International Journal of Production Economics最新文献

{"title":"Multi-factor driving paths of green supply chain management implementation in leading manufacturers: A fuzzy-set qualitative comparative analysis","authors":"Yihui Tian,&nbsp;Qinyuan Zhang,&nbsp;Tiffany C.H. Leung","doi":"10.1016/j.ijpe.2025.109689","DOIUrl":"10.1016/j.ijpe.2025.109689","url":null,"abstract":"<div><div>Environmental pollution and ecological exploitation have increasingly received global attention. Manufacturers in global supply chain are one of the biggest polluters. Green supply chain management (GSCM) has become an important operational strategy for companies to achieve sustainable production. Companies in different sectors implement GSCM practices in different ways. Therefore, it is important to understand which factors affect a company's GSCM and how these factors work together to drive corporate green behavior. Previous studies focused on the individual impact of GSCM practices, while a few studies have examined how different combinations of multiple factors lead to GSCM practices. This study uses content analysis and fuzzy-set qualitative comparative analysis (fsQCA) to analyze the main driving factors, such as the leading global manufacturing companies, market, competitors, and countries, on GSCM (n = 74). We apply configuration thinking and qualitative comparative research methods to explore the multiple concurrent factors and complex causal mechanisms that affect the differences in GSCM levels. The multiple configurations reveal the complexity of companies on GSCM. Finally, we discussed the theoretical and practical implications, limitations, and future research directions.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"287 ","pages":"Article 109689"},"PeriodicalIF":9.8,"publicationDate":"2025-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144190124","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":"To adopt an online recommender system? A manufacturer’s strategic choice in a dual-channel setting","authors":"Chi Zhou ,&nbsp;He Li ,&nbsp;Mingming Leng ,&nbsp;Jing Yu","doi":"10.1016/j.ijpe.2025.109677","DOIUrl":"10.1016/j.ijpe.2025.109677","url":null,"abstract":"<div><div>The past years have witnessed the prosperity of online recommender systems. Some firms have utilized such systems to promote their products and services whereas others have not. To reveal the motivation to use recommender systems, we consider a dual channel setting in which a manufacturer sells his products to consumers in a direct-sale channel and also uses a wholesale channel to sell via an online retailer. The manufacturer decides on whether to use an online recommender system in the direct-sale channel or not, for both the case of the retailer’s adoption of the recommendation system and the case of no recommendation in the wholesale channel. Considering both the cost-per-sale (CPS) and cost-per-click (CPC) payment schemes in the context of the recommender system, we examine whether it is optimal for the manufacturer to adopt the recommendation service under two distinct scenarios: when the retailer utilizes the recommender system and when the retailer does not. Our game-theoretic analysis exposes that, if the retailer does not adopt the recommender system under both the CPS and CPC payment schemes, then the manufacturer’s system adoption decision depends on the recommendation strength and cost. We also find that the manufacturer can benefit from the CPS payment with a sufficiently low recommendation cost. When the retailer adopts the recommender system, the manufacturer’s optimal strategy is to abandon the recommender system under any payment scheme, and the manufacturer reduces his wholesale price when the recommendation strength increases.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"287 ","pages":"Article 109677"},"PeriodicalIF":9.8,"publicationDate":"2025-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144190123","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":"Machine learning applied to forecasting the manufacturing time of new products prototypes and ETO products: An exploratory study","authors":"Roberto Canedo Rosa ,&nbsp;Marcelo Carneiro Gonçalves ,&nbsp;Sanderson César Macêdo Barbalho","doi":"10.1016/j.ijpe.2025.109688","DOIUrl":"10.1016/j.ijpe.2025.109688","url":null,"abstract":"<div><div>Industry 4.0 is a transformative initiative that integrates various technologies and reshapes industrial processes, production methods, and business models. However, forecasting future events within this paradigm shift presents significant challenges. Predicting the cycle time for new product development (NPD) in a dynamic and competitive environment, especially in a highly globalized market driven by innovation, is crucial. Previous research has shown that prototype manufacturing lead times are key parameters for predicting NPD times-to-market. This study investigates the predictive capabilities of artificial intelligence algorithms in estimating manufacturing lead times under varying part geometries and materials at an aerospace and medical equipment company. By leveraging predictive analysis and machine learning techniques, specifically Artificial Neural Networks (ANN), Support Vector Machine (SVM), and Random Forest (RF) algorithms, the proposed methodology demonstrates its efficacy and variations. The results show that top-performing models achieve an accuracy rate exceeding 87 % and an average absolute error of less than one day, which have significant practical benefits for project production planners. They can utilize the most popular AI frameworks on easier-to-use programming platforms to estimate the time required to manufacture their prototypes, predict their new product development (NPD) cycle times, and negotiate lead times for in-house and third-party manufacturing more effectively, thereby improving project planning and delivery.