International Journal of Production Economics最新文献_第10页

Leveraging artificial intelligence to facilitate green servitization: Resource orchestration and Re-institutionalization perspectives

IF 9.8 1区工程技术

International Journal of Production Economics Pub Date : 2025-01-10 DOI: 10.1016/j.ijpe.2025.109519

Soumyadeb Chowdhury , Shuang Ren , Robert Glenn Richey Jnr.

{"title":"Leveraging artificial intelligence to facilitate green servitization: Resource orchestration and Re-institutionalization perspectives","authors":"Soumyadeb Chowdhury , Shuang Ren , Robert Glenn Richey Jnr.","doi":"10.1016/j.ijpe.2025.109519","DOIUrl":"10.1016/j.ijpe.2025.109519","url":null,"abstract":"<div><div>Research in operations and supply chain management (O&SCM) has highlighted drivers of digital servitization, along with the influence of Industry 4.0 technologies, such as artificial intelligence (AI). Amidst growing environmental concerns, green servitization (GS) has emerged as a strategic alternative to achieve sustainability. However, few studies have examined the interaction between AI capabilities and GS. To address this gap, this study integrates the resource orchestration theory and theory of institutional entrepreneurship for sustainable organizations, to develop a conceptual model examining the relationship between AI-driven decision support systems (ADSS) capabilities, supply-chain alertness (SCA), resource orchestration (REO), re-institutionalization (REI), circular economy practices (CEP), and GS. A survey was conducted with 248 UK supply chain managers and partial least squares-structural equation modelling was used for analysis. The results indicate that ADSS capabilities will significantly enhance SCA (β = 0.597), and the latter will significantly influence REO (β = 0.461), REI (β = 0.495), and CEP (β = 0.160). We also found that the CEP will significantly impact GS (β = 0.781). Both REO (β = 0.169) and REI (β = 0.142) significantly mediates the relationship between SCA and CEP, i.e., REO and REI will facilitate implementing CEP resulting from AI-driven SCA. These findings highlight the critical role of ADSS in enabling managers to orchestrate resources and implement new institutional frameworks, essential for adopting GS in the supply chain.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"281 ","pages":"Article 109519"},"PeriodicalIF":9.8,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143259474","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}

引用次数: 0

Functional resonance analysis via a genetic algorithm to ensure cost-effective maintenance planning

IF 9.8 1区工程技术

International Journal of Production Economics Pub Date : 2025-01-08 DOI: 10.1016/j.ijpe.2025.109516

Riccardo Patriarca, Lorenzo Lovaglio, Francesco Simone

{"title":"Functional resonance analysis via a genetic algorithm to ensure cost-effective maintenance planning","authors":"Riccardo Patriarca, Lorenzo Lovaglio, Francesco Simone","doi":"10.1016/j.ijpe.2025.109516","DOIUrl":"10.1016/j.ijpe.2025.109516","url":null,"abstract":"<div><div>The tight interaction between organizations, humans and technologies drives production systems towards an ever-increasing complexity. Novel methods are required to support complex managerial actions and ensure their cost effectiveness. In this context, the objective of this research is to propose a methodology to optimize the maintenance operations of safety-critical production and service systems. The methodology is grounded on the principles of the Functional Resonance Analysis Method (FRAM), that has proved to be an effective approach to study complex socio-technical orchestrations. The FRAM is then integrated with a genetic algorithm (GA) to quantify functional performance indicators capable of optimizing maintenance practices, via an economically advantageous tasks allocation. The methodology is instantiated on a real case study related to maintenance operations of aircraft. Promising results have been obtained in the proposed application: a saving of almost 6% (128 man-hours) in resource allocation over 16 days of work has been highlighted for the real case study at hand. The methodological result provides maintenance planners with a support tool to guide decision making, ensuring cost effectiveness of operations, and emphasizing the direct relationships with economical convenience. Overall, the integration of the FRAM with GA proposed in this paper presents a strategy to address cost-effective maintenance planning in complex systems.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"281 ","pages":"Article 109516"},"PeriodicalIF":9.8,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143194302","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}

引用次数: 0

Cost-effective industrial internet of things network planning for sustainable manufacturing systems

IF 9.8 1区工程技术

International Journal of Production Economics Pub Date : 2025-01-07 DOI: 10.1016/j.ijpe.2025.109517

