Supply Chain Performance Evaluation Research Articles

A fuzzy cognitive mapping model for service supply chains performance

PurposeThe aim of this study is to present a model for service supply chain performance evaluation (SSCPE) based on fuzzy cognitive mapping (FCM).Design/methodology/approachDespite the unique nature of services, which distinguishes them from goods, the performance evaluation of service supply chains (SSCs) has still not received adequate attention from researchers or practitioners. With the help of in-depth interviews conducted with insurance industry experts in Iran, the performance measures of SSCs are defined, and the relevance between the performance measures, which are based upon the knowledge of experts in this field, are presented as a fuzzy cognitive map.FindingsBy blocking the aggregate map of experts, a model for SSCPE is developed that discusses performance measures and metrics of strategic, tactical and operational SSC processes, such as service-providing management, service-enabling management, market management, cash-flow management, customer-relationship management, supplier-relationship management, knowledge- and information-flow management and risk management. Indexes of FCM models indicate that the supply chain service quality and strategy blocks have the most importance compared with others.Originality/valueThe paper develops an original SSCPE model that can be used as a basis for SSC improvement and develops an excellence model for SSC.

Quantitative models for supply chain performance evaluation: A literature review

Display Omitted Review of 84 studies of quantitative models to supply chain performance evaluation.A conceptual framework is proposed to characterize the studies.AHP and DEA are the most used techniques.Pairwise comparisons and fuzzy theory are the dominant approaches to uncertainty.There are no comparative studies on benefits and drawbacks of different techniques. This paper presents a review of 84 studies published in the literature from 1995 onwards that propose quantitative models to support supply chain performance evaluation. A conceptual framework is proposed to characterize the studies according to several factors such as the purpose and scope of the model, supply chain strategy, choice of metrics, modeling uncertainty, type of model, techniques, learning capacity, type of application, data source for performance evaluation and validation approach. The reviewed papers were selected from Science Direct, Scopus, Emerald Insight and IEEE Xplore databases, as well as the Google Scholar search tool. The results show that most of the studies evaluate more than one performance dimension and are based on multicriteria decision making techniques. AHP and DEA are the most used techniques. Pairwise comparisons and the fuzzy set theory are the dominant approaches to deal with uncertainty. Most studies have reported real case applications and do not include a validation procedure. The paper also discusses some research opportunities and suggestions of further studies brought about by reviewing the current body of knowledge on quantitative models for supply chain performance evaluation.

Performance evaluation of heterogeneous bank supply chain systems from the perspective of measurement and decomposition

Bank supply chain performance evaluation problems are inherently complex given their linked internal activities. Network-DEA models using radial measures of efficiency have been used to address supply chain performance evaluation problems. However, such models applied to bank supply chains are found to have potentially three disadvantages. First, they do not consider bank supply chains’ undesirable outputs. Second, existing studies frequently omit the impact of the heterogeneity of production technologies across different bank supply chain systems. Third, Network-DEA models fail to deconstruct the latent improvement sources of performance, thus unable to support adequately decision makers’ policy targets. To address these issues, this paper proposes two alternative network-DEA models which incorporate the directional distance function (DDF) and meta-frontier methods for evaluating bank supply chain system performance. The main characteristic of the proposed models is that they take intrinsic technology-level differences between different supply chains into account. To measure the technology levels of different types of bank supply chain systems, this paper proposes a technology gap ratio (TGR) index. A case study of 16 Chinese commercial banks from 2007 to 2014 is presented to exhibit the effectiveness of the proposed network-DEA models and demonstrate the applicability of the proposed TGR index to the supply chain performance evaluation problem in the bank industry. Empirical results show that the deposit/loan efficiency of Chinese banks is still relatively low. The managerial and technological factors cause Chinese banks’ deposit/loan inefficiency. Specific suggestions are also proposed for each type of banks.

Analysis of Business Process at PT XYZ by Using SCOR Thread Diagram

Supply Chain Operations Reference (SCOR) is a standard supply chain performance evaluation model which is proposed by Supply Chain Council (SCC). SCOR makes companies can analyse and evaluate their supply chain performance. SCOR has Thread Diagram which describes business process simply and systematically to help the analysis of company’s business process. This research takes place in PT XYZ that is involved in Crude Palm Oil (CPO) industry. PT XYZ used to be the market leader of CPO industry but nowadays they have a trouble to compete with new competitors. The purpose of this study is to provide the input for PT XYZ business process improvement to enhance the competitiveness of the company with the others. The result obtained shows that there are two performance metrics that are not reached. The analysis of business process shows the lack of control role of PT XYZ to supplier and customer side which is going to be the suggestion of improvement.

