Supply Chain Model Research Articles

Supply chain optimization: bibliometric analysis, research structure and future outlook

Purpose Supply chain (SC) research has boomed over the past two decades. Significant contributions have been made to the field from various analytical and decision-making perspectives. This paper, a comprehensive bibliometric study, aims to identify the key research contributors, institutions and themes. Design/methodology/approach A comprehensive knowledge domain visualization of over 1,000 articles, published between 2000 and 2022, is carried out to construct a bird’s eye view of the field in terms of research production, key authors, main publication outlets, geographic disparity of the contributions and emerging research trends. Additionally, collaboration patterns among researchers and institutions are mapped to highlight the communication networks underlying research initiatives. Findings Results show an explosive growth in the number of articles tackling supply chain optimization (SCO) issues with a significant concentration of the contributions in a relatively small cluster of authors, journals, institutions and countries. Among the many important findings, our analysis indicates that mixed-integer linear programming is the most commonly used model, while robust optimization is the method of choice for handling uncertainty. Furthermore, most SC models are developed at only one level of the organizational hierarchy and consider only one planning horizon. The importance of developing integrated SCO systems is key for future research. Originality/value The study fills the optimization techniques gap that exists in SC management bibliometric studies and presents a thematic map for the SCO research highlighting the various research foci.

Analyzing and Controlling chaos phenomena in fractional chaotic supply chain models

Supply Chain Management (SCM) is a critical business function that involves the planning, coordination, and control of the flow of goods, information, and finances as they move from the manufacturer to the wholesaler to the retailer and finally to the end customer. SCM is a holistic approach to managing the entire process of delivering products or services to consumers. In this study, we will enhance the findings as outlined in Anne et al. (2009). While certain attributes of these systems will have been investigated, numerous aspects of these systems will still require further scrutiny. This calls for additional research studies on these systems. This paper examines a Fractional-Order Supply Chain Management (FOSCM) model utilizing the Adomian Decomposition Method (ADM) and explores qualitative aspects through an approach that addresses existence and uniqueness. By using Arzelà–Ascoli's principle, this system proves that the Caputo FOSCM model has at least one solution. Furthermore, we investigate the dynamics of the system by using the Lyapunov Exponent (LE), Bifurcation Diagram (BD), Complexity Analysis (CA) and 0–1 test. Finally, we introduce the control for FOSCM model using the Linear Feedback Control (LFC) method. We verify the correctness of our analysis by using numerical simulations.

The quality admission and price decisions of production capacity on the third‐party platform for shared manufacturing

AbstractMany third‐party platforms for shared manufacturing (platforms) have developed rapidly in recent years. The quality admission and pricing of production capacity are crucial issues for these platforms. This paper focuses on the platform supply chain composed of a platform, multiple manufacturers with surplus production capacity (sharers), and multiple manufacturers with insufficient production capacity (renters). Considering the impact of the production capacity quality on the shared scale and rental demand of production capacity, this paper constructs a game model for the platform supply chain under different quality admission scenarios, investigates the quality admission and price decisions of production capacity on the platform, and analyses the impact of the quality admission on the sharers’ and renters’ profits. The results show that the platform sets the quality admission when the sharers’ production capacity scale is small and the platform regulatory cost is low. The platform always increases its service price but may reduce the rental price of production capacity under the quality admission scenario. When the sharers’ production capacity scale is large, the platform lowers the threshold of quality admission with the quality elasticity of production capacity increasing. In addition, when the quality elasticity of production capacity and platform regulatory cost are low, and the sharers’ production capacity scale is small, the quality admission of the platform realizes the win–win–win situation for the platform, renters, and sharers.

