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Abdullatif, M I (1992) A system for quality-related costs for construction projects, Unpublished PhD Thesis, , University of Kansas.

Bypaneni, S P K (2017) A Bayesian network-based decision framework for selecting project delivery methods in highway construction, Unpublished PhD Thesis, , University of Kansas.

Chui, K W (2010) Comparison of construction labor productivity between U.S. and China: Using on-site productivity measurement methods, Unpublished PhD Thesis, , University of Kansas.

  • Type: Thesis
  • Keywords: accuracy; competitiveness; complexity; continuous improvement; efficiency; failure; market; measurement; measurement method; construction firms; construction project; municipality; benchmarking; markets; productivity; safety; China; statistical analysis
  • ISBN/ISSN:
  • URL: https://www.proquest.com/docview/746607980
  • Abstract:
    One of the main entry barriers faced by U. S. construction firms for entering the booming Chinese construction market is the acquisition of accurate labor productivity data in China. The accuracy of labor productivity data can mean the difference between the success or failure of a construction project. Due to the sheer diversity and complexity of international construction practices, minimal research has been performed on comparative labor productivity between the U. S. and China. In this study, on-site measurement research was conducted in the U. S. and China to assist U. S. construction firms in competing in the Chinese market by comparing the Chinese construction labor productivity with the U. S. labor productivity. The labor productivity data were collected randomly at jobsites located in Kansas, U. S. , and in Chongqing, China (Chongqing is the largest and most populated municipality of China’s four provincial-level municipalities) by using time studies method. Various statistical analysis methods were applied to analyze and compare the collected productivity data from both countries. Comparative review of productivity data will help enhance U. S. construction firms’ competitiveness in the Chinese market and improve project management capabilities in China. In addition, the results of a productivity comparison will provide U. S. construction firms the advancement of knowledge in the Chinese construction industry and support benchmarking and continuous improvement of efficiency and productivity with greater worker safety and satisfaction in the U. S. , China, or global construction markets.

Eilers, H I (2015) Impact of sustainable business practices on strategic performance for commercial building contractors, Unpublished PhD Thesis, , University of Kansas.

Guthrie, J L (2000) Group-level reengineering process, Unpublished PhD Thesis, , University of Kansas.

Hunt, B J P (1980) Development of a research program for scaffolding standards, Unpublished PhD Thesis, , University of Kansas.

Kim, S (2008) Development of a wireless real-time productivity measurement system for rapid construction operations, Unpublished PhD Thesis, , University of Kansas.

Maali, O M (2022) Management practices to improve adoption and employee well-being during organizational changes in the AEC industry, Unpublished PhD Thesis, , University of Kansas.

Mohamed, M (2022) A risk-based model for construction inspection in highways, Unpublished PhD Thesis, , University of Kansas.

Nguyen, P H D (2020) Development of fuzzy hybrid approaches to project delivery method selection in highway construction, Unpublished PhD Thesis, , University of Kansas.

Pasley, G P (1997) Steelteam: Creating a collaborative design environment for the steel building industry, Unpublished PhD Thesis, , University of Kansas.

Penland, J L (2002) Implementation of web-based team collaboration tools in the architectural, engineering and construction industry, Unpublished PhD Thesis, , University of Kansas.

Shalwani, A (2021) Empirical analysis of issue management in small vertical construction projects: Relationship between project performance, project team actions, and issue types, Unpublished PhD Thesis, , University of Kansas.