{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T00:47:53Z","timestamp":1782953273930,"version":"3.54.5"},"reference-count":56,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T00:00:00Z","timestamp":1776297600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JTAER"],"abstract":"<jats:p>This study examines the impact of explainable artificial intelligence (XAI) features on user satisfaction and purchase intention in Saudi mobile shopping applications, utilising the stimulus\u2013organism\u2013response (S\u2013O\u2013R) framework. With the increasing reliance on AI-driven decision support in e-commerce, enhancing transparency, fairness, trustworthiness, and interpretability has become crucial for shaping consumer perceptions and behavioural responses. The research employed a quantitative methodology using partial least squares structural equation modelling (PLS-SEM) to examine the relationships among stimulus factors, cognitive and affective states, consumer satisfaction, and purchase intention. In a survey of 597 respondents from Jeddah and Makkah, Saudi Arabia, the findings highlight that fairness and bias detection, trustworthiness, and transparency significantly influence consumers\u2019 cognitive and affective states, which in turn enhance satisfaction and intention to purchase. Consumer satisfaction emerged as a critical mediator, reinforcing the role of positive emotional and cognitive experiences in driving purchase behaviours. However, interpretability showed limited impact, suggesting that consumers may prioritise fairness and trustworthiness over technical clarity of explanations. Theoretically, this study contributes to advancing knowledge on the role of XAI in consumer behaviour by integrating fairness, transparency, and affective responses into the S\u2013O\u2013R paradigm. From a managerial perspective, the results underscore the importance for mobile shopping platforms to design AI systems that foster trust, reduce perceived bias, and ensure transparency, thereby improving consumer engagement and purchase outcomes. By addressing gaps in interpretability and transparency, businesses can strengthen user trust and loyalty, ultimately enhancing competitive advantage in Saudi Arabia\u2019s rapidly growing e-commerce sector.<\/jats:p>","DOI":"10.3390\/jtaer21040120","type":"journal-article","created":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T11:35:42Z","timestamp":1776339342000},"page":"120","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Effect of Explainable AI Features on User Satisfaction and Purchase Intention in Saudi Mobile Shopping Apps"],"prefix":"10.3390","volume":"21","author":[{"given":"Ahmed S. M.","family":"Almamy","sequence":"first","affiliation":[{"name":"College of Administration and Finance, Saudi Electronic University, Riyadh 11673, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2561-0716","authenticated-orcid":false,"given":"Sufyan","family":"Habib","sequence":"additional","affiliation":[{"name":"College of Administration and Finance, Saudi Electronic University, Riyadh 11673, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Layla K.","family":"Nasser","sequence":"additional","affiliation":[{"name":"College of Administration and Finance, Saudi Electronic University, Riyadh 11673, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2170-2074","authenticated-orcid":false,"given":"Nawaf N.","family":"Hamadneh","sequence":"additional","affiliation":[{"name":"Department of Basic Sciences, College of Science and Theoretical Studies, Saudi Electronic University, Riyadh 11673, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,4,16]]},"reference":[{"key":"ref_1","unstructured":"Grand View Research (2024). mHealth Apps Market Size, Share & Trends Analysis Report by App Type, by Platform, by Region, and Segment Forecasts 2024, 2024\u20132030, Grand View Research. Available online: https:\/\/www.grandviewresearch.com\/industry-analysis\/mhealth-apps-market."},{"key":"ref_2","unstructured":"Chaffey, D., and Ellis-Chadwick, F. (2019). Digital Marketing, Pearson UK."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"52138","DOI":"10.1109\/ACCESS.2018.2870052","article-title":"Peeking inside the black-box: A survey on Explainable Artificial Intelligence (XAI)","volume":"6","author":"Adadi","year":"2018","journal-title":"IEEE Access"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"82","DOI":"10.1016\/j.inffus.2019.12.012","article-title":"Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI","volume":"58","author":"Arrieta","year":"2020","journal-title":"Inf. Fusion"},{"key":"ref_5","unstructured":"Mehrabian, A., and Russell, J.A. (1974). An Approach to Environmental Psychology, MIT Press."