Lingxiang Yun , Lin Li , Jiapei Zhang , Jingze Guan

{"title":"Cost-effective industrial internet of things network planning for sustainable manufacturing systems","authors":"Lingxiang Yun , Lin Li , Jiapei Zhang , Jingze Guan","doi":"10.1016/j.ijpe.2025.109517","DOIUrl":"10.1016/j.ijpe.2025.109517","url":null,"abstract":"<div><div>The industrial Internet of Things (IoT) has been gaining significant momentum and is considered a promising technology for establishing a foundation for energy and carbon management in the manufacturing sector. Existing management studies commonly assume the availability of IoT data for all manufacturing equipment, yet connecting every single piece of equipment requires enormous investments without necessarily yielding significant improvements in management effectiveness. In practice, the value derived from IoT data collected from diverse manufacturing equipment varies based on the unique features of the equipment and its role within the manufacturing system. Therefore, this study proposes a planning method for cost-effective industrial IoT networks in the context of sustainable manufacturing. The proposed approach jointly considers the quality-of-service requirements of the IoT network and the characteristics of the manufacturing system. It aims to balance the trade-offs between industrial IoT investments and the effectiveness of IoT data-enabled carbon management in manufacturing systems. In addition, an efficient algorithm is developed to solve the network planning problem and identify cost-effective solutions. Case studies on automobile assembly lines indicate the effectiveness of the proposed method in generating economically favorable industrial IoT networks, leading to a 38.9% reduction in industrial IoT implementation costs while maintaining satisfactory carbon emission reduction effects for manufacturing systems.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"281 ","pages":"Article 109517"},"PeriodicalIF":9.8,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143194272","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}

引用次数: 0

Strategic navigation of supply chain ambidexterity for resilience and agility in the digital era: A review

IF 9.8 1区工程技术

International Journal of Production Economics Pub Date : 2025-01-02 DOI: 10.1016/j.ijpe.2024.109514

Sachin Kumar, Vinay Singh

{"title":"Strategic navigation of supply chain ambidexterity for resilience and agility in the digital era: A review","authors":"Sachin Kumar, Vinay Singh","doi":"10.1016/j.ijpe.2024.109514","DOIUrl":"10.1016/j.ijpe.2024.109514","url":null,"abstract":"<div><div>Navigating the complexities and uncertainties of the modern business landscape requires resilient supply chains to ensure long-term viability and success. Referring to Industry 5.0 principles, Supply Chain Resilience must accommodate the characteristics of adaptability, sustainability, customer centricity, and innovativeness to accommodate the ambidextrous characteristics. The present study aims to address its objectives by examining current trends and themes in Supply Chain Ambidexterity (SCA) and exploring the intricate relationship among Supply Chain Ambidexterity, Resilience, Agility, and Digital Transformation while also identifying possible directions for future research. Through a bibliometric analysis of 290 articles from the Web of Science (WoS) and Scopus databases until August 2024, complemented with a systematic literature review of 77 articles, this research proposed an integrated research framework. It reveals a significant relationship between Digital Transformation, Dynamic capabilities, and their role in enhancing SCA, with Digital Transformation as an influencing factor. The research highlights the influence of SCA on resilience and agility empowered by Digital Transformation. This research also proposes ten propositions based on the systematic literature review and identifies research gaps for each proposition. This study is positioned at the nexus of bibliometric analysis and systematic literature review to identify research trends and provide a s an overall comprehensive overview of SCA in the context of Dynamic Capabilities, Digital Transformation, Supply Chain Resilience, and Agility. Its findings present the current state of research in SCA and, therefore, guide future academic endeavors in the dynamic arena. This research serves as a significant resource by pinpointing existing research gaps, delineating future directions, and providing practical recommendations for implementation within the industry.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"281 ","pages":"Article 109514"},"PeriodicalIF":9.8,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143194233","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}

引用次数: 0

The big data newsvendor problem under demand and yield uncertainties

IF 9.8 1区工程技术

International Journal of Production Economics Pub Date : 2025-01-01 DOI: 10.1016/j.ijpe.2024.109409

