Purpose In the transformation to the circular economy, circular logistics nodes are becoming increasingly important to, for example, match supply and demand, coordinate flows, increase logistics efficiency and customer utility, and reduce environmental impact. The purpose of this study is to expand our theoretical understanding of the circular retail transformation and its implications for circular logistics nodes. Design/methodology/approach An integrative literature review was conducted to synthesize diverse sources of knowledge on the circular transformation. The review focused on circular retail stores as representative nodes and then generalized these insights to a broader range of circular logistics nodes. Given the topic's interdisciplinary nature, knowledge about retail stores in a circular retail context exists, but is fragmented across multiple domains (e.g. sustainability, marketing, logistics and supply chain). To the authors’ knowledge, no previous study has integrated extant knowledge to advance our theoretical understanding of retail stores as circular logistics nodes. Findings The study identified seven themes that shape the circular transformation and retail-store configuration: (1) incentives and regulatory enablers, (2) introducing the circular consumer, (3) the issue of supply, (4) circular governance and organization, (5) integrating and scaling circular services and operations, (6) leveraging resources and (7) the need for new performance indicators. Research limitations/implications Anchored in a network-node-resource perspective, the study findings are extended to discuss implications for a broader range of circular logistics nodes. The themes and implications are then connected in a research agenda for circular logistics nodes, which outlines research avenues and questions as well as potential theoretical and methodological approaches. Originality/value The article brings a new perspective by conceptualizing retail stores as circular logistics nodes and discussing broader configuration consideration for logistics nodes in the circular retail network.
Purpose This study systematically explores the pathways through which smart packaging (SP) enhances logistics capabilities (LCs) to simultaneously address two key challenges for the circular economy (CE) – physical value and information loss. While the link between SP and circularity is recognised, the specific pathways through which item-level data reconfigures LCs and leads to circular outcomes remain underexplored. This paper clarifies these connections, detailing how and why SP serves as a foundational enabler for the strategic transition from reactive recovery to proactive circular supply chains. Design/methodology/approach Following a theory-informed systematic literature review (SLR), 59 articles were analysed using axial coding and multi-layered framework synthesis. The research utilises packaging functionalities (PFs) and LCs as micro-level and macro-level units of analysis, respectively, while adopting the R-imperative framework as a strategic lens to map circular outcomes. Findings The study identifies four thematic pathways: (1) proactive logistics management and dynamic optimisation, (2) autonomous and scalable reverse flows, (3) systemic trust and quality of material streams, and (4) collaborative value co-creation. The findings demonstrate that SP-enhanced LCs address the challenges of achieving circularity by mitigating physical value loss through functional preservation and information loss through item-level visibility. Information-management capabilities are the foundational antecedents allowing supply-management, demand-management, and coordination capabilities to mitigate the information asymmetry inherent in closed-loop systems. Originality/value This research develops a novel multi-layered conceptual framework explaining the “how” and “why” behind SP-enabled higher-order circularity. It identifies the theoretical boundaries of logistics-led interventions, highlighting the limits of item-level intelligence in supporting design-led strategies like repair and refurbish.
PurposeThis paper proposes an adaptive local Distribution Network (DN) approach supported by real-time consumer preference and inventory data for dynamic order allocation.Design/methodology/approachAn operational approach is outlined for DNs fulfilling omni-channel online orders, tailoring different delivery modes to cater to heterogeneous consumer demands. Since these combinations generate high task uncertainty, the approach draws on Organizational Information Processing Theory (OIPT), leveraging real-time data to enhance the retailer's information processing capacity. To evaluate its performance in a real-world scenario, a simulation was conducted implementing the proposed approach in a Brazilian retailer context.FindingsResults highlight the importance of aligning delivery strategies with diverse consumer expectations, suggesting that relying on a single facility type may be insufficient to meet such diverse demands. Computational outcomes indicate that decentralizing the DN into an adaptive hybrid approach, combining facilities and postponing fulfillment decisions using real-time data can mitigate task uncertainty, reducing fulfillment time for quick commerce and minimizing delivery attempts.Practical implicationsThis technology-driven solution empowers retailers to overcome the limitations of static networks. By aligning logistics operations with consumer preferences, it enhances fulfillment performance and balances operational trade-offs, preparing retailers for ever-evolving market trends.Originality/valueThis research addresses a gap in the holistic integration of multiple delivery modes, consumer logistics preferences and inventory locations by incorporating intelligent systems that enhance information processing capacity for postponed fulfillment decisions.
