Advanced Processes Optimization in Logistics and Supply Chain Management

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Environmental and Green Processes".

Deadline for manuscript submissions: closed (20 August 2023) | Viewed by 38893

Special Issue Editors


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Guest Editor
1. Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung 807618, Taiwan
2. Department of Logistics and Supply Chain Management, Hong Bang International University, Ho Chi Minh 72320, Vietnam
Interests: group decision making; data envelopment analysis (DEA); multi-criteria decision analysis (MCDA); fuzzy set theory; applied operations research; forecasting; production planning and inventory control; lean manufacturing; logistics and supply chain network design; design of experiment (DOE)
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung 80778, Taiwan
Interests: multi-criteria decision-making; operational research; supply chain management; data envelopment analysis; procurement
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Complex logistics systems and supply chain networks have always been important challenges in today's globally competitive economy. Logistics and supply chains have a long tradition of improving operations, especially in cost reduction, new product development, supplier selection, technology innovation, production planning, distribution, process procedures, green environments, and customer value generation, to name a few. As a result of the ever-changing nature and growth of technology, modern logistics and supply chains confront new challenges regarding the integration of physical and cyber systems, resilience to unpredictable events, and flexibility of dynamic situations. All of them are critical to an organization's operational and long-term success. More significantly, in response to global climate change and the post-COVID-19 era, businesses have begun to consider investing in low-carbon technologies in their production process to improve the green level of supply chain practices.

Optimization techniques are widely used in the complex issues of logistics and supply chain. Recent studies in advanced optimization modeling and its applications in logistics and supply chain practices have become very important for industries and academics. Moreover, fundamental research has looked further into low-carbon, sustainable, and recycling supply chain concerns and how firms, their supply chain partners, and customers can all work together to have a lasting effect and improve sustainability performance.

In this Special Issue, we solicit high-quality research focused on state-of-the-art techniques and methods employed in sustainable logistics and supply chain systems. Authors are invited to present original research and review articles that will stimulate the continuing efforts in this field.

Dr. Chia-Nan Wang
Dr. Thanh-Tuan Dang
Dr. Ngoc-Ai-Thy Nguyen
Guest Editors

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Keywords

  • supply chain management
  • sustainable supply chain
  • green supply chain
  • closed-loop supply chain
  • omni-channel supply chain
  • supply chain agility
  • supply chain adaptability
  • dynamic supply chain alignment
  • supply chain resilience
  • low-carbon logistics
  • mathematical logistics
  • optimization techniques
  • soft computing
  • multi-criteria decision-making (MCDM)
  • data envelopment analysis (DEA)
  • fuzzy applications
  • big data
  • blockchain
  • artificial intelligence

Published Papers (16 papers)

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Research

14 pages, 1855 KiB  
Article
A City Logistics Distribution Model: A Physical Internet Approach
by Jianxun Li, Haoxin Fu, Kin Keung Lai and Bhagwat Ram
Processes 2023, 11(11), 3198; https://doi.org/10.3390/pr11113198 - 09 Nov 2023
Viewed by 825
Abstract
The Physical Internet (PI) provides a solution for coping with the continuous rise in urban logistical demands by exploring same-level and cross-level paths. This research suggests a PI-based urban logistical distribution model based on PI distribution that minimizes transportation costs. It also intends [...] Read more.
