THE EFFECTS OF AI ON Agricultural Quality Management Systems — An Examination of Shanghai SQ Agrotech Co., Ltd.

Abstract

As an extensive management concept, Total Quality Management (TQM) stresses the need of all organizational members actively working to improve the quality of goods and services via continuous process improvement. Originally implemented in China's industrial sector, Total Quality Management (TQM) has now spread across many other industries, most notably agriculture. Precision agriculture, smart agriculture, and green agriculture have all found new life in China's agricultural enterprises thanks to TQM and the incredible advances and widespread uses of technologies like 5G, big data, satellite remote sensing, and Artificial Intelligence (AI). These innovations have been supported by government policies in China. As a result, new possibilities and obstacles have arisen for the implementation and development of TQM in farming. In this study, we will focus on the behavioral and awareness aspects of the five-factor quality management model that is based on total quality management theory: characteristic quality, tool quality, system quality, behavioral quality, and awareness quality.
This study uses a questionnaire survey and interviews with Shanghai SQ Agricultural Technology Company's management and staff to investigate how AI is changing the quality of awareness and behavior in agricultural enterprises, as well as to identify the main challenges and potential solutions that AI faces when applied to quality management in these sectors.
These terms are related to the following: agricultural enterprises, five-dimensional quality management framework, total quality management, artificial intelligence (AI).