{"title":"Additive manufacturing scenario for automotive spare parts supply: A case study approach","authors":"Alexander Bade, Rainer Lasch, Nick Schneider","doi":"10.1016/j.ijpe.2025.109552","DOIUrl":"10.1016/j.ijpe.2025.109552","url":null,"abstract":"<div><div>The rise of Industry 4.0 technologies is transforming the automotive industry. Additive manufacturing is one innovation that could prove pivotal in the automotive spare parts supply chain. On-demand production, enabled by additive manufacturing, could lead to significant cost savings by reducing inventory. The complex structure of the automotive supply chain offers many opportunities for the positioning of additive manufacturing and realizing the potential for production closer to the point of use. While several scenarios for the positioning of additive manufacturing have been proposed in the literature, there is a lack of empirical research and case studies evaluating the practicality of the scenarios. An embedded single case study was conducted with eight key informants from the automotive industry to extend the theory and examine the feasibility of the scenarios from the literature in practice. The findings suggest the implementation of additive manufacturing in a regional distribution center or outsourcing to additive manufacturing service providers. Both scenarios have shortcomings that are of practical importance. Implementing additive manufacturing in various regional distribution centers would require greater investment by the original equipment manufacturer while outsourcing to additive manufacturing service providers would entail costly certification procedures. With this in mind, a two-stage implementation scenario was developed and validated. This scenario proposes the production of spare parts in a regional distribution center or at an additive manufacturing service provider, depending on the complexity of the manufacturing process. The responsibilities of each participant in the automotive supply chain are discussed, and an exemplary process flow is presented.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"282 ","pages":"Article 109552"},"PeriodicalIF":9.8,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143266816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Beyond efficiency: Revisiting AI platforms, servitization and power relations from a critical perspective","authors":"Başak Canboy , Wafa Khlif","doi":"10.1016/j.ijpe.2025.109550","DOIUrl":"10.1016/j.ijpe.2025.109550","url":null,"abstract":"<div><div>This study examines the evolving power dynamics within servitization ecosystems, and especially the role of AI platform providers in them. Drawing on French and Raven's (1959) bases of power, as well as resource dependence theory, we propose a conceptual model that shows how AI providers centralize control and reshape power relations. As AI integrates into servitization, providers leverage informational and expert power through data management and algorithmic expertise, alongside legitimate and referent power, to influence behaviours, promote risk-taking, foster dependency, and establish themselves as central authorities setting standards and norms. They further exploit coercive and reward power to impose conditions and offer incentives that deepen platform reliance, ultimately dominating the ecosystem and establishing a quasi-monopolistic position. We enrich the servitization literature by challenging the prevailing view that AI adoption benefits downstream manufacturers.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"282 ","pages":"Article 109550"},"PeriodicalIF":9.8,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143436424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Manufacturers’ performance with industrial symbiosis under cap-and-trade policy considering waste supply-demand mismatch","authors":"Quanyao Cao , Zhongdong Xiao , T.C. Edwin Cheng , Qiangfei Chai","doi":"10.1016/j.ijpe.2025.109523","DOIUrl":"10.1016/j.ijpe.2025.109523","url":null,"abstract":"<div><div>As a circular economy subfield, industrial symbiosis could relieve resource scarcity and ecological damage. This paper considers an industrial symbiosis chain in which a downstream manufacturer can replace raw materials with waste from an upstream manufacturer for production. We develop a two-stage Stackelberg game to investigate the effects of industrial symbiosis on firm performance under the cap-and-trade policy. We also study the emissions-dependent price scenario, where the price considers the consumer's green preference. Contract design between firms in an industrial symbiosis chain is explored. We obtain the following findings. First, the cap-and-trade policy can encourage manufacturers to make abatement investments when emissions allowances reach certain thresholds. Second, the cap-and-trade policy hinders the upstream manufacturer's emissions reduction due to industrial symbiosis when the waste demand does not exceed supply. Third, industrial symbiosis could improve the downstream manufacturer's abatement level under moderate regulations and increase its emissions reduction amount under stringent regulations. Finally, the two manufacturers can achieve a win-win outcome through industrial symbiosis under the cap-and-trade policy, and a quantity discount contract can achieve Pareto improvement.