Narrow Results

This research aims to develop a conceptual framework in order to inquire into the dynamic growth process of university spin-outs (hereafter referred to as USOs) in China, attempting to understand the configuration of capabilities that are necessary for dynamic growth. Based on the extant literature and empirical cases, the study attempts to address the following question: How do USOs in China build and configure the innovation capabilities to cope with the dynamic growth? This paper aims to contribute to the existing literature by providing a theoretical discussion on the USOs' dynamic entrepreneurial process, by investigating the interconnections between innovation problem-solving and the required configuration of innovation capabilities in four growth phases. Further, it takes particular interest in the integrative capabilities and their impact on the USOs' entrepreneurial innovation process, in terms of knowledge integration, alliance, venture finance and venture governance. To date, studies have investigated the dynamic development process of USOs in China and have recognized the heterogeneity of USOs. Yet studies of capabilities that are required for rapid growth remain sparse. Addressing this research gap will be of great interest to entrepreneurs, policy-makers and venture investors.

In order to improve the influence of economic green transformation from the perspective of coordinated development of the industrial economy, an evaluation model of the influence of economic green transformation from the perspective of coordinated development of the industrial economy is constructed. An impact evaluation model of economic green transformation from the perspective of industrial economy coordinated development based on a clustering algorithm is proposed. A big data parameter collection model for the impact evaluation of economic green transformation in the perspective of coordinated development of the industrial economy is constructed, a structural block feature reorganization evaluation model, and adopt fuzzy C-means clustering method to realize the cluster analysis of the big data for the impact evaluation of economic green transformation in the perspective of coordinated development of the industrial economy is established. The cluster center optimization of the big data for the impact evaluation of economic green transformation in the perspective of coordinated development of the industrial economy is realized, and the candidate target set of the big data cluster area for the impact evaluation of economic green transformation in the perspective of coordinated development of the industrial economy is traversed, and the impact on economic green transformation in the perspective of coordinated development of the industrial economy is realized according to the different levels of clustering characteristics.