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Yin, J., and Qiu, X. (2021). AI Technology and Online Purchase Intention: Structural Equation Model Based on Perceived Value. Sustainability, 13.","DOI":"10.3390\/su13105671"},{"key":"ref_7","unstructured":"Erliana, S. (2025). A Systematic Literature Review on Artificial Intelligence Features Driving Purchase Intention on Web Commerce: Insights into Customer Experience and Trust Using Python-Based Analysis. J. Digit. Bus. Innov. Manag., 4."},{"key":"ref_8","unstructured":"Doshi-Velez, F., and Kim, B. (2017). Towards a rigorous science of interpretable machine learning. arXiv."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.artint.2018.07.007","article-title":"Explanation in artificial intelligence: Insights from the social sciences","volume":"267","author":"Miller","year":"2019","journal-title":"Artif. Intell."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1016\/S0148-2963(99)00087-9","article-title":"Atmospheric qualities of online retailing: A conceptual model and implications","volume":"54","author":"Eroglu","year":"2001","journal-title":"J. Bus. Res."},{"key":"ref_11","unstructured":"Muslim, S.N. (2024). Promotion of Accountability in Bangladesh: Civil Service Problems and Strategies, University of Dhaka."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"372","DOI":"10.62345\/jads.2025.14.2.30","article-title":"The Impact of Artificial Intelligence on Consumer Decision-Making in Digital Marketing","volume":"14","author":"Mumtaz","year":"2025","journal-title":"J. Asian Dev. Stud."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Khan, S.M.F.A., and Shehawy, Y.M. (2025). Perceived AI Consumer-Driven Decision Integrity: Assessing Mediating Effect of Cognitive Load and Response Bias. Technologies, 13.","DOI":"10.3390\/technologies13080374"},{"key":"ref_14","unstructured":"Zhang, S. (2025, March 02). The Role of Artificial Intelligence in Enhancing Online Sales and the Customer Experience. Available online: https:\/\/www.theseus.fi\/handle\/10024\/858780."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Khrais, L.T. (2020). Role of artificial intelligence in shaping consumer demand in E-commerce. Future Internet, 12.","DOI":"10.3390\/fi12120226"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1797","DOI":"10.1080\/09669582.2022.2067167","article-title":"The effect of destination source credibility on tourist environmentally responsible behavior: An application of stimulus-organism-response theory","volume":"31","author":"Qiu","year":"2023","journal-title":"J. Sustain. Tour."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1145\/3236386.3241340","article-title":"The mythos of model interpretability: In machine learning, the concept of interpretability is both important and slippery","volume":"16","author":"Lipton","year":"2018","journal-title":"Queue"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Oliver, R.L. (2014). Satisfaction: A Behavioral Perspective on the Consumer: A Behavioral Perspective on the Consumer, Routledge.","DOI":"10.4324\/9781315700892"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1080\/10864415.2003.11044275","article-title":"Consumer acceptance of electronic commerce: Integrating trust and risk with the technology acceptance model","volume":"7","author":"Pavlou","year":"2003","journal-title":"Int. J. Electron. Commer."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Wiratsin, I.-O., and Ragkhitwetsagul, C. (2025). Effectiveness of explainable artificial intelligence (XAI) techniques for improving human trust in machine learning models: A systematic literature review. IEEE Access.","DOI":"10.1109\/ACCESS.2025.3575022"},{"key":"ref_21","first-page":"5625","article-title":"Explainable AI in Personalized Marketing: Implications for Trust and Transparency in the Tech Industry","volume":"270","author":"Mary","year":"2026","journal-title":"Procedia Comput. Sci."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Yoon, S., Shin, H., and Choi, J. (2026). Regulatory Fit in Explainable AI-Based Recommendations: A Comparative Study of Personalized Explanation Strategies on User Experience and Persuasion. Int. J. Hum.\u2013Comput. Interact., 1\u201335.","DOI":"10.1080\/10447318.2025.2602717"},{"key":"ref_23","unstructured":"Donovan, R.J., and Rossiter, J.R. (2017, March 02). Store Atmosphere: An Environmental Psychology. Available online: https:\/\/www.researchgate.net\/publication\/248766608_Store_Atmosphere_An_Environmental_Psychology_Approach."},{"key":"ref_24","first-page":"44","article-title":"DARPA\u2019s explainable artificial intelligence (XAI) program","volume":"40","author":"Gunning","year":"2019","journal-title":"AI Mag."