Supply Chain Performance Evaluation Research Articles

Supply chain performance evaluation using a network data envelopment analysis model with bias-corrected estimates

Supply chain performance evaluation using a network data envelopment analysis model with bias-corrected estimates

Screening of sustainable supply chain performance evaluation indicators based on the ill-conditioned index cycle method.

The establishment of an evaluation indicator system that can accurately assess the sustainability of a supply chain while further enhancing its performance is vital and relevant. Based on the connotation of sustainable supply chains and triple bottom line theory, indicators are initially proposed from economic, environmental, and social dimensions. To increase the explanatory power of the indicator system and decrease information redundancy, the coefficient of variation is applied to identify the indicators with weak interpretation intensity, the ill-conditioned index cycle method is utilized to filter out indicators with redundant information, and data on 100 Chinese listed companies from 2019 to 2021 are used as samples. A performance evaluation indicator system of sustainable supply chains with 16 indicators is ultimately established. The information interpretation strength index and cumulative information contribution rate verify the rationality of the final indicator system. The outcome demonstrates that this screening method can strengthen the representativeness of the indicator system and rapidly reduce redundancy, leading to the better discrimination of the evaluation results. The findings of this study provide an indicator system and a methodological reference for both companies and policymakers and can aid in the transformation of supply chains toward sustainability.

Performance Evaluation of Intelligent Agricultural Supply Chain Based on Structural Equation Model

To solve the problems of unstable chain and poor supply chain (SC) function in the China’s agriculture industry, the relevant study is carried out on the function evaluation of the sustainable agricultural SC by structural equation modelling (SEM) under the background of digital technology. Primarily, the analysis is implemented on the research status of the sustainable SC and SC function. Then, starting with the relationship among big data (BD) application, information sharing, and sustainable SC function of agricultural production, a function evaluation model is implemented for the sustainable SC of SEM-based agricultural production. Next, a questionnaire is designed for the research on the impact of BD applications on the function of the sustainable agricultural SC. Ultimately, the statistical analysis of the obtained data reveals the correlation between the interaction and influence among the BD application, information sharing, and sustainable SC function of agricultural production. The results show that the BD application dimension, information sharing dimension, and all sub-dimensions have is beneficial to the function of the agricultural sustainable SC. The application of multidimensional cloud technology in BD has no obvious relationship with the dimensionality and level of information sharing, and the relationship between other corresponding dimensions shows a significant positive impact. A referenceable method is provided for the practice of sustainable SC management of agricultural production.

Using DEMATEL, clustering, and fuzzy logic for supply chain evaluation of electric vehicles: A SCOR model

<abstract> <p>The transportation sector is considered among the major sources of greenhouse gas emissions. Given advancements in transportation technology, customers' willingness to reduce carbon footprints, as well as policy incentives, Electric Vehicles (EVs) are becoming an increasingly important part of the passenger vehicle industry. Evaluation of Supply Chain (SC) performance in the EV industry seems to contribute significantly to the enhancement of the operational consequences across the supply chain tiers. The SCOR (Supply Chain Operations Reference) model was designed to help businesses optimize their supply chain operations, reduce costs, and improve customer satisfaction. Although many performance measurement models have been developed in the context of SC, there is no performance measurement model in relation to the EV supply chain based on indicators of customer perceived value (Reliability, Responsiveness and Agility) in the SCOR model. Therefore, we aimed to develop a new method to evaluate the performance of the EV supply chain using a set of critical SC performance evaluation indicators. Multi-criteria decision-making along with machine learning was used in order to develop a new method for evaluating SC performance. We used k-means clustering and fuzzy logic approaches in the development of the new method. An assessment of indicators' importance level was performed using the fuzzy logic approach. The results of the method evaluation show that the proposed method is capable of predicting the performance of the EV supply chain accurately. According to the results, by optimizing their supply chain, companies can improve their ability to deliver products and services that meet or exceed customer expectations, resulting in higher customer perceived value and customer satisfaction.</p> </abstract>

Research on the Management Model and Performance Evaluation of Guangxi ASEAN Cross border Agricultural Product Supply Chain