Supply chain performance evaluation through AHM and Membership degree transformation

In today’s competitive business environment, evaluation of supply chain is also a principal functionality in any kind of business organization. It is due to the uncertainty within the business environment. In this paper, hybrid methodology of Attribute Hierarchy Model (AHM) and Membership Degree Transformation- M (1, 2, 3) is proposed for evaluation of supply chain performance. This planned methodology is not only useful to judge the complete performance of the supply chain but also to identify the critical criteria upon which the organizations need to concentrate to improve the performance of their supply chains.

Performance evaluation of four-stage blood supply chain with feedback variables using NDEA cross-efficiency and entropy measures under IER uncertainty

Blood supply chain management has been considered by many managers in recent years, as one of the major challenges in health systems. In order to ensure the optimal performance of the supply chain, enable continuous improvement and create competitive advantage, establishment of a performance evaluation system is essential. For this purpose, the current study proposes a Network Data Envelopment Analysis (NDEA) model for measuring efficiency of four-stage serial network of blood supply chain in presence of feedback variables by identifying comprehensive and balanced criteria as evaluation variables. Since criteria values are obtained from subjective judgment of individuals, are uncertain. Interval Evidential Reasoning (IER) approach that deals with a variety of uncertainties such as ignorance and vagueness, has been used to control the uncertainty and provide reliable evaluation. In order to rank the units a new cross-efficiency based model is presented as a remedy for the issue of non-uniqueness of optimal weights in cross efficiency. Then, Gibbs entropy is utilized to measure the uncertainty of obtained interval cross efficiency. Finally, a numerical example is provided to illustrate the proposed model.

Supply chain performance measurement using SCOR model based on interval-valued fuzzy TOPSIS

Performance measurement is known to be the best way of investigating the supply chains' success. In this regard, managers can identify the root causes of weakness points and improve supply chain's performance through analysing and solving these problems. Concerning this problem, various supply chain performance evaluation models have been presented in literature. Through all of the models, this paper used supply chain operations reference (SCOR) model for performance measurement of three Iranian automotive supply chains. First SCOR model is employed to define the performance criteria. Afterwards, technique for order of preference by similarity to ideal solution (TOPSIS) is used to determine the supply chain that performs best. In this paper, expert's judgment is used to determine the criteria's value and weight but uncertainties in expert's judgment was unavoidable, also experts cannot reach an agreement on the method of defining linguistic variables based on fuzzy sets. So, paper used interval-valued fuzzy set to solve these problems. To the best of authors' knowledge, this is the first study that have applied interval-valued fuzzy TOPSIS in group decision-making in order to evaluate and improve the performance of supply chains on the basis of SCOR model.

Research on Supply Chain Performance Evaluation of Logistics Enterprise under the Constraint of Carbon Footprint

Due to increase in customer environmental awareness, governments require enterprises to incorporating carbon footprint in the supply chain performance evaluation. For utilizing expert interviews, this paper designs a new supply chain carbon footprint index system from the perspective of economy, resources and environment. The system highlights the logistics enterprises operational status under the constraint of carbon footprint. However, in order to reduce the influence of subjective factors, this study combined the entropy method and fuzzy comprehensive evaluation to establish the performance assessment model. To verify the validity of the model and practical indexes, this paper selects a logistics enterprise for empirical research. Therefore, recommendations are given based on performance evaluation results lay the foundation for the further development of low-carbon supply chain operations.

Research and Application of Supply Chain Performance Evaluation Model from the Perspective of Logistics Service

Research and Application of Supply Chain Performance Evaluation Model from the Perspective of Logistics Service

A framework for performance evaluation of energy supply chain by a compatible Network Data Envelopment Analysis model

Inadequate supply of energy due to consumers’ increasing demand has become one of the major problems in societies. Economic growth is a key reason for the increase in the energy consumption. Although different policies can be employed for resolving this problem, optimizing the efficiency of energy suppliers can be addressed as a key policy in this regard. This paper presents an adjusted Network Data Envelopment Analysis (NDEA) model for evaluating performance of energy supply chain in Iran from production to distribution stages. Some suggestions are proposed to optimize the performance of the energy supply chain. The NDEA model is adjusted by using assurance region (AR) to achieve more real and scientific results. Borders of the assurance region obtained fromData Envelopment Analytic Hierarchy Process (DEAHP) method are entered into the NDEA model. The results obtained from this model are compared with those of conventional NDEA and technical efficiency in pairs. Finally, the Spearman and Kendall's-Tau correlation tests are used for validating the results.

