Pub Date : 2024-04-10DOI: 10.3390/logistics8020041
Behzad Maleki Vishkaei, Pietro De Giovanni
Background: Business continuity entails the potential negative consequences of uncertainty on a firm’s ability to achieve strategic objectives. The COVID-19 pandemic significantly impacted business continuity due to lockdowns, travel restrictions, and social distancing measures. Consequently, firms adopted specific supply chain (SC) practices to effectively navigate this global crisis. Methods: This research adopted a stochastic approach based on Bayesian Networks to evaluate the implications of business continuity on firms’ decisions to embrace SC practices, focusing on omnichannel strategies, SC coordination, and technologies such as artificial intelligence systems, big data and machine learning, and mobile applications. Results: Our findings revealed that firms facing disruption in a single performance area can apply specific strategies to maintain resilience. However, multiple areas of underperformance necessitate a varied approach. Conclusions: According to our empirical analysis, omnichannel strategies are critical when disruptions simultaneously impact quality, inventory, sales, and ROI, particularly during major disruptions such as the COVID-19 pandemic. AI and big data become vital when multiple risks coalesce, enhancing areas such as customer service and supply chain visibility. Moreover, supply chain coordination and mobile app adoption are effective against individual performance risks, proving crucial in mitigating disruption impacts across various business aspects. These findings help policy-makers and business owners to have a better understanding of how business continuity based on performance resistance to disruptions pushes companies to adopt different practices including new technologies and supply chain coordination. Accordingly, they can use the outputs of this study to devise strategies for improving resilience considering their supply chain vulnerabilities.
{"title":"The Impact of Business Continuity on Supply Chain Practices and Resilience Due to COVID-19","authors":"Behzad Maleki Vishkaei, Pietro De Giovanni","doi":"10.3390/logistics8020041","DOIUrl":"https://doi.org/10.3390/logistics8020041","url":null,"abstract":"Background: Business continuity entails the potential negative consequences of uncertainty on a firm’s ability to achieve strategic objectives. The COVID-19 pandemic significantly impacted business continuity due to lockdowns, travel restrictions, and social distancing measures. Consequently, firms adopted specific supply chain (SC) practices to effectively navigate this global crisis. Methods: This research adopted a stochastic approach based on Bayesian Networks to evaluate the implications of business continuity on firms’ decisions to embrace SC practices, focusing on omnichannel strategies, SC coordination, and technologies such as artificial intelligence systems, big data and machine learning, and mobile applications. Results: Our findings revealed that firms facing disruption in a single performance area can apply specific strategies to maintain resilience. However, multiple areas of underperformance necessitate a varied approach. Conclusions: According to our empirical analysis, omnichannel strategies are critical when disruptions simultaneously impact quality, inventory, sales, and ROI, particularly during major disruptions such as the COVID-19 pandemic. AI and big data become vital when multiple risks coalesce, enhancing areas such as customer service and supply chain visibility. Moreover, supply chain coordination and mobile app adoption are effective against individual performance risks, proving crucial in mitigating disruption impacts across various business aspects. These findings help policy-makers and business owners to have a better understanding of how business continuity based on performance resistance to disruptions pushes companies to adopt different practices including new technologies and supply chain coordination. Accordingly, they can use the outputs of this study to devise strategies for improving resilience considering their supply chain vulnerabilities.","PeriodicalId":507203,"journal":{"name":"Logistics","volume":"2019 37","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140718047","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 : 2024-04-09DOI: 10.3390/logistics8020037
Hisatoshi Naganawa, Enna Hirata, Nailah Firdausiyah, Russell G. Thompson
Background: The global logistics industry is facing looming challenges related to labor shortages and low-efficiency problems due to the lack of logistics facilities and resources, resulting in increased logistics delays. The Physical Internet is seen as a way to take logistics into the next generation of transformation. This research proposes a Physical Internet-enabled system that allows multiple companies to efficiently share warehouses and trucks to achieve operational efficiency and reduce CO2 emissions. Methods: We propose a novel demography-weighted combinatorial optimization model utilizing a genetic algorithm and the Lin–Kernighan heuristic. The model is tested with real data simulations to evaluate its performance. Results: The results show that compared to the existing model presented in a previous study, our proposed model improves location optimality and distributive routing efficiency and reduces CO2 emissions by 54%. Conclusions: By providing a well-founded novel model, this research makes an important contribution to the implementation of the Physical Internet by computing optimal logistics hubs and routes as well as providing a solution to cut CO2 emissions by half.