The Physical Internet (PI) provides a solution for coping with the continuous rise in urban logistical demands by exploring same-level and cross-level paths. This research suggests a PI-based urban logistical distribution model based on PI distribution that minimizes transportation costs. It also intends to maintain the integrity of the logistical transportation process. This proposed model enhances the flexibility of goods operation and reduces the global cost of logistics’ distribution using an interconnected and open PI logistics distribution mode. This model also explores the functional aspects of the operational problems of city logistical systems and relates to optimization problems. These functionalities are realized by the hierarchical functional structure and are characterized by different cost specifications. The proposed framework provides better integration and cooperation between city logistics warehouses and higher utilization level of logistical infrastructure. The experimental results show that the distribution cost of the PI logistics model is significantly better than that of a traditional logistics model. The elastic and cost advantages grow relatively as the infrastructure for distribution scales up and interruptions from emergencies occur. Full article
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28 pages, 1493 KiB  
Article
Simulation-Based Approach for Multi-Echelon Inventory System Selection: Case of Distribution Systems
by Noucaiba Sbai and Abdelaziz Berrado
Processes 2023, 11(3), 796; https://doi.org/10.3390/pr11030796 - 07 Mar 2023
Cited by 1 | Viewed by 3538
Abstract
Due to the current complexity of the supply chain, multi-echelon inventory management has become challenging while also being an interesting field of research as it allows efficient control of supply chain interdependencies. It became clear to many researchers that analytical models are no [...] Read more.
Due to the current complexity of the supply chain, multi-echelon inventory management has become challenging while also being an interesting field of research as it allows efficient control of supply chain interdependencies. It became clear to many researchers that analytical models are no longer effective for addressing the multi-echelon inventory management problem. Simulation can be used to assess and quantify the impact of each inventory strategy on a supply chain performance. Our paper aims to provide a simulation-based approach to guide decision makers select and validate a multi-echelon distribution inventory system. The proposed approach is composed of four major steps that involve characterization of the current supply chain, conceptual modeling of the multi-echelon inventory system alternatives, and finally, simulation modeling using appropriate simulation software to compare and test different options. The approach was also tested and validated through an application to the case of the Moroccan pharmaceutical products supply chain in the public sector. The results of the simulation demonstrated that adopting an installation stock policy at all levels of the supply chain with an allocation of safety stocks in the most downstream stages is the best and most appropriate alternative for the pharmaceutical supply chain under study. Full article
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32 pages, 4908 KiB  
Article
SAPEVO-H² a Multi-Criteria Systematic Based on a Hierarchical Structure: Decision-Making Analysis for Assessing Anti-RPAS Strategies in Sensing Environments
by Miguel Ângelo Lellis Moreira, Fernando Cesar Almeida Silva, Igor Pinheiro de Araújo Costa, Carlos Francisco Simões Gomes and Marcos dos Santos
Processes 2023, 11(2), 352; https://doi.org/10.3390/pr11020352 - 22 Jan 2023
Cited by 4 | Viewed by 1556
Abstract
Regarding high-level and complex decision-making scenarios, the study presents an extensive approach to the Simple Aggregation of Preferences Expressed by Ordinal Vectors-Multi Decision Making method (SAPEVO-M). In this context, the modeling proposal, named SAPEVO-Hybrid and Hierarchical (SAPEVO-H²), the objective of this study, based [...] Read more.
Regarding high-level and complex decision-making scenarios, the study presents an extensive approach to the Simple Aggregation of Preferences Expressed by Ordinal Vectors-Multi Decision Making method (SAPEVO-M). In this context, the modeling proposal, named SAPEVO-Hybrid and Hierarchical (SAPEVO-H²), the objective of this study, based on the concepts of multi-criteria analysis, provides the evaluation of alternatives under the light of multiple criteria and perceptions, enabling the integration of the objectives of a problem, which are transcribed into attributes and structured in a hierarchical model, analyzing qualitative and quantitative data through ordinal and cardinal entries, respectively. As a case study, a decision analysis concerning the defense strategies against anti-Remotely Piloted Aircraft Systems (RPAS) strategies for the Brazilian Navy is carried out. Using the technique of the causal maps approach based on Strategic Options Development and Analysis (SODA) methodology, the problematic situation is structured for numerical implementation, demonstrating the performance of objectives and elements of a hierarchical structure. As a result, rankings concerning objectives and anti-RPAS technologies, based on the treatment of subjective information, are presented. In the end, the main contribution of the study and its limitations are discussed, along with the conclusions and some proposals for future studies. Full article
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13 pages, 1997 KiB  
Article
Logistics Trends and Innovations in Response to COVID-19 Pandemic: An Analysis Using Text Mining
by Niels A. Zondervan, Frazen Tolentino-Zondervan and Dennis Moeke
Processes 2022, 10(12), 2667; https://doi.org/10.3390/pr10122667 - 12 Dec 2022
Cited by 5 | Viewed by 4428
Abstract
The disruptions caused by the COVID-19 pandemic have forced many companies in the logistics sector to innovate, or even transform their business and underlying processes. Closing borders, limited supply and manpower, and continuous changes in regulations challenged many logistics firms to innovate. This [...] Read more.
