Pub Date : 2025-02-14DOI: 10.1016/j.ijpe.2025.109563
Najam Anjum , Antony Paulraj , Constantin Blome , Christopher Rajkumar
While learning by doing is considered a key to new knowledge creation, little is known if, by its inherent nature, environmental process design could benefit from this mode of knowledge creation. Furthermore, it is also necessary to understand how empowered employees can create more conducive designs for better environmental performance and how these phenomena are affected by their ability to freely experiment and learn through experience and experiments. Through a sample of 500 German and USA-based manufacturing firms, we establish that learning by doing positively affects both environmental process design and the environmental performance of firms. Employee empowerment was also found to moderate this relationship positively but to varying degrees. Our study has far-reaching implications for both academia and industry as it furthers the agenda of human resource management research that aims to find ways in which employees could enhance the environmental performance of firms.
{"title":"Environmental process design and performance: Understanding the key role of learning by doing and employee empowerment","authors":"Najam Anjum , Antony Paulraj , Constantin Blome , Christopher Rajkumar","doi":"10.1016/j.ijpe.2025.109563","DOIUrl":"10.1016/j.ijpe.2025.109563","url":null,"abstract":"<div><div>While learning by doing is considered a key to new knowledge creation, little is known if, by its inherent nature, environmental process design could benefit from this mode of knowledge creation. Furthermore, it is also necessary to understand how empowered employees can create more conducive designs for better environmental performance and how these phenomena are affected by their ability to freely experiment and learn through experience and experiments. Through a sample of 500 German and USA-based manufacturing firms, we establish that learning by doing positively affects both environmental process design and the environmental performance of firms. Employee empowerment was also found to moderate this relationship positively but to varying degrees. Our study has far-reaching implications for both academia and industry as it furthers the agenda of human resource management research that aims to find ways in which employees could enhance the environmental performance of firms.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"282 ","pages":"Article 109563"},"PeriodicalIF":9.8,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143436423","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}
Pub Date : 2025-02-13DOI: 10.1016/j.ijpe.2025.109561
Jianwen Zheng , Justin Zuopeng Zhang , Muhammad Mustafa Kamal , Sachin Kumar Mangla
Existing research emphasizes the importance of understanding the digital transformation process, yet there remains a significant gap in capturing its dynamic stages and transitions, particularly for small and medium-sized enterprises (SMEs). To address this gap, this study draws on organizational information processing theory and analyzes interview data from six traditional manufacturing SMEs. The findings lead to the development of a data-driven digital transformation process model comprising three distinct stages: (1) data-informed operational excellence, (2) data-synchronized supply chain integration, and (3) data-catalyzed ecosystem innovation. This model also maps the evolution of firm value propositions across these stages: (1) intrinsic value mapping, (2) value chain alignment, and (3) ecosystem value co-creation. Additionally, the study identifies critical preconditions for stage transitions, including supply chain mastery to progress from Stage 1 to Stage 2 and strategic ecosystem analytics integration to advance from Stage 2 to Stage 3. By offering a structured framework for understanding data-driven digital transformation, this study makes a significant contribution to the literature, particularly within the context of traditional manufacturing SMEs.