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"287 ","pages":"Article 109688"},"PeriodicalIF":9.8,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144194934","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 novel robust optimization approach for supply chain resilience: The role of flexibility and collaboration","authors":"Seyed Ashkan Hosseini Shekarabi ,&nbsp;Reza Kiani Mavi ,&nbsp;Neda Kiani Mavi ,&nbsp;Flavio Romero Macau ,&nbsp;Sobhan (Sean) Arisian","doi":"10.1016/j.ijpe.2025.109686","DOIUrl":"10.1016/j.ijpe.2025.109686","url":null,"abstract":"<div><div>Supply chains are increasingly vulnerable to disruptive events that impair performance and stability. Despite research on supply chain resilience, a significant gap remains in risk management approaches on how to simultaneously minimize expected costs and control extreme cost variations. Existing methods neglect to narrow the gap between worst-case and best-case outcomes and to quantify the economic benefit of enhanced information in decision-making under uncertainty. This gap underscores the need for an integrated robust optimization framework that balances expected cost and risk while incorporating the assessment of novel digital technologies. In response, this study proposes a two-stage stochastic mixed-integer nonlinear programming (MINLP) model that introduces two new metrics: Evolutionary Modified Conditional Value at Risk (EMCVaR) and the Information Impact Metric (IIM). EMCVaR unifies tail risk, solution variance, and model infeasibility into a single measure, yielding a controllable and predictable cost range, while IIM quantifies the economic benefit derived from the data-driven decision support system. Moreover, our model incorporates digital technologies, such as advanced screening, predictive analytics, and real-time digital monitoring, to enhance supply chain flexibility and collaboration. Our computational analysis demonstrates that diversified resilience strategies reduce both expected and worst-case costs, decrease cost variability by up to 15 %, and narrow the gap between extreme outcomes by over 30 %. From a managerial perspective, the study recommends adopting EMCVaR as a risk-budget to bound cost volatility, employing IIM to prioritize digital-technology investments that accelerate recovery, and formalizing backup-capacity and spot-market clauses with key suppliers, an integrated strategy shown to reduce worst-case disruption costs by more than 30 % while limiting routine cost variability to roughly 7 %.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"287 ","pages":"Article 109686"},"PeriodicalIF":9.8,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144204065","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":"Strategic counterfeit suppression on online platform: Considering network externalities and online consumer reviews in a two-period framework","authors":"Haiqing Song ,&nbsp;Kai Cao ,&nbsp;Housheng Duan","doi":"10.1016/j.ijpe.2025.109684","DOIUrl":"10.1016/j.ijpe.2025.109684","url":null,"abstract":"<div><div>The presence of counterfeiters on online platforms often has detrimental effects on consumers, authentic sellers, and the platforms themselves, highlighting the need for effective anti-counterfeit policies. In addition, consumer purchasing behavior is influenced not only by price and quality but also by online consumer reviews (OCRs). In this paper, we examine a two-sided market scenario where authentic sellers and counterfeiters coexist on an online platform, and consumers can use OCRs to assess product quality. We construct a two-period model to investigate how anti-counterfeiting efforts and pricing decisions by the platform and sellers evolve over time, considering the impact of network externalities and OCRs. Our findings reveal that without OCRs, increased anti-counterfeiting efforts consistently align with changes in retail prices and authentic sellers' profits. Interestingly, with OCRs, the platform can adopt one of two strategies: “<em>relaxed first, then strict</em>” or “<em>strict first, then relaxed</em>”, each with its own benefits, and the platform's efforts to combat counterfeiters do not consistently increase, and platform profits are not necessarily compromised. Furthermore, we find that the online platform earns lower profits with OCRs than without them. Contrary to past literature, our study shows that sellers may benefit from OCRs when there is a significant reference effect or low production costs. Additionally, the comparison of social welfare across different scenarios reveals that OCRs do not always enhance social welfare.