An integrated academic library supply chain (IALSC) model

Purpose This exploratory study illustrated an integrated academic library supply chain (IALSC) model to design the strategic planning management tool of the academic library. The supply chain (SC) model has been widely used in manufacturing industries and has also been applied in many service industries with the same objectives. However, very few studies for academic libraries, particularly the implementation of the integrated SC model, are being executed, although it has been proven that SC management in practice can enhance stakeholder satisfaction, increase revenues and decrease total costs. The academic library also needs to be successful in providing quality products, services and information to fulfil the library users’ needs within the library budget. This research aims to develop a verified model of the integrated SC for the academic library. Design/methodology/approach This research used both qualitative and quantitative approaches to achieve its objectives. The proposed conceptual SC model, named as IALSC, for the academic library has been developed using the system thinking method; eventually, it has been validated through the fuzzy Delphi method, an expert judgement technique. Findings The research findings could contribute to academic library management in planning and formulating a roadmap for the library to increase its quality services for all stakeholders. Originality/value The conceptual model would have a high potential to be proposed as the strategic decision-making tool for an academic library, i.e. the flow of funds through the operations of the library, the library stakeholders’ satisfaction measurement, the decision process currently made by the library management team on the purchase of new library resources, the library resource suppliers, etc.

Reviewing the Roles of AI-Integrated Technologies in Sustainable Supply Chain Management: Research Propositions and a Framework for Future Directions

In the post-pandemic era, the uncertain global market and rising social-environmental issues drive organizations to adapt their supply chain strategies to more dynamic, flexible models, leveraging advanced technologies like AI, big data analytics, and decision support systems. This review paper aims to examine the current research on AI-integrated technologies in sustainable supply chain management (SSCM) to inform future research directions. We adopted bibliometric and text analysis, targeting 170 articles published between 2004 and 2023 from the Scopus database following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) protocol. We confirm that AI-integrated technologies have demonstrated the capability to enable SSCM across various sectors. We generated ten future research topics using the Latent Dirichlet Allocation (LDA) method and proposed 20 propositions. The results show that AI-integrated technologies in supply chain processes primarily address sustainability, focusing on environmental and economic issues. However, there is still a technological gap in tackling social issues like working conditions and fair dealing. Thus, we proposed a dynamic framework of AI in SSCM to help researchers and practitioners synthesize AI-integrated technologies in SSCM and optimize their supply chain models in future directions.

A multinational firm’s global manufacturing location and outsourcing strategies

Due to rising labor costs in China and trade friction, many multinational firms (MNFs) consider moving manufacturing outside China to Southeast Asian Countries. Based on observations in real world, we build a three-tier supply chain model consisting of one component supplier, two contract manufacturers (CMs), an MNF, and a local original equipment manufacturer (OEM). The MNF monopolizes the market in country 1 (e.g., U.S.), but competes in country 2 (e.g., China) with the local OEM. The component supplier and one CM are located in country 2, and the other CM is located in country 3 (e.g., a country in Southeast Asia). We investigate the MNF’s global manufacturing location and procurement outsourcing strategies with considerations of tariffs and market environments. Currently, the MNF outsources its manufacturing to the CM in country 2, and decides whether to continue the cooperation with the current CM or develop a new CM in country 3. The MNF also considers whether to outsource its component procurement to the corresponding CM. Our study reveals that the MNF’s optimal strategy depends on the relative market sizes, the fixed cost of developing a new CM, as well as the manufacturing cost and tariff disadvantages in country 2. Interestingly, we find that the tariff disadvantage in country 2 does not always motivate the MNF to cooperate with the CM in country 3. Instead, an appropriate tariff may be beneficial to the MNF that manufactures in country 2. In addition, the MNF’s preferred procurement strategy is related to its manufacturing location. When cooperating with the CM in country 2, the MNF would switch from direct procurement to outsourced procurement as the market size of country 1 increases.