{"title":"Logistics Hub and Route Optimization in the Physical Internet Paradigm","authors":"Hisatoshi Naganawa, Enna Hirata, Nailah Firdausiyah, Russell G. Thompson","doi":"10.3390/logistics8020037","DOIUrl":"https://doi.org/10.3390/logistics8020037","url":null,"abstract":"Background: The global logistics industry is facing looming challenges related to labor shortages and low-efficiency problems due to the lack of logistics facilities and resources, resulting in increased logistics delays. The Physical Internet is seen as a way to take logistics into the next generation of transformation. This research proposes a Physical Internet-enabled system that allows multiple companies to efficiently share warehouses and trucks to achieve operational efficiency and reduce CO2 emissions. Methods: We propose a novel demography-weighted combinatorial optimization model utilizing a genetic algorithm and the Lin–Kernighan heuristic. The model is tested with real data simulations to evaluate its performance. Results: The results show that compared to the existing model presented in a previous study, our proposed model improves location optimality and distributive routing efficiency and reduces CO2 emissions by 54%. Conclusions: By providing a well-founded novel model, this research makes an important contribution to the implementation of the Physical Internet by computing optimal logistics hubs and routes as well as providing a solution to cut CO2 emissions by half.","PeriodicalId":507203,"journal":{"name":"Logistics","volume":"17 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140725251","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 : 2024-04-09DOI: 10.3390/logistics8020039
Paula Ferreira da Cruz Correia, João Gilberto Dos Mendes dos Reis, Pedro Sanches Amorim, Jaqueline Severino da Costa, Márcia Terra da Silva
Background: The coffee industry is one of the most important world supply chains, with an estimated consumption of two billion cups daily, making it the most consumed beverage worldwide. Coffee beans are primarily grown in tropical countries, with Brazil accounting for almost 50% of the production. The objective of this study is to examine the Brazilian trade between 2018 and 2022, focusing on state producers, logistical corridors, and importer countries. Methods: The methodology approach revolves around a quantitative method using Social Network Analysis measures. Results: The results reveal a massive concentration in local production (99.5%—Minas Gerais), port movements (99.9%—Santos, Itaguai, and Rio de Janeiro), and country buyers (80.9%—the United States, United Kingdon, and Japan). Conclusions: The study concludes that the Brazilian green coffee supply chain relies on a fragile and overloaded logistical network. Due to that, this study indicates that the stakeholders and decision-makers involved must consider this high concentration of production in some areas and companies. They must also address the bottlenecks in logistical corridors and the fierce competition involved in acquiring and processing Brazilian coffee production because these factors can drastically affect the revenue of the companies operating in this sector.
