Pub Date : 2023-04-11DOI: 10.1080/21681015.2023.2194877
Ziaul Haq Adnan, Ertunga C. Özelkan
ABSTRACT Supply chain price variability, also known as the “Bullwhip effect in Pricing (BP),” refers to the absorption or amplification of the variability of prices from one stage to another in a supply chain. This article derives analytical conditions that result in BP considering a buyback contract and conducts numerical simulations to gain further insights. For this, a joint price and replenishment setting newsvendor model with a wholesale-Stackelberg game is considered. Two demand types (linear and isoelastic) are analyzed along with uniformly and normally distributed additive and multiplicative uncertainties. The outcome of this research reveals that the main influential factors that affect BP are the structure and error type of the demand functions. Absorption (amplification) in price fluctuations occurs for linear (isoelastic) demand cases. Moreover, the price variances and BP ratios differ under the buyback and wholesale-price-only cases. The overall results help understand the fluctuation of market prices under various conditions.
{"title":"Supply chain price variability under the buyback contract","authors":"Ziaul Haq Adnan, Ertunga C. Özelkan","doi":"10.1080/21681015.2023.2194877","DOIUrl":"https://doi.org/10.1080/21681015.2023.2194877","url":null,"abstract":"ABSTRACT Supply chain price variability, also known as the “Bullwhip effect in Pricing (BP),” refers to the absorption or amplification of the variability of prices from one stage to another in a supply chain. This article derives analytical conditions that result in BP considering a buyback contract and conducts numerical simulations to gain further insights. For this, a joint price and replenishment setting newsvendor model with a wholesale-Stackelberg game is considered. Two demand types (linear and isoelastic) are analyzed along with uniformly and normally distributed additive and multiplicative uncertainties. The outcome of this research reveals that the main influential factors that affect BP are the structure and error type of the demand functions. Absorption (amplification) in price fluctuations occurs for linear (isoelastic) demand cases. Moreover, the price variances and BP ratios differ under the buyback and wholesale-price-only cases. The overall results help understand the fluctuation of market prices under various conditions.","PeriodicalId":16024,"journal":{"name":"Journal of Industrial and Production Engineering","volume":"40 1","pages":"301 - 322"},"PeriodicalIF":4.5,"publicationDate":"2023-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43919180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-11DOI: 10.1080/21681015.2023.2200611
Van Hop Nguyen
ABSTRACT In this paper, a hierarchical heuristic algorithm is proposed to allocate order quantities to suppliers and determine the best lot sizing for each supplier. Pre-defined policies are first implemented to generate the initial order allocation to suppliers. The solutions are then modified by reducing the gap of the least satisfying level to search for a compromised solution, and this process is repeated until no further improvement can be made. The fine-tuning process finally reduces the gap between the two consecutive order allocation schemes. In the second level, a dynamic programming approach is modified to determine the best lot-sizing plan and compensate for the loss of quality and late delivery. The contributions of this work are to develop not only the best order allocation plan instead of supplier selection but also effective lot sizing plan that can reduce supply uncertainties. Experiments are tested to confirm the performance of the proposed method. Graphical Abstract
{"title":"A hierarchical heuristic algorithm for multi-objective order allocation problem subject to supply uncertainties","authors":"Van Hop Nguyen","doi":"10.1080/21681015.2023.2200611","DOIUrl":"https://doi.org/10.1080/21681015.2023.2200611","url":null,"abstract":"ABSTRACT In this paper, a hierarchical heuristic algorithm is proposed to allocate order quantities to suppliers and determine the best lot sizing for each supplier. Pre-defined policies are first implemented to generate the initial order allocation to suppliers. The solutions are then modified by reducing the gap of the least satisfying level to search for a compromised solution, and this process is repeated until no further improvement can be made. The fine-tuning process finally reduces the gap between the two consecutive order allocation schemes. In the second level, a dynamic programming approach is modified to determine the best lot-sizing plan and compensate for the loss of quality and late delivery. The contributions of this work are to develop not only the best order allocation plan instead of supplier selection but also effective lot sizing plan that can reduce supply uncertainties. Experiments are tested to confirm the performance of the proposed method. Graphical Abstract","PeriodicalId":16024,"journal":{"name":"Journal of Industrial and Production Engineering","volume":"40 1","pages":"343 - 359"},"PeriodicalIF":4.5,"publicationDate":"2023-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41896624","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-10DOI: 10.1080/21681015.2023.2197907