With the proposal of the "Belt and Road Initiative", China's cross-border trade has been further developed. In order to comply with the development trend of "double cycle", the trade of agricultural products can make full use of "two resources and two markets" both at home and abroad. However, the supply chain of cross-border trade of agricultural products involves many links and has a wide range of chain coverage, showing relatively complex characteristics. In order to realize the sustainable development of cross-border agricultural products trade, an empirical study on the management model and performance evaluation of Guangxi-ASEAN cross-border agricultural products supply chain was carried out. On the basis of defining the concept of Guangxi-ASEAN cross-border agricultural product supply chain, this study first analyzed the management mode of Guangxi-ASEAN cross-border agricultural product supply chain, designed the performance evaluation model of Guangxi-ASEAN cross-border agricultural product supply chain according to the importance of cross-border logistics and demand of agricultural products, and then set evaluation indicators on the basis of target level and criterion level through the selection rules of evaluation indicators. Principal component analysis was used to evaluate the scores of each index, so as to obtain the evaluation level of Guangxi-ASEAN cross-border agricultural supply chain performance, and complete the empirical analysis of performance evaluation. The empirical analysis results are as follows: The logistics system of Guangxi-ASEAN cross-border trade is gradually improved, the delivery timeliness and accuracy of cross-border trade are constantly increasing, the quality of cross-border agricultural products is gradually enhanced, and the information exchange of cross-border trade is becoming more transparent. This improves the satisfaction of consumers, increases the profits of enterprises, reduces the customs clearance time and finished products of agricultural trade, and strengthens the close trade cooperation between Guangxi and ASEAN countries.

Evaluation of Sustainability Supply Chain Performance in the Food Industry: A Case Study

Evaluating sustainability in the food supply chain has multiple benefits, including reducing environmental impact, meeting regulations, satisfying consumer demands, improving efficiency, and enhancing business reputation. This paper outlines a Sustainability Supply Chain Management (SSCM) framework using the Analytic Hierarchy Process (AHP) to weigh Key Performance Indicators (KPIs). With 12 variables and 39 KPIs, the method involves data collection, performance measure selection, and analysis. KPIs with lower weight values highlight areas needing improvement, such as recycling costs, personnel expenses, sales responsiveness, eco-friendly labelling, distribution efficiency, green product development, recycled material usage, employee capabilities, product reputation, worker satisfaction, and stakeholder trust. Based on KPI weights, recommendations include prioritizing energy use in production and marketing, ensuring timely product delivery, maintaining product quality, streamlining production processes, focusing on energy efficiency, promoting eco-labelling, fostering eco-awareness, and advancing environmental technology.

Enhancement the Performance of Multi-Level and Multi-Commodity in Supply Chain: A Simulation Approach

In today's global economy, effective supply chain management plays a pivotal role in the success of a business. The repercussions of a business strategy on the entire supply chain remain uncertain until it is implemented. Utilizing simulations offers the opportunity to gauge performance before implementing the strategy. The primary aim of employing supply chain simulation is to analyze the effects of different strategies on profit enhancement and cost reduction across all supply chain tiers. This research paper has formulated a discrete event simulation model using Arena software to evaluate and enhance the operational efficiency of the detergent supply chain. The problem involves multiple levels and commodities, encompassing four manufacturers, two intermediate storage warehouses, and four main distributors following an (s, S) inventory control approach. Shortages are permitted, leading to a partial loss or back-ordering of products. The overarching objective is to minimize the overall inventory costs within the system, accounting for holding costs at each tier, managing shortages, and the expense incurred due to lost sales. A range of scenarios are developed to set control parameters, with the evaluation of supply chain performance falling into two main categories: financial and operational considerations.

Statistical Analysis of Export Waybill Data of Cross-Border E-Commerce Based on ISM Model

Abstract This paper uses the expository structural model (ISM) as the basis for research. Firstly, it briefly analyzes the business structure of our cross-border e-commerce and foreign trade business. The specific organizational structure of the enterprise will encounter a variety of interference. This paper constructs a set of enterprise supply chain performance evaluation indexes based on balanced scoring. The writing improves the information level, logistics ability, customer status maintenance, and other vital links. Simulation results show that this method can improve the overall performance of foreign trade documents.

