Pub Date : 2023-08-16DOI: 10.3390/logistics7030052
Patricia Inês Schwantz, L. L. Klein, Eugênio de Oliveira Simonetto
Background: This study aims to analyze the relationship between lean practices and organizational performance in a public institution, specifically, a military organization. Methods: The research has a quantitative approach with a descriptive character, having as a sample the members of a military unit located in Rio Grande do Sul. A valid sample of 116 answered questionnaires was obtained. Data analysis was carried out through multivariate statistical treatment, known as Structural Equation Modeling (SEM), using the Smart-PLS software. Results: At the end of the study, it was possible to confirm the central hypothesis of the study and conclude that lean practices (waste elimination, continuous improvement, support and leadership, member involvement, education and training, long-term thinking, quality, and systemic vision) positively impact organizational performance. Together, these elements combine to engender organizational effectiveness and success, promoting more productivity, quality, profitability, and customer satisfaction, thus improving the organization’s performance. Conclusions: It is evident that the members of the military unit are committed to optimizing organizational performance, showing constant improvement in productivity, rarely committing errors, cost reduction in activities and works, high effectiveness in meeting goals, prioritizing cost reduction in the execution of activities, as well as achieving goals and objectives related to the services provided.
{"title":"The Relationship between Lean Practices and Organizational Performance: An Analysis of Operations Management in a Public Institution","authors":"Patricia Inês Schwantz, L. L. Klein, Eugênio de Oliveira Simonetto","doi":"10.3390/logistics7030052","DOIUrl":"https://doi.org/10.3390/logistics7030052","url":null,"abstract":"Background: This study aims to analyze the relationship between lean practices and organizational performance in a public institution, specifically, a military organization. Methods: The research has a quantitative approach with a descriptive character, having as a sample the members of a military unit located in Rio Grande do Sul. A valid sample of 116 answered questionnaires was obtained. Data analysis was carried out through multivariate statistical treatment, known as Structural Equation Modeling (SEM), using the Smart-PLS software. Results: At the end of the study, it was possible to confirm the central hypothesis of the study and conclude that lean practices (waste elimination, continuous improvement, support and leadership, member involvement, education and training, long-term thinking, quality, and systemic vision) positively impact organizational performance. Together, these elements combine to engender organizational effectiveness and success, promoting more productivity, quality, profitability, and customer satisfaction, thus improving the organization’s performance. Conclusions: It is evident that the members of the military unit are committed to optimizing organizational performance, showing constant improvement in productivity, rarely committing errors, cost reduction in activities and works, high effectiveness in meeting goals, prioritizing cost reduction in the execution of activities, as well as achieving goals and objectives related to the services provided.","PeriodicalId":56264,"journal":{"name":"Logistics-Basel","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2023-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46249090","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: E-commerce’s convenience, speed, and ability to overcome geographical barriers have made it increasingly popular across industries. This study analyzed the impact of the COVID-19 pandemic on customer experience and satisfaction in supermarket retail e-commerce in the Brazilian market. The objective was to understand how the pandemic influenced satisfaction in this sector. Methods: A survey research method was employed, utilizing the Critical Incident Technique to identify key quality dimensions important to customers. A total of 133 valid responses underwent exploratory factor analysis. Results: Data analysis identified three dimensions significantly affecting overall customer satisfaction. “Presentation of Products in the Application (app)” had the highest correlation, while “Delivery Logistics” had the lowest. However, when considering the COVID-19 factor, “Delivery Logistics” showed the highest correlation. This indicates that the dimension most affected by the pandemic has the least impact on overall satisfaction in supermarket e-commerce. Conclusions: The study emphasizes the significance of understanding customer satisfaction in supermarket e-commerce, not just during the COVID-19 pandemic but also its post-pandemic consequences. Retailers should prioritize improving product presentation in apps, as it greatly influences overall satisfaction. Addressing the pandemic’s impact on delivery logistics is also crucial to ensure competitiveness in the e-commerce market.