Purpose With the increased use of global supply chains in order to secure necessary resources and lower costs, there is a growing concern regarding occurrences of human trafficking, specifically forced labor, in the supply chain. For this reason, supply chain visibility and transparency are crucial. The purpose of this study was to provide a starting point for considering how AI-powered technology can play a role in addressing forced labor in supply chains.Design/methodology/approach The researchers used artificial intelligence (AI) to enhance supply chain visibility. An AI-powered analytic tool called "Break Chain" was developed and tested. A mixed-methods action research approach was used where quantitative data analysis was integrated with qualitative action steps. This allowed for a more comprehensive understanding of the complex and multifaceted nature of supply chain dynamics.Findings In this study, "Break Chain" was used to evaluate 50 businesses from various industries across Northeast Texas. "Break Chain" provided a dashboard visualization that synthesized the flagged data into an interactive interface. This allowed stakeholders to efficiently navigate and interpret complex datasets. The "Break Chain" technology also allowed for predictive modeling to forecast potential trafficking activities within corporate supply chains. This study found that the model had a precision rate of 91% and a recall rate of 87%, which point to "Break Chain's" calibrated sensitivity and specificity.Originality/value "Break Chain" is an innovative example of how technology can be used to locate and predict instances of forced labor within supply chains.
Purpose This study investigates whether supply chain transparency through sustainable supply management (SSM) disclosure influences consumer purchase behavior. When firms understand this behavior, they can optimize operations and craft clearer, more impactful supply-chain sustainability disclosures.Design/methodology/approach Two controlled laboratory experiments and a natural field experiment are used to evaluate various elements of SSM disclosures. The first laboratory experiment examines consumer willingness to pay a premium for products with SSM disclosures, when compared across firms. The second laboratory experiment examines consumer response to SSM disclosures across different products offered within the same firm. The field experiment evaluates whether consumers are willing to buy or pay a premium in actual market situations where SSM information is disclosed.Findings Results demonstrate significant consumer preferences for products accompanied by SSM disclosures. The analysis of the natural field experiment indicates that consumers are inclined to purchase more from firms that transparently communicate their SSM practices. Further, we find that at least some consumers are willing to pay a premium for products with SSM disclosure. The laboratory experiments, on the other hand, fail to provide significant evidence that consumers are willing to pay more for products with SSM disclosures. These results offer insights into how signaling and legitimacy concerns within the downstream supply chain shape consumers' purchasing behavior and, in turn, firm performance.Practical implications A proactive communication strategy on firm SSM engagement can gain market share and build competitive advantage. The costs associated with gathering SSM information can potentially be offset by greater market share and premium pricing. Regulators and policymakers can support efforts for supply chain transparency by providing impetus for consumer requests for such information and encouraging firms to supply it.Originality/value This research uniquely integrates a series of behavioral experiments to robustly assess the influence of supply chain transparency on consumer purchasing behavior. Through legitimacy and signaling theoretical lenses, our study shows the reason for firm strategic communication in SSM efforts. There is an emphasis on how supply chain decisions related to collaboration and facilitating transparency are critical to organizational market competitiveness due to consumer preferences and behavior. The role of transparency and legitimacy in sustainable supply chain management is further advanced.