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"184","DOI":"10.1177\/0092070399272005","article-title":"The role of emotions in marketing","volume":"27","author":"Bagozzi","year":"1999","journal-title":"JAMS"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"102551","DOI":"10.1016\/j.ijhcs.2020.102551","article-title":"The effects of explainability and causability on perception, trust, and acceptance: Implications for explainable AI","volume":"146","author":"Shin","year":"2021","journal-title":"Int. J. Hum.\u2013Comput. Stud."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Samek, W., Montavon, G., Vedaldi, A., Hansen, L.K., and M\u00fcller, K.-R. (2019). Explainable AI: Interpreting, Explaining and Visualizing Deep Learning, Springer Nature.","DOI":"10.1007\/978-3-030-28954-6"},{"key":"ref_28","unstructured":"Ramon, Y., Vermeire, T., Toubia, O., Martens, D., and Evgeniou, T. (2021). Understanding consumer preferences for explanations generated by XAI algorithms. arXiv."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1317","DOI":"10.52783\/jes.3539","article-title":"Consumer\u2019s cognitive and affective perceptions of artificial intelligence (AI) in social media: Topic modelling approach","volume":"20","author":"Mohanna","year":"2024","journal-title":"J. Electr. Syst."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Palac\u00ed, F., Salcedo, A., and Topa, G. (2019). Cognitive and affective antecedents of consumers\u2019 satisfaction: A systematic review of two research approaches. Sustainability, 11.","DOI":"10.3390\/su11020431"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Bernardo, E., and Seva, R. (2023). Affective design analysis of explainable artificial intelligence (XAI): A user-centric perspective. Informatics, 10.","DOI":"10.3390\/informatics10010032"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"6978","DOI":"10.1007\/s12144-025-07456-0","article-title":"The impact of AI recommendation\u2019s price and product accuracy on customer satisfaction: SEM-SOR theoretical approach","volume":"44","author":"Shan","year":"2025","journal-title":"Curr. Psychol."},{"key":"ref_33","unstructured":"Domingos, M.I.R.V.V. (2024). Impact of Recommender Agents Used in Online Retail on Customer Satisfaction and Purchase Intention. [Ph.D. Thesis, Universidade NOVA de Lisboa]."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"618","DOI":"10.1108\/ITP-08-2014-0172","article-title":"The mediation of cognitive attitude for online shopping","volume":"29","author":"Chang","year":"2016","journal-title":"Inf. Technol. People"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Abdul, A., Vermeulen, J., Wang, D., Lim, B.Y., and Kankanhalli, M. (2018, January 21\u201326). Trends and trajectories for explainable, accountable and intelligible systems: An hci research agenda. Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, Montreal, QC, Canada.","DOI":"10.1145\/3173574.3174156"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Ribeiro, M.T., Singh, S., and Guestrin, C. (2016, January 13\u201317). \u201cWhy should i trust you?\u201d Explaining the predictions of any classifier. Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Francisco, CA, USA.","DOI":"10.1145\/2939672.2939778"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"e12532","DOI":"10.1016\/j.heliyon.2022.e12532","article-title":"Factors affecting adoption and use of M-commerce services among the customers in Saudi Arabia","volume":"8","author":"Wasiq","year":"2022","journal-title":"Heliyon"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Jacovi, A., Marasovi\u0107, A., Miller, T., and Goldberg, Y. (2021, January 3\u201310). Formalizing trust in artificial intelligence: Prerequisites, causes and goals of human trust in AI. Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, Online.","DOI":"10.1145\/3442188.3445923"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Hair, J.F., Hult, G.T.M., Ringle, C.M., Sarstedt, M., Danks, N.P., and Ray, S. (2021). Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R: A Workbook, Springer.","DOI":"10.1007\/978-3-030-80519-7"},{"key":"ref_40","first-page":"7","article-title":"Structural equation modeling and regression: Guidelines for research practice","volume":"4","author":"Gefen","year":"2000","journal-title":"Commun. Assoc. Inf. Syst."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1177\/002224378101800104","article-title":"Evaluating structural equation models with unobservable variables and measurement error","volume":"18","author":"Fornell","year":"1981","journal-title":"J. Mark. Res."},{"key":"ref_42","unstructured":"Kline, R.B. (2023). Principles and Practice of Structural Equation Modeling, Guilford Publications. [5th ed.]