Md Shamimul Islam, Imranul Hoque, S. Rahman, Mohammad Asif Salam
ABSTRACT This study contributes to the complex adaptive system theory by offering a valid hierarchical model to evaluate the theory’s important features related to resilience. The garment industry in Bangladesh encountered disruption in the supply chain during the COVID-19 pandemic and the supply chain competencies played a vital role in overcoming the crisis. Limited studies are built on a solid theoretical foundation and considered supply chain competencies in assessing supply chain resilience. This study aims to develop a multi-criteria hierarchical measurement structure by considering the supply chain competencies to evaluate supply chain resilience. Fuzzy Delphi method and Fuzzy importance and performance analysis approach were applied for the study purpose. Findings reveal health and safety management, information management system, business intelligence, innovation capabilities management, technological innovation, and artificial intelligence as critical criteria, and data, information, and computing, technological innovation and adaptation are critical aspects that require improvement. Graphical abstract
{"title":"Evaluating supply chain resilience using supply chain management competencies in the garment industry: a post COVID analysis","authors":"Md Shamimul Islam, Imranul Hoque, S. Rahman, Mohammad Asif Salam","doi":"10.1080/21681015.2023.2197907","DOIUrl":"https://doi.org/10.1080/21681015.2023.2197907","url":null,"abstract":"ABSTRACT This study contributes to the complex adaptive system theory by offering a valid hierarchical model to evaluate the theory’s important features related to resilience. The garment industry in Bangladesh encountered disruption in the supply chain during the COVID-19 pandemic and the supply chain competencies played a vital role in overcoming the crisis. Limited studies are built on a solid theoretical foundation and considered supply chain competencies in assessing supply chain resilience. This study aims to develop a multi-criteria hierarchical measurement structure by considering the supply chain competencies to evaluate supply chain resilience. Fuzzy Delphi method and Fuzzy importance and performance analysis approach were applied for the study purpose. Findings reveal health and safety management, information management system, business intelligence, innovation capabilities management, technological innovation, and artificial intelligence as critical criteria, and data, information, and computing, technological innovation and adaptation are critical aspects that require improvement. Graphical abstract","PeriodicalId":16024,"journal":{"name":"Journal of Industrial and Production Engineering","volume":"40 1","pages":"323 - 342"},"PeriodicalIF":4.5,"publicationDate":"2023-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43607727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-27DOI: 10.1080/21681015.2023.2194302
Sinan Çıkmak, Buşra Kesici
ABSTRACT Circular supply chain management (CSCM) is a process used to design the supply chain by recycling, remanufacturing or refurbishing, repairing, and reusing products However, no study has been encountered in the literature that analyzes CSCM barriers in the air conditioning sector. Hence, this study is aimed to investigate the barriers to CSCM adoption in the air conditioning industry. A case study was conducted on a company operating in the global air conditioning sector. Initially, literature review and expert opinions have been used to identify essential barriers. Later, 6 main barriers and 21 sub-barriers were ranked using Analytical Hierarchy Process (AHP) method based on the interval type-2 fuzzy sets. The findings indicate that “Regulatory” is the most crucial, and “Operational” is the least important main barrier. The findings of the study would be useful for practitioners and policymakers to focus on the most prominent barriers in the air conditioning supply chains. GRAPHICAL ABSTRACT
