Supply Chain Network Structure Research Articles

Creating a Sustainable Supply Chain Network by Adopting Relationship Management Strategies

ABSTRACT Purpose: This paper develops a conceptual framework to analyze the impact of a supply chain network (SCN) structure on relationship management strategies (RMS) that focal firms apply to manage sustainability issues within the SCN. Design/methodology/approach: This paper is based on a comprehensive review and analysis of the industrial marketing and purchasing (IMP), sustainable supply chain management (SSCM), and SCN literature. Findings: The conceptual framework expands the network perspective in the SSCM context by considering the important role of the SCN structure in the firm’s decision-making process. Four factors (dependency, distance, power, and transparency) were found that are useful in conceptualizing the SCN structure. The conceptual framework also categorizes various sustainability practices into four RMS (noncompliance, transactional, dictatorial, and collaborative), which are needed to make an SCN more sustainable. In addition, 16 propositions are developed based on how firms may identify the most effective RMS to implement appropriate sustainability practices through examining their SCN structure. Research limitations/implications: The conceptual framework, developed as a result of a comprehensive review of the literature, led to the development of 16 propositions, which can assist in furthering a research agenda on RMS to diffuse various sustainability practices within SCN structures. Originality/value: The relationship between SCN structure and RMS in the sustainability context remains an under-researched but emerging area of interest. This paper leverages existing research to develop a conceptual framework suitable for empirical testing.

Green closed-loop supply chain network design considering cost control and CO2 emission

PurposeEnvironmental issues have become an important concern in modern supply chain management. The structure of closed-loop supply chain (CLSC) networks, which considers both forward and reverse logistics, can greatly improve the utilization of materials and enhance the performance of the supply chain in coping with environmental impacts and cost control.Design/methodology/approachA biobjective mixed-integer programming model is developed to achieve the balance between environmental impact control and operational cost reduction. Various factors regarding the capacity level and the environmental level of facilities are incorporated in this study. The scenario-based method and the Epsilon method are employed to solve the stochastic programming model under uncertain demand.FindingsThe proposed stochastic mixed-integer programming (MIP) model is an effective way of formulating and solving the CLSC network design problem. The reliability and precision of the Epsilon method are verified based on the numerical experiments. Conversion efficiency calculation can achieve the trade-off between cost control and CO2 emissions. Managers should pay more attention to activities about facility operation. These nodes might be the main factors of costs and environmental impacts in the CLSC network. Both costs and CO2 emissions are influenced by return rate especially costs. Managers should be discreet in coping with cost control for CO2 emissions barely affected by return rate. It is advisable to convert the double target into a single target by the idea of “Efficiency of CO2 Emissions Control Reduction.” It can provide managers with a way to double-target conversion.Originality/valueWe proposed a biobjective optimization problem in the CLSC network considering environmental impact control and operational cost reduction. The scenario-based method and the Epsilon method are employed to solve the mixed-integer programming model under uncertain demand.

Assessment of pre and post-disaster supply chain resilience based on network structural parameters with CVaR as a risk measure

The present study assesses supply chain resilience based on network structural parameters. Resilience is computed as a composite effect of density, centrality, connectivity, and network size of the network. A simulation-based approach is adopted, wherein networks of 23 firms operating in India are subjected to risk combinations of five mutually inclusive independent scenarios of probability levels and five mutually exclusive and exhaustive impact levels. The worst-case performance of the supply chain network when subjected to high impact and low probability risks is captured using conditional-value at risk (CVaR). Results reveal that the firm which has the lowest density and centrality and the highest connectivity and network size, exhibits the highest resilience. Whereas, the firm which has the highest density and high centrality due to an aggregation node exhibits the lowest resilience.The two main contributions of the present study are as follows. First, it derives insights for practicing managers from actual instead of theoretical networks. Second, it captures the worst-case performance of the supply chain network using CVaR, which has not been reported by any study in the supply chain network structure domain. The simulation-based approach can be easily adopted by the managers to assess the resilience of their supply chain networks and their preparedness to face potential risks. The information available in the form of CVaR is an important input to practicing managers to evaluate whether their supply chain network can face severe disruptions or not. The managers can then make informed decisions on how to increase the resilience of their supply chain networks.

