International Journal of Production Economics最新文献

{"title":"Integration of machine learning and optimization models for a data-driven lot sizing problem with random yield","authors":"Bijan Bibak,&nbsp;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 ,&nbsp;Xavier Delorme ,&nbsp;Daria Battini ,&nbsp;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}

{"title":"Advancing towards industry 4.0: A maturity model for smart shop floor control","authors":"Adauto Bueno ,&nbsp;Moacir Godinho Filho ,&nbsp;Moiseis Cecconello ,&nbsp;Luis Antonio de Santa-Eulália ,&nbsp;Rodrigo Goyannes Gusmão Caiado ,&nbsp;Gilberto Miller Devós Ganga ,&nbsp;João Vidal Carvalho","doi":"10.1016/j.ijpe.2025.109538","DOIUrl":"10.1016/j.ijpe.2025.109538","url":null,"abstract":"<div><div>This research introduces the smart Shop Floor Control Maturity Model (S²FC MM), a comprehensive framework designed to assess the maturity of shop floor control function in the context of Industry 4.0 environments. Developed through a meticulous Design Science Research approach, the model combines mixed methods such as literature surveys, expert interviews, focus groups, an observational case study, and fuzzy expert system modeling. S²FC MM is designed from a socio-technical systems theory (STS) lens. Additionally, it was applied to measure the maturity of a multinational steel manufacturing company dealing with an Industry 4.0 project in the past three years. S²FC MM is distinguished by its granular, multi-layer structure, comprising five maturity focus areas, twenty implementation key factors, ninety-six smart capabilities, and five progressive maturity levels. A key feature of the model is its fuzzy rule-based self-assessment tool, which accurately reflects managerial perceptions of maturity levels, addressing the imprecision often found in such evaluations. Applying our S²FC MM in a large steel manufacturing company has showcased its effectiveness. It has significantly aided shop floor managers and steel company professionals in identifying key operational improvements and systematically navigating the progression of maturity levels within their operations. Consequently, the S²FC MM emerges as a valuable tool for facilitating the transition of the shop floor control function towards smart, technology-driven operations, providing a clear pathway for manufacturing companies to maximize value-creation and enhance performance in the Industry 4.0 era. Theoretically, our research extends the socio-technical systems theory to smart shop floor control by integrating technological and social dimensions essential for Industry 4.0. The proposed S²FC MM framework defines five focus areas that balance human and technical elements. By tailoring socio-technical systems theory principles to manufacturing-specific challenges, the study provides a socio-technical perspective for managing digital transformation in production environments.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"282 ","pages":"Article 109538"},"PeriodicalIF":9.8,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143266813","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":"Examining corporate social irresponsibility in manufacturing: An eye-tracking study of social media news","authors":"Xinwei Li ,&nbsp;Ying Kei Tse ,&nbsp;Xiangzhi Bu","doi":"10.1016/j.ijpe.2025.109539","DOIUrl":"10.1016/j.ijpe.2025.109539","url":null,"abstract":"<div><div>This research aims to experimentally examine how consumers respond to environmental corporate social irresponsibility (CSI) news about manufacturing production on social media, focusing on the cognitive mechanisms underlying consumers’ behaviour decisions. Drawing on existing literature in CSI, consumer behaviour, and social media crisis communication, this study employs an eye-tracking methodology in conjunction with a 2 x 2 x 2 experimental vignette design with a nationally representative sample of 325 UK adults. Results reveal that the presence of evidence and a higher degree of harm in CSI events do not evoke stronger negative responses. Instead, the study highlights conformity behaviour on social media, showing that critical comments significantly drive negative responses. A significant three-way interaction between evidence, harmfulness, commentary on negative word-of-mouth (WoM) demonstrates that when a CSI event is evidence-based with low harm, critical comments accompanying CSI news provoke substantially greater negative WoM than supportive comments. The eye-tracking results indicate that collective opinions significantly moderated the relationship between visual attention and negative response levels. Specifically, higher visual attention leads to reduced negative responses when customers encounter critical rather than supportive comments. This study makes notable contributions by unwrapping the mechanisms shaping public perceptions of CSI news. It provides valuable insights for companies to mitigate the escalation of CSI news, minimise potential reputational harm, and enhance preparedness in managing CSI-related risks. Additionally, the integration of eye-tracking technology within a scenario-based experimental framework represents a novel methodological advancement, enriching the understanding of consumer behaviour in the context of social media crises.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"281 ","pages":"Article 109539"},"PeriodicalIF":9.8,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143194279","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":"Prepositioning of emergency supplies and channel coordination: Considering a loss-averse supplier and government penalty","authors":"Yang Liu ,&nbsp;Jun Tian ,&nbsp;Ning Yu","doi":"10.1016/j.ijpe.2025.109536","DOIUrl":"10.1016/j.ijpe.2025.109536","url":null,"abstract":"<div><div>In humanitarian contexts, less attention has been paid to the bounded rationality of suppliers, which may lead to understocking of emergency supplies. Failing to recognize and correct understocking significantly impacts the reliability of humanitarian supply chains (HSCs). To bridge the gap, we redesign a humanitarian system composed of a local authority and a loss-averse supplier with a non-zero reference profit. Introducing an option contract and penalty mechanism into the public-private cooperation (PPC) in stocking emergency supplies. The conditions under which the supplier adopts either a stocking-to-order or understocking strategy are identified. The