Supply Chain Model Research Articles

Order or Collaborate? Manufacturers Utilize 3D-Printed Parts to Sustainably Facilitate Increased Product Variety

3D printing (3DP) has garnered significant attention from industries, prompting traditional manufacturers to adopt 3DP to sustainably facilitate increased product variety. Observing manufacturers’ two adoption strategies, ordering parts and collaboratively printing 3DP parts, in a real-world setting, we utilize a wholesale price contract and a Nash Bargaining contract to describe these two strategies and then develop a supply-chain model including a 3DP supplier (Supplier) and a traditional manufacturer (Manufacturer). Further, we employ backward induction to solve the subgame-perfect Nash equilibrium for the model to reveal differences between these two strategies and the impact of 3DP’s improved resource efficiency. According to equilibrium outcomes, analytical results show that first, as long as the unit cost of each 3DP part is not overly high and 3DP’s resource efficiency is not extremely low, the Manufacturer is willing to implement 3DP to increase product variety. Second, a rise in the resource efficiency can create a “win-win” scenario for the Manufacturer and the Supplier. Third, supply-chain collaboration can be achieved when the Manufacturer’s and the Supplier’s bargaining powers approach equality. Interestingly, a Nash bargaining contract can incentivize the manufacturer to substitute a base product with a variety of products, a change facilitated by an increase in the retail price of this base product. The managerial implication of this research is that enhanced resource efficiency can lead to less environmental pollution in the collaboration model by resulting in the sale of lower quantities of the base product, which would otherwise consume more resources and generate greater environmental pollution.

A new hybrid modeling of sustainable supply chain planning with imprecise data in textile industry

A new hybrid modeling of sustainable supply chain planning with imprecise data in textile industry

Participant fairness concern and cost‐sharing‐based dual‐channel low‐carbon supply chain management

AbstractConsidering consumer channel preferences, our paper establishes a two‐echelon differential low‐carbon supply chain model and discusses the effects of member's cost‐sharing and fairness concerns on equilibrium results. From a static perspective, the results indicate that retailers' fairness concern behavior will lead to a decrease in pricing and participants' efforts while manufacturers cost‐sharing strategy will only enhance retailers' advertising efforts. From a dynamic perspective, products' greenness, long‐term benefits of manufacturers and retailers, and social welfare will gradually increase and eventually saturate over time. In most cases, manufacturer‐to‐retailer cost‐sharing is a win–win strategy that not only enhances the long‐term interests but also realizes the greening and upgrading of the supply chain.

A decision-making model for echelon utilization of retired batteries in competitive duopoly: the role of government subsidy

As the wave of retirements in the new energy vehicle sector approaches, China’s emphasis on echelon utilization has grown to optimize battery reuse and recycling. However, the burgeoning industry will inevitably face the challenges of competition, influencing stakeholders across the supply chain. In this study, we employ game theoretic models to investigate the interplay between competitive dynamics and government subsidy policies within this industry. Through the development of a competitive duopoly echelon utilization supply chain model, our analysis offers valuable insights and recommendations for the advancement of the industry. We find that increases in echelon utilization costs prompt adjustments in retail prices by echelon utilization enterprises, third-party recyclers, and new energy vehicle manufacturers. As competition intensifies, overall supply chain profitability diminishes, resulting in a lose-lose situation, favoring only third-party recyclers, who raise wholesale prices as new energy vehicle manufacturers reduce transfer payments. Conversely, government subsidies stimulate higher total demand, benefiting subsidized echelon utilization enterprises, which enhance consumer and social value. Non-subsidized enterprises are compelled to raise retail prices. Given the positive impact of subsidies, governments should prioritize support for enterprises demonstrating superior echelon utilization practices.

