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PurposeThe objective of this paper is to develop a comprehensive model of supply chain and supply chain decision‐making complexity that provides an understanding of the drivers of supply chain complexity and strategies to manage supply chain and supply chain decision‐making complexity and outcomes.Design/methodology/approachGrounded theory methodology is employed to build a theory of supply chain and supply chain decision‐making complexity and develop propositions related to antecedents, moderators, and outcomes of supply chain complexity. In addition, extensive literature review and informal interactions with a number of supply chain professionals have been used to validate the theory.FindingsIn addition to identifying the antecedents of supply chain complexity, the authors explore strategic, human cognitive ability, and tactical moderators for managing supply chain complexity.Research limitations/implicationsThe comprehensive framework presented in the paper builds a theory of supply chain and supply chain decision‐making complexity that is grounded in empirical data. The research also incorporates disparate findings, constructs from multi‐disciplinary research on supply chain complexity and provides future research directions.Practical implicationsThe research helps practitioners better understand the sources and outcomes of supply chain complexity and how to manage it. Various strategies to moderate the impact of supply chain complexity are presented.Originality/valueAn integrated, comprehensive theory of supply chain complexity is proposed along with definitions of supply chain complexity and supply chain decision‐making complexity. The proposed model is rooted in actual practice and supported by the existing literature.

PurposeGlobal supply chains are more risky than domestic supply chains due to numerous links interconnecting a wide network of firms. These links are prone to disruptions, bankruptcies, breakdowns, macroeconomic and political changes, and disasters leading to higher risks and making risk management difficult. The purpose of this paper is to explore the phenomenon of risk management and risk management strategies in global supply chains.Design/methodology/approachThis paper is based on an extensive literature review and a qualitative study comprising 14 in‐depth interviews and a focus group meeting with senior supply chain executives.FindingsThe study provides insights into the applicability of six risk management strategies with respect to environmental conditions and the role of three moderators.Research limitations/implicationsThe model is developed in a global manufacturing supply chain context. It should be tested in other contexts and with other methods to provide generalizability. The study takes a much needed step toward building a theory of risk management in global supply chains, which opens important future research directions.Practical implicationsThis research provides direction to managers for choosing risk management strategies based on the global supply chain environment. Moderators have practical implications for global supply chain managers.Originality/valueThe paper addresses an identified gap in the literature for selecting risk management strategies in global supply chains. It employs grounded theory, a methodology appropriate for theory‐building, to explore a phenomenon with an inadequate theoretical base.

Purpose
While, supply chain resilience (SCRES) continues to be a dominant topic in both academic and business literature and has gained more attention recently, there is limited knowledge on SCRES capabilities specific to business functions. The purpose of this paper is to identify and investigate capabilities shared between supply, operations and logistics that are most important for SCRES.


Design/methodology/approach
To address this gap, the authors followed a multi-method research approach. First, the authors used the grounded theory method to generate a theoretical framework based on interviews with 51 managers from five companies in automotive SCs. Next, the authors empirically validated the framework using a survey of 340 SC professionals from the manufacturing industry.


Findings
Five significant capabilities emerged from the qualitative study; all were significant in empirical validation. This research advances the knowledge of SCRES as it informs managerial decision-making by identifying capabilities common to supply, logistics and operations that impact SCRES.


Originality/value
This research advances the knowledge of SCRES as it informs managerial decision-making by identifying capabilities common to supply, logistics and operations that impact SCRES. In addition, the findings of this research help managers better allocate resources among significant capabilities.

Purpose
The purpose of this paper is to understand and measure empirically the objective and perceived dimensions of supplier-induced complexity in supply chains.


Design/methodology/approach
An equal-weight, complementary mixed-method approach is used to investigate supplier-induced complexity and understand its impact on outcomes. Initial qualitative research and extant literature review allowed the identification of supplier characteristics that add complexity to supply chains and development of four research hypotheses. Subsequently, quantitative analysis was used for testing the hypotheses.


Findings
The results suggest that supplier-induced complexity is related to adverse outcomes, and both perceived and objective dimensions of complexity are valuable in understanding and measuring supplier-induced complexity.


Research limitations/implications
This study employs a mixed-method approach to establish and test relationships among perceived and objective supplier-induced complexity, and their outcomes. The unit of analysis is the first-tier suppliers of one farm equipment manufacturing firm. This limits the generalizability of the results to similar industrial manufacturing firms.