{"title":"Analysis of barriers to the adoption of circular supply chain management: a case study in the air conditioning industry","authors":"Sinan Çıkmak, Buşra Kesici","doi":"10.1080/21681015.2023.2194302","DOIUrl":"https://doi.org/10.1080/21681015.2023.2194302","url":null,"abstract":"ABSTRACT Circular supply chain management (CSCM) is a process used to design the supply chain by recycling, remanufacturing or refurbishing, repairing, and reusing products However, no study has been encountered in the literature that analyzes CSCM barriers in the air conditioning sector. Hence, this study is aimed to investigate the barriers to CSCM adoption in the air conditioning industry. A case study was conducted on a company operating in the global air conditioning sector. Initially, literature review and expert opinions have been used to identify essential barriers. Later, 6 main barriers and 21 sub-barriers were ranked using Analytical Hierarchy Process (AHP) method based on the interval type-2 fuzzy sets. The findings indicate that “Regulatory” is the most crucial, and “Operational” is the least important main barrier. The findings of the study would be useful for practitioners and policymakers to focus on the most prominent barriers in the air conditioning supply chains. GRAPHICAL ABSTRACT","PeriodicalId":16024,"journal":{"name":"Journal of Industrial and Production Engineering","volume":"40 1","pages":"287 - 300"},"PeriodicalIF":4.5,"publicationDate":"2023-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"60445155","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-20DOI: 10.1080/21681015.2023.2190766
Maria Ijaz Baig, E. Yadegaridehkordi
ABSTRACT Industry 4.0 adoption helps businesses to achieve sustainable operations. This study aims to identify the drivers of firms’ sustainable performance and explore the moderating role of industry 4.0 adoption on financial, environmental, and social sustainable performance. The triple bottom line, resource-based view, and stakeholder theory were used as the foundational theories and data was collected from 269 Malaysian manufacturing three organizations. The results showed significant effects of stakeholder pressure, organization capabilities, green marketing, and green entrepreneurial orientation on organizational sustainable performance. Meanwhile, the direct impacts of organizational sustainable performance on financial, environmental, and social aspects were supported. Industry 4.0 adoption showed remarkable moderating effects on financial and environmental aspects of sustainable performance. The study provides manufacturers with significant insights into how they need to respond to sustainable development in effective ways. The findings can assist managers and policymakers in setting strategic plans to achieve sustainable performance through industry 4.0 adoption. GRAPHICAL ABSTRACT
{"title":"Exploring moderating effects of industry 4.0 adoption on sustainable performance of Malaysian manufacturing organizations","authors":"Maria Ijaz Baig, E. Yadegaridehkordi","doi":"10.1080/21681015.2023.2190766","DOIUrl":"https://doi.org/10.1080/21681015.2023.2190766","url":null,"abstract":"ABSTRACT Industry 4.0 adoption helps businesses to achieve sustainable operations. This study aims to identify the drivers of firms’ sustainable performance and explore the moderating role of industry 4.0 adoption on financial, environmental, and social sustainable performance. The triple bottom line, resource-based view, and stakeholder theory were used as the foundational theories and data was collected from 269 Malaysian manufacturing three organizations. The results showed significant effects of stakeholder pressure, organization capabilities, green marketing, and green entrepreneurial orientation on organizational sustainable performance. Meanwhile, the direct impacts of organizational sustainable performance on financial, environmental, and social aspects were supported. Industry 4.0 adoption showed remarkable moderating effects on financial and environmental aspects of sustainable performance. The study provides manufacturers with significant insights into how they need to respond to sustainable development in effective ways. The findings can assist managers and policymakers in setting strategic plans to achieve sustainable performance through industry 4.0 adoption. GRAPHICAL ABSTRACT","PeriodicalId":16024,"journal":{"name":"Journal of Industrial and Production Engineering","volume":"40 1","pages":"271 - 286"},"PeriodicalIF":4.5,"publicationDate":"2023-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48888565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-06DOI: 10.1080/21681015.2023.2184426
Bingtao Quan, Sujian Li, Kuo-Jui Wu