Providing solutions for carbon emission reduction using the TOE framework

Firms are adopting low-carbon strategies to stay competitive and manage operations sustainably. We studied how to reduce carbon emissions and design tailored solutions for different firms using the TOE framework. Our research used a three-pronged approach, including a supply chain model, panel regression analysis, and fuzzy sets of qualitative comparative analysis (fsQCA). We discovered that 80% is a significant threshold for determining the number of TOE factors. Our study also confirms the Matthew effect in carbon reduction. These results provide valuable insights and practical recommendations for managers to reduce emissions and promote sustainable development.

Dynamical Analysis and Sliding Mode Controller for the New 4D Chaotic Supply Chain Model Based on the Product Received by the Customer

Supply chains comprise various interconnected components like suppliers, manufacturers, distributors, retailers, and customers, each with unique variables and interactions. Managing dynamic supply chains is highly challenging, particularly when considering various sources of risk factors. This paper extensively explores dynamical analysis and multistability analysis to understand nonlinear behaviors and pinpoint potential risks within supply chains. Different phase portraits are used to demonstrate the impact of various factors such as transportation risk, quality risk, distortion, contingency reserves, and safety stock on both customers and retailers. We introduced a sliding mode control method that computes the sliding surface and its derivative by considering the error and its derivative. The equivalent control law based on the sliding surface and its derivative is derived and validated for control purposes. Our results show that the controller SMC can significantly enhance supply chain stability and efficiency. This research provides a robust framework for understanding complex supply chain dynamics and offers practical solutions to enhance supply chain resilience and flexibility.

Decision of a trade credit policy in a supply chain model of growing items under linguistic fuzzy term set

ABSTRACT This article deals with a novel trade credit policy for growing items where the buyer collects the new born items from a supplier and sells them to the consumers when they are grown up. The supplier provides a credit period to the buyer through negotiation. From the buyer’s view point first of all, a profit maximization growing items with carbon emission supply chain model has been studied under three different scenarios over the length of credit periods. To capture the non-random uncertainty of the model parameters and the learning effects we have assumed the demand rate of the consumers and all the cost parameters as triangular fuzzy linguistic terms set by means of a learning matrix. For defuzzification we have utilized the eigen values of the corresponding fuzzy learning matrices and solved the problem with the help of a solution algorithm under optimum number of new born items. However, for numerical computations we have utilized the data set studied by Alamri from a real case study. A comparative analysis has also been discussed for model validation. Finally, sensitivity analysis and graphical illustration are carried out to focus the novelty and to study the impact of the inventory parameters of the proposed approach.

Enabling industrial decarbonization: A MILP optimization model for low-carbon hydrogen supply chains

This study develops a an optimization model focused on the layout and dispatch of a low-carbon hydrogen supply chain. The objective is to identify the lowest Levelized Cost of Hydrogen for a given demand. The model considers various elements, including electricity supply from the local grid and renewable sources (photovoltaic and wind), alongside hydrogen production, compression, storage, and transportation to end users. Applied to an industrial case study in Sweden, the findings indicate that the major cost components are linked to electricity generation and investment in electrolyzers, with the LCOH reaching 5.2 EUR/kgH2 under typical demand conditions. Under scenarios with higher peak demands and greater demand volatility, the LCOH increases to 6.8 EUR/kgH2 due to the need for additional renewable energy capacity. These results highlight the critical impact of electricity availability and demand fluctuations on the LCOH, emphasizing the complex interdependencies within the hydrogen supply chain. This study provides valuable insights into the feasibility and cost-effectiveness of adopting hydrogen as an energy carrier for renewable electricity in the context of decarbonizing industrial processes in the energy system.

