Enhancing construction productivity through continuous process improvements

Cottrell, D S (1995) Enhancing construction productivity through continuous process improvements. PhD thesis, Texas A&M University, USA.

Abstract

This dissertation presents a series of regression models that relate job site productivity to process improvement initiatives executed both before and during construction. Applied during early project stages, these models help predict the expected value of productivity based on certain inputs related to pