Building knowledge by mapping model uncertainty in six studies of social and financial performance

SSRN Electronic Journal(2022)

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摘要
Research Summary Many scholars bemoan the difficulty of learning from individual research reports. Replication is often prescribed as a salve, but few replications are conducted, and even fewer allow the formation of a coherent understanding. In this article, we propose a complement to replication that emphasizes the mapping of epistemic uncertainties. We demonstrate our approach by exploring the results of six related studies on the link between social and financial performance. We show that our method allows the synthesis of seemingly conflicting findings, and we propose that it should be used proactively, prior to replication, to speed the growth of knowledge. Managerial Summary Any single empirical study provides a weak basis for inference. As a result, scholars advocate repeated analysis of important issues, but evidence from replications can be hard to integrate into a coherent understanding. For example, six important studies of the link between corporate social and financial performance have been published in this journal, but their conflicting results have defied integration. We show that a new approach to empirical research allows their reconciliation: all six suggest that across firms, social and financial performance are correlated but that improvements in social performance seldom precede increased financial performance.
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关键词
epistemology, model selection, model uncertainty, research methods, social and financial performance
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