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The purpose of this paper is to propose a risk-sharing model to coordinate the decision-making behavior of players in a cassava-based bioethanol supply chain under random yield and demand environment, so as to mitigate the yield and demand uncertainty risk and improve the bioethanol supply chain resiliency and performance.

The decision-making behavior under three models, namely, centralized model, decentralized model and risk-sharing model, are analyzed. An empirical test of the advantages and feasibility of the proposed risk-sharing model, as well as the test of yield uncertainty risk, risk-sharing coefficients and randomly fluctuating cassava market price on the decision-making behavior and performances are provided.

Though the proposed risk-sharing model cannot achieve the supply chain performance in the centralized model, it does help to encourage the farmers and the company to increase the supply of cassava and achieve the Pareto improvement of both players compared to the decentralized model. In particular, these improvements will be enlarged as the yield uncertainty risk is higher.

The findings will help decision makers in the bioethanol supply chain to understand how to mitigate the yield uncertainty risk and improve the supply chain resiliency under yield and demand uncertainty environment. It will also be conducive to ensure the supply of feedstock and the development of the bioethanol industry.

The proposed risk-sharing model incorporates the yield uncertainty risk, the random market demand and the hierarchical decision-making behavior structure of the bioethanol supply chain in the model.

The purpose of this paper is to examine pre-entry resources and capabilities (R&Cs) of de alio and de novo entrants in an emerging industry. Then, the authors investigate how entrants modify their firm boundaries, after entering a new industry, to acquire the R&Cs deemed critical to be competitive and survive in the industry.

The analysis uses the global biofuel industry as a case study. The authors use multiple sets of data, including primary data collected from semi-structured interviews with industry stakeholders and experts across major biofuel-producing countries as well as quantitative data from industry reports.

Firms typically deploy two successive strategies in order to survive and grow. First, they extend vertical boundaries to capitalize on their own pre-entry R&Cs. Then they move quickly to acquire new R&Cs, which are classified as critical in the value chain of the industry. A new taxonomy of pre-entry R&Cs is proposed to distinguish critical and non-critical forms of R&Cs, and to reflect the ease of acquisition of any requisite R&Cs, which are context specific. These strategic moves lead to the bi-directional vertical integration observed in the biofuel industry.

Managers need to be able to assess the opportunities for entry and subsequent strategies to be competitive by assessing their R&Cs in terms of criticality and ease of acquisition in their entry decision making.

A new taxonomy of R&Cs of the firm is proposed which has theoretical significance and practical implications for new entrants.

Businesses are increasingly vulnerable and exposed to physical climate change risks, which can cascade through local, national and international supply chains. Currently, few methodologies can capture how physical risks impact businesses via the supply chains, yet outside the business literature, methodologies such as sustainability assessments can assess cascading impacts.

Adopting a scoping review framework by Arksey and O'Malley (2005) and the PRISMA extension for scoping reviews (PRISMA-ScR), this paper reviews 27 articles that assess climate risk in supply chains.

The literature on supply chain risks of climate change using quantitative techniques is limited. Our review confirms that no research adopts sustainability assessment methods to assess climate risk at a business-level.

Alongside the need to quantify physical risks to businesses is the growing awareness that climate change impacts traverse global supply chains. We review the state of the literature on methodological approaches and identify the opportunities for researchers to use sustainability assessment methods to assess climate risk in the supply chains of an individual business.

This paper provides a practical framework for managers to develop a sustainable supply chain. Given that rapid globalization has increased supply disruption risk, managers have been forced to establish efficient and responsive supply chain strategies. Nevertheless, diverse uncertainty factors, such as risk perception of strategies, have made practical management difficult. Quantifying managers' risk perceptions and applying them to supply chain strategies allows the authors to propose a structural and practical model for managing supply disruption.

The existing structural model is refined by taking subjective factors into account using the analytic hierarchy process. The applicability of the refined model is demonstrated through a comparative case study.

