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El-adaway, I H, Ali, G G, Eissa, R, Abdul Nabi, M, Ahmed, M O, Elbashbishy, T and Khalef, R (2023) Construction Management and Economics 40th anniversary: investigating knowledge structure and evolution of research trends. Construction Management and Economics, 41(04), 338–60.
Maslova, S and Burgess, G (2023) Delivering human-centred housing: understanding the role of post-occupancy evaluation and customer feedback in traditional and innovative social housebuilding in England. Construction Management and Economics, 41(04), 277–92.
Puolitaival, T, Kähkönen, K and Kestle, L (2023) The framing of construction management responsibilities in job advertisements in the UK and the USA. Construction Management and Economics, 41(04), 307–21.
Wang, Y, Yao, Y, Zhang, Y, Su, B and Wu, T (2023) Impact of industrial agglomeration on total factor productivity in the construction industry: evidence from China. Construction Management and Economics, 41(04), 322–37.
- Type: Journal Article
- Keywords: Industrial agglomeration; total factor productivity; the construction industry; linear regression model; non-linear regression model;
- ISBN/ISSN: 0144-6193
- URL: https://doi.org/10.1080/01446193.2022.2156570
- Abstract:
Industrial agglomeration (IA), a common industrial phenomenon, has been verified to have a significant impact on total factor productivity (TFP) in many industries. However, the impact of IA on TFP is seldom investigated in the construction industry, despite the existence of the industrial agglomeration phenomenon in the construction industry. As such, this study aims to probe into the impact of IA on TFP in the construction industry, so as to provide new insights into the industry development and improvement of TFP in the construction industry. Based on the competing results of the agglomeration effect and congestion effect caused by IA, this study proposed three hypotheses on the impact mechanism of IA on TFP in the construction industry. Then, the non-linear regression model and linear regression model were developed to test the hypotheses based on the provincial panel data from 2002 to 2017 in China. The empirical results reveal that IA has a positive linear impact on TFP in the construction industry, and the impact of IA on TFP in the Chinese construction industry during the observed period is in the embryonic stage. Besides, both the firm scale and economic development level have positive impacts on TFP, whereas the specialization structure has a negative impact. Hence, the government can encourage industrial agglomeration in the construction industry to enhance TFP, in order to leverage the knowledge spillovers, labor pool, and other benefits from IA.
Zapata Quimbayo, C A and Mejía Vega, C A (2023) Credit risk in infrastructure PPP projects under the real options approach. Construction Management and Economics, 41(04), 293–306.