The disruptions caused by the COVID-19 pandemic have forced many companies in the logistics sector to innovate, or even transform their business and underlying processes. Closing borders, limited supply and manpower, and continuous changes in regulations challenged many logistics firms to innovate. This study analyzes 5098 abstracts of logistics articles using text mining to identify and to quantify the changes in logistics trends and innovations before and during the COVID-19 pandemic, and if these trends and innovations were accelerated by the COVID-19 pandemic. Results indicate that (1) resiliency is an ongoing trend in logistics and has shown increasing importance during the COVID-19 pandemic; (2) there appears to be acceleration in digitalization trend in logistics based on emerging focus on blockchain, Internet of Things, data, drones, robots, and unmanned vehicles during COVID-19 pandemic, and (3) there seems to be no evidence of acceleration in sustainability due to COVID-19 despite an observed shift in sustainability trends in terms of bioenergy and biofuel before COVID-19 pandemic to low-carbon, hydrogen and electric vehicles during COVID-19 pandemic. This paper recommends logistics firms, especially Small and Medium Enterprises (SMEs), to analyze their readiness to adopt digitalization in terms of data, resources, and technology via, e.g., the use of a maturity scan, to contribute to sustainable and resilient logistics and to make sure that they remain competitive and future-proof. Policy makers can provide support to these SMEs by providing information, funding, and template solutions. Full article
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24 pages, 3239 KiB  
Article
A Study of Performance Evaluation for Textile and Garment Enterprises
by Chia-Nan Wang, Phuong-Thuy Thi Nguyen, Yen-Hui Wang and Thanh-Tuan Dang
Processes 2022, 10(11), 2381; https://doi.org/10.3390/pr10112381 - 13 Nov 2022
Cited by 1 | Viewed by 3526
Abstract
Vietnam’s textile and garment enterprises make an important contribution to the country with the second largest export turnover. The existence and development of textile and garment enterprises have a significant influence on the socioeconomic development of Vietnam. Currently, Vietnam’s textile and garment industry [...] Read more.
Vietnam’s textile and garment enterprises make an important contribution to the country with the second largest export turnover. The existence and development of textile and garment enterprises have a significant influence on the socioeconomic development of Vietnam. Currently, Vietnam’s textile and garment industry is facing difficulties caused by the COVID-19 pandemic, along with competition from foreign direct investment (FDI) enterprises. Therefore, it is imperative for managers to assess competitiveness by measuring their past and current performance indicators. This study assesses the performance of Vietnam’s 10 textile and garment enterprises from 2017 to 2020 by combining the DEA–Malmquist productivity index (MPI) and epsilon-based measure (EBM) model. The proposed model considered three inputs (total assets, cost of goods sold, and liabilities) and two outputs (total revenue and gross profit). In addition to showing the best-performing companies from certain aspects during the period (2017–2020), the results show that the EBM method combined with the Malmquist model in the field can be successfully applied. This study is a reference for companies in the textile and garment industry to identify their position to improve their operational efficiency and overcome their weaknesses. Full article
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16 pages, 2034 KiB  
Article
An Optimization Method for Distributing Emergency Materials Which Balances Multiple Decision Criteria
by Yanyan Wang
Processes 2022, 10(11), 2317; https://doi.org/10.3390/pr10112317 - 07 Nov 2022
Cited by 2 | Viewed by 1167
Abstract
In emergency rescue operations, it is very important for emergency management to arrange emergency materials scientifically and reasonably according to emergency needs. However, the decision criteria for emergency material distribution are often diverse, coupled with the lack of information acquisition due to the [...] Read more.