Investigating the relationship between supply chain finance and supply chain collaborative factors

PurposeIt is important to understand the factors that are significant in supply chain (SC) collaboration decision making and whether supply chain collaborative factors that are considered in the literature are still valid. To date, SC collaboration has not been extensively studied in the literature with supply chain finance (SCF) factors to evaluate SCF performance. Therefore, in this paper, the authors investigate the interrelationships between SCF and supply chain collaborative (SCC) factors for achieving SCF performance. The authors identified the most important factors from the literature on SCF and SCC and with inputs from experts in the textile industry in Pakistan.Design/methodology/approachThe authors employed the Gray-Decision Making Trial and Evaluation Laboratory approach to help examine the cause-and-effect relationship between the factors and identify the influence of each factor on the others.FindingsThe findings showed that the most prominent factors of the study are “level of digitalization”, “information sharing”, and “collaborative communication”, and “most effect factors of this study are incentive alignment” and “information quality”. Furthermore, the “Level of digitalization” was identified as the factor with the central role and most significant correlation with other factors.Research limitations/implicationsThe major implication of the study is that textile industries should effectively develop their supply chain decisions after analyzing their internal and external factors, which will help in developing strategies that will facilitate better management of SCF relationships. The limitations of the study are that only 15 SCF and supply chain collaborative factors were considered, and time and scope are also limited. This study is only applied in the textile industry, so generalization may be limited.Originality/valueTo date, this study is the only one that has taken into consideration SCC with SCF factors to evaluate supply chain performance. This paper therefore makes this initial attempt and original contribution to this discussion, which can be helpful for those working to enhance supply chain performance, such as practitioners and policymakers.

A new fuzzy DEA network based on possibility and necessity measures for agile supply chain performance evaluation: A case study

With respect to the necessity (Nec) measure, suggesting by Dubois and Prade, there is a dearth of any procedure or formula to deal with equality chance constraints. Therefore, this study attempted to introduce (Nec) and possibility (Pos) equality constraints in a real-case network non-oriented slack based model problem via agile supply chain (ASC) theory. The efficiency of different levels of agility of a dairy supply chain (SC), using a new fuzzy network Date Envelopment Analysis slack based model (FNDEA-SBM) on the basis of (Pos)/(Nec) measures, has been measured in this paper. The measurement took place in a multi-stage process. Since the agility features were rather qualitative in nature, the measures were likely to be delineated subjectively using linguistic expressions and fuzzy data. The application of (Pos)/(Nec) measures and different confidence levels made decision makers capable of getting information of all efficiency and sub efficiency scores through optimistic-pessimistic lenses and taking appropriate decisions on the basis of different optimistic-pessimistic points of view and confidence levels. The validity of the suggested approach was demonstrated through a real-life case study related to Iranian top twenty dairy firms. The results indicated the success of the suggested approach and computations were straightforward.

Identifying Critical Indicators in Performance Evaluation of Green Supply Chains Using Hybrid Multiple-Criteria Decision-Making

Performance evaluation of green supply chains (GSC) is an important tool to improve their comprehensive management. Identifying critical indicators is crucial to evaluation. This study examines the critical indicators in performance evaluations of GPC and provides relevant suggestions for managers to improve GSCs’ performances. Firstly, we summarized 24 evaluation indicators from five dimensions—financial value, customer service-level, business processes, innovation and development, and the so-called green level. Secondly, the Delphi method was used to determine the formal research framework. The fuzzy decision-making trial and evaluation laboratory based analytic network process (fuzzy DEMATEL-based ANP) model was applied. The weighted prominence of each indicator was calculated to identify those that were critical, and a causality diagram was constructed for them. Finally, corresponding countermeasures and implications regarding those were put forward. The research results show that the critical indicators include the return rate of net assets, the growth rate of profit, the rate of service satisfaction, market share, production flexibility, and the green consensus. Among them, the green consensus, the growth rate of profit and the rate of service satisfaction form a virtuous circle, leading to the improvement of the overall performance of GSC.

Evaluation of sustainable supply chain performance on apple chips using the integration of quality function deployment, fuzzy analytical network process, and data envelopment analysis

Batu City is the largest apple producer in Indonesia, producing around 55,891 tons. One way to optimize supply chains is sustainable supply chain performance in the economic, social, and environmental fields. Problems in apple chip small- and medium-scale enterprises (SMEs) are the price of apples increases in the dry season, accumulation of apple peel waste, and poor employee work performance. This study aimed to analyze the level of importance variables in measuring the supply chain performance level and the strategies to improve the supply chain of apple chips SMEs in Batu City. The integration of quality function deployment (QFD) and Fuzzy analytical network process (FANP) was used to obtain the level of cooperation interest. Data envelopment analysis (DEA) was used to determine the efficiency of each stakeholder's interest. The results showed that the three highest important cooperative behavior factors were production costs (0.16), raw material costs (0.15), and raw material inventory (0.14). The efficiency level of partner cooperation and apple chip SMEs from 17 SMEs indicated that two partners were inefficient, with an efficiency score of 0.973 (D3) and 0.957 (D4). The improvement strategies proposed to apple chip SMEs were reducing production costs, revising agreements between suppliers and farmers, and implementing information technology.

