Organizing for- and in- the Digital Age: A Case of the Indian Banking Industry
Abstract
For striving and thriving in the digital age, while firms are rushing to digitally transform their organizing practices as well as offerings, scholars are tasked with revisiting the assumptions of extant theories to unpack the phenomenon of organizing for- and in- the digital age. This thesis focuses on distinct facets of this phenomenon. In particular, I examine the firm strategies and work practices of practitioners in Indian banking and financial organizations (Essays 1, 2), as well as the work practices of academic researchers (Essay 3), as they engage with digital technologies.
The first essay elaborates on and tests the theory of discontinuity in trust in money and the resulting spillover effect, through the degree of association with the source of trust discontinuity, on the financial organizations’ ability to capture value through their digital offerings. Using India’s 2016 demonetization as an exogeneous policy shock, organizational-level digital currency transactions as data sources, and regression discontinuity as empirical strategy, this essay documents an unintended consequence of demonetization—value slipping from government- to private- organizations.
The second essay examines the work practices of data scientists as they strive to perform rationality in practice using a qualitative methodology based on observations, interviews, and archival records at three large Indian banks. The study documents the paradoxical tensions faced by the data scientists as they enact the informing practices of inscribing expertise and prescribing insights for rational decision-making in the organizations, and explicates some mechanisms through which the data scientists alleviate those tensions. This study contributes to the emerging literature on data science as a new profession (Part A), as well as offers recommendations for practitioners (Part B).
The third essay examines the work practices of academic researchers using AI-enabled analytical tools. Based on a systematic methodologic review of articles published in IS and management journals, this study documents the prevalent practices of applying topic modeling––namely, the lack of explicit description, contentious justifications, and polarized, partial, or no validation––that potentially threaten the reliability and validity of academic research. The study proposes a framework to help scholars in mindfully employing algorithmic intelligence in research.