{"title":"Analyzing the Influence of COVID-19 on the E-Commerce Customer’s Retail Experience in the Supermarket Industry: Insights from Brazil","authors":"Beatriz Moschetta Cunha, Carolina Kato Lettieri, Giulia Wiltenburg Cadena, Veridiana Rotondaro Pereira","doi":"10.3390/logistics7030053","DOIUrl":"https://doi.org/10.3390/logistics7030053","url":null,"abstract":"Background: E-commerce’s convenience, speed, and ability to overcome geographical barriers have made it increasingly popular across industries. This study analyzed the impact of the COVID-19 pandemic on customer experience and satisfaction in supermarket retail e-commerce in the Brazilian market. The objective was to understand how the pandemic influenced satisfaction in this sector. Methods: A survey research method was employed, utilizing the Critical Incident Technique to identify key quality dimensions important to customers. A total of 133 valid responses underwent exploratory factor analysis. Results: Data analysis identified three dimensions significantly affecting overall customer satisfaction. “Presentation of Products in the Application (app)” had the highest correlation, while “Delivery Logistics” had the lowest. However, when considering the COVID-19 factor, “Delivery Logistics” showed the highest correlation. This indicates that the dimension most affected by the pandemic has the least impact on overall satisfaction in supermarket e-commerce. Conclusions: The study emphasizes the significance of understanding customer satisfaction in supermarket e-commerce, not just during the COVID-19 pandemic but also its post-pandemic consequences. Retailers should prioritize improving product presentation in apps, as it greatly influences overall satisfaction. Addressing the pandemic’s impact on delivery logistics is also crucial to ensure competitiveness in the e-commerce market.","PeriodicalId":56264,"journal":{"name":"Logistics-Basel","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2023-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46189802","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}
Nowadays, the business landscape is highly focused on establishing efficient logistics systems, with numerous companies striving to gain a strong foothold in the global market and achieve maximum productivity and cost effectiveness [...]
{"title":"Recent Advances of Solutions Algorithms for Logistics Routing Problems","authors":"Erfan Babaee Tirkolaee, Alireza Goli, Behnam Malmir","doi":"10.3390/logistics7030051","DOIUrl":"https://doi.org/10.3390/logistics7030051","url":null,"abstract":"Nowadays, the business landscape is highly focused on establishing efficient logistics systems, with numerous companies striving to gain a strong foothold in the global market and achieve maximum productivity and cost effectiveness [...]","PeriodicalId":56264,"journal":{"name":"Logistics-Basel","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42116598","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 : 2023-08-09DOI: 10.3390/logistics7030050
Adnan Al-Banna, Z. A. Rana, Mohammed Yaqot, B. Menezes
Background: As industry and society move towards the second decade of the deluge of advanced technologies of the Industry 4.0 (I4.0) age, introduced circa 2012, it is evident that the global economy continues to grapple with a plethora of ever-intensifying disruptions and vulnerabilities that inflict unexpected and uncontrolled damages on multiple organizational processes. These circumstances demand significant paradigm shifts, placing supply chain resilience (SCR) in the foreground of boardrooms and agendas of executive meetings. Method: This paper presents a bibliometric analysis of selected articles that examine the intricate interplay of I4.0 and SCR under investment constraints. Employing a funnel approach, this study delves deeper into about a hundred papers that were initially selected from a pool of approximately four thousand publications on SCR. The study thoroughly analyzes the interconnection between SCR, I4.0, and investment (INV) while classifying these articles in a structured manner, based on industry type and focus. Results: The primary aim of the paper is to identify trends, gaps, and potential opportunities for future research on the SCR-I4.0-INV interplays. Conclusions: The findings reveal that industries are converging towards the implementation of digital technologies as a strategic move to tackle unexpected, unplanned, and undesired situations. This research illuminates the needs for organizations to prioritize supply chain resilience in the face of disruptions and vulnerabilities while highlighting the potential of digital technologies to enhance their resilience, therefore ensuring sustainable growth.
