. Background: With the emergence of supply chain management as a key strategic function in the agrifood sector, a lot of research has been conducted to find ways to improve the performance and sustainability of agri-food supply chains. The Triple-A Supply Chain concept, which refers to the agility, adaptability, and alignment of the supply chains, has been a field of study for various researchers aiming at shaping meaningful and sustainable competitive advantages for businesses and organizations in various sectors. Over the years, alternative, complementary, or upgraded versions of this approach have been proposed, such as the “New AAA Supply Chain”, which describes the renewed Triple-A Supply Chain model based on Super-Agility, Architectural Adaptability, and Ecosystem Alignment, and the “Triple A & R” framework, which refers to Agility for Robustness, Adaptability, and Resilience, and Re-Alignment. Methods: This paper presents the results of a selective study of the bibliography considering the Triple-A Supply Chain model, the “New AAA Supply Chain” model and the “Triple A & R” framework. These frameworks are analyzed and compared with each other considering their principles, and their implementation in the agri-food sector is researched. The scope of this study is to analyze the potential of the application and suitability of these frameworks in agri-food supply chains, having considered the particularities of the sector. Results: Examining the models concerning the evolution of the Triple-A Supply Chain paradigm, it is evident that they differ from each other, as they approach supply chain management from different viewpoints. Conclusions: The potential of application of various models originating from the Triple-A Supply Chain paradigm was examined in the case of the agri-food sector considering product nature, sustainability, and investment cost as the factors affecting it. These frameworks could partially find application in the agri-food sector, as some of their guidelines promote the increase of the agri-food supply chain effectiveness.
． 背景:随着供应链管理作为农业食品部门的一项关键战略职能的出现，人们进行了大量的研究，以寻找提高农业食品供应链绩效和可持续性的方法。aaa供应链概念，指的是供应链的敏捷性、适应性和一致性，一直是各种研究人员的研究领域，旨在为各个部门的企业和组织塑造有意义和可持续的竞争优势。多年来，这种方法的替代、补充或升级版本已经被提出，例如“新AAA供应链”，它描述了基于超级敏捷性、架构适应性和生态系统一致性的更新的AAA供应链模型，以及“Triple A & R”框架，它指的是健壮性、适应性和弹性的敏捷性，以及重新校准。方法:本文结合AAA供应链模型、“新AAA供应链”模型和“Triple a&r”框架对文献文献进行了选择性研究。根据其原理，对这些框架进行了分析和比较，并对其在农业食品部门的实施进行了研究。本研究的范围是分析这些框架在农业食品供应链中的应用潜力和适用性，考虑到该部门的特殊性。结果:检查有关aaa供应链范式演变的模型，很明显它们彼此不同，因为它们从不同的角度看待供应链管理。结论:在考虑产品性质、可持续性和投资成本作为影响因素的情况下，以农业食品部门为例，研究了源自aaa供应链范式的各种模型的应用潜力。这些框架可以部分应用于农业食品部门，因为其中的一些指导方针促进了农业食品供应链效率的提高。
{"title":"Analyzing new ways to adapt the Triple-A Supply Chain model and its extensions in agri-food supply chains","authors":"M. Kontopanou, G. Tsoulfas","doi":"10.17270/j.log.2022.735","DOIUrl":"https://doi.org/10.17270/j.log.2022.735","url":null,"abstract":". Background: With the emergence of supply chain management as a key strategic function in the agrifood sector, a lot of research has been conducted to find ways to improve the performance and sustainability of agri-food supply chains. The Triple-A Supply Chain concept, which refers to the agility, adaptability, and alignment of the supply chains, has been a field of study for various researchers aiming at shaping meaningful and sustainable competitive advantages for businesses and organizations in various sectors. Over the years, alternative, complementary, or upgraded versions of this approach have been proposed, such as the “New AAA Supply Chain”, which describes the renewed Triple-A Supply Chain model based on Super-Agility, Architectural Adaptability, and Ecosystem Alignment, and the “Triple A & R” framework, which refers to Agility for Robustness, Adaptability, and Resilience, and Re-Alignment. Methods: This paper presents the results of a selective study of the bibliography considering the Triple-A Supply Chain model, the “New AAA Supply Chain” model and the “Triple A & R” framework. These frameworks are analyzed and compared with each other considering their principles, and their implementation in the agri-food sector is