Supply Chain Research Research Articles

Conducting engaged logistics and supply chain research: From real‐world problems to journal publication

Conducting engaged logistics and supply chain research: From real‐world problems to journal publication

A Bibliometric Literature Review of Digital Supply Chain: Trends, Insights, and Future Directions

This paper presents a comprehensive bibliometric literature review that aims to analyze and synthesize the existing research on the digital supply chain. By employing a bibliometric approach, this study provides insights into the trends, key research themes, influential authors, and relevant journals in the field of DSC. Furthermore, it explores the geographical distribution of publications, collaboration networks among researchers, and the evolution of research topics. The comprehensive bibliometric analysis of literature in DSC is performed through data visualization and content analysis. Data visualization enables the analysis of publication performance and science mapping by examining prolific journals, authors, countries, influential papers, and conducting citation, co-citation, and bibliographic coupling analyses. Content analysis is carried out by examining the occurrence and clustering of textual data. The bibliometric literature review and content analysis were carried out on 114 documents indexed in the Scopus database, which were selected using the Prisma protocol. The data visualization analysis of the literature review through VOSviewer draws the landscape of scholarly research in the digital supply chain. Based on the research landscape, the content analysis demonstrates the significant effects that the incorporation of digital technology into supply chain management has had on several important research topics. The main research trends in digital supply chain according to the content analysis are: intelligent supply chain management, technologies to drive supply chains performance, circular supply chains, information reliability in supply chains, and sustainable supply chains. The findings of this review highlight the transformative potential of digital technologies in supply chain management and its performance optimization.

The Trend of Halal Cosmetics Supply Chain Research in a Decade: A Systematic Review and Bibliometric Analysis

The Halal cosmetics sector has risen in recent years, and it has received attention from academics and practitioners. Prior works on halal studies have examined food and beverage, but not the supply chain of halal cosmetics. This study aims to explore the distributions and trends of the halal cosmetics supply chain and to identify the gap in this research domain. The integrated systematic literature review and bibliometric analysis were employed to gain insight and evaluate the literature of this study. Based on the reviewed articles, the number of published halal cosmetics supply chain studies is limited. Data were obtained from the Scopus database, resulting in a limited dataset of 58 articles published between 2012 and 2023. Several tools and software were utilized for data extraction and analysis, including Publish or Perish, Excel Spreadsheet, and VOS Viewer. Co-citations analysis and co-words analysis were used to map the trends of publications and distinguish current research potentials. The findings reported the top authors of this research area, the main sub-research areas, and the most cited articles. In addition, new research directions in the realm of halal cosmetics supply chains were offered. Future academics could investigate new study clusters of the halal cosmetics supply chain empirically.

Supply chain management research productivity and topics: 2020–2022

AbstractThis article continues the longest‐standing evaluation of publication productivity in the academic field of supply chain with the combined series spanning 55 years. In this edition, we update the schools and individual scholars producing the most supply chain publications from 2020 to 2022. Despite a new top‐ranked school, the top 10 list remains largely consistent with previous editions, as does the core set of top supply chain doctoral programs. In contrast, the list of the remaining top 25 schools continues to change and includes more international (i.e., non‐U.S.) schools. Additionally, the barriers to entry to become a strong supply chain research school are lower than in the past, while author concentration analyses confirm that the supply chain scholarly field has become more dispersed. Combined, the results support not only highly productive authors and schools with recognition and resource requests but also aspiring authors and schools with their research paths and benchmarking. We voice concerns, however, about both the supply of new supply chain scholars and the decreasing authorship of industry practitioners that had been a staple of our applied field. As a further contribution, we organize the most frequent keywords since 2020 to help scholars identify contemporary and understudied topics.

Optimization algorithm for enterprise supply chain network based on blockchain distributed technology in the context of digital economy

In the era of digital economy, the optimization of enterprise supply chain networks has become a key challenge, while the problems of traditional supply chains, including information asymmetry and lack of trust, seriously hinder the development of enterprise supply chain networks. This paper will use the blockchain distributed technology and the digital economy background to explore how to use the blockchain distributed technology to optimize the existing problems. Firstly, study the supply chain information sharing to develop resources to reduce costs, then use the application of block chain technology and smart contract to establish information sharing mechanism to help the supply chain information more transparent and improve trust; secondly, use the block chain technology decentralized storage model to realize the decentralized supply chain research, and finally use the consensus method to improve the privacy protection of information, to avoid information asymmetry among users. Through experiments, it could be found that the optimization method of enterprise supply chain network based on blockchain distributed technology had a traceability accuracy of over 92.35% for the extracted products, with an average traceability accuracy of 93.791% for 10 products. Research on the transparency of different supply chain information was above 89.73% . By utilizing blockchain distributed technology, information protection in enterprise supply chains could be effectively improved; trust mechanisms could be better established; risk control effectiveness could be improved; optimization of enterprise supply chain networks could be better assisted.