{"title":"Impacts of Brazilian Green Coffee Production and Its Logistical Corridors on the International Coffee Market","authors":"Paula Ferreira da Cruz Correia, João Gilberto Dos Mendes dos Reis, Pedro Sanches Amorim, Jaqueline Severino da Costa, Márcia Terra da Silva","doi":"10.3390/logistics8020039","DOIUrl":"https://doi.org/10.3390/logistics8020039","url":null,"abstract":"Background: The coffee industry is one of the most important world supply chains, with an estimated consumption of two billion cups daily, making it the most consumed beverage worldwide. Coffee beans are primarily grown in tropical countries, with Brazil accounting for almost 50% of the production. The objective of this study is to examine the Brazilian trade between 2018 and 2022, focusing on state producers, logistical corridors, and importer countries. Methods: The methodology approach revolves around a quantitative method using Social Network Analysis measures. Results: The results reveal a massive concentration in local production (99.5%—Minas Gerais), port movements (99.9%—Santos, Itaguai, and Rio de Janeiro), and country buyers (80.9%—the United States, United Kingdon, and Japan). Conclusions: The study concludes that the Brazilian green coffee supply chain relies on a fragile and overloaded logistical network. Due to that, this study indicates that the stakeholders and decision-makers involved must consider this high concentration of production in some areas and companies. They must also address the bottlenecks in logistical corridors and the fierce competition involved in acquiring and processing Brazilian coffee production because these factors can drastically affect the revenue of the companies operating in this sector.","PeriodicalId":507203,"journal":{"name":"Logistics","volume":"132 20","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140726090","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 : 2024-04-09DOI: 10.3390/logistics8020038
Abderahman Rejeb, Karim Rejeb, Imen Zrelli
Background: Effective humanitarian logistics (HL) is essential in disaster response. The “Internet of Things” (IoT) holds potential to enhance the efficiency and efficacy of HL, yet adoption is slowed by numerous barriers. Methods: This study employs interpretive structural modeling (ISM) and decision-making trial and evaluation laboratory (DEMATEL) to explore and classify barriers to IoT integration in HL. Results: A total of 12 barriers were identified, classified, and ranked according to their driving power and dependence. Key barriers include lack of standardization, organizational resistance, data quality issues, and legal challenges. Conclusions: Overcoming these barriers could significantly improve relief operations, reduce errors, and enhance decision-making processes in HL. This investigation is the first of its kind into IoT barriers in HL, laying the groundwork for further research and providing valuable insights for HL managers.
{"title":"Analyzing Barriers to Internet of Things (IoT) Adoption in Humanitarian Logistics: An ISM–DEMATEL Approach","authors":"Abderahman Rejeb, Karim Rejeb, Imen Zrelli","doi":"10.3390/logistics8020038","DOIUrl":"https://doi.org/10.3390/logistics8020038","url":null,"abstract":"Background: Effective humanitarian logistics (HL) is essential in disaster response. The “Internet of Things” (IoT) holds potential to enhance the efficiency and efficacy of HL, yet adoption is slowed by numerous barriers. Methods: This study employs interpretive structural modeling (ISM) and decision-making trial and evaluation laboratory (DEMATEL) to explore and classify barriers to IoT integration in HL. Results: A total of 12 barriers were identified, classified, and ranked according to their driving power and dependence. Key barriers include lack of standardization, organizational resistance, data quality issues, and legal challenges. Conclusions: Overcoming these barriers could significantly improve relief operations, reduce errors, and enhance decision-making processes in HL. This investigation is the first of its kind into IoT barriers in HL, laying the groundwork for further research and providing valuable insights for HL managers.","PeriodicalId":507203,"journal":{"name":"Logistics","volume":"44 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140727731","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 : 2024-04-07DOI: 10.3390/logistics8020036
Keren A. Vivas, Ramon E. Vera, Sudipta Dasmohapatra, R. Marquez, Sophie Van Schoubroeck, Naycari Forfora, Antonio José Azuaje, Richard B. Phillips, Hasan Jameel, J. Delborne, Daniel Saloni, Richard A. Venditti, Ronalds Gonzalez
Background: The pulp and paper industry (P&PI) is undergoing significant disruption driven by global megatrends that necessitate advanced tools for predicting future behavior and adapting strategies accordingly. Methods: This work utilizes a multi-criteria framework to quantify the effects of digitalization, changes in social behavior, and sustainability as three major megatrends transforming the P&PI industry, with a specific focus on hygiene tissue products. Thus, the research combines a comprehensive literature review, insights from a Delphi study, and topic modeling to qualitatively and quantitatively assess the present and future impacts of these global megatrends. Results: The findings suggest an urgent need to identify alternative raw materials to prevent potential supply chain disruptions. Moreover, due to shifts in social behavior, it becomes critical for businesses to substantiate their sustainability claims with hard data to avoid the risk of a “greenwashing” perception among consumers. Conclusions: This study provides decision support for strategic planning by highlighting actionable insights, quantitative predictions, and trend analysis, alongside the examination of consumer and market trends. It aims to incorporate diverse stakeholder perspectives and criteria into decision-making processes, thereby enriching the strategic planning and sustainability efforts within the P&PI industry.
