Pub Date : 2023-06-27DOI: 10.1080/21681015.2023.2229341
Pralhad Pesode, S. Barve
ABSTRACT The use of cutting-edge techniques is beneficial for the research and development of biomaterials and the production of new sustainable biomaterials. Eco-friendly biomaterials should be promoted. As prospective substitutes for conventional materials, a variety of biomaterials have been conceived and produced to date and successfully used in various biomedical disciplines. The sustainability component in the additive manufacturing of biomaterials is the main goal of this article. There is discussion of various metallic biomaterials, including titanium, stainless steel, magnesium, cobalt-chromium alloy, zinc, tantalum etc. The effects of several additive manufacturing techniques on sustainability are examined. Also, the properties of additive manufactured biomaterials and sustainability aspect of biomaterials are discussed in detail. By reducing material waste and using time and energy efficiently, additive manufacturing can assist to lower costs and having less harmful effects on the environment. This article discussed sustainability aspects of different additive manufacturing techniques used for manufacturing of biomaterials. Graphical abstract
{"title":"Additive manufacturing of metallic biomaterials: sustainability aspect, opportunity, and challenges","authors":"Pralhad Pesode, S. Barve","doi":"10.1080/21681015.2023.2229341","DOIUrl":"https://doi.org/10.1080/21681015.2023.2229341","url":null,"abstract":"ABSTRACT The use of cutting-edge techniques is beneficial for the research and development of biomaterials and the production of new sustainable biomaterials. Eco-friendly biomaterials should be promoted. As prospective substitutes for conventional materials, a variety of biomaterials have been conceived and produced to date and successfully used in various biomedical disciplines. The sustainability component in the additive manufacturing of biomaterials is the main goal of this article. There is discussion of various metallic biomaterials, including titanium, stainless steel, magnesium, cobalt-chromium alloy, zinc, tantalum etc. The effects of several additive manufacturing techniques on sustainability are examined. Also, the properties of additive manufactured biomaterials and sustainability aspect of biomaterials are discussed in detail. By reducing material waste and using time and energy efficiently, additive manufacturing can assist to lower costs and having less harmful effects on the environment. This article discussed sustainability aspects of different additive manufacturing techniques used for manufacturing of biomaterials. Graphical abstract","PeriodicalId":16024,"journal":{"name":"Journal of Industrial and Production Engineering","volume":null,"pages":null},"PeriodicalIF":4.5,"publicationDate":"2023-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47146043","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 : 2023-06-05DOI: 10.1080/21681015.2023.2221699
Bing Li, Shangtao Jiang, Yanjie Zhou, H. Xuan
ABSTRACT Train formation planning (TFP) is essential for rail freight logistics services. The fluctuation of railcar flows dramatically compared with before the outbreak of COVID-19. This paper studies train formation planning, considering three types of train services provided for railcar flow between pairs of technical stations (TS), including direct trains, district trains, and pickup trains. This paper introduces an optimization model with average railcars flow data (OMAD) and an optimization model with dynamic railcars flow data (OMDD) for the train formation planning based on TS under railcar demand fluctuation while minimizing railcar-hour consumption. The OMAD is a deterministic model, and the OMDD is a probability constraint model. To solve the OMDD, an approach for transforming probability constraints into deterministic constraints is presented. Various groups of scenarios are given to verify the effectiveness of the proposed models. Graphical abstract
{"title":"Optimization of train formation plan based on technical station under railcar demand fluctuation","authors":"Bing Li, Shangtao Jiang, Yanjie Zhou, H. Xuan","doi":"10.1080/21681015.2023.2221699","DOIUrl":"https://doi.org/10.1080/21681015.2023.2221699","url":null,"abstract":"ABSTRACT Train formation planning (TFP) is essential for rail freight logistics services. The fluctuation of railcar flows dramatically compared with before the outbreak of COVID-19. This paper studies train formation planning, considering three types of train services provided for railcar flow between pairs of technical stations (TS), including direct trains, district trains, and pickup trains. This paper introduces an optimization