Artificial intelligence related agristartup environment of farmers

Introduction

In India agristartups are rapidly booming, with sustainable growth in investments and increasing government intiatives (Kumar et al., 2024) [4] . The encouragement from family at scalable level and government and other organizational at policy level can strengthen their capacities and also startup network (Nain et al, 2013) [6] . India has 83 unicorn startups with a combined valuation of over 280 billion dollars most of these under service sector which contribute to half of the Indian GDP (Patwardhan, 2022) [5] . Agristart-ups helps in collaborating between the farmers, institutions, wholesalers, retailers, and consumers (Adhya and Sahoo, 2022) [1] . Agristartups also helps in linking among farmers, researchers, and investors, leading to create more agristartup ecosystem. The major challenges for agristartup for farmers is technological skills to handle them. (Aparna etal, 2022) [2] . In this artificial intelligence revolution, priority for agristartups is essential and many youths amidst from nonagriculture background are coming forward in investing on the agristartups. Agristartup environment of farmers is also crucial to make the entire agristartups successful. Thus the present study was done to estimate the agristartup environment of farmers with the help of the Agristartup environment index (AEI).

Methodology

Tthe individuals from the farming community who actually subscribed to the agristartups on artificial intelligence and receiving the services from them were selected purposively.

Relationship between Profile of farmers and their agristartup environment

It is shown from the Table .3 that calculated 'r' values between farming experience, social networking, innovativeness and agristartup environment were greater than table 'r' value at 0.01 level of significance. Whereas, the calculated 'r' value of the variables digital literacy, extension contact, information seeking behaviour and agristartup environment were greater than the 'r' table value at 0.05 level of significance. The calculated 'r' value is greater than the table value at 0.05 level of significance. Hence, null hypothesis was rejected, and empirical hypothesis was accepted. Therefore, it can be interpreted, a positive and significant relationship between age, digital literacy, farming experience, extension contact, social networking, innovativeness, information seeking behaviour and agristartup environment. The variable social participation, negatively significant with agristartup environment. The calculated 'r' value is greater than the table value at 0.05 level of significance. Hence, null hypothesis was rejected, and empirical hypothesis was accepted. The calculated 'r' values between age, farm size and farm equipment possesion agristartup environment were less than the 'r' table value. It is interpreted that there was a significant positive relationship between variables digital literacy, farming experience and agristartup environment of farmers it is due to the fact farmers with middle, young age their age progresses they get more digital knowledge along with the farming experience with the agristartup indirectly influence the agristartup environment. The age, farm size variable is positive and has non-significant relation, this is due to farmers are using the services unrelated to their farmer size. The variable social participation is negative and significant, middle and young age farmers are digitally due lack of time and interested to try new technologies. The variable extension contact is positive and significant, due to more contact with extension personnel's would help individual to more exposure to agristartups on artificial intelligence. Farm equipment possession is positive and non-significant, because that machinery impact is very low. The variable innovativeness is positive and significant, this is due to middle and young age farmers, as they are aging they try new technologies. Information seeking behaviour is positive and significant relation, which would helpful in developing awareness and interest by listening to the other farmers testimonials.

Conclusion

Farmers perceived the political and legal environment as favourable and less favourable. It would helpful if the meetings, awareness programmes and trainings were conducted for creating awareness on the agristartups on artificial intelligence. In case sociocultural environment awareness need to be created on the agristartups on artificial intelligence. The economic and technological environment create importance in the usage of agristartups on artificial intelligence when agristartups are made easy and understandable. The microenvironment helps the farmers in when the agristartup entrepreneurs focuses on answering the queries and respond timely in giving services to farmers.

References

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