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"287 ","pages":"Article 109684"},"PeriodicalIF":9.8,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144194851","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 metric for the asymmetry in matched-pair data for buyer–supplier dyads","authors":"ManMohan S. Sodhi","doi":"10.1016/j.ijpe.2025.109653","DOIUrl":"10.1016/j.ijpe.2025.109653","url":null,"abstract":"<div><div>Although various difference-based methods are utilized to analyze asymmetry in buyer–supplier matched-pair data within the literature, these approaches are ad hoc and do not always address differences across multiple dimensions. Furthermore, they do not provide a significance test. This paper extends the concept of the paired t-test for dyad-level differences by developing a Mahalanobis distance-based metric in multiple dimensions, along with a significance test. The metric and the significance test can be used in empirical research to identify dyads in a dataset that are significantly asymmetric at any selected confidence level. In practice, the method can identify those suppliers for a buyer that have significantly mismatched expectations relative to other suppliers. The paper utilizes simulated datasets to compare the proposed metric with other distance-based metrics that lack a significance test. Finally, the paper applies a retail dataset to demonstrate (1) the utility of the metric in identifying significantly asymmetric dyads and (2) the use of the same distance concept to consolidate multiple items in any buyer or supplier construct into a single score for the construct, rather than using factor scores. The latter approach is lossless, in contrast to factor analysis. Using distance-based metrics with this retail dataset in a structural equation model suggests that asymmetry can negatively affect relationship-specific operational performance for buyers and suppliers. This study contributes a robust methodological framework, offering a structured basis for future research in the measurement of dyadic asymmetry.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"287 ","pages":"Article 109653"},"PeriodicalIF":9.8,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144204066","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":"Skill-and-Knowledge Sharing HUB-CI model for resilient production systems","authors":"Praditya Ajidarma ,&nbsp;Shimon Y. Nof","doi":"10.1016/j.ijpe.2025.109681","DOIUrl":"10.1016/j.ijpe.2025.109681","url":null,"abstract":"<div><div>The use of innovative technologies and the integration of efficient human-robot interaction have had a significant influence on all facets of modern manufacturing. While automation has advanced, numerous tasks still depend on human operators due to their superior dexterity and reasoning abilities. Augmented reality (AR) has emerged as a critical enabler, enhancing the skills of less-experienced workers, improving operational resilience, and enabling rapid adaptation to disruptions. This study presents a novel skill-and-knowledge-sharing paradigm for manufacturing systems. The architecture, called HUB-CI (a hub for collaborative intelligence), facilitates an efficient learning protocol. The model uses quantified learning curves to evaluate operator performance over time and incorporates AR-driven skill and knowledge sharing to reduce response times, optimize scheduling makespan, and improve resilience metrics such as system stability, adaptability, and recovery speed under disruptive conditions. Numerical experiments reveal that HUB-CI significantly decreases response times and improves scheduling makespan by up to 20.52 % after 500 iterations, (p-value &lt;0.01) and achieves consistent performance gains under disruptive conditions, due to its ability to maintain makespan robustness within 5 % of the non-disrupted baseline. In more stable environments with converging agent skill levels, the model sustains strong performance, demonstrating its versatility. By integrating quantified learning curves with four core resilience metrics—adaptability, collaboration and visibility, robustness, and sustainability—HUB-CI enables adaptive task allocation and real-time collaboration, offering a substantial advancement in cyber-collaborative production systems.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"287 ","pages":"Article 109681"},"PeriodicalIF":9.8,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144194852","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":"Greenwashing in ESG information disclosure: An intertemporal signaling game approach","authors":"Xiaoyuan Xu ,&nbsp;Zhiguo Li ,&nbsp;Fengling Liu","doi":"10.1016/j.ijpe.2025.109674","DOIUrl":"10.1016/j.ijpe.2025.109674","url":null,"abstract":"<div><div>Strategic consumers are increasingly willing to pay a premium for durable products with ESG attributes, leading firms to potentially engage in greenwashing by exaggerating or embellishing their actual ESG investments to capture this premium. This paper develops an intertemporal signaling game model where a firm privately knows his level of ESG investment cost and can choose between two disclosure