Actual Usage Behavior Toward Generative AI-Based Fashion Shopping Platforms (GAIFSP) : Perspectives from DeLone and McLean’s Information Systems Success Model
DOI:
https://doi.org/10.17010/ijom/2025/v55/i1/174686Keywords:
GAIFSP
, DeLone and McLean IS success model, habit, actual use.Paper Submission Date
, June 15, 2024, Paper sent back for Revision, October 15, Paper Acceptance Date, October 25, Paper Published Online, January 15, 2025Abstract
Purpose : This study focused on actual use behavior towards Generative AI-based Fashion Shopping Platforms (GAIFSP), intention to use, and factors influencing it by adopting the DeLone and McLean information systems success model as the theoretical foundation. The specific research objectives were to investigate the relationship of system quality, information quality, and service quality with users’ intention to know and actual use of the systems.
Methodology : The research used a descriptive research design and a purposive sampling technique. A total of 440 respondents responded to the questionnaire.
Findings : People who were systematic and had high standards for the system design with effectiveness and accuracy in the information received were likely to have strong engagement with the platform. Unlike other types of innovative products, though, the habit of GAIFSP did not moderate the relation between intention and actual use; this could be attributed to the fact that GAIFSP was a new product.
Implications : Building on the theory, the study further included the introduction of the DeLone and McLean model to understand generative AI. It also has managerial implications for platform design, user assistance, and strategies aimed at user retention.
Originality : It provided a deeper understanding of the role of generative AI in achieving sustainable approaches.
Downloads
Published
How to Cite
Issue
Section
References
Alanadoly, A. B., Sidhu, S. K., & Richards-Carpenter, N. (2024). AI landscape in fashion: Insights on transforming design, supply chains, marketing, and consumer experiences. In P. Raj, A. Rocha, P. K. Dutta, M. Fiorini, & C. Prakash (eds.), Illustrating digital innovations towards intelligent fashion (Vol. 18, pp. 417–439). Springer. https://doi.org/10.1007/978-3-031-71052-0_16
Aldholay, A. H., Isaac, O., Abdullah, Z., & Ramayah, T. (2018). The role of transformational leadership as a mediating variable in DeLone and McLean information system success model: The context of online learning usage in Yemen. Telematics and Informatics, 35(5), 1421–1437. https://doi.org/10.1016/j.tele.2018.03.012
Andreoni, M., Lunardi, W. T., Lawton, G., & Thakkar, S. (2024). Enhancing autonomous system security and resilience with generative AI: A comprehensive survey. IEEE Access, 12, 109470–109493. https://doi.org/10.1109/ACCESS.2024.3439363
Babu, M. M., Akter, S., Rahman, M., Billah, M. M., & Hack-Polay, D. (2024). The role of artificial intelligence in shaping the future of agile fashion industry. Production Planning & Control, 35(15), 2084–2098. https://doi.org/10.1080/09537287.2022.2060858
Çelik, K., & Ayaz, A. (2022). Validation of the Delone and McLean information systems success model: A study on student information system. Education and Information Technologies, 27(4), 4709–4727. https://doi.org/10.1007/s10639-021-10798-4
Cenfetelli, R. T. (2004). Inhibitors and enablers as dual factor concepts in technology usage. Journal of the Association for Information Systems, 5(11), 472–492. https://doi.org/10.17705/1jais.00059
Chakraborty, D. (2018). Impact of celebrity endorsed advertisements on rural consumers' purchase intention towards mobile SIM cards: A study conducted in West Bengal. Indian Journal of Marketing, 48(10), 52–63. https://doi.org/10.17010/ijom/2018/v48/i10/132335
Chakraborty, D. (2021). Factors influencing passengers' purchase intention towards app-cab services in metro cities of India: A study on smartphone users. Indian Journal of Marketing, 51(1), 41–54. https://doi.org/10.17010/10.17010/ijom/2021/v51/i1/156933
Chakraborty, D., & Altekar, S. (2021). What drives people to use grocery apps? The moderating & mediating role of customer involvement and trust. Indian Journal of Marketing, 51(11), 23–37. https://doi.org/10.17010/ijom/2021/v51/i11/166734
Chakraborty, D., Bhatnagar, S. B., Biswas, W., & Khatua, A. K. (2022). What drives people to adopt grocery apps? The moderating role of household size. Business Perspectives and Research. https://doi.org/10.1177/22785337221091640
Chakraborty, D., & Dash, G. (2022). 'The new normal' and the strategies of marketers to attract consumers. Indian Journal of Marketing, 52(1), 58–62. https://doi.org/10.17010/ijom/2022/v52/i1/167652