Tiantian Cao , Yi Yang , Han Zhu , Mingyue Yu

{"title":"The big data newsvendor problem under demand and yield uncertainties","authors":"Tiantian Cao , Yi Yang , Han Zhu , Mingyue Yu","doi":"10.1016/j.ijpe.2024.109409","DOIUrl":"10.1016/j.ijpe.2024.109409","url":null,"abstract":"<div><div>We consider a variant of the classic newsvendor problem in which the firms face both demand and yield randomness. Different from the existing literature, we assume that decision-makers have no priori knowledge of the distribution functions of demand and yield, but have access to past observations of demand, yield, and related feature information. We integrate predictive machine learning algorithms to determine the optimal order quantity directly from historical data, respectively based on the empirical risk minimization (ERM) principle, kernel regression approach, <span><math><mi>K</mi></math></span>-nearest neighbors (<span><math><mi>k</mi></math></span>NN), and classification and regression trees (CART). These data-driven approaches can not only sufficiently capture useful information from relevant features, but also take into account the structure of the optimization problem, which can effectively avoid inconsistency solutions in the traditional “prediction-then-optimization” approach. Most importantly, we establish out-of-sample generalization error bounds under mild conditions using uniform stability-based and Rademacher complexity-based methods in computational learning theory and then show the asymptotic optimality of the data-driven approaches based on kernel regression and <span><math><mi>k</mi></math></span>NN. Our data-driven approaches can tractably deal with both independent and interdependent demand and yield uncertainties. Finally, numerical experiments based on both synthetic data and real data are conducted to compare our proposed methods with two traditional benchmark approaches, including the Sample Average Approximation (SAA) approach and the traditional “Predict-then-Optimize” framework based on CART. We observe that our data-driven approaches can achieve significant performance improvement and the one based on the kernel regression method tends to perform the best on real data, with an average daily cost saving of up tp 54.92%.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"279 ","pages":"Article 109409"},"PeriodicalIF":9.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143134846","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}

引用次数: 0

Mitigating the negative financial effects of extreme weather events through supply chain analytics

IF 9.8 1区工程技术

International Journal of Production Economics Pub Date : 2025-01-01 DOI: 10.1016/j.ijpe.2024.109441

Yangchun Xiong , Runyue Han , Xiaoxuan Ma , Hugo K.S. Lam , Andrew Lyons

{"title":"Mitigating the negative financial effects of extreme weather events through supply chain analytics","authors":"Yangchun Xiong , Runyue Han , Xiaoxuan Ma , Hugo K.S. Lam , Andrew Lyons","doi":"10.1016/j.ijpe.2024.109441","DOIUrl":"10.1016/j.ijpe.2024.109441","url":null,"abstract":"<div><div>Despite extensive discussions on the value of integrating big data analytics into supply chains, or supply chain analytics (SCA) for short, it remains unclear whether SCA can effectively help firms mitigate the negative financial impacts of extreme weather events. To address this important research question, we first employed the event study methodology to quantify extreme weather events' financial effects in terms of abnormal stock returns. Then, we compared the difference in abnormal stock returns between firms that have adopted SCA and matched control firms without SCA adoption. Our event study results indicate that, although these events affected firms' stock returns negatively, the effects were less severe for firms with (rather than without) SCA adoption. Furthermore, firms having more stable innovation outputs reaped greater benefits from SCA in the extreme weather context. Conversely, firms facing more unstable market demands benefited more from SCA in the extreme weather context. Overall, our research demonstrates the mitigating role played by SCA during extreme weather events but also reveals how this mitigating role is contingent on the firm's internal and external operating uncertainties.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"279 ","pages":"Article 109441"},"PeriodicalIF":9.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143134847","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}

引用次数: 0

Extreme weather and production economics: Insights, challenges, and future directions

IF 9.8 1区工程技术

International Journal of Production Economics Pub Date : 2024-12-27 DOI: 10.1016/j.ijpe.2024.109504

Tsan-Ming Choi , Hugo K.S. Lam , Joseph Sarkis , Yuanzhu Zhan , Qinghua Zhu

引用次数: 0

Examining the effects of blockchain technology on sales models: A study from the dual perspectives of economy and environment

IF 9.8 1区工程技术

International Journal of Production Economics Pub Date : 2024-12-26 DOI: 10.1016/j.ijpe.2024.109502

