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This article sheds light on the missing links concerning the study of using integrated enabling technologies toward sustainable and circular agriculture supply chains by examining the available literature and proposing future research possibilities.

The relevant literature was researched through online databases such as Scopus, Web of Science, Academic Search Premier, Emerald, IEEE Xplore, Science Direct, World Scientific Net and Springer-Link Journals, covering a period from 1999 to 2020. A systematic literature review based on 75 papers analyzed the integration of the concepts of enabling technologies, sustainability, circular economy and supply chain performance in agriculture supply chains.

It was identified that enabling technologies and agriculture supply chains alone have been explored further than integrated enabling technologies, sustainability, circular economy, supply chain performance and agriculture supply chains. Enabling technologies and agriculture supply chains' main findings are: enabling technologies have been studied to improve food safety, food quality and traceability in agriculture supply chains. The main results regarding integrated enabling technologies, sustainability, circular economy, supply chain performance and agriculture supply chains are: Internet of Things and information communication technology play an important role in addressing food security, traceability and food quality, which help achieve sustainable development goals.

This review study provides 13 research questions to underpin future trends regarding integrated technologies' application in agriculture supply chains for circular and sustainable growth.

Poultry production supply chains produce substantial wastes that are transformable into favorable environmental outcomes and profitable products. While overwhelming evidence supports this conclusion, scant literature is available on how such transformations are doable. Using systems dynamics, this study addresses this research gap in a national (Bangladesh) context. This study aims to contribute an integrated model for poultry supply chains that incorporate reverse flows of wastes using system dynamics (SD) engineering with empirical simulations.

This study applies SD and simulations of alternative supply chains with versus without reverse loops that transform wastes into viable products in poultry production and downstream marketing operations. This research reports on an in-depth case study of systems thinking and use of the Massachusetts Institute of Technology systems dynamics software. Data for the study are longitudinal and come from written operation records and extensive, repeated, one-on-one Interview from a large poultry plant operation in Bangladesh.

This study finds that several current poultry waste production problems are solvable through an integrated approach that generates viable new marketable products with substantial profitable opportunities that also contributes to reductions in industrial pollution. This study confirms that forward, backward and reverse supply chains need to be under one umbrella system to achieve economic, social and environmental benefits.

This study’s SD model and outputs need additional applications in poultry supply chains in multiple countries. Applying the firm-level model that this study provides is a necessary but insufficient step toward empirical confirmation through replicating.

The authors originally explore the factors for blockchain technology (BCT) adoption in agricultural supply chains (ASCs) to enhance circularity and understand the dependencies, hierarchical structure and causalities between these factors.

Based on an extant literature review and expert opinion, the present study identified ten enablers for adopting BCT to leverage the circular economy (CE) practices in the ASCs. Then, using an integrated interpretive structural modeling and decision-making trial and evaluation laboratory (ISM-DEMATEL) approach, hierarchical and cause–effect relationships are established.

It was observed that traceability is the most prominent enabler from the CE perspective in ASCs. However, traceability, being a net effect enabler, will be realized through the achievement of other cause enablers, such as seamless connectivity and information flow and decentralized and distributed ledger technology. The authors also propose a 12 Rs framework for enhancing circularity in ASC operations.

The paper identifies enablers to BCT adoption that will enhance circularity in ASC operations. The ISM hierarchical model is based on the driving and dependence powers of the enablers, and DEMATEL aids in identifying causal relationships among the enablers.

The study's findings and proposed 12 Rs framework may help the practitioners and policymakers devise effective BCT implementation strategies in ASCs, thereby empowering sustainability and circularity.

This study enriches the literature by identifying and modeling enablers for BCT adoption in ASCs. The study also proposes a new 12 Rs framework to help enhance ASC circularity.

This work aims to review past and present articles about data-driven quality management (DDQM) in supply chains (SCs). The motive behind the review is to identify associated literature gaps and to provide a future research direction in the field of DDQM in SCs.

A systematic literature review was done in the field of DDQM in SCs. SCOPUS database was chosen to collect articles in the selected field and then an SLR methodology has been followed to review the selected articles. The bibliometric and network analysis has also been conducted to analyze the contributions of various authors, countries and institutions in the field of DDQM in SCs. Network analysis was done by using VOS viewer package to analyze collaboration among researchers.