{"title":"A dual evolutionary perspective on the Co-evolution of data-driven digital transformation and value proposition in manufacturing SMEs","authors":"Jianwen Zheng , Justin Zuopeng Zhang , Muhammad Mustafa Kamal , Sachin Kumar Mangla","doi":"10.1016/j.ijpe.2025.109561","DOIUrl":"10.1016/j.ijpe.2025.109561","url":null,"abstract":"<div><div>Existing research emphasizes the importance of understanding the digital transformation process, yet there remains a significant gap in capturing its dynamic stages and transitions, particularly for small and medium-sized enterprises (SMEs). To address this gap, this study draws on organizational information processing theory and analyzes interview data from six traditional manufacturing SMEs. The findings lead to the development of a data-driven digital transformation process model comprising three distinct stages: (1) data-informed operational excellence, (2) data-synchronized supply chain integration, and (3) data-catalyzed ecosystem innovation. This model also maps the evolution of firm value propositions across these stages: (1) intrinsic value mapping, (2) value chain alignment, and (3) ecosystem value co-creation. Additionally, the study identifies critical preconditions for stage transitions, including supply chain mastery to progress from Stage 1 to Stage 2 and strategic ecosystem analytics integration to advance from Stage 2 to Stage 3. By offering a structured framework for understanding data-driven digital transformation, this study makes a significant contribution to the literature, particularly within the context of traditional manufacturing SMEs.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"282 ","pages":"Article 109561"},"PeriodicalIF":9.8,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143419288","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}
Pub Date : 2025-02-11DOI: 10.1016/j.ijpe.2025.109533
Behzad Maleki Vishkaei , Pietro De Giovanni
This research examines smart mobility, specifically focusing on e-scooters as a mode of urban transportation. It underscores the advantages of e-scooters in smart cities while also addressing the issues stemming from incorrect riding practices. To understand the strategies of both cities and e-scooter companies, the study adopts a game theory approach. The research delves into how blockchain technology and hardware oracles can promote the appropriate use of e-scooters. In one scenario, the city allocates resources to infrastructure to facilitate e-scooter travel, while the e-scooter company defines its service. Nonetheless, continuous misuse of e-scooters negatively impacts both parties. Therefore, in another scenario, the research assesses how blockchain can detect and penalize incorrect behaviors using smart contracts. The findings reveal that while blockchain bolsters smart mobility and curbs the incorrect use of e-scooters, it might also dissuade certain users from utilizing the service, presenting a set of challenges to smart mobility.
{"title":"A smart mobility game with blockchain and hardware oracles","authors":"Behzad Maleki Vishkaei , Pietro De Giovanni","doi":"10.1016/j.ijpe.2025.109533","DOIUrl":"10.1016/j.ijpe.2025.109533","url":null,"abstract":"<div><div>This research examines smart mobility, specifically focusing on e-scooters as a mode of urban transportation. It underscores the advantages of e-scooters in smart cities while also addressing the issues stemming from incorrect riding practices. To understand the strategies of both cities and e-scooter companies, the study adopts a game theory approach. The research delves into how blockchain technology and hardware oracles can promote the appropriate use of e-scooters. In one scenario, the city allocates resources to infrastructure to facilitate e-scooter travel, while the e-scooter company defines its service. Nonetheless, continuous misuse of e-scooters negatively impacts both parties. Therefore, in another scenario, the research assesses how blockchain can detect and penalize incorrect behaviors using smart contracts. The findings reveal that while blockchain bolsters smart mobility and curbs the incorrect use of e-scooters, it might also dissuade certain users from utilizing the service, presenting a set of challenges to smart mobility.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"282 ","pages":"Article 109533"},"PeriodicalIF":9.8,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143436422","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}
Pub Date : 2025-02-11DOI: 10.1016/j.ijpe.2025.109556
He Zhu, Jiayao Hu, Ying Yang
While the significance of circular supply chains in boosting the sustainability of retired electric vehicle batteries through ongoing material secondary use and recycling is clear, there is a distinct absence of thorough studies that explore retired electric vehicle batteries from a circular supply chain standpoint. This gap is particularly evident in the lack of research detailing existing patterns, pinpointing research gaps, and offering directives for future inquiries. This study undertakes a systematic literature review, analysing 249 academic articles from Scopus and Web of Science up to September 2024. Three keyword clusters, which are supply chain management for battery recycling, environmental assessment, and economic analysis are identified by keyword co-occurrence networks. The structural dimension analysis further reveals that the existing literature predominantly focuses on recycling and remanufacturing within closed-loop supply chains, highlighting an incomplete current sustainability assessment. A circular supply chain framework and archetype for retired electric vehicle batteries, along with a future research agenda, have been proposed to guide research in four streams: i) open-loop supply chains, ii) novel business models, iii) empirical research for circular economy strategies, and iv) the sustainability assessment frameworks. This study enriches researchers and practitioners’ understanding of the current development of retired electric vehicle batteries circular supply chains, underlining the potential value of retired electric vehicle batteries, fostering effective collaboration among supply chain actors, and uncovering new business opportunities.