Practical implications
This paper presents an approach to identify suppliers that add the highest levels of complexity to a supply chain and, thus, require closer monitoring. Specific supplier characteristics are identified for individual suppliers. Developing specific complexity-related measures helps better identify critical suppliers compared to traditional approaches (e.g. ABC analysis).


Originality/value
This paper contributes to supply chain management literature by comprehensively exploring supplier-induced complexity, incorporating the often-ignored perceived complexity dimension, and providing a managerially useful framework.

PurposeThe purpose of this paper is to analyze previous grounded theory articles and, based on this analysis, to provide a framework to assist reviewers in evaluating grounded theory research and increasing the rigor and credibility of this methodology in logistics and supply chain journals.Design/methodology/approachAn analysis of existing articles appearing in the leading logistics and supply chain journals combined with an extensive review of the grounded theory method literature were used to develop a comprehensive framework for evaluating grounded theory research.FindingsThe paper finds that no standard criteria for publication of grounded theory research exists in logistics and supply chain journals. Grounded theory is routinely confused with other qualitative methodologies. Overall, this situation leads to publications that do not adequately address or report on the process for developing a grounded theory.Research limitations/implicationsReviewers can use this paper to establish the quality of grounded theory research. Reviewers who are unfamiliar with or skeptical of the grounded theory method can use the framework to evaluate the rigor and credibility of a grounded theory study rather than rejecting such research. The checklist can be used to provide thorough and constructive reviews to authors.Originality/valueThe paper presents a framework that provides a ready reference for reviewers to assess whether the authors have taken appropriate action in selecting a grounded theory methodology, collecting and analyzing data, developing a theory grounded in the data, and for evaluating their research. Existing research is compared with the framework to identify potential shortcomings in the review process. The application of the framework to the review of future articles provides an opportunity to increase the credibility and rigor of grounded theory research in logistics and supply chain management journals.

PurposeThe purpose of this article is to identify and explain most frequently misunderstood steps in the use of grounded theory (GT) as a methodology and provide guidance on proper execution of these elements.Design/methodology/approachThis research provides meaningful guidance to both reviewers and authors interested in applying GT. This research is expected to advance the pursuit of formal theory development.FindingsThere are four most frequently misunderstood steps in the use of GT as a methodology. These are related to the use of literature, theoretical sampling, core category and formal theory development. Proper execution of these elements is important for convincing reviewers and readers that the findings of the research are meaningful and trustworthy.Originality/valueThis paper should be of significant value to researchers who are interested in GT as a methodology. It adds to the few journal articles that address the proper ways to conduct GT.

PurposeThe purpose of this paper is to present an eight‐step simulation model development process (SMDP) for the design, implementation, and evaluation of logistics and supply chain simulation models, and to identify rigor criteria for each step.Design/methodology/approachAn extensive review of literature is undertaken to identify logistics and supply chain studies that employ discrete‐event simulation modeling. From this pool, studies that report in detail on the steps taken during the simulation model development and model more than one echelon in logistics, supply chain, or distribution systems are included to illustrate rigor in developing such simulation models.FindingsLiterature review reveals that there are no preset rigor criteria for publication of logistics and supply chain simulation research, which is reflected in the fact that studies published in leading journals do not satisfactorily address and/or report the efforts taken to maintain the rigor of simulation studies. Although there has been a gradual improvement in rigor, more emphasis on the methodology required to ensure quality simulation research is warranted.Research limitations/implicationsThe SMDP may be used by researchers to design and execute rigorous simulation research, and by reviewers for academic journals to establish the level of rigor when reviewing simulation research. It is expected that such prescriptive guidance will stimulate high quality simulation modeling research and ensure that only the highest quality studies are published.Practical implicationsThe SMDP provides a checklist for assessment of the validity of simulation models prior to their use in practical decision making. It assists in making practitioners better informed about rigorous simulation design so that, when answering logistics and supply chain system questions, the practitioner can decide to what extent they should trust the results of published research.Originality/valueThis paper develops a framework based on some of the most rigorous studies published in leading journals, provides rigor evaluation criteria for each step, provides examples for each step from published studies, and illustrates the SMDP using a supply‐chain risk management study.

