road mapping of artificial intelligence technologies for the food industry: a tde approach

This paper discusses the application of the technology development envelope (tde) as a road mapping tool in combination with the delphi method and the analytic hierarchy process (ahp). the method helps policy and decision-makers in organizations strategically manage emerging technologies by mapping their anticipated development path. the paper focused on creating a technology development envelope (tde) for artificial intelligence (ai) technologies in the food industry. in the first step, an expert panel identified a list of ai technologies applicable to the food industry. a hierarchical decision-making model, comprising 5 criteria and 24 sub-criteria for technology evaluation, was extracted from the literature and validated using the delphi method. the analytic hierarchy process (ahp) was used to determine the relative importance of criteria and sub-criteria for evaluating the identified technologies. at this stage, the most important criteria considered were food safety and social and political acceptance of the technology. the expected value of each technology was calculated over different periods, resulting in the development of the technology development evaluation (tde) for ai technologies in the food industry within a ten-year horizon. the analysis of the future indicates that technologies such as computer vision, robotics, industrial automation, and machine learning will undergo continuous improvements over time and eventually become dominant technologies in the food industry. these advancements can lead to an increase in quality and efficiency within the food industry. finally, sensitivity analysis was conducted to test the model’s sensitivity and explore how policymakers’ extreme strategies affect the model’s outputs.

road mapping of artificial intelligence technologies for the food industry: a tde approach

this paper discusses the application of the technology development envelope (tde) as a road mapping tool in combination with the delphi method and the analytic hierarchy process (ahp). the method helps policy and decision-makers in organizations strategically manage emerging technologies by mapping their anticipated development path. the paper focused on creating a technology development envelope (tde) for artificial intelligence (ai) technologies in the food industry. in the first step, an expert panel identified a list of ai technologies applicable to the food industry. a hierarchical decision-making model, comprising 5 criteria and 24 sub-criteria for technology evaluation, was extracted from the literature and validated using the delphi method. the analytic hierarchy process (ahp) was used to determine the relative importance of criteria and sub-criteria for evaluating the identified technologies. at this stage, the most important criteria considered were food safety and social and political acceptance of the technology. the expected value of each technology was calculated over different periods, resulting in the development of the technology development evaluation (tde) for ai technologies in the food industry within a ten-year horizon. the analysis of the future indicates that technologies such as computer vision, robotics, industrial automation, and machine learning will undergo continuous improvements over time and eventually become dominant technologies in the food industry. these advancements can lead to an increase in quality and efficiency within the food industry. finally, sensitivity analysis was conducted to test the model’s sensitivity and explore how policymakers’ extreme strategies affect the model’s outputs.