Performance Evaluation of Supply Chain and Logistics Management System using Balanced Score Card for Efficiency Enhancement in Indian Automotive Industries

Objective: In universal spirited environment, automotive industries are desired to perform efficiently to meet the maximum percentage of demand by minimum cost. The objective of this article is to create a balance scorecard model for the evaluation of reliability and performance of automotive manufacturing industries to evaluate their supply and demand chain system. Method/Analysis: Using this new idea, the performance of industries should be assessed regarding their supply and demand chain system with the major four criteria like design and development, manufacturing point, financial requirement and consumer’s point of view. The main four features of the industries are policies and firm coordination, design and execution, effectiveness of shipment and information technology usagetotally covers by the new designed balanced scorecard with twenty five evaluation points. Findings: Abroad survey was carried out in Indian automotive manufacturingindustries with well structured questionnaires to collect the necessary data. Application/Improvements: The comparison between multinational, public limited, private limited and small scale organizations were carried out tomeasure the performance variation of their supply and demand chain system. Based on the correlation of above four features, a structural equation model was designed toimprove the supply and demand chain management systemfor automotive manufacturing industries and found that the α coefficient was above 0.80 hence, the balanced score card was reliable.

Performance evaluation of port supply chain based on fuzzy-matter-element analysis

Performance evaluation of port supply chain based on fuzzy-matter-element analysis

Supply Chain Performance Evaluation Model Based on Unascertained Clustering

Supply Chain Performance Evaluation Model Based on Unascertained Clustering

Impacts of decision sequences on a random yield supply chain with a service level requirement

The last decade has witnessed a rising trend of social network structures where decision making may be influenced by members’ channel power. This paper considers a decentralized supply chain that comprises a random yield supplier and a manufacturer with a service level requirement. The supplier determines the production quantity while the manufacturer decides on the replenishment quantity. We investigate several game-theoretic models with respect to decision sequences of the supplier and manufacturer with a service level requirement. We compare firms’ equilibrium production/order quantity and profits under these models. Both firms achieve a higher payoff in the manufacturer-leader game than in the supplier-leader and simultaneous move games, which indicates that the manufacturer-leader game is Pareto efficient from the channel structure perspective. A critical value is observed at the service level, beyond which the supplier’s profit decreases, while the manufacturer’s profit increases in the service level requirement. Interestingly, the critical value is independent of the models and it just depends on the wholesale price and production cost. We also examine the decentralized random yield supply chain under the vendor-managed inventory arrangement. Finally, numerical computations are conducted to evaluate supply chain performance with respect to various parameters.

Humanitarian Relief Supply Chain Performance Evaluation: A Literature Review

<p>Nowadays small, medium and severe disasters are threatening our world. One of the important role players in alleviating these traits are humanitarian relief supply chains. The increasing number of disasters in our planet earth urges the humanitarian relief supply chains to focus on the assurance of safety of the victims. In order for this to occur, these supply chains should work effectively and efficiently. This can be possible through considerable evaluation of their supply chain performance. In this paper a literature review on supply chain performance evaluation in general and humanitarian relief supply chain performance in particular is presented. Previously conducted researches from the year 2000 until the present time have been reviewed. The works were categorized according to writers, publication year, publishing journal, technique utilized and objective intended. Then an analysis was made on humanitarian relief supply chain literature with respect to the publishing journals and the research technique applied. The result shows that humanitarian relief supply chain evaluation is almost an untouched area which needs further study. Recent supply chain management techniques can be applied for the improved performance of these supply chains. Based on this result, Supply Chain Operations Reference (SCOR), Fuzzy Logic System, and Artificial Neural Networks are found to be the areas which need further study.</p>

Configuration of supply chain integration and delivery performance

Purpose – The purpose of this paper is to develop a conceptual framework of integrated supply chain model that can be used to measure, evaluate and monitor operational performance under dynamic and uncertain conditions. Design/methodology/approach – The research methodology consists of two stages: configuration of a conceptual framework of integrated supply chain model linked with performance measures and illustration of the integrated supply chain model and delivery performance using a case of dairy industry. The integrated supply chain model is based on a unitary structuring technique and forms the basis for measuring and evaluating supply chain performance. Delivery performance with variation of demand (forecast and actual) is monitored using a fuzzy-based decision support system, based on three inputs: capacity utilization (influenced by production disruption), raw materials shortage and quality of dairy products. Findings – Integration of supply chain components (materials, resources, operations, activities, suppliers, etc.) of key processes using unitary structuring approach enables information integration in real time for performance evaluation and monitoring in complex supply chain situations. In addition, real-time performance monitoring is recognized as being of great importance for supply chain management in responding to uncertainties inherent in the operational environment. Research limitations/implications – Implementation of an integrated model requires maintenance of supply chain components with all necessary data and information in a system environment such as enterprise resource planning. Practical implications – The integrated model provides decision-makers with an overall view of supply chain components and direct links that need to be maintained for supply chain performance evaluation and monitoring. Wider adaptation and diffusion of the proposed model require further validation of the model and feasibility of implementation, using real-time data and information on selected performance measures. Originality/value – Integration of supply chain components across supply chain processes directly linked with performance measures is a novel approach for effective supply chain performance evaluation and monitoring in complex supply chains under dynamic and uncertain conditions.