In emergency rescue operations, it is very important for emergency management to arrange emergency materials scientifically and reasonably according to emergency needs. However, the decision criteria for emergency material distribution are often diverse, coupled with the lack of information acquisition due to the suddenness and development complexity of disasters, which makes the scientific decisions about emergency material distribution face great challenges. This paper proposes a multi-criteria decision optimization model of emergency material distribution under uncertainty that combines the 4E criteria of performance evaluation (economic criterion, efficiency criterion, effectiveness criterion and equity criterion). Then, the solution method of the multiple decision criteria model is designed. Finally, a case study of emergency medical material distribution during COVID-19 in China was conducted for model verification. The results show that different decision criteria have an important impact on the distribution of emergency materials, and the proposed model has significant advantages in the allocation of large-scale disaster relief materials, which can provide a useful reference for emergency material distribution under uncertain information conditions. Full article
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27 pages, 23972 KiB  
Article
A Modified FMEA Approach to Predict Job Shop Disturbance
by Yongtao Qiu and Hongtao Zhang
Processes 2022, 10(11), 2223; https://doi.org/10.3390/pr10112223 - 28 Oct 2022
Cited by 2 | Viewed by 1157
Abstract
Failure modes and effects analysis (FMEA) is a systematic approach that focuses on evaluating critical disturbances in a system. However, traditional FMEA has its own drawbacks, such as invalid computations and ambiguous priority definitions, which lead to many constraints in the application of [...] Read more.
Failure modes and effects analysis (FMEA) is a systematic approach that focuses on evaluating critical disturbances in a system. However, traditional FMEA has its own drawbacks, such as invalid computations and ambiguous priority definitions, which lead to many constraints in the application of complex production processes, especially in job shops with various resources. Therefore, this paper proposes an analytic disturbance prediction method for job shop with multiple resources and multiple evaluation indexes, which combines the vector computing techniques, FMEA, and fuzzy analytic hierarchy process (FAHP). In contrast to other work, this paper focuses on the establishment of FMEA mathematical model to improve the readability of multi-resource disturbance risk results. To this end, the projection of the disturbance vector is visualized to reduce repeated calculation results, triangles and trapezoids are used as membership functions to improve the accuracy of weight, and the differentiation index is used to reduce the ambiguity of priorities. The proposed method can effectively discover the critical disturbances and enable managers to undertake more assertive decisions. Full article
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32 pages, 2298 KiB  
Article
Evaluating the Performance of a Safe Insulin Supply Chain Using the AHP-TOPSIS Approach
by Mona Haji, Laoucine Kerbache and Tareq Al-Ansari
Processes 2022, 10(11), 2203; https://doi.org/10.3390/pr10112203 - 26 Oct 2022
Cited by 5 | Viewed by 2396
Abstract
People with type 1 diabetes require insulin, a lifesaving and essential medication, to maintain their blood sugar levels below dangerous levels. Unfortunately, the insulin industry faces supply and affordability issues, and patients and their families face an enormous burden. As a result of [...] Read more.