model with average railcars flow data (OMAD) and an optimization model with dynamic railcars flow data (OMDD) for the train formation planning based on TS under railcar demand fluctuation while minimizing railcar-hour consumption. The OMAD is a deterministic model, and the OMDD is a probability constraint model. To solve the OMDD, an approach for transforming probability constraints into deterministic constraints is presented. Various groups of scenarios are given to verify the effectiveness of the proposed models. Graphical abstract","PeriodicalId":16024,"journal":{"name":"Journal of Industrial and Production Engineering","volume":null,"pages":null},"PeriodicalIF":4.5,"publicationDate":"2023-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49157449","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 : 2023-05-27DOI: 10.1080/21681015.2023.2216701
M. Ghobakhloo, M. Iranmanesh, M. Tseng, Andrius Grybauskas, A. Stefanini, A. Amran
ABSTRACT This study addresses the emerging concept of Industry 5.0, which aims to tackle societal concerns associated with the ongoing digital industrial transformation. However, there is still a lack of consensus on the definition and scope of Industry 5.0, as well as limited understanding of its technological components, design principles, and intended values. To bridge these knowledge gaps, the study conducts a content-centric review of relevant literature and synthesizes evidence to develop an architectural design for Industry 5.0. The findings reveal that Industry 5.0 represents the future of industrial transformation, offering potential solutions to socio-economic and environmental issues that were inadequately addressed or exacerbated by Industry 4.0. The study provides managers, industrialists, and policymakers with a comprehensive overview of Industry 5.0, including its technological constituents, design principles, and smart components, emphasizing the importance of stakeholder involvement and integration for effective governance of digital industrial transformation within this framework.
{"title":"Behind the definition of Industry 5.0: a systematic review of technologies, principles, components, and values","authors":"M. Ghobakhloo, M. Iranmanesh, M. Tseng, Andrius Grybauskas, A. Stefanini, A. Amran","doi":"10.1080/21681015.2023.2216701","DOIUrl":"https://doi.org/10.1080/21681015.2023.2216701","url":null,"abstract":"ABSTRACT This study addresses the emerging concept of Industry 5.0, which aims to tackle societal concerns associated with the ongoing digital industrial transformation. However, there is still a lack of consensus on the definition and scope of Industry 5.0, as well as limited understanding of its technological components, design principles, and intended values. To bridge these knowledge gaps, the study conducts a content-centric review of relevant literature and synthesizes evidence to develop an architectural design for Industry 5.0. The findings reveal that Industry 5.0 represents the future of industrial transformation, offering potential solutions to socio-economic and environmental issues that were inadequately addressed or exacerbated by Industry 4.0. The study provides managers, industrialists, and policymakers with a comprehensive overview of Industry 5.0, including its technological constituents, design principles, and smart components, emphasizing the importance of stakeholder involvement and integration for effective governance of digital industrial transformation within this framework.","PeriodicalId":16024,"journal":{"name":"Journal of Industrial and Production Engineering","volume":null,"pages":null},"PeriodicalIF":4.5,"publicationDate":"2023-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45260398","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 : 2023-05-25DOI: 10.1080/21681015.2023.2213688
Mohammadreza Eslamipirharati, F. Jolai, A. Aghsami
ABSTRACT There is a growing concern over environmental pollution resulting from the production. Moreover, the expansion of various industries has led to an increased demand for raw materials. To address these challenges, this paper aims to investigate the bi-objective optimization of a sustainable reverse supply chain network while considering two key sources of uncertainty in the returned product quality and the remanufacturing capacity. Additionally, the study considers the effects of carbon tax policies and government subsidies on remanufactured products, while also focusing on three important sustainability aspects - economic, social, and environmental. The study uses two quality thresholds at inspection centers to sort products, and the epsilon constraint and NSGA-II are applied to solve the model. Through numerical analysis, the research demonstrates that objective functions are sensitive to uncertain parameters and minimum acceptable quality levels. Furthermore, the study reveals that government subsidies can offset the negative effects of carbon tax policies. Graphical abstract