."},{"key":"ref_43","first-page":"185","article-title":"Knowledge management: An organizational capabilities perspective","volume":"18","author":"Gold","year":"2001","journal-title":"JIMS"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1007\/s11747-014-0403-8","article-title":"A new criterion for assessing discriminant validity in variance-based structural equation modeling","volume":"43","author":"Henseler","year":"2015","journal-title":"J. Acad. Mark. Sci."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/10705519909540118","article-title":"Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives","volume":"6","author":"Hu","year":"1999","journal-title":"Struct. Equ. Model. Multidiscip. J."},{"key":"ref_46","first-page":"33","article-title":"Effects of reputation and website quality on online consumers\u2019 emotion, perceived risk and purchase intention: Based on the stimulus-organism-response model","volume":"7","author":"Kim","year":"2013","journal-title":"J. Res. Interact. Mark."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Sarstedt, M., Ringle, C.M., and Hair, J.F. (2021). Partial least squares structural equation modeling. Handbook of Market Research, Springer.","DOI":"10.1007\/978-3-319-57413-4_15"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"13","DOI":"10.2307\/25148715","article-title":"The Personalization Privacy Paradox: An Empirical Evaluation of Information Transparency and the Willingness to be Profiled Online for Personalization1","volume":"30","author":"Awad","year":"2006","journal-title":"MIS Q."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Kizilcec, R.F. (2016, January 7\u201312). How much information? Effects of transparency on trust in an algorithmic interface. Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems, San Jose, CA, USA.","DOI":"10.1145\/2858036.2858402"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"103473","DOI":"10.1016\/j.artint.2021.103473","article-title":"What do we want from Explainable Artificial Intelligence (XAI)?\u2014A stakeholder perspective on XAI and a conceptual model guiding interdisciplinary XAI research","volume":"296","author":"Langer","year":"2021","journal-title":"Artif. Intell."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"61","DOI":"10.4018\/JDM.2019010104","article-title":"Artificial intelligence, machine learning, automation, robotics, future of work and future of humanity: A review and research agenda","volume":"30","author":"Wang","year":"2019","journal-title":"J. Database Manag. (JDM)"},{"key":"ref_52","first-page":"65","article-title":"Investigating the impact of social media advertising features on customer purchase intention","volume":"42","author":"Alalwan","year":"2018","journal-title":"Int. J. Inf. Manag."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"534","DOI":"10.1016\/j.jbusres.2020.08.051","article-title":"Home sharing in marketing and tourism at a tipping point: What do we know, how do we know, and where should we be heading?","volume":"122","author":"Lim","year":"2021","journal-title":"J. Bus. Res."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"1679","DOI":"10.1108\/EJM-10-2017-0707","article-title":"User experience in personalized online shopping: A fuzzy-set analysis","volume":"52","author":"Pappas","year":"2018","journal-title":"Eur. J. Mark."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"750","DOI":"10.1002\/mar.21767","article-title":"Metaverse marketing: How the metaverse will shape the future of consumer research and practice","volume":"40","author":"Dwivedi","year":"2023","journal-title":"Psychol. Mark."},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Bhatt, U., Xiang, A., Sharma, S., Weller, A., Taly, A., Jia, Y., Ghosh, J., Puri, R., Moura, J.M., and Eckersley, P. (2020, January 27\u201330). Explainable machine learning in deployment. Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency, Barcelona, Spain.","DOI":"10.1145\/3351095.3375624"}],"container-title":["Journal of Theoretical and Applied Electronic Commerce Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/0718-1876\/21\/4\/120\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T12:09:37Z","timestamp":1776341377000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/0718-1876\/21\/4\/120"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,16]]},"references-count":56,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2026,4]]}},"alternative-id":["jtaer21040120"],"URL":"https:\/\/doi.org\/10.3390\/jtaer21040120","relation":{},"ISSN":["0718-1876"],"issn-type":[{"value":"0718-1876","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,4,16]]}}}