People with type 1 diabetes require insulin, a lifesaving and essential medication, to maintain their blood sugar levels below dangerous levels. Unfortunately, the insulin industry faces supply and affordability issues, and patients and their families face an enormous burden. As a result of high prices and lack of availability, individuals are turning to other options for purchasing insulin, such as online pharmacies, which may or may not be legitimate. Despite the necessity of safe insulin for diabetics in the legitimate Pharmaceutical Supply Chain (PSC), few researchers have considered implementing strategies to maximize patient safety for purchasing insulin. Therefore, the current research seeks to bridge this gap and provide cohesive information on overcoming this challenge and maximizing insulin safety. This study employs a Multi-Criteria Decision-Making (MCDM) model that combines Supply Chain Operations Reference (SCOR) metrics, Analytic Hierarchy Process (AHP), and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to develop a model that can prioritize and select the best criteria for maximizing insulin safety and achieving the study objective. A comparison of two insulin supply chain scenarios was performed. As a result of this research, adding a traceability technology to the insulin supply chain, specifically blockchain (T42) in scenario 2 provides the best results to the supply chain for maximizing and ensuring the safety of insulin, as compared to scenario 1, where the final score achieved almost 71%. This research provides a useful tool for assessing the safety of other critical goods that customers value in strategic and complex decision-making. Academics, professionals, and decision-makers can benefit from this research using a rigorous scientific decision-support system. Full article
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25 pages, 4277 KiB  
Article
Social Media Strategy Processes for Centralized Payment Network Firms after a War Crisis Outset
by Damianos P. Sakas, Nikolaos T. Giannakopoulos, Marina C. Terzi, Ioannis Dimitrios G. Kamperos, Dimitrios K. Nasiopoulos, Dimitrios P. Reklitis and Nikos Kanellos
Processes 2022, 10(10), 1995; https://doi.org/10.3390/pr10101995 - 02 Oct 2022
Cited by 9 | Viewed by 1982
Abstract
From the outset of the war in Ukraine, extensive crises in many sectors of the world economy have occurred, with firms offering services and products both online and through physical stores facing serious problems. These problems are mainly related to higher operational costs [...] Read more.
From the outset of the war in Ukraine, extensive crises in many sectors of the world economy have occurred, with firms offering services and products both online and through physical stores facing serious problems. These problems are mainly related to higher operational costs and the lack of website visibility. For this research study, centralized payment network organizations (CPNs), firms providing online payment services through their networks, were selected and analytical data from their websites were collected for a period of 6 months. The main focus of this research study is to evaluate benefits and the role of social media strategies for CPNs’ digital marketing performance during crisis events and to also assess their utility as a risk-management tool. Following data collection, the authors performed statistical processes (regression and correlation analysis) and stationary modeling with Fuzzy Cognitive Mapping (FCM) tools; finally, dynamic simulations were performed by utilizing Agent-Based Models (ABM). The authors suggest that various variables of CPNs’ social media platforms can aid in improving their digital marketing performance and, using proper analysis, can lead to higher user social engagement, thus rendering social media strategy a useful risk-management tool. Full article
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14 pages, 2554 KiB  
Article
Optimization of Logistics System with Fuzzy FMEA-AHP Methodology
by Guangying Jin, Qingpu Meng and Wei Feng
Processes 2022, 10(10), 1973; https://doi.org/10.3390/pr10101973 - 30 Sep 2022
Cited by 10 | Viewed by 2484
Abstract
The COVID-19 pandemic broke out and the global logistics industry suffered severe losses; therefore, the Fuzzy FMEA-AHP (Fuzzy Failure Mode and Effects Analysis-Analytic Hierarchy Process) method is proposed to analyze the failure reasons of the logistics system in the COVID-19 pandemic. In this [...] Read more.
The COVID-19 pandemic broke out and the global logistics industry suffered severe losses; therefore, the Fuzzy FMEA-AHP (Fuzzy Failure Mode and Effects Analysis-Analytic Hierarchy Process) method is proposed to analyze the failure reasons of the logistics system in the COVID-19 pandemic. In this article, we have made an optimization on the basis of the FMEA method: the fuzzy is integrated into the FMEA algorithm, referred to as F-RPWN (fuzzy risk priority-weighted number). Meanwhile, the AHP is used to determine the weights of risk indicators. In this article, we consider new logistics failures, such as the failure modes and failure reasons of the logistics system under the COVID-19 pandemic. There are 12 failures that have been determined, and relevant preventive and corrective measures have been recommended to cut off the path of failure propagation and reduce the impact of failures. In addition, the proposed method can help logistics firms, their supply chain partners, and customers with risk management issues during the COVID-19 pandemic. Full article
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19 pages, 3393 KiB  
Article
A Multi-Regional Collaborative Optimization Model of Emergency Medical Materials for Responding to COVID-19
by Yanyan Wang and Xiaoxin Zhu
Processes 2022, 10(8), 1488; https://doi.org/10.3390/pr10081488 - 28 Jul 2022
Cited by 5 | Viewed by 1525
Abstract
Medical materials are the most important, fundamental resources necessary for emergency relief of major infectious disease disasters. The scientific and optimal allocation of emergency medical materials is the key to reducing casualties and losses in epidemic regions, and to improving the effectiveness and [...] Read more.
