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What We Know and Don’t Know About Corporate Social Responsibility

企业社会责任 适度 微观基础 意外事故 多学科方法 价值(数学) 动作(物理) 透视图(图形) 公共关系 心理学 知识管理 政治学 社会学 社会心理学 计算机科学 认识论 经济 社会科学 哲学 物理 量子力学 人工智能 机器学习 宏观经济学
作者
Herman Aguinis,Ante Glavas
出处
期刊:Journal of Management [SAGE Publishing]
卷期号:38 (4): 932-968 被引量:3397
标识
DOI:10.1177/0149206311436079
摘要

The authors review the corporate social responsibility (CSR) literature based on 588 journal articles and 102 books and book chapters. They offer a multilevel and multidisciplinary theoretical framework that synthesizes and integrates the literature at the institutional, organizational, and individual levels of analysis. The framework includes reactive and proactive predictors of CSR actions and policies and the outcomes of such actions and policies, which they classify as primarily affecting internal (i.e., internal outcomes) or external (i.e., external outcomes) stakeholders. The framework includes variables that explain underlying mechanisms (i.e., relationship- and value-based mediator variables) of CSR–outcomes relationships and contingency effects (i.e., people-, place-, price-, and profile-based moderator variables) that explain conditions under which the relationship between CSR and its outcomes change. The authors’ review reveals important knowledge gaps related to the adoption of different theoretical orientations by researchers studying CSR at different levels of analysis, the need to understand underlying mechanisms linking CSR with outcomes, the need for research at micro levels of analysis (i.e., individuals and teams), and the need for methodological approaches that will help address these substantive knowledge gaps. Accordingly, they offer a detailed research agenda for the future, based on a multilevel perspective that aims to integrate diverse theoretical frameworks as well as develop an understanding of underlying mechanisms and microfoundations of CSR (i.e., foundations based on individual action and interactions). The authors also provide specific suggestions regarding research design, measurement, and data-analytic approaches that will be instrumental in carrying out their proposed research agenda.
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