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

The consideration of ecological and social impacts of supply chains is becoming a pressing issue and a competitive advantage for companies. Therefore, sustainability-related aspects have to be identified and integrated into supply chain management to allow for sustainable performance measurement. However, the widely recognized Supply Chain Operations Reference (SCOR) model and its extensional Green SCOR model do not comprehensively address the triple bottom line (TBL) of sustainability, i.e., the interplay of the economic, environmental, and social dimensions, especially because social aspects are neglected so far. Furthermore, the ecological metrics are mainly output oriented, thereby omitting input factors that are crucial to environmental performance. Against this background, this chapter (1) elaborates on literature concerned with the integration of the TBL of sustainability into supply chain management processes and (2) develops a conceptual framework to match sustainability metrics to the SCOR processes. On the one hand, the resulting conceptualization contributes to closing the current research gap on the integration of sustainability metrics into supply chain process models, and on the other hand, it alleviates practice application through compatibility with the standardized SCOR model. It is found that environmental metrics can be directly related to existing SCOR process elements, while social metrics are more difficult to integrate. Nevertheless, the research presented should subsequently be subject to empirical validation and formal mathematical modeling to shed light on holistic sustainability performance measurement of supply chains.

Supply Chain Management aims to overcome the challenges to integrate the Supply Chain Entities with a shared vision and evolving gradually as a legion in the business ecosystem and supply network. With the integrated inter-company activities, these entities can work as united one to respond quickly to market, to source in a multinational setting, to control available products/services to deliver to the customers, and to maximumally achieve financial benefits as a group. The Supply Chain Operations Reference (SCOR) Model, which has been developed by academics and practitioners and hosted by the APCIS Supply Chain Council is a major framework to serve for Supply Chain integration as a referential guide. Its content includes supply chain management practices, business process elements and enablers in a multi-company context that business owners and supply chain consultants can adjust their supply chain activities and organizations following the referential guideline. Despite SCOR model has many merits, it does not clearly state how to identify the existing problems and how those problems can be resolved in a supply chain project. Based on the speaker's industrial experience, this tutorial will provide a mapping technique for gap identifying, prioritization of problem solutions, and business process modifications in a supply chain setting based on SCOR model. The tutorial can enhance participants' knowledge to facilitate the implementation processes of multinational supply chain projects by identifying the gaps and integrate the channel entities.

The importance of performance management in supply chains has long been recognized from a variety of functional disciplines. But much of the work has focused on designing performance measures with less concern for the other stages of the entire performance management process. The supply chain operations reference (SCOR) model, developed by the Supply-Chain Council (SCC), is widely accepted as the only cross-industry standard for supply chain management, which not only provides a standard description of supply chain processes, but standard metrics to measure supply chain performance. Based on the SCOR model, a comprehensive framework for supply chain performance management is presented in this paper, which includes all aspects of performance management from performance measurement to performance improvement. The methods for performance model design and performance analysis are mainly discussed

Sector Logistics plays an important role in maintaining the smoothness and efficiency of national and global supply chains, especially for third-party logistics ( 3PL ) service providers who face demands for reliability and speed of service amidst global competition. The complexity of the logistics process creates the need for a structured and measurable performance evaluation model. This study aims to apply the Supply Chain Operations Reference ( SCOR ) model in identifying and prioritizing key performance indicators ( KPI ) in a 3PL company . The method used involves distributing questionnaires to decision makers in operational and managerial fields. The weights of SCOR performance attributes including reliability, responsiveness, flexibility, cost measures, and asset management efficiency are calculated using the Fuzzy Analytic Hierarchy Process ( FAHP ) method. Furthermore, the Technique for Order Preference by Similarity to Ideal Solution ( TOPSIS ) is used to determine KPI priorities at PT.X. The results of the study show that there are 17 indicators to measure the performance of the freight forwarding sector with the largest weight being operator reliability (0.251) on the reliability attribute, the number of on-time deliveries (0.694) on the responsiveness attribute, load flexibility (0.317) on the flexibility attribute, shipping costs per km (0.379) on the cost attribute and cash-to-cash cycle time (0.479) on the asset management attribute. The SCOR model has proven effective as an initial framework in measuring the performance of 3PL logistics service providers, because it is able to integrate various aspects of performance systematically and quantitatively.