Conceptual foundations of Tech-Driven logistics and supply chain management for economic competitiveness in the United Kingdom

The concept paper explores the transformative potential of technology in enhancing the logistics and supply chain sector to bolster the UK's economic competitiveness. This executive summary highlights the paper's primary objectives, theoretical frameworks, and anticipated outcomes, focusing on the integration of advanced technologies to streamline supply chain operations and drive economic growth. This paper aims to provide a comprehensive framework for understanding how technology can be leveraged to optimize logistics and supply chain management in the UK. It underscores the importance of a robust and efficient supply chain as a cornerstone of economic competitiveness, enabling businesses to reduce costs, improve delivery times, and enhance overall operational efficiency. Central to this paper is the exploration of various technological innovations that can revolutionize supply chain management. It discusses the impact of emerging technologies such as the Internet of Things (IoT), artificial intelligence (AI), blockchain, and big data analytics on the logistics sector. These technologies enable real-time tracking, predictive analytics, enhanced transparency, and improved decision-making processes, which are crucial for maintaining a competitive edge in the global market. The paper delves into theoretical models and frameworks that support the integration of technology into supply chain management. It examines concepts such as the Digital Supply Chain (DSC) model, which emphasizes the interconnectedness of digital technologies in creating a seamless supply chain network. Additionally, the paper explores the Supply Chain Operations Reference (SCOR) model, which provides a structured approach to measuring and improving supply chain performance through technology-driven metrics and best practices. Addressing the practical challenges of implementing tech-driven logistics, the paper highlights issues such as cybersecurity risks, high initial investment costs, and the need for skilled labor. It proposes solutions like fostering public-private partnerships, investing in cybersecurity measures, and developing training programs to build a tech-savvy workforce capable of managing advanced supply chain systems. The expected outcomes of tech-driven logistics and supply chain management include increased operational efficiency, reduced operational costs, improved customer satisfaction, and enhanced agility in responding to market changes. These improvements can significantly contribute to the UK's economic competitiveness, positioning it as a leader in the global supply chain landscape. The paper provides a strategic roadmap for integrating advanced technologies into the logistics sector. By leveraging these technologies, the UK can enhance its supply chain efficiency, drive economic growth, and maintain a competitive advantage in the global economy. The paper calls for concerted efforts from policymakers, industry leaders, and academia to foster an environment conducive to technological innovation and supply chain excellence. Keywords: Logistic, Supply Chain, Technology, Cyber Security, UK.

Dual channel closed-loop supply chain coordination with exchange policy, sales efforts and green innovation under uncertain market

ABSTRACT This paper explores a dual-channel supply chain within an uncertain environment where a manufacturer produces a green product and a retailer makes sales efforts to attract a higher customer base. Moreover, we incorporate a reverse supply chain model in which the manufacturer retrieves end-of-used products from customers through a collection initiative. Simultaneously, the retailer gathers end-of-used products from customers by implementing an exchange policy facilitated through a coupon applied to the product’s selling price. Then, we explore centralized, manufacturer Stackelberg, option contracts and cost-sharing contracts strategies to maximize supply chain profits under various circumstances. Subsequently, a numerical example is undertaken to showcase the utility of the models and explore sensitivity that examines how different parameters impact the supply chain’s profit. Findings suggest that the supply chain members will be profitable if they engage in the option contract model under a suitable value of the option price and exercise price.

Sales promotion and supply chain finance for shopping days: Strategies of e‐commerce platform and seller

AbstractIn shopping days, e‐commerce platforms (ECPs) and their sellers cooperate to promote sales through price discount and marketing effort. Supply chain finance (SCF) has been offered by ECPs to fuel sellers' preparations for shopping days. An ECP‐seller supply chain (PSSC) model is constructed to study the strategic interaction between the ECP and the seller. Given a price discount rate, we derive the ECP's optimal marketing effort level and feasible SCF service rule, as well as the seller's optimal supply quantity and financing decisions. Furthermore, we identify a price‐discount‐rate interval, in which the Pareto improvement of the PSSC can be achieved.