{"title":"Interconnectedness between Supply Chain Resilience, Industry 4.0, and Investment","authors":"Adnan Al-Banna, Z. A. Rana, Mohammed Yaqot, B. Menezes","doi":"10.3390/logistics7030050","DOIUrl":"https://doi.org/10.3390/logistics7030050","url":null,"abstract":"Background: As industry and society move towards the second decade of the deluge of advanced technologies of the Industry 4.0 (I4.0) age, introduced circa 2012, it is evident that the global economy continues to grapple with a plethora of ever-intensifying disruptions and vulnerabilities that inflict unexpected and uncontrolled damages on multiple organizational processes. These circumstances demand significant paradigm shifts, placing supply chain resilience (SCR) in the foreground of boardrooms and agendas of executive meetings. Method: This paper presents a bibliometric analysis of selected articles that examine the intricate interplay of I4.0 and SCR under investment constraints. Employing a funnel approach, this study delves deeper into about a hundred papers that were initially selected from a pool of approximately four thousand publications on SCR. The study thoroughly analyzes the interconnection between SCR, I4.0, and investment (INV) while classifying these articles in a structured manner, based on industry type and focus. Results: The primary aim of the paper is to identify trends, gaps, and potential opportunities for future research on the SCR-I4.0-INV interplays. Conclusions: The findings reveal that industries are converging towards the implementation of digital technologies as a strategic move to tackle unexpected, unplanned, and undesired situations. This research illuminates the needs for organizations to prioritize supply chain resilience in the face of disruptions and vulnerabilities while highlighting the potential of digital technologies to enhance their resilience, therefore ensuring sustainable growth.","PeriodicalId":56264,"journal":{"name":"Logistics-Basel","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2023-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42497205","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 : 2023-08-04DOI: 10.3390/logistics7030049
Silvia Araújo dos Reis, J. Leal, A. M. T. Thomé
Background: The soybean market is representative of the world. Brazil is the largest producer and exporter of this crop and has low production costs but high logistical costs, which are influenced mainly by transport costs. Added to these characteristics, the disputed grain supply, the possibility of crop failure, and the randomness of some parameters that influence the soybean supply chain make decisions even more challenging. Methods: To mathematically model this problem, we carried out an analysis of the scientific production related to grain supply chain and the models used to address the problem, as well as a document analysis and a case study. Results: This paper proposes a new two-stage stochastic linear programming model with fixed recourse for tactical planning in the soybean supply chain from the perspective of the shipper under take or pay contracts over a one-year time horizon. The first-stage variables are the grain purchasing decisions and the volumes of rail and road transportation hired in advance. The model addresses 243 scenarios derived from four uncertainty sources: the purchase and sale prices of raw agricultural products on the spot market, the probability of crop failure, and the external demand. Conclusions: The model is successfully applied to a soybean trade firm in Brazil with expected gain of US$4,299,720 when using the stochastic model instead of the deterministic model. The stochastic model protected the firm from take or pay fines and crop failures, contracting a smaller volume of rail transport than what the company does.
{"title":"A Two-Stage Stochastic Linear Programming Model for Tactical Planning in the Soybean Supply Chain","authors":"Silvia Araújo dos Reis, J. Leal, A. M. T. Thomé","doi":"10.3390/logistics7030049","DOIUrl":"https://doi.org/10.3390/logistics7030049","url":null,"abstract":"Background: The soybean market is representative of the world. Brazil is the largest producer and exporter of this crop and has low production costs but high logistical costs, which are influenced mainly by transport costs. Added to these characteristics, the disputed grain supply, the possibility of crop failure, and the randomness of some parameters that influence the soybean supply chain make decisions even more challenging. Methods: To mathematically model this problem, we carried out an analysis of the scientific production related to grain supply chain and the models used to address the problem, as well as a document analysis and a case study. Results: This paper proposes a new two-stage stochastic linear programming model with fixed recourse for tactical planning in the soybean supply chain from the perspective of the shipper under take or pay contracts over a one-year time horizon. The first-stage variables are the grain purchasing decisions and the volumes of rail and road transportation hired in advance. The model addresses 243 scenarios derived from four uncertainty sources: the purchase and sale prices of raw agricultural products on the spot market, the probability of crop failure, and the external demand. Conclusions: The model is successfully applied to a soybean trade firm in Brazil with expected gain of US$4,299,720 when using the stochastic model instead of the deterministic model. The stochastic model protected the firm from take or pay fines and crop failures, contracting a smaller volume of rail transport than what the company does.","PeriodicalId":56264,"journal":{"name":"Logistics-Basel","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2023-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42513761","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 : 2023-08-04DOI: 10.3390/logistics7030048
Leonel J. R. Nunes, Sandra Silva
This study delves into the critical role of logistical cost optimization in the residual woody biomass supply chain, aiming to enhance the sustainability and efficiency of this resource’s exploitation. The research underscores that proficient cost management of logistical operations is pivotal for the economic feasibility of residual biomass utilization. The paper scrutinizes key aspects, such as collection, transportation, storage, and processing of biomass, emphasizing their individual contributions to the overall cost. It also pays particular attention to the impacts of seasonality and biomass quality variations, which directly influence the cost and effectiveness of the supply chain. To facilitate a deeper understanding of these factors, the study introduces mathematical models that enable the exploration of diverse scenarios and optimization strategies. The use of linear programming, genetic algorithms, and tabu search techniques are discussed in the context of these models. The findings of this research hold significant implications for the management of the residual biomass supply chain and contribute to the transition towards a low-carbon economy.