Blockchain Adoption for Traceability in Food Supply Chain Networks

Innovative retailers in food supply chains have been exploring blockchain-based tracing systems as part of an ongoing effort to reduce contamination risks and food waste. We develop a three-tier supply chain model with multiple upstream (tier-2) suppliers to investigate: how blockchain adoption affects incentives of supply chain members, and whether and how its anticipated benefits can be realized. We find that blockchain-enabled full traceability brings direct revenue benefit to every supply chain member by saving uncontaminated food from disposal (pure traceability effect), but also leaves each tier of the supply chain vulnerable to its immediate downstream buyer’s exploitation through strategically lowering the purchasing price (strategic pricing effect). The interplay of the two effects may result in some of the supply chain members (even the retailer) being worse off with blockchain adoption, and the system being exposed to higher contamination risk; the latter is due to the weakened upstream supplier’s incentive to exert contamination risk-reduction effort. Moreover, we find that the supply chain network structure also influences the benefit distribution of blockchain adoption: The retailer always benefits from blockchain adoption in network structures where the tier-1 supplier’s strategic pricing power is eliminated or weakened; all supply chain members benefit from blockchain adoption in a network with a large number of tier-2 suppliers. Finally, we show that alternative risk-mitigation schemes such as tier-2 coordination can diminish the value of blockchain adoption, and partial traceability enabled by tier-1 product inspection can be more beneficial to the retailer than blockchain-enabled traceability.

A p-Robust Green Supply Chain Network Design Model under Uncertain Carbon Price and Demand

The problem of designing a multi-product, multi-period green supply chain network under uncertainties in carbon price and customer demand is studied in this paper. The purpose of this study is to develop a robust green supply chain network design model to minimize the total cost and to effectively cope with uncertainties. A scenario tree method is applied to model the uncertainty, and a green supply chain network design model is developed under the p-robustness criterion. Furthermore, the solution method for determining the lower and upper bounds of the relative regret limit is introduced, which is convenient for decision-makers to choose the corresponding supply chain network structure through the tradeoff between risk and cost performance. In particular, to overcome the large scale of the model caused by a high number of uncertain scenarios and reduce the computational difficulty, a scenario reduction technique is applied to filter the scenarios. Numerical calculations are executed to analyze the influence of relevant parameters on the performance of the designed green supply chain network. The results show that the proposed p-robust green supply chain network design model can effectively deal with carbon and demand uncertainties while ensuring cost performance, and can offer more choices for decision-makers with different risk preferences.

Role of Strategic Leadership of a Firm in Successful Implementation of Supply Chain Management: Implications for Sri Lankan Managers

The role of strategic leadership of a firm whithin a supply chain is an antecedent to the successful implementation of supply chain management. A strategic leader of the firm should interact and work with diferent value chain within the supply chain to add and deliver value to the final customer. The most imporant roles of the strategic leader dealing with the member value chains include cultivating a supply chain orientation within the firm, designing the supply chain network structure, organizing the supply chain business process and putting supply chain practitices into effect. Managers must realize the characteristics of national culture and cultivate consistent and uniform supply chain orientation within the firm in applying the supply chain orientation and implementing the supply chain practices in Sri Lankan companies.