{"title":"Towards a circular supply chain for retired electric vehicle batteries: A systematic literature review","authors":"He Zhu, Jiayao Hu, Ying Yang","doi":"10.1016/j.ijpe.2025.109556","DOIUrl":"10.1016/j.ijpe.2025.109556","url":null,"abstract":"<div><div>While the significance of circular supply chains in boosting the sustainability of retired electric vehicle batteries through ongoing material secondary use and recycling is clear, there is a distinct absence of thorough studies that explore retired electric vehicle batteries from a circular supply chain standpoint. This gap is particularly evident in the lack of research detailing existing patterns, pinpointing research gaps, and offering directives for future inquiries. This study undertakes a systematic literature review, analysing 249 academic articles from Scopus and Web of Science up to September 2024. Three keyword clusters, which are supply chain management for battery recycling, environmental assessment, and economic analysis are identified by keyword co-occurrence networks. The structural dimension analysis further reveals that the existing literature predominantly focuses on recycling and remanufacturing within closed-loop supply chains, highlighting an incomplete current sustainability assessment. A circular supply chain framework and archetype for retired electric vehicle batteries, along with a future research agenda, have been proposed to guide research in four streams: i) open-loop supply chains, ii) novel business models, iii) empirical research for circular economy strategies, and iv) the sustainability assessment frameworks. This study enriches researchers and practitioners’ understanding of the current development of retired electric vehicle batteries circular supply chains, underlining the potential value of retired electric vehicle batteries, fostering effective collaboration among supply chain actors, and uncovering new business opportunities.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"282 ","pages":"Article 109556"},"PeriodicalIF":9.8,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143419287","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}
Pub Date : 2025-02-11DOI: 10.1016/j.ijpe.2025.109554
Umair Tanveer , Shamaila Ishaq , Thinh Gia Hoang
The emergence of blockchain technology is compelling firms to rethink traditional operations and management strategies, with asset tokenization presenting a transformative potential to optimize transaction processes and redefine value chains. This study explores how blockchain-enabled asset tokenization influences transaction efficiency, value creation, and risk distribution across different market contexts. Utilizing a multiple-case study design, this research analyzes four asset tokenization business cases in multiple sectors —real estate, gold, gaming assets, and carbon credits—through 30 semi-structured interviews with participants from each case. Our research findings indicate that while tokenization significantly enhances transaction efficiency and creates new value propositions, it also introduces complexities in governance and risk distribution, which may challenge market stability. This study contributes to the contemporary blockchain literature by empirically illustrating how asset tokenization alters traditional asset management and investment models, highlighting the importance of tailored regulatory frameworks to address this emerging blockchain-enabled business models. Additionally, the research offers practical insights for business practitioners, suggesting that a balanced approach is necessary to leverage the benefits of asset tokenization while safeguarding market trust and sustainability.
{"title":"Tokenized assets in a decentralized economy: Balancing efficiency, value, and risks","authors":"Umair Tanveer , Shamaila Ishaq , Thinh Gia Hoang","doi":"10.1016/j.ijpe.2025.109554","DOIUrl":"10.1016/j.ijpe.2025.109554","url":null,"abstract":"<div><div>The emergence of blockchain technology is compelling firms to rethink traditional operations and management strategies, with asset tokenization presenting a transformative potential to optimize transaction processes and redefine value chains. This study explores how blockchain-enabled asset tokenization influences transaction efficiency, value creation, and risk distribution across different market contexts. Utilizing a multiple-case study design, this research analyzes four asset tokenization business cases in multiple sectors —real estate, gold, gaming assets, and carbon credits—through 30 semi-structured interviews with participants from each case. Our research findings indicate that while tokenization significantly enhances transaction efficiency and creates new value propositions, it also introduces complexities in governance and risk distribution, which may challenge market stability. This study contributes to the contemporary blockchain literature by empirically illustrating how asset tokenization alters traditional asset management and investment models, highlighting the importance of tailored regulatory frameworks to address this emerging blockchain-enabled business models. Additionally, the research offers practical insights for business practitioners, suggesting that a balanced approach is necessary to leverage the benefits of asset tokenization while safeguarding market trust and sustainability.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"282 ","pages":"Article 109554"},"PeriodicalIF":9.8,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143419261","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}
Pub Date : 2025-02-04DOI: 10.1016/j.ijpe.2025.109540
Yuxin Zhang , Min Huang , Yaoxin Wu , Zhiguang Cao , Yuan Lin , Jie Zhang , Xingwei Wang
As carbon emissions become a significant issue worldwide, sustainability has emerged as a driving force in fourth-party logistics (4PL) network design. To ensure service quality, transportation time cannot be ignored. Considering the carbon cap-and-trade policy, a novel mixed-integer non-linear programming model is proposed to design a green 4PL network under the service time constraint. An equivalent reformulation is proposed to obtain the optimal solution for small-scale problems. For larger-scale problems, the Q-learning based dynamic memetic particle swarm optimisation algorithm is proposed to adaptively select suitable parameters and local search strategies for each individual. Numerical experimental results demonstrate the effectiveness and efficiency of proposed algorithm. Furthermore, the influence of 4PL, credit price, carbon cap, service time, and different carbon policies on the network are investigated. Compared with traditional third-party logistics, 4PL has more advantages in terms of cost, carbon emissions, and customer service. The credit price has a greater influence on cost and carbon emissions compared to the cap. Emissions sensitivity shifts from the purchased credit price under lower caps to the sell price under higher caps. The influence of the cap on emissions is driven by the prices of purchased and sold credits. The appropriate maximum allowable service time is crucial for cost and carbon emissions. Overall, the carbon cap-and-trade policy is beneficial to company economics and sustainable development.
