Lotte van Hezewijk , Nico P. Dellaert , Willem L. van Jaarsveld
{"title":"Scalable deep reinforcement learning in the non-stationary capacitated lot sizing problem","authors":"Lotte van Hezewijk , Nico P. Dellaert , Willem L. van Jaarsveld","doi":"10.1016/j.ijpe.2025.109601","DOIUrl":"10.1016/j.ijpe.2025.109601","url":null,"abstract":"<div><div>Capacitated lot sizing problems in situations with stationary and non-stationary demand (SCLSP) are very common in practice. Solving problems with a large number of items using Deep Reinforcement Learning (DRL) is challenging due to the large action space. This paper proposes a new Markov Decision Process (MDP) formulation to solve this problem, by decomposing the production quantity decisions in a period into sub-decisions, which reduces the action space dramatically. We demonstrate that applying Deep Controlled Learning (DCL) yields policies that outperform the benchmark heuristic as well as a prior DRL implementation. By using the decomposed MDP formulation and DCL method outlined in this paper, we can solve larger problems compared to the previous DRL implementation. Moreover, we adopt a non-stationary demand model for training the policy, which enables us to readily apply the trained policy in dynamic environments when demand changes.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"284 ","pages":"Article 109601"},"PeriodicalIF":9.8,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143725367","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}
Surajit Bag , Susmi Routray , Muhammad Sabbir Rahman , Santosh Kumar Shrivastav
{"title":"Investigate the effect of green hydrogen supply chain integration on supply chain resilience: Organization information processing theory perspective","authors":"Surajit Bag , Susmi Routray , Muhammad Sabbir Rahman , Santosh Kumar Shrivastav","doi":"10.1016/j.ijpe.2025.109613","DOIUrl":"10.1016/j.ijpe.2025.109613","url":null,"abstract":"<div><div>Integrating green hydrogen supply chains is crucial in enhancing firms’ resilience in a world characterized by VUCA (volatility, uncertainty, complexity, and ambiguity). Using organization information processing theory, this study explores the impact of green hydrogen supply chain integration and planning on supply chain resilience under the conditional moderating effect of social uncertainties. The proposed conceptual model is tested using data from 600 professionals in the green hydrogen domain, and hypotheses testing is performed using structural equation modeling. The findings indicate that green hydrogen supply chain integration positively influences resilience. The results support the moderated mediation hypothesis, suggesting that the indirect effect of green hydrogen supply chain integration on green hydrogen supply chain resilience through comprehensiveness of planning in green hydrogen operations is moderated by social uncertainties. This study provides significant theoretical and practical implications for academics and practitioners in the green hydrogen domain.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"284 ","pages":"Article 109613"},"PeriodicalIF":9.8,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143740046","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}
Néstor Fabián Ayala , Jassen Rodrigues da Silva , Maria Auxiliadora Cannarozzo Tinoco , Nicola Saccani , Alejandro G. Frank
{"title":"Artificial Intelligence capabilities in Digital Servitization: Identifying digital opportunities for different service types","authors":"Néstor Fabián Ayala , Jassen Rodrigues da Silva , Maria Auxiliadora Cannarozzo Tinoco , Nicola Saccani , Alejandro G. Frank","doi":"10.1016/j.ijpe.2025.109604","DOIUrl":"10.1016/j.ijpe.2025.109604","url":null,"abstract":"<div><div>The advancement of digital technologies and the pursuit of higher-value solutions have driven companies to expand their portfolios with smart products and digital services, resulting in the innovation known as 'digital servitization.' This concept merges servitization —integrating services with products— and digitization —enhancing operations through digital technologies. While previous research has examined digital servitization and smart technologies, a gap remains in understanding how Artificial Intelligence (AI) specifically supports various types of digital servitization across both back-office and front-office activities. This study addresses this gap by investigating how AI enhances digital servitization through six case studies of companies implementing AI-driven servitized solutions. Adopting a capability theoretical perspective, we analyze the application of AI in both back-office and front-office activities for the delivery of base, intermediate, and advanced services. Our findings reveal that AI's role varies by service type, affecting customer interactions and operational tasks differently. We present a theoretical framework with five propositions that elucidate how AI capabilities enhance digital servitization. This framework gives scholars a refined understanding of AI's roles beyond the generalized black box approach and offers practitioners practical insights on leveraging AI for digital transformation.