{"title":"A Multi-Criteria Approach for Quantifying the Impact of Global Megatrends on the Pulp and Paper Industry: Insights into Digitalization, Social Behavior Change, and Sustainability","authors":"Keren A. Vivas, Ramon E. Vera, Sudipta Dasmohapatra, R. Marquez, Sophie Van Schoubroeck, Naycari Forfora, Antonio José Azuaje, Richard B. Phillips, Hasan Jameel, J. Delborne, Daniel Saloni, Richard A. Venditti, Ronalds Gonzalez","doi":"10.3390/logistics8020036","DOIUrl":"https://doi.org/10.3390/logistics8020036","url":null,"abstract":"Background: The pulp and paper industry (P&PI) is undergoing significant disruption driven by global megatrends that necessitate advanced tools for predicting future behavior and adapting strategies accordingly. Methods: This work utilizes a multi-criteria framework to quantify the effects of digitalization, changes in social behavior, and sustainability as three major megatrends transforming the P&PI industry, with a specific focus on hygiene tissue products. Thus, the research combines a comprehensive literature review, insights from a Delphi study, and topic modeling to qualitatively and quantitatively assess the present and future impacts of these global megatrends. Results: The findings suggest an urgent need to identify alternative raw materials to prevent potential supply chain disruptions. Moreover, due to shifts in social behavior, it becomes critical for businesses to substantiate their sustainability claims with hard data to avoid the risk of a “greenwashing” perception among consumers. Conclusions: This study provides decision support for strategic planning by highlighting actionable insights, quantitative predictions, and trend analysis, alongside the examination of consumer and market trends. It aims to incorporate diverse stakeholder perspectives and criteria into decision-making processes, thereby enriching the strategic planning and sustainability efforts within the P&PI industry.","PeriodicalId":507203,"journal":{"name":"Logistics","volume":"5 31","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140732937","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 : 2024-04-03DOI: 10.3390/logistics8020035
Samin Yaser Anon, Saman Hassanzadeh Amin, Fazle Baki
Background: This literature review delves into the concept of ‘Third-party Reverse Logistics selection’, focusing on its process and functionality using deterministic and uncertain decision-making models. In an increasingly globalized world, Reverse Logistics (RL) plays a vital role in optimizing supply chain management, reducing waste, and achieving sustainability objectives. Deterministic decision-making models employ predefined criteria and variables, utilizing mathematical algorithms to assess factors such as cost, reliability, and capacity across various geographical regions. Uncertain decision-making models, on the other hand, incorporate the unpredictability of real-world scenarios by considering the uncertainties and consequences of decision making and choices based on incomplete information, ambiguity, unreliability, and the option for multiple probable outcomes. Methods: Through an examination of 41 peer-reviewed journal publications between the years 2020 and 2023, this review paper explores these concepts and problem domains within three categories: Literature Reviews (LR), Deterministic Decision-Making (DDM) models, and Uncertain Decision-Making (UDM) models. Results: In this paper, observations and future research directions are discussed. Conclusions: This paper provides a comprehensive review of third-party reverse logistics selection papers.