researched. The scope of this study is to analyze the potential of the application and suitability of these frameworks in agri-food supply chains, having considered the particularities of the sector. Results: Examining the models concerning the evolution of the Triple-A Supply Chain paradigm, it is evident that they differ from each other, as they approach supply chain management from different viewpoints. Conclusions: The potential of application of various models originating from the Triple-A Supply Chain paradigm was examined in the case of the agri-food sector considering product nature, sustainability, and investment cost as the factors affecting it. These frameworks could partially find application in the agri-food sector, as some of their guidelines promote the increase of the agri-food supply chain effectiveness.","PeriodicalId":44682,"journal":{"name":"LogForum","volume":"20 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88335412","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}
{"title":"Identifying the cognitive gap in the causes of product name ambiguity in e-commerce","authors":"M. Niemir, B. Mrugalska","doi":"10.17270/j.log.2022.738","DOIUrl":"https://doi.org/10.17270/j.log.2022.738","url":null,"abstract":"","PeriodicalId":44682,"journal":{"name":"LogForum","volume":"76 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83930330","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}
. Background: The concept of humanitarian supply chain management is based on theoretical and methodological assumptions of the idea of cooperation between industry and trade. The overarching goal of humanitarian aid is to save or improve people's quality of life, which makes the problem of economic efficiency a secondary issue. The subjective structure of supply chains is also different, which determines the division of roles and motives in the process of cooperation between their participants. The publication aims to identify differences and controversies related to the transformation of the business concept of supply chain management into the cooperation of entities as part of humanitarian aid actions. Consequently, the second objective tends to identify factors of logistic cooperation among humanitarian organizations. Methods: To achieve both goals, the article was divided into a theoretical part on the idea of logistics cooperation in supply chains (methods: logical analysis and critical analysis of the subject literature) and a presentation of the results of an anonymous questionnaire survey diagnosing initiators and determinants of logistics cooperation in humanitarian supply chains in Poland (methods: questionnaire survey and descriptive statistics). Results: Humanitarian and business supply chains differ in terms of the purpose of functioning, the main entity that coordinates material, information, financial, human and reverse flows, stakeholders of the activities carried out, the location of the idea of cooperation in the supply chain management system and the impact of external conditions on efficiency of functioning. Regularities are diagnosed with respect to the initiators and factors of logistic cooperation in humanitarian supply chains: (1) the main initiators of logistic cooperation in humanitarian supply chains are humanitarian organizations who (2) underestimate the important factors and opportunities to achieve synergistic effects, there is a (3) requirement for greater involvement of national government institutions and international humanitarian organizations, and (4) the type of a humanitarian crisis has an impact on logistic cooperation. Conclusions: A random sample of 100 humanitarian NGOs based on a survey requires a more complete diagnosis of the initiators and the correctness of logistic cooperation in humanitarian supply chains from the perspective of other actors and beneficiaries of aid actions, as well as in the context of competition of cooperating entities, i.e., coopetition. Survey responses obtained should be confronted with an in-depth analysis of a case study of logistic cooperation in humanitarian supply chains to war refugees from Ukraine.