A Robust Fuzzy Optimization Model for Closed-Loop Supply Chain Networks Considering Sustainability

Supply chain network design (SCND) is an important strategic decision determining the structure of each entity in the supply chain, which has an important impact on the long-term development of a company. An efficient and effective supply chain network is of vital importance for improving customer satisfaction, optimizing the allocation of resources, and increasing profitability. The environmental concerns and social responsibility awareness of the whole society have spurred researchers and managers to design sustainable supply chains (SSCs) integrating the economic, environmental, and social factors. In addition, the innate uncertainty of the SCND problem requires an integrated method to cope. In this regard, this study develops a multi-echelon multi-objective robust fuzzy closed-loop supply chain network (CLSCN) design model under uncertainty including all three dimensions of sustainability. This model considers the total cost minimization, carbon caps, and social impact maximization concurrently to realize supply chain sustainability, and is able to make a balance between the conflicting multiple objectives. Meanwhile, the uncertainty of the parameters is divided into two categories and addressed with two approaches: the first category is missed working days related to social impact, which is solved by the fuzzy membership theory; the second category is the demand and remanufacturing rate, which is settled by a robust optimization method. To validate the ability and applicability of the model and solution approach, a numerical example is conducted and solved using ILOG CPLEX. The result shows that the supply chain network structure and the value of the optimization objectives will change when considering sustainability and different degrees of uncertainty. This will enable supply chain managers to reduce the environmental impact and enhance the social benefits of their supply chain activities, and design a more stable supply chain to better cope with the influence of uncertainty.

Supply chain design with time-limited transportation contracts

Market globalization and increased costs have tightened profit margins within the chemical process industry. A supply chain design dictates the supply chain network structure and plays a vital role in determining the profitability of a process manufacturing enterprise. This work considers the design of supply chains, with a particular focus on capturing the effects of time-limited transportation contracts in which specified minimum durations of transportation linkages must be adhered to. An optimization-based design formulation is proposed, with flexibility in allowable node connections and direction of material flow. The design problem is formulated as a MILP. The proposed approach is applied to an industrially based case study, and the economic impact of taking time-limited contractual constraints into account, where these exist, is demonstrated.

Supply Chain Network Structure and Environmental Information Disclosure

Recognizing that supply network structure has implications for a focal firm’s ability to access environmental information embedded in its supply network, this paper draws on structural, environment...

The Equilibrium Model for the Coexistence of Renewable Portfolio Standards and Emissions Trading: The Supply Chain Analysis

China will impose both renewable portfolio standards (RPS) and emissions trading (ET) on the electricity industry, but the product competition in the retail market and the influence of the supply chain network structure has not been investigated. This paper studies policy effects by comparing equilibrium results under different supply chain network structures, and we use the concept of consumer environmental awareness to capture a product’s substitutability. Results indicate that: (1) Both increases in the permit price and the rise of the quota obligation reduces the aggregate profits of the supply chain, but the former rather than the latter increases the profits of the renewable power generating company; (2) the differential pricing improves the retailer’s flexibility in the charged price when confronting increases in the permit price and the quota obligation; (3) higher consumer environmental awareness makes the supply chain less profitable and increases the costs of ET suffered by the consumer; (4) the cooperation between the thermal power generating company and the retailer significantly increases the aggregated profits of the supply chain, although the cooperative profit is sensitive to environmental awareness. Moreover, the consumer suffers the highest costs that the retailer passes on them, and may prefer to feel that the emission cost and compliance cost are less affordable. In contrast, the cooperation between power generating companies removes the influence of environmental awareness, but the aggregated profits of the supply chain are smaller than in the decentralized decision scenario.

Investigation of closed-loop supply chains with product refurbishment as integrated location-inventory problem

Traditionally, the three most important decisions in Supply Chain Management (SCM) are: Facility location, inventory management and distribution decisions. These decisions are often analysed separately in order to reduce the computational complexity of the corresponding planning problems. This typically results in non-optimal decisions, as in reality the different decisions interact with each other. The major focus of this paper is to bridge the gap between location and inventory planning. The resulting problem is known as location-inventory problem and the e-commerce business serves as motivating example. A solution methods (second-order cone programm) is developed which is able to solve large-scale real-world problem instances. The structure of the closed-loop supply chain network is investigated and altogether promising insights are obtained for decision makers in SCM.