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"284 ","pages":"Article 109604"},"PeriodicalIF":9.8,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143740050","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":"Analysis of optimal defective allowance policies for reducing product returns under alternative modeling of consumer behavior","authors":"Christos Zikopoulos","doi":"10.1016/j.ijpe.2025.109609","DOIUrl":"10.1016/j.ijpe.2025.109609","url":null,"abstract":"<div><div>Motivated by the challenges of managing returns of products with cosmetic defects at a home appliances manufacturer, we investigate the establishment of a defective allowance policy as a strategy to encourage consumers to avoid returning defective products. By offering a discount to consumers, the manufacturer can achieve cost savings by avoiding replacement expenses, including those related to returns handling and transportation. To our knowledge, this study is the first to analytically determine the optimal discount rate that a manufacturer should offer is such cases. We explore various models of consumer response to discounts and analyze their impact on both the optimal decisions and the financial outcomes of the defective allowance policy. Our findings indicate that simplistic consumer behavior models may reduce policy's effectiveness and underestimate its benefits, potentially deterring manufacturers from adopting such policies. Additionally, we examine differences in the optimal discount policy across product categories that differ in manufacturing cost, remaining value, handling and transportation costs, and price. Our analysis indicates that the ratio of replacement cost to product price plays a critical role in determining the optimal discount. Also, we find that product price exerts a greater influence on the optimal discount rate, whereas the impact of replacement costs depends on the price level: for high-priced products, these costs have negligible effect on the discount, whereas for low-priced products, these costs affect the optimal discount rate. Additionally, for lower-priced products, improved financial benefits are observed. Our analysis further suggests that accurately modeling consumer behavior and precisely determining the optimal discount rate are essential for maximizing the benefits of a defective allowance policy.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"284 ","pages":"Article 109609"},"PeriodicalIF":9.8,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143747578","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":"Easy-to-use estimators for waste, on shelf availability and number of orders in a periodic review inventory system with perishable items","authors":"Karel van Donselaar, Rob Broekmeulen","doi":"10.1016/j.ijpe.2025.109608","DOIUrl":"10.1016/j.ijpe.2025.109608","url":null,"abstract":"<div><div>We consider a periodic review inventory system with perishable items having a fixed case pack size and a shelf life between three and nine days. To assist retailers in reducing food waste, we develop easy-to-use estimators for the waste fraction, the on shelf availability and the number of orders. Since the estimators are easy to use, managers can develop their own logic and tools to support assortment, buying and replenishment decisions for perishable items. We assume stochastic discrete demand, consumers buying the oldest items first and a replenishment policy which considers information on the ages of the inventory on the shelf. The estimators can be used for classification, evaluation and optimization purposes. The average relative cost error when using the easy-to-use estimators to determine the optimal safety buffer as well as the optimal case pack size in the base setting is equal to 0.40 % and its standard deviation is equal to 1.19 %. Relaxing the assumptions in the model leads to average relative cost errors which are still less than 1 % except for two scenario's: when demand shows a very strong week pattern and when a large part of customers do not buy the oldest item first. For those scenario's additional research is needed. While the estimators perform well for classification and cost optimization in most scenario's, the estimators may be far off when used as stand-alone estimators. For those situations we suggest to use a more advanced estimator. Hence we also determine the added value from using more advanced estimators.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"284 ","pages":"Article 109608"},"PeriodicalIF":9.8,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143705854","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}
Mao Xu , Ying Kei Tse , Ruoqi Geng , Zhenyuan Liu , Andrew Potter
