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The moderate-reputation trap: Evidence from a Chinese cross-border business-to-business e-commerce portal

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Abstract

How does review-based online reputation (for brevity, online reputation) influence online firm survival? Drawing insights from the resource-based view and signaling theory, we examine a nonlinear (U-shaped) relationship between online reputation and firm survival on a cross-border business-to-business (B2B) platform and the resulting moderate-reputation trap. We further examine how online firms employ product strategies to moderate the effect of online reputation on firm survival and thus mitigate the moderate-reputation trap. Using data from 17,920 monthly observations (3145 sellers) from July 2016 to December 2017 on DHgate.com in China, we find strong evidence supporting our hypothesized relationships. More specifically, we demonstrate the existence of the moderate-reputation trap and that this trap can be mitigated by a high product price or low product diversity. Our research provides important insights for managers of online firms, B2B platform providers, and governments.

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Notes

  1. While the concept of reputation is broad, in this study, we focus on review-based online reputation.

  2. We follow the broad definition of product that includes service. More specifically, product is defined as anything that can be offered in a market for attention, acquisition, use, or consumption that might satisfy a need or want (Kotler & Armstrong, 2014).

  3. https://www.zdnet.com/article/china-accounts-for-40-percent-of-global-ecommerce-transactions/

  4. Source: Seller policy of DHgate, http://seller.dhgate.com/policynew/c_5004000.html.

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Acknowledgements

We would like to thank our editor Prof. Cui Lin and the two anonymous reviewers for their valuable comments. This study was supported by National Office for Philosophy and Social Sciences (CN) (No: 18BGL051), Tsinghua University Center for Industrial Development and Environmental Governance (CIDEG), CityU Strategic Research Grants (No: 7005199 & No: 7005388), CityU Startup Grant for Professor (No: 9380098), and Shanghai Planning Office of Philosophy and Social Science (No: 2019EGL009).

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Appendix

Appendix

Appendix Table 9 presents the subsample Cox regression results and z-statistics of different groups by using review rating as the proxy of online reputation. Following Lamin and Livanis (2013), we use the median value of price and diversity to dichotomize the full sample into “low price” versus “high price” subsamples as well as “low diversity” versus “high diversity” subsamples. The results show support for Hypotheses 2 and 3, and we draw Figs. 3 and 4 based on the results in Appendix Table 9.

Table 9 Robustness test results: Cox regression results with subsamples

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Luo, L., Ma, X. & Wang, Z. The moderate-reputation trap: Evidence from a Chinese cross-border business-to-business e-commerce portal. Asia Pac J Manag 39, 395–432 (2022). https://doi.org/10.1007/s10490-020-09730-0

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