Managers' risk perceptions vary not only among companies but also between managing divisions within a company, which necessitates possible changes in strategy due to environmental turbulence. The principal component analysis (PCA) characterizes managers' risk perceptions that illustrate companies' emphases on disruption risk.

The proposed approach quantifies risk perception, which enables practitioners to deal with subjective information in quantitative form. Comparative studies clarify differences in perception given different business backgrounds. The results provide managers with in-depth insights for establishing supply chain strategies reflecting their risk perception.

Quantification of managers' subjective risk perception clarifies both the trend and the individual features for uncertainties. The results allow the authors to conduct the PCA, which characterizes companies. Comparative studies generalize the results of extant work, shedding light on cross-sectional differences given different business backgrounds. The effectiveness of the approach is confirmed through retrospective interviews with practitioners.

The design of a biomass supply chain is a problem where multiple stakeholders with often conflicting objectives are involved. To accommodate the aspects stakeholder, the supply chain design should incorporate multiple objectives. In addition to the supply chain design, the management of energy from biomass is a demanding task, as the operation of production of biomass products needs to be aligned with the rest of the operations of the biomass supply chain. The purpose of the paper is to propose a mathematical framework for the optimal design of biomass supply chain.

An integrated mathematical framework that models biomass production, transportation and warehousing throughout the nodes of a biomass supply chain is presented. Owing to conflicting objectives, weights are imposed on each aspect, and a 0-1 weighted goal programming mixed-integer linear programming (WGP MILP) programming model is formulated and used for all possible weight representations under environmental, economic and social criteria.

The results of the study show that emphasis on the environmental aspect, expressed with high values in the environmental criterion, significantly reduces the level of CO₂ emissions derived from the transportation of biomass through the various nodes of the supply chain. Environmental and economic criteria seem to be moving in the same direction for high weight values in the corresponding aspect. From the results, social criterion seems to move to the opposite direction from environmental and economic criteria.

An integrated mathematical framework is presented modeling biomass production, transportation and warehousing. To the best of the authors’ knowledge, such a model that integrates multiple objectives with supply chain design has not yet been published.

The purpose of this paper is to explore the peer-reviewed literature, as well as literature written by practitioners having authority on green supply chains and allied areas with a view to identify future research directions with the help of an extensive literature review.

In line with this objective, the constructs “Green Supply Chain Practices” and “Green Supply Chain Performance” were the two terms that were identified for a co-relational study.

As indicated by the literature review, there is a need to do a more detailed study that can pinpoint particular components of green supply chain practices that have a strong association with particular components of green supply chain performance. This paper attempts to achieve the aim by using a different connotation of these two constructs.

Such a study with the connotation and components of green supply chain (GSC) practices and GSC performance as identified and used in this paper might not have been conducted before in the way it is proposed to be used in this paper, thus making this an appropriate contribution. Accordingly, a framework for the research has been depicted, and research questions have been framed.

The purpose of this article is to explore and classify the pattern of themes and challenges in developing socially sustainable supply chains.

The methodology is based on a systematic review of the peer-reviewed literature to explore what major themes and challenges have been discussed and the significant gaps where opportunities for further research can be found.

In total, four categories of themes were identified, namely, human-centric, focal organization-centric, supply chain-centric and governance-centric. Challenges were classified into seven categories, namely, inadequate and asymmetric knowledge, difficulties of operationalization, shifting the values, subjectivity in evaluation, governance complexity, difficulties of small- and medium-sized enterprises and sustainability fade.

The focus of the article is on the social pillar of sustainable development in the context of supply chains. A more holistic systematic investigation of synergy of all the three pillars/bottom lines of sustainable development (economic, environmental and social) can be an opportunity for further research.

Taking a more holistic view of the pattern of currently discussed themes and challenges may be beneficial in increasing the absorptive capacity of industrial and business practitioners, by accumulating and assimilating external knowledge, when they design and operationalize innovative strategies in developing sustainable supply chains.

This article may increase awareness about the social responsibilities of supply chains actors and stakeholders in different scales. It may also guide managers, decision makers and practitioners to better understand the difficulties, obstacles or dilemmas that can hinder the sustainable development of supply chains. The results section presents a framework driven from the emerged themes, and the discussion section provides propositions for tackling the challenges and opportunities for further research.