Fuzzy analysis and evaluation of supply chain performance: a focus on leather products in Tanzania

In this study, a fuzzy comprehensive model is applied to evaluate the performance of supply chain for leather products in Tanzania. The evaluation procedure starts by identifying major criteria and sub-criteria that influence the supply chain performance of leather products. These criteria and sub-criteria are used by assessors to assign values that are used to generate each single factor evaluation set; which is used to compose the single factor evaluation matrix. The relative importance of each criterion in the weight set is obtained by fuzzy triangular number (FTN) method. Eventually, the weight set of influential factors (i.e., criteria) is multiplied by the single factor evaluation matrix to compose the fuzzy-based comprehensive evaluation. The computational results show that the performance of the leather products supply chain (LPSC) in Tanzania is poor. Thus, the findings call for all stakeholders in the Tanzanian leather industry to take appropriate measures that would boost the supply chain performance. Moreover, the proposed model can be used to evaluate vague objectives in other industries.

Quality function deployment approach to measure supply chain performance: a case study on garments accessories industries

In the competitive markets, effective management of supply chain and realisation of customer expectations are crucial factors for the better performance of an organisation. In the modern era, performance measurement has a significant role to get the competitive advantage. Quality function deployment (QFD) methodology is the most reliable and proved method to identify customer-based strategy. The objective of this research is to determine critical customer requirements and prioritise them to determine the critical supply chain factors to improve supply chain performances. This is a case study on six-selected garments accessories industries (GAI) in Bangladesh with respect to 17 readymade garments industries and buying house as a customer. This paper shows a new system of supply chain performance evaluation using transformation matrix called quality function deployment. By this system, it is possible to measure supply chain performance of any kind of manufacturing industry. Research findings can be used for the selection of manufacturing industries supply chain strategy.

Evaluation of Supply Chain Efficiency Based on a Novel Network of Data Envelopment Analysis Model

Performance evaluation of supply chain (SC) is a vital topic in SC management and inherently complex problems with multilayered internal linkages and activities of multiple entities. Recently, various Network Data Envelopment Analysis (NDEA) models, which opened the “black box” of conventional DEA, were developed and applied to evaluate the complex SC with a multilayer network structure. However, most of them are input or output oriented models which cannot take into consideration the nonproportional changes of inputs and outputs simultaneously. This paper extends the Slack-based measure (SBM) model to a nonradial, nonoriented network model named as U-NSBM with the presence of undesirable outputs in the SC. A numerical example is presented to demonstrate the applicability of the model in quantifying the efficiency and ranking the supply chain performance. By comparing with the CCR and U-SBM models, it is shown that the proposed model has higher distinguishing ability and gives feasible solution in the presence of undesirable outputs. Meanwhile, it provides more insights for decision makers about the source of inefficiency as well as the guidance to improve the SC performance.

Assessing the efficiency of supply chain scheduling algorithms using data envelopment analysis

Where different supply chain planning algorithms are used, generally similar results may pose some challenges on the differentiating powers of evaluating different production schedules because of the increasing complexity of a supply chain network structure. For the comparison purpose, performance evaluation of different supply chain planning algorithms aims to use different supply chains models with different demands, capacities, and commonality through efficiency perspective by using a modified network rational data envelopment analysis (DEA) model. The proposed DEA model has the abilities: (1) to treat only undesirable outputs that exist without normal output, and the situation where input and output are both zero by introducing two new parameters to denote the maximum inventory and amount of delayed demands of a given node in a given time period; and (2) to evaluate the effect of the undesirable outputs/inputs on efficiency with assumption that they leave the system at the end of the current time period and re-enter the system at the beginning of the next time period. To prove the effectiveness of this DEA model, eighteen scenarios with different demands, capacities, and multiple periods are compared. In addition, this study tests the DEA model on a wafer testing/probing operation of a leading global semiconductor manufacturing and testing company in Taiwan by internal supply chain perspective. Results show that the DEA model proposed in this study can be used to assess the efficiency of a real-world operation with undesirable outputs/inputs, such as inventory and delayed demands.