Operating minimally intelligent agent-based manufacturing systems across the Average demand Interval – coefficient of variation (ADI-CV) demand state space

ABSTRACT Minimally Intelligent Agent-Based Manufacturing concerns the provision of agents with the minimal intelligence required to autonomously negotiate and broker work across machines and jobs. The minimal intelligence of agents can be updated in real-time and when coupled with technologies, such as Additive Manufacturing (AM), robotics, automated inventory, and Computer Numerical Control (CNC) affords highly flexible, re-configurable, resilient and responsive systems. The concept has become topical as changes to global supply chains are necessitating a shift to responsive and resilient on-demand manufacturing. However, understanding and characterising how these systems operate under various demand profiles is required to support operators operating these future systems. This paper reports a numerical study into the operating behaviour of minimally intelligent agent-based manufacturing systems operating across the Average Demand Interval and Coefficient of Variation (ADI-CV) demand state space. An established state space used in spare part supply chain research. The results show minimally intelligent manufacturing systems are stable across much of the ADI-CV demand space 85%, 63% and 76–84% for constant, triangular and lognormal manufacturing time distribution profiles respectively. The stability is largely independent of the combination of intelligence. Rather, the combination of intelligence impacts job Time-in-System and system response.

Pricing strategy research in the dual-channel pharmaceutical supply chain considering service.

In the context of developing a new era, the pharmaceutical supply chain market has gradually transformed from a seller's market to a buyer's market. The closer the consumers are, the greater the market pricing power, so the pharmaceutical market power of manufacturers and retailers has also changed. This study considers the effect of service on the pricing strategy of the pharmaceutical platform supply chain. The study aimed to coordinate optimization, and the coordination strategy of the pharmaceutical platform supply chain of complementary products is discussed mainly by researching the price and service factors. Various situations are studied by hypothesis and model solving. This study uses Stackelberg game decision-making. Manufacturers are at the forefront of platform supply chain decisions. The research found that the price was lower under centralized decision-making than under decentralized decision-making. Coordination between price and service levels needs attention in the pharmaceutical platform supply chain of complementary products, and the service level should be controlled within a certain range. Only by improving the service level can enterprises maximize profits, providing a theoretical basis for pharmaceutical supply chain pricing strategy research. Supply chain members must strive to improve service levels to improve medical supply consumers' (patients) psychological satisfaction level. Service levels do not fully mitigate channel conflict. Therefore, pharmaceutical complements have become a way to alleviate the conflicts in the pharmaceutical platform supply chain.

The Role of Collaboration and Digital Technology in Supply Chain Management in Micro Enterprises

Micro businesses have revived, and many have sprung up after the COVID-19 pandemic, including the Coffee Shop micro business. In addition, technological developments in the increasingly rapid digital era have provided nuances and dynamics in research in micro-enterprise supply chains. This study aims to explore supply chain management behavior in micro-enterprises in the era of digital technology. This research contributes to enriching knowledge from research on micro-enterprise agility after the COVID-19 pandemic. This research strategy uses a qualitative approach that allows the author to conduct an in-depth analysis and sort the data into themes. Data was collected from a micro-scale coffee shop in Padang City, North East Coffee Shop. This paper found that (1) the best strategy is to collaborate with small roasteries that are more open to micro-scale coffee shops. (2) The coffee shop micro business has a level of technology adoption to support its operations. This research contributes to enriching knowledge from research on micro-enterprise agility after the COVID-19 pandemic.

