Business scandals like sweatshop labor have received growing attention in the field of supply management. Yet little is known about how detrimental such scandals are to buying firms. This study aims to fill this gap by examining the magnitude of the consequences of what are termed as supplier sustainability risks (SSRs). To this end, we conduct an event study analysis followed by regression modeling based on a sample of 196 U.S. publicly traded firms’ SSRs. The results reveal that SSRs are associated with a 1.00 percent reduction in shareholder wealth. The market reacts negatively but not differently to the two types of SSR: process‐related risks and product‐related risks. Finally, a firm's moral capital does play a mitigating role for SSRs and process‐related risks; however, it does not provide insurance‐like protection for product‐related risks.

The purpose of this study is to present a rigorous, focused review on how this field of ethical sourcing research has grown and evolved over the decades, providing implications for future research. We combine two research methodologies in this study: a systematic literature review and a citation network analysis. The former is used as a scientific tool to select the most relevant ethical sourcing articles, while the latter is then applied as a research technique to analyse these selected articles. Such a combined approach allows for a rigorous investigation into this field of research in a more scientific and objective way. Based on this approach, we identify (1) distinctive features of ethical sourcing studies such as growth trends and content issues; (2) important articles that have played a significant role in developing this field; (3) evolutionary paths that show how its knowledge has been created and transferred; (4) emerging trends that have received growing attention in the recent literature; (5) main research areas that underlie the entire ethical sourcing studies; and (6) major implications that need to be pursued in future research. The results of this study provide not only the current status of the literature but also the patterns of evolution in this field of research, thus contributing to the existing literature.

Although corrupt practices in the supply chain are not rare, this topic seems neglected in the literature. This could potentially be because a supply chain focused framework is lacking, and therefore it is difficult to measure the true impact of such issues. Why, how, and how much does corruption damage the corresponding firm in the supply chain? Our study takes what we term a supply chain view of corruption, and then estimates the stock price effect of corruption from that point of view. We focus on kickbacks and bribery issues that may damage a target firm's reputation and its market value. In particular, we address firms’ corrupt practices from a sustainability risk perspective with the conceptualization of corruption risk (CR). Using an event study methodology, based on a sample of 315 CR cases in the United States, we find significant market penalties for allegations of the target firms’ CRs (triggers) and its subsequent issues (investigation, regulatory and resolution). However, the market penalties are largely driven by triggers, not by the subsequent issues. We further reveal that the stock market reacts more negatively to CRs that occur upstream with suppliers than downstream with customers. Therefore, target focal firms must be cautious with upstream–trigger CRs.

Since 1990s, the world has seen a lot of advances in providing humanitarian aid through sophisticated logistics operations. The current consensus seems to be that humanitarian relief organizations (HROs) can improve their relief operations by collaborating with logistics service providers (CLSPs) in the commercial sector. The question remains: how can HROs select the most appropriate CLSP for disaster preparation? Despite its practical significance, no explicit effort has been done to identify the criteria/factors in prioritizing and selecting a CLSP for disaster relief. The present study aims to address this gap by consolidating the list of criteria from a socio-technical systems (STS) perspective. Then, to handle the interdependence among the criteria derived from the STS, we develop a hybrid multi-criteria decision making model for CLSP selection in the disaster preparedness stage. The proposed model is then evaluated by a real-life case study, providing insights into the decision-makers in both HROs and CLSPs.

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