Conservative agriculture practices adoption and impact on the sustainable farm performance for rice farmers in Punjab, Pakistan

The industrial revolution blesses the world with the development and riches of human life on earth. However, the industrial revolution caused an upsurge in global climate change and the rise of 2oC temperature on earth. The world needs a solution to address the issue of Greenhouse gases (GHGs) emissions, as world agriculture is the 3rd most substantial contributor to GHGs emissions. The solution for reducing GHGs emissions from the agriculture sector is to use conservative agriculture practices (CAPs). However, CAPs not widely adopted by the farmers of developing countries. Adoption of innovation is complex, as numerous factors impact the farmers at various levels enabling the adoption of CAPs. Moreover, the adoption of CAPs reported low as the impact of the adoption is not much discussed at farmers’ and farm level. This research aims to explore the CAPs adoption as a process based on the mix of the farmer personal inclination towards the environment, trust on extension, innovativeness, profit orientation, and risk-taking attitude as well as attributes of the conservative agriculture practices like performance expectancy, effort expectancy, and social influence for the formation of the intention to adopt the CAPs among the Pakistani rice farmers. The farmer’s age, education, and farming experience moderate the relationship as well. The intention to adopt CAPs leads to the actual use of CAPs, with the facilitating condition for CAPs and voluntariness of use among the farmers. The voluntariness of use moderates the relationship between the facilitating conditions and use of CAPs. Then the adoption of CAPs effects on sustainable farm performance at the environment, yield, and economic level. The cross-sectional data collected with the face-to-face survey-based interviews from the rice cultivation rice area of Punjab, Pakistan. Collected data examined for missing data, normality, and descriptive analysis by the use of SPSS. Subsequently, partial least square structural equation modelling (SEM-PLS) employed with the SmartPLS 3.1. Results of analysis provide shreds of evidence that farmers’ personal inclinations of profit orientation and environment attitude suggestively influence the intention to adopt CAPs. Furthermore, CAPs attribute of effort expectancy significantly impact the intention to adopt CAPs. Farmers’ experience encouragingly moderates the relationship between the performance expectancy & effort expectancy on the intention to adopt CAPs. Moreover, the intention to adopt CAPs’, facilitating conditions for CAPs and voluntariness of use positively & meaningfully influence the adoption of CAPs. The use of CAPs significantly affects the perception of sustainable farm performance. Artificial neural network (ANN) analysis employed to estimate the predictive precision for intention to adopt and use of CAPs. ANN is a non-compensatory analysis technique based on a multilayer with a hidden layer called ‘black-box.’ The nodes from input construct neurons associated with the outcome construct neurons by the neurons of the hidden layer. Three-layer ANN model utilised for the study. The ANN analysis results show that effort expectancy, profit orientation, and social influence are three critical factors forming an intention to adopt CAPs. Intention to adopt CAPs and the facilitating condition for CAPs significantly contribute to the use of CAPs. Sustainable farm performance meaningfully contributed to the use of CAPs. Finally, theoretical and methodological contributions, managerial implications, and recommendations for future research offered in the end.