Ontology alignment for networked enterprise information system interoperability in supply chain environment

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.

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.

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.

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.

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.

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.

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.

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.

: An emerging area in supply chain practice is green supply chain management, which integrates environmental management with traditional supply chain management. GreenSCOR is the solution to closing this gap. GreenSCOR is a modification of version 5.0 of the Supply Chain Operations Reference (SCOR) model developed by the Supply-Chain Council (SCC). LMI used SCOR as a foundation because it has been proven over several years of continual development. SCOR also fit well with the LCA approach now common in environmental management.

The recent introduction of Supply Chain Operations Reference (SCOR) approach for modeling supply chains has been positively received by practitioners and consultants. SCOR is perceived to provide a simple though powerful standard for modeling supply chains. As SCOR is emerged from a practitioner's perspective, comparatively less little academic attention has been paid to SCOR to date. This paper aims to address one aspect of SCOR while at the same time providing a short overview of its concepts and use. Specifically, we examine SCOR from a methodological perspective, by adopting a systems development framework and using a socio-technical lens as a basis for assessment. To effect such an assessment, a fictitious timing instrument manufacturing company supply chain case (TimeWise) is used to create the context for developing and assessing SCOR approach. It was found that SCOR was strong on technical dimensions such as modeling process and techniques but weak on the social dimensions. The contribution of the paper includes an overview of SCOR and a systemic assessment of a method to develop a SCOR model in order to highlight the strengths and limitations of the approach and to guide future research in this domain.

This paper describes the work that led to the realisation of an extended graph-based virtual clustering-enhanced approach to supply chain optimisation. The Supply-Chain Operations Reference (SCOR) model defined by the Supply-Chain Council in Pittsburgh, PA, USA is used to denote a typical supply chain, which may include geographically distributed suppliers, warehouses, factories, distribution centres (DCs), transportation and customers. A graph representation is proposed to represent and analyse the business processes of the SCOR model from customer orders to suppliers. Furthermore, logical relationships are superimposed onto the graph. This extended graph enables the complex relationships between the nodes of two adjoining layers to be described. By so doing, it is able to model a complex supply chain with multiple level assembly, various types of transportations and a multiple split and merge of orders. In order to handle a large-scale supply chain optimisation problem, the extended graph is enhanced by virtual clustering so as to realise an approach that is able to downscale the optimisation problem and reduce the search space. A case study is used to illustrate the effectiveness of the proposed approach. The details of the SCOR model, the extended graph, the virtual clustering, the proposed approach and the case study are presented in this paper.