PhD Thesis Defense, Saverio D. Favaron, Strategy and Business Policy
Congratulations to Dr Saverio Dave Favaron, Strategy and Business Policy, who successfully defended his Doctoral thesis at HEC Paris, on June 23, 2020. Saverio will join the Skema Business School (KTO research centre) as Assistant Professor.
Thesis Topic: Firms' strategic responses to evaluations
Supervisor(s): Olivier Chatain, Associate Professor, HEC Paris, Giada Di Stefano, Associate Professor, Bocconi University
Olivier Chatain, Associate Professor, HEC Paris, Supervisor
Giada Di Stefano, Associate Professor, Bocconi University, Co-supervisor
Rodolphe Durand, Professor, HEC Paris
Elisa Operti, Associate Professor, ESSEC
Patricia Thornton, Professor, Texas A&M University
Maurizio Zollo, Professor, Imperial College London
The rise of digital media technology over the last decades has transformed the way in which organizations are evaluated. Judgments by experts and critics, recognized for their knowledge of evaluation criteria, appropriate weightings, and appropriate preferences, are losing their appeal to customers in many industries. Every day, on a plurality of platforms and websites, individuals disclose information about their interactions with organizations and their products or services. Compared to traditional media or professional critics, digital users and customers tend to share subjective and partial experiences, have lower concerns for accuracy and balance, and often put emphasis on the emotional content. As more customers rely on this information for their purchasing choices, firms in many industries find themselves in a position where it is hard to ignore the opinions expressed online by customers as inconsequential. In this thesis, I study how the strategies and behaviors of organizations are affected by this “democratization” of evaluation process. The empirical setting for my analyses is the restaurant industry. In the first chapter, I study online reviews as a source of information for restaurants, which may learn about problems, errors, or improvement opportunities. I examine what features of customer feedback make it more likely to be considered by target restaurants. With an online experiment in the French restaurant industry, I find that decision makers allocate attention to feedback that is expected to have a stronger impact on the reputation and performance of the restaurant. However, I also find evidence of a “disturbance” effect of the emotions evoked by certain feedback features. With this chapter I emphasize the importance of incorporating affective mechanisms in the study of attention, and shed light on how individual-level emotions impact organizational-level outcomes. In the second chapter, I analyze the effects of the interaction between amateur and expert evaluations. In particular, I study the entry of an expert evaluator (i.e., Michelin guide) in a market, and how it pushes some organizations to make strategic choices that signal their aspirations. Drawing on literature on organizational status, I find that restaurants better rated by Michelin make changes to their offer with the aim to self-identify with the élite group. These changes consist in the adoption or removal of certain features displayed in their menus. In addition, by using topic modeling techniques applied to Yelp reviews, I observe that customers’ reactions to the entry of Michelin make restaurants more or less sensitive to the expert’s evaluations. In the third chapter, I focus on how organizations use public responses to customers to address criticism in online settings. Recent studies are not conclusive on the reputational benefits of public responses to reviews. These responses may reduce the likelihood of future negative reviews while, at the same time, draw attention to problems. Building on existing literature on reputation and impression management, I propose that organizations may resolve this trade-off by making a strategic use of different types of verbal accounts (e.g., apology). Although public responses to customers may be counterproductive, adapting the style of public responses to the features of customer reviews might be an optimal strategy for organizations. For this study I analyze restaurant reviews in France and the United States using standard econometric models supported by supervised learning techniques.