{"title":"Green fourth-party logistics network design under carbon cap-and-trade policy","authors":"Yuxin Zhang , Min Huang , Yaoxin Wu , Zhiguang Cao , Yuan Lin , Jie Zhang , Xingwei Wang","doi":"10.1016/j.ijpe.2025.109540","DOIUrl":"10.1016/j.ijpe.2025.109540","url":null,"abstract":"<div><div>As carbon emissions become a significant issue worldwide, sustainability has emerged as a driving force in fourth-party logistics (4PL) network design. To ensure service quality, transportation time cannot be ignored. Considering the carbon cap-and-trade policy, a novel mixed-integer non-linear programming model is proposed to design a green 4PL network under the service time constraint. An equivalent reformulation is proposed to obtain the optimal solution for small-scale problems. For larger-scale problems, the Q-learning based dynamic memetic particle swarm optimisation algorithm is proposed to adaptively select suitable parameters and local search strategies for each individual. Numerical experimental results demonstrate the effectiveness and efficiency of proposed algorithm. Furthermore, the influence of 4PL, credit price, carbon cap, service time, and different carbon policies on the network are investigated. Compared with traditional third-party logistics, 4PL has more advantages in terms of cost, carbon emissions, and customer service. The credit price has a greater influence on cost and carbon emissions compared to the cap. Emissions sensitivity shifts from the purchased credit price under lower caps to the sell price under higher caps. The influence of the cap on emissions is driven by the prices of purchased and sold credits. The appropriate maximum allowable service time is crucial for cost and carbon emissions. Overall, the carbon cap-and-trade policy is beneficial to company economics and sustainable development.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"282 ","pages":"Article 109540"},"PeriodicalIF":9.8,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143372525","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}
Pub Date : 2025-02-04DOI: 10.1016/j.ijpe.2025.109535
André Luiz Siqueira Mota, Romulo Gonçalves Lins
The modernization of production and the consumer market’s demand for customized products in the commercial vehicle segment require new approaches and methodologies for development and manufacturing at competitive prices. Thus, to meet such needs, combined with the fact that companies are only interested in such demand with adequate financial results, it is necessary to adapt the customization process to the existing structure. The main objective of this research is to develop a structured method for designing and manufacturing customized commercial vehicles using serial production lines already installed and available in the automotive industries, mainly in environments where Industry 4.0 (I4.0) technologies are available. To this end, the proposed method is divided into three phases (Scoping phase, Design & Documentation, and Custom Production) in such a way as first to understand the customer’s needs, passing through the execution of the project in an optimized way based on standard products from the company’s portfolio to the manufacture of technically and financially possible modifications in Assembly Line (AL), through the application of Lean tools and I4.0 Technologies. The method is validated with a case study in a large company in the commercial vehicle market installed in Brazil, where the results obtained showed that it is possible to develop customized products with reduced time from existing products and among the modifications that can be manufactured in AL the results show an average reduction of over 80% in production times compared to manufacturing time in dedicated customization workshops, allowing the company to increase its annual production of customized vehicles in without any additional investment.