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"282 ","pages":"Article 109523"},"PeriodicalIF":9.8,"publicationDate":"2025-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143419260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Reselling or hosting? Examining platform’s co-opetition strategy with third-party sellers","authors":"Xuhong Wang , Yongbo Xiao , Yifan Dou","doi":"10.1016/j.ijpe.2025.109520","DOIUrl":"10.1016/j.ijpe.2025.109520","url":null,"abstract":"<div><div>E-commerce retailers (etailers) often run the self-operated storefronts while hosting stores from third-party sellers (3PSs), which potentially causes the price competition in between. Besides, the etailer may be better off because of the commission contributed by these 3PSs’ stores. Motivated by the real-world practice, our paper studies the cooperation and competition strategy with 3PSs from the perspective of an etailer. Specifically, our paper extends the prior literature from two aspects: (1) we look into the scenario where the 3PS serves as the supplier such that a co-opetition case emerges; (2) we compare the cases with exogenous and endogenous wholesale prices. Benchmarked by a standard two-channel structure, we find that, when the 3PS plays a dual role (i.e., a supplier and a marketplace seller), co-opetition is more preferred as the 3PS is better off when the etailer opens a competing, self-operated store, suggesting a more nuanced relationship between the etailer’s platform and 3PSs. What is more, a powerful etailer can capitalize its advantage of consumer reach by inducing the supplier to choose a particular channel structure.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"282 ","pages":"Article 109520"},"PeriodicalIF":9.8,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143266871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Design of supply chain resilience strategies from the product life cycle perspective","authors":"Yi Yang , Chen Peng , En-Zhi Cao","doi":"10.1016/j.ijpe.2025.109532","DOIUrl":"10.1016/j.ijpe.2025.109532","url":null,"abstract":"<div><div>Supply chain (SC) resilience strategies are frequently employed to hedge against disruptions. Despite a substantial body of literature examining the design of SC resilience strategies, there is a paucity of literature exploring the impact of the product life cycle (PLC) on the design of such strategies. This paper presents scenario-based and time-dependent mixed integer programming mathematical models for optimizing performance in terms of costs and service levels. The models consider the distinctive characteristics of each PLC phase. Simulation-based analyses are utilized to simulate disruptions at different stages of the PLC and to explore the impact of the PLC on SC resilience strategies design. Moreover, a resilience multi-portfolio method is modified using simulation techniques to determine optimal resilience portfolios from the PLC perspective. Through computational examples and sensitivity analysis, our models are capable of achieving resilience supply and production portfolios by making a trade-off between costs and service levels from the PLC perspective. The results illustrate that our approaches facilitate the identification of critical relationships between the severity of disruptions and the formulation of SC resilience strategies in terms of the PLC. The findings are instructive for SC managers when considering the impact of disruptions from the perspective of the PLC.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"282 ","pages":"Article 109532"},"PeriodicalIF":9.8,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143266873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Baozhuang Niu , Chengwei Lai , Zebin Zheng , Zhiyuan Qi , Zhipeng Dai
{"title":"AI quality control in competitive recycling facing material contamination","authors":"Baozhuang Niu , Chengwei Lai , Zebin Zheng , Zhiyuan Qi , Zhipeng Dai","doi":"10.1016/j.ijpe.2025.109541","DOIUrl":"10.1016/j.ijpe.2025.109541","url":null,"abstract":"<div><div>In a typical material recycling supply chain, material recovery facilities (MRFs) are generally classified as dirty MRFs(dMRFs) whose material faces contamination and clean MRFs(cMRFs) whose material is of high clarity. As the downstream manufacturer, purchasing from dMRFs or cMRFs faces the trade-off between material purchasing price (dMRF's material is cheaper) and the waste disposal cost (dMRF's contaminated material will be wasted and disposed of). This also motivates dMRFs to adopt an AI quality control system to eliminate contamination. We build a game-theoretic model