I am a doctoral student in the Organizational Behavior and Strategy area at the Gies School of Business at the University of Illinois, Urbana-Champaign. I completed my Masters in Economics and BE in Computer Science from BITS Pilani. My research interests include understanding and enhancing the cultural life of organizations, studying technological discontinuities, and the governing role of institutions. My work employs a variety of computational methods, including natural language processing, and machine learning.
Below is a list of my current projects.
Organizational Culture and Wrongdoing - A view through the Glassdoor
(with Prof. Geoffrey Love, Prof. Donald Sull, & Prof. Matthew Kraatz)
Organizational culture is frequently identified as an important antecedent to wrongdoing by scholars as well as the popular media. However, organizational culture is not a monolithic entity, but is in fact, an amalgam of different elements (of shared expectations, assumptions, beliefs, and values) that influence actions. In this study, we investigate which elements of culture are most predictive of organizational wrongdoing. First, we use NLP to identify cultural norms and values from reviews posted on Glassdoor by employees of large public US-based firms. Then, we employ ML methods (combining XGboost and SHAP values) to identify cultural features that are the most salient predictors of deliberate financial wrongdoing. We find that organizations excessively favoring a culture of high workload, lacking the requisite resources (both human and capital), or having an unfriendly work environment, are more likely to engage in unethical behavior. Our paper aims to enhance our collective understanding of culture and wrongdoing literature in two main ways. First, we shed light on the values and norms that are essential in predicting fraudulent behavior, a link that, in our view, scholars have studied only limitedly. Secondly, by using ML techniques to understand cultural antecedents to wrongdoing, we aim to contribute to theory-building by algorithm-supported induction.
An Eye for AI - Insights into the Governance of Artificial Intelligence and Vision for Future Research (Published)
(with Prof. Ruth Aguilera)
In this 60th anniversary of Business and Society essay, we review existing management research on artificial intelligence (AI), particularly its governance, and offer a framework to examine how governance can support sustainable AI-adoption by businesses and society. The governance of AI-powered technologies is essential and yet complex because of AI’s significant impact, where AI is redefining the legal environment, changing industry practices, creating emerging organizational forms, and giving rise to new labor and leadership responsibilities. We discuss the AI challenges studied across various research themes, highlight AI governance's role in mitigating such challenges, and propose a governance framework for bridging the management literature with this emerging yet rapidly growing research topic. We conclude by offering suggestions for future empirical research and theory-building on the governance of AI. This review contributes to the literature by elucidating how businesses and their governance may harness AI’s power without creating or amplifying societal inequalities.