{"title":"Optimization of the Residual Biomass Supply Chain: Process Characterization and Cost Analysis","authors":"Leonel J. R. Nunes, Sandra Silva","doi":"10.3390/logistics7030048","DOIUrl":"https://doi.org/10.3390/logistics7030048","url":null,"abstract":"This study delves into the critical role of logistical cost optimization in the residual woody biomass supply chain, aiming to enhance the sustainability and efficiency of this resource’s exploitation. The research underscores that proficient cost management of logistical operations is pivotal for the economic feasibility of residual biomass utilization. The paper scrutinizes key aspects, such as collection, transportation, storage, and processing of biomass, emphasizing their individual contributions to the overall cost. It also pays particular attention to the impacts of seasonality and biomass quality variations, which directly influence the cost and effectiveness of the supply chain. To facilitate a deeper understanding of these factors, the study introduces mathematical models that enable the exploration of diverse scenarios and optimization strategies. The use of linear programming, genetic algorithms, and tabu search techniques are discussed in the context of these models. The findings of this research hold significant implications for the management of the residual biomass supply chain and contribute to the transition towards a low-carbon economy.","PeriodicalId":56264,"journal":{"name":"Logistics-Basel","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2023-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42353355","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 : 2023-08-03DOI: 10.3390/logistics7030047
Nataliia Letunovska, Felix Amoako Offei, Prince Amoh Junior Junior, Oleksii Lyulyov, Tetyana Pimonenko, Aleksy Kwilinski
Background: Sustainable procurement is about considering social and environmental factors alongside financial factors in making procurement decisions and purchasing goods and services that take into account the social, economic, and environmental impact that such purchasing has on people and communities. This study was carried out to address the effects of procurement sustainability on reverse logistics. It considered four objectives: to establish the relationship between environmental procurement sustainability and reverse logistics, to examine the relationship between economic procurement sustainability and reverse logistics, to examine the relationship between social sustainability procurement and reverse logistics, and to examine the moderating role of government policy. Methods: This study applied structural equation modeling to check the research hypotheses. A purposive sampling technique was used. A structured questionnaire was used to gather primary data. The data gathered were analyzed using descriptive and inferential analysis. The data were analyzed in SPSS version 21. The study found that environmental, economic, and social procurement sustainability has a significant and positive effect on reverse logistics. Government policy moderates the relationships between environmental, economic, and social procurement sustainability and reverse logistics. Conclusions: This study recommends that organizations team up with environmental protection agencies to produce environmentally friendly products. Social interventions that can help protect society from damage should be acknowledged. Good economic policies that ensure that organizations increase their wealth should also be acknowledged.