{"title":"Greenwashing and market value of firms: An empirical study","authors":"Mao Xu , Ying Kei Tse , Ruoqi Geng , Zhenyuan Liu , Andrew Potter","doi":"10.1016/j.ijpe.2025.109606","DOIUrl":"10.1016/j.ijpe.2025.109606","url":null,"abstract":"<div><div>In today's business environment, green or sustainable claims are rising as companies strive to strengthen environmental practices in response to climate change and sustainable development challenges. However, with increasing expectations of sustainable performance, companies encounter mounting financial pressure to adopt more efficient sustainable practices, which may lead some to exploit sustainability efforts for their own gain. Many companies make environmentally friendly assertions to conceal or mask their actual activities—a phenomenon known as greenwashing—which fosters public scepticism about the authenticity of their green messaging. This study employs an event study methodology to examine how the stock market values greenwashing news, drawing on 121 global greenwashing news since the 2015 Paris Agreement. Our findings reveal a negative correlation between greenwashing news and stock market reactions. The market reactions to greenwashing news are more negative for firms with greater ESG performance than for weak ESG performance. Additionally, greenwashing news supported by concrete evidence elicits stronger adverse reactions. Companies operating in the manufacturing industry experience more significant market value losses than those in the service sector. The findings also indicate that the Asia-Pacific market demonstrates particularly strong negative responses to greenwashing news compared to other stock markets. This study contributes to the signalling theory and advances the literature on corporate sustainability practices by providing empirical insights in a global context.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"284 ","pages":"Article 109606"},"PeriodicalIF":9.8,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143696658","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":"Optimal security and pricing strategies for AI cloud service providers: Balancing effort and price discounts across public, private, and hybrid AI cloud models","authors":"Xiaotong Guo , Yong He , Joshua Ignatius","doi":"10.1016/j.ijpe.2025.109605","DOIUrl":"10.1016/j.ijpe.2025.109605","url":null,"abstract":"<div><div>In this study, we focus on cloud security and pricing as key factors that influence end users' choices. We develop an analytical model to examine how an artificial intelligence (AI) cloud service provider optimally sets security investments and price discounts, considering users' different views of public, private, and hybrid AI cloud services. Our results show how end users' characteristics and market dynamics affect these strategies and reveal the balance providers must strike between improving user experiences, capturing market share, and maximizing profits. We find that the provider's control over AI cloud security—along with security costs for both the provider and users, as well as users' potential security losses—plays a critical role in shaping effective strategies. In low-security-loss environments, end users gain more from choosing public AI cloud solutions. However, private AI cloud solutions become more favorable if the provider's security cost coefficient falls within certain limits. In the hybrid AI cloud scenario, the model becomes more complex. Under some conditions, security investment and price discounts act as complementary strategies; in others, they substitute for one another. We also analyze how these choices affect market share and profitability, and find that in some cases, security investments can outperform price discounts.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"284 ","pages":"Article 109605"},"PeriodicalIF":9.8,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143714325","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}
Ahmed Mohammed , Ana Beatriz Lopes de Sousa Jabbour , Nasiru Zubairu , Charbel Jose Chiappetta Jabbour , Hajer Al Naabi
{"title":"Food waste in the era of e-commerce: A novel farm-to-fork management methodology","authors":"Ahmed Mohammed , Ana Beatriz Lopes de Sousa Jabbour , Nasiru Zubairu , Charbel Jose Chiappetta Jabbour , Hajer Al Naabi","doi":"10.1016/j.ijpe.2025.109603","DOIUrl":"10.1016/j.ijpe.2025.109603","url":null,"abstract":"<div><div>Online shopping is a growing market, and research on food waste (FW) in e-commerce food supply chains (e-FSCs) is limited. The e-FSC comprises competitive, complex, and evolving value streams, requiring advanced methodologies to address the issue of e-food wastage. This work develops a novel empirical-analytical farm-to-fork e-FW management methodology (F-t-F-eFWMM) to explore, measure, and mitigate FW in e-FSCs, focusing on the Sultanate of Oman as an empirical case study. As the case study, questionnaires were developed and administered to collect data from two leading retailers. The data collection extends to their suppliers, distributors, last-mile transporters (delivery), and consumers within the e-FSC. In addition, two rounds of meetings with senior managers and supply chain partners upstream and downstream of the e-FSC were facilitated to validate and extend prior findings. Subsequently, multi-criteria decision-making (MCDM) algorithms were employed to analytically identify the root causes of FW across the e-FSC network. The research highlighted ‘lack of production planning,’ ‘overstocking,’ and ‘inadequate storage’ as significant factors at the supply, distribution, and consumption stages, respectively. The main contributors to food waste (FW) were consumers, suppliers, and retailers, with retailers playing a crucial role in e-FSC compared to traditional physical FSC. Identified strategies for mitigation included the implementation of legislation, the adoption of advanced technologies, and enhanced forecasting methods. This study offers practical guidance for policymakers and practitioners to create effective interventions for electronic food supply chains.