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Technology is advancing at a very rapid pace, and it helps the user in predicting things, taking the right decisions, making life less difficult and eventually increasing the profitability of their business. Due to the increasing global population, changing climatic conditions, and other natural factors predominating in nature, agriculture practice is becoming less predictable and as a result, farmers’ confidence is being lost, poverty and food insecurity are rising, and other issues are becoming more prevalent. In addition, it affects the sustainability of the food supply chain. So, there is a critical need for agriculture to adopt Industry 4.0 technologies. Here, we want to select a suitable technology acceptance model which comprehensively and robustly defines all the aspects of technology adoption factors in agriculture. From the different adoption theories, we choose one theory that fits our criteria very accurately; for this, we use a hybrid MCDM approach. We utilised fuzzy AHP and fuzzy VIKOR to make the selection logically and systematically correct. Three experts are employed in the study. Fuzzy AHP helps to find the weightage of criteria used by the fuzzy VIKOR technique in ranking the theories. The results showed that the UTAUT ranking comes number one after applying all the suitable criteria and alternatives, and it is the most accurate theory for analysing the adoption of Industry 4.0 technologies in agriculture. This article offers readers a methodical approach for choosing a technology adoption paradigm. The hypothesis that best fits a person’s criteria can be determined by comparing them to potential alternatives.
Jain et al. (Wed,) studied this question.