I am an assistant professor of Management Information Systems at the Terry College of Business, University of Georgia. I completed my Ph.D. Information Systems from Kelley School of Business, Indiana University.
My research focuses on the informed application, use, and management of intelligent systems and technologies. I seek to conduct theory-driven examinations of the consequences of unexpected and potentially undesirable reactions, such as maladaptive coping, moral disengagement, and mixed feelings, that emerge from individuals’ interaction with processes enabled by or information generated by such systems.
I have been trained in various quantitative research methods, including experimentation, econometrics, NeuroIS, and machine learning, and have used them in my research. I thus espouse the philosophy of methodological pluralism, i.e., the use of multiple methodologies, to develop a methodology agnostic research agenda.
Prior to Ph.D., I have an engineering degree in electronics and communication and have completed my MBA from the Indian Institute of Technology, New Delhi. I have also served in the consulting industry as a financial advisor.
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Unexpected disruptions can evoke maladaptive tendencies in individuals and lead to questionable or deviant behaviors. Novel technologies, powered by artificial intelligence (AI) algorithms, bear the capability to lower the discernibility and detection of such questionable behaviors (QBs) and can empower individuals to engage in QBs during a major disruption. We situate our examination in the educational context in the United States to examine the role of such novel AI enabled technologies in enabling QBs among strained individuals. Our findings present rise in agency of novel AI-enabled technologies in aiding QBs during major disruptions. We aim to develop discussion on the need and approaches for immediate attention by researchers, educational institutions, platforms, and policy makers to this unintended rise in agency that novel AI-enabled technologies exert over QBs.
Despite the increased adoption of AI based algorithms in recruitment, their opacity has raised several debates, and have motivated governance standards directed toward transparent and accountable use of AI. Our research examines the psychological and behavioural reactions among candidates elicited because of AI based systems. Intended and unintended consequences of AI driven transparency are examined for the candidate and the organization.
AI-enabled technology artefacts, such as conversational agents, have started to pervade our day-to-day lives. Our research examines the use of AI-enabled conversational agents in collaborative teams within organizations to understand how their adoption in such contexts disrupt individual teammates attitudes and behaviors.
Online platforms typically capture users' preferences through various information representations, such as ratings and reviews. our research focuses on how and why the valence, e.g., positive, or negative aspects or connotations, associated with such representations may elicit mixed feelings and influence individuals’ decision-making in online environments. We focus on how coexisting positivity and negativity, i.e., ambivalence, or their absence, i.e., indifference, are formed and resolved into distinct attentional processes and outcomes, relative to extreme valence. We aim to explain how ambivalence and indifference, two distinct mixed feelings may influence individuals’ attentional and behavioral consequences during decision-making in online contexts, and highlight the inability of incumbent representations in accurately capturing mixed feelings expressed in digital contents.
A compelling support for negative consequences of product recalls has led researchers to call for increased attention toward its strategic and operational organizational drivers. In this research, we examine how an organizations’ ability to ambidextrously explore new ideas while simultaneously exploiting existing processes can influence the number of recall events, a prevalent indicator of product quality, as well as organizations’ capacity to initiate recalls faster.