Purpose Post-retail liquidation platforms (PLRPs) are reshaping inventory disposition strategies, offering scalable channels for managing excess inventory. Yet, PRLP adoption remains uneven and the mechanisms driving value are not well-understood. Prior work has examined reverse logistics and secondary markets more broadly, but research focused on how sellers can most effectively disposition goods through PLRPs is limited. This study examines seller strategies and identifies the structural factors that shape performance in digital liquidation environments.Design/methodology/approach This study draws on qualitative insights from Fortune 500 retailers, a state agency and industry experts to understand the current landscape of online PRLPs. In addition, it analyzes more than 21,000 auction listings from a leading PRLP to assess how seller characteristics, lot design and listing strategies shape performance.Findings The study highlights significant inefficiencies in current PRLP utilization practices, including a lack of sophistication and inconsistent tactics. Yet amid these inefficiencies, the study identifies that liquidation outcomes follow systematic patterns driven by three seller-controlled mechanisms: seller equity, listing quality and product context. These findings, based on PRLP data from the United States, demonstrate that value recovery is not random but shaped by deliberate engagement strategies.Originality/value By bridging field-based insights with large-scale platform data, this study moves beyond descriptive accounts of secondary markets to identify prescriptive design principles for digital liquidation. Theoretically, it highlights a structural misalignment between seller practices and platform performance drivers. Managerially, it provides actionable guidance for improving recovery rates through strategic listing and engagement. At an ecosystem level, it positions PRLPs as emerging infrastructure within modern supply chains, with implications for circular economy objectives and sustainable secondary market flows.
Purpose Grocery retailers in the fast-moving consumer goods (FMCG) sector are reconfiguring their logistics networks to address rising operational complexity and technological disruption. In this context, warehouse automation is moving beyond operational support to play a strategic role, enabling firms to redesign processes and adapt logistics systems to dynamic market and technological conditions. Despite the growing relevance of automation, empirical understanding of how automated technologies are selected, combined, and adapted in grocery DCs remains limited. This study addresses this gap by investigating how grocery retailers implement warehouse automation to transform logistics processes in response to evolving operational complexity and market demands.Design/methodology/approach A multi-phase qualitative approach was adopted, combining semi-structured interviews with eight automation providers and six grocery retailers, complemented by site visits. Data were analysed through the Gioia method to inductively derive recurring patterns and managerial logics. The emerging framework was then interpreted through the lens of the DCT.Findings The study identifies six DC processes supported by distinct automation technologies, such as AS/RS systems, miniloads, shuttles, and robotic picking stations, and five strategic decision factors guiding automation decisions: selectivity, accessibility, expandability, scalability and resilience. Interpreted through the lens of dynamic capabilities theory, these dimensions show how the implementation of automation supports firms in sensing operational requirements, seizing technological opportunities and sustaining long-term adaptability and operational continuity.Originality/value This research bridges the gap between theory and practice in grocery logistics by conceptualising warehouse automation implementation as a dynamic capability. It provides a validated framework for scholars and practitioners, supporting informed, future-oriented automation strategies in retail distribution.
Purpose This study examines when and how supply chain traceability and due diligence practices enhance financial performance, measured as asset turnover (ATO), in the fashion industry. Drawing on legitimacy theory and organizational slack, we argue that the financial returns from these practices are contingent on firms' operational efficiency, specifically, inventory efficiency and selling, general and administrative (SG&A) efficiency, rather than universal or unconditional. Design/methodology/approach We combine archival data from the fashion revolution foundation's annual fashion transparency index with financial data from Compustat for a sample of 40 publicly traded fashion companies. Moderated regression analysis tests whether inventory efficiency and SG&A efficiency condition the traceability-ATO and due diligence–ATO relationships. Findings The direct effects of traceability and due diligence on ATO are not statistically significant when examined in isolation. However, traceability positively influences ATO when moderated by high inventory efficiency and high SG&A efficiency. Contrary to the moderating pattern for traceability, due diligence shows negative interaction effects under conditions of high operational efficiency, suggesting important theoretical and practical distinctions between these two types of transparency practice. Originality/value This article offers the first empirical evidence linking supply chain traceability and due diligence to financial performance in the fashion industry, introducing operational efficiency as a boundary condition that explains when, and for whom, these practices yield measurable returns. The asymmetric moderation patterns for traceability versus due diligence challenge prevailing assumptions that transparency is uniformly beneficial, and contribute to legitimacy theory by specifying the resource conditions under which CSP investments translate into financial gains.