Green Supply Chain Performance of Prefabricated Construction from the Perspective of Collaborative Innovation

In order to implement the new development concept and improve the performance evaluation system of green supply chain of prefabricated Constructions in my country, a performance evaluation of green supply chain of prefabricated Constructions from the perspective of collaborative innovation is proposed. First, draw lessons from the balanced scorecard theory and apply it to construct a performance evaluation index system for the green supply chain of prefabricated Constructions based on the balanced scorecard. Meta-extension model. Then, the performance evaluation grade is determined by the asymmetric closeness of the matter element to be evaluated about the evaluation grade of each index and the characteristic value of the grade index. Finally, the established evaluation model is applied to a green supply chain of a prefabricated Construction, and the results prove the validity of the model.

Підвищення ефективності ланцюгів поставок

The article defines the important role of enterprise management as a tool of strategic development, while it should be noted that in order to achieve the set goals, it is necessary to use specialized methods and models - effective engineering, effective optimization, and effective reengineering of the enterprise's logistics systems. The goal is to study in depth the theoretical and practical foundations of the application of analytical methods and models in logistics to solve the problems of logistics management, to systematize the skills of developing and using analytical systems in various areas of application of logistics activities. The views of various scientists on the meaning of the concept of "Effectiveness of the supply chain" are considered. The main directions and elements that make up the concept of supply chain efficiency have been studied. Let us note the main areas of effectiveness of SCM implementation: increasing the number of orders, increasing the stability of demand, reducing insurance reserves, reducing risk and increasing the reliability of planning and delivery. According to the basic supply chain process, it is recommended to consider the main indicators of supply chain performance evaluation in the SCOR model: planning, procurement, production, sales and returns. For each set of indicators, growth and decline indicators are highlighted separately. A general index of supply chain performance evaluation is proposed. The direction of increasing the efficiency of the supply chain is proposed: increasing the visibility of the supply chain; certification training; investments in smart technologies; development of project plans.

Impact of Ordering Decisions on Performance of a Supply Chain – An Experimental and Simulation Study

A supply chain consists of a network of organizations. Each organization in it acts as either customer or supplier to others. Ordering and replenishment decisions of each organization or stage contribute to supply chain performance. A simulation study and experimentation were conducted in this study to determine the impact of ordering decisions on supply chain performance. The ordering decisions at each stage are taken by intuition for experimentation and are taken by inventory policies for simulation. Under customer demand distribution information sharing, the performance of a supply chain is evaluated and compared between those two conditions. A supply chain role play game software package is used to evaluate supply chain performance by intuition, and simulation is used to evaluate different inventory policies. Fixed order policy, Order Up-to Level (OUL), Modified OUL (MOUL), (r, Q) and (r, S) inventory policies are considered in this study. The performance measures used are the total supply chain inventory per period, bullwhip effect and supply chain fill rate. Grey Relational Analysis (GRA) is used to identify the best method to take decisions in supply chain. Results show that supply chain performance is best under MOUL policy. Based on the results of this study, supply chain members are encouraged to identify the best inventory policy and use that rather than making decisions based on intuition.

Optimization Approaches for Multiple Conflicting Objectives in Sustainable Green Supply Chain Management

Over the years, the global supply chain has evolved into a more extensive interconnected complex network with multiple suppliers, manufacturers, and customers. Since environmental issues have become a burning question in recent years, the focus has shifted to attaining sustainability in supply chain management. The green supply chain or sustainable network is a concept to reduce environmental impacts in the life cycle of a product. However, green supply chain management is often challenged with additional operating costs and difficulty monitoring the implications within the complex network system. Additionally, many stakeholders are unaware of the importance of sustainability analysis, which eventually complicates adopting green cultures in actual applications. Since green supply chain management deals with multiple aspects, such as cost and carbon emission, the multiobjective optimization method is widely used to evaluate supply chain performance. This paper intensively reviews the state-of-the-art literature on applying multiobjective optimization techniques in green supply chain management. The study highlights aspects of green supply chain structures, model formulation techniques considering multiple objectives simultaneously, and solution methods for multiobjective optimization problems. Finally, a conclusion is drawn with the scope of the potential research opportunities for integrating economic and environmental considerations in sustainable supply chain management practice.