Medical materials are the most important, fundamental resources necessary for emergency relief of major infectious disease disasters. The scientific and optimal allocation of emergency medical materials is the key to reducing casualties and losses in epidemic regions, and to improving the effectiveness and efficiency of rescue operations. In response to the cross-border characteristics of major infectious diseases, the imbalance of material storage, and the differences of supply across regions, a multi-objective optimization model for a multi-regional collaborative allocation of emergency medical materials was developed. Then, an improved adaptive genetic algorithm (IAGA) was designed and applied to solve the proposed model. Finally, a case study of the collaborative response to the COVID-19 epidemic in the Yangtze River Delta of China was conducted for model verification. The results show that collaborative allocation can improve the material satisfaction rate at demand points, especially under peak demand pressure during the early stage of the response, and can meet all material needs at all demand points in the shortest possible amount of time. The proposed model can achieve the effective integration and mutual sharing of emergency materials across regions, and improve the efficiency of emergency material utilization and rescue efforts. The material allocation scheme considers the difference coefficients in different regions, which is conducive to enhancing the flexibility of decision-making and the practical applicability of collaborative allocation operations. A comparative analysis of the algorithms shows that the proposed IAGA is an effective method for managing large-scale multi-regional emergency material allocation optimization problems, as it has higher solving efficiency, better convergence, and stronger stability. Full article
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18 pages, 2420 KiB  
Article
Selection of Supply Chain Sustainability Management System by Fuzzy Additive Preference Programming Method
by Saruntorn Panjavongroj and Busaba Phruksaphanrat
Processes 2022, 10(6), 1189; https://doi.org/10.3390/pr10061189 - 14 Jun 2022
Cited by 3 | Viewed by 1776
Abstract
A selection of suitable sustainability management systems (SMS) is a major part of supply chain strategies to create a competitive advantage, reduce total costs, and manage long-term sustainability. A framework and method for prioritizing supply chain SMSs are presented in this research. Analytic [...] Read more.
A selection of suitable sustainability management systems (SMS) is a major part of supply chain strategies to create a competitive advantage, reduce total costs, and manage long-term sustainability. A framework and method for prioritizing supply chain SMSs are presented in this research. Analytic hierarchy process (AHP) is the most common method for alternative selection in multi-criteria decision-making (MCDM). However, complex information is mixed with ambiguity and uncertainty, which makes decision makers unable to use precise or crisp numbers, so fuzzy numbers are presented to remedy this difficulty. Therefore, this research proposes a fuzzy additive preference programming (FAPP) to select the optimum SMS for a supply chain. FAPP method can produce the unique normalized optimal priority vector of fuzzy pairwise comparison matrices for SMS selection effectively with linear constraints. The additive linear constraints can eliminate the weaknesses of existing methods and equalize the upper and lower triangular fuzzy judgments. In addition, the proposed method can identify abnormal pairs of fuzzy judgments that cause inconsistency. The proposed methodology can prioritize the key criteria which lead to the selection of the most appropriate SMS. An example of SMS selection in a rubber factory demonstrates the feasibility and validity of the proposed method. Full article
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28 pages, 5899 KiB  
Article
A Supplier Selection Model Using Alternative Ranking Process by Alternatives’ Stability Scores and the Grey Equilibrium Product
by Shervin Zakeri, Yingjie Yang and Dimitri Konstantas
Processes 2022, 10(5), 917; https://doi.org/10.3390/pr10050917 - 06 May 2022
Cited by 10 | Viewed by 1929
Abstract
Supply chain management begins with supplier evaluation and selection. The supplier selection deals with various criteria with different contexts which makes it a complex multi-criteria decision-making (MCDM) method. In this paper, a novel MCDM method, called the alternative ranking process by alternatives’ stability [...] Read more.
