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Converging Tides Lift All Boats: Consensus in Evaluation Criteria Boosts Investments in Firms in Nascent Technology Sectors
Although previous studies show that the emergence of evaluation criteria for a new technology improves the life chances of well-performing firms, we theorize that consensus in such criteria among technology experts increases investments to all firms in the new sector. We provide a variety of support...
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Published in: | Organization science (Providence, R.I.) R.I.), 2023-11, Vol.34 (6), p.2415-2435 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Although previous studies show that the emergence of evaluation criteria for a new technology improves the life chances of well-performing firms, we theorize that
consensus
in such criteria among technology experts increases investments to
all
firms in the new sector. We provide a variety of supportive evidence for this claim. First, in an experiment with 80 Chinese investors (Study 1), we provide evidence of a causal relation between evaluation consensus and investments. We follow this with a second experiment with 412 U.S. participants (Study 2), showing that evaluation criteria consensus increases participants’ propensity to view a firm as technologically competent and to expect others to favor investing in the firm. Analyses of longitudinal archival data on investment in artificial intelligence technology firms in the United States (Study 3a) and China (Study 3b) support the generalizability of our findings. By exploring the social-cognitive processes that link evaluation criteria consensus to investors’ decisions to invest in firms in nascent technology fields, this paper advances the scholarly understanding of the microfoundations of the institutionalization processes in new market sectors.
History:
This paper has been accepted for the
Organization Science
Special Issue on Experiments in Organizational Theory.
Funding:
This work was supported by Cornell University (Innovation, Entrepreneurship, and Technology Theme Research Grant, Jeffrey S. Lehman Fund for Scholarly Exchange with China).
Supplemental Material:
The online appendix is available at
https://doi.org/10.1287/orsc.2021.1493
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ISSN: | 1047-7039 1526-5455 |
DOI: | 10.1287/orsc.2021.1493 |