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"285 ","pages":"Article 109603"},"PeriodicalIF":9.8,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143776817","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":"Effects of operations executives’ power on shareholder wealth","authors":"Mehdi Nezami , Sara Rezaee Vessal , Ali Shantia","doi":"10.1016/j.ijpe.2025.109602","DOIUrl":"10.1016/j.ijpe.2025.109602","url":null,"abstract":"<div><div>This study investigates the effect of operations executives' power (OEP) within a firm's organizational structure on the firm's shareholder value. In doing so, we employ a multidimensional measure that captures the relative power dynamics within a firm's TMT and is sensitive to shifts in these dynamics, enabling us to more precisely operationalize the power held by operations executives. Further, we link OEP to abnormal stock returns to evaluate the market's perception of operations executives' influence within a firm's TMT, and to idiosyncratic stock returns risk to explore how this influence contributes to the uncertainty in stock returns. In addition, we examine the contingency roles of firm maturity and market turbulence in moderating the OEP–shareholder value relationship. Using a longitudinal dataset of manufacturing firms (SIC 20–39) from 1998 to 2018, our findings reveal that while OEP boosts abnormal stock returns, it negatively impacts idiosyncratic stock returns risk. Additionally, firm maturity reduces the positive (resp., negative) effect of OEP on abnormal stock returns (resp., idiosyncratic stock return risk), whereas market turbulence enhances the positive (resp., negative) effect of OEP on abnormal stock returns (resp., idiosyncratic stock returns risk). These findings contribute to a deeper understanding of the dynamic interplay between operations executives' influence, firm characteristics, and market conditions in driving shareholder value.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"284 ","pages":"Article 109602"},"PeriodicalIF":9.8,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143714314","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":"Incentives or time-of-use pricing: Strategic responses to electricity demand response programs for energy-intensive manufacturers","authors":"Yunrong Zhang , Zhaofu Hong , Zhixiang Chen","doi":"10.1016/j.ijpe.2025.109588","DOIUrl":"10.1016/j.ijpe.2025.109588","url":null,"abstract":"<div><div>The integration of renewable energy into the electricity grid introduces significant challenges due to its intermittent nature, necessitating effective electricity demand response programs (EDRPs) to manage industrial consumption patterns. Energy-intensive manufacturers, while well-positioned to benefit from programs such as Time-of-Use (TOU) pricing and Incentive-Based Programs (IBPs), encounter operational complexities associated with production adjustments and potential reductions, complicating their participation. This study develops an analytical model to explore optimal responsive strategies for manufacturers under TOU pricing and IBPs, with the goal of minimizing total operational costs. The results indicate that TOU pricing enables manufacturers to adopt either load shifting (LS) or load reduction (LR) strategies depending on penalty costs. However, under IBPs, insufficient incentives often result in non-responsiveness (NP). While higher off-peak responsive costs typically make LR strategies more appealing, manufacturers under TOU pricing are more likely to adopt LS strategy as responsive costs increase, when faced with shorter expected peak periods. In contrast, the choice between LS and NP strategies under IBPs is unaffected by peak period uncertainty. A comparative analysis reveals that IBPs offer superior responsive performance when penalty costs are sufficiently high, but TOU pricing generally outperforms IBPs in productive performance across most scenarios. These findings, illustrated through a case study, provide valuable insights for manufacturers in selecting the most appropriate responsive strategies, helping them navigate the trade-offs between electricity cost savings and operational burdens under different EDRPs.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"284 ","pages":"Article 109588"},"PeriodicalIF":9.8,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143681102","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}