Supply chain management begins with supplier evaluation and selection. The supplier selection deals with various criteria with different contexts which makes it a complex multi-criteria decision-making (MCDM) method. In this paper, a novel MCDM method, called the alternative ranking process by alternatives’ stability scores (ARPASS), is proposed to solve supplier selection problems. ARPASS considers each alternative as a system that is constructed on integrated components. To perform properly, a system requires high integrity and stability. ARPASS utilizes the stability of alternatives as an effective element for ranking the alternatives. The ARPASS is developed in two forms, ARPASS and ARPASS*. The new method utilizes standard deviations and Shannon’s entropy to compute the alternatives’ stabilities. In this paper, in addition to the new MCDM methods, a new method called the grey equilibrium product (GEP) is introduced to convert grey linguistic variables into crisp values, using decision makers’ subjective perceptions and judgments. To highlight and validate the novel methods’ performance, they are applied to two sustainable supplier selection problems. For evaluation of the reliability of ARPASS and ARPASS*, their results were compared with the results of the popular MCDM methods. We compared the methods in terms of calculation time, simplicity, transparency, and information type. Full article
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20 pages, 4460 KiB  
Article
The Effects of Logistics Websites’ Technical Factors on the Optimization of Digital Marketing Strategies and Corporate Brand Name
by Damianos P. Sakas, Dimitrios P. Reklitis, Panagiotis Trivellas, Costas Vassilakis and Marina C. Terzi
Processes 2022, 10(5), 892; https://doi.org/10.3390/pr10050892 - 01 May 2022
Cited by 22 | Viewed by 3215
Abstract
In a world overwhelmed with unstructured information, logistics companies increasingly depend on their websites to acquire new customers and maintain existing ones. Following this rationale, a series of technical elements may set the ground for differentiating one logistics website from another. Nevertheless, a [...] Read more.
In a world overwhelmed with unstructured information, logistics companies increasingly depend on their websites to acquire new customers and maintain existing ones. Following this rationale, a series of technical elements may set the ground for differentiating one logistics website from another. Nevertheless, a suitable digital marketing strategy should be adopted in order to build competitive advantage. In this paper, the authors attempt to respond by implementing an innovative methodology building on web analytics and big data. The first phase of the research collects data for 180 days from 7 world-leading logistics companies. The second phase presents the statistical analysis of the gathered data, including regression, correlations, and descriptive statistics. Subsequently, Fuzzy Cognitive Mapping (FCM) was employed to illustrate the cause-and-effect links among the metrics in question. Finally, a predictive simulation model is developed to show the intercorrelation among the metrics studied as well as various optimization strategies. Research findings reveal a significant correlation between the logistics websites’ technical factors and the growth of the corporate brand name. Full article
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23 pages, 3412 KiB  
Article
Integrating Triple Bottom Line in Sustainable Chemical Supplier Selection: A Compromise Decision-Making-Based Spherical Fuzzy Approach
by Chia-Nan Wang, Chien-Chang Chou, Thanh-Tuan Dang, Hoang-Phu Nguyen and Ngoc-Ai-Thy Nguyen
Processes 2022, 10(5), 889; https://doi.org/10.3390/pr10050889 - 30 Apr 2022
Cited by 8 | Viewed by 2639
Abstract
As a consequence of increased awareness of environmental preservation and the associated rigorous regulations, the adoption of sustainable practices has become a crucial element for corporate organizations in regard to their supply chains. In the chemical industry, which is characterized by high risks, [...] Read more.