Zichen Zou , Mingwu Liu , Yu Gong , Xinwei Dong , Jiang Duan

引用次数: 0

Supply chain strategic behavior and coordination with a risk-averse manufacturer under random yield and demand

IF 9.8 1区工程技术

International Journal of Production Economics Pub Date : 2024-12-24 DOI: 10.1016/j.ijpe.2024.109492

Liangwei Yu, Boshi Tian

{"title":"Supply chain strategic behavior and coordination with a risk-averse manufacturer under random yield and demand","authors":"Liangwei Yu, Boshi Tian","doi":"10.1016/j.ijpe.2024.109492","DOIUrl":"10.1016/j.ijpe.2024.109492","url":null,"abstract":"<div><div>Random yield and demand (dual random) have been long plaguing the operational decisions of supply chain enterprises. In this paper, we introduce a comprehensive supply chain model characterized by a risk-averse manufacturer and a risk-neutral distributor, with the latter providing a credit guarantee to secure financing for the former. Employing the conditional value-at-risk (CVaR) criterion, we conduct a thorough analysis of the strategic dynamics inherent in the dual random supply chain, yielding key findings. Firstly, our investigation begins by defining a risk-dominant yield rate, from which we derive a risk-averse level-dependent safety purchasing threshold. We find that the distributor’s purchasing decision at this threshold depends on a comparative assessment of revenue and risk, which is primarily influenced by the manufacturer’s risk attitude and the guarantee coefficient. Secondly, we discover that the production strategies of manufacturers are predominantly influenced by yield risk if the distributor’s actual purchasing quantity falls below the threshold, leading to the maintenance of a safety production quantity. Conversely, when the purchasing quantity surpasses the threshold, the distributor’s behavior becomes the focal point, prompting the manufacturer to expand production. Lastly, we identify that the credit guarantee plays a significant role in operational decisions only when the distributor’s orders exceed the safety purchasing threshold and the manufacturer exhibits a high risk tolerance. Under these circumstances, we design the credit guarantee contract to facilitate supply chain coordination, mitigating the double marginal effect and enhancing overall supply chain efficiency.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"281 ","pages":"Article 109492"},"PeriodicalIF":9.8,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143194235","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}

引用次数: 0

Optimizing Q-commerce delivery: Unravelling the interplay of fee, penalty, and rider-platform collaborative efforts

IF 9.8 1区工程技术

International Journal of Production Economics Pub Date : 2024-12-24 DOI: 10.1016/j.ijpe.2024.109503

Ashish Raj, Debabrata Das

{"title":"Optimizing Q-commerce delivery: Unravelling the interplay of fee, penalty, and rider-platform collaborative efforts","authors":"Ashish Raj, Debabrata Das","doi":"10.1016/j.ijpe.2024.109503","DOIUrl":"10.1016/j.ijpe.2024.109503","url":null,"abstract":"<div><div>Q-commerce businesses that promise to deliver goods and services in 10–20 min are growing 20–25% faster than those that deliver in hours or longer. Although the success of a Q-commerce company depends heavily on the performance of its delivery riders, in most cases, the riders are gig workers and face challenges related to job security, variable compensation, and long working hours. At the same time, retaining skilled and professional riders is a challenge for Q-commerce companies. Therefore, in the present study, we develop an analytical model that studies the interaction between “<em>the delivery fees paid to the riders by the Q-commerce company</em>” and “<em>the efforts put by both the players - the delivery riders as well as the Q-commerce company towards a successful delivery</em>” under two different setups: <em>with</em> versus <em>without penalty</em>. The findings suggest that prior commitments to efforts by the Q-commerce company lead to better payoffs for both the company and the riders. Moreover, contrary to popular belief, the analysis shows that the sharing of rider's effort-cost mechanism in which a Q-commerce company shares some percentage of the operating cost of the riders accrues more significant benefits. Finally, this study uncovers various managerial insights into how both players' payoffs are affected by the delivery fee offered to the riders, any penalties imposed on them, and the individual and joint efforts of both the riders and Q-commerce companies. It also aids in framing effective policies that the decision-makers could use to improve the performance of Q-commerce delivery.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"281 ","pages":"Article 109503"},"PeriodicalIF":9.8,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143194353","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}

引用次数: 0