Purpose Supply chain concentration (SC concentration) is a key aspect of supply chain structure and a determinant of a firm's resilience to external disruptions. However, previous research on how SC concentration affects firm resilience has been inconclusive. This study investigates the nuances of this relationship by examining the moderating effects of political ties and board interlocks.Design/methodology/approach We used both cross-sectional and panel designs to test the hypotheses. Our main analysis is conducted on a cross-sectional sample of 3,745 publicly listed Chinese companies during the COVID-19 pandemic. For a robustness check, we test the hypotheses using a panel dataset of Chinese firms from 2007 to 2022. We also interviewed managers at two Chinese manufacturing firms to understand the mechanisms underlying the theorized relationships.Findings We find that both supplier and customer concentration are detrimental to firm resilience. Specifically, firms with high SC concentration experience greater firm value losses and take longer to recover following the COVID-19 outbreak. Furthermore, firms can leverage social capital with external parties to mitigate such effects. We find that the impact of supplier and customer concentration is weaker for firms with strong political ties and high levels of board interlocks. The results are robust across alternative measures and research designs.Originality/value These findings extend prior research by identifying key dimensions of social capital - specifically, political ties and board interlocks - that mitigate the negative impact of SC concentration on firm resilience.
Purpose This paper aims to advance understanding of freight transport network disruptions by reconceptualising them as systemic, multi-level phenomena. It examines how disruptive events originating in European freight transport networks generate ripple effects across transport networks, supply chains and society, and how resilience is expressed across these interconnected levels. Design/methodology/approach The qualitative, multi-stage research design combines focus group discussions, semi-structured interviews and document analysis. Data on four disruptive events is analysed using an analytical framework capturing ripple effects, intersectionality and resilience across transport network, supply chain and societal levels. Findings Disruptions generate ripple effects that propagate into supply chains and society. They vary in scale, scope and intensity, and intersect with existing vulnerabilities. Ripple effects are not linear but unfold through interacting and co-occurring dynamics across levels, highlighting the systemic nature of transport disruptions. Research limitations/implications The study is based on a limited number of qualitative cases and does not aim for statistical generalisation. It opens avenues for further research on multi-level disruption dynamics, ripple effects and transport network resilience. Practical implications The findings highlight the need for resilient transport infrastructure, improved coordination, and enhanced stakeholder communication to mitigate ripple effects. Social implications Freight transport disruptions have far-reaching societal consequences, emphasising the importance of preparedness, communication and disruption management. Originality/value The paper contributes to disruption and resilience literature by shifting analytical focus from individual firms and supply chains to freight transport networks and their societal embeddedness. By examining multiple disruptive events, it reveals shared vulnerabilities and recurring patterns of propagation.