{"title":"Production of customized commercial vehicles in assembly line based on modified-to-order demands: A novel method and study case","authors":"André Luiz Siqueira Mota, Romulo Gonçalves Lins","doi":"10.1016/j.ijpe.2025.109535","DOIUrl":"10.1016/j.ijpe.2025.109535","url":null,"abstract":"<div><div>The modernization of production and the consumer market’s demand for customized products in the commercial vehicle segment require new approaches and methodologies for development and manufacturing at competitive prices. Thus, to meet such needs, combined with the fact that companies are only interested in such demand with adequate financial results, it is necessary to adapt the customization process to the existing structure. The main objective of this research is to develop a structured method for designing and manufacturing customized commercial vehicles using serial production lines already installed and available in the automotive industries, mainly in environments where Industry 4.0 (I4.0) technologies are available. To this end, the proposed method is divided into three phases (Scoping phase, Design & Documentation, and Custom Production) in such a way as first to understand the customer’s needs, passing through the execution of the project in an optimized way based on standard products from the company’s portfolio to the manufacture of technically and financially possible modifications in Assembly Line (AL), through the application of Lean tools and I4.0 Technologies. The method is validated with a case study in a large company in the commercial vehicle market installed in Brazil, where the results obtained showed that it is possible to develop customized products with reduced time from existing products and among the modifications that can be manufactured in AL the results show an average reduction of over 80% in production times compared to manufacturing time in dedicated customization workshops, allowing the company to increase its annual production of customized vehicles in <span><math><mrow><mo>≈</mo><mn>35</mn><mtext>%</mtext></mrow></math></span> without any additional investment.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"282 ","pages":"Article 109535"},"PeriodicalIF":9.8,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143372527","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}
Pub Date : 2025-02-01DOI: 10.1016/j.ijpe.2024.109498
Gopalakrishnan Narayanamurthy , R Sai Shiva Jayanth , Roger Moser , Tobias Schaefers , Narayan Prasad Nagendra
Agriculture financing in developing countries is dominated by informal lending. One challenge in the expansion of institutional (formal) credit is the lack of reliable data on the historical performance of farmers. Due to the absence of data, financial institutions face uncertainties that obstruct the decision-making process, leading to sub-optimal credit disbursal. Based on the theoretical lens of uncertainty reduction, this study focuses on achieving two key research objectives: identifying uncertainties in institutional crop credit management processes and examining how a data-driven digital transformation for social innovation based on satellite imagery analytics could alleviate these hindrances. We longitudinally study a satellite imagery analytics firm and complement the case data with stakeholder interviews. The results capture state space, option, and ethical uncertainties institutional lenders face in expanding crop credit and explain how data-driven digital transformation can reduce these uncertainties. Adopting such a data-driven digital transformation promises to make different stakeholder groups interact and collaborate to achieve the common objective of financial inclusion of small-scale economic actors. Further, we show that satellite imagery in crop credit management can significantly reduce the uncertainties caused by the lack of independent data sources.
{"title":"Data-driven digital transformation for uncertainty reduction – Application of satellite imagery analytics in institutional crop credit management","authors":"Gopalakrishnan Narayanamurthy , R Sai Shiva Jayanth , Roger Moser , Tobias Schaefers , Narayan Prasad Nagendra","doi":"10.1016/j.ijpe.2024.109498","DOIUrl":"10.1016/j.ijpe.2024.109498","url":null,"abstract":"<div><div>Agriculture financing in developing countries is dominated by informal lending. One challenge in the expansion of institutional (formal) credit is the lack of reliable data on the historical performance of farmers. Due to the absence of data, financial institutions face uncertainties that obstruct the decision-making process, leading to sub-optimal credit disbursal. Based on the theoretical lens of uncertainty reduction, this study focuses on achieving two key research objectives: identifying uncertainties in institutional crop credit management processes and examining how a data-driven digital transformation for social innovation based on satellite imagery analytics could alleviate these hindrances. We longitudinally study a satellite imagery analytics firm and complement the case data with stakeholder interviews. The results capture state space, option, and ethical uncertainties institutional lenders face in expanding crop credit and explain how data-driven digital transformation can reduce these uncertainties. Adopting such a data-driven digital transformation promises to make different stakeholder groups interact and collaborate to achieve the common objective of financial inclusion of small-scale economic actors. Further, we show that satellite imagery in crop credit management can significantly reduce the uncertainties caused by the lack of independent data sources.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"280 ","pages":"Article 109498"},"PeriodicalIF":9.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143138122","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}