Complex Network-Based Resilience Assessment of the Integrated Circuit Industry Chain

With the improvement of social production efficiency and the enhancement of the supply chain system, the traditional linear supply chain model is gradually evolving into a more complex and dynamic industrial chain network. This article uses complex network theory combined with the basic attributes of the industrial chain and supply chain to conduct a comprehensive and in-depth analysis of the integrated circuit industry chain. Firstly, a cooperative network model of the integrated circuit industry chain in Shaanxi Province is established based on the supply chain relationships of enterprises. Secondly, the study analyzes the basic characteristics of the collaborative network model. Thirdly, this study explores the efficiency, resilience, and innovation capacity of industrial chains using a novel set of indexes: the industry chain efficiency index (ICEI), the industry chain resilience index (ICRI), and the industry chain innovation capability index (ICICI). By employing principal component analysis (PCA), the study provides a comprehensive evaluation of industrial chain performance. The findings reveal that the ICEI highlights the critical importance of average path length and network density, showing that shorter paths and higher density are associated with greater efficiency. The ICRI emphasizes the roles of average degree and standard deviation, indicating that higher connectivity and lower variability contribute to resilience. The ICICI identifies the clustering coefficient and network density as key factors, suggesting that tight-knit networks foster innovation. These results offer significant insights into the dynamics of industrial chain collaboration and provide practical recommendations for enhancing supply chain management. Finally, the effectiveness of the proposed method is demonstrated through a case study. The results of the case study indicate the following: (1) Key Enterprises’ Identification: The analysis identified key enterprises like Samsung Semiconductor and HT-tech with the highest betweenness centrality, highlighting their crucial intermediary roles within the network; (2) Efficiency and Innovation Assessment: Compared with foreign-owned and other immigrant businesses, local businesses generally perform below average in terms of efficiency and resilience, indicating that there is room for improvement in technology adoption and innovation capabilities.

Strategies for Integrating Marginalized Communities into Supply Chains: Empowering Suppliers, Producers, and Distributors

Integrating marginalized communities into supply chains as suppliers, producers, and distributors is a vital step for ensuring inclusive economic growth and poverty elimination. This study investigates effective strategies that enable businesses and organizations to incorporate disadvantaged groups into both global and local supply chains. Drawing on case studies and qualitative data, the research identifies critical factors in successful integration, including capacity-building initiatives, access to affordable financing, fair trade practices, and the utilization of technology for streamlined operations and market connectivity. Findings reveal several barriers these communities face, such as societal mindsets, limited financial support, lack of skills, and logistical challenges, which can impede their participation in supply chains. To address these challenges, this study proposes actionable strategies to create sustainable, inclusive supply chain models, highlighting the role of consistent training, transparent communication, and impact-oriented partnerships. The research underscores the significant socioeconomic benefits of inclusive supply chains, offering valuable insights and models for stakeholders aiming to empower marginalized communities, improve social cohesion, and drive local development through equitable business practices.

An inventory-routing optimization model for pharmaceutical supply chain with time-dependent travel time on a multi-graph network: a case study

PurposeSpurred by the high turnover in the pharmaceutical industry, locating pharmacies inside urban areas along with the high product perishability in this industry, the pharmaceutical supply chain management has recently gained increasing attention. Accordingly, this paper unveils an inventory-routing problem for designing a pharmaceutical supply chain with perishable products and time-dependent travel time in an uncertain environment.Design/methodology/approachIn this study, mathematical programming is employed to formulate a multi-graph network affected by the traffic volume in order to adapt to real-world situations. Likewise, by transforming the travel speed function to the travel time function using a step-by-step algorithm, the first-in-first-out property is warranted. Moreover, the Box–Jenkins forecasting method is employed to diminish the demand uncertainty.FindingsAn appealing result is that the delivery horizon constraint in the under-study multi-graph network may eventuate in selecting a longer path. Our analysis also indicates that the customers located in the busy places in the city are not predominantly visited in the initial and last delivery horizon, which are the rush times. Moreover, it is concluded that integrating disruption management, routing planning and inventory management in the studied network leads to a reduction of costs in the long term.Originality/valueApplying the time-dependent travel time with a heterogeneous fleet of vehicles on the multi-graph network, considering perishability in the products for reducing inventory costs, considering multiple trips of transfer fleet, considering disruption impacts on supply chain components and utilizing the Box–Jenkins method to reduce uncertainty are the contributions of the present study.