Exploring the Application and Optimization Strategy of the LMBP Algorithm in Supply Chain Performance Evaluation.

In recent years, with the emergence of new technologies, big data, artificial intelligence, and other technologies have had a greater impact on supply chain management. Among them, big data analysis capability, as one of the important capabilities that supply chain enterprises should have, has a particularly significant impact on supply chain resilience management. From the perspective of performance management, based on supply chain resilience theory, the relationship between the supply chain performance management level, supply chain collaboration, and other supply chain resilience elements, as well as big data analysis capability and supply chain performance can be analyzed to study the impact of big data analysis capability on supply chain performance of enterprises of different scales. The impact on the level of supply chain performance is being studied. This paper investigates the problem of supply chain performance evaluation and optimization based on the LMBP algorithm and provides some references for supply chain performance evaluation and optimization.

A Comprehensive Performance Evaluation of Chinese Energy Supply Chain under “Double-Carbon” Goals Based on AHP and Three-Stage DEA

In 2020, China put forward the goals of “peak carbon dioxide emissions” and “carbon neutrality” (“double-carbon”) and it is urgent for the energy industry to achieve green transformation. Aiming at the rigid requirements of the carbon-peaking and carbon-neutrality goals (“double-carbon”), this study established a performance evaluation index system for an energy supply chain of a four-tier structure based on the “double-carbon” goals, calculating its weight by the analytic hierarchy process (AHP). On this basis, a three-stage data envelopment analysis (DEA) evaluation model was established to evaluate the performance of the energy supply chain in 2010–2019. According to the three-stage DEA evaluation mode, the initial input–output efficiency value of the energy supply chain was calculated by the DEA-BCC (extended by Banker, Charnes and Cooper) model and DEA-CCR (proposed by Charnes, Cooper and Rhodes) model and the influence of environmental noise was eliminated by stochastic frontier analysis (SFA) regression; we then obtained the adjusted efficiency value for the energy supply chain. At the same time, taking 2015 as the dividing point, the advantages and disadvantages between the traditional energy supply chain and new energy supply chain were analyzed and summarized. Further analysis and suggestions are provided to consumers, enterprises and countries from four aspects: energy supply, energy production and processing, energy transmission and distribution and energy consumption.

Resource reallocation for improving sustainable supply chain performance: An inverse data envelopment analysis

In recent years, globalization has highlighted the vital role of sustainable supply chains (SSCs) in the development of organizations and production systems to increase profits. The high-performing SSCs not only increase the organizations’ profit but also guarantee responsiveness and sustainability in the networks. Thus, SSC performance evaluation is of cardinal importance in managing the entire network. Due to the importance of supply chain management, various versions of data envelopment analysis models have been introduced in the literature to evaluate supply chain performance. The inverse data envelopment analysis (IDEA) models have been employed to analyze the sensitivity of parameters and assess the risk of a system to changes in inputs and outputs. The IDEA model measures the impact of these changes on the remaining inputs and outputs by applying changes to one or more inputs or outputs, provided that the efficiency remains constant or improves. In this study, we develop a network IDEA model to evaluate SSCs performance considering the nature of network systems. This model considers different stages of an SSC network based on the importance and priority of each stage over the others. Then, a two-phase method is introduced to solve the proposed model to estimate the inputs and outputs while efficiency improves or remains unchanged. An important feature of the proposed model is to consider the relationships between the internal stages in the IDEA model. Furthermore, the proposed model guarantees the integer values for all parameters. The applicability of the IDEA model is demonstrated using a real case study.

SUPPLY CHAIN PERFORMANCE EVALUATION MODELS: A LITERATURE REVIEW

Our structured literature review reveals the current state-of-the-art supply chain performance evaluation models (SCPEMs) from the last 21 years of research. Seventy related papers from the 2000 to 2021 time period were found to contribute by using ISI and SCOPUS databases. This paper has classified SCPEMs in terms of focus area and the perspective considered (financial and non-financial). With the analysis, these models’ applicability in today’s business environment pinpointed the most usable models and their current shortcomings. Findings disclose current SCPEMs limitations and misalignments with the emerging disruptive technologies observed in today’s supply chains. Given the findings, this study has highlighted the lack of overall supply chain performance evaluation and the failure to underline the underperforming decision criteria in the SC network. Therefore, to tackle these gaps, the authors have suggested visibility, leagility, collaboration, digitalization, sustainability, and integration as SCM characteristics to be considered in the future when developing a novel SCPEM. Finally, this study can be used as guidance for future studies.