Emotions in logistics and supply chain management

Purpose Supply chains are powered by people, and people are driven by emotions. Yet research on logistics and supply chain management (LSCM) has largely portrayed decision-makers as rational actors, prioritizing efficiency while overlooking the emotional dynamics that shape relationships and performance. Although recent studies have begun to link emotions such as fear, anger, and sympathy to outcomes like panic buying, negotiation breakdowns, and resilience, insights remain fragmented and undertheorized. Design/methodology/approach This review addresses that gap by systematically analyzing how emotions have been conceptualized and operationalized in LSCM. Anchored in Ekman's (1992) taxonomy of basic emotions, we identified and coded 40 peer-reviewed articles from leading LSCM journals, combining deductive and inductive approaches to capture how constructs align with or extend beyond basic categories. We also assess how concepts imported from psychology and marketing have been adapted to LSCM contexts. Findings The systematic review shows that LSCM research on emotions is skewed toward negative emotions and relies primarily on attribution and appraisal lenses. Existing studies explain breakdowns (e.g. anger following blameworthy failures) more clearly than the emergence and maintenance of positive relational dynamics. Across the literature, boundary conditions such as dependence, power asymmetry, and switching constraints remain largely undertheorized, despite their likely influence on whether emotions translate into voice, accommodation, or retaliation. To address these gaps, we develop a modified middle-range framework linking discrete emotions to performance, compliance, and resilience outcomes across different structural conditions. Research limitations/implications The study identified several avenues to advance research on emotions in LSCM, including exploring emotions such as disgust, surprise, and contempt, investigating new areas, such as increased enthusiasm for innovation adoption and technological advancements, as well as employing innovative research designs through the cautious use of AI-enabled emotion recognition and neuroscience-based approaches. Originality/value The article positions emotions as core constructs in LSCM, advancing behavioral LSCM by guiding researchers to engage with emotions more deliberately and by formulating research propositions across established and emerging fields of application. We further support managers with structured approaches to incorporate emotional considerations into buyer-supplier relationships, workplace behavior, as well as resilience and risk management.