Supply Chain Network Management Research Articles

Supply chain network design and operation: Systematic decision-making for centralized, distributed, and mobile biofuel production using mixed integer linear programming (MILP) under uncertainty

Biomass resources are dispersed and subject to seasonal and geographical uncertainties. Therefore, supply chain network design and management can significantly influence the economic viability of a biofuel technology. Fast pyrolysis offers several advantages for biofuel production. It is a relatively cheap process and can be conducted in centralized, decentralizes, or even mobile configurations. Furthermore, it does not overlap with the human food supply chain, using wastes or lignocellulosic feedstocks. In this article, a mixed integer (piece-wise) linear program (MILP) was developed to determine the optimal supply chain design and operation, under uncertainty. Rigorous process modelling and detailed economic analysis were coupled with exhaustive search of potential production locations and biomass resources in order to enhance the fidelity of the solution. The optimisation results suggest that a combination of geographically centralized pyrolysis and upgrading centres would suffice for supply chain management under deterministic conditions. However, under uncertain scenarios, it is advantageous to deploy mobile pyrolyzers to add extra flexibility to the process operation. Further analysis suggested that as the mobile pyrolyzers are commercialized and their unit price is reduced, this technology has the potential to become a key member of the biofuel supply chain.

A Framework for Traceability and Transparency in the Dairy Supply Chain Networks

Food processing industries are assuming greater importance and processed food is now not a matter of choice but it is a necessity. As a result there is greater awareness of safety concerns, emerging risks and challenges in the context of food products. Consumers want guarantees for food characteristics, thus, calling for transparency and effective response in case of any food related health problem. This paper presents a framework for transparency, traceability and information flow for management of dairy supply chain networks. This paper follows a case study approach and presents findings from three types of dairy supply chains as prevalent in India. The paper analyses complexity of dairy products as well as processes in terms of intrinsic and extrinsic factors and their effects on the underlying dairy supply chain networks (DSCN). Governance mechanisms dovetailing various stages of the DSCN are presented in terms of their gaps and adequacy. Key components of the presented frameworks are harmonization of national standards with codex standards, hygiene control, strengthening quality control systems, enhancing information flow across stages, animal health care, disease free zones and formation of cooperatives of small dairy processors (CSDP) in line with the present dairy cooperative society (DCS). CSDP aims at collective action and public-private partnerships by the unorganized sector units to face the competition from large organized processors of dairy products in terms of quality, transparency, traceability and information flow. Transparency of a DSCN is the extent to which all its stakeholders have a shared understanding of and access to the product related information without loss, noise, delay and distortion. Given the perishable nature of dairy products, an effective traceability system is an important tool not only to manage food quality and safety risks, but also to promote the development of effective dairy supply chain management. This paper contributes to the nascent literature on transparency and traceability issues of dairy supply chain networks. Findings would be useful for policy makers in framing standards and effective regulations. Analysis of complexity would be useful for dairy industry managers.

A Fuzzy Decision Making Trial and Evaluation Laboratory Analysis of SCM System Implementation

This study has two phases. The first phase constructs a comprehensi ve model of key success factors (KSFs) for supply chain network management implementation in the semiconductor industry based on both a literature review and an expert review. The model has four dimensions: strategy, process, organization, and technolog y (SPOT), and 15 KSFs. The SPOT model can be a checklist for future projects. The second phase analyzed the complicated interrelationship among KSFs with Fuzzy Decision Making Trial and Evaluation Laboratory and discussed its managerial implications. Lastly, we provide two case studies to confirm the importance of the two most important factors.

ERP SaaS value chain: a proposed SaaS model for manufacturing SCM networked activities

This paper aims at proposing an ERP-SaaS model systems solution for manufacturing SCM networked value systems to enable the end-customer organisation to decrease the cost of implementation, maintenance and the overall administration of the application. This applied research employed an industrial pilot case study with an OEM industrial partner. The proposed ERP-SaaS model in this paper attempts to propose industrial systems solution value-adding benefits including: low preliminary-and-anticipated ongoing costs, faster implementations and value-adding, affordable ownership cost, greater reliability, improved support, reduced IT complexity and improved business motivation. Salesforce.com is one example of such successful ERP-SaaS systems solution vendors. However, ERP systems delivered as software-as-a-service; is not yet a systems solution that has had a commercial breakthrough, specifically for supply-chain management (SCM) network. Thus, this paper will be very relevant to industries keen on achieving competitive advantage of their SCM network as well as R&D both in the industry and academia.

