Implementation of relevant fourth industrial revolution innovations across the supply chain of fruits and vegetables: A short update on Traceability 4.0

Hassoun, Abdo; Kamiloğlu, Senem; García-García, Guillermo; Parra-López, Carlos; Trollman, Hana; Jagtap, Sandeep; Aadil, Rana Muhammad; Esatbeyoglu, Tuba

doi:10.1016/j.foodchem.2022.135303

Cited by 47 publications

(16 citation statements)

References 113 publications

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“…The findings presented in Figure 1 indicate that the agri-food industry is a widely discussed topic among scholars, constituting 30% of the total frequency, followed by manufacturing and healthcare supply chain, accounting for 27% and 15% of selected papers, respectively. The findings align with current research and industry trends, as the growing utilization of AI in the agricultural and food industry is propelled by the imperatives of food security (Bhatia and Albarrak, 2023), traceability (Hassoun et al , 2023), and sustainability (Sharma et al , 2022). Similarly, the adoption of AI in manufacturing supply chains is driven by the circular economy agenda (Bag et al , 2021b), while the pursuit of sustainable healthcare services has sparked substantial interest in AI implementation (Sood et al , 2022).…”

Section: Findings From Descriptive and Thematic Analysissupporting

confidence: 78%

“…Consequently, prioritizing environmental sustainability has become critical in mitigating these adverse effects. Secondly, social issues such as food security and quality have gained attention (Hassoun et al , 2023), particularly in responsible sourcing and sustainable supply chain efforts. Lastly, given the intricate and often opaque nature of the supply chains, supply chain integration (Nayal et al , 2022), efficiency (Nakandala et al , 2016) and sustainability (Sharma et al , 2020) have become crucial factors to consider.…”

Section: Discussion With Practical Implicationsmentioning

confidence: 99%

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Artificial intelligence in supply chain decision-making: an environmental, social, and governance triggering and technological inhibiting protocol

Hao

Demir

2023

JM2

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Purpose 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. Design/methodology/approach 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. Findings 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. Research limitations/implications 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. Originality/value 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.

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Section: Findings From Descriptive and Thematic Analysissupporting

confidence: 78%

Section: Discussion With Practical Implicationsmentioning

confidence: 99%

Artificial intelligence in supply chain decision-making: an environmental, social, and governance triggering and technological inhibiting protocol

Hao

Demir

2023

JM2

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“…2). Given the substantial amount of data generated in the FSC, digitisation is necessary to collect, process and analyse data efficiently (Hassoun et al ., 2023).…”

Section: Resultsmentioning

confidence: 99%

Turn‐key research in food processing and manufacturing for reducing the impact of climate change

Martindale

Hollands²,

Jagtap

et al. 2023

Int J of Food Sci Tech

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SummaryThis study addresses the critical need to report original and current findings on the global food system's ability to meet the growing natural resource demands of an estimated 9 billion global population. The objective is to provide guidance for researchers in developing strategies to reduce climate change risks in the food and beverage supply. To achieve this, we propose integrating innovative industry insights and digital applications into existing food system models as industrial demonstrators. Our research encompasses six impactful themes, demonstrating effective delivery methodologies. We highlight that human‐centred activities and practices, often overlooked in sustainability assessments, hinder improved security and sustainability in the food system. Through our work, we showcase how smarter food production processes, along with active citizen engagement, can achieve desired outcomes outlined in frameworks, such as the Sustainable Development Goals. A crucial aspect is the development of Internet of Things (IoT) platforms, integrating workforce practices into manufacturing activities, and driving the necessary cultural changes for a sustainable food system. This study illuminates challenges faced by the global food system and provides actionable insights and methodologies to guide researchers and industry stakeholders in creating a more sustainable and secure future for food production and consumption.

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“…Under the umbrella of the so-called Industrial Revolution 4.0 (IR4.0), digital technologies such as the Internet of Things, Big Data, and Artificial Intelligence have been increasingly incorporated in food systems [ 120 ]. Regarding the topic of the present study, the IR4.0 offers numerous opportunities for both the development of a hybrid forage seed sector in East Africa and the adoption of the hybrids by dairy farmers.…”

Section: Resultsmentioning

confidence: 99%

Potential Forage Hybrid Markets for Enhancing Sustainability and Food Security in East Africa

Paredes

Florez

Enciso

et al. 2023

Foods

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The cattle sector is strategic for both the economic development and food security of Africa, but the low availability and quality of forage puts the most vulnerable population at risk. Hybrid forages are an alternative for enhancing both food security and sustainability of the sector but adoption levels are still low in Africa, which is related to various factors such as the availability of seeds. This document analyzes potential markets for new interspecific hybrids of Urochloa and potential hybrids of Megathyrsus maximus, adapted to the environmental conditions of eastern and partially western Africa, applying a four-step methodology based on estimating (i) required forage amounts for each country according to its dairy herd, (ii) potential hectares for forage cultivation based on (i), (iii) hectares that can be covered by the two hybrids of interest according to a Target Population of Environment approach, and (iv) potential market values for each country and hybrid. The results show a potential market of 414,388 ha for new interspecific hybrids of Urochloa and 528,409 ha for potential hybrids of Megathyrsus maximus, with approximate annual values of 73.5 and 101.1 million dollars, respectively. Ethiopia, Tanzania, and Kenya hold a market share of 70% for Urochloa, and South Sudan, Ethiopia, and Tanzania a 67% market share for Megathyrsus maximus. The results will help different actors in decision-making, i.e., regarding private sector investments in forage seed commercialization or public sector incentives supporting adoption processes, and thus contribute to increasing food security and sustainability in the region.

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Implementation of relevant fourth industrial revolution innovations across the supply chain of fruits and vegetables: A short update on Traceability 4.0

Cited by 47 publications

References 113 publications

Artificial intelligence in supply chain decision-making: an environmental, social, and governance triggering and technological inhibiting protocol

Artificial intelligence in supply chain decision-making: an environmental, social, and governance triggering and technological inhibiting protocol

Turn‐key research in food processing and manufacturing for reducing the impact of climate change

Potential Forage Hybrid Markets for Enhancing Sustainability and Food Security in East Africa

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