The findings of the study reveal that the adoption of data-driven technologies and quality management tools can help in strategic decision making. The usage of data-driven technologies such as artificial intelligence and machine learning can significantly enhance the performance of SC operations and network.

The paper discusses the importance of data-driven techniques enabling quality in SC management systems. The linkage between the data-driven techniques and quality management for improving the SC performance was also elaborated in the presented study.

This paper presents a review of the existing state-of-the-art literature on machine learning (ML) in logistics and supply chain management (LSCM) by analyzing the current literature, contemporary concepts, data and gaps and suggesting potential topics for future research.

A systematic/structured literature review in the subject discipline and a bibliometric analysis were organized. Information regarding industry involvement, geographic location, research design and methods, data analysis techniques, university, affiliation, publishers, authors, year of publications is documented. A wide collection of eight databases from 1994 to 2019 were explored using the keywords “Machine Learning” and “Logistics“, “Transportation” and “Supply Chain” in the title and/or abstract. A total of 110 articles were found, and information on a chain of variables was gathered.

Over the last few decades, the application of emerging technologies has attracted significant interest all around the world. Analysis of the collected data shows that only nine literature reviews have been published in this area. Further, key findings show that 53.8 per cent of publications were closely clustered on transportation and manufacturing industries and 54.7 per cent were centred on mathematical models and simulations. Neural network is applied in 22 papers as their exclusive algorithms. Finally, the main focuses of the current literature are on prediction and optimization, where detection is contributed by only seven articles.

This review is limited to examining only academic sources available from Scopus, Elsevier, Web of Science, Emerald, JSTOR, SAGE, Springer, Taylor and Francis and Wiley which contain the words “Machine Learning” and “Logistics“, “Transportation” and “Supply Chain” in the title and/or abstract.

This paper provides a systematic insight into research trends in ML in both logistics and the supply chain.

The food supply chain (FSC) challenges coupled with global disruptions, such as the recent coronavirus disease 2019 (COVID-19) pandemic outbreak, exacerbate its vulnerability. The Internet of things (IoT) is one of the disruptive technologies being adopted in food supply chain management (FSCM). This study aims to address the challenges of IoT adoption in the FSC by systematically analyzing the prior pertinent literature.

A structured literature review was used to collate a list of peer-reviewed and relevant publications. A total of 72 out of 210 articles were selected for the final evaluation.

The literature review findings suggest five themes: technical, financial, social, operational, educational and governmental related challenges. A total of 15 challenges were devised from the review related literature of IoT adoption. The study concludes with future research recommendations for scholars and practical implications for practitioners.

While this study focuses on the overall FSC, further research should address other domains in the FSC such as cold supply chain, agriculture and perishable food to gain a better contextual understanding of the specific case.

The topic of IoT adoption in the FSCM is still considered emerging. Therefore, the present work contributes to the limited studies and documentation on the level of IoT implementation in the FSCM. This study should help organizations to assimilate how to adopt and manage the IoT application by addressing the factors and challenges presented in this research.

The role of data analytics is significantly important in manufacturing industries as it holds the key to address sustainability challenges and handle the large amount of data generated from different types of manufacturing operations. The present study, therefore, aims to conduct a systematic and bibliometric-based review in the applications of machine learning (ML) techniques for sustainable manufacturing (SM).

In the present study, the authors use a bibliometric review approach that is focused on the statistical analysis of published scientific documents with an unbiased objective of the current status and future research potential of ML applications in sustainable manufacturing.

The present study highlights how manufacturing industries can benefit from ML techniques when applied to address SM issues. Based on the findings, a ML-SM framework is proposed. The framework will be helpful to researchers, policymakers and practitioners to provide guidelines on the successful management of SM practices.

A comprehensive and bibliometric review of opportunities for ML techniques in SM with a framework is still limited in the available literature. This study addresses the bibliometric analysis of ML applications in SM, which further adds to the originality.