Internet of behaviors: conceptual model, practical and theoretical implications for supply chain and operations management

The Internet of Behaviours (IoB) is a network designed and used for replicating, understanding, predicting, and influencing human behaviour through data analytics. This study aims to advance our understanding of how the IoB will impact supply chain and operations management (SCOM). Based on a combination of the existing IoB frameworks with industrial Metaverse and digital supply chain twins, we propose a framework for IoB in SCOM encompassing management, organisation, and technology dimensions. We conclude that the IoB will impact a multitude of SCOM areas such as supply chain design, demand forecasting, sales and operations planning, distribution and transportation, inventory and production management, sourcing strategy and purchasing, vehicle routeing, supply chain resilience and sustainability. We offer a structured future research agenda pointing to new research questions and topics stemming from IoB-driven real-time visibility, data analytics, and remote control. Methodology of SCOM can also be enriched by the IoB through a combination of artificial intelligence and digital technology with operations research and behavioural operations management.

Integrated resilient and sustainable gasoline supply chain model with operational and disruption risks: a case study of Iran

Integrated resilient and sustainable gasoline supply chain model with operational and disruption risks: a case study of Iran

Decision-Making Approach to Design a Sustainable Photovoltaic Closed-Loop Supply Chain Considering Market Share for Electric Vehicle Energy

This study aims to develop a model for the closed-loop supply chain of photovoltaic (PV) systems. The primary objective addresses strategic and tactical decision-making using a two-stage approach. To pinpoint suitable locations for solar power plants, the PROMETHEE II method is utilized, which is a component of multi-attribute decision making (MADM) approaches. Next, a multi-objective modeling of the closed-loop PV supply chain is conducted. This model aims to minimize total supply chain costs, reduce environmental impacts, mitigate adverse social effects, maximize the on-time delivery (OTD) of manufactured products, and maximize market share. Additionally, a robust fuzzy mathematical model is introduced to examine the model’s sustainability under various uncertainties. An evaluation of the effectiveness and utility of this model is conducted in Tehran city. Furthermore, a comprehensive analysis of various supply chain costs indicates that production centers have the highest costs, while separation centers have the lowest costs.

A novel BWM-entropy-COPRAS group decision framework with spherical fuzzy information for digital supply chain partner selection

The transformation and upgrading of traditional supply chain models through digital technology receive widespread attention from the fields of circular economy, manufacturing, and sustainable development. Enterprises need to choose a digital supply chain partner (DSCP) during the process of digital transformation in uncertain and sustainable environments. Thus, the research constructs an innovative decision methodology for selecting the optimal DSCP to achieve digital transformation. The proposed methodology is propounded based upon the entropy measure, generalized Dombi operators, integrated weight-determination model, and complex proportional assessment (COPRAS) method under spherical fuzzy circumstances. Specifically, a novel entropy measure is proposed for measuring the fuzziness of spherical fuzzy (SF) sets, while generalized Dombi operators are presented for fusing SF information. The related worthwhile properties of these operators are discussed. Further, an integrated criteria weight-determination model is presented by incorporating objective weights obtained from the SF entropy-based method and subjective weights from the SF best worst method. Afterward, an improvement of the COPRAS method is proposed based on the presented generalized Dombi operators with SF information. Lastly, the practicability and validity of the proposed methodology are verified by an empirical study that selects an appropriate DSCP for a new energy vehicle enterprise to finish the goal of digital transformation. The sensitivity and comparative analysis are carried out to illustrate the stability, reliability, and superiority of the propounded methodology from multiple perspectives. The results and conclusions indicate that the propounded method affords a synthetic and systematic uncertain decision-making framework for identifying the optimal DSCP with incomplete weight information.

