Identification of Key Success Factors for Private Science Parks Established from Brownfield Regeneration: A Case Study from China

Abstract

Private science parks (PSPs) are infrastructure elements of national high technology industrial development zones. Increasing private capital is being invested in this field to transform abandoned factories into science parks through brownfield regeneration, which not only effectively utilizes urban space, but also greatly strengthens the power of scientific and technological innovation. The evolution of these PSPs, however, is not satisfactory, and some operation and innovation-related problems often lead to their failures. Therefore, identifying key success factors is crucial for the sustainable growth of PSPs. This study employs Fuzzy Analytic hierarchy process (FAHP) and Fuzzy-DEMATEL (Decision Making Trial and Evaluation Laboratory) methods to construct an identification model for key success factors of PSPs established from brownfield regeneration. Associated influencing factors were collected through literature analysis, on-site interviews, and questionnaire, based on which key success factors were identified. The results of the study showed that five factors—resources sharing capacity of the park, park scale, financing and financial services, legal policy services and administrative capability, and construction level of facilities in the park—are the key success factors for such PSPs. The results also provide a theoretical basis for the development of PSPs established from brownfield regeneration, and support the formulation of PSP-related policies.

Science Parks, talent attraction and stakeholder involvement: an international study

“…This study measures park performance, dividing the Science Park success concept into two factors: (1) Successful tenant firms and (2) Successful innovation and technology transfer. Despite the lack of uniformity over the objectives of Science Parks and the methods to measure the performance of Science Parks, few studies have made substantial contributions to identifying the critical performance factors and empirically examining these effects (see Albahari et al 2013;Bigliardi et al 2006;Weng et al 2019). The literature does not present a clear definition of Science Parks (Quintas et al 1992), being their characteristics depend on the host country, level of regional development, fields of operations and industry characteristics (Spolidoro and Audy 2008).…”

Science Parks and talent attraction : a study on the development of Science Parks

“…The model shows that the characteristics of talents; the structure, processes, and characteristics of Science Parks; and relationships with stakeholders positively affect the development of activities for attracting talent. The model supplements existing research on Science Park development (Albahari et al, 2013(Albahari et al, , 2019Bigliardi et al, 2006;Weng et al, 2019) by introducing talent attraction activities as mediators for Science Park performance. The model thus offers tools for analysing Science Park performance based on an understanding of how they carry out talent attraction activities.…”

Spatial Identification and Redevelopment Evaluation of Brownfields in the Perspective of Urban Complex Ecosystems: A Case of Wuhu City, China

“…The existence of specificity and contradiction of various potential evaluation factors can cause fuzzy and uncertain evaluation results, making it difficult to reasonably choose clear boundaries to judge the risk of various factors in the evaluation process [ 34 ]. In this study, a fuzzy comprehensive evaluation method based on fuzzy set theory is used to precisely convert natural language into mathematical language to solve various difficult to quantify and non-deterministic problems.…”