Long-term forecasting of fuel demand at theater entry points

Managing the distribution of fuel in theater requires Army fuel planners to forecast demand at the strategic level to ensure that fuel will be in the right place, at the right time, and in the amounts needed. This work presents a simulation approach to forecasting that accounts for the structure of the supply chain network when aggregating the demand of war fighters across the theater over the forecasting horizon. The resulting empirical distribution of demand at the theater entry point enables planners to identify forecast characteristics that impact their planning process, including the amplitudes and temporal positions of peaks in demand, and the estimated lead time to the point of use. Experimentation indicates that the forecasts are sensitive to the pattern of war fighter demand, the precise structure of the in-theater supply chain network, and the constraints and uncertainty present in the network, all of which are critical planning considerations.

A Review of Structural Relationships in Closed-Loop Supply Chain Model

The acquisition strategy of returned products has become essential in the study of reverse supply chain. There are three primary activities included in the process of a the reverse supply chain, the acquisition of returned products, the remanufacturing process, and redistribution. This literature review intends to study the existing relationship amongst supply chain players in a closed-loop supply chain (CLSC) model. In the remanufacturing process performed by the company, returned products must be collected from consumers. Therefore, remanufacturing companies rely upon consumers as cores suppliers. This makes the good relationship between the two become crucial in company operational sustainability successfully. In this study, the identified journal articles were categorized into types of structural relationships between supply chain players and network structures of a reverse supply chain. Types of structural relationships are ownership-based, service-contract, direct-order, deposit-based, credit-based, buy-back, and voluntary–based. There are four types of returned product collector and remanufacturer: Original Equipment Manufacturer (OEM), a third party (3PL), retailer, and remanufacturer. Discussion of the journal articles was presented in each category. After that, the structural relationship was explored to find its advantage and disadvantage, so that CLSC can be managed effectively and efficiently. As a summary, suggestions for future research were described as the result of the literature review conducted.

Evaluating the Readiness Level of Additively Manufactured Digital Spare Parts: An Industrial Perspective

Additive manufacturing of digital spare parts offers promising new possibilities for companies to drastically shorten lead times and to omit storage costs. However, the concept of digital spare parts has not yet gained much footing in the manufacturing industry. This study aims to identify grounds for its selective rejection. Conducted from a corporate perspective, outlining a holistic supply chain network structure to visualize different digital spare part distribution scenarios, this survey study evaluates technical and economic additive manufacturing capabilities. Results are analyzed and discussed further by applying the Mann-Whitney test to examine the influence of the company size and the presence of 3D-printed end-use components within supply networks on gathered data. Machines’ limited build chamber volumes and the necessity of post-processing are considered as the main technical challenges of current additive manufacturing processes. Furthermore, it can be concluded that company sizes have a significant effect on perceived technological limitations. Overall, the results lead to the conclusion that the readiness level of the digital spare parts concept demands for further development.

The complexity measurement and evolution analysis of supply chain network under disruption risks

Based on the study of the complexity of supply chain network, this chapter mainly analyzes the complexity of supply chain network structure in the context of disruption risk, and proposes a quantitative measurement method for the complexity of supply chain network based on DSM model. On this basis, this measure method is used to measure the complexity and evolution of ER random networks, small-world networks, and BA scale-free networks. Finally, the internal relationship between the complexity value, network size and connection probability is analyzed, which provides a theoretical basis for the structural design of supply chain network under the disruption risks.

Broadening the perspective of supply chain finance: The performance impacts of network power and cohesion

Because firms do not operate in isolation, they are bound by the structure of the networks in which they are embedded. This structure has implications on a firm's ability to access resources and utilize them to their advantage. We consider two critical components of this network structure: network power and network cohesion. Both of these network structures can be critical determinants of firm financial success. Yet, to date the extant research has not yet considered the role of network relations in the context of Supply Chain Finance (SCF). This manuscript attempts to contribute to this gap. Through the use of a dynamic supply chain network structure, we test the role that network power and cohesion have on a firm's financial performance. The results indicate network cohesion contributes positively to efficiency in financial performance, whereas power is a critical factor in earnings performance. Taken together, the study advances a nuanced perspective of managing the firm's levels of network power and cohesion to allow for heightened financial performance.