{"title":"Third-Party Reverse Logistics Selection: A Literature Review","authors":"Samin Yaser Anon, Saman Hassanzadeh Amin, Fazle Baki","doi":"10.3390/logistics8020035","DOIUrl":"https://doi.org/10.3390/logistics8020035","url":null,"abstract":"Background: This literature review delves into the concept of ‘Third-party Reverse Logistics selection’, focusing on its process and functionality using deterministic and uncertain decision-making models. In an increasingly globalized world, Reverse Logistics (RL) plays a vital role in optimizing supply chain management, reducing waste, and achieving sustainability objectives. Deterministic decision-making models employ predefined criteria and variables, utilizing mathematical algorithms to assess factors such as cost, reliability, and capacity across various geographical regions. Uncertain decision-making models, on the other hand, incorporate the unpredictability of real-world scenarios by considering the uncertainties and consequences of decision making and choices based on incomplete information, ambiguity, unreliability, and the option for multiple probable outcomes. Methods: Through an examination of 41 peer-reviewed journal publications between the years 2020 and 2023, this review paper explores these concepts and problem domains within three categories: Literature Reviews (LR), Deterministic Decision-Making (DDM) models, and Uncertain Decision-Making (UDM) models. Results: In this paper, observations and future research directions are discussed. Conclusions: This paper provides a comprehensive review of third-party reverse logistics selection papers.","PeriodicalId":507203,"journal":{"name":"Logistics","volume":"190 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140746468","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 : 2024-03-22DOI: 10.3390/logistics8020034
Yahel Giat
Background: Exchangeable item repair systems are inventory systems. A nonfunctional item is exchanged for a functional item and returns to the system after being repaired. In our periodic review setting, repair is performed either in-house or outsourced. When repair is in-house, a repaired item is returned to stock regardless of the repair status of the other items in its order. In contrast, with outsourced repair, the entire order must be repaired for it to return to stock. Methods: We develop formulas for the window fill rate (probability for a customer to be served within a given time window) to measure the system’s performance and compute it for each repair model. The cost of outsourcing is the difference between the number of spares needed to maintain a target performance level when repair is internal and when it is outsourced. Results and Conclusions: In our numerical example, we show that the window fill rate in both models is S-shaped in the number of spares and show how the graph shifts to the right when customer tolerance decreases and order cycle time increases. Further, we show that the cost of outsourcing is increasing with customer tolerance and with the target performance level.
背景介绍可交换物品维修系统是一种库存系统。非功能性物品被交换为功能性物品，并在维修后返回系统。在我们的定期审查环境中，维修要么在内部进行，要么外包。内部维修时，无论订单中其他物品的维修状态如何，维修后的物品都会返回库存。而外包维修时，整个订单必须维修完毕才能返回库存。方法：我们制定了窗口填充率（在给定时间窗口内为客户提供服务的概率）公式来衡量系统的性能，并为每种维修模式计算了该公式。外包成本是内部维修和外包维修时维持目标性能水平所需的备件数量之差。结果和结论：在数值示例中，我们发现两种模式下的窗口填充率与备件数量呈 S 型关系，并显示了当客户容忍度降低和订单周期增加时，图形如何向右移动。此外，我们还表明，外包成本随着客户容忍度和目标性能水平的提高而增加。
{"title":"Stock Levels and Repair Sourcing in a Periodic Review Exchangeable Item Repair System","authors":"Yahel Giat","doi":"10.3390/logistics8020034","DOIUrl":"https://doi.org/10.3390/logistics8020034","url":null,"abstract":"Background: Exchangeable item repair systems are inventory systems. A nonfunctional item is exchanged for a functional item and returns to the system after being repaired. In our periodic review setting, repair is performed either in-house or outsourced. When repair is in-house, a repaired item is returned to stock regardless of the repair status of the other items in its order. In contrast, with outsourced repair, the entire order must be repaired for it to return to stock. Methods: We develop formulas for the window fill rate (probability for a customer to be served within a given time window) to measure the system’s performance and compute it for each repair model. The cost of outsourcing is the difference between the number of spares needed to maintain a target performance level when repair is internal and when it is outsourced. Results and Conclusions: In our numerical example, we show that the window fill rate in both models is S-shaped in the number of spares and show how the graph shifts to the right when customer tolerance decreases and order cycle time increases. Further, we show that the cost of outsourcing is increasing with customer tolerance and with the target performance level.","PeriodicalId":507203,"journal":{"name":"Logistics","volume":" 34","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140219709","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 : 2024-03-20DOI: 10.3390/logistics8010033
Mohsin Ali, Abdul Razaque, Joon Yoo, Uskenbayeva Raissa Kabievna, A. Moldagulova, Satybaldiyeva Ryskhan, Kalpeyeva Zhuldyz, Aizhan Kassymova
