Sustainability, Vol. 15, Pages 1809: The Driving Factors of Innovation Quality of Agricultural Enterprises—A Study Based on NCA and fsQCA Methods
Sustainability doi: 10.3390/su15031809
Agricultural product processing enterprises are a significant cornerstone to support the improvement of agricultural economy. How to reinforce the main position of innovation of agricultural product processing enterprises, gather innovation factors, and improve the innovation quality of enterprises is an important question to answer. Based on the technology&ndash;organization&ndash;environment (TOE) theory , dynamic capability theory, organizational learning theory, and sustainable business model theory, this essay develops a comprehensive system for sustainable innovation quality, takes 36 agricultural processing enterprises in Liaoning province, China, as research samples, and applies necessary condition analysis (NCA) and fuzzy set qualitative comparative analysis (fsQCA) to recognize the driving factors of innovation quality in agricultural processing enterprises. The results show that: (1) a single driving factor is not a necessary condition for high innovation quality, but entrepreneurship and the enhancement of green technology capability have a more universal role in producing high innovation quality in agricultural product processing corporations; (2) a combination of four paths enables internal and external factors to couple and interact with each other to achieve high sustainable innovation quality in agricultural processing enterprises in Liaoning province, which can be further divided into two major categories. The first category is &ldquo;entrepreneurship&ndash;government support driven path&rdquo;, in which entrepreneurship and government support are the main drivers, supplemented by green technology capability, organizational learning, and market demand; the second category is &ldquo;green technology capability&ndash;market demand driven path&rdquo;, in which green technology capability and market demand are the main drivers, supplemented by organizational learning, entrepreneurship, and government support. This paper also identifies seven conditional configurations that lead to non-high innovation quality, which can be categorized as the technology-inhibited type, entrepreneurship-deprived type, and government and market-driven type. The discoveries of this paper have significant hypothetical and practical value for improving the innovation quality of agricultural enterprises.