersecurity governance. Issues in Information Systems, 24(4). https://doi.org/10.48009/4_iis_2023_125
Pantano, E., & Scarpi, D. (2022). I, robot, you, consumer: Measuring artificial intelligence types and their effect on consumers emotions in service. Journal of Service Research, 25(4), 583-600. https://doi.org/10.1177/10946705221103538.
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.
Quarteroni, S. (2018). Natural language processing for industry: ELCA’s experience. Informatik-Spektrum, 41(2), 105-112. https://doi.org/10.1007/s00287-018-1094-1.
Rana, J., Jain, R., & Santosh, K. C. (2023). Automation and AI-enabled customer journey: a bibliometric analysis. Vision, 09722629221149854. https://doi.org/10.1177/09722629221149854
Rathore, B., Gupta, R., Biswas, B., Srivastava, A., & Gupta, S. (2022). Identification and analysis of adoption barriers of disruptive technologies in the logistics industry. The International Journal of Logistics Management, 33(5), 136-169. DOI 10.1108/IJLM-07-2021-0352
Reyes, P. M., Visich, J. K., & Jaska, P. (2020). Managing the dynamics of new technologies in the global supply chain. IEEE Engineering Management Review, 48(1), 156-162. https://doi.org/10.1109/EMR.2020.2968889
Schultz, C. D., & Paetz, F. (2023). Trust in Digital Voice Assistants: A Fundamental Determinant for Companies’ and Customers’ Engagement in Voice Commerce. Marketing, Zeitschrift Fur Forschung Und Praxis, 45(2), 4–21. DOI:10.15358/0344-1369-2023-2-4
Servos, N., Liu, X., Teucke, M., & Freitag, M. (2019). Travel time prediction in a multimodal freight transport relation using machine learning algorithms. Logistics, 4(1), 1. https://doi.org/10.3390/logistics4010001
Sharifpour, H., Ghaseminezhad, Y., Hashemi-Tabatabaei, M., & Amiri, M. (2022). Investigating cause-and-effect relationships between supply chain 4.0 technologies. Engineering Management in Production and Services, 14(4), 22-46. Sharma, S., Islam, N., Singh, G., & Dhir, A. (2022). Why do retail customers adopt artificial intelligence (Ai) based autonomous decision-making systems?. IEEE Transactions on Engineering Management. https://doi.org/10.2478/emj-2022-0029
Song, C. S., & Kim, Y. K. (2022). The role of the human-robot interaction in consumers’ acceptance of humanoid retail service robots. Journal of Business Research, 146, 489-503. https://doi.org/10.1016/j.jbusres.2022.03.087
Song, C. S., Kim, Y. K., Jo, B. W., & Park, S. H. (2022). Trust in humanoid robots in footwear stores: A large-N crisp-set qualitative comparative analysis (csQCA) model. Journal of Business Research, 152, 251-264. https://doi.org/10.1016/j.jbusres.2022.07.012
Song, M., Xing, X., Duan, Y., Cohen, J., & Mou, J. (2022). Will artificial intelligence replace human customer service? The impact of communication quality and privacy risks on adoption intention. Journal of Retailing and Consumer Services, 66, 102900. https://doi.org/10.1016/j.jretconser.2021.102900
Sung, E. C., Bae, S., Han, D. I. D., & Kwon, O. (2021). Consumer engagement via interactive artificial intelligence and mixed reality. International journal of information management, 60, 102382. https://doi.org/10.1016/j.ijinfomgt.2021.102382
Tang, C. S., & Veelenturf, L. P. (2019). The strategic role of logistics in the industry 4.0 era. Transportation Research Part E: Logistics and Transportation Review, 129, 1-11. https://doi.org/10.1016/j.tre.2019.06.004
Tang, Z. (2022). Application of de-noising automatic coding method in freight volume prediction under intelligent logistics. International Journal of Grid and Utility Computing, 13(1), 21-29. https://doi.org/10.1504/IJGUC.2022.121425
Toorajipour, R., Sohrabpour, V., Nazarpour, A., Oghazi, P., & Fischl, M. (2021). Artificial intelligence in supply chain management: A systematic literature review. Journal of Business Research, 122, 502-517. https://doi.org/10.1016/j.jbusres.2020.09.009
Tran, A. D., Pallant, J. I., & Johnson, L. W. (2021). Exploring the impact of chatbots on consumer sentiment and expectations in retail. Journal of Retailing and Consumer Services, 63, 102718. https://doi.org/10.1016/j.jretconser.2021.102718
Woods, R., Doherty, O., & Stephens, S. (2022). Technology driven change in the retail sector: Implications for higher education. Industry and Higher Education, 36(2), 128-137. https://doi.org/10.1177/09504222211009180
van Esch, P., Cui, Y., & Jain, S. P. (2021). Self‐efficacy and callousness in consumer judgments of AI‐enabled checkouts. Psychology & Marketing, 38(7), 1081-1100. https://doi.org/10.1002/mar.21494
Veres, P. (2023). Increasing the efficiency of warehouse analysis using artificial intelligence. Acta Logistica (AL), 10(3). https://doi.org/10.22306/al.v10i3.415
Villegas-Ch, W., Amores-Falconi, R., & Coronel-Silva, E. (2023). Design Proposal for a Virtual Shopping Assistant for People with Vision Problems Applying Artificial Intelligence Techniques. Big Data and Cognitive Computing, 7(2), 96. https://doi.org/10.3390/bdcc7020096
Zhu, Y., Zhang, J., Wu, J., & Liu, Y. (2022). AI is better when I'm sure: The influence of certainty of needs on consumers' acceptance of AI chatbots. Journal of Business Research, 150, 642-652. https://doi.org/10.1016/j.jbusres.2022.06.044
Zwanka, R. J., & Zondag, M. M. (2023). Tired or Inspired: A Conceptual Model for Using Regenerative Artificial Intelligence to Create Context, User, and Time-Aware Individualized Shopping Guidance. Journal of International Consumer Marketing, 1-12. http://dx.doi.org/10.1080/08961530.2023.2266897