Background: The modern credit card system is critical, but it has not been fully examined to meet the unique financial needs of a constantly changing number of manufacturers and importers. Methods: An intelligent credit card system integrates the features of artificial intelligence and blockchain technology. The decentralized and unchangeable ledger of the Blockchain technology significantly reduces the risk of fraud while maintaining real-time transaction recording. On the other hand, the capabilities of AI-driven credit assessment algorithms enable more precise, effective, and customized credit choices that are specifically tailored to meet the unique financial profiles of manufacturers and importers. Results: Several metrics, including predictive credit risk, fraud detection, credit assessment accuracy, default rate comparison, loan approval rate comparison, and other important metrics affecting the credit card system, have been investigated to determine the effectiveness of modern credit card systems when using Blockchain technology and AI. Conclusion: The study of developing an intelligent scoring system for crediting manufacturers and importers of goods in Industry 4.0 can be enhanced by incorporating user adoption. The changing legislation and increasing security threats necessitate ongoing monitoring. Scalability difficulties can be handled by detailed planning that focuses on integration, data migration, and change management. The research may potentially increase operational efficiency in the manufacturing and importing industries.
{"title":"Designing an Intelligent Scoring System for Crediting Manufacturers and Importers of Goods in Industry 4.0","authors":"Mohsin Ali, Abdul Razaque, Joon Yoo, Uskenbayeva Raissa Kabievna, A. Moldagulova, Satybaldiyeva Ryskhan, Kalpeyeva Zhuldyz, Aizhan Kassymova","doi":"10.3390/logistics8010033","DOIUrl":"https://doi.org/10.3390/logistics8010033","url":null,"abstract":"Background: The modern credit card system is critical, but it has not been fully examined to meet the unique financial needs of a constantly changing number of manufacturers and importers. Methods: An intelligent credit card system integrates the features of artificial intelligence and blockchain technology. The decentralized and unchangeable ledger of the Blockchain technology significantly reduces the risk of fraud while maintaining real-time transaction recording. On the other hand, the capabilities of AI-driven credit assessment algorithms enable more precise, effective, and customized credit choices that are specifically tailored to meet the unique financial profiles of manufacturers and importers. Results: Several metrics, including predictive credit risk, fraud detection, credit assessment accuracy, default rate comparison, loan approval rate comparison, and other important metrics affecting the credit card system, have been investigated to determine the effectiveness of modern credit card systems when using Blockchain technology and AI. Conclusion: The study of developing an intelligent scoring system for crediting manufacturers and importers of goods in Industry 4.0 can be enhanced by incorporating user adoption. The changing legislation and increasing security threats necessitate ongoing monitoring. Scalability difficulties can be handled by detailed planning that focuses on integration, data migration, and change management. The research may potentially increase operational efficiency in the manufacturing and importing industries.","PeriodicalId":507203,"journal":{"name":"Logistics","volume":"4 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140227453","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 : 2024-03-19DOI: 10.3390/logistics8010032
Sina Abbasi, Ilias Vlachos, Ali Samadzadeh, Shayan Etemadifar, Mohamad Afshar, Mohsen Amra
Background: Supply chain networks (SCNs) have been interrupted by the COVID-19 pandemic, leaving them open to financial losses. SCs have been impacted by the pandemic, necessitating the adoption of sustainable practices and dynamic capacities to ensure resilience and performance. Several studies have focused on this subject, offering insights into the importance of sustainable supply-chain management, corporate governance, big data management activities, and digital technology in minimising the consequences of the pandemic and fostering sustainability. Methods: This study suggests an analytical framework for assessing environmentally friendly procedures and dynamic capacities to assure performance in a disruptive environment. Results: The following are some of the important details and contributions in this article: (1) developed a conceptual framework for assessing dynamic capacities and sustainable behaviours considering COVID-19, (2) concentrates on financial ratios during COVID-19, and (3) established drivers for sustainable practices and competencies during disruption and unpredictable business settings. Conclusions: The suggested model can assist practitioners in creating and implementing sustainable supply chain (SC) activities and tracking and assessing their effects on the sustainability of businesses. So, the proposed model can assist managers in creating and implementing sustainable supply-chain activities and tracking and analysing their effects on the sustainability of businesses.
