Research

Conference Proceedings

• Rahman, Md Jabir, and Huigang Liang. "Beyond Ratings: Exploring Familial Influence on Sharing Economy Success," Thirtieth Americas Conference on Information Systems, Salt Lake City, 2024

• Rahman, Md Jabir, Robert Greve, and Faruk Ahmed. "Faceless Appeal: Rethinking Visibility in Sharing," Thirtieth Americas Conference on Information Systems, Salt Lake City, 2024

• Rahman, Md Jabir, Samira Rahman, and Md Juber Rahman. "Decoding Trust: LLM in Provider Topic Modeling," Thirtieth Americas Conference on Information Systems, Salt Lake City, 2024

• Rahman, Md Jabir and Huigang Liang. "Personality and Trust Dynamics in Peer-To-Peer Business," 26th Proceedings of the Southern Association for Information Systems Conference, Gulf Shores, Alabama, USA March 15-16th, 2024

• Rahman, Md Jabir and Faruq Ahmed. "Comparing Generative AI and Humans in Image Feature Extraction," 26th Proceedings of the Southern Association for Information Systems Conference, Gulf Shores, Alabama, USA March 15-16th, 2024

• Rahman, Samira, Md Jabir Rahman, and Loknath Sai Ambati. "Beyond Names: Gender Bias in Peer-To-Peer Markets," 26th Proceedings of the Southern Association for Information Systems Conference, Gulf Shores, Alabama, USA March 15-16th, 2024

• Rahman, Samira, and Md Jabir Rahman. "LLMs for Gender Prediction: A Comparative Study," 26th Proceedings of the Southern Association for Information Systems Conference, Gulf Shores, Alabama, USA March 15-16th, 2024

• Ahmed, Faruk, Md Jabir Rahman and Robert Greve. "Consumers’ Trust Dynamics: Edited Photo Effects," 26th Proceedings of the Southern Association for Information Systems Conference, Gulf Shores, Alabama, USA March 15-16th, 2024

• Rahman, Samira, Md Jabir Rahman, and Sri Beldona. "Warm Words, Unequal Opportunities!," Thirtieth Americas Conference on Information Systems, Salt Lake City, 2024

• Sammangi, Harsha, Md Jabir Rahman, Sandeep Lingam, and Loknath Sai Ambati. "Enhancing Real-Time Streaming Content Security: An Adaptive QIM Watermarking Approach for Dynamic Tampering Detection," Thirtieth Americas Conference on Information Systems, Salt Lake City, 2024

• Rahman, Md Jabir; Liang, Huigang; and Xue, Yajiong, "AI Aversion: A Task Dependent Multigroup Analysis" (2023). PACIS 2023 Proceedings. 86. https://aisel.aisnet.org/pacis2023/86

• Rahman, Md Jabir, and Huigang Liang (2021). Why Do People Avoid AI? A quadruple Perspective, Memphis Data – A Data Science Conference, The University of Memphis, 2021

Works In Progress

• Liang, Huigang; Rahman, Md Jabir; Xue, Yajiong. Title omitted to maintain anonymity, Manuscript submitted for publication into MisQ.

• Rahman, Md Jabir, and Huigang Liang. Title omitted to maintain anonymity, Manuscript submitted for publication into Decision Support Systems.

• Rahman, Md Jabir, "How Your Profile Photo Shapes Your Business", Results available, manuscript under development, targeted at the Journal of Management Information Systems: JMIS

• Rahman, Md Jabir, "You Reap What You Sow: How Personal Bios Shape Demand and Reputation in Peer-to-Peer Markets", targeted at the Tourism Management

• Rahman, Md Jabir, Huigang, Liang.  “Behind the Clicks: Exploring the Dynamics of Fake News Engagement”. targeted at the MIS Quarterly

• Rahman, Md Jabir, and Huigang Liang. Trust and Distrust in AI: A Task Level Perspective on Users’ AI Aversion, Targeted at Information Systems Research

• Rahman, Md Jabir, and Huigang Liang. A Deeper Look into User’s Perceived Autonomy: A Randomized Controlled Experiment to Investigate AI Aversion, targeted at the MIS Quarterly

Dissertation

Artificial Intelligence Aversion: Two Essays 

In this dissertation, we comprehensively examine the phenomenon of AI aversion - a negative emotional response accompanied by cognitions and behaviors toward Artificial Intelligence (AI). We aim to understand the factors that contribute to this phenomenon thoroughly. To accomplish this, we have developed a framework that considers all possible dimensions influencing users' reactions to AI applications, including the user, AI, task, and environment. We have drawn upon a wealth of existing theories and carefully synthesized relevant literature to inform our research. In addition, we have collected data through a series of rigorous randomized experiments and used CB-SEM analysis to validate our research model through empirical evidence. We have also subjected our model to further testing in various contexts to assess potential changes in the hypothesized relationships and identify the presence of potential mediators. Our findings demonstrate that several factors can negatively impact users' perceptions of AI, leading to aversion and that the nature of the task may influence these relationships.