Collaborative design and analysis of supply chain network management key processes model

This study focuses on collaboratively designing a structured and comprehensive supply chain (SC) network management key processes model and analyzing the relative importance of these key processes for semiconductor industry. The collaborative design and analysis are performed by a multidisciplinary team consisting of over 20 members from both academia and industry. This research is based on experiences of these team members who joined a successful e-SCM project, used as a case study in this research, between the world's largest semiconductor foundry and the world's largest assembly and testing service provider. This study adopts focus group methodology for collaborative design and fuzzy analytic hierarchy process (FAHP) for collaborative analysis. The result of the design is a structured and comprehensive key processes model consisting of four dimensions: strategy and planning, manufacturing, logistics, and risk management (SMLR) with a total of 15 key processes included in these four dimensions. The resulting weightings from FAHP analysis can identify the most critical one dimension and four key processes since they account for approximately half of the overall weighting in their level. The SMLR model provides a structured and comprehensive reference model for future SC network management project executives, ensuring that all key processes are supported to avoid extremely costly failure. The resulting weightings provide these managers with the relative importance of these key processes and can help them make critical decisions in allocating limited resources to support the most critical processes. To confirm the results and further explore the managerial implications, a second session of focus group meeting was conducted and practices of the top three key processes in the semiconductor manufacturing industry were used to illustrate what actions can be performed to improve these processes and hence benefit the entire SC network. The research results can serve as a foundation for related academic researches.

Firm and whole chain success: network management in the Ukrainian food industry

This article develops the theoretical foundations of supply chain network management in order to investigate the constructs surrounding whole chain success rather than just success at firm level. It is argued that the ‘network success’ link has been under-studied, with most empirical studies focusing on the achievement of goals by an individual firm in a network context. A model of the whole network's success in the context of supply chain networks in food industry supply chain relationships is used. The results identify that network-level goals must be considered alongside firm-level goals in supply chain networks. Furthermore, network-level goals are subject to the impacts of chain management and have to be of particular interest for focal firms that are responsible for the development and implementation of collective strategies.

A locally linear neuro-fuzzy model for supplier selection in cosmetics industry

Supplier selection and evaluation is a complicated and disputed issue in supply chain network management, by virtue of the variety of intellectual property of the suppliers, the several variables involved in supply demand relationship, the complex interactions and the inadequate information of suppliers. The recent literature confirms that neural networks achieve better performance than conventional methods in this area. Hence, in this paper, an effective artificial intelligence (AI) approach is presented to improve the decision making for a supply chain which is successfully utilized for long-term prediction of the performance data in cosmetics industry. A computationally efficient model known as locally linear neuro-fuzzy (LLNF) is introduced to predict the performance rating of suppliers. The proposed model is trained by a locally linear model tree (LOLIMOT) learning algorithm. To demonstrate the performance of the proposed model, three intelligent techniques, multi-layer perceptron (MLP) neural network, radial basis function (RBF) neural network and least square-support vector machine (LS-SVM) are considered. Their results are compared by using an available dataset in cosmetics industry. The computational results show that the presented model performs better than three foregoing techniques.

FlexRFID Middleware in the Supply Chain

Radio Frequency Identification (RFID) has been used since the Second World War to identify “friend or foe” aircrafts. It has become an enabling wireless technology that is widely used in a number of application areas, such as product tracking through manufacturing and assembly, inventory control, and supply chain management (SCM). By 2006, Wal-Mart used RFID for all of its suppliers. The use of RFID in supply chain networks has allowed Wal-Mart to create value through greater visibility in its networks, higher product velocity, reduce human error and labor cost, and more efficient inventory management, which led to the achievement of Quick Response (QR) and improved Customer Relationship Management (CRM) in the supply chain. However, RFID system challenges and uncertain Return-On-Investment (ROI) must be overcome to fully achieve these objectives. This paper introduces RFID technology and its key components and concepts, and presents an RFID middleware solution called FlexRFID that achieves the maximum benefits of RFID technology independently of the interested backend applications. This paper illustrates how RFID technology is used to solve the main problems in SCM, the advantages and key issues when implementing RFID in SCM networks, and the relationship between RFID and the main SCM processes.

Inoperability input‐output modeling (IIM) of disruptions to supply chain networks

AbstractIn this paper, the Inoperability Input‐Output Model (IIM) is deployed for assessing the impacts of disruptive events on supply chain networks under an unsafe environment. The IIM for supply chain networks has been proposed, based on the original IIM used in macro‐economics. A new method called the OWA (Ordered Weighted Averaging) Operator has been formulated to evaluate the interdependency matrix, a key component of the IIM. Similar to the capability of the basic IIM to describe the propagation impacts of disruptions to macroeconomic systems, the IIM for supply chain networks is capable of describing the propagation effects of disruptions to interdependent supply chain components. IIM assesses the impacts of disruptions to supply chain networks with “inoperability” and “economic losses” metrics, which can provide helpful insights for risk management of supply chain networks. An example supply chain network is used to illustrate the application of IIM for systemic risk assessment of supply chains under an unsafe environment. A risk mitigation strategy by increasing the number of suppliers has been considered to reduce the adverse effects caused by the supply reduction of the single secondary supplier in the example supply chain network. In addition, a simulation model integrated with Monte Carlo simulation method has been developed to validate the accuracy of the IIM for supply chain. The example shows that the application of IIM can provide useful guidance toward supply chain risk management or mitigation strategies and it could also be used to test the effectiveness of these strategies. © 2009 Wiley Periodicals, Inc. Syst Eng

A DECADE OF SCM LITERATURE: PAST, PRESENT AND FUTURE IMPLICATIONS

This study covers a decade of academic research in the Supply Chain Management (SCM) field, offering an in‐depth analytical review focused on the existing trends and gaps in the supply chain literature. Nine academic journals were investigated and a subject categorization is developed for SCM research. A content analysis was then conducted on 405 articles, focusing on the categories covered within the SCM literature, various levels of the chain examined and sample populations and industries studied, as well as the research methods employed. Finally, a conceptual framework of the most highly researched categories in SCM indicates that there is a need for more research that seeks to understand the nature of multiple links in SCM chains and networks, as opposed to focusing on dyadic and inter‐firm relationships.

