This study investigates problems related to the high variance in the success rate of lean implementations, using a unique data set from a specific approach to implementing lean. We develop insights about how to effectively resolve the ‘Lean paradox’, namely that Lean concepts promise so much in theory yet deliver infrequently in practice. Our primary data of 268 Lean implementation initiatives illuminates the core elements of lean implementation success that explain this success variance. We present an in-depth case study of that specific method of lean implementation. Lean implementation success occurs when specific processes are followed, namely integration of job role and process analysis, comprehensive end-to-end deployment rather than spot-based problem solving, use of operator-based data about processes and waste, detailed level of data and change deployment focussed on waste reduction, and ongoing measurement and control of process changes. These ‘how’ factors provide both conceptual and practical insights for managers. JEL Classification: M11

PurposeThis study aims to develop a basis for understanding the antecedents, or trigger mechanisms, for buying firms encountering resurgent supplier sustainability incidents after prior exposure to stakeholder criticism.Design/methodology/approachThe authors use a sample of 52,781 media items for firms listed in the S&P 500 index from 2007 to 2021. Data was drawn from RepRisk and Compustat and analyzed via hierarchical linear regression and PROCESS modeling.FindingsThe resulting analyses demonstrate that the media plays a vital role in how novel versus resurgent supplier sustainability incidents are reported contingent upon severity and novelty. Moreover, the institutional distance (ID) between the buying firm and supplier impacts how much traction the incidents gain in terms of media attention.Research limitations/implicationsThis is among the very first studies, to the best of the authors' knowledge, that investigate the mechanisms through which buying firms decide how to navigate resurgent supplier sustainability incidents. The authors relied on media reports as a source of data, which can show little or no partiality when identifying repeat offenders in terms of environmental, social and governance issues.Practical implicationsThe findings can inform buying firms and their stakeholders on how supplier sustainability incidents are affected by various factors, and such can be directed toward mitigating resurgent incidents by understanding the antecedents.Social implicationsThis study has implications for public awareness with respect to patterns of supplier sustainability incident resurgence and media reach. The findings can inform regulatory frameworks by drawing attention to contexts, particularly when ID is higher. Lastly, scholars should remain mindful that publicizing firm-level findings can reinforce reputational harm, particularly in cases where incidents are contested or resolved.Originality/valueThis research contributes to the literature on sustainability supply chain management, particularly on when/where/why sustainability risks resurface in supply chains by outlining the interplay between the severity of supplier sustainability incidents and their reach among stakeholders. The research also emphasizes ID as an umbrella effect, which moderates buying firms' decisions toward their supplier's sustainability-related grievances.

Recent global disruptive events have emphasized the importance of selecting partners with non-conflicting relationships to create a stable operating supply chain. To address this challenge, this research developed a methodological system for building supply chains that utilizes configuration theory and a portfolio perspective. The method objectively extracts the configuration structure using theLatent Dirichlet allocation (LDA) method and confirm comprehensive partner selection criteria through case studies with different strategic orientations. This approach provides a holistic and detailed criteria framework for supply chain partner selection. Additionally, a framework has been designed for an optimal partner portfolio selection process that employs Three-way Decision methods to identify the relationship set, offering a standardized and objective way to improve the efficiency and effectiveness of partner selection. The results illustrate that the methodology can effectively identify the optimal partner portfolio for supply chain building, minimize management costs and risks, and ensure supply chain stability and sustainability. Empirical evidence from a pharmaceutical enterprise supply chain supports the robustness and rationality of our proposed method.

Building resilience against global disruptions is vital for modern supply chains. This research explores under-researched aspects of closed-loop supply chain (CLSC) resilience, focusing on network structure and resilience enablers. It examines the multi-directional ripple effect in CLSCs, where disruptions spread forward (production/distribution), laterally (same-tier facilities), and backward (reverse logistics), analysing them as complex, interconnected systems, unlike prior studies on simpler networks. We simulate real-world disruption/recovery scenarios to evaluate the resilience of various CLSC structures against global disruptions. This analysis highlights how the combination of proactive planning, reactive response, and agility can enhance resilience, demonstrating their synergistic impact. The study also investigates the impact of supplier diversification on resilience, showing that while diversification improves performance under localised disruptions, its effectiveness diminishes when disruptions become global. Based on the findings, we propose a bi-objective optimisation model that balances resilience gains with cost constraints, focusing on supplier diversification for optimal CLSC performance. A case study in Australia validates the model, demonstrating resilience improvements of 20% with $15,000, 27.1% with $30,000, and 32.9% with $50,000 relative to the baseline. This research provides decision-makers with flexible strategies, integrating a proactive-reactive approach, strategic and real-time agility, and supplier diversification to enhance CLSC resilience while considering budget.