PurposeThis study examines how consumer motivation toward drone delivery emerges in omnichannel retailing, addressing a critical gap in consumer-centric supply chain management by exploring underexplored motivational processes that shape consumer readiness for logistics innovations. While prior research has primarily emphasized behavioral intention or adoption using frameworks such as TAM, TPB, and UTAUT, the formation of motivation itself as a psychological state that precedes and sustains intention has received little theoretical attention. Drawing on Expectancy Theory, this study investigates the antecedent mechanisms that underpin motivational readiness and identifies the threshold conditions required for that motivation to emerge.Design/methodology/approachA survey of consumers in the United States was conducted to capture perceptions of valence, expectancy, instrumentality, consumer engagement with retailer (CER), and consumer motivation toward drone delivery. Structural relationships were tested using PLS-SEM, complemented by Necessary Condition Analysis (NCA) to identify threshold conditions required for motivation to emerge.FindingsThe results reveal a hierarchical motivational structure underlying consumer readiness for drone delivery. Valence functions as a foundational gatekeeper. Expectancy and instrumentality are statistically necessary conditions, while valence is the only component that imposes a binding bottleneck threshold on motivation. Consumer Engagement with Retailer (CER) partially mediates the effects of valence, expectancy, and instrumentality, underscoring its amplifying rather than essential role. Together, the results demonstrate how motivational predictors and necessary prerequisites jointly shape pre-adoption readiness for drone delivery in omnichannel retailing, providing a diagnostic framework to assess whether the motivational conditions necessary for logistics innovation scaling have been met.Practical implicationsRetailers and logistics providers can leverage these findings to design implementation strategies and managerial emphasis aligned with motivational thresholds. Specifically, firms should emphasize value propositions (Valence) to activate consumer motivation, reinforce service reliability and usability (Expectancy) as motivation strengthens, and highlight outcome utility (Instrumentality) to sustain motivation at higher levels. Integrating drone delivery into broader Consumer Engagement with Retailer (CER) strategies can further amplify motivation, providing a structured framework to inform pilot deployments and subsequent scaling decisions in omnichannel retail environments.Originality/valueThis study is the first to empirically operationalize and validate Valence, Instrumentality, and Expectancy (VIE) scales in the context of consumer drone delivery within omnichannel retailing. By positioning Consumer Motivation rather than behavioral intention as the focal outcome, it addresses a critical gap in logistics and delivery innovation research where the motivational processes underlying consumers' responses to logistics innovations remain underexamined. The study further introduces Consumer Engagement with Retailer (CER) as a novel application in omnichannel fulfillment research, demonstrating its amplifying role in translating motivational beliefs into consumer readiness for emerging delivery innovations.
Purpose"Buy-Online-Return-In-Store" (BORIS) cross-channel returns is a notable tactic e-retailers use to attract consumers. Yet, the approach may create operational challenges, motivating concerns regarding its overall impact. This study provides empirical evidence on associations between use of BORIS and e-retailer performance, while also exploring interactions with same-channel free return shipping policies and two promotion tactics (i.e. social media use, sponsored search).Design/methodology/approachUsing annual data (2013-2019) for the Top 1,000 e-retailers in North America, we employ regressions, robustness checks and endogeneity corrections to examine associations between BORIS and four performance metrics: website sales, order conversion rates, average customer order value and website traffic.FindingsFixed-effect model results suggest offering BORIS to online customers provides a negligible direct benefit to website sales and no meaningful impact across performance metrics among pure e-retailers. For bricks-and-clicks e-retailers, BORIS interacts with free return shipping policies to weakly bolster average order value and website traffic. When sponsored search spend is low, BORIS lifts average order value but does not improve conversion rates. Conversely, BORIS drives incremental website traffic via tactical synergies with sponsored search. Endogeneity-corrected random-effect estimates are broadly consistent and further reveal that e-retailers offering BORIS for competitive purposes may experience additional significant consequences from social media moderation.Originality/valueThe study contributes to research by theorizing potential performance impacts of BORIS use and finding empirical outcomes that motivate questions about its overall effectiveness. The nuanced findings show BORIS can provide scope-specific benefits under certain conditions. For e-retail managers, the findings translate anecdotal evidence about the importance of BORIS returns into empirical evidence that BORIS returns policies can matter, yet for some metrics, may exhibit only weak associations with e-retailer performance.
PurposeThis study examines whether generative AI can serve as an effective knowledge translation tool, bridging the long-standing theory-practice gap in supply chain management (SCM). While prior SCM scholarship has focused on AI's operational capabilities, we investigate its potential to enhance practitioner engagement with academic research.Design/methodology/approachDrawing primarily on cognitive load theory, with further support from construal-level theory, we conduct a 2 & times; 2 between-subjects behavioral experiment with supply chain decision-makers. Participants are exposed to either an excerpt from an academic article or its generative AI-created translation. The vignette is further framed with either near-term or far-term temporal distance. Measures include ICL, practitioner engagement, knowledge retention, and attitudes toward AI.FindingsResults show that Generative AI-created translations significantly reduce ICL compared to original academic articles and increase practitioner engagement. Additionally, we find no loss in knowledge retention. The indirect effect of knowledge source on engagement via ICL is significant, indicating that reduced cognitive effort is associated with higher engagement. Psychological distance shows a partial effect in planned contrasts but does not significantly moderate the mediated pathway.Originality/valueThis work is among the first in SCM to empirically test the role of generative AI in translating scholarly knowledge into practice. We extend cognitive load theory into the SCM knowledge transfer context and position generative AI as a dual-purpose technology. This technology can support both operational efficiency and academic-practitioner alignment, offering a scalable approach to a persistent challenge in the field.