{"title":"Initiators and motives for cooperation in humanitarian supply chains","authors":"J. Witkowski, J. Marcinkowski","doi":"10.17270/j.log.2022.736","DOIUrl":"https://doi.org/10.17270/j.log.2022.736","url":null,"abstract":". Background: The concept of humanitarian supply chain management is based on theoretical and methodological assumptions of the idea of cooperation between industry and trade. The overarching goal of humanitarian aid is to save or improve people's quality of life, which makes the problem of economic efficiency a secondary issue. The subjective structure of supply chains is also different, which determines the division of roles and motives in the process of cooperation between their participants. The publication aims to identify differences and controversies related to the transformation of the business concept of supply chain management into the cooperation of entities as part of humanitarian aid actions. Consequently, the second objective tends to identify factors of logistic cooperation among humanitarian organizations. Methods: To achieve both goals, the article was divided into a theoretical part on the idea of logistics cooperation in supply chains (methods: logical analysis and critical analysis of the subject literature) and a presentation of the results of an anonymous questionnaire survey diagnosing initiators and determinants of logistics cooperation in humanitarian supply chains in Poland (methods: questionnaire survey and descriptive statistics). Results: Humanitarian and business supply chains differ in terms of the purpose of functioning, the main entity that coordinates material, information, financial, human and reverse flows, stakeholders of the activities carried out, the location of the idea of cooperation in the supply chain management system and the impact of external conditions on efficiency of functioning. Regularities are diagnosed with respect to the initiators and factors of logistic cooperation in humanitarian supply chains: (1) the main initiators of logistic cooperation in humanitarian supply chains are humanitarian organizations who (2) underestimate the important factors and opportunities to achieve synergistic effects, there is a (3) requirement for greater involvement of national government institutions and international humanitarian organizations, and (4) the type of a humanitarian crisis has an impact on logistic cooperation. Conclusions: A random sample of 100 humanitarian NGOs based on a survey requires a more complete diagnosis of the initiators and the correctness of logistic cooperation in humanitarian supply chains from the perspective of other actors and beneficiaries of aid actions, as well as in the context of competition of cooperating entities, i.e., coopetition. Survey responses obtained should be confronted with an in-depth analysis of a case study of logistic cooperation in humanitarian supply chains to war refugees from Ukraine.","PeriodicalId":44682,"journal":{"name":"LogForum","volume":"4 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88919228","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}
M. K. Zuhanda, S. Suwilo, O. S. Sitompul, Mardiningsih Mardiningsih
. Background: The rise of e-commerce in the community makes competition between logistics companies increasingly tight. Every e-commerce application offers the convenience and choices needed by the community. The Two-Echelon Vehicle Routing Problem (2E-VRP) model has been widely developed in recent years. 2E-VRP makes it possible for customers to combine shipments from several different stores due to satellites in their distribution stream. The aim of this paper is to optimize a two-echelon logistics distribution network for package delivery on e-commerce platforms, where vans operate in the first echelon and motorcycles operate in the second echelon. The problem is formulated as 2E-VRP, where total travel costs and fuel consumption are minimized. This optimization is based on determining the flow in each echelon and choosing the optimal routing solution for vans and motorcycles. Methods: This paper proposes a combination of the K-means Clustering Algorithm and the 2-opt Algorithm to solve the optimization problem. Many previous studies have used the K-means algorithm to help streamline the search for solutions. In the solution series, clustering is carried out between the satellite and the customer in the first echelon using the K-means algorithm. To determine the optimal k-cluster, we analyzed it using the silhouette, gap statistic, and elbow methods. Furthermore, the routing at each echelon is solved by the 2-opt heuristic method. At the end of the article, we present testing of several instances with the different number of clusters. The study results indicate an influence on the determination of the number of clusters in minimizing the objective function. Results: This paper looks at 100 customers, 10 satellites, and 1 depot. By working in two stages, the first stage is the resolution of satellite and customer problems, and the second stage is the resolution of problems between the satellite and the depots. We compare distance and cost solutions with a different number of k-clusters. From the test results, the number of k-clusters shows an effect of number and distance on the solution. Conclusions: In the 2E-VRP model, determining the location of the cluster between the satellite and the customer is very important in preparing the delivery schedule in logistics distribution within the city. The benefit is that the vehicle can divide the destination according to the location characteristics of the satellite and the customer, although setting the how many clusters do not guarantee obtaining the optimal distance. And the test results also show that the more satellites there are, the higher the shipping costs. For further research, we will try to complete the model with the metaheuristic genetic algorithm method and compare it with the 2-opt heuristic method.