Policymakers have portrayed the tariff rate on imports as an enabler for domestic firms to exploit opportunities and improve performance. However, a large tariff increase (LTI) may hinder domestic firms’ access to affordable operational inputs from overseas, potentially reducing their operational efficiency (OE). This study treats 52 LTIs imposed by the United States (U.S.) between 1990 and 2020 as exogenous shocks and employs a quasi-natural experiment to assess their impact on 258 U.S. domestic firms. Specifically, we examine the impact of LTI through the lens of downside risk and upside opportunity, measuring it in terms of the downside loss and upside gain in OE. The results indicate that LTI has adverse effects in both respects: it increases the downside loss and decreases the upside gain of OE. LTI has a more pronounced negative impact on the upside gain than on the downside loss of OE, indicating that it more severely limits domestic firms’ ability to exploit opportunities. We also find that the availability of a potential domestic supply base and the top management team’s supply chain management experience mitigate the negative effects of LTI on both the downside loss and upside gain of OE. This study reveals the holistic effects of LTI on OE and identifies mitigating factors from an operations and supply chain management perspective.

The resilience of supply chain networks (SCNs) is critical for economic stability. This study examines SCN resilience by analysing their response to disruptions in complex, multi-tier structures. Using a network generator algorithm, we simulated disruption impacts and recovery across SCNs ranging from two to seven tiers. Resilience was assessed through average functionality and recovery duration, leading to eight significant observations. The study addresses literature gaps by exploring tier-specific effects, realistic disruption dynamics, facility and connection disruptions, and the role of intra-/inter-tier connections. It evaluates mitigation strategies such as redundancy, supplier diversification, and government support. Case studies on a biofuel SCN and a municipal solid waste system are included in the supplementary material. Results indicate that disruptions persist longer in higher tiers, with Tier 7 experiencing up to 26% disruption duration, compared to 3% and 7% in the first and second tiers. Increasing redundancy reduces recovery time by up to 57% in seven-tier SCNs while expanding the supplier base from one to two regions cuts recovery time by up to 50%. These insights offer strategies for enhancing SCN resilience and guiding future research.

Multinational corporations increasingly choose flexible suppliers over low-cost options to manage uncertainties effectively. While previous research highlights the importance of buyer network design for supplier flexibility and reconfiguration, the literature barely discusses supplier network flexibility based on a supplier’s network position (e.g., centrality). The structural flexibility of the buyer network is often overlooked despite its crucial role in recovery from disruptions. Furthermore, prior research exploring supplier centrality enhances a focal buyer’s performance and provides limited insight into suppliers’ financial performance within the buyer network. Additionally, the dimensions of business environmental uncertainty are likely to interact with supplier network flexibility in the buyer network, affecting supplier financial performance. However, the literature also offers little insight into this aspect. Therefore, this study investigates the impact of the interplay between supplier network flexibility (eigenvector and closeness centralities) and business environmental uncertainty (dynamism, munificence, and complexity) on supplier financial performance. This study relies on social network theories and the literature on supplier network flexibility, environmental uncertainty, and financial performance. It develops a section of Toyota’s triadic buyer network at the corporate level, with this network involving 6152 suppliers and 14,156 relationships. Using a hierarchical moderated regression model, this study finds that higher closeness and eigenvector centralities positively impact supplier financial performance, with dynamism and complexity positively moderating these effects, whereas munificence negatively moderates them. These findings offer insights into how central suppliers can enhance their financial performance and strategically position themselves within buyer networks to adapt to business environmental uncertainties.