ABSTRACT Sustainable production is proposed to guide manufacturers in achieving sustainable development goals. Although previous studies have developed diverse metaheuristics algorithms in finding the optimal method for balancing economic and environmental aspects, the social aspect is still omitted. In addressing this shortcoming, this study attempts to design a hybrid metaheuristic algorithm to balance economic performance with social expectations by matching the employees’ characteristics with those of a job shop. This study contributes to (1) confirming the importance of considering the social aspect for strengthening the theoretical basis; (2) proposing a hybrid metaheuristic algorithm in matching employees’ characteristics with the job shop; and (3) utilizing the optimal scenario leads the related firms in practicing sustainable production. The findings indicate that matching the employee-job-shop can fulfill the social expectation for generating positive effects on economic performance. If manufacturers insist on lowering labor costs, it may have a negative impact on production efficiency. Graphical Abstract
{"title":"A hybrid metaheuristic algorithm to achieve sustainable production: involving employee characteristics in the job-shop matching problem","authors":"Bingtao Quan, Sujian Li, Kuo-Jui Wu","doi":"10.1080/21681015.2023.2184426","DOIUrl":"https://doi.org/10.1080/21681015.2023.2184426","url":null,"abstract":"ABSTRACT Sustainable production is proposed to guide manufacturers in achieving sustainable development goals. Although previous studies have developed diverse metaheuristics algorithms in finding the optimal method for balancing economic and environmental aspects, the social aspect is still omitted. In addressing this shortcoming, this study attempts to design a hybrid metaheuristic algorithm to balance economic performance with social expectations by matching the employees’ characteristics with those of a job shop. This study contributes to (1) confirming the importance of considering the social aspect for strengthening the theoretical basis; (2) proposing a hybrid metaheuristic algorithm in matching employees’ characteristics with the job shop; and (3) utilizing the optimal scenario leads the related firms in practicing sustainable production. The findings indicate that matching the employee-job-shop can fulfill the social expectation for generating positive effects on economic performance. If manufacturers insist on lowering labor costs, it may have a negative impact on production efficiency. Graphical Abstract","PeriodicalId":16024,"journal":{"name":"Journal of Industrial and Production Engineering","volume":"40 1","pages":"246 - 270"},"PeriodicalIF":4.5,"publicationDate":"2023-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46392448","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ABSTRACT As a flexible and effective production mode, seru production has been adopted successfully in electronic industry. In practice, the processing time may be affected by many stochastic factors, such as worker absence, shortage of resources, and so on. This paper focuses on seru scheduling problems with stochastic processing time, and considers the influence of dynamic resource allocation, job deterioration, learning effecteffect, and setup time simultaneously to minimize the makespan. A genetic-simulated annealing algorithm is proposed, in which a simulated annealing procedure is constructed to re-optimize the optimal individual obtained by geneticthe genetic algorithm. Experiment results validate the effectiveness of proposedthe proposed seru scheduling model and genetic-simulated annealing algorithm for solving large-scale cases, and indicate that the stochastic processing time has a great influence on the makespan whichmakespan that can help production manager to makeproduce more consistent results according to the actual situation. Graphical abstract
{"title":"A genetic-simulated annealing algorithm for stochastic seru scheduling problem with deterioration and learning effect","authors":"Zhe Zhang, Ling Shen, Xue Gong, X. Zhong, Yong Yin","doi":"10.1080/21681015.2023.2167875","DOIUrl":"https://doi.org/10.1080/21681015.2023.2167875","url":null,"abstract":"ABSTRACT As a flexible and effective production mode, seru production has been adopted successfully in electronic industry. In practice, the processing time may be affected by many stochastic factors, such as worker absence, shortage of resources, and so on. This paper focuses on seru scheduling problems with stochastic processing time, and considers the influence of dynamic resource allocation, job deterioration, learning effecteffect, and setup time simultaneously to minimize the makespan. A genetic-simulated annealing algorithm is proposed, in which a simulated annealing procedure is constructed to re-optimize the optimal individual obtained by geneticthe genetic algorithm. Experiment results validate the effectiveness of proposedthe proposed seru scheduling model and genetic-simulated annealing algorithm for solving large-scale cases, and indicate that the stochastic processing time has a great influence on the makespan whichmakespan that can help production manager to makeproduce more consistent results according to the actual situation. Graphical abstract","PeriodicalId":16024,"journal":{"name":"Journal of Industrial and Production Engineering","volume":"40 1","pages":"205 - 222"},"PeriodicalIF":4.5,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43673029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-03DOI: 10.1080/21681015.2023.2173317
