Today's globally competitive environment presents ample opportunity for buyers to dissolve relationships by switching suppliers. While previous studies have described supplier switching behavior based on supplier attributes and switching costs, our study leverages attribution theory to evaluate the impact of psychological contracts on supplier switching behavior. We report the results of a controlled experiment involving 265 subjects in which we manipulate three characteristics of a psychological contract breach: attribution (whether the breach was due to reneging by the supplier or a disruption), severity (whether the breach was major or minor), and timing (whether the breach was early or late in the life cycle of the exchange history). Our analysis indicates that in the context of supplier switching, buyers are affected by the attribution and severity of a breach but not by the timing. In contrast to previous experimental research in noncompetitive settings, we find that psychological contract violation mediates the relationship between breach and behavior. We further complement our primary findings with a vignette-based experiment and interview data collected from experienced managers. Our research makes an important contribution to the relationship dissolution and industrial buyer behavior literatures by providing a behavioral explanation for supplier switching and reveals the complex role of psychological contracts in supply chain exchanges.

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Purpose Content analysis is a methodology that has been used in many academic disciplines as a means to extract quantitative measures from textual information. The purpose of this paper is to document the use of content analysis in the supply chain literature. The authors also discuss opportunities for future research. Design/methodology/approach The authors conduct a literature review of 13 leading supply chain journals to assess the state of the content analysis-based literature and identify opportunities for future research. Additionally, the authors provide a general schema for and illustration of the use of content analysis. Findings The findings suggest that content analysis for quantitative studies and hypothesis testing purposes has rarely been used in the supply chain discipline. The research also suggests that in order to fully realize the potential of content analysis, future content analysis research should conduct more hypothesis testing, employ diverse data sets, utilize state-of-the-art content analysis software programs, and leverage multi-method research designs. Originality/value The current research synthesizes the use of content analysis methods in the supply chain domain and promotes the need to capitalize on the advantages offered by this research methodology. The paper also presents several topics for future research that can benefit from the content analysis method.

With the growth of e‐commerce and associated home deliveries, understanding the role of drivers in shaping the customer experience in last‐mile delivery is now more crucial than ever. Delivery drivers increasingly act as retailers' frontline employees and are thus instrumental in developing pseudorelationships between customers and retailers. Industry surveys, however, reveal that drivers admit to engaging in unprofessional behaviors with customers and often refuse to address customers' requests beyond package delivery. Following a middle‐range theorizing approach and leveraging Cognitive Appraisal Theory, we investigate how two negative driver behaviors, inappropriate behavior and inflexibility, impact customer satisfaction and repurchase intentions. We also examine the moderating effect of driver affiliation, private versus outsourced, in altering the magnitude of customer responses. Results from a scenario‐based experiment indicate that while the negative effects of driver inappropriate behavior on customer outcomes are mediated by anger, the effects of driver inflexibility are mediated by sadness. Moreover, the negative effect of driver inflexibility on customer outcomes is weaker for outsourced logistics than for private fleet drivers. In turn, driver inappropriate behavior exhibits similar negative effects on customer outcomes for both driver affiliations. These findings offer important insights for last‐mile delivery strategy and operations research and practice.

While the extant literature has examined causes for buyer–supplier relationship dissolution, the restoration of severed buyer–supplier relationships has been overlooked. Drawing on organizational justice theory, our research develops and tests a model of relationship restoration. We examine how the supplier's restoration tactics—acknowledgment, compensation, and operational transparency, influence the interactional, distributive, and procedural fairness perception, respectively, of the buyer, resulting in relationship restoration. The results are based on a 2 (Acknowledgment – Yes/No) × 2 (Compensation – Yes/No) × 2 (Operational Transparency – Yes/No) vignette‐based study with 390 experienced practitioners. The analysis shows that compensating the buyer and providing transparent procedures for dealing with similar situations in the future, lead to higher distributive fairness and procedural fairness, respectively, resulting in restored relationships. Compensation makes up for past supplier malperformance, whereas operational transparency mitigates future concerns. We also find that restoration tactics based on interactional justice are less effective than those based on procedural and distributive justice. There is only marginal support for the indirect positive effect of acknowledgment on restoration intentions (p < 0.10). These results point to the importance of knowing how to approach a buyer to initiate relationship restoration. Managers must understand and evaluate the specific needs of each buyer when proposing a compensatory design that appeals to the buyer. Additionally, establishing procedures that are appealing to all buyers can be a challenge for a supplier, due to the differing benefits to the supplier provided by each buyer.