As a consequence of increased awareness of environmental preservation and the associated rigorous regulations, the adoption of sustainable practices has become a crucial element for corporate organizations in regard to their supply chains. In the chemical industry, which is characterized by high risks, high pollution, and high efficiency, these characteristics can help businesses analyze their long-term development and sustainability. The goal of this research is to analyze and choose possible suppliers based on their sustainability performance in the chemical sector. A methodology based on multi-criteria decision making (MCDM) is proposed for this evaluation, using spherical fuzzy analytical hierarchy process (SF-AHP) and combined compromise solution (CoCoSo) methods, in which the novel spherical fuzzy sets theory is employed to present the ambiguous linguistic preferences of experts. In the first stage, an evaluation criteria system is identified through literature review and experts’ opinions. The SF-AHP is used to determine the criteria weights, while the CoCoSo method is utilized to select the right sustainable supplier. A case study in the chemical industry in Vietnam is presented to demonstrate the effectiveness of the proposed approach. From the SF-AHP findings, “equipment system and technology capability”, “flexibility and reliability”, “logistics cost”, “green materials and technologies”, and “on-time delivery” were ranked as the five most important criteria. From the CoCoSo analysis, Vietnam National Chemical Group (CHE-05) was found to be the best supplier. A sensitivity study and a comparison analysis of methods were also conducted to verify the robustness of the proposed model, and the priority rankings of the best suppliers were very similar. To the best of our knowledge, this is the first study that has proposed SF-AHP and CoCoSo to prioritize SSS evaluation criteria and determine the best alternatives. The suggested method and findings can be used to make well-informed decisions that help businesses to achieve supply chain sustainability, capture opportunities, and maintain competitiveness through reconfiguring resources. The method could be useful for case studies in other countries and for other sustainability problems. Full article
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20 pages, 5287 KiB  
Article
A Sustainable Advance Payment Scheme for Deteriorating Items with Preservation Technology
by Dipa Roy, S. M. Mahmudul Hasan, Md Mamunur Rashid, Ibrahim M. Hezam, Md Al-Amin, Tutul Chandra Roy, Adel Fahad Alrasheedi and Abu Hashan Md Mashud
Processes 2022, 10(3), 546; https://doi.org/10.3390/pr10030546 - 11 Mar 2022
Cited by 5 | Viewed by 1630
Abstract
Profitably managing inventories is always a big challenge for retailers in the current context of transparent and competitive business. A general retailer always needs to handle both deteriorating and non-deteriorating products simultaneously to run a business. Deterioration of products sometimes impacts a retailer’s [...] Read more.
Profitably managing inventories is always a big challenge for retailers in the current context of transparent and competitive business. A general retailer always needs to handle both deteriorating and non-deteriorating products simultaneously to run a business. Deterioration of products sometimes impacts a retailer’s profits badly—a situation which can be alleviated by implementing proper preservation technology. In addition, to improve profits and minimize costs, a retailer always seeks some credit facilities (e.g., advance payment, trade credit facilities, etc.) from the supplier to continue the business smoothly with minimum investment. Advance payment is renowned for preventing the possibility of business orders being canceled and helping the retailer to minimize the risk of investing significant amounts at a single time. The foremost objective of this research is to analyze the facilities of advance payment and preservation technology investment and concurrent attempts to deal with shortages. This study shows that, given the presence of preservation technology, the result of case II is 68.06% higher than that of case I, whereas when preservation technology is absent, the result of case II is 71.93% higher than that of case I. The managerial insights of this analysis reveal that preservation technology attempts to prolong product life by preventing deterioration, which contributes to the retailer’s profitable business. On the other hand, in the case of an advance payment scheme, although the costs are relatively high, the study emphasizes the importance of the advance payment facility as it limits the risk of order cancellation and makes business more flexible for both supplier and retailer. The proposed model is solved by the classical optimization technique. Some theoretical derivations with numerical analysis support the model and provide some managerial insights for practitioners. Full article
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