results show that the supplier's optimal reserve quantity of emergency supplies decreases with increasing loss aversion and optimism levels, with a greater sensitivity to changes in optimism than in loss aversion. Increasing the penalty coefficient slows the rate of decline in the supplier's reserve quantity if the loss aversion (optimism) level is low but has the opposite effect if the supplier's loss aversion (optimism) level is high. Humanitarian channel coordination is achieved under four conditions, two of which require that the supplier's loss aversion level must not exceed the loss aversion threshold and that the penalty coefficient must fall within a specific range. Additionally, a Nash bargaining model is developed to determine an optimal option price acceptable to the authority and the supplier, which enhances the willingness of the HSC members to jointly preposition emergency supplies. Finally, the case study shows that the PPC model leads to utility improvements for authorities and suppliers and provides direct validation of the PPC model's effectiveness. Our paper explains the motivations behind supplier understocking from a behavioral perspective and provides a penalty mechanism for regulating suppliers in line with government orders, which is of great significance for guaranteeing the reliable supply of emergency supplies.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"282 ","pages":"Article 109536"},"PeriodicalIF":9.8,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143266805","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":"Digital transformation in the blockchain era: Balancing efficiency and resilience in operations management","authors":"Jing Xue ,&nbsp;Guo Li ,&nbsp;Dmitry Ivanov","doi":"10.1016/j.ijpe.2025.109525","DOIUrl":"10.1016/j.ijpe.2025.109525","url":null,"abstract":"<div><div>Nowadays, blockchain and other disruptive digital technologies have driven corporate digital transformation (DT) and empowered traditional business processes for achieving high-quality development. DT is considered an effective way for gaining a competitive advantage by incentivizing innovation. However, theoretical and empirical mechanisms behind the effect of DT on corporate innovation remain unclear from the perspective of operations and supply chain management (OSCM). To fill this gap, we use panel data of China’s A-share listed companies from 2010 to 2020 and employ a two-way fixed effect model to uncover the relationship between DT and corporate innovation. Our findings suggest that DT can significantly improve innovation outcomes. Sub-technology regression analysis reveals that artificial intelligence (AI), big data, cloud computing, and digital applications positively affect corporate innovation in terms of quantity and quality. Surprisingly, joint effect analysis shows that the interaction term coefficient between blockchain and AI is significantly negative, indicating a competitive relationship between these two technologies. Moreover, firms with higher information transparency and lower market competition are more adaptable during DT and thus generate higher innovation returns compared with their counterparts. Mechanism tests indicate that digitalization can stimulate innovation through balancing efficiency and resilience. Specifically, DT reduces resource misallocation and waste, which in turn enhances the resource allocation efficiency of firms. Information sharing supported by digital platforms improves firms’ visibility and velocity to market environments, ensures the continuity and stability of business operations, and ultimately improves organizational resilience. These findings shed light on the substantial potential of the effect of blockchain and other disruptive digital technologies from the perspective of OSCM and provide insights for promoting the digitalization of enterprises.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"282 ","pages":"Article 109525"},"PeriodicalIF":9.8,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143266876","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":"A representative product configuration ranking approach considering requirement interactions and inconsistent group preferences","authors":"Xinwei Zhang ,&nbsp;Qiong Feng ,&nbsp;Yihang Li ,&nbsp;Chen Zheng ,&nbsp;Salvatore Corrente","doi":"10.1016/j.ijpe.2025.109534","DOIUrl":"10.1016/j.ijpe.2025.109534","url":null,"abstract":"<div><div>Configuration solving is essential in product configuration because it supports decisions on selecting final configuration alternatives to satisfy stakeholders' preferences. However, the inherent interaction of product Design Requirements (DRs) and multiple stakeholders involved lead to three limitations in developing an appropriate configuration solving model: (i) the existing models have limitations in balancing the tractability of the model and the diversity of interactions; (ii) it is impractical to assume that different stakeholders have consistent preferences for the alternatives, and directly removing inconsistent preferences can lead to the loss of preference information; (iii) the representativeness of preference functions built from incomplete preference information is doubtful. To address these limitations, a robust product configuration ranking approach is proposed. First, the Choquet integral with the <em>k</em>-interactive fuzzy measure is applied to evaluate alternatives with DRs’ interactions, improving the tractability by reducing the number of parameters and related constraints. Second, an interactive method of identifying a minimum set of adjustable inconsistent preferences is proposed to adjust them among different stakeholders, avoiding the preferences loss and ensuring the trade-off among stakeholders. Third, a representative ranking model based on the <em>k</em>-interactive Choquet integral and nonadditive robust ordinal regression is proposed to select the robust alternative concerning individual and group stakeholders' preferences. To validate its feasibility and effectiveness, the proposed approach is applied to an example of configuration solving for a robotic manufacturing system.