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PhD Thesis Defense, Paul Gouvard, Strategy and Business Policy

Paul Gouvard

Congratulations to Dr Paul Gouvard, Strategy and Business Policy, who successfully defended his Doctoral thesis at HEC Paris, on July 1, 2020. Paul will join the University of Lugano (Switzerland) as Assistant Professor. 

Thesis Topic: Explaining the Variability of Audiences’ Valuations: An Approach Based on Market Categories and Natural Language Processing

Supervisor:  Rodolphe Durand, Professor of Strategy and Business Policy, HEC Paris

Jury members:  
Mary-Ann Glynn, Professeor, Caroll School of Management, Boston College
Sameer Srivastava, Associate Professor, Haas Business School, UC Berkeley
Rose Luo, Associate Professor, INSEAD

Rodolphe Durand Professor, HEC Paris (supervisor)

Abstract: This dissertation examines whether the different categorization processes shaping audiences’ valuations in markets bring stability or variability to audiences’ valuations. While seminal research on categorization emphasized the stabilizing role of market categories, recent research suggests that audiences’ valuations can vary substantially even in markets which are wellstructured by pre-existing categories. This variability notably results from audiences’ heterogeneous preferences for typical offerings, from shifts in categories’ meanings or from audiences’ reliance on multiple models of valuation. Taking stock of these new results, this dissertation asks why audiences’ valuations are so variable and explores in more details the role that market categories play in this phenomenon. 
This dissertation proposes that i) ambiguous categories, ii) the influence of temporary attractions among audiences alongside more stable categories and iii) the co-existence of different types of evaluators all contribute to produce variability in audiences’ valuations. The first two empirical essays use data from publicly listed firms in the U.S. In these essays, firms’ similarity to existing category prototypes or audiences’ temporary attractions toward certain features are measured using semantics extracted from large corpora of annual reports and IPO prospectuses. The third essay is a theoretical model. This dissertation contributes to the literature on market categories, to the burgeoning research on optimal distinctiveness and to computational approaches to the study of organizations.