strategies: the active disclosure strategy (AS) and the reluctant disclosure strategy (RS). Our analysis explores the impact of greenwashing on dynamic pricing, sales volume, consumer surplus and social welfare. We show that, the firm with low level of ESG investment (low-type) cannot greenwash effectively when the cost difference between low and high ESG investment levels is large, since the firm with high level of ESG investment (high-type) is more willing to reveal his type; otherwise, the low-type firm has the opportunity to greenwash because the high-type firm prefers to hide his type. Moreover, choosing AS over RS increases the firm’s first-period sales but reduces his second-period sales due to the “information-inference” effect and the “price-shifting” effect. Interestingly, under certain conditions, greenwashing can actually increase consumer surplus, driven by consumers’ strategic behavior. Remarkably, the government’s “anti-greenwashing” requirements do not incentivize the firm to increase his ESG investment if the valuation discounts in the second-period is significant.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"287 ","pages":"Article 109674"},"PeriodicalIF":9.8,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144168000","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":"How customer digital orientation drives supplier green and low-carbon efforts: The roles of supplier dependence and common ownership","authors":"Yiran Chen ,&nbsp;Shaopeng Cao","doi":"10.1016/j.ijpe.2025.109680","DOIUrl":"10.1016/j.ijpe.2025.109680","url":null,"abstract":"<div><div>Amid escalating climate change threats and the global imperative to achieve net-zero emissions by 2050, supply chain decarbonization has emerged as a pivotal mitigation strategy. This study examines how customer digital orientation drives supplier green and low-carbon efforts, leveraging spillover effects within buyer-supplier relationships. Using a 2010-2022 panel dataset from multiple sources, we find that customer digital orientation significantly enhances supplier green and low-carbon efforts through normative pressures and empowerment effects. From a supplier-customer relationship view, we further identify that this effect is amplified when suppliers are highly dependent on their customers, as dependence strengthens compliance pressures and enhances technology and resource empowerment. Furthermore, vertical common ownership between suppliers and customers acts as a relational governance mechanism, aligning interests and enhancing collaboration, thereby intensifying the positive spillover effects of customer digital orientation. Finally, heterogeneity tests reveal that the positive spillover effects is more pronounced when suppliers operate in highly competitive industries or face a narrower digital divide with their customers. Our findings provide novel insights into the mechanisms of digital-enabled decarbonization across supply chains, offering actionable pathways for policymakers and firms to accelerate the transition toward net-zero emissions.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"287 ","pages":"Article 109680"},"PeriodicalIF":9.8,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144167999","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":"Agency selling or reselling? Differentiated medication pricing in a healthcare platform with consultation","authors":"Shaofu Du ,&nbsp;Hengjia Bao ,&nbsp;Tengfei Nie","doi":"10.1016/j.ijpe.2025.109639","DOIUrl":"10.1016/j.ijpe.2025.109639","url":null,"abstract":"<div><div>The rapid evolution of Internet healthcare has enabled online healthcare platforms to enter the healthcare market, where they typically operate under two predominant agreements: agency selling agreements and reselling agreements. Considering the diverse patient demands for medications of varying quality, these platforms strategically introduce medication suppliers with differentiated quality levels to enhance market coverage. This study examines how an online healthcare platform influences patients’ medication choices through a consultation fee and differentiated medication prices under two agreements within a game-theoretic model. Our findings indicate that when the quality differentiation between medications is small, the strategy for introducing medication suppliers varies significantly across different agreements. Moreover, the healthcare platform is more likely to adopt an agency selling agreement and introduce a high-quality supplier when the commission rate and cost of medications are both relatively high, which can result in an increased patient surplus. Surprisingly, we demonstrate that a greater differentiation in medication quality does not always benefit the platform when introducing a high-quality supplier. The study provides strategic insights into how a healthcare platform can effectively balance and enhance both its profitability and patient surplus through careful management of medication quality differentiation.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"286 ","pages":"Article 109639"},"PeriodicalIF":9.8,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144134599","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}