According to recent trends, food production must double by 2050 to meet the world's growing population's expected demand. To achieve this goal, agri-food companies have begun implementing different digital technologies to increase food production while utilising fewer resources, thus reducing production processes' environmental impact. This study aims to review Industry 4.0 and agri-food sustainability research published in the last decade. Text classification and data extraction machine learning techniques have been used to support the literature review process. Notably, text classification was used to support the screening phase of titles and abstracts, while data extraction was used to support the content analysis phase by identifying the main topics on which documents are focused. The descriptive analysis shows a summary of the leading scientific journals in the research field, as well as the most influential countries and the research topic evolution over time. The results of the study allowed us to identify ten main research clusters, providing in-depth discussions and perspectives on critical areas for future research avenues. Finally, this study provides significant implications for the agri-food industry, suggesting firms redesign their business models according to a logic that prioritises long-term, shared value creation over short-term efficiency, and profitability. Incorporating digital technologies may help control farming activities' impact on soil and air quality, minimising the use of natural resources, pollutants, and CO2 emissions, thus providing long-term economic, environmental, and social advantages.

The digital and sustainable transition of the agri-food sector

Cerchione R.
2023-01-01

Abstract

According to recent trends, food production must double by 2050 to meet the world's growing population's expected demand. To achieve this goal, agri-food companies have begun implementing different digital technologies to increase food production while utilising fewer resources, thus reducing production processes' environmental impact. This study aims to review Industry 4.0 and agri-food sustainability research published in the last decade. Text classification and data extraction machine learning techniques have been used to support the literature review process. Notably, text classification was used to support the screening phase of titles and abstracts, while data extraction was used to support the content analysis phase by identifying the main topics on which documents are focused. The descriptive analysis shows a summary of the leading scientific journals in the research field, as well as the most influential countries and the research topic evolution over time. The results of the study allowed us to identify ten main research clusters, providing in-depth discussions and perspectives on critical areas for future research avenues. Finally, this study provides significant implications for the agri-food industry, suggesting firms redesign their business models according to a logic that prioritises long-term, shared value creation over short-term efficiency, and profitability. Incorporating digital technologies may help control farming activities' impact on soil and air quality, minimising the use of natural resources, pollutants, and CO2 emissions, thus providing long-term economic, environmental, and social advantages.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11367/112640
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