Purpose This article aims to advance an emergent multilevel perspective as a useful lens for capturing the dynamics that shape behavior in real-world operational settings. Design/methodology/approach The article adopts a conceptual approach by examining three foundational domains of behavioral operations (BO) research–inventory management, supply-chain management and productivity management–to clarify the analytical boundaries of prevailing single-level and top-down perspectives. It then illustrates the potential of an emergent multilevel lens to advance the understanding of how behavioral patterns develop over time through interaction, coordination and role dynamics across organizational levels. Findings By reframing core domains through an emergent multilevel perspective, the article demonstrates the added explanatory power and analytical clarity this approach offers and outlines the theoretical and methodological opportunities it opens for future research. Originality/value The article strengthens the conceptual foundations of BO by complementing existing perspectives with an emergent, interaction-driven view of behavioral dynamics. In doing so, it lays the groundwork for investigations that closely align with the multilayered nature of everyday operational activities.
Purpose Supply chain management literature describes generative AI (GenAI) as transformative for operations, but its socio-technical consequences for the professional workforce remain underexplored. This study investigates how GenAI adoption reshapes core supply chain planning (SCP) roles. Design/methodology/approach Employing an exploratory multi-case study design, the study compares job specifications from GenAI adopter firms (Amazon, Tesla, Colgate-Palmolive and The Warehouse Group) with those of matched non-adopter firms across three deployment architectures. A strict separation between classification data (strategic documents, executive statements and technical publications) and analysis data (job specifications) prevents circular reasoning. Semi-structured interviews with senior SCP leaders were triangulated with the textual analysis to reveal day-to-day practices that formal documentation does not capture. Findings Two different archetypes emerge: the process guardian, who executes procedures within transaction-focused systems and the supply chain architect, who orchestrates adaptive planning across AI-enabled platforms. GenAI adoption produces an autonomy–ambiguity paradox, whereby planner authority expands while the decision space becomes harder to define. Formal hiring documentation lags behind operational deployment across firms. Four transition-specific paradoxes characterize the progression from early to advanced GenAI maturity in SCP roles. Originality/value A transformation framework models pathways from GenAI deployment to augmentation or overwhelm. A three-category typology of deployment maturity (GenAI-native, GenAI-augmented and build-phase) captures variations that binary adopter/non-adopter classification would collapse. A maturity model operationalizes this framework through diagnostic stages that comprise transition paradoxes and resolution requirements. Nine propositions structure future research on human–AI collaboration in SCP.
PurposeIncreasing volumes of product returns present significant challenges for many companies. Understanding how to develop strong capabilities in returns management has never been more important. However, a clear understanding of what constitutes returns management capability is largely missing in academic literature as well as in business practice. The purpose of this research is to identify key dimensions of returns management capability to guide future development.Design/methodology/approachThis research identifies specific dimensions of the broad returns management capability concept using a mixed-method research design. In the qualitative portions of this study, a literature review and an initial round of semi-structured interviews were conducted to identify and explore key dimensions of returns management capability. In the quantitative portion, data were collected and analysed to validate the identified dimensions. A latent profile analysis is also used to provide valuable insights. An additional round of qualitative interviews was conducted to generate additional insights.FindingsFive critical dimensions of returns management capability emerged from the analysis: customer interface, information systems support, processing, asset recovery and network design. The results of this research suggest that the development of returns management capability dimensions should have a sustainability orientation and be supported by enabling factors such as adaptability and cross-firm collaboration.Originality/valueTo the best of our knowledge, this is the first empirical research that takes a holistic view to explore specific returns management capability dimensions. The findings enable future research to explore returns management in enhanced depth and detail. Furthermore, the findings offer valuable guidance and a comprehensive assessment tool for companies to develop effective returns management strategies.