From a supply chain perspective, logistics firms collaborate with other supply chain members to extend their business scope. Investment in circular economy projects in the supply chain can not only broaden the scope of business but also increase the value of the entire supply chain. Third-party logistics companies are gradually participating in the construction and operation of many circular economy projects. How to coordinate multiple circular economy supply chain projects is at the core of its operation.

This paper first analyzes some typical supply chain projects in China and summarizes the main features of these projects. Secondly, considering the benefits of the project and the stakes of each project, a multi-stage stochastic programming model is established. Finally, Cplex, nested decomposition, LocalSolver and other methods are adopted to simulate and analyze the model.

The final experimental results find that the importance of coordinating multiple circular economy supply chain projects to increase the value of the entire supply chain. The multi-stage stochastic programming model presented in this research can provide a useful tool for logistics enterprises and third-party logistics companies to optimize their investment decisions and maximize their profits in the context of a circular economy.

There are still some limitations to this study; for example, it is limited to the analysis of circular economy supply chain projects in China. The study focused on third-party logistics companies, and other enterprises in the circular economy supply chain were not considered. The research also assumed that the benefits of each circular economy project and the stakes of each project were known, which may not always be the case in real-world scenarios.

This manuscript found that investing in other circular economy projects in the supply chain can broaden the scope of business and increase the value of the entire supply chain. Third-party logistics companies are gradually participating in the construction and operation of many circular economy projects, such as recycling and repurposing initiatives. It highlights the importance of coordinating multiple circular economy supply chain projects to increase the value of the entire supply chain. The multi-stage stochastic programming model presented in this research can provide a useful tool for logistics enterprises and third-party logistics companies to optimize their investment decisions and maximize their profits in the context of a circular economy.

Decision-making, reinforced by artificial intelligence (AI), is predicted to become potent tool within the domain of supply chain management. Considering the importance of this subject, the purpose of this study is to explore the triggers and technological inhibitors affecting the adoption of AI. This study also aims to identify three-dimensional triggers, notably those linked to environmental, social, and governance (ESG), as well as technological inhibitors.

Drawing upon a six-step systematic review following the preferred reporting items for systematic reviews and meta analysis (PRISMA) guidelines, a broad range of journal publications was recognized, with a thematic analysis under the lens of the ESG framework, offering a unique perspective on factors triggering and inhibiting AI adoption in the supply chain.

In the environmental dimension, triggers include product waste reduction and greenhouse gas emissions reduction, highlighting the potential of AI in promoting sustainability and environmental responsibility. In the social dimension, triggers encompass product security and quality, as well as social well-being, indicating how AI can contribute to ensuring safe and high-quality products and enhancing societal welfare. In the governance dimension, triggers involve agile and lean practices, cost reduction, sustainable supplier selection, circular economy initiatives, supply chain risk management, knowledge sharing and the synergy between supply and demand. The inhibitors in the technological category present challenges, encompassing the lack of regulations and rules, data security and privacy concerns, responsible and ethical AI considerations, performance and ethical assessment difficulties, poor data quality, group bias and the need to achieve synergy between AI and human decision-makers.

Despite the use of PRISMA guidelines to ensure a comprehensive search and screening process, it is possible that some relevant studies in other databases and industry reports may have been missed. In light of this, the selected studies may not have fully captured the diversity of triggers and technological inhibitors. The extraction of themes from the selected papers is subjective in nature and relies on the interpretation of researchers, which may introduce bias.

The research contributes to the field by conducting a comprehensive analysis of the diverse factors that trigger or inhibit AI adoption, providing valuable insights into their impact. By incorporating the ESG protocol, the study offers a holistic evaluation of the dimensions associated with AI adoption in the supply chain, presenting valuable implications for both industry professionals and researchers. The originality lies in its in-depth examination of the multifaceted aspects of AI adoption, making it a valuable resource for advancing knowledge in this area.