{"title":"A combination k-means clustering and 2-opt algorithm for solving the two echelon e-commerce logistic distribution","authors":"M. K. Zuhanda, S. Suwilo, O. S. Sitompul, Mardiningsih Mardiningsih","doi":"10.17270/j.log.2022.734","DOIUrl":"https://doi.org/10.17270/j.log.2022.734","url":null,"abstract":". Background: The rise of e-commerce in the community makes competition between logistics companies increasingly tight. Every e-commerce application offers the convenience and choices needed by the community. The Two-Echelon Vehicle Routing Problem (2E-VRP) model has been widely developed in recent years. 2E-VRP makes it possible for customers to combine shipments from several different stores due to satellites in their distribution stream. The aim of this paper is to optimize a two-echelon logistics distribution network for package delivery on e-commerce platforms, where vans operate in the first echelon and motorcycles operate in the second echelon. The problem is formulated as 2E-VRP, where total travel costs and fuel consumption are minimized. This optimization is based on determining the flow in each echelon and choosing the optimal routing solution for vans and motorcycles. Methods: This paper proposes a combination of the K-means Clustering Algorithm and the 2-opt Algorithm to solve the optimization problem. Many previous studies have used the K-means algorithm to help streamline the search for solutions. In the solution series, clustering is carried out between the satellite and the customer in the first echelon using the K-means algorithm. To determine the optimal k-cluster, we analyzed it using the silhouette, gap statistic, and elbow methods. Furthermore, the routing at each echelon is solved by the 2-opt heuristic method. At the end of the article, we present testing of several instances with the different number of clusters. The study results indicate an influence on the determination of the number of clusters in minimizing the objective function. Results: This paper looks at 100 customers, 10 satellites, and 1 depot. By working in two stages, the first stage is the resolution of satellite and customer problems, and the second stage is the resolution of problems between the satellite and the depots. We compare distance and cost solutions with a different number of k-clusters. From the test results, the number of k-clusters shows an effect of number and distance on the solution. Conclusions: In the 2E-VRP model, determining the location of the cluster between the satellite and the customer is very important in preparing the delivery schedule in logistics distribution within the city. The benefit is that the vehicle can divide the destination according to the location characteristics of the satellite and the customer, although setting the how many clusters do not guarantee obtaining the optimal distance. And the test results also show that the more satellites there are, the higher the shipping costs. For further research, we will try to complete the model with the metaheuristic genetic algorithm method and compare it with the 2-opt heuristic method.","PeriodicalId":44682,"journal":{"name":"LogForum","volume":"102 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85836348","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}
. Background: Some phrases become common and contemporary without justification. One such term for business activities is the term smart. In the field of logistics, the trend toward "smart" warehousing is increasingly attracting attention. It is necessary to define it and the stage where intelligence can be achieved using available state-of-the-art technology, to follow the trend of the dehumanization of warehouse and in general manufacturing operations in the direction of Industry 4.0. Methods: The article is based mainly on observational methods, literature review, and document analysis, based on data obtained during the implementation of consulting projects. The subject is limited to warehouses designated to process palletised goods. Results: The available state-of-the-art solutions, like IoT, automation, robots, and communication standards, are close to smart warehouse implementation. But on the other hand, lack of full cooperation between various parties of supply chain and long-term return on investment stand in opposition to implementation. Conclusions: Smart warehouse is the matter of the future. Technology is predominantly achievable, but standardization, universalization and trust are necessary to reach the level of real implementation. Smart solutions are within the reach of a single enterprise, but only in isolation from its microenvironment.