PurposeDespite the proliferation of cyberthreats upon the supply chain (SC) at large, knowledge on SC cybersecurity is scarce and predominantly conceptual or descriptive. Addressing this gap, this research examines the effect of SC cyber risk management strategies on integration decisions for cybersecurity (with suppliers, customers, and internally) to enhance the SC's cyber resilience and robustness.Design/methodology/approachA research model grounded in the supply chain risk management (SCRM) literature, with roots in the Dynamic Capabilities View and the Relational View, was developed. Survey responses of 388 SC managers at US manufacturers were obtained to test the model.FindingsAn impact of SC cyber risk management strategies on internal cyber integration was detected, which in turn impacted external cyber integration with both suppliers and customers. Further, a positive effect of internal and customer cyber integration on both cyber resilience and robustness was found, while cyber integration with suppliers impacted neither.Practical implicationsIndustry practitioners may adapt certain risk management and integration strategies to enhance the cybersecurity posture of their SCs.Originality/valueThis research bridges between the established domain of SCRM and the emergent field of SC cybersecurity by forming and testing novel relationships between SCRM-rooted constructs tailored to an SC cyber risks context.

PurposeThe proliferation of ride-hailing businesses brings significant considerations for improving the driver's operational performance. Informed by the literature on sharing economy, general deterrence theory and protection motivation theory this research investigates the behavioral factors impacting ride-hailing drivers' operational performance.Design/methodology/approachThe authors empirically test the antecedents impacting a ride-hailing driver's operational performance using an online survey dataset comprising 513 ride-hailing drivers working for Uber and Lyft in the United States.FindingsRide-hailing drivers' intention to comply with the ride-hailing company guidelines results in better operational performance for the driver. Moreover, drivers believe that ride-hailing companies have effective penalties to deter drivers from violating company guidelines. However, drivers also believe that the chances of being caught while ignoring the company guidelines are low.Practical implicationsThe results of this research support the decision-making processes of ride-hailing company managers and offer insights on how managers can enhance the operational performance of their drivers.Originality/valueThis study provides unique contributions to emerging research at the intersection of peer-to-peer asset sharing, behavioral studies and technology management. This research is one of the first to explore the role of behavioral factors such as coping mechanisms on the operational performance of sharing economy workers.

PurposeDrawing on the social identity theory, this paper explores the impact of rider–driver ethnicity match on the driver's expected ride satisfaction and willingness to perform, and rider's trust on the driver.Design/methodology/approachThe study relies on scenario-based online experiments with 291 ride-hailing drivers and 282 riders in the USA.FindingsThe findings indicate that ethnicity match between ride-hailing drivers and riders positively impact driver's ride satisfaction and willingness to perform, and rider's trust in the driver. The study also revealed a significant positive moderation effect of ethnic identity on the relationship of ethnicity match and those constructs.Practical implicationsWhile it may be challenging to influence an individual's level of ethnic identity, managers can take steps to educate and train their employees regarding the impact of ethnic identity and discrimination, with a particular focus on those individuals who possess a strong sense of ethnic identity.Originality/valueThe findings of this research provide theoretical contributions to the existing literature on ride-hailing services and adds to the limited stream of logistics research that examines the impact of ethnicity on ride-hailing operations.

PurposeThis paper investigates the integration of middle mile drones (MMD) into logistics operations, addressing two key questions: (1) What are the drivers, financial implications and upcoming innovations associated with integrating drones into MM logistics? and (2) What challenges need to be overcome for successful implementation of drones in MM logistics?Design/methodology/approachThe study combines expertise from an industry professional with over ten years of experience in drone operations and logistics applications, along with insights gained from discussions with 33 industry executives.FindingsThe research identifies several unique advantages of integrating drones into MM logistics, including their potential to improve operational efficiency in challenging environments. However, significant challenges related to scalability, evolving airframe designs and operational constraints remain. Early-stage use cases demonstrate the viability of MMD technologies in lower-risk logistics environments, but broader implementation requires overcoming the identified challenges.Research limitations/implicationsAs MMD logistics is a nascent field, the study is exploratory and based on early-stage use cases and expert discussions. The limited scope of practical implementations may restrict the generalizability of the findings. Future research should focus on larger-scale operations and empirical studies of MMD integration in diverse logistics contexts.Practical implicationsThe findings offer valuable insights for practitioners related to the costs, benefits and challenges of integrating drones into logistics operations and for policymakers related to societal implications, workforce development, privacy and safety concerns, and environmental impact.Originality/valueThis paper contributes to the evolving understanding of drone applications in MM logistics by presenting early use cases and identifying both challenges and opportunities for MMD technology and offers a foundation for future research and practice in this emerging domain.