Bi-objective design of fresh food supply chain networks with reusable and disposable packaging containers

Abstract Packaging is crucial in protecting and handling products through the stages of their logistic networks. Actually, both disposable and reusable packaging containers are used. The former ends its life at the last stage of the distribution chain, the latter requires reverse flows to collect, recondition and, then, reuse it. Costs and emissions associated to the two types of packaging containers are different in nature, i.e. raw materials and landfill cost and emissions vs. reverse logistic costs and emissions, so that their choice is not univocal. Furthermore, such choice heavily affects the supply chain network structure and management. This paper addresses this topic aiming at designing a supply chain network including the packaging container best selection, storage/handling node location and flow allocation. An original bi-objective mixed integer linear programming model supports the decisional process. Despite the approach is general, a deep focus is on fresh fruit and vegetable distribution chain because of disposable and reusable packaging containers coexist in practice. The model looks at the cost and environmental impact minimisation over the whole network getting the Pareto frontier and supporting the logistic managers, industrial practitioners and policy makers in the network design and management. A real instance from Emilia-Romagna region, Italy, showcases the model application getting the economic and environmental optima together with best-balance configurations. Results stress the convenience of mixing reusable and disposable packaging containers to reach a global optimum. 47.1% reusable and 52.9% disposable is a possible good balance configuration reducing emissions while containing the cost increase.

A Network-Based Impact Measure for Propagated Losses in a Supply Chain Network Consisting of Resilient Components

The topology of a supply chain network affects the impacts of disruptions in it. We formulate a network-based measure of the impact of a disruption loss in a supply chain propagating downstream from an originating node. The measure takes into account the loss profile of the originating node, the structure of the supply network, and the resilience of the network components. We obtain an analytical expression for the impact measure under a beta-distributed initial loss (generalizable to any continuous distribution supported on the interval 0,1), under a breakthrough scenario (in which a fraction of the initial production loss reaches a focal company downstream as opposed to containment upstream or at the originating point). Furthermore, we obtain a closed-form solution for a supply chain network with a k-ary tree topology; a numerical study is performed for a scale-free network and a random network. Our proposed approach enables the evaluation of potential losses for a focal company considering its supply chain network structure, which may help the company to plan or redesign a robust and resilient network in response to different types of disruptions.

Research on supply chain partner selection and task alloca-tion based on fuzzy theory under an uncertain environment

Nowadays the enterprises pay the closer attention to the relationship among suppliers, manufacturers and distributors due to the global competitive market economy. And they manage the supply chain through establishing strategic cooperative partnership, which can greatly enhance the competitive advantage and obtain greater overall profits. In this paper, the fuzzy theory is applied to study the supply chain partner selection and the task coarse allocation problem in under multi-attribute fuzzy comprehensive decision-making and fuzzy constraints. Finally, the fuzzy comprehensive decision of supply chain network structure was verified through the case of Shaoxing textile.

A variational inequality formulation for designing a multi-echelon, multi-product supply chain network in a competitive environment

In a competitive environment, supply chains are competing with each other to gain the market share and competition is a critical factor influencing the supply chain network structure. The current paper presents a variational inequality formulation and provides the results for a competitive supply chain network design model. The new-entrant supply chain competes against an existing one in a non-cooperative behavior. The networks include raw material suppliers, manufacturers, retailers, and the same demand markets. The manufacturers produce multiple products with deterministic, price-dependent demand. The goal is to maximize the future revenue of both chains. The problem is modeled by mathematical programming and the governing Nash equilibrium conditions are derived. Then, a finite-dimensional variational inequality formulation is presented to solve the equilibrium problem. Qualitative properties of the equilibrium pattern are provided to establish existence and uniqueness results under reasonable conditions. The modified projection algorithm is used to solve the variational inequality problem. A numerical example is presented in order to show the efficiency of the proposed model and to investigate the behavior of the model under different conditions.