This study aims to highlight the usefulness of studying the performance of supply chains (SC) at the sectoral level in greater detail through the combination of a disaggregated supply chain operations reference (SCOR) model, with a multicriteria decision-making approach, specifically using an AHP, to adjust the analysis to the particularities of the sector under study by stakeholders’ judgements. The methodology was applied to the Ecuadorian flower industry, and the data for the analysis was from a survey of a group of companies that represent this sector. In addition, a focus group of SC experts weighted the model constructs as part of the analytic hierarchy process (AHP), and then the performance level for each construct was determined. According to the results methodologies, this model allows the classification of companies by their performance, as well as the performance of the aggregate sector. The processes that Ecuadorian flower companies need to improve on are planning, procurement, and manufacturing. The study’s main contribution is developing a general framework for measuring the overall performance of SCs and how the results are obtained. This tool could help managers, consultants, industries, and governments to assess the performance of SCs, as well as improving SC management in order to increase the sector’s competitiveness in the international market.

With the growing environmental concerns, green supply chain management (GSCM) is gaining significant attention in the construction industry. Tracking and monitoring the environmental effects brought forth by the participating members along a supply chain is important to GSCM. The GreenSCOR model developed by the Supply Chain Council provides a generic framework for measuring the total carbon footprint and environmental footprint in a supply chain. The model is based on the Supply Chain Operations Reference (SCOR) model, which represents a supply chain network in a hierarchically structured manner. This paper describes the GreenSCOR framework and its potential application to the construction industry. This paper also presents a web services approach to incorporate the GreenSCOR model to the implementation of collaborative information systems. Each process element in the SCOR model is represented and delivered as individual web service units, which can be reused and integrated using standard web services technologies. The service units are combined and managed in a prototype web service collaborative framework, called SC Collaborator, which is designed and developed for supporting construction supply chain management. An illustrative example is presented to demonstrate the implementation of the GreenSCOR-based SC Collaborator framework.

Proper supply chain management (SCM) provides material control on product information and financial flows. A model used in many industrial sectors that allows to manage the supply chain and evaluate its redesign, is the SCOR (Supply Chain Operations Reference). This research proposes a framework that integrates the SCOR model in the Enterprise resource planning (ERP) system, for a Supply Chain based on RFID (Radio Frequency Identification). The methodology is presented through a case study on the new distribution of Italian postal stamps on the Italian. Through the AS-IS situation we explain the operation of the supply chain in each unit and define the information that could be collected through RFID. The RFID-enabled supply chain based on the SCOR framework involves shorter delivery times and greater product traceability, as accurate real-time information has been shared between partners. Each process of the SCOR model is analyzed and customized with respect to the RFID application, with a deep analysis of the improvements that can be achieved thanks to this technology. The SCOR model also involves a selection of performance measurement indicators used to monitor and manage the supply chain. The adoption of the RFID-based SCOR model, together with the definition of standardized Key Performance Indicators (KPIs), enabled rapid implementation of ERP software. The case study also produced some best practices such as stamp tracking and a specific warehouse layout configuration that resulted in better performance in operations management.

When a company's supply chain has achieved a desirable degree of eco-friendliness in all regards, from a sustainability perspective, its performance will be satisfactory. Since the closed-loop e-waste supply chain's operations are primarily focused on achieving sustainability objectives related to the manufacturing, distribution, reusing, and discarding electrical components, it is crucial to evaluate its success in this area. In order to monitor the performance of supply chains and enhance the processes, the supply chain operations reference model offers suggestions and benchmarking tools. In this study, a conceptual framework is illustrated to show how these standards could be used in the E-waste supply chain to link business processes, metrics, industry standards, and technology in order to enhance the relationship and coordination between the supply chain members and to increase sustainability throughout the supply chain. Insufficient attention so far has been paid to the SCOR model's sustainability criteria, according to an assessment of the literature. Consequently, in the wake of portraying the structure of Supply Chain Operation Reference model, we make sense of which credits should be included in Supply Chain Operation Reference so to reflect manageability and which cycles and practices are related with every standard or should be remembered for Supply Chain Operation Reference to lay out the connection between execution, cycles, and practices.

Supply chain performance measurement and improvement is required to control the performance and define a strategy to improve agroindustry’s competitiveness. The objectives of the research were to identify supply chain configuration and mechanism, and to analyze the supply chain performance and define the supply chain performance improvement for palm oil agroindustry. The research was conducted at Riau Province and Jambi Province as the central palm oil production in Indonesia. The Supply Chain Operation Reference (SCOR) and Analytical Hierarchy Process (AHP) were applied to analyze the supply chain performance and the performance improvement strategies were formulated descriptively with expert discussion. The results showed that the average performance of farmers, traders and refinery at Riau Province were 77.77%, 74.60% and 79.20%. The average performance of farmers, traders and refinery at Riau Province were 72.66%, 75.39% and 83.11%. This research had succeeded to define the strategies to improve palm oil supply chains at Riau Province and Jambi Province. The strategies were focused on good agricultural and good handling practice, specifying the palm oil prices refractions based on quality and implementing the information system to improve the supply chain performance.