Evaluation on network optimization model of low-carbon multi-level supply chain based on big data algorithm evaluation

Evaluation on network optimization model of low-carbon multi-level supply chain based on big data algorithm evaluation

Supply chain management (SCM) framework for small and medium manufacturing enterprises (SMEs) in Ghana

Efficient supply chain management is essential for small and medium-sized enterprises (SMEs) in Ghana to guarantee a dependable flow of products and services, sustain competitiveness, and promote growth and job creation. The objective of this study is to analyse the current supply chain models utilised by manufacturing small and medium-sized enterprises (SMEs) in Ghana. Additionally, it intends to propose a prototype model that will aid manufacturing SMEs in achieving sustainability, growth, and future expansion in Ghana and other regions. The Conceptual framework was developed by examining variables identified in the existing literature on supplier management practices in small and medium-sized enterprises (SMEs), as well as inventory management approaches that are relevant to SMEs. A structured questionnaire was employed to collect data from the main source. This study employs a mixed method approach, which includes the participation of 363 respondents. Interviews and surveys were carried out with small and medium-sized enterprise (SME) owners and managers. The data was analysed using the SPSS (v 27.0) computer application, which involved both inferential and descriptive statistical analysis. The findings revealed essential components of the prototype, such as the implementation of supply management (SM), proficient information management (IM), streamlined distribution strategies, and strong marketing and sales strategies, in addition to customer relationship management (CRM) and effective post-sales services. Implementing these supply chain management (SCM) principles effectively can guarantee the sustainability, growth, employment generation, and overall performance of small and medium-sized enterprises (SMEs) in Ghana.

Complexity analysis of technology spillover supply chain with dual business objectives

ABSTRACT Based on the existence of technology spillover effect of manufacturers, considering the manufacturer's commercial goals of profit and market share, a dynamic price game model of technology spillover supply chain with dual commercial goals is established. Based on game theory and nonlinear dynamics theory, the equilibrium point and local stability of the system are analyzed. In addition, the effects of price adjustment rate, balance coefficient of business objectives, and technology spillover on model complexity, the change of manufacturer price and profit were analyzed through numerical simulation. The results show that the price adjustment rate, the balance coefficient of business objectives, and the technology spillover have an impact on the stability and complexity of the manufacturer's price competition model. Rationally controlling the price adjustment rate, and enhancing technological spillovers are beneficial to the healthy development of manufacturers and the healthy competition among manufacturers, maintaining the stability of product market prices, and effectively avoiding market chaos. Moreover, when considering market share, manufacturers can expand the system stability domain.

Sustainable supply chains – Designing a requisite holistic model

AbstractOur study explored the relationships between supply chain (SC) members and their local and global stakeholders in achieving sustainability goals based on requisite holistic analysis and system dynamics modeling, which goes beyond the previous attempts to improve SC sustainability. In this research, we first developed a model that addresses the basic holistic treatment of SC sustainability; in a second model of sustainable SC (SSC), we then considered requisite holistic interactions among its stakeholders. We used the theory‐based viable system model to diagnose the proposed holistic model of SSC. The results show that especially the low‐tier SC members require supporting frameworks to develop and maintain the capacity for sustainable interactions with nature and society. These supportive frameworks should be provided by the regulatory bodies, society, and nature representatives to surpass the limited SC profit‐oriented incentives and structures. The implications of the proposed models are aimed at developing supportive SC sustainable policies and improving the capacities of SC members to coexist with local social and natural environments. Regulators, society, and the natural environment representatives can apply the proposed models to establish new policies for sustainable interactions between SC members and other societal stakeholders.