More Than Meets the Eye: Misconduct and Decoupling Against Blockchain for Supply Chain Transparency

The fashion industry has consistently ranked high in terms of its association with modern slavery. While scandals like the Rana Plaza incident have focused the world's attention on Asia, in Brazil, over 35,000 people have been rescued from conditions analogous to slavery in the past 15 years. Outsourcing and the underlying social structures that blur the implementation of outsourcing are central to this problem. Fashion supply chains are highly fragmented and labour intensive, exhibiting power asymmetry and informality. Although supply chain research has focused on how focal firms can control or improve supplier practices, this study examines focal firm misconduct and decoupling. Our research presents an intervention aimed at developing a blockchain solution to create a census of fashion working conditions in Brazil. The project included two non-governmental organisations, two fashion brands and their suppliers, the fashion retail association, a blockchain start-up and the research team (18 organisations). We contribute to both theory and practice, revealing that the blockchain's potential to ease transaction costs is outweighed by governance costs related to third-party supervision. We show that focal firms justify unfair purchasing practices via victimisation and diverting attention from themselves to consumers (‘unwilling to pay’) and suppliers (‘not behaving as expected’), unveiling how these drivers of organisational misconduct lead to supplier decoupling (means–end) and focal firm decoupling (policy–practice). Such underlying social structures sustain inaction or, at best, advance focal firms’ visibility of their supply chains while offering no true transparency to the broader society.

Toward a configurational understanding of global supply chain complexity

AbstractIn this editorial for our special topic forum (STF) on Global Supply Chain Research, we present a novel approach that empowers firms to evaluate their supply chain complexity's current state and potentially reveal hidden patterns of complexity. Our focus lies in developing a configurational understanding of global supply chain complexity, leveraging the diverse perspectives, and insights provided by the existing literature on this subject. Furthermore, we shed light on exciting opportunities for future research and introduce the accepted research papers featured in this STF.

Supply chain job and vocational fit: links to supervisor ability, benevolence and integrity

PurposeSupply chain has long faced a persistent workforce shortage. To help both organizations and the field create environments that are more conducive to employee retention, the authors investigate the outcomes of supply chain employee trust in their supervisor.Design/methodology/approachApplying person-environment fit theory, the authors evaluate the well-established antecedents to trust in supervisor ability, benevolence and integrity (ABI) relative to person-job (P-J) fit and person-vocation (P-V) fit of US supply chain employees.FindingsConfirmatory factor analysis indicates that ABI is best modeled as dimensions of a second-order formative trust construct rather than as its antecedents. However, PLS-SEM provides somewhat unconvincing support for the impacts of ABI-trust. Instead, qualitative comparative analysis (QCA) delineates that all three ABI dimensions are not always needed for P-J and P-V fit in supply chain. Some employees respond to affective-based (i.e. benevolence) trust and others to cognitive-based (i.e. ability and integrity) trust.Practical implicationsThe QCA results offer specific recommendations for supply chain organizations to enhance employee trust in supervisors to succeed in the struggle for labor.Originality/valueThe results counter extant trust theory, encouraging scholars to consider ABI as distinct dimensions of trust. The study also demonstrates the importance of considering QCA in supply chain research to meaningfully expand contributions to theory and practice.