Supply chain model having stochastic lead time demand with variable production rate and demand dependent on price and advertisement

In this present study, a single-manufacturer and single-retailer supply chain management model are formulated for a single product. This study specifically looks at a supply chain with variable production rate, stochastic lead time demand, and price- and advertisement-dependent demand. By incorporating these complex aspects into a model, which enables to examine their combined effects on supply chain performance, this study adds to the body of knowledge. The study reveals unique insights into the complex interplay between pricing tactics, advertising efforts, production dynamics, and the variability brought on by stochastic lead times through meticulous study and modelling. Finally, the total system profit is calculated and optimized with all the decision variables. A classical approach is performed to obtain the optimized solution of the joint profit function along with the decision variables. Two models are discussed in the study: (1) the model with normally distributed lead time demand and (2) the model with distribution-free lead time demand. The joint profit of the supply chain is found to be lesser by 1% for the normally distributed lead time demand than the distribution free pattern. The comparison of the shipment policies and the safety factors for the different distribution patterns of the lead time demand are shown. Though the huge increment in the safety factor for unknown leadtime demand distribution may help in reducing the uncertainity factor and disruptions in the supply chain, but also it may unnecessarily tie up more capital which can be invested in other sectors of the supply chain.

The conceptual model of Indonesian palm oil supply chain based on blockchain

Abstract Indonesia is the world’s largest producer and consumer of palm oil. However, the palm oil supply chain faces numerous challenges related to actors, traceability, transparency, and sustainability. To address these issues, a conceptual model for a blockchain-based palm oil supply chain in Indonesia is proposed. The model aims to leverage the decentralized and immutable nature of blockchain technology. It incorporates components such as smart contracts, distributed ledgers, and data sharing mechanisms to enhance traceability, transparency, and sustainability in the palm oil supply chain. The research utilized the SSM (Soft System Methodology) and CATWOE (Customer, Actor, Transformation, Worldview, Owner, Environment) methodologies. The actors involved in the palm oil supply chain include smallholders, plantation companies, third-party suppliers, middlemen, traders, palm oil mills, refineries, distributors, retailers, and consumers. The blockchain conceptual model is structured based on a sustainable supply chain model that considers economic, social, and environmental aspects. Blockchain transactions regulate the process of supply chain actors, while stakeholders such as the government, financial institutions, palm oil research organizations, NGOs, and consumers are involved. The blockchain-based supply chain model is expected to address the key issues of the palm oil supply chain, aiming for a sustainable supply chain system. By implementing this model, it is anticipated that the palm oil industry can achieve greater accountability, transparency, and environmental sustainability.

Dual-channel decision models for the transnational supply chain considering strategic inputs and compensation

Based on a transnational dual-channel supply chain consisting of the domestic manufacturer and retailer, this paper constructs four models, namely, the without tariff model, the tariff model, the retailer’s strategic inputs model, and the manufacturer’s compensation model, to investigate the impact of the tariff imposing on supply chain decisions, the effect of the retailer’s strategic inputs to hedge against tariffs, and the incentive effect of the manufacturer’s compensation. The results show that the tariff imposed by the foreign government leads to higher product prices and lower sales volumes, resulting in welfare losses for foreign consumers. When the domestic retailer makes strategic inputs, the prices of products in the foreign market decrease and the sales volumes increase, which increases the profits of the domestic retailer and manufacturer and improves the welfare of foreign consumers. The equilibrium solutions of the models also show that the manufacturer has an incentive to compensate the retailer for its strategic inputs; when the manufacturer compensates for the retailer’s strategic inputs, the profit of the retailer and the manufacturer will be improved again, and thus, the whole supply chain will achieve Pareto improvement.

Utilizing CNN2D for regressor analysis and time series forecasting & modelling of the foods demand supply chain

Utilizing CNN2D for regressor analysis and time series forecasting & modelling of the foods demand supply chain

Research on dynamic pricing and coordination model of fresh produce supply chain based on differential game considering traceability goodwill