Examining supply chain networks using V‐A‐T material flow analysis

PurposeThe purpose of this paper is to examine the use of V‐A‐T analysis in the management of supply chain networks.Design/methodology/approachThe paper provides a conceptual overview of V‐A‐T analysis as a procedure for categorizing manufacturing facilities, and explores the use of V‐A‐T analysis as a technique for the management of supply chain networks.FindingsThere are several challenges to the effective management of supply chain networks. However, organizations can overcome these challenges by understanding the nature of network control points as revealed through the application of V‐A‐T analysis on their supply chains.Research limitations/implicationsThe paper is conceptual in nature and must be validated through empirical research studies.Practical ImplicationsThe concepts presented can be used by supply chain professionals to increase the likelihood of effective supply chain management within their organizations, and by supply chain researchers to further explore the use of V‐A‐T analysis as a tool for examining supply chain networks.Originality/valueThe paper makes a start in filling a void in the literature concerning how V‐A‐T analysis can be used as a tool to facilitate improved supply chain management.

On the Study of Complexity in Information Systems

This article addresses complexity in information systems. It defines how complexity can be used to inform information systems research, and how some individuals and organizations are using notions of complexity. Some organizations are dealing with technical and physical infrastructure complexity, as well as the application of complexity in specific areas such as supply chain management and network management. Their approaches can be used to address more general organizational issues. The concepts and ideas in this article are relevant to the integration of complexity into information systems research. However, the ideas and concepts in this article are not a litmus test for complexity. We hope only to provide a starting point for information systems researchers to push the boundaries of our understanding of complexity. The article also contains a number of suggested research questions that could be pursued in this area.

Promise and problems with supply chain management approaches to health care purchasing

Double-digit health care inflation, coupled with widespread reports of poor care quality and deadly medical errors, has caused private sector employers to reevaluate their health benefits purchasing strategies, with a focus on supply chain management approaches. In other industries, this strategy has proven to be an effective method for simultaneously reducing costs and increasing quality. This article describes four current applications of supply chain management network methodologies to health care systems and identifies potential ways to improve purchasers' return on investment. In particular, information exchanges, purchase decision, and payment agreement components of integrated supply chains are described. First, visual depictions of the health care supply chain are developed from a purchaser's perspective. Next, five nationwide programs designed to realign incentives and rewards across the health care supply chain are described. Although several nationwide efforts are gaining traction in the marketplace, at this time, no cost reduction and quality improvement program initiative appears to systematically align the entire health care supply chain from providers to purchasers, raising doubt about the ability of supply chain management network techniques to significantly impact the health care marketplace in the short run. Current individual efforts to coordinate the health care supply chain do not act on all of the actors necessary to improve outcomes, promote safety, and control costs. Nevertheless, there are indications that several of the individual efforts are coming together. If national efforts touching on all critical elements can coordinate with purchasers, then the health care supply chain's performance may improve significantly.

A structural equation model of supply chain quality management and organizational performance

In this paper, we identify through the use of empirical data collected from Taiwan and Hong Kong, the factors that influence supply chain quality management. The data was collected from practicing managers. The findings for the two sets of data were consistent. The data showed that Quality Management (QM) practices are significantly correlated with the supplier participation strategy and this influences tangible business results, and customer satisfaction levels. The data also showed that QM practices are significantly correlated with the supplier selection strategy. The empirical results presented could be used to improve the management of supply chain networks in the economies studied.

E‐knowledge networks for inter‐organizational collaborative e‐business

Evaluates the increase in inter‐ and intra‐organizational knowledge sharing capabilities brought about by the Internet‐driven “new economy” technologies and the resulting managerial implications. Presents a framework for evaluating and deploying such technologies. Firms employing knowledge networks can also use e‐knowledge to improve organizational decision making, react more quickly to changes in the economic landscape, and create dynamic custom content and consumer intimacy. Builds on the extensive literature in knowledge management and inter‐organizational systems by identifying the opportunities of each in creating “e‐knowledge networks” to support organizational collaboration. This framework is applied to four industry case studies – supply chain management networks, adserver networks, content syndication networks, and business‐to‐business exchange networks. Analysis suggests that in the new economy, characterized by ubiquitous and often automated information sharing capabilities, the ability to create knowledge‐based networks of partners will be critical to maintaining competitive advantage.