Virtual technologies adoption to sustain quality in agricultural sector: An emerging economy perspective

Abstract

The study aims to identify the antecedents responsible for sustaining quality control in the context of under-studied agriculture value chains. There is a pressing need to understand the dynamics of technology implementation in an emerging economy context. The conceptual model is designed from complexity, and collective action theory perspectives. An empirical study validates the model and considers the role of traceability, collective action, big data predictive capability, and behavioral uncertainties in sustaining quality in agriculture value chains (AVCs). The paper addresses the call for in-depth deliberations on exploring the factors of AVC quality. The empirical validation of the theoretical model shows a significant positive relationship among the antecedents. The path coefficients and effect size have been derived from understanding the regression equations of cause and effect groups. It also identifies the avenues for improving quality in value chains. This is a pioneering study to design a new operation model for sustaining the quality of AVCs. It also adds a new theoretical debate to AVC technology deployment in the context of an emerging economy. The study is limited to recognizing a few antecedents from the literature in the Indian context. The deliberations contribute significantly to minimizing agricultural waste in developing countries through quality control.