To exercise risk control at the corporate level, firms often appoint Chief Risk Officers (CROs) to their top management team. By establishing CRO positions, firms can reduce firm risk and potential financial losses caused by operational disruptions. Yet, by inducing stringent control measures on risks, security, and compliance, CRO appointments might create unwieldy bureaucracies with operational hurdles and incur burdensome costs that offset efficiency. Using longitudinal secondary data collected from multiple sources, we analyze the impact of CRO appointments on firm risk and operational efficiency of 435 publicly listed firms in the United States from 2006 to 2016. Our results indicate that CRO appointments not only reduce risks, but also improve efficiency in operations. We delve into the power of CROs and find that more powerful CROs are more effective in enhancing the operational efficiency of firms. We further examine the contextual factors and reveal that firms operating under high industry litigation threats and industry dynamism improve operational efficiency to a greater extent after CRO appointments. Overall, CROs' appointments are more beneficial to firms when they have stronger power in the top management team and when the operating environments are uncertain and volatile.

Contemporary supply chains are facing myriad types of risks caused by unprecedented risk factors. This condition motivates us to develop a contemporary supply chain risk typology to help identify and monitor newly surfaced risks and reveal emerging topics and research collaborators to help foster impactful research in supply chain risk management (SCRM). In this paper, we applied the scholarly network analysis approach to critically analyse an extensive list of 345 SCRM journal articles published from 2011 to 2020. We address two research questions: What is the contemporary supply chain risk typology? How can SCRM research be mapped comprehensively in terms of its emerging topics and research collaborators? First, we propose a novel and holistic classification of supply chain risks based on three interconnected perspectives, namely the characteristics, the location, and the impact of risks. Second, we identify five emerging SCRM topics. In each of these emerging topics, we identify the prominent collaborators and the core author, the main research themes, commonly used approaches and theories, and potential research agendas for bridging the identified research gaps. This paper contributes to the field of SCRM by aiding scholars and practitioners in managing contemporary supply chains resiliently and sustainably.

Interorganizational fraud, or fraud that occurs between organizations, is a critical component of supply chain fraud and supply chain relational risk, yet empirical evidence on the scale of interorganizational fraud and its antecedents remains scant. Despite its hidden nature, interorganizational fraud can have major implications for supply chain performance. Based on the theories of transaction cost economics, agency theory, and the fraud triangle, widely used in accounting and auditing research, five potential antecedents of supply chain fraud are considered and compared with reported losses due to interorganizational fraud. The data collected via a survey questionnaire with a sample of 151 supply chain employees in manufacturing demonstrate that informants estimated median losses due to interorganizational fraud to be 9% of their firm's total revenue. The most common types of fraud reported include product quality fraud, pricing/invoicing fraud, and corruption. Using a two-step generalized method of moments technique for estimation, the results found that transactional complexity, competitive pressures facing the supply chain, and weak firm ties were significantly related to interorganizational fraud, and that supply chain monitoring and ethical sourcing were not significantly related to interorganizational fraud. These findings contribute to the research on relational risk, supply chain risk management, and opportunism.

Efficiency measurement is a key and strategic factor in improving an organization’s performance and increasing their competitive advantage. Nevertheless, measuring efficiency in settings with multicomponent production technologies is a major issue with the existing approaches in the literature. The main contribution of the current paper is to develop a novel nonparametric approach to evaluate efficiency and obviate some of the theoretical barriers in multi-output settings. To this end, for the first time, new technologies assuming multiple hybrid returns-to-scale (MHRTS) with output-specific inputs, joint inputs, and outputs are developed. The new technologies are based on some of the axiomatic principles in data envelopment analysis (DEA) for forming a new production possibility set (PPS) to measure the efficiency of decision-making units (DMUs). By implementing the MHRTS technologies with output-specific inputs, joint inputs, and outputs, the proposed models can deal with undesirable outputs. Compared with the existing technologies in the DEA literature, the new technologies not only can incorporate output-specific inputs, joint inputs, and outputs for the performance evaluation of DMUs but also obviate existing theoretical barriers in the MHRTS technology. The applicability and usefulness of the proposed method are validated using a case study in the energy sector.