to analyze the decision-makers’ incentive of AI adoption and interesting findings include: (1) Even AI quality control pushes the purchasing price upward, dMRF's supply quantity can be surprisingly reduced, indicating “inefficient use of AI”; (2) AI quality control cost and the manufacturer's waste disposal cost exhibit a substitutable relationship in promoting the dMRF's AI adoption. These findings provide important insights for managers in formulating purchasing strategies, investment decisions, and AI adoption. They are suggested to pay attention to win-win-win situations regarding the dMRF's profit, the manufacturer's profit, and the system's environmental sustainability with the dMRF's AI quality control. Since all-win situations for the stakeholders will not sustain as the equilibrium, subsidy schemes should be designed to improve the cMRF's profit.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"282 ","pages":"Article 109541"},"PeriodicalIF":9.8,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143266869","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Na Luo , Zhangwei Feng , Yanping Liu , Sihong Wu , Xiaoxiao Liang
{"title":"Tackling food waste: The role of food suppliers’ investment in preservation technology and government intervention","authors":"Na Luo , Zhangwei Feng , Yanping Liu , Sihong Wu , Xiaoxiao Liang","doi":"10.1016/j.ijpe.2025.109542","DOIUrl":"10.1016/j.ijpe.2025.109542","url":null,"abstract":"<div><div>Investing in preservation technologies (PT) within the food industry has become increasingly important owing to global food crises. While many studies analyze the benefits and costs of investing in PT, there is a limited understanding of how market prices and food deterioration rates influence these investment decisions. Additionally, the impact of government interventions on this process has not been thoroughly explored. This study aims to address these knowledge gaps, motivated by data from interviews, by using optimization models to analyze food suppliers’ investments in PT amid varying market prices, transportation costs, and deterioration rates. Our findings identify specific conditions that drive PT investment, including scenarios where deterioration rates and market prices fall within certain ranges, and where low transportation costs align with high or moderate market prices. Moreover, government interventions can support PT investment by improving these conditions, though their effectiveness may be limited if suppliers lack access to affordable low-carbon PTs or face high costs. We also identify a breakeven point for social welfare, showing that excessive taxation can significantly reduce welfare. This study introduces a novel framework that integrates multiple elements to offer a deeper understanding of the motivations behind suppliers' investment decisions. It seeks to align supplier incentives with the goals of sustainable food supply chains, thereby fostering more effective policy strategies for tackling food waste. The insights gained will offer valuable guidance to practitioners and identify avenues for future research.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"282 ","pages":"Article 109542"},"PeriodicalIF":9.8,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143266872","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Violetta Giada Cannas, Rossella Pozzi, Nicolò Saporiti, Andrea Urbinati
{"title":"Unveiling the interaction among circular economy, industry 4.0, and lean production: A multiple case study analysis and an empirically based framework","authors":"Violetta Giada Cannas, Rossella Pozzi, Nicolò Saporiti, Andrea Urbinati","doi":"10.1016/j.ijpe.2025.109537","DOIUrl":"10.1016/j.ijpe.2025.109537","url":null,"abstract":"<div><div>Recent years have seen a growing interest among academics and practitioners in the approaches of Industry 4.0 (I40), Lean Production (LP), and Circular Economy (CE). Scientific studies have largely examined these approaches separately, or in a dual, pairwise combination. More recent research has also shown how I40 technologies and LP practices affect the implementation of CE strategies. In particular, it has been noted that I40 technologies and LP practices mutually not only enhance each other's efficacy but also have a positive impact on CE strategies. Despite this evidence, many of the existing works leave a critical gap in our knowledge about an integrated perspective among these three approaches. In other words, a more synergistic interaction among the I40 technologies, LP practices, and CE strategies is not yet well explored in the existing academic literature and needs to be developed. To address this research gap, this study leverages a multiple case study analysis of six companies operating in the manufacturing sector that operate with I40 technologies, LP practices, and CE strategies. Our results confirm that I40 technologies and LP practices foster each other and enable CE strategies. In addition, our empirical analysis adds to the existing studies that the synergistic interaction among the three approaches lies in the fact that the implementation of one approach triggers another one sequentially. In other words, the implementation of I40 technologies contributes to the activation of LP practices, which in turn enable the adoption of CE strategies. The evidence of our results has been visualized in empirically based framework that highlights for scholars and managers how manufacturing companies can optimize their transition pathway towards CE through I40 technologies and LP practices and paving thus the way for a more sustainable and effective industrial environment.