{"title":"A Bi-objective two-stage stochastic optimization model for sustainable reverse supply chain network design under carbon tax policy and government subsidy considering product quality","authors":"Mohammadreza Eslamipirharati, F. Jolai, A. Aghsami","doi":"10.1080/21681015.2023.2213688","DOIUrl":"https://doi.org/10.1080/21681015.2023.2213688","url":null,"abstract":"ABSTRACT There is a growing concern over environmental pollution resulting from the production. Moreover, the expansion of various industries has led to an increased demand for raw materials. To address these challenges, this paper aims to investigate the bi-objective optimization of a sustainable reverse supply chain network while considering two key sources of uncertainty in the returned product quality and the remanufacturing capacity. Additionally, the study considers the effects of carbon tax policies and government subsidies on remanufactured products, while also focusing on three important sustainability aspects - economic, social, and environmental. The study uses two quality thresholds at inspection centers to sort products, and the epsilon constraint and NSGA-II are applied to solve the model. Through numerical analysis, the research demonstrates that objective functions are sensitive to uncertain parameters and minimum acceptable quality levels. Furthermore, the study reveals that government subsidies can offset the negative effects of carbon tax policies. Graphical abstract","PeriodicalId":16024,"journal":{"name":"Journal of Industrial and Production Engineering","volume":null,"pages":null},"PeriodicalIF":4.5,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46435782","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 : 2023-05-12DOI: 10.1080/21681015.2023.2212006
Xiaolong Zhang, Yadong Dou, Jianbo Mao, Wensheng Liu
ABSTRACT Accurate price prediction for carbon trading is essential to provide the guidance for investment and production. The current prediction methods mainly depend on the carbon price itself, from which the change pattern of carbon price is studied. However, fusing the multi-source data, e.g. trading message and public sentiment, and taking proper data processing to improve the prediction accuracy need in-depth research. In this paper, a hybrid price prediction method utilizing both the statistical and intelligent models is established on multi-source data, and the data characteristics are fully explored by correlation analysis and multi-frequency analysis. The study on Guangdong market show that: the accuracy of proposed method is superior to the benchmark ones: root mean square error and mean absolute percentage error are reduced by 19.27% and 7.16%, while determination coefficient and trading return are increased by 8.31% and 25.11%. The proposed method is helpful for stakeholders to manage their trading. Graphical abstract
{"title":"A hybrid price prediction method for carbon trading with multi-data fusion and multi-frequency analysis","authors":"Xiaolong Zhang, Yadong Dou, Jianbo Mao, Wensheng Liu","doi":"10.1080/21681015.2023.2212006","DOIUrl":"https://doi.org/10.1080/21681015.2023.2212006","url":null,"abstract":"ABSTRACT Accurate price prediction for carbon trading is essential to provide the guidance for investment and production. The current prediction methods mainly depend on the carbon price itself, from which the change pattern of carbon price is studied. However, fusing the multi-source data, e.g. trading message and public sentiment, and taking proper data processing to improve the prediction accuracy need in-depth research. In this paper, a hybrid price prediction method utilizing both the statistical and intelligent models is established on multi-source data, and the data characteristics are fully explored by correlation analysis and multi-frequency analysis. The study on Guangdong market show that: the accuracy of proposed method is superior to the benchmark ones: root mean square error and mean absolute percentage error are reduced by 19.27% and 7.16%, while determination coefficient and trading return are increased by 8.31% and 25.11%. The proposed method is helpful for stakeholders to manage their trading. Graphical abstract","PeriodicalId":16024,"journal":{"name":"Journal of Industrial and Production Engineering","volume":null,"pages":null},"PeriodicalIF":4.5,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46869318","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 : 2023-05-09DOI: 10.1080/21681015.2023.2207848
