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In the past decade, there has been a dramatic decline in agricultural employment in Bulgaria and several reports have pointed at supply chain modernisation and poor milk quality as the main reasons for the dramatic decline in the number of farms. However, to date the policy debate is been based on ad hoc claims, while there is relatively little micro-level evidence. The purpose of this paper is to analyse the determinants of structural change in the Bulgarian dairy sector in the period 2003-2009.

This paper analyses the determinants of structural change in the Bulgarian dairy sector in the period 2003-2009, using a unique panel survey of 296 farm households in the North and South Central Region of Bulgaria. In order to control for sample attrition bias, the authors use a two-step Heckman model of farm survival and growth model.

The data confirms the rapid outflow of agricultural labour from dairy farming activities: 55 per cent of the farm households supplying milk to a dairy company in 2003 stopped supplying in 2009. The main reasons for quitting are ageing of the household, health problems and an increase in off-farm employment alternatives and not supply chain modernisation and milk quality standards. The institutional innovations which are associated with integration in modern supply chains, such as the provision of farm assistance programmes, have a positive impact on small farms’ growth.

The study is one of the first to use panel data to analyse the impact of standards on the survival and growth of small farms in value chains. The authors analyse the determinants of farm survival and growth in the Bulgarian dairy sector in the period 2003-2009, using panel surveys of 296 dairy farm households in the North and South Central Region of Bulgaria and panel data from interviews with dairy companies. The findings are relevant beyond the Bulgarian dairy sector as supply chain modernisation and changes in quality regulations are taken place in many other transition and developing countries.

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.

This viewpoint article provides insights into the potential role of blockchain technology in addressing crucial issues facing society and global supply chains. We seek to bring more attention to blockchain capabilities for social good in global supply chain settings.

This viewpoint paper provides a perspective on some major current social good and global supply chain issues. The method is based on the current state-of-the-art debate and discourse on blockchain technology as an enabler for social good. Literature, practice and author knowledge concerning the topic are used to support the concepts and actions presented in this study.

Social good, sustainable supply chains and blockchain technology have great promise and potential. Joint research and practice evaluation are essential to reveal the full potential and applications of blockchain technology and address the trade-offs and challenges. Theory and modeling are needed for understanding and advancing these topical areas.

Blockchain application for social good is a new area. We call for transdisciplinary research and development to advance this emerging area. We propose many open questions, and many more are arising in this blockchain and benchmarking community. The impact of this research can be substantive as we can actually seek to make our world a better place as we focus on social good.

The purpose of this paper is to review the post-harvest loss experience of several Asia-Pacific economies to analyse the potential impacts of reduction of such losses using a range of remedial measures.

A conceptual framework has been developed and then applied to a case study based on several Asia-Pacific economies to provide an empirical basis for the analysis in the paper.

Limited access to vital farm inputs and credit, poor infrastructure and lack of technical and market information are some of the critical challenges confronting many small farmers in developing economies including those in the selected case-study countries. The estimated “food savings” are considerable if Asia-Pacific Economic Cooperation’s pledge to reduce food losses and waste by 10 per cent by 2020, relative to the 2011-2012 levels is realised in the case-study economies.

Further work is urgently required to collect more up-to-date data on food losses along the food supply chain, including post-harvest losses, in many economies across the world, including the Asia-Pacific region.

The analysis of post-harvest losses is underpinned by a conceptual framework that has been developed and applied to several Asia-Pacific economies.

This study provides a reflective overview on the role of traditional and emergent digitalization and information technologies for leveraging environmental supply chain sustainability – while reflecting on potential trade-offs and conflicts of digitalization and greening.

The authors use relevant literature and literature from Industrial Management and Data Systems (IMDS) research published in this journal over the past 50 years. They also use their knowledge and over 30 years of research experience in the field to provide professional scholarly reflections and perspective.

The authors provide a focused and succinct evaluation for research directions. A pressures, practices and performance framework sets the stage for pertinent research questions and theoretical needs to investigate the nexus of digitalization and green supply chain management. The authors provide two frameworks with exemplary practices and research for traditional and emergent digitalization and information technology. Their reflection concludes with a summary and steps forward.

The authors show how research and practice can be used to affect supply chain greening with digitalization and information technology. They observe that care should be taken given that these technologies can paradoxically simultaneously offer solutions to environmental degradation and potentially be a source of environmental degradation across the supply chain.

This work provides a summary and unique perspective that links traditional and emergent digitalization technology to green and environmental sustainability work. The area has not seen a clear summary and path forward and shows how IMDS literature has contributed to the field for decades.

While it is commonly argued that food supply chains are characterized by severe imbalances of power between contracting parties, there is an insufficient understanding of the factors affecting the negotiating position of farmers. The purpose of this paper is to provide quantitative evidence documenting the position of farmers and to explain variation in farm gate prices in the dairy supply chain by using unique micro-survey data from Poland.