This study aims to solve the current pricing and coordination problems in the fresh produce supply chain by proposing a dynamic pricing and coordination differential game model based on traceability goodwill to optimize the operational efficiency and profitability of the supply chain. Freshness and traceability are critical consumer trust and brand value factors incorporated into the dynamic pricing and coordination model in the agricultural supply chain. The research methodology of this paper integrates critical factors such as supply chain cost and market demand to construct a comprehensive differential game model. It also highlights the motivation of dynamic pricing strategy and coordination mechanism based on traceability goodwill. Through traceability goodwill, operating companies can better assess and manage product quality and improve consumer trust in agricultural products, thus enhancing brand value. The dynamic pricing strategy based on traceability goodwill can flexibly adjust prices according to changes in the quality characteristics of agricultural products and market demand, realizing a dynamic balance between supply and demand. On the other hand, the mutual cost-sharing and coordination mechanism promotes the synergy between the various links of the supply chain. It improves overall efficiency through cooperation coo, coordination, and other means. The validity and reliability of the model are verified through numerical simulation experiments. The numerical simulation results show that the dynamic pricing and coordination model based on traceability will significantly improve supply chain efficiency and profitability compared with the traditional model. Specifically, the interests of supply chain participants are balanced, and the overall supply chain operational efficiency is improved. The main contribution of this study is to propose a dynamic pricing and coordination model based on traceability goodwill and verify its superiority through numerical simulation experiments. This study provides a valuable reference for fresh agricultural products supply chain management and offers new ideas for improving supply chain efficiency and profitability.

An integrated planning approach for perishable goods with stochastic lifespan: Production, inventory, and routing

This paper focuses on addressing the crucial challenges posed by the uncertainty surrounding perishable goods within the supply chain. With staggering socioeconomic costs and significant environmental implications, effective management of perishable goods emerges as a critical imperative. Globally, the annual loss of approximately 14% of food, amounting to a staggering USD 1 trillion, highlights the urgency of the issue. However, Prevailing classification methods for perishable products oversimplify their complexity by dividing them into fixed or variable lifespans, neglecting the random lifespans endured due to fluctuating storage conditions, blurring traditional boundaries between fixed and variable classifications. In response to these pressing challenges, the research proposes a novel approach: the development of a nonlinear mixed-integer programming model for a green closed-loop supply chain. This innovative model seamlessly integrates production, inventory, and routing decisions for both main and secondary products of a manufacturer. Moreover, it optimizes order splitting and transportation modes to efficiently convert perished items into raw materials under conditions of uncertainty. Central to the approach is the adoption of a scenario-based methodology to model uncertainties, particularly focusing on the variability in the lifespan of perishable products. This approach allows for a more nuanced understanding of the complex dynamics inherent in managing perishable goods within the supply chain. To solve the proposed model, a novel hybrid algorithm is introduced: the Particle Swarm Optimization (PSO) and Simulated Annealing (SA) algorithm, or PSOSA, ensuring robust optimization under uncertainty and enhancing decision-making within the perishable goods supply chain. The research findings underscore the inadequacy of prevailing assumptions regarding the fixed lifespan of perishable products, commonly observed in the literature. By accounting for uncertainty in perishable goods’ lifespan, a more accurate representation of total producer costs is achieved, highlighting the misleading reduction of 25% observed when neglecting such uncertainty.

Linear Programming Model for Sunflower Oil Supply Chain Network

Food supply networks are vital to the global economy, producing and consuming products worldwide. Supply chain management (SCM) has emerged as a crucial technique to optimize the integrated network of suppliers, factories, warehouses, customers, and distribution channels. SCM aims to ensure efficient raw material sources, transformation, transportation, and timely customer delivery. Edible oil, a crucial ingredient for cooking and food preparation, is utilized by people from all social classes. Vegetable oils, particularly sunflower, soybean, peanut, and others, are the main source of edible oils, which have less unsaturated fatty acids compared to animal oils. The production and consumption of edible oils have substantial environmental impacts, necessitating increased research to address these implications. Sunflower, a valuable oilseed crop, is grown worldwide due to its short growing season and adaptability to various climates and soil types. Sunflower seeds have high oil and protein content, making them popular for their health benefits. This article uses a linear optimization model for the sunflower oil supply chain from the farmer to the end user. The objective is to minimize the overall transportation cost subject to capacity, demand fulfillment, and waste management.