背景:可持续采购是指在做出采购决策和购买商品和服务时考虑社会和环境因素以及财务因素，并考虑到这种采购对人民和社区的社会、经济和环境影响。本研究旨在解决采购可持续性对逆向物流的影响。它考虑了四个目标:建立环境可持续性采购与逆向物流之间的关系，研究经济可持续性采购与逆向物流之间的关系，研究社会可持续性采购与逆向物流之间的关系，以及研究政府政策的调节作用。方法:采用结构方程模型对研究假设进行检验。采用了有目的的抽样技术。采用结构化问卷收集原始数据。收集的数据采用描述性和推断性分析进行分析。数据采用SPSS version 21进行分析。研究发现，环境、经济和社会采购可持续性对逆向物流具有显著的正向影响。政府政策调节了环境、经济和社会采购可持续性与逆向物流之间的关系。结论:本研究建议组织与环境保护机构合作生产环境友好型产品。应当承认有助于保护社会免受损害的社会干预措施。确保组织增加财富的良好经济政策也应该得到承认。
{"title":"Green Supply Chain Management: The Effect of Procurement Sustainability on Reverse Logistics","authors":"Nataliia Letunovska, Felix Amoako Offei, Prince Amoh Junior Junior, Oleksii Lyulyov, Tetyana Pimonenko, Aleksy Kwilinski","doi":"10.3390/logistics7030047","DOIUrl":"https://doi.org/10.3390/logistics7030047","url":null,"abstract":"Background: Sustainable procurement is about considering social and environmental factors alongside financial factors in making procurement decisions and purchasing goods and services that take into account the social, economic, and environmental impact that such purchasing has on people and communities. This study was carried out to address the effects of procurement sustainability on reverse logistics. It considered four objectives: to establish the relationship between environmental procurement sustainability and reverse logistics, to examine the relationship between economic procurement sustainability and reverse logistics, to examine the relationship between social sustainability procurement and reverse logistics, and to examine the moderating role of government policy. Methods: This study applied structural equation modeling to check the research hypotheses. A purposive sampling technique was used. A structured questionnaire was used to gather primary data. The data gathered were analyzed using descriptive and inferential analysis. The data were analyzed in SPSS version 21. The study found that environmental, economic, and social procurement sustainability has a significant and positive effect on reverse logistics. Government policy moderates the relationships between environmental, economic, and social procurement sustainability and reverse logistics. Conclusions: This study recommends that organizations team up with environmental protection agencies to produce environmentally friendly products. Social interventions that can help protect society from damage should be acknowledged. Good economic policies that ensure that organizations increase their wealth should also be acknowledged.","PeriodicalId":56264,"journal":{"name":"Logistics-Basel","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136163313","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 : 2023-07-29DOI: 10.3390/logistics7030046
Rana Azab, Rana Mahmoud, Rahma Elbehery, M. Gheith
Background: Agro-food supply chains possess specific characteristics due to the diverse nature of products involved and contribute to all three pillars of sustainability, making the optimal design of a sustainable agro-food supply chain a complex problem. Therefore, efficient models incorporating the unique characteristics of such chains are essential for making optimal supply chain decisions and achieving economically and environmentally sustainable agro-food supply chains that contribute to global food security. Methods: This article presents a multi-objective mixed-integer linear programing model that integrates agricultural-related strategic decisions into the tactical design of an agro-food supply chain. The model considers transportation, inventory, processing, demand fulfilment, and waste disposal decisions. It also accounts for seasonality and perishability, ensuring a comprehensive approach to sustainability. The model aims to maximize the total generated profits across the supply chain while simultaneously minimizing CO2 emissions as a measure of environmental impact. Results: By implementing the model on a sugar beet supply chain in the Netherlands, strategic crop rotation farm schedules for the crop rotation cycle and the optimum supply network decisions are obtained. Furthermore, different objectives are analyzed and the Pareto-efficient frontier is investigated to analyze the underlying trade-offs. Additionally, the model serves as a decision support tool for managers facilitating informed investment decisions in technologies that prolong product shelf life while maintaining profitability. Conclusions: The proposed multi-objective model offers a valuable framework for designing economically and environmentally sustainable agro-food supply chains. By aligning with sustainability goals and providing decision support, this research contributes to enhancing global food security and promoting sustainable resource utilization.