In era of reglobalization, sustainably resilient supply chains (SCs) are imperative in corporations to improve performance and meet stockholders’ expectations. However, sustainably resilient SCs could not be effective if are not assessed by using advanced frameworks, systems, and models. As such, developing a novel network data envelopment model (DEA) to appraise sustainably resilient SCs is our purpose in this article. To do so, we present a new double-frontier methodology to provide optimistic and pessimistic efficiency measures in network structures. Moreover, ideas of outputs weak disposability, chance-constrained programming, and discrete dominance are incorporated in a unified framework of modelling efficient and inefficient production technologies. The new network DEA model also can address dissimilar types of data, including undesirable and integer-valued and ratio outputs, stochastic intermediate products, and integer-valued inputs in a unified framework. Furthermore, an aggregated Farrell type efficiency measure is developed which allows to provide the complete ranking of units so that each decision-making unit (DMU) has its own rank in both overall and divisional point of view. We show the unique features of our developed model using a real case study in paint industry to evaluate the efficiency and reducing carbon dioxide (CO2) emissions. The results show that how well the proposed models can evaluate the sustainability and resilience of supply chains in the presence of uncertainty and with dissimilar types of data.

This study investigates students' perceptions in a formative feedback initiative introduced in a quantitative management subject. It uses data from 157 undergraduate and graduate students over two semesters collected via a survey and focus group discussion. It provides a novel contribution to the under-researched area of formative feedback in business education. Results were generally positive, with over 75% of the students agreeing that formative feedback is useful. They reported positive results across the survey questions relating to ease of and keenness to the feedback activity, their enjoyment in participating, improvement in their understanding, the usefulness of the feedback, and whether they would recommend such activity in other subjects. Results from the focus groups also reiterate these positive perceptions, where students highly regarded the immediacy and usability of the feedback in their learning and the engaging and non-threatening nature of the activity. Implications include practical uses and applicability to other disciplines.

In “Operations Research: Topics, Impact and Trends from 1952–2019,” A. Calma, W. Ho, L. Shao, and H. Li retrospectively look at 68 years of publication of the Operations Research. Using 5,440 journal articles, they highlight the top contributing countries and authors and top research methods and problems investigated. Mathematical programming is the most common research method, whereas inventory is the most investigated problem. Investigations related to pricing are growing significantly. The United States, Canada, and the United Kingdom publish the most papers, with the United States and Canada having similar publication profiles per capita. Inventory is the most popular research problem studied by North American, Asian, and Middle Eastern countries, whereas European countries focus on scheduling problems. Network visualizations of the journal’s last 10 years show dynamic programming as the most used method and pricing as the most studied problem. Coauthor networks on collaborations on both dynamic programming and pricing are also shown.

This paper considers a three-tier supply chain in which a manufacturer uses raw materials sourced from multiple suppliers to produce an item and sells it through multiple distributors. We develop an integrated optimisation model to study supply chain procurement and distribution decisions incorporating the manufacturer’s aversion to risk and the distributors’ concern for fairness in a climate of uncertain supply and demand. Resilient strategies, such as alternative sourcing and transshipment, are also considered when optimising the supply chain cost and service level. To solve the problem, a Monte Carlo simulation-based multi-objective stochastic programming model is built. It uses the CVaR (Conditional Value-at-Risk) and unfairness aversion utility function to reflect the decision maker’s risk aversion and the customer’s concern for fairness, respectively. A Normalised Normal Constraint based algorithm is adopted to obtain the Pareto Frontier. In addition, the numerical analysis provides some valuable insights for supply chain managers.

Rapid new product introduction is an effective method for firms to capture market share. Considering the growing concerns of environmental threats, firms are under intense pressure to measure their impacts on the environment. Before launching a new product, a firm should make the appropriate decision regarding the order quantity with incomplete information to achieve the goals of both profit maximization and environmental threat minimization simultaneously. In this paper, distribution-free news vendor models with the environmental constraints are proposed to obtain efficient order decisions. The models are formulated based on the absolute minimax regret criterion. Based on the moment bound problem framework, the models are translated into a semi-infinite linear optimization problem. In addition, the closed-form solutions of the robust order quantities and carbon emission volumes are derived. The characteristics of effective order decisions are discussed under three types of carbon emissions regulations (i.e., the carbon capacity policy, carbon tax scheme, and carbon trading mechanism). By analyzing the product characteristics from both economic and environmental aspects, four possible new product introduction strategies are proposed that the firm might employ under different environmental constraints. The characteristics of the optimal order quantity are also investigated under three carbon emissions regulations across four new product introduction strategies.