Chau, P. Y., & Hu, P. J. (2002). Examining a model of information technology acceptance by individual professionals: An exploratory study. Journal of Management Information Systems, 18(4), 191–229. https://doi.org/10.1080/07421222.2002.11045699
Chen, J., Liu, Z., Huang, X., Wu, C., Liu, Q., Jiang, G., Pu, Y., Lei, Y., Chen, X., Wang, X., Zheng, K., Lian, D., & Chen, E. (2024). When large language models meet personalization: Perspectives of challenges and opportunities. World Wide Web, 27(4), Article no. 42. https://doi.org/10.1007/s11280-024-01276-1
Choi, W., Jang, S., Kim, H. Y., Lee, Y., Lee, S.-G., Lee, H., & Park, S. (2023). Developing an AI-based automated fashion design system: Reflecting the work process of fashion designers. Fashion and Textiles, 10(1), Article ID 39. https://doi.org/10.1186/s40691-023-00360-w
Chopdar, P. K., Lytras, M. D., & Visvizi, A. (2023). Exploring factors influencing bicycle-sharing adoption in India: A UTAUT 2 based mixed-method approach. International Journal of Emerging Markets, 18(11), 5109–5134. https://doi.org/10.1108/IJOEM-06-2021-0862
Dash, G., Akmal, S., & Chakraborty, D. (2022). A study on adoption of e-health services: Developing an integrated framework in a multinational context. Indian Journal of Marketing, 52(5), 25–40. https://doi.org/10.17010/ijom/2022/v52/i5/169415
Dash, G., Akmal, S., & Chakraborty, D. (2023). A study on adoption of mobile learning apps (MLA): Development of an integrated framework in a multinational context. Indian Journal of Marketing, 53(5), 8–24. https://doi.org/10.17010/ijom/2023/v53/i5/172724
Davies, J., Sharifi, H., Lyons, A., Forster, R., & Elsayed, O. K. (2024). Non-fungible tokens: The missing ingredient for sustainable supply chains in the metaverse age? Transportation Research Part E: Logistics and Transportation Review, 182, Article ID 103412. https://doi.org/10.1016/j.tre.2024.103412
Deng, H., Jiang, J., Yu, Z., Ouyang, J., & Wu, D. (2024). CrossGAI: A cross-device generative AI framework for collaborative fashion design. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 8(1), Article No. 35, 1–27. https://doi.org/10.1145/3643542
Fang, J., Zhao, Z., Wen, C., & Wang, R. (2017). Design and performance attributes driving mobile travel application engagement. International Journal of Information Management, 37(4), 269–283. https://doi.org/10.1016/j.ijinfomgt.2017.03.003
Gorla, N., Somers, T. M., & Wong, B. (2010). Organizational impact of system quality, information quality, and service quality. The Journal of Strategic Information Systems, 19(3), 207–228. https://doi.org/10.1016/j.jsis.2010.05.001
Gorry, G. A., & Westbrook, R. A. (2011). Once more, with feeling: Empathy and technology in customer care. Business Horizons, 54(2), 125–134. https://doi.org/10.1016/j.bushor.2010.10.003
Gupta, A. S., & Mukherjee, J. (2024). Framework for adoption of generative AI for information search of retail products and services. International Journal of Retail & Distribution Management, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IJRDM-05-2024-0203
Gursoy, D., Chi, O. H., Lu, L., & Nunkoo, R. (2019). Consumers acceptance of artificially intelligent (AI) device use in service delivery. International Journal of Information Management, 49, 157–169. https://doi.org/10.1016/j.ijinfomgt.2019.03.008
Huang, P., Lurie, N. H., & Mitra, S. (2009). Searching for experience on the web: An empirical examination of consumer behavior for search and experience goods. Journal of Marketing, 73(2), 55–69. https://doi.org/10.1509/jmkg.73.2.55
Jasperson, J., Carter, P. E., & Zmud, R. W. (2005). A comprehensive conceptualization of post-adoptive behaviors associated with information technology enabled work systems. MIS Quarterly, 29(3), 525–557. https://doi.org/10.2307/25148694
Kim, Y. H., Kim, D. J., & Wachter, K. (2013). A study of mobile user engagement (MoEN): Engagement motivations, perceived value, satisfaction, and continued engagement intention. Decision Support Systems, 56, 361–370. https://doi.org/10.1016/j.dss.2013.07.002
Kumar, N., & Singh, V. (2022). Shopping with voice assistant: Understanding consumer intention and the mediating role of trust. Indian Journal of Marketing, 52(8), 51–65. https://doi.org/10.17010/ijom/2022/v52/i8/171224
Lee, J.-C., & Chen, X. (2022). Exploring users' adoption intentions in the evolution of artificial intelligence mobile banking applications: The intelligent and anthropomorphic perspectives. International Journal of Bank Marketing, 40(4), 631–658. https://doi.org/10.1108/IJBM-08-2021-0394
Ma, W., Li, R. Y., Manta, O., & Alzuman, A. (2024). Balancing wellbeing and responsibility: CSR's role in mitigating burnout in hospitality under UN-SDGs. Sustainability, 16(8), 3374. https://doi.org/10.3390/su16083374
