Article
Dynamic Interplay of Environmental Sustainability and Corporate Reputation: A Combined Parametric and Nonparametric Approach
Annals of Operational Research
(2021)
Abstract
For decades, research on the relationship between environmental sustainability and firm performance focused on determining whether the effect of the former on the latter was positive or negative. That potentially controversial approach had driven mainstream research to ask two focal questions: Does it pay to be green? and Does it cost to be green? Recent papers have explored a curvilinear effect (i.e., U-shaped and inverted U-shaped) by tackling another question: When does it pay to be green? These efforts, however, have either oversimplified the complex linkage between these two things into a linear relationship or confined the complexity within a formatted frame. This paper overcomes these shortfalls by exploring the holistic effect of environmental sustainability on firm performance, contingent upon corporate reputation. In conjunction with direct effect analysis, this paper uniquely explores the synergistic effect of environmental sustainability and corporate reputation on performance. In addition to detecting the nonlinear synergy pattern, we found that the synergy effect is asymmetric. Specifically, the effect is complementary for low-reputation firms but substitutive for high-reputation firms. In addition to its theoretical contributions and pragmatic implications, this paper uniquely presents PROCESS-Neural network as a promising analytic paradigm.
Keywords
- corporate reputation,
- neural networks,
- sustainability,
- Tobin's Q
Disciplines
Publication Date
Fall October 30, 2021
DOI
https://doi.org/10.1007/s10479-021-04331-6
Publisher Statement
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021
Citation Information
He-Boong Kwon, Jooh Lee and Laee Choi. "Dynamic Interplay of Environmental Sustainability and Corporate Reputation: A Combined Parametric and Nonparametric Approach" Annals of Operational Research (2021) ISSN: 0254-5330 Available at: http://works.bepress.com/jooh-lee/59/