The authenticity premium: Balancing conformity and innovation in high technology industries

Helena Buhr, Russell J. Funk, Jason Owen-Smith

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

Research on categories and markets suggests that audiences rely on categorical distinctions to make sense of market offerings. Market offerings that deviate from category norms risk devaluation. Although literature in this area has led to valuable insights, scholars have begun to question whether there has been an overemphasis on conformity, leaving existing theories ill-equipped to account for innovation. Within this context, we argue that research on authenticity in cultural sociology offers a useful platform for theorizing. We draw on the work of Peterson (1997), who underscores the importance of signals in evaluation. Objective features of market offerings (e.g., quality) matter, but particularly for innovations, these features are not readily visible. Because authentic producers are typically thought to be more committed, capable, and intrinsically motivated, when visibility of such objective features is lacking, authenticity may serve as an alternative indicator of value. Appearing authentic requires signaling believability with respect to category norms, while also being distinctive. Using data on 684 firms from five high technology sectors, we explore the relationship between authenticity and investor perceptions of value. Focusing on three different proxies for signals of authenticity—networks, governance, and narratives—we find a curvilinear association between conformity/distinctiveness and Tobin's q. Consistent with our view of authenticity as a signal, we also find that this relationship flattens as firms gain better track records and face stiffer competition.

Original languageEnglish (US)
Article number104085
JournalResearch Policy
Volume50
Issue number1
DOIs
StatePublished - Jan 2021

Bibliographical note

Publisher Copyright:
© 2020 Elsevier B.V.

Keywords

  • Authenticity
  • Categories
  • High-Technology
  • Innovation
  • Market Value
  • Natural Language Processing
  • Networks
  • Text Analysis

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