Biography

Saby Mitra is the John H. Harland Dean of Emory University's Goizueta Business School. An accomplished academic leader and scholar in information systems, his research and teaching focus on the strategic use of technology to drive organizational performance and innovation.

Prior to joining Emory in August 2026, Mitra served as dean of the University of Florida's Warrington College of Business for six years, where he led the college's undergraduate, graduate, and doctoral programs while overseeing strategic growth, faculty excellence, philanthropy, and operations. During his tenure, Warrington strengthened its national reputation through expanded AI and analytics education, new graduate programs, significant investments in student career and professional development, and the launch of new program locations in Miami and Jacksonville. Under his leadership, the college also reinforced its position as a national leader in online business education and experienced substantial growth in research productivity and financial strength.

Before joining the University of Florida, Mitra spent 27 years at the Georgia Institute of Technology's Scheller College of Business, where he held the Thomas R. Williams–Wells Fargo Professorship in Information Technology Management. He served in several senior leadership roles, including Senior Associate Dean of Faculty and Research and Senior Associate Dean of Programs, providing leadership for faculty affairs, doctoral education, academic and corporate programs, and strategic initiatives. His work helped establish innovative interdisciplinary degree programs and strengthened collaborations across business, engineering, computing, and medicine.

An internationally recognized scholar, Mitra's research examines the strategic application of technology to create business value. His areas of expertise include business analytics, information security management, online consumer behavior, IT governance, digital platforms, innovation, and artificial intelligence. His research has been published in many of the field's leading journals, including Management Science, Information Systems Research, MIS Quarterly, Journal of Marketing, and Production and Operations Management. He has also served as senior editor and associate editor for Information Systems Research.

Education

  • PhD in Management Science (Information Systems)
    University of Iowa
  • Bachelor of Technology in Mechanical Engineering
    Indian Institute of Technology

Aligning With Metrics: Differential Impact of IT and Organizational Metrics on Cognitive Coordination in Top Management Teams

Production and Operations Management
Siamionava K., Mitra S., Westerman G.
September 1, 2024
Achieving cognitive coordination in cross-functional teams is a perennial challenge in organizations. It is especially challenging in the context of information systems, where strategic alignment remains a top concern of leaders despite decades of research on the topic. In this study, we develop and empirically validate a theoretical model that explores the role of communicating about performance metrics in fostering cognitive coordination between the Chief Information Officer (CIO) and top management team (TMT). Building on a theoretical lens of transactive memory systems, we hypothesize how the use of unit-specific metrics of information technology (IT) performance and collective metrics of organizational performance can differentially influence mutual trust and shared understanding in the CIO–TMT relationship. Through a survey of 268 CIOs, an experiment with 106 participants using a novel IT leadership game, and an algorithmic analysis of 3200+ articles in a trade publication, we find that communications using narrowly focused IT unit metrics improve mutual trust between the CIO and the TMT, while communications using broader organizational metrics (along with mutual trust) increase shared understanding of IT's role in improving organizational performance. Our multimethod study adds an important new facet to the rich literature on IT strategic alignment as well as the use of performance metrics in operations management. We discuss its implications for both theory and practice in improving cognitive coordination among the CIOs and TMT. Our model and findings are also relevant to other cross-functional teams where specialized individuals must collaborate to achieve collective goals.

Swayed by the reviews: Disentangling the effects of average ratings and individual reviews in online word-of-mouth

Production and Operations Management
Z Lei, D Yin, S Mitra, H Zhang
February 14, 2022
Online word‐of‐mouth studies generally assume that a product's average rating is the primary force shaping consumers’ purchase decisions and driving sales. Similarly, practitioners place more emphasis on average ratings by displaying them at more salient places than individual reviews. In contrast, emerging evidence suggests that individual reviews also affect the decision‐making of those consumers who consult both kinds of information. However, because average ratings and individual reviews are often correlated and confounded empirically, little research has attempted to disentangle their effects. To address this empirical challenge, we construct trade‐off situations in which the average ratings and top‐ranked reviews of different product options do not align with each other. We then investigate consumers’ preferences that can indirectly reveal the relative impact of average ratings versus top reviews. Through an archival analysis of a panel dataset and two laboratory experiments, we find consistent evidence for a swaying effect of individual reviews and reveal their textual content as a likely reason. These findings challenge the commonly accepted assumption of average ratings being the primary driver of consumers’ purchase decisions and suggest that consumers may not be as rational as previous literature assumed. In addition, this paper is the first to disentangle the effects of average ratings and individual reviews on consumer decision‐making and explore a possible reason for the swaying effect of individual reviews. Our paper illustrates the importance of information accessibility in consumers’ purchase decisions, and our findings offer valuable insights for product manufacturers, online retailers, and review platforms.

Capturing value in platform business models that rely on user-generated content

Organization Science
H Subramanian, S Mitra, S Ransbotham
January 13, 2021
Business models increasingly depend on inputs from outside traditional organizational boundaries. For example, platforms that generate revenue from advertising, subscription, or referral fees often rely on user-generated content (UGC). But there is considerable uncertainty on how UGC creates value—and who benefits from it—because voluntary user contributions cannot be mandated or contracted or its quality assured through service-level agreements. In fact, high valuations of these platform firms have generated significant interest, debate, and even euphoria among investors and entrepreneurs. Network effects underlie these high valuations; the value of participation for an individual user increases exponentially as more users actively participate. Thus, many platform strategies initially focus on generating usage with the expectation of profits later. This premise is fraught with uncertainty because high current usage may not translate into future profits when switching costs are low. We argue that the type of user-generated content affects switching costs for the user and, thus, affects the value a platform can capture. Using data about the valuation, traffic, and other parameters from several sources, empirical results indicate greater value uncertainty in platforms with user-generated content than in platforms based on firm-generated content. Platform firms are unable to capture the entire value from network effects, but firms with interaction content can better capture value from network effects through higher switching costs than firms with user-contributed content. Thus, we clarify how switching costs enable value for the platform from network effects and UGC in the absence of formal contracts.

Research Note: When Do Consumers Value Positive versus Negative Reviews? An Empirical Investigation of Confirmation Bias in Online Word of Mouth

Information Systems Research
Yin D., Mitra S., Zhang H.
February 19, 2016
In the online word-of-mouth literature, research has consistently shown that negative reviews have a greater impact on product sales than positive reviews. Although this negativity effect is well documented at the product level, there is less consensus on whether negative or positive reviews are perceived to be more helpful by consumers. A limited number of studies document a higher perceived helpfulness for negative reviews under certain conditions, but accumulating empirical evidence suggests the opposite. To reconcile these contradictory findings, we propose that consumers can form initial beliefs about a product on the basis of the product’s summary rating statistics (such as the average and dispersion of the product’s ratings) and that these initial beliefs play a vital role in their subsequent evaluation of individual reviews. Using a unique panel data set collected from Apple’s App Store, we empirically demonstrate confirmation bias—that consumers have a tendency to perceive reviews that confirm (versus disconfirm) their initial beliefs as more helpful, and that this tendency is moderated by their confidence in their initial beliefs. Furthermore, we show that confirmation bias can lead to greater perceived helpfulness for positive reviews (positivity effect) when the average product rating is high, and for negative reviews (negativity effect) when the average product rating is low. Thus, the mixed findings in the literature can be a consequence of confirmation bias. This paper is among the first to incorporate the important role of consumers’ initial beliefs and confidence in such beliefs (a fundamental dimension of metacognition) into their evaluation of online reviews, and our findings have significant implications for researchers, retailers, and review websites.