{"title":"The smart warehouse trend: actual level of technology availability","authors":"Wiktor Żuchowski","doi":"10.17270/j.log.2022.702","DOIUrl":"https://doi.org/10.17270/j.log.2022.702","url":null,"abstract":". Background: Some phrases become common and contemporary without justification. One such term for business activities is the term smart. In the field of logistics, the trend toward \"smart\" warehousing is increasingly attracting attention. It is necessary to define it and the stage where intelligence can be achieved using available state-of-the-art technology, to follow the trend of the dehumanization of warehouse and in general manufacturing operations in the direction of Industry 4.0. Methods: The article is based mainly on observational methods, literature review, and document analysis, based on data obtained during the implementation of consulting projects. The subject is limited to warehouses designated to process palletised goods. Results: The available state-of-the-art solutions, like IoT, automation, robots, and communication standards, are close to smart warehouse implementation. But on the other hand, lack of full cooperation between various parties of supply chain and long-term return on investment stand in opposition to implementation. Conclusions: Smart warehouse is the matter of the future. Technology is predominantly achievable, but standardization, universalization and trust are necessary to reach the level of real implementation. Smart solutions are within the reach of a single enterprise, but only in isolation from its microenvironment.","PeriodicalId":44682,"journal":{"name":"LogForum","volume":"473 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83424739","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}
. Background: The paper is devoted to the analysis of the trends and roles of decoupling point in the revolution of new technologies and Industry 4.0. Ever-growing demands and market requirements pressure to optimize the operations and be agile in every area of action. The crucial thing is to create a stable supply chain considering both the cost perspective and customer orientation. Fluctuations, congestion, and unexpected events may have a critical impact on operations and strategy, causing shortages and reducing efficiency. The objective of proper supply chain management is to optimize stocks and use technology to build synergy, which is a key point to increasing competitiveness throughout the entire stream and meeting customer demands. In our research, we offer a perspective on the growing field of 3D printing that may open a way to redefine a decoupling point and create more efficient networks. Methods: This paper uses an analysis of literature related to the decoupling point, presenting the ground rules and their importance in supply chain management. A comparison of theory, current state, and trends is intended to heuristically identify bottlenecks and risks as a case study for continuous improvements in global logistics. Presented data aim to define a way how the supply chain can evolve and use 3D print to create a new perspective on the decoupling point. Results: This study provides an overview of the trends in supply chain management and presents figures on the most common structures of current networks. Analysis of theory and technology development presents the possible changes in the definition of the decoupling point. Conclusions: Surging market requirements and the necessity of cost competitiveness make supply chains more difficult to manage. Unexpected fluctuations, force majeure events, and limited infrastructure capacity are adventurous for ensuring continuous operations. The research provides the insight into the development of logistics to reduce uncertainty and may define a starting point for further analysis of advanced supply chain management based on new technologies.
{"title":"Industry 4.0 and 3D print: a new heuristic approach for decoupling point in future supply chain management","authors":"P. Cyplik, Mateusz Zwolak","doi":"10.17270/j.log.2022.733","DOIUrl":"https://doi.org/10.17270/j.log.2022.733","url":null,"abstract":". Background: The paper is devoted to the analysis of the trends and roles of decoupling point in the revolution of new technologies and Industry 4.0. Ever-growing demands and market requirements pressure to optimize the operations and be agile in every area of action. The crucial thing is to create a stable supply chain considering both the cost perspective and customer orientation. Fluctuations, congestion, and unexpected events may have a critical impact on operations and strategy, causing shortages and reducing efficiency. The objective of proper supply chain management is to optimize stocks and use technology to build synergy, which is a key point to increasing competitiveness throughout the entire stream and meeting customer demands. In our research, we offer a perspective on the growing field of 3D printing that may open a way to redefine a decoupling point and create more efficient networks. Methods: This paper uses an analysis of literature related to the decoupling point, presenting the ground rules and their importance in supply chain management. A comparison of theory, current state, and trends is intended to heuristically identify bottlenecks and risks as a case study for continuous improvements in global logistics. Presented data aim to define a way how the supply chain can evolve and use 3D print to create a new perspective on the decoupling point. Results: This study provides an overview of the trends in supply chain management and presents figures on the most common structures of current networks. Analysis of theory and technology development presents the possible changes in the definition of the decoupling point. Conclusions: Surging market requirements and the necessity of cost competitiveness make supply chains more difficult to manage. Unexpected fluctuations, force majeure events, and limited infrastructure capacity are adventurous for ensuring continuous operations. The research provides the insight into the development of logistics to reduce uncertainty and may define a starting point for further analysis of advanced supply chain management based on new technologies.","PeriodicalId":44682,"journal":{"name":"LogForum","volume":"30 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72527335","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}