J. Chandramohan, U. R.
ABSTRACT The COVID-19 outbreak has posed significant challenges to the worldwide supply chain. As result, there is an urgent need to develop a model for the manufacturer that includes multi-phase manufacturing with fluctuating demand during various levels of pandemic and a supply system that takes into account the environmental benefits of the product and production. This study recommends inventory model to the company for estimating optimal production amount and replenishment cycle in order to reduce overall cost and maximize profit along with green product pricing and carbon tax. The current study considers models with and without shortages for instantaneously deteriorating commodities. Because of the social awareness concern, firms can avoid the suffering from labor shortage during the pandemic crisis. Numerical examples are given to demonstrate the model’s use. A sensitivity analysis of crucial factors was performed in order to uncover more sensitive parameters that offer a clear portrayal of current concerns.
{"title":"A multi-objective economic production quantity model for deteriorating items with impact of the pandemic, social and environmental concerns","authors":"J. Chandramohan, U. R.","doi":"10.1080/21681015.2023.2207848","DOIUrl":"https://doi.org/10.1080/21681015.2023.2207848","url":null,"abstract":"ABSTRACT The COVID-19 outbreak has posed significant challenges to the worldwide supply chain. As result, there is an urgent need to develop a model for the manufacturer that includes multi-phase manufacturing with fluctuating demand during various levels of pandemic and a supply system that takes into account the environmental benefits of the product and production. This study recommends inventory model to the company for estimating optimal production amount and replenishment cycle in order to reduce overall cost and maximize profit along with green product pricing and carbon tax. The current study considers models with and without shortages for instantaneously deteriorating commodities. Because of the social awareness concern, firms can avoid the suffering from labor shortage during the pandemic crisis. Numerical examples are given to demonstrate the model’s use. A sensitivity analysis of crucial factors was performed in order to uncover more sensitive parameters that offer a clear portrayal of current concerns.","PeriodicalId":16024,"journal":{"name":"Journal of Industrial and Production Engineering","volume":null,"pages":null},"PeriodicalIF":4.5,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43756759","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 : 2023-04-24DOI: 10.1080/21681015.2023.2201267
Milad Mohammadi, Dariush Mohamadi, Ali Nikzad
ABSTRACT This study addresses the optimization of price and production quantity using game theory in the coffee supply chain in the city of Isfahan. The presented model focuses on the competition among members of the chain in a probabilistic environment and is based on discrete selection models. This model examines the impact of inventory and routing costs on the pricing model at the same time. To effectively solve real-world problems, the method of normal distribution approximation is used instead of the binomial distribution. The results of the model indicate that the computational time of the applied approximate model does not change with increasing the number of customers, and the model can determine the optimal price and production quantity. The advantage of the proposed model over other classic models is that it considers the inventory costs that have not yet been considered in price competition models with discrete selection. Graphical Abstract
{"title":"Equilibrium pricing in supply chains with discrete stochastic demands: A case study in coffee supply and distribution industry","authors":"Milad Mohammadi, Dariush Mohamadi, Ali Nikzad","doi":"10.1080/21681015.2023.2201267","DOIUrl":"https://doi.org/10.1080/21681015.2023.2201267","url":null,"abstract":"ABSTRACT This study addresses the optimization of price and production quantity using game theory in the coffee supply chain in the city of Isfahan. The presented model focuses on the competition among members of the chain in a probabilistic environment and is based on discrete selection models. This model examines the impact of inventory and routing costs on the pricing model at the same time. To effectively solve real-world problems, the method of normal distribution approximation is used instead of the binomial distribution. The results of the model indicate that the computational time of the applied approximate model does not change with increasing the number of customers, and the model can determine the optimal price and production quantity. The advantage of the proposed model over other classic models is that it considers the inventory costs that have not yet been considered in price competition models with discrete selection. Graphical Abstract","PeriodicalId":16024,"journal":{"name":"Journal of Industrial and Production Engineering","volume":null,"pages":null},"PeriodicalIF":4.5,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46441997","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: 10.1080/21681015.2023.2194877
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":null,"pages":null},"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":null,"pages":null},"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":null,"pages":null},"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}
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