Davide Basile, Idiano D’Adamo, V. Goretti, P. Rosa
ABSTRACT The integration of circular economy (CE) models into everyday contexts generates huge amount of data involved in goods tracking and tokenization procedures. The sector of blockchain platforms is extremely varied, and the choice of the proper technology is not easy. It is important that the selection is conducted consistently with respect to the CE models. With this study, we present a performance index named Blockchain Circular Economy Index (BCEI). BCEI, obtained through Multicriteria Decision Analysis and Analytic Hierarchy Process, aims to measure the suitability of blockchain platforms to the needs highlighted by a CE scenario. The present study is contextualized by comparing six blockchain platforms, for each of which, the related BCEI is calculated. The results of the analysis show that transaction fee and energy consumption are the two most critical parameters. In addition, the results show the lack of a leading blockchain technology in CE models. Thus, there is a market space that can be exploited given the growing interest in digital and sustainable issues. Graphical abstract
{"title":"Digitalizing Circular Economy through Blockchains: The Blockchain Circular Economy Index","authors":"Davide Basile, Idiano D’Adamo, V. Goretti, P. Rosa","doi":"10.1080/21681015.2023.2173317","DOIUrl":"https://doi.org/10.1080/21681015.2023.2173317","url":null,"abstract":"ABSTRACT The integration of circular economy (CE) models into everyday contexts generates huge amount of data involved in goods tracking and tokenization procedures. The sector of blockchain platforms is extremely varied, and the choice of the proper technology is not easy. It is important that the selection is conducted consistently with respect to the CE models. With this study, we present a performance index named Blockchain Circular Economy Index (BCEI). BCEI, obtained through Multicriteria Decision Analysis and Analytic Hierarchy Process, aims to measure the suitability of blockchain platforms to the needs highlighted by a CE scenario. The present study is contextualized by comparing six blockchain platforms, for each of which, the related BCEI is calculated. The results of the analysis show that transaction fee and energy consumption are the two most critical parameters. In addition, the results show the lack of a leading blockchain technology in CE models. Thus, there is a market space that can be exploited given the growing interest in digital and sustainable issues. Graphical abstract","PeriodicalId":16024,"journal":{"name":"Journal of Industrial and Production Engineering","volume":"40 1","pages":"233 - 245"},"PeriodicalIF":4.5,"publicationDate":"2023-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43413224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-28DOI: 10.1080/21681015.2023.2170481
Yu-Chung Tsao, Chien-Wei Ho, Chi-chuan Wu
ABSTRACT Unexpected crises such as the COVID-19 pandemic considerably influence business operations and supply chains worldwide. Therefore, many companies have adopted digitalization to address the rapidly changing environment. However, few studies have explored the mediating mechanism between digitalization and collaborative planning. Based on structural equation modeling, this study examines how digital transformation can improve collaborative planning through the mediating roles of management participation and information sharing. The results indicate that digital transformation significantly affects management and information sharing. Additionally, management participation and information sharing positively affect collaborative planning. However, this study reveals that digital transformation does not directly influence collaborative planning. Overall, owing to a lack of research exploring the mediating mechanism between digital transformation and collaborative planning, this study contributes to digitalization and manufacturing and provides valuable suggestions. Fundamentally, companies that want to develop digitalization and encourage collaborative planning should consider the effects of management participation and information sharing.