PurposeThis study aims to examine how supplier behavior, specifically relationship-specific adaptation and product quality, shapes two forms of buyer commitment: affective and calculative. Drawing on social exchange theory, we investigate how reputational power, operationalized as the non-coercive influence a supplier derives from its industry reputation, moderates these behavioral effects. We treat industry reputation not as a behavioral act but as a reputational form of non-coercive power that alters how buyers interpret suppliers' actions.Design/methodology/approachGuided by social exchange theory, this manuscript employs two field studies targeting purchasing professionals. Study 1 investigates how relationship-specific adaptation affects affective commitment, while Study 2 examines the impact of product quality on calculative commitment. Both models assess the moderating effect of perceived reputational power. Psychometric validity was evaluated using covariance-based structural equation modeling in Analysis of Moment Structures, and hypotheses were tested using Hayes' PROCESS macro in Statistical Package for the Social Sciences, employing moderated mediation models with bootstrapped confidence intervals.FindingsRelationship-specific adaptation increases affective commitment, while product quality drives calculative commitment. Reputational power strengthens the relational pathway but does not affect the economic one, indicating that buyers respond emotionally to reputation only when relational behaviors are present. Power's influence is thus relational rather than transactional.Practical implicationsSuppliers with high power can reduce adaptation yet retain loyalty and performance benefits. Managers should thus invest in building strong brand recognition, balancing the trade-offs between meeting demands and leveraging reputational capital. Meanwhile, buyers must avoid over-reliance on powerful suppliers to preserve bargaining capacity. The findings highlight that intangible factors like reputation can be as critical as product or service quality. Suppliers must ensure responsiveness to maintain trust. Overall, managing power asymmetries is vital for sustaining healthy, performance-enhancing buyer-supplier relationships.Social implicationsIn highlighting how supplier reputation can tilt relationship power, the study's findings have broader societal implications around fairness and collaboration in business partnerships. When powerful suppliers leverage their industry status, it can create unequal power dynamics that may pressure buyers into unfavorable terms, potentially affecting employee welfare, local communities and smaller firms with fewer resources. Conversely, understanding these dynamics encourages transparent, equitable relationships, prompting businesses to adopt fair negotiation practices, share information and foster trust. Consequently, better-managed power imbalances can lead to more ethical business conduct, greater social responsibility and potentially more inclusive supply chain ecosystems for all stakeholders.Originality/valueThis study introduces supplier industry reputation as a non-coercive form of power and shows how it differentially affects relational and economic forms of commitment. Guided by social exchange theory, we model relationship-specific adaptation and product quality as behavioral antecedents of affective and calculative commitment, respectively and test how supplier reputation - conceptualized as non-coercive power - moderates both pathways By distinguishing between affective and calculative commitment and modeling them in parallel, the study advances understanding of how social and economic value interact in supply chain relationships, re-centering power as a critical dynamic in an era dominated by relationship marketing.