Impact of Carbon Emission Policy on Fresh Food Supply Chain Model for Deteriorating Imperfect Quality Items

Impact of Carbon Emission Policy on Fresh Food Supply Chain Model for Deteriorating Imperfect Quality Items

Selection of financing and selling modes in a green and capital‐constrained platform supply chain

AbstractCurrently, manufacturers can collaborate with online platforms to better sell green products and also finance from platforms to relieve financial pressure. To cater to this trend, we establish a platform supply chain model by considering a manufacturer with capital constraints that invests in a green production program. Then, it can sell green products via the reselling or the agency channel on a platform and finance from a bank, the platform, or both. In this context, we examine the choices of financial strategies and selling channels from the perspectives of both parties, as well as the corresponding environmental benefit and social welfare. Our findings show that the manufacturer prefers bank financing in most cases when the bank's interest rate is smaller than that offered by the platform. However, in the reselling channel, the manufacturer may choose platform financing even if its interest rate is higher. The platform tends to provide the agency channel when the commission rate is within a reasonable range. It is possible to realize the highest environmental benefit and social welfare in specific regions where both parties agree on the financing and selling modes to maximize their profits. When the manufacturer has only partial access to bank financing, it can choose mixed financing. However, the manufacturer cannot always treat mixed financing as a complete replacement of bank financing.

A Novel Technique to Detect an Optimal Two Layer Supply Chain Model for Imperfect Items Under Various Neutrosophic Environment

A Novel Technique to Detect an Optimal Two Layer Supply Chain Model for Imperfect Items Under Various Neutrosophic Environment

Innovative decision support tools for perishable food supply chain management

PurposeWe introduce decision support tools aimed at optimizing perishable food supply chain management, effectively balancing conflicting objectives such as the exporter’s product collection cost and the importer’s profit. This involves considering factors like perishability, selling price, discount rate, and order quantity to achieve optimal outcomes.Design/methodology/approachThis study considered a three-echelon supply chain comprising farmers, a single exporter, and a single importer providing a single, random-lifetime, perishable product under deterministic customer demand. The proposed mathematical model derived the optimal order quantity, selling price, and discount rate for the entire supply chain. This integrated optimization model treats both demand and supply sides as a multi-objective problem, employing a nonlinear program and a two-stage capacitated vehicle routing problem formulation. Numerical examples and a case study focusing on Thailand durian supply chain were conducted to illustrate the approach of the proposed model.FindingsTaking into account both the importer’s profit and the exporter’s product collection cost, the proposed integrated supply chain model and tools maximize profitability, minimizes waste, and meets demand by optimizing perishable product collection costs and proposing a discount system for selling prices.Research limitations/implicationsLimited to a single perishable product in a three-echelon international food supply chain. Future research can explore different products and supply chain contexts.Practical implicationsThe tools enhance decision-making for supply chain managers, improving efficiency, reducing costs, and enhancing customer satisfaction in the perishable food industry.Social implicationsThe proposed model aids in local workforce management by forecasting required manpower for upcoming seasons. By factoring in product quality and pricing, it ensures customers receive fresh products at fair prices. Furthermore, the near-zero waste concept enhances storage conditions at importers' facilities, contributing to improved environmental hygiene.Originality/valueThe integrated model and decision support tools offer a novel approach to address complexities and conflicting objectives in perishable food supply chains, providing practical insights for researchers and practitioners.

A supply chain finance risk management model for the electric vehicle supply chain: a data-driven analysis

ABSTRACT Government policies and financial regulations, supply chain risk assessments, and technology have made electric vehicle (EV) supply chain challenging for Thailand to adopt and implement (SCF) effectively. This study aims to perform a data-driven analysis that provides insight into SCF risk management and inputs for an EV supply chain. Prior studies are lacking to propose a data driven SCF risk management model and present the model in the EV supply chain. This study proposed a hybrid approach to validate the attributes and formed the hierarchical structure. This study contributes insights into a valid SCF risk management hierarchical structure, identifies the causal interdependent relationships among the attributes, and determines the attributes for the model. The results show that financing risk control and global SCF strategies are needed for improvement. The bullwhip effect, decision-making processes, bank credit, corporate social responsibility, and reverse factoring are important for practices.