Crowdsourcing food security: introducing food choice derivatives for sustainability

Trollman, Hana; Jagtap, Sandeep; Trollman, Frank

doi:10.1007/s12571-023-01363-7

Cited by 5 publications

(2 citation statements)

References 65 publications

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“…A multi-agent system relying on artificial intelligence and edge computing has been designed as an alternative consumer-based price-making mechanism to mitigate food speculation whilst improving the sustainability of agricultural production [66]. However, there is a scarcity of case studies into the application of deep learning techniques in supply chain management [65].…”

Section: Literature Reviewmentioning

confidence: 99%

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

Trollman

2024

Discov Food

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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.

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Section: Literature Reviewmentioning

confidence: 99%

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

Trollman

2024

Discov Food

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“…Moreover, the COVID-19 pandemic may further strengthen these trends. In the post-pandemic era, the global trade environment and geopolitical landscape have become more complex and uncertain, leading to a sharp rise in internal and external uncertainties and risks for agricultural supply chains [ 3 , 4 ]. In response to these influences, large-scale foreign trade enterprises have accelerated the deployment of digital online channels and shifted their strategic focus from the demand side to the supply side, promoting the emergence of new forms of integration in agricultural supply chains [ 5 ].…”

Section: Introductionmentioning

confidence: 99%

Research on the Influencing Factors of Sustainable Supply Chain Development of Agri-Food Products Based on Cross-Border Live-Streaming E-Commerce in China

Wang,

Zhang,

et al. 2023

Foods

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The organization and coordination of cross-border e-commerce platforms in agricultural product trading are continuously increasing, and the involvement of digital platforms has driven the integration and development of cross-border agricultural product supply chains with live-streaming e-commerce, effectively facilitating the comprehensive development of producers, sellers, and professional service providers within the ecosystem. However, despite the growing importance of this integration model in the market, there are still numerous unresolved issues from a supply chain perspective, and existing research provides relatively limited guidance on the effective operation of this integrated supply chain model. To address this gap in theoretical research, this study first delves into the essence and fundamental characteristics of sustainable cross-border agricultural product supply chains in the context of live streaming. Secondly, employing grounded theory as the primary research method and combining platform theory and ecosystem theory, an influencing factor system and an impact model for the development of sustainable cross-border agricultural product supply chains in the context of live streaming are constructed to gain a more comprehensive understanding of the complexity of this integrated supply chain model. Finally, from the perspectives of government agencies and practitioners, development pathways for sustainable cross-border agricultural product supply chains in the context of live-streaming e-commerce are proposed, aiming to enhance existing research and provide decision-making support for relevant stakeholders in formulating development strategies. The findings of this study contribute to expanding the research perspective on the ecosystem of live-streaming e-commerce and sustainable cross-border agricultural product supply chains, providing theoretical support for the establishment and operation of sustainable cross-border agricultural product supply chains in the context of live streaming. Additionally, it offers important references for promoting the sustainable development of live-streaming e-commerce and cross-border agricultural product supply chains, facilitating industry upgrading, global agricultural trade, and achieving mutually beneficial outcomes.

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Sustainability decision‐making in times of crisis: An empirical study in Italy under the lens of the Russian‐Ukraine war

Dorrego Viera,

Santolin,

Lazzarotti

et al. 2024

Corp Soc Responsibility Env

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This research examines the impact of the Russian‐Ukraine war on the decisions made by managers regarding the three dimensions of the triple bottom line (TBL) of sustainability. Specifically, it investigates how managers in the Lombardy region of Italy adapted their approaches towards sustainability during this crisis. The descriptive statistics and PCA analyses demonstrate that managers adjusted their decisions regarding the social dimension of sustainability in response to the prevailing circumstances. The Russian‐Ukraine war has led to a convergence of the social and economic dimensions within firms. However, the study also reveals that the social dimension is often considered secondary to the core business, making it the weakest aspect of the TBL approach. Nonetheless, external disruptions, such as in the case of the Russian‐Ukraine war, can influence this approach, leading to a repositioning of the social dimension as a focal point in business strategies. By emphasizing the importance of considering social aspects in sustainability decision‐making during crises, this research contributes valuable insights to the existing literature. The findings can inform the development of strategies to address challenges posed by the Russian‐Ukraine war and enhance the integration of social criteria in sustainability decision‐making.

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Crowdsourcing food security: introducing food choice derivatives for sustainability

Cited by 5 publications

References 65 publications

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

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

Research on the Influencing Factors of Sustainable Supply Chain Development of Agri-Food Products Based on Cross-Border Live-Streaming E-Commerce in China

Sustainability decision‐making in times of crisis: An empirical study in Italy under the lens of the Russian‐Ukraine war

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