Contemporary literature reveals that, to date, the poultry livestock sector has not received sufficient research attention. This particular industry suffers from unstructured supply chain practices, lack of awareness of the implications of the sustainability concept and failure to recycle poultry wastes. The current research thus attempts to develop an integrated supply chain model in the context of poultry industry in Bangladesh. The study considers both sustainability and supply chain issues in order to incorporate them in the poultry supply chain. By placing the forward and reverse supply chains in a single framework, existing problems can be resolved to gain economic, social and environmental benefits, which will be more sustainable than the present practices.

The theoretical underpinning of this research is ‘sustainability’ and the ‘supply chain processes’ in order to examine possible improvements in the poultry production process along with waste management. The research adopts the positivist paradigm and ‘design science’ methods with the support of system dynamics (SD) and the case study methods. Initially, a mental model is developed followed by the causal loop diagram based on in-depth interviews, focus group discussions and observation techniques. The causal model helps to understand the linkages between the associated variables for each issue. Finally, the causal loop diagram is transformed into a stock and flow (quantitative) model, which is a prerequisite for SD-based simulation modelling. A decision support system (DSS) is then developed to analyse the complex decision-making process along the supply chains.

The findings reveal that integration of the supply chain can bring economic, social and environmental sustainability along with a structured production process. It is also observed that the poultry industry can apply the model outcomes in the real-life practices with minor adjustments. This present research has both theoretical and practical implications. The proposed model’s unique characteristics in mitigating the existing problems are supported by the sustainability and supply chain theories. As for practical implications, the poultry industry in Bangladesh can follow the proposed supply chain structure (as par the research model) and test various policies via simulation prior to its application. Positive outcomes of the simulation study may provide enough confidence to implement the desired changes within the industry and their supply chain networks.

This chapter introduces the volume’s theme by describing the challenges of sustainability in the agri-food industry and the critical role of agri-food supply chains. Following a description of traditional and sustainable supply chain management practices, we discuss the likely characteristics of sustainability-oriented innovations and how organizations pursuing higher levels of economic, social, and environmental performance will need to adapt their capabilities.

Drawing on the emerging concepts and practices from sustainable supply chain management as well as traditional and emerging concepts from innovation, we develop general propositions and expectations about how organizations might address sustainable effectiveness in their supply chains. The importance of the agri-food industry to all three pillars of sustainable effectiveness and predictions about the inability to feed future populations gives the discussion a certain urgency.

Sustainability-oriented innovations in the agri-food supply chain are different from traditional innovations. We develop propositions regarding the driving motivations, their nature and scope (i.e., more radical and systemic than incremental and focused), and the importance of a multi-stakeholder approach. The 10 cases presented in the volume are summarized.

This paper is designed to assess the sustainable value chain approaches for marketing channel development opportunities for agricultural products in coastal Bangladesh to combat climate change through an approach of community-based adaptation options.

The study was designed to select the potential value chain candidate and to analyze and establish a value chain map to benefit the crop farmers. In this connection, the resources of the whole context were evaluated. The approach uses few tools to generate three outputs, the last of which are the final list of value chains selected for in-depth assessment to design interventions as community-based adaptation practices of the study to combat climate change in the study areas.

The study demonstrated that the difference in the institutional circumstances of the end markets of the agriculture products is connected to the different categories of harmonization and control of the facilitating environment throughout the supply chains. National and local networks improve the value chain in terms of the value addition of the agriculture products, technology improvement, market access and profitability of the products. Strengthening the weak financial structure, focus more on formal financial systems and resolving sociocultural and climate change-induced hazard concerns are the major concerns on the development of value chains in the countries. Apparently, guarantee for good governance, checking illegal and unregulated market contexts, proper mitigation measures to climate change are some paramount important issues for the sustainable management of livelihood, yield, income and development.

All kinds of stakeholders of the agriculture product value chain should focus on competitiveness and productivity and look for and exploit multiple ways to add value once initial success has been attained with a single deal. Ensuring sustainability within the value chains is an important feature to cater to the challenges and changing demands of the age.

The study will help to established a sustainable value chain approach in response to climate change, which process will help to existent opportunities for firms to manage the issue of climate risk by codeveloping and employing adaptation options that may be more preferred or accepted by consumers across the entire chain for the sustainable management of livelihood, yield, income and development.