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The existing state of over-utilization of input resources affected the efficient production of the agricultural output, which created a challenge for the profitability of the farming community as well as sustainability of different agricultural production systems (APSs). Hence, it is crucial to explore the important input variables, which affect farming efficiency across different APSs. In past studies, data envelopment analysis (DEA) has been used extensively to estimate the mean technical efficiency (MTE) of agricultural farms. In this study, a meta-regression analysis has been performed to examine variables that affect the MTE variation in 100 studies. The selected studies have been classified based on the study period, farm location, journals, product type, sample size and their outcomes. Results revealed that the year of study, location and sample size were not significant, whereas agricultural products such as vegetables, fruits, flowers and livestock significantly affected the performance of MTE across studies. These empirical results establish the importance of related variables in the MTE estimation of different APSs, which will lead and assist better-quality future research in the agricultural efficiency domain.
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