Pub Date : 2025-02-01DOI: 10.1016/j.ijpe.2024.109500
Hung-Kai Wang , Ting-Yun Yang , Ya-Han Wang , Chia-Le Wu
Surface mount technology (SMT) is widely used in semiconductor packaging factories to assemble electronic components onto printed circuit boards. Therefore, reducing bottlenecks in SMT implementation is crucial for achieving the optimal production efficiency and meeting customer demands in semiconductor factories. This study developed a hybrid dispatching and genetic algorithm (HDGA) which uses a genetic algorithm (GA) and dispatch rules, to reduce machine set-up times and increase delivery fulfillment rates. The proposed HDGA is embedded in a scheduling system to optimize production scheduling by considering all practical constraints associated with SMT implementation, such as machine and job statuses, lot consolidation constraints, processing time, works in progress and machine priority, multiple processing rounds, and issue-number-related constraints. To validate the effectiveness of this algorithm, the present study compared its performance with that of a traditional GA and a hybrid GA. The results indicated that the HDGA outperformed the other three algorithms. The proposed algorithm can improve productivity, product quality, product delivery rates, and overall scheduling efficiency in semiconductor factories.
{"title":"Hybrid dispatching and genetic algorithm for the surface mount technology scheduling problem in semiconductor factories","authors":"Hung-Kai Wang , Ting-Yun Yang , Ya-Han Wang , Chia-Le Wu","doi":"10.1016/j.ijpe.2024.109500","DOIUrl":"10.1016/j.ijpe.2024.109500","url":null,"abstract":"<div><div>Surface mount technology (SMT) is widely used in semiconductor packaging factories to assemble electronic components onto printed circuit boards. Therefore, reducing bottlenecks in SMT implementation is crucial for achieving the optimal production efficiency and meeting customer demands in semiconductor factories. This study developed a hybrid dispatching and genetic algorithm (HDGA) which uses a genetic algorithm (GA) and dispatch rules, to reduce machine set-up times and increase delivery fulfillment rates. The proposed HDGA is embedded in a scheduling system to optimize production scheduling by considering all practical constraints associated with SMT implementation, such as machine and job statuses, lot consolidation constraints, processing time, works in progress and machine priority, multiple processing rounds, and issue-number-related constraints. To validate the effectiveness of this algorithm, the present study compared its performance with that of a traditional GA and a hybrid GA. The results indicated that the HDGA outperformed the other three algorithms. The proposed algorithm can improve productivity, product quality, product delivery rates, and overall scheduling efficiency in semiconductor factories.</div></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":"280 ","pages":"Article 109500"},"PeriodicalIF":9.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143137350","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}
Pub Date : 2025-02-01DOI: 10.1016/j.ijpe.2024.109493
Zhijia Tan , Shuai Shao , Min Xu , Kun Wang
Transport authorities often adopt mode-based emission regulations to mitigate air pollution from road and waterway modes. However, this unilateral approach can lead to freight shifts among different transport modes, distorting regulation efficiency. This paper explores the policy implications of emission regulation in a bi-modal (road and waterway) freight corridor, managed by two non-cooperative transport authorities. A Bertrand-like competition model is used to represent the market structure of bi-modal transport along the corridor. We introduce a concept, the Price-of-Regulation (), to quantify the market utility that an authority is willing to pay to reduce unit emissions. We examine the design of emission taxes under different s, considering both aggregated and spatially-distributed demands, under three market structures: substitutable, independent, and complementary. Our findings suggest that, for the case of aggregated demand, equilibrium emission taxes increase (decrease) both market size (shipment demand) and quantity of emissions when two modes are substitutable (complementary). We also demonstrate that a win-win emission tax scheme exists when two modes are substitutable, simultaneously enlarging the market size and reducing emissions. For spatially-distributed demand, a non-linear mathematical programming model and a non-dominated sorting genetic algorithm II (NSGA-II) are proposed to determine the win-win emission tax scheme. Our models and algorithms are validated using data from the Yangtze River Economic Belt. This study provides valuable insights for policymakers in designing effective emission regulations for bi-modal freight corridors.
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