From Failure to Success: A Framework for Successful Deployment of Industry 4.0 Principles in the Aerospace Industry

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Feature extraction for artificial intelligence enabled food supply chain failure mode prediction

The Farm to Fork Strategy of the European Commission is a contingency plan aimed at always ensuring a sufficient and varied supply of safe, nutritious, affordable, and sustainable food to citizens. The learning from previous crises such as COVID-19 indicates that proactive strategies need to span numerous levels both within and external to food networks, requiring both vertical and horizontal collaborations. However, there is a lack of systematic performance management techniques for ripple effects in food supply chains that would enable the prediction of failure modes. Supervised learning algorithms are commonly used for prediction (classification) problems, but machine learning struggles with large data sets and complex phenomena. Consequently, this research proposes a manual approach to feature extraction for artificial intelligence with the aim of reducing dimensionality for more efficient algorithm performance, and improved interpretability/explainability for benefits in terms of ethics and managerial decision-making. The approach is based on qualitative comparative analysis informed by in-depth case knowledge which is refined through Boolean logic, yielding solutions that reflect complex causality as opposed to single failure point modes. Two case exemplars are presented to support the proposed framework for implementation: export readiness of dairy supply chains under the Russia-Ukraine war, and egg supply chain sustainability during COVID-19 lockdown in the United Kingdom

From Failure to Success: A Framework for Successful Deployment of Industry 4.0 Principles in the Aerospace Industry

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Crowdsourcing food security: introducing food choice derivatives for sustainability

Global food supply chains are unprepared for the increasing number and severity of the expected environmental, social and economic shocks in the coming years. The price-setting process of commodities is directly impacted by such shocks, influencing consumer behavior regarding food choice and consumption. Both the market and advances in precision agriculture drive increased production and consumption. However, there has been a lack of consideration of how consumer behavior could be harnessed to mitigate such shocks through decreased consumption and reduced waste. The SAPPhIRE model of causality was applied to design sustainable and ecologically embedded futures derivatives that could have a role in affecting commodity markets. Multi-agent systems were combined with artificial intelligence and edge computing to provide the necessary functionality. The impact of war in Ukraine was used to exemplify the design of consumer “food choice” derivatives. This resulted in a mechanism to bring aggregated acts of consumer compassion and sustainability to commodities markets to mitigate food security shocks. When implementing food choice derivatives, care must be taken to ensure that consumer food choices are rational and compatible with individual nutritional needs and financial situations, and that the legitimate interests of agri-food businesses are protected.</p

The imperative of embedding sustainability in business: A model for transformational sustainable development

 Sustainable development is the current strategic trajectory with transformative intent for complex global challenges including eradication of poverty, full social inclusion and prevention of ecological collapse. However, discourses related to the private sector emphasise economic and social development over the environmental components of sustainable development. Embedding sustainability is the related management imperative for business, supported by numerous frameworks, yet there is confusion about implementation in both literature and practice. This research addresses these issues with a mixed methods study combining a scoping literature review with a qualitative e-Delphi study. The main findings are that the economic system constrains the embedding of sustainability in business; and that a paradigm shift towards ecocentric business models lacks support. The results are used to develop a novel model to aid transformational sustainable development that acknowledges the influences of the economic system in business whilst respecting social and ecological embeddedness. </p

Blockchain for Ecologically Embedded Coffee Supply Chains

 Background: This research aims to identify how blockchain technology could support the ecological embeddedness of the coffee supply chain. Ecological embeddedness is a subset of the circular economy (CE) that demands legitimacy through design changes to product, production and/or packaging for benefits to economic actors and the environment. This is in contrast with legitimacy as a public relations exercise. Blockchain is a digital transformation technology that is not fully conceptualized with respect to supply chain implementation and the related strategy formulation, particularly in the context of sustainability. Furthermore, the integration of consumers into the CE remains not well understood or researched, with the main focus of CE being the cycling of resources. Methods: This research employs a qualitative case study methodology of the first coffee business in the USA to use blockchain technology as an exemplar. Gap analysis is then applied to identify how blockchain could be used to advance from the current state to a more sustainable one. Results: Findings indicate that the implementation of blockchain is not ecologically embedded in the example studied.  Conclusions: The extension of blockchain technology to consider the by-products of production and valorizable waste throughout the supply chain as assets would support ecologically embedded CE for coffee. </p

A Circularity Indicator Tool for Measuring the Ecological Embeddedness of Manufacturing

Circularity in manufacturing is critical to reducing raw material usage and waste. Ecological embeddedness examines circular relationships intended to benefit both economic actors and the natural environment. By understanding circular relationships in the value chain, manufacturers can formulate strategies that are eco-effective. This work develops and validates an original circularity tool to measure the ecological embeddedness of manufacturers using exploratory and confirmatory factor analysis. The tool is tested on process manufacturers selling products in the United Kingdom. The three main results are that the tool is useful and comprehensive (87% of users), enables simple comparisons with competitors, and identifies weaknesses in strategies related to the five dimensions connecting manufacturers, consumers, and the environment: understanding, realising, utilising, negotiating, and reclaiming. Manufacturers may use the tool to improve their ecological embeddedness, and sector-based circularity levels may be established for policy development. The novelty of the tool is in the use of ecological relationships to support achievement of a circular economy

Surviving the Storm: Navigating the Quadruple Whammy Impact on Europe's Food Supply Chain

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Ecologically Embedded Design in Manufacturing: Legitimation within Circular Economy

Circular economy has gained momentum since the 1970s as a regenerative alternative to the traditional linear economy. However, as the circular economy has gone mainstream, circularity claims have become fragmented and remote, consisting of indirect contributions, such as the life extension of other products and the use of waste as feedstock, without addressing the actual cause of waste. The present study aims to identify the strategic motivations of manufacturers participating in the circular economy and the corresponding relationship to ecological embeddedness. This paper explores the circular economy in manufacturing through existing products on the market and their relationship to eco-design by considering the product, packaging, and its production. Legitimacy is found to be a decisive factor in whether the type of circular economy strategy manufacturers adopt yields ecological benefits. The results from the case study of products clearly indicate the superiority of ecological embeddedness, as a form of circularity supporting strong sustainability. Finally, a novel template is proposed to support the implementation of ecological embeddedness in manufacturing

Unlocking AI's potential in the food supply chain: A novel approach to overcoming barriers

This paper delves into the challenges impeding the seamless integration of artificial intelligence (AI) within the food supply chain (FSC) and introduces a novel methodological framework that combines the NK Model with the Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique. Through an exhaustive literature analysis and expert discussions, the research identifies and categorizes significant obstacles to AI deployment in the FSC. These hurdles include the imperative for a skilled labor force, financial limits, regulatory complexity and technological limitations. The unique DEMATEL-NK approach highlights the interconnected nature of these barriers, pinpointing the most critical impediments. The study's implications extend to the broader domains of AI adoption in agriculture and the food industry, offering a nuanced perspective for policymakers, industry stakeholders, and researchers. The findings underscore the imperative of overcoming these barriers for the successful implementation of AI technologies in the FSC, promising advancements in efficiency, quality, and sustainability. The innovative methodology not only sheds light on the interconnectedness of these barriers but also provides a systematic approach for prioritizing and implementing solutions. This research offers a fresh viewpoint on barrier relationships, guiding decision-makers in crafting effective strategies and interventions to propel AI integration in the FSC forward.</p