{"title":"Optimisation of the stock structure of a single stock item taking into account stock quantity constraints, using a lagrange multiplier","authors":"S. Krzyżaniak","doi":"10.17270/j.log.2022.730","DOIUrl":"https://doi.org/10.17270/j.log.2022.730","url":null,"abstract":"","PeriodicalId":44682,"journal":{"name":"LogForum","volume":"37 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86862107","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}
Background: Covid 19 impacted many healthcare logistics systems. An enormous number of people suffer from the effect of a pandemic, infection diseases can spread rapidly within and between countries. People from the Kingdom of Cambodia and the Lao People's Democratic Republic are most likely to cross-border into Thailand for diagnosis and special treatment. In this situation, international referral cannot predict the volume of patients and their destination. Therefore, the aim of the research is to use deep learning to construct a model that predicts the travel demand of patients at the border. Methods: Based on previous emergency medical services, the prediction demand used the gravity model or the regression model. The novelty element in this research paper uses the neural network technique. In this study, a two-stage survey is used to collect data. The first phase interviews experts from the strategic group level of The Public Health Office. The second phase examines the patient's behavior regarding route selection using a survey. The methodology uses deep learning training using the Sigmoid function and Identity function. The statistics of precision include the average percent relative error (APRE), the root mean square error (RMSE), the standard deviation (SD), and the correlation coefficient (R). Results: Deep learning is suitable for complex problems as a network. The model allows the different data sets to forecast the demand for the cross-border patient for each hospital. Equations are applied to forecast demand, in which the different hospitals require a total of 58,000 patients per year to be diagnosed by the different hospitals. The predictor performs better than the RBF and regression model. Conclusions: The novelty element of this research uses the deep learning technique as an efficient nonlinear model;moreover, it is suitable for dynamic prediction. The main advantage is to apply this model to predict the number of patients, which is the key to determining the supply chain of treatment;additionally, the ability to formulate guidelines with healthcare logistics effectively in the future.
{"title":"Deep learning for the prediction of trans-border logistics of patients to medical centers","authors":"Sawettham Arunrat, Ngeovwijit Sumalee, Pitakaso Rapeepan, Charoenrungrueang Chitpinan, Saisomboon Supattraporn, Monika Kosacka-Olejnik","doi":"10.17270/j.log.2022.689","DOIUrl":"https://doi.org/10.17270/j.log.2022.689","url":null,"abstract":"Background: Covid 19 impacted many healthcare logistics systems. An enormous number of people suffer from the effect of a pandemic, infection diseases can spread rapidly within and between countries. People from the Kingdom of Cambodia and the Lao People's Democratic Republic are most likely to cross-border into Thailand for diagnosis and special treatment. In this situation, international referral cannot predict the volume of patients and their destination. Therefore, the aim of the research is to use deep learning to construct a model that predicts the travel demand of patients at the border. Methods: Based on previous emergency medical services, the prediction demand used the gravity model or the regression model. The novelty element in this research paper uses the neural network technique. In this study, a two-stage survey is used to collect data. The first phase interviews experts from the strategic group level of The Public Health Office. The second phase examines the patient's behavior regarding route selection using a survey. The methodology uses deep learning training using the Sigmoid function and Identity function. The statistics of precision include the average percent relative error (APRE), the root mean square error (RMSE), the standard deviation (SD), and the correlation coefficient (R). Results: Deep learning is suitable for complex problems as a network. The model allows the different data sets to forecast the demand for the cross-border patient for each hospital. Equations are applied to forecast demand, in which the different hospitals require a total of 58,000 patients per year to be diagnosed by the different hospitals. The predictor performs better than the RBF and regression model. Conclusions: The novelty element of this research uses the deep learning technique as an efficient nonlinear model;moreover, it is suitable for dynamic prediction. The main advantage is to apply this model to predict the number of patients, which is the key to determining the supply chain of treatment;additionally, the ability to formulate guidelines with healthcare logistics effectively in the future.","PeriodicalId":44682,"journal":{"name":"LogForum","volume":"23 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86501339","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}