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"282 ","pages":"Article 109537"},"PeriodicalIF":9.8,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143266874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Integration of machine learning and optimization models for a data-driven lot sizing problem with random yield","authors":"Bijan Bibak, Fikri Karaesmen","doi":"10.1016/j.ijpe.2025.109529","DOIUrl":"10.1016/j.ijpe.2025.109529","url":null,"abstract":"<div><div>We investigate a data-driven lot sizing problem under random yield. Motivated by semi-conductor production, we focus on the case where the random yield rate of a manufacturing process depends on a large number of features that can be observed before the lot sizing decision is made. Similarly, demand may also be random and may depend on a number of features. The lot sizing problem in this setting is challenging because the optimal decision depends on a large number of observed features for which there is limited data. To address this challenge, we propose estimation and optimization methods that combine tools from machine learning with tools from stochastic optimization. Using a publicly available data set for semi-conductor yield data and an additional synthetic data set, we compare the performance of different estimation and optimization approaches. We show that there is significant value of taking feature information into account for cost minimization. We also find that the best method for this problem combines tools from estimation with theoretical optimization properties of the random yield inventory problem.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"282 ","pages":"Article 109529"},"PeriodicalIF":9.8,"publicationDate":"2025-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143266875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Scenario-based optimization and simulation framework for human-centered Assembly Line Balancing","authors":"Mohammed-Amine Abdous , Xavier Delorme , Daria Battini , Fabio Sgarbossa","doi":"10.1016/j.ijpe.2024.109513","DOIUrl":"10.1016/j.ijpe.2024.109513","url":null,"abstract":"<div><div>Assembly lines are essential components of manufacturing operations but often face challenges due to variable operation times and ergonomic risks leading to increased musculoskeletal disorders (MSDs) and associated economic burdens such as absenteeism and workers’ compensation. Assembly line balancing approaches frequently overlook these issues and their impact on worker well-being, highlighting the need for models that integrate both ergonomics and variable operation times.</div><div>This paper introduces a new scenario-based optimization model for assembly line balancing, incorporating a fatigue and recovery ergonomic assessment. The model aims to reduce worker fatigue by considering the variability of operation times across different scenarios and their probabilities. An Integer Linear Program (ILP) is developed and efficiently solved using an Iterative Dichotomic Search algorithm. A simulation framework evaluates the model’s robustness and supports dynamic managerial policies such as job rotation, overrun policies, and scheduled rest allowances.</div><div>Numerical experiments demonstrate the effectiveness of the proposed approach in improving ergonomic conditions and reducing the risk of MSDs without compromising production efficiency. Implementing the model enables managers to proactively address worker fatigue, enhancing well-being, increasing productivity, and achieving significant cost savings through reduced absenteeism and lower compensation claims. The model also provides actionable insights for managerial decision-making to improve resource allocation and strategic planning. By aligning with Industry 5.0 principles, the approach fosters sustainable, human-centric production systems, offering competitive advantages. The method’s adaptability provides practical solutions that enhance operational management and contribute to long-term organizational success by balancing worker health with economic efficiency.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"282 ","pages":"Article 109513"},"PeriodicalIF":9.8,"publicationDate":"2025-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143266870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}