{"title":"Modelling a Logistics and Financial Supply Chain Network during the COVID-19 Era","authors":"Sina Abbasi, Ilias Vlachos, Ali Samadzadeh, Shayan Etemadifar, Mohamad Afshar, Mohsen Amra","doi":"10.3390/logistics8010032","DOIUrl":"https://doi.org/10.3390/logistics8010032","url":null,"abstract":"Background: Supply chain networks (SCNs) have been interrupted by the COVID-19 pandemic, leaving them open to financial losses. SCs have been impacted by the pandemic, necessitating the adoption of sustainable practices and dynamic capacities to ensure resilience and performance. Several studies have focused on this subject, offering insights into the importance of sustainable supply-chain management, corporate governance, big data management activities, and digital technology in minimising the consequences of the pandemic and fostering sustainability. Methods: This study suggests an analytical framework for assessing environmentally friendly procedures and dynamic capacities to assure performance in a disruptive environment. Results: The following are some of the important details and contributions in this article: (1) developed a conceptual framework for assessing dynamic capacities and sustainable behaviours considering COVID-19, (2) concentrates on financial ratios during COVID-19, and (3) established drivers for sustainable practices and competencies during disruption and unpredictable business settings. Conclusions: The suggested model can assist practitioners in creating and implementing sustainable supply chain (SC) activities and tracking and assessing their effects on the sustainability of businesses. So, the proposed model can assist managers in creating and implementing sustainable supply-chain activities and tracking and analysing their effects on the sustainability of businesses.","PeriodicalId":507203,"journal":{"name":"Logistics","volume":"52 14","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140231121","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 : 2024-03-15DOI: 10.3390/logistics8010030
Thomas K. Dasaklis, Evangelia Kopanaki, Panos T. Chountalas, N. Rachaniotis, Theodore G. Voutsinas, Kyriakos Giannakis, Gregory Chondrokoukis
Background: The electronic Freight Transport Information (eFTI) regulation is critical in modernizing freight transport (FT) within the European Union by establishing a framework for the electronic exchange of information. Despite its importance, there is a notable gap in the literature regarding the practical implementation challenges, especially from an empirical perspective. Methods: To address this gap, our study utilized a grounded theory approach, conducting interviews with a diverse group of logistics experts from Greece. The selection of experts was strategic to ensure a comprehensive range of knowledge and expertise, including insights at the policy level as well as practical experiences. Results: Our findings highlight several significant challenges in the implementation of eFTI, including the digital skill gap among the workforce, issues with system interoperability, and diverse capacities and resources of companies of different sizes. Economic factors, regulatory frameworks and the necessity for targeted training and leadership support were also identified as crucial for the digital transition. Conclusions: The study shows that uniform eFTI implementation may not work for all organizations, highlighting the necessity for customized strategies that address specific challenges in the FT chain. Our research deepens the understanding of these issues, providing actionable insights for successful eFTI adoption.
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