The management of a supply chain is both an offensive and defensive weapon that organisations can use to increase their competitive edge and capture a larger share of the market. In management science and supply chain management, multi-criteria decision making techniques have been used to solve a range of real-world problems. The problem is that many, if not most, companies in South Africa either do not have the required skills to use these decision-making techniques to improve or re-configure their supply chain, or they do not have a complete data set with which to model it effectively. In order to manage supply chains effectively, organisations at the very least need feedback on the performance of their entire supply chain. In this article, generic supply chain performance measures were used and a theoretical or empirical model was developed for the performance measurement of a national egg producer’s supply chain. It focused on a managerial program for the identification and management of their supply chain with recommendations for applying a measurement model. The overall performance of the supply chain as well as the five different performance attributes was presented to management in a dashboard format. This article could be used as a basis for future studies of supply chain performance measurement and the model could be used as a foundation for developing an improved version, not only for the egg industry, but for other industries as well.

The supply chain system is an important factor in the commodity process or an effective and efficient logistics system. In the field of the fishing industry, the supply chain system greatly influences the process of activity flow starting from fish availability, productivity, fish quality assurance to distribution to consumers. Effective and efficient supply chain system management will have a huge impact on the commodities of the national fishing industry. Therefore, the purpose of this study is to measure the performance of the supply chain management system based on the level of maturity so that it can be a benchmark as an improvement in the future. The approach method used in this study is to use the concept of the Supply Chain Operation Reference (SCOR) model which is collaborated with key performance indicators (KPI) and analytical hierarchy processes (AHP) to produce the maturity value of supply chain performance. This research uses a descriptive method by making observations, distributing instruments in the form of questionnaires, interviews and literature studies in its preparation. The results of the study obtained a level of supply chain performance in PPSNZJ obtained a final value of 84.38 by entering the Good performance category based on the SCOR method and the supply chain maturity level obtained a maturity level of 4.3 on a scale of 0-5 withmanaged and measurable conditions. Efforts to measure supply chain performance are carried out to realize the improvement of supply chain performance in the national fishing industry which is integrated with suppliers, fishermen, companies, stakeholders and consumers

The advent of information and communication technologies (ICT) ushers a cost-effective prospect to take care of large volumes of complex data, commonly known as “big data” in the supply chain operational environment. Big data is being generated today by web applications, social media, intelligent machines, sensors, mobile phones, and other smart handheld devices. Big data is characterized in terms of the velocity, volume, and variety with which it produces along the supply chain. This is due to recent advances in telecommunication networks along with centralized and decentralized data storage systems, which are processed thanks to modern digital computational capabilities. There is a growing interest in the use of this large volume of data and advanced analytics for diverse types of business problems in supply chain management (SCM). Such decision-support software applications employ pure mathematical techniques, artificial intelligence techniques, and sometimes uses both techniques to perform analytical operations that undercover relationships and patterns within supply chain generated big data. This chapter proposes a framework for the utilization of big data in SCM decision making. The framework is based on the SCOR (supply chain operations reference) model, which is endorsed by Supply Chain Council (SCC). The proposed framework is influenced by the enterprise potential of augmented reality and virtual reality in supply chain applications, and it identifies key categories of big data analytics applications for the key businesses of SCOR model. Finally, the chapter highlights research issues to extract insight from big data sources for enterprise decision making.

PurposeThe purpose of this paper is to propose an integrated supply chain performance measurement framework for the case of small and medium scale enterprises (SMEs) using set of qualitative and quantitative insights gained during the case study research.Design/methodology/approachThis paper develops the supply chain performance measurement framework using the facts revealed through case study analysis, secondary data specific to various SME clusters in India and detailed contemporary studies reported on supply chain management in SMEs. It integrates the salient features of balanced scorecard (BSC) and supply chain operation reference (SCOR) model to deliver a comprehensive performance measurement framework for SMEs.FindingsThis paper reports set of performance indicators for the supply chain processes like “source,” “make,” and “deliver” in SMEs. It also relates the measures with various supply chain cycles like “procurement,” “manufacturing,” “replenishment,” and “customer order.” As a result, paper delivers an integrated performance measurement framework for supply chain evaluation and planning in SMEs. It also outlines the detailed guideline for the implementation and use of the framework.Practical implicationsThis paper is expected that the developed framework: will help SME managers to improve the visibility of their supply chain amongst interacting partners; and will help SME firms to explain the basis of their decisions to the other supply chain partners and specifically, origingal equipment manufacturer organizations where less bargaining power exist.Originality/valueThis paper integrates the spirit of two well‐known contributions in the field of performance measurement namely BSC and SCOR. The proposed framework is deduced using the findings of real life case study research and hence establishes an adequate platform for its application. It would help the managers or decision makers in SMEs to gain a systematic insight into their supply chain problems and hence undertake the necessary improvements.

