The Sports and Leisure Characteristic Town (SLCT) has become a reasonable strategy for enhancing the sustainability of new urbanization processes in rural China. Although the Chinese government has issued a series of policies to support the development of SLCTs, limited financial resources are a major obstacle. Thus, public-private partnerships (PPPs) have been increasingly encouraged for establishing SLCT projects. However, the factors that significantly influence private partners’ willingness to participate in SLCT PPP projects remain unclear. The authors of this paper conducted expert interviews and questionnaire surveys concerning the SLCT PPP projects that have been implemented in China, identifying 23 factors that can be grouped into five major components using principal component factor analysis. Multiple linear regression was then performed to evaluate the relationships between factors and private partners’ willingness to participate. The results indicated that the factors that critically influence private partners’ willingness to participate include stakeholder factors, the internal factors of private partners, external environmental risk factors, the supporting measure factors of SLCTs, and the locational factors of SLCTs. This work also offers suggestions for encouraging private partners to participate in SLCT PPP projects. This study can provide a theoretical basis and practical guidance for government and private partners in order to help them implement sustainable SLCT PPP projects.
PurposeHuman–robot collaboration (HRC) is an emerging research field for the construction industry along with construction robot adoption, but its implementation remains limited in construction sites. This paper aims to identify critical risk factors and their interactions of HRC implementation during engineering project construction.Design/methodology/approachLiterature research, expert interviews, a questionnaire survey and a social network analysis (SNA) method were used. First, literature research and expert interviews were employed to identify risk factors of HRC implementation and preliminarily understand factor interactions. Second, a questionnaire survey was conducted to determine the degree of interactions between risk factors. Third, based on the data collected from the questionnaire survey, SNA metrics were used to find critical risk factors and critical interactions.FindingsThe critical risk factors consist of robot technology reliability, robot-perceived level, conflict between designers and users of construction robots, organisational culture, organisational strength, project cost requirements, changeability of project construction, project quality requirements and project safety requirements. The interactions between risk factors are strong and complex. Robot technology risk factors were relatively fundamental risk factors, and project risk factors had a direct influence on the risk of HRC implementation. The implementation cost of HRC was not identified as a critical risk factor. Individual risk factors could be mitigated by improving technical and organisational factors.Originality/valueThis paper contributes to the body of knowledge in the field of both HRC behaviours and its risk management in construction project management. Identifying the critical risk factors and their interactions of HRC implementation in the construction industry and introducing social network theory to the research on critical risk factors are the innovations of this paper. The findings and proposed suggestions could help construction professionals to better understand the HRC risk factors and to manage the risk of HRC implementation more effectively.
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