Supply chain research based on complex network theory

Supply chain is a chain structure formed by the sequential processes of production and distribution, spanning from raw material suppliers to end customers. An efficient and reliable supply chain is of great significance in enhancing enterprise’s market competitiveness and promoting sustainable social and economic development. The supply chain includes the interconnected flows of materials, resources, capital, and information across various stages, including procurement, production, warehousing, distribution, customer service, information management, and financial management. By representing the various participants in the supply chain as nodes and their interactions—such as the logistics, capital flow, information flow, and other interactions—as edges, the supply chain can be described and characterized as a complex network. In recent years, using complex network theory and methods to model and analyze supply chains has attracted increasing attention from researchers. This paper systematically reviews the supply chain research based on complex network theory, providing an in-depth analysis of supply chain networks in terms of network construction, structural properties, and management characteristics. First, this paper reviews two kinds of approaches to constructing supply chain network: empirical data-based approach and network model-based approach. In the empirical data-based research, scholars use common supply chain databases or integrate multiple data sources to identify the supply chain participants and clarify their attributes, behaviors, and interactions. Alternatively, the research based on network models employs the Barabási–Albert (BA) model, incorporating factors such as node distance, fitness, and edge weights, or uses hypergraph models to construct supply chain networks. Next, this paper summarizes the research on the structural properties of supply chain networks, focusing on their topological structure, key node identification, community detection, and vulnerability analysis. Relevant studies explore the topological structure of supply chain networks, uncovering the connections between nodes, hierarchical structures, and information flow paths between nodes. By analyzing factors such as node centrality, connection strength, and flow paths, the key nodes within the supply chain network are identified. Community detection algorithms are used to investigate the relationships between different structural parts and to analyze the positional structure, cooperative relationships, and interaction modes. Furthermore, quantitative evaluation indicators and management strategies are proposed for the robustness and resilience of supply chain networks. Further research has explored the management characteristics of supply chain networks, including risk propagation and competition game. Relevant studies have employed three main methods—epidemic model, cascading failure model, and agent-based model—to construct risk propagation models, simulate the spread of disruption risks, and analyze the mechanisms, paths, and extent of risk propagation within supply chain networks. These studies provide valuable insights for developing risk prevention and mitigation strategies. In addition, the game theory has been used to investigate the cooperative competition, resource allocation, and strategy selection among enterprises within the supply chain network. This paper reviews the research contents and emerging trends in supply chain studies based on complex network methods. It demonstrates the effectiveness and applicability of complex network theory in supply chain network research, discusses key challenges, such as how to obtain accurate, comprehensive, and timely supply chain network data, proposes standardized data processing methods, and determines the attributes of supply chain network nodes and the strength of their relationships. Furthermore, research on the structure of supply chain network has not yet fully captured the unique characteristics of supply chain networks. Existing models and methods for vulnerability assessment often fail to consider the dynamic and nonlinear characteristics of supply chain networks. Research on risk propagation in supply chains has not sufficiently integrated empirical data, overlooking the diversity of risk sources and the complexity of propagation paths. The asymmetry and incompleteness of information in supply chain networks, as well as multiple sources of uncertainty, make the prediction and analysis of multi-party decision-making behavior more complex. This paper also outlines several key directions for future research. One direction involves using high-order network theory to model interactions among multiple nodes and to describe the dynamics of multi-agent interactions within supply chain networks. Furthermore, integrating long short-term memory (LSTM) methods to process long-term dependence in time-series data can enhance the analysis of network structure evolution and improve the prediction of future states. The application of reinforcement learning algorithms can also adaptively adjust network structures and strategies according to changing conditions and demands, thereby improving the adaptability and response speed of supply chain networks in emergency situations. This paper aims to provide valuable insights for supplying chain research and promoting the development and application of complex network methods in this field.

A systematic literature review of modern slavery in supply chain management: State of the art, framework development and research opportunities

Given increased awareness about modern slavery in supply chain management (SCM), this paper undertakes a systematic literature review (SLR) covering 106 published articles. We first carry out a descriptive analysis, with results showing that modern slavery research is on an upward trajectory but suffers from a lack of primary data and theory application. We then extract themes from the published articles and use them to provide theory elaboration of Gold et al. (2015) model of modern slavery in SCM. Specifically, we introduce business culture and high impact risk factors like pandemics as new institutional factors; highlight external stakeholders like recruitment agents and audit firms as integral to understanding the business context of modern slavery; and add prevention and remediation to detection and response as discrete categories in managing modern slavery risks. We also discuss the gaps in modern slavery research in supply chains. Finally, we propose that reshoring, industry 4.0 and supply chain collaboration represent SCM specialisms that can inform modern slavery research going forward.

Mathematical optimization of the sustainable gasoline supply chain: systematic literature review

Purpose The purpose of this paper is to review studies on mathematical optimization of the sustainable gasoline supply chain to help decision-makers understand the current situation, the exact dimensions of the problem and the models provided in the literature. So, a more realistic mathematical optimization model can be achieved by fully covering all dimensions of the supply chain of this product. Design/methodology/approach To evaluate and comprehend the mathematical optimization of the sustainable gasoline supply chain research area, a systematic literature review is undertaken that covers material collection, descriptive analysis, content analysis and material evaluation steps. Finally, based on this process, 69 related articles were carefully investigated. Findings The results of the systematic literature review show the main areas of the published papers on mathematical optimization of sustainable gasoline supply chain problems and the gaps for future research in this field presented based on them. Research limitations/implications This approach is subject to limitations because the protocol of the systematic review of the research literature only included searching for the considered combination of keywords in the Scopus and ProQuest databases. Furthermore, the protocol used in this paper restricts documents to English. Practical implications The results have significant implications for both academicians and practitioners in this field. It can be useful for academics to comprehend the gaps and future trends in this field. Also, for practitioners, it can be useful to identify and understand the parts of the mathematical optimization model, which can help them model this problem effectively and efficiently. Originality/value No systematic literature review has been done in this field by considering gasoline to the best of the authors’ knowledge and delivers new facts for the future development of this field.