The bargaining power of farmers is elicited from their self-reported assessment about how confident they feel in their relationships with both the processing industry and input suppliers.

Using econometric modelling, it is shown that farmers who perceive themselves as having a relatively “strong position” in the food chain receive a higher milk price from dairy companies.

While this result comes with some caveats, it suggests that the self-reported beliefs farmers hold about relations with their contractors may reveal additional insights into the distribution of power throughout the food chain.

Compared to the existing studies, the paper offers two innovations. First, to construct a proxy for farmers’ bargaining power, their subjective opinion on how easy they could be substituted for by their contractors is used. In effect, the paper goes beyond the standard measures which focus on farm size or its location. Second, it investigates farmers’ relationships vis-à-vis both processing industry and input suppliers. Consequently, this paper is the first to analyze power relationships by explicitly taking into account three stages of the supply chain.

Amid rising environmental concerns, Industry 4.0 and blockchain technology (BCT) are transforming circular economy practices and prevailing business models. Recognizing the same, the current study examines the role of advanced technology in circular practices and their impact on eco-environmental performance, which influences organizational performance. The study collects data from 185 food processing enterprises that are located in Malaysian territories. By employing CB-SEM modeling, the study provides three key findings. First, Industry 4.0 significantly improves the circular economy practices. Second, circular economy practices help to improve firms' environmental performance but did not stimulate operational performance. Third, higher eco-environmental performance significantly boosts organizational performance. This study set out the foundations for participating countries/firms that help to achieve sustainable goals through the integration of blockchain technology in circular economy practices.

In this study, the authors examine artificial knowledge as a fundamental stream of knowledge management for sustainable and resilient business models in supply chain management (SCM). The study aims to provide a comprehensive overview of artificial knowledge and digitalization as key enablers of the improvement of SCM accountability and sustainable performance towards the UN 2030 Agenda.

Using the SCOPUS database and Google Scholar, the authors analyzed 135 English-language publications from 1990 to 2022 to chart the pattern of knowledge production and dissemination in the literature. The data were collected, reviewed and peer-reviewed before conducting bibliometric analysis and a systematic literature review to support future research agenda.

The results highlight that artificial knowledge and digitalization are linked to the UN 2030 Agenda. The analysis further identifies the main issues in achieving sustainable and resilient SCM business models. Based on the results, the authors develop a conceptual framework for artificial knowledge and digitalization in SCM to increase accountability and sustainable performance, especially in times of sudden crises when business resilience is imperative.

The study results add to the extant literature by examining artificial knowledge and digitalization from the resilience theory perspective. The authors suggest that different strategic perspectives significantly promote resilience for SCM digitization and sustainable development. Notably, fostering diverse peer exchange relationships can help stimulate peer knowledge and act as a palliative mechanism that builds digital knowledge to strengthen and drive future possibilities.

This research offers valuable guidance to supply chain practitioners, managers and policymakers in re-thinking, re-formulating and re-shaping organizational processes to meet the UN 2030 Agenda, mainly by introducing artificial knowledge in digital transformation training and education programs. In doing so, firms should focus not simply on digital transformation but also on cultural transformation to enhance SCM accountability and sustainable performance in resilient business models.

This study is, to the authors' best knowledge, among the first to conceptualize artificial knowledge and digitalization issues in SCM. It further integrates resilience theory with institutional theory, legitimacy theory and stakeholder theory as the theoretical foundations of artificial knowledge in SCM, based on firms' responsibility to fulfill the sustainable development goals under the UN's 2030 Agenda.

Recent literature has considerably improved our understanding of vertical relations in the food chain. One area which has received relatively little attention however relates to the resilience of an agro-food supply chain, that is its ability to face and, if needed, to recover after a major disruption. The purpose of this paper is to study what factors, including characteristics of vertical links between upstream and downstream sectors, may make farmer-processor relationships more or less resilient to adverse shocks.

To do so, the author uses a unique region-level data set on disruptions to dairy supply chain in Poland during the transition from a centrally planned economy to a market economy. More specifically, using between-region variation, the author investigates why in some regions supply chain disruptions, measured as the breakdown of relationships between farmers and processing industry, were smaller than in other regions.

The findings suggest that the supply chain which the author analysed was less resilient to crisis, i.e. the author observed larger disruptions to supply relations, when the supply base was more fragmented and when farmers had better outside options to market their produce via direct sales to consumers. In addition, dairy supply chain in Poland seemed to be less resilient in regions with larger share of the state-owned land.

The results come with several caveats. First, the empirical evidence comes from Poland during the specific period and thus it may not be easily generalised. Second, the results are based on historical correlations. Therefore, although they are robust across various specifications which the author estimates, they may not establish causal relationship due to some omitted variables or potential endogeneity issue. Finally, what the author uses here are region-level data. One may argue therefore that farm-level data would give more fine-tuned focus for testing impacts and theories regarding supply chain resilience.

To the best of the author’s knowledge, this paper is the first to provide some evidence on agro-food supply chain from this perspective.