{"title":"A Bi-Objective Mixed-Integer Linear Programming Model for a Sustainable Agro-Food Supply Chain with Product Perishability and Environmental Considerations","authors":"Rana Azab, Rana Mahmoud, Rahma Elbehery, M. Gheith","doi":"10.3390/logistics7030046","DOIUrl":"https://doi.org/10.3390/logistics7030046","url":null,"abstract":"Background: Agro-food supply chains possess specific characteristics due to the diverse nature of products involved and contribute to all three pillars of sustainability, making the optimal design of a sustainable agro-food supply chain a complex problem. Therefore, efficient models incorporating the unique characteristics of such chains are essential for making optimal supply chain decisions and achieving economically and environmentally sustainable agro-food supply chains that contribute to global food security. Methods: This article presents a multi-objective mixed-integer linear programing model that integrates agricultural-related strategic decisions into the tactical design of an agro-food supply chain. The model considers transportation, inventory, processing, demand fulfilment, and waste disposal decisions. It also accounts for seasonality and perishability, ensuring a comprehensive approach to sustainability. The model aims to maximize the total generated profits across the supply chain while simultaneously minimizing CO2 emissions as a measure of environmental impact. Results: By implementing the model on a sugar beet supply chain in the Netherlands, strategic crop rotation farm schedules for the crop rotation cycle and the optimum supply network decisions are obtained. Furthermore, different objectives are analyzed and the Pareto-efficient frontier is investigated to analyze the underlying trade-offs. Additionally, the model serves as a decision support tool for managers facilitating informed investment decisions in technologies that prolong product shelf life while maintaining profitability. Conclusions: The proposed multi-objective model offers a valuable framework for designing economically and environmentally sustainable agro-food supply chains. By aligning with sustainability goals and providing decision support, this research contributes to enhancing global food security and promoting sustainable resource utilization.","PeriodicalId":56264,"journal":{"name":"Logistics-Basel","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2023-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42860511","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 : 2023-07-27DOI: 10.3390/logistics7030045
J. Vasilev, R. Nikolaev, Tanka Milkova
Background: With regard to the definition of an optimal transport plan for some material flow in the logistics system in literature and practice, the classical transport task model is developed. The minimization of total transport costs is usually considered for optimality. Some modifications to the classical transport task have also been developed. Methods: The article uses the methods of linear optimization. Based on these methods, two modified transport task models have been constructed, which consider the possibility of planning in advance the quantities available from the suppliers of the transported cargo. These models are applicable in SCM for pharmaceuticals with a national logistics hub. Furthermore, a solver in MS Excel is used to determine the optimal solution of optimization models. Results: Two new (modified, extended) models of the transport task have been constructed, in which a preliminary planning of the available quantities of the transported cargo at the suppliers is made. These quantities shall be planned in such a way as to ensure a minimum total transport cost. Conclusions: By applying the proposed new transport task models, lower total transport costs for carrying out imported pharmaceuticals can be ensured compared to an application of the classical transport task model.
{"title":"Transport Task Models with Variable Supplier Availabilities","authors":"J. Vasilev, R. Nikolaev, Tanka Milkova","doi":"10.3390/logistics7030045","DOIUrl":"https://doi.org/10.3390/logistics7030045","url":null,"abstract":"Background: With regard to the definition of an optimal transport plan for some material flow in the logistics system in literature and practice, the classical transport task model is developed. The minimization of total transport costs is usually considered for optimality. Some modifications to the classical transport task have also been developed. Methods: The article uses the methods of linear optimization. Based on these methods, two modified transport task models have been constructed, which consider the possibility of planning in advance the quantities available from the suppliers of the transported cargo. These models are applicable in SCM for pharmaceuticals with a national logistics hub. Furthermore, a solver in MS Excel is used to determine the optimal solution of optimization models. Results: Two new (modified, extended) models of the transport task have been constructed, in which a preliminary planning of the available quantities of the transported cargo at the suppliers is made. These quantities shall be planned in such a way as to ensure a minimum total transport cost. Conclusions: By applying the proposed new transport task models, lower total transport costs for carrying out imported pharmaceuticals can be ensured compared to an application of the classical transport task model.","PeriodicalId":56264,"journal":{"name":"Logistics-Basel","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2023-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49077276","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 : 2023-07-26DOI: 10.3390/logistics7030044
Ming Li, M. D. Voss, J. Cangelosi
Background: To help ensure roadway safety, the federal government mandates trucking companies to conduct pre-employment urine drug tests before allowing drivers to operate a commercial motor vehicle. Unfortunately, urine testing has a short detection window and is easily thwarted, leading some carriers to employ hair testing. Methods: t-tests were utilized to compare hair and urine pre-employment drug test results provided by seven large U.S. trucking companies. Results: results indicate that hair’s positivity rate is statistically greater than urine for each examined drug and across all drugs combined. Conclusions: This paper is the only supply chain work of which we are aware that assesses the statistical differences between hair and urine testing positivity rates. Results support hair testing’s increased ability to prevent lifestyle drug users from operating commercial motor vehicles and should be considered by public policy makers considering whether hair testing results should be allowed into the Drug and Alcohol Clearinghouse.
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