Intelligent selection of healthcare supply chain mode - an applied research based on artificial intelligence.

Due to the inefficiency and high cost of the current healthcare supply chain mode, in order to adapt to the great changes in the global economy and public health, it is urgent to choose an effective mode for sustainable development of healthcare supply chain. The aim of this paper is to use artificial intelligence systems to make intelligent decisions for healthcare supply chain mode selection. Firstly, according to the economic benefits, social benefits and environmental benefits of healthcare supply chain, this paper identifies different healthcare supply chain modes in combination with artificial intelligence technology. Secondly, this paper presents the intelligent choice optimization method of healthcare supply chain mode based on deep reinforcement learning algorithm. Finally, the effect of artificial intelligence in healthcare supply chain mode selection is verified by simulation experiment. The experimental results show that healthcare supply chain mode selected by artificial intelligence is basically consistent with the target mode, while healthcare supply chain mode selected by the basic selection method, BP neural network method and big data method is different from the target mode, which indicates that AI has more advantages in the selection of medical supply chain mode. Therefore, we recommend the application of artificial intelligence to healthcare supply chain management. This study not only makes up for the ineffective problems of existing methods, but also makes up for the gaps in the application of AI technology in the field of healthcare supply chain. The scientific value of this paper is that the proposed framework and the artificial intelligence algorithm enrich the relevant theories of healthcare supply chain research and provide methodological guidance for intelligent decision-making of healthcare supply chain. At the same time, for medical enterprises, this research provides a new practical guideline for the application of artificial intelligence in the sustainable development and modern management of healthcare supply chain.

The influences of boundary spanning capabilities and long–term orientation on opportunism in inter–firm relationships

ABSTRACT Opportunism is a common issue in inter – firm relationships, which increases transaction costs, impairs firm performance and supply chain efficiency, and deteriorates relationship quality. Previous studies have intensively investigated factors influencing opportunism but overfocusing on the organisational level. Recently, supply chain researchers have called for identifying factors influencing opportunism at the individual level to gain a more comprehensive understanding of opportunism. Based on transaction cost theory, resource dependence theory, and boundary spanning theory, this study seeks to advance the emerging research stream on opportunism at the individual level by investigating how buyer agents’ boundary spanning capabilities and firms’ long – term relationship orientation can help manage supplier agents’ opportunism. Using a cross – sectional data set of 406 buyer agents from manufacturing companies collected from February to April 2021 in Japan, we tested a set of hypotheses through regression and conditional process analyses. Our findings suggest that buyer agents’ strategic communication and firms’ long – term relationship orientation are critical factors that reduce supplier agents’ opportunism.

Seeing with fresh eyes – the potential of paradox theory to explore persistent, interdependent tensions in supply chains

PurposeThis study explores the potential of paradox theory as a novel theoretical lens to investigate persistent and interdependent tensions in supply chains. It is based on a critical literature review focusing on paradoxes observed within complex supply chains in dynamic business environments, including the articles selected for this special issue, “Environmental Dynamism and Supply Chain Complexity: Managing the Paradoxes.”Design/methodology/approachThis study introduces the key concepts and themes of the paradox theory literature and possible methodological approaches to studying paradoxes in supply chains. Through a literature review, this study also reflects on the current state of paradox research in the field of operations and supply chain management (OSCM) and proposes future research questions.FindingsThe application of paradox theory to OSCM research is in its early stages. This paper presents opportunities to explore persistent and interdependent tensions in supply chains using paradox theory.Research limitations/implicationsThe paper suggests several new research questions that should be translated into more precise propositions. The main implication for research is a call to focus attention on how and why a paradox perspective can help supply chain researchers view complex supply chain problems with fresh eyes.Originality/valueThe study provides the first critical review of paradoxical tensions in OSCM research. While the papers in this special issue contribute significantly to a better understanding of these issues, there is still significant potential for understanding how to respond to paradoxes in supply chains.