MartÃnez-López, F. J., Li, Y., Liu, H., & Feng, C. (2020). Do safe buy buttons and integrated path-to-purchase on social platforms improve users' shopping-related responses? Electronic Commerce Research and Applications, 39, Article ID 100913. https://doi.org/10.1016/j.elerap.2019.100913
McCormick, H., Cartwright, J., Perry, P., Barnes, L., Lynch, S., & Ball, G. (2014). Fashion retailing – past, present and future. Textile Progress, 46(3), 227–321. https://doi.org/10.1080/00405167.2014.973247
Murthy, D. N., & Kumar, B. V. (2015). Internet of things (IoT): Is IoT a disruptive technology or a disruptive business model? Indian Journal of Marketing, 45(8), 18–27. https://doi.org/10.17010/ijom/2015/v45/i8/79915
Naylor, R. W., Lamberton, C. P., & West, P. M. (2012). Beyond the “like†button: The impact of mere virtual presence on brand evaluations and purchase intentions in social media settings. Journal of Marketing, 76(6), 105–120. https://doi.org/10.1509/jm.11.0105
Negash, S., Ryan, T., & Igbaria, M. (2003). Quality and effectiveness in web-based customer support systems. Information & Management, 40(8), 757–768. https://doi.org/10.1016/S0378-7206(02)00101-5
Nicolaou, A. I., Ibrahim, M., & van Heck, E. (2013). Information quality, trust, and risk perceptions in electronic data exchanges. Decision Support Systems, 54(2), 986–996. https://doi.org/10.1016/j.dss.2012.10.024
Pahari, S., Polisetty, A., Sharma, S., Jha, R., & Chakraborty, D. (2023). Adoption of AI in the banking industry: A case study on Indian banks. Indian Journal of Marketing, 53(3), 26–41. https://doi.org/10.17010/ijom/2023/v53/i3/172654
Pan, J., Ding, S., Wu, D., Yang, S., & Yang, J. (2019). Exploring behavioural intentions toward smart healthcare services among medical practitioners: A technology transfer perspective. International Journal of Production Research, 57(18), 5801–5820. https://doi.org/10.1080/00207543.2018.1550272
Pappas, A., Fumagalli, E., Rouziou, M., & Bolander, W. (2023). More than machines: The role of the future retail salesperson in enhancing the customer experience. Journal of Retailing, 99(4), 518–531. https://doi.org/10.1016/j.jretai.2023.10.004
Petter, S., DeLone, W., & McLean, E. (2008). Measuring information systems success: Models, dimensions, measures, and interrelationships. European Journal of Information Systems, 17(3), 236–263. https://doi.org/10.1057/ejis.2008.15
Raut, S., Chandel, A., & Mittal, S. (2025). Enhancing marketing and brand communication with AI-driven content creation. In M. Tunio (ed.), AI, corporate social responsibility, and marketing in modern organizations (pp. 139–172). IGI Global Scientific Publishing. https://doi.org/10.4018/979-8-3373-0219-5.ch008
Sharma, S. K., & Sharma, M. (2019). Examining the role of trust and quality dimensions in the actual usage of mobile banking services: An empirical investigation. International Journal of Information Management, 44, 65–75. https://doi.org/10.1016/j.ijinfomgt.2018.09.013
Sharma, S., Sharma, R., Kayal, G., & Kaur, J. (2022). Digital banking: A meta-analysis approach. Indian Journal of Marketing, 52(5), 41–68. https://doi.org/10.17010/ijom/2022/v52/i5/169416
Sinclair, J., & Aho, A.-M. (2018). Experts on super innovators: Understanding staff adoption of learning management systems. Higher Education Research & Development, 37(1), 158–172. https://doi.org/10.1080/07294360.2017.1342609
Singu, H. B., & Chakraborty, D. (2022). I have the bank in my pocket: Theoretical evidence and perspectives. Journal of Public Affairs, 22(3), Article No. e2568. https://doi.org/10.1002/pa.2568
Venkatesh, V., Davis, F. D., & Zhu, Y. (2023). Competing roles of intention and habit in predicting behavior: A comprehensive literature review, synthesis, and longitudinal field study. International Journal of Information Management, 71, Article ID 102644. https://doi.org/10.1016/j.ijinfomgt.2023.102644
Xi, N., & Hamari, J. (2021). Shopping in virtual reality: A literature review and future agenda. Journal of Business Research, 134, 37–58. https://doi.org/10.1016/j.jbusres.2021.04.075
Yan, H., Zhang, H., Liu, L., Zhou, D., Xu, X., Zhang, Z., & Yan, S. (2022). Toward intelligent design: An AI-based fashion designer using generative adversarial networks aided by sketch and rendering generators. IEEE Transactions on Multimedia, 25, 2323–2338. https://doi.org/10.1109/TMM.2022.3146010
Yan, M., Filieri, R., & Gorton, M. (2021). Continuance intention of online technologies: A systematic literature review. International Journal of Information Management, 58, Article ID 102315. https://doi.org/10.1016/j.ijinfomgt.2021.102315