{"title":"The role of digital transformation in improving collaborative planning to address unexpected crisis","authors":"Yu-Chung Tsao, Chien-Wei Ho, Chi-chuan Wu","doi":"10.1080/21681015.2023.2170481","DOIUrl":"https://doi.org/10.1080/21681015.2023.2170481","url":null,"abstract":"ABSTRACT Unexpected crises such as the COVID-19 pandemic considerably influence business operations and supply chains worldwide. Therefore, many companies have adopted digitalization to address the rapidly changing environment. However, few studies have explored the mediating mechanism between digitalization and collaborative planning. Based on structural equation modeling, this study examines how digital transformation can improve collaborative planning through the mediating roles of management participation and information sharing. The results indicate that digital transformation significantly affects management and information sharing. Additionally, management participation and information sharing positively affect collaborative planning. However, this study reveals that digital transformation does not directly influence collaborative planning. Overall, owing to a lack of research exploring the mediating mechanism between digital transformation and collaborative planning, this study contributes to digitalization and manufacturing and provides valuable suggestions. Fundamentally, companies that want to develop digitalization and encourage collaborative planning should consider the effects of management participation and information sharing.","PeriodicalId":16024,"journal":{"name":"Journal of Industrial and Production Engineering","volume":"40 1","pages":"223 - 232"},"PeriodicalIF":4.5,"publicationDate":"2023-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49207215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-07DOI: 10.1080/21681015.2022.2162616
Chih-Cheng Chen, Faza Muhammad Sukarsono, Kuo-Jui Wu
ABSTRACT There is a large increase in the wastes and emissions from the Indonesian fashion industry under economic and population growth. To address this issue, the sustainable circular economy is proposed to reach the goal of sustainable development and zero waste. Previous studies neglect to provide a specific interrelationship model to guide practice to reach a sustainable circular economy. This study proposes a hybrid method integrating exploratory factor analysis, the fuzzy synthetic method and the decision-making trial and evaluation laboratory approach to overcome these shortcomings. It contributes to enhancing the understanding of theory through visual diagrams. The hybrid method makes it possible to interpret complex interrelationships and leads to improvements under resource limitations based on the model. The results reveal that emission reduction and welfare improvement are the causal aspects. Graphic Abstract
{"title":"Evaluating a sustainable circular economy model for the Indonesian fashion industry under uncertainties: a hybrid decision-making approach","authors":"Chih-Cheng Chen, Faza Muhammad Sukarsono, Kuo-Jui Wu","doi":"10.1080/21681015.2022.2162616","DOIUrl":"https://doi.org/10.1080/21681015.2022.2162616","url":null,"abstract":"ABSTRACT There is a large increase in the wastes and emissions from the Indonesian fashion industry under economic and population growth. To address this issue, the sustainable circular economy is proposed to reach the goal of sustainable development and zero waste. Previous studies neglect to provide a specific interrelationship model to guide practice to reach a sustainable circular economy. This study proposes a hybrid method integrating exploratory factor analysis, the fuzzy synthetic method and the decision-making trial and evaluation laboratory approach to overcome these shortcomings. It contributes to enhancing the understanding of theory through visual diagrams. The hybrid method makes it possible to interpret complex interrelationships and leads to improvements under resource limitations based on the model. The results reveal that emission reduction and welfare improvement are the causal aspects. Graphic Abstract","PeriodicalId":16024,"journal":{"name":"Journal of Industrial and Production Engineering","volume":"40 1","pages":"188 - 204"},"PeriodicalIF":4.5,"publicationDate":"2023-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45640855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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