This paper studies the way supplier firms’ corporate social responsibility (CSR) affects their likelihood of being selected as new suppliers. Using a large sample of US public firms with detailed supply chain and CSR data, we provide empirical evidence that corporate customers prefer socially responsible suppliers, and that the effect is more prominent when the supplier industry is more competitive, the customer’s own CSR performance is better, or the supplier and the customer have more similar CSR focuses. Our paper contributes (...) to the literature of instrumental stakeholder theory (IST) by confirming corporate customer attraction as a desirable outcome of supplier CSR engagement. It complements the existing IST studies on customer responses by showing that CSR attracts not only final customers but also corporate customers. Moreover, by focusing on corporate customers’ revealed preferences for socially responsible suppliers, our paper also complements the stated-preference-based evidence in the literature of sustainable supply chain management. Our paper’s findings encourage supplier firm managers to invest in CSR to gain competitive advantages in the form of a higher likelihood of selection while simultaneously making positive contributions to society. (shrink)

This article proposes a conceptual mapping to outline salient properties and relations that allow for a knowledge transfer from the well-established greenwashing phenomenon to the more recent machinewashing. We account for relevant dissimilarities, indicating where conceptual boundaries may be drawn. Guided by a “reasoning by analogy” approach, the article addresses the structural analogy and machinewashing idiosyncrasies leading to a novel and theoretically informed model of machinewashing. Consequently, machinewashing is defined as a strategy that organizations adopt to engage in misleading behavior (...) about ethical Artificial Intelligence /algorithmic systems. Machinewashing involves misleading information about ethical AI communicated or omitted via words, visuals, or the underlying algorithm of AI itself. Furthermore, and going beyond greenwashing, machinewashing may be used for symbolic actions such as lobbying and prevention of stricter regulation. By outlining diverse theoretical foundations of the established greenwashing domain and their relation to specific research questions, the article proposes a machinewashing model and a set of theory-related research questions on the macro, meso, and micro-level for future machinewashing research. We conclude by stressing limitations and by outlining practical implications for organizations and policymakers. (shrink)