{"title":"Carrying the Burden of the Pandemic: The relationship between internal marketing, burnout, and job satisfaction in courier service industry","authors":"Özgür Uğur Arikan, E. Öztürk","doi":"10.17270/j.log.2022.715","DOIUrl":"https://doi.org/10.17270/j.log.2022.715","url":null,"abstract":"","PeriodicalId":44682,"journal":{"name":"LogForum","volume":"49 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86101479","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}
. Background : The intra-hospital patient transportation is an important aspect of patient care. It is about the transfer of patients between different healthcare units in the hospital. Many tasks are required for transferring the patients from one to another unit depending on available resources and the needs of the patients, such as types of supporting equipment, transfer routes, and supporters. Limited and unprepared resources for transferring the patients, such as lack of supporting equipment and available supporters, may impact the patient treatment and service quality. Therefore, these resources should be managed effectively in order to minimize these impacts. The case study hospital located in Chiang Mai province, northern Thailand is currently encountering the problem in managing and planning the intra-hospital transportation process. Therefore, this research aimed to propose a mathematical model for planning the intra-hospital transportation system in this case study hospital. Methods: Our research proposed a bi-level mathematical model to tackle the intra-hospital transportation planning problems. The system is represented by a deterministic model using integer linear programming. The first level of the mathematical model is for identifying the locations and setting them as transportation depots. The second level of the model is to optimize the number of resources used for intra-hospital patient transportation. The model was then validated by using two sets of instances via LINGO solver. Results: This research proposed a bi-level mathematical model that could help to manage the intra-hospital transportation challenges in the case study hospital. Furthermore, the outcomes from the test with two instances were depots positioned at a set of feasible locations. The model was used to designate resources to each depot for the instance, such as wheelchairs, stretchers, oxygen tanks, and employees. In each case, the outcomes are dependent on varying service timings and demands. Conclusion: This research used the deterministic mathematical model for planning the intra-hospital transportation system consisting of the location assignment and resource allocation. The model, in addition, can solve with the exact method. Consequently, we can ensure that the presented model can apply to real situations in further study.
{"title":"Intra-hospital patient transportation system planning using Bilevel Decision Model","authors":"Thanawat Maka, C. Kasemset, Tinnakorn Phongthiya","doi":"10.17270/j.log.2022.681","DOIUrl":"https://doi.org/10.17270/j.log.2022.681","url":null,"abstract":". Background : The intra-hospital patient transportation is an important aspect of patient care. It is about the transfer of patients between different healthcare units in the hospital. Many tasks are required for transferring the patients from one to another unit depending on available resources and the needs of the patients, such as types of supporting equipment, transfer routes, and supporters. Limited and unprepared resources for transferring the patients, such as lack of supporting equipment and available supporters, may impact the patient treatment and service quality. Therefore, these resources should be managed effectively in order to minimize these impacts. The case study hospital located in Chiang Mai province, northern Thailand is currently encountering the problem in managing and planning the intra-hospital transportation process. Therefore, this research aimed to propose a mathematical model for planning the intra-hospital transportation system in this case study hospital. Methods: Our research proposed a bi-level mathematical model to tackle the intra-hospital transportation planning problems. The system is represented by a deterministic model using integer linear programming. The first level of the mathematical model is for identifying the locations and setting them as transportation depots. The second level of the model is to optimize the number of resources used for intra-hospital patient transportation. The model was then validated by using two sets of instances via LINGO solver. Results: This research proposed a bi-level mathematical model that could help to manage the intra-hospital transportation challenges in the case study hospital. Furthermore, the outcomes from the test with two instances were depots positioned at a set of feasible locations. The model was used to designate resources to each depot for the instance, such as wheelchairs, stretchers, oxygen tanks, and employees. In each case, the outcomes are dependent on varying service timings and demands. Conclusion: This research used the deterministic mathematical model for planning the intra-hospital transportation system consisting of the location assignment and resource allocation. The model, in addition, can solve with the exact method. Consequently, we can ensure that the presented model can apply to real situations in further study.","PeriodicalId":44682,"journal":{"name":"LogForum","volume":"1 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91111421","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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