Purpose Considering a growing emphasis on sustainability, companies that historically pursued offshoring for cost efficiency are now broadening their focus from shareholders to a wider range of stakeholders. In this regard, this study investigates how a company's performance in environmental, social and governance (ESG) areas can serve as a critical framework for evaluating global production realignment (GPR).Design/methodology/approach Utilizing a unique dataset of 1,755 firm-year observations collected over 14 years, this study analyzes the influence of the three ESG pillars - social responsibility, governance and environmental performance - on GPR announcements.Findings The results demonstrate that firms exhibiting higher levels of social responsibility are more prone to make GPR announcements, while robust governance is associated with a reduced likelihood of such announcements. Furthermore, controversies surrounding a firm moderate the relationship between social responsibility and GPR announcements, where fewer controversies significantly amplify the positive impact of social responsibility. Additional investigation also reveals that foreign incorporated firms exhibiting higher levels of environmental performance are less likely to make GPR announcements.Research limitations/implications This study examines GPR announcements in the United States and improves our theoretical understanding by clarifying the complex role that ESG dimensions play in GPR decisions. It also provides practical insights for managers on how to effectively incorporate ESG performance into their strategic decision-making processes.Practical implications Even though this dataset spans 14 years (from 2008 to 2022), it does not reflect the recent discussion around tariffs. To be fair, we might see that effect in GPR in a few years and not immediately.Originality/value This study is among the first to examine empirical data on reshoring and sustainability. Additionally, it emphasizes the importance of social and governance performance in relation to GPR announcements, while indicating that the impact of a firm's environmental performance is more nuanced. This study also explores the moderating role of controversies that have not been examined in the context of GPR announcements.
PurposeThis study quantifies the impact of technology-enabled delivery platform partnerships on the direct channel sales of restaurant chains.Design/methodology/approachWe leverage a proprietary dataset that tracks expenditures from over 9 million individuals across the USA. The analysis assesses the influence of delivery platform partnerships on direct-channel sales. To identify the causal impact, we use difference-in-difference models with propensity score matching.FindingsOn average, each delivery platform partnership results in a 1.36% increase in physical channel sales and a 42.6% increase in direct, online sales for the restaurant chains' websites and mobile applications. Moreover, our moderation analysis reveals the following: (1) restaurant chains with sparse physical store networks in a market derive greater increases in store sales from delivery platform partnerships than do chains with dense physical networks and (2) deeper channel integration, where restaurants offer delivery options from their own websites (with fulfillment services contracted to delivery platforms), leads to higher online sales from delivery platform partnerships.Practical implicationsThe results suggest that delivery platform partnerships are especially attractive in generating direct-channel revenues for restaurant chains in markets with sparse physical store presence and when customers can access delivery services directly through restaurant chains' websites or applications. This revenue information, combined with a restaurant chain's costs of partnering with delivery platforms, can indicate which markets may be the most profitable for delivery platform partnerships.Originality/valueWe add to segmentation research in logistics by examining how platform partnerships differentially affect two key segments: physical and online direct-sales customers. We extend the channel-capabilities literature by analyzing how a delivery-platform channel, with its distinct search and fulfillment capabilities, reshapes outcomes in the direct sales channels of restaurants. We further contribute to the delivery-platform literature by testing the moderating roles of two operational strategies, physical store presence and direct-fulfillment service, on physical and online sales. Finally, we provide practical guidance: Collaborating with platforms expands, rather than substitutes for, higher-margin direct-channel sales.
PurposeThis study develops a structured framework for supplier risk assessment that supports the empirical assessment of supplier-level resilience capabilities. The framework integrates specific and overarching risk dimensions, factors and indicators, thereby enabling companies to proactively identify and manage potential disruptions. It addresses existing research gaps by consolidating fragmented perspectives into a coherent structure that enables empirical investigation and operationalization.Design/methodology/approachA node-level approach combines a structured literature review with expert workshops to derive operationalizable supplier-specific indicators that facilitate empirical investigation and cross-sector validation. The literature review identified essential risk dimensions, associated factors, and operational indicators, each linked to potential information sources. These were validated and weighted through expert workshops, forming the basis of a measurement approach intended as an assessment instrument for future application and testing.FindingsThe resulting framework comprises environmental, financial, social and operational risk dimensions, each associated with structured risk factors and indicators, providing a foundation for assessing supplier-specific vulnerabilities. By explicitly assigning information sources, such as certifications, indices, and internal records, the framework facilitates data acquisition. The expert workshops corroborated the relevance of a flexible model that allows for industry-specific adaptation while remaining amenable to model building.Originality/valueThis novel framework provides an integrated, multi-layered structure that translates resilience concepts into testable components for supplier risk assessment. It bridges theoretical constructs and operational indicators, paving the way for systematic supplier risk assessment across industries.