A systematic literature review exploring and linking circular economy and sustainable development goals in the past three decades (1991–2022)

Amid the escalating environmental crises and economic disparities, Circular Economy (CE) has garnered recognition as a pragmatic mechanism for achieving Sustainable Development Goals (SDGs). In response, several supply chain organisations are integrating CE strategies into their business operations and production processes. Despite these developments and since the introduction of Business Charter for Sustainable Development by the International Chamber of Commerce in 1991, the academic corpus comprehensively connecting CE research themes, catalysts, deterrents, practices with the SDGs has remained limited. To bridge this gap, we present a systematic literature review (SLR) of CE research in operations, supply chain and production management encompassing a time span of 31 years (January 1991 – June 2022), by sourcing, screening, and analysing articles obtained from multiple research databases. Our thematic coding analysis generated ten research themes, and subsequently linking them with relevant SDGs. Additionally, we interweaved CE catalysts and deterrents, establishing a connection with the SDGs. This is further enriched with CE strategies aimed at equipping business practitioners to enhance sustainable business performance and contributing to specific SDGs. Lastly, we delineate CE knowledge data management and priority actions frameworks to aid organisations to enhance employee capability and actively leverage digital technologies for implementing CE strategies.

Future research of supply chain resilience: Network perspectives and incorporation of more stakeholders

In recent years, global supply chains face great challenges driven by events such as trade wars, the Covid-19 pandemic, and the Russia-Ukraine War. Since the disruptions caused by such shocks are more systematic and the duration is harder to predict compared to natural disasters or other operational risks, we highlight two features for future supply chain research: network perspectives and incorporation of more stakeholders such as governments that can influence overarching performances of industrial and supply chains. From the network perspective, we review the literature on vulnerable nodes & links identification, risk propagation modeling, network resilience measures, and disruption mitigation strategies. We suggest promising research directions such as deriving non-probabilistic resilience measures that can incorporate dynamics, extending existing methods for bottleneck detection to the network setting, balancing efficiency and resilience in a more sophisticated way, etc. In terms of incorporating more stakeholders’ roles in supply chain network decisions, we review the relevant literature and discuss research opportunities on governments’ roles in global supply chains (i.e., an external circulation perspective) and in incentivizing firms’ R&D and stimulating domestic demand (i.e., an internal circulation perspective). We suggest topics including global supply chain resilience evaluation using trade networks, technology networks, and firm ownership networks, the impact of trade policies with network perspectives, design of tariff and non-tariff measures under trade agreements, domestic industry relocation, evaluating the effects of government subsidies on firms’ long-term innovation, and design of subsidy strategies for supply chain stability and resilience. We believe research on supply chain resilience will thrive in the years ahead, better supporting firms’ and governments’ decisions.

Generic technology R&D strategies in dual competing photovoltaic supply chains: A social welfare maximization perspective

In the context of global warming, photovoltaic (PV) industry is growing rapidly to advance carbon neutrality. A new generation PV technology based on perovskite solar cells has attracted high attention from the industry due to its advantage of low cost and high photoelectric conversion efficiency, and has gradually carried out relevant technology research and development (R&D), as well as small and medium-sized product trials. However, there are still some generic technical issues with perovskite solar cells, such as the stability of large area preparation, efficiency over large areas, and long service life under high efficiency. Collaborative R&D around generic technologies among module suppliers across PV supply chains will help create complementary synergies and accelerate breakthroughs in generic technologies. To explore R&D strategies and subsidy policies for the generic technology in competing PV supply chains, twelve game-theoretical decision models considering cooperative/non-cooperative R&D with/without government subsidy under four scenarios are developed, analyzed and compared respectively. The research results indicate that: (i) in all four scenarios, the adoption of a centralized operational strategy is more effective in terms of government subsidies and the operational performance of the PV supply chains than a hybrid or decentralized operational strategy. (ii) the government should adopt an appropriate subsidy intensity for the dual-competing PV supply chains and set a “threshold” subsidy policy. (iii) the positive externality of R&D effort has a positive spillover effect on profits, social welfare and other indicators. The positive externality of R&D effort for the generic technology can be better exploited by the two PV supply chains jointly deciding on the level of R&D expenditure and by the government providing financial subsidy support. This study is a pioneering study of dual competing PV supply chains in terms of cooperative R&D of generic technology, which is very limited in the PV supply chain management and subsidy policy research literature. The findings and some unnoticed issues in this paper provide a basis for future PV supply chain research.