Abstract. This study aims to analyze the Supply Chain performance of spunbond products at PT. Mekar Maju Spunjaya using the Supply Chain Operation Reference (SCOR) model. The SCOR framework was chosen due to its systematic approach in evaluating Supply Chain performance through five key processes: Plan, Source, Make, Return, and Return. A descriptive quantitative method was employed, with data collected through direct observation, interviews, documentation, and benchmarking against ideal industry performance standards. The results indicate performance gaps in several key attributes, such as Perfect Order Fulfillment (POF), which reached only 64% compared to the ideal 95%, and Order Fulfillment Cycle Time (OFCT), which took 14 days versus the standard of 8 days. Furthermore, Cost efficiency requires improvement, as shown by the Cost of Goods Sold (COGS) reaching 68%, whereas the industry benchmark is 40%. These findings highlight the need for improvements in reliability, process speed, and Cost control. The study concludes that the Supply Chain performance of PT. Mekar Maju Spunjaya has not yet reached optimal levels when compared to industry benchmarks. Therefore, it is recommended that the company continuously evaluate its Supply Chain processes based on SCOR indicators to enhance competitiveness and overall operational efficiency. Abstrak. Penelitian ini bertujuan untuk menganalisis kinerja rantai pasok produk spunbond di PT. Mekar Maju Spunjaya dengan menggunakan pendekatan Supply Chain Operation Reference (SCOR). Model SCOR dipilih karena mampu memberikan kerangka kerja yang sistematis dalam mengevaluasi kinerja rantai pasok melalui lima proses utama, yaitu Plan, Source, Make, Return, dan Return. Metode penelitian yang digunakan adalah kuantitatif deskriptif, dengan pengumpulan data melalui observasi langsung, wawancara, dokumentasi, serta benchmarking terhadap standar kinerja ideal industri sejenis. Hasil penelitian menunjukkan adanya gap kinerja pada beberapa atribut utama, seperti Perfect Order Fulfillment (POF) yang hanya mencapai 64% dari standar ideal 95%, serta Order Fulfillment Cycle Time (OFCT) yang memerlukan waktu 14 hari dibanding standar 8 hari. Selain itu, efisiensi biaya masih perlu ditingkatkan, terbukti dari Cost of Goods Sold (COGS) yang mencapai 68% dibanding standar industri sebesar 40%. Temuan ini menunjukkan perlunya perbaikan pada aspek keandalan, kecepatan proses, dan pengendalian biaya. Penelitian ini menyimpulkan bahwa kinerja rantai pasok PT. Mekar Maju Spunjaya belum sepenuhnya optimal jika dibandingkan dengan benchmark industri. Oleh karena itu, perusahaan disarankan untuk melakukan evaluasi berkelanjutan terhadap proses rantai pasoknya berdasarkan indikator-indikator dalam model SCOR agar dapat meningkatkan daya saing dan efisiensi operasional secara menyeluruh.

Purpose Indonesia released a self-declared halal certification program to increase the number of business actors with low-risk products. This study aims to examine and provide guidelines for measuring performance in the halal supply chain for business actors with halal certification. Design/methodology/approach The primary data used in this study were collected through expert interviews in four stages of the Delphi method and closed questionnaires with a Likert scale. This study employs the supply chain operations reference (SCOR) model to provide a framework for measuring performance by integrating it with the Delphi-analytic hierarchical process (AHP) method. Findings Based on the Delphi-AHP analysis, the halal supply chain performance is categorized as 83% in the good category. The highest halal supply chain performance is the plan dimension. It represents government efforts to accelerate halal certification by improving governance and providing halal assistance and transparency in the halal certification application process. Practical implications This research can be a reference for regulators and business actors in measuring business performance. Originality/value This study presents a novel integration of the SCOR model with the Delphi-AHP method to measure halal supply chain performance among micro, small and medium enterprises (MSMEs) engaged in Indonesia's self-declared halal certification program. Unlike prior studies that focus solely on conceptual indicators, this research prioritizes performance dimensions using empirical expert consensus. The framework provides a replicable, data-driven tool for evaluating halal supply chains, especially in developing regions. It contributes both methodologically and practically by guiding regulators and MSMEs in enhancing halal compliance and supply chain integration.