To Stand Out or Blend In? The Role of Expert Type in the Funding Decisions of Innovation Projects
Lun Li
Abstract
Lun Li
Abstract
Is optimal distinctiveness the moderate distinctiveness? We argue that the answer to this question depends on the audience’ experience. In this paper, we explore the effects of distinctiveness on the funding decisions made by different types of experts, namely, the business experts and technology experts. We found that the relationship between distinctiveness and business experts’ ratings exhibits an inverted-U shape, supporting the market value logic held by business experts; however, the relationship between distinctiveness and technology experts’ ratings is positive, supporting technology advancement logic held by technology experts. Moreover, our paper evidenced the moderating role of competitive intensity and institutional endorsement played in the relationship between distinctiveness and experts’ ratings. These ?ndings are integrated into a discussion of the implications for research on optimal distinctiveness.
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Is optimal distinctiveness the moderate distinctiveness? We argue that the answer to this question depends on the audience’ experience. In this paper, we explore the effects of distinctiveness on the funding decisions made by different types of experts, namely, the business experts and technology experts. We found that the relationship between distinctiveness and business experts’ ratings exhibits an inverted-U shape, supporting the market value logic held by business experts; however, the relationship between distinctiveness and technology experts’ ratings is positive, supporting technology advancement logic held by technology experts. Moreover, our paper evidenced the moderating role of competitive intensity and institutional endorsement played in the relationship between distinctiveness and experts’ ratings. These ?ndings are integrated into a discussion of the implications for research on optimal distinctiveness.
Key concepts: Optimal distinctiveness theory, Value (mathematics), Marketing, Psychology, Business, Knowledge management, Computer science, Social psychology