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"282 ","pages":"Article 109534"},"PeriodicalIF":9.8,"publicationDate":"2025-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143266802","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":"Contracting for system availability with zero ownership cost via redundancy, maintenance and repairable inventory","authors":"Tongdan Jin","doi":"10.1016/j.ijpe.2025.109531","DOIUrl":"10.1016/j.ijpe.2025.109531","url":null,"abstract":"<div><div>Though various types of availability-based contract models have been developed, there is a lack of studies in which reliability-redundancy and maintenance service logistics are jointly considered. This paper proposes a principal-agent model to manage performance-based contract for zero ownership cost and no moral hazard. The equipment supplier plays as an agent who determines redundant units, maintenance time, spares inventory and repair capacity to maximize the service profit. The customer plays as a principal who stipulates system availability target and the payment scheme for attaining zero cost of asset ownership. The novelty of the model lies in two aspects: a) it represents a first-of-its-kind in designing system availability-based contract in an integrated redundancy-maintenance-inventory optimization framework; and b) the customer bears zero ownership cost while the supplier's profit margin is guaranteed. Three major findings are obtained. First, the supplier's actions are proved to be fully observable to the customer, hence a first-best contract solution is obtained. Second, if the customer imposes the cost limit on individual systems, the supplier opts to increase the system availability for reaping a larger profit. Third, one emergency repair server is generally sufficient to remedy the spares stockout situation regardless of the fleet size.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"281 ","pages":"Article 109531"},"PeriodicalIF":9.8,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143194281","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":"Exploring resilience in the downstream supply chain of the semiconductor industry: The mediating roles of risk mitigation, process simplification, and flexibility","authors":"Zhenwei Liao ,&nbsp;Bingyan Tantai ,&nbsp;Asma-Qamaliah Abdul-Hamid ,&nbsp;Dzulkifli Mukhtar ,&nbsp;Mohd Helmi Ali","doi":"10.1016/j.ijpe.2025.109530","DOIUrl":"10.1016/j.ijpe.2025.109530","url":null,"abstract":"<div><div>This study enhances knowledge of the indicators of supply chain resilience (SCR) within the downstream supply chain of the semiconductor industry. The focus is on risk mitigation, process simplification and flexibility. Despite the complexity of global supply chains, how these factors interact to enhance SCR in the semiconductor sector remains underexplored. SCR enables downstream parties in the semiconductor industry to recover and maintain operations after disruption. Previous studies have overlooked (1) the determinants of process simplification, risk mitigation competency, and supply chain flexibility within the semiconductor industry and (2) the mediating roles of those three factors in achieving SCR. This study surveys 226 managers in the downstream semiconductor industry in China and analyzes the data using SmartPLS 4.0, a tool for Partial Least Squares Structural Equation Modeling (PLS-SEM). The results underscore that efficient and flexible information systems significantly improve SCR through process simplification, while a risk management culture and an orientation to risk mitigation also significantly enhance SCR through risk mitigation competency. Process simplification and risk mitigation competency also significantly impact SCR within the sector through supply chain flexibility. These findings offer actionable insights, highlighting the need for targeted investments in information systems and risk management to strengthen supply chain resilience in China's semiconductor industry. Knowledge of the important mediating roles of risk mitigation, process simplification, and flexibility is essential for strategic investment in information systems, process optimization, and aligning technological infrastructure with strategic goals.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"281 ","pages":"Article 109530"},"PeriodicalIF":9.8,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143194351","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":"We belong together - A system-level investigation regarding AGV-assisted order picking performance","authors":"Jonas Koreis ,&nbsp;Dominic Loske ,&nbsp;Matthias Klumpp ,&nbsp;Christoph H. Glock","doi":"10.1016/j.ijpe.2025.109527","DOIUrl":"10.1016/j.ijpe.2025.109527","url":null,"abstract":"<div><div>Automation technologies are currently being introduced in many warehouse intralogistics operations to support human workers in manual order picking. Robotic systems supporting manual order picking are therefore receiving increasing attention in the production economics literature. One related concept is human–robot collaboration, in which automated guided vehicles (AGV) and human pickers collaborate in the same work space. As these automation technologies still represent a minority in a larger manual order picking setting, we propose a role-model opportunity for analyzing the system level of joint operations from an economic perspective. We empirically investigate a pilot test of a new industrial truck deployed as an AGV that automatically follows order pickers in their travel direction within one specific warehouse of a brick-and-mortar grocery retailer. Our data set comprises 140,991 pick location visits performed in one dedicated warehouse aisle between 01 February 2023 and 30 June 2023, with an average of 31.89% of picks involving human–robot and 68.11% human–manual order pickers, with both groups sharing the identical aisle work space. We find that an increasing share of AGVs in the system has a U-shaped impact on order picking time. Therefore, the intuitive assumption of “the more, the better” for introducing AGVs and their impact on order picking performance is not confirmed for the context under investigation. Our findings can guide researchers and managers on how to analyze and economically design system-level order picking in scenarios in which the complete transition to automation remains a distant reality or requires long-term transition windows, a real-life operations management challenge for most order picking contexts.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"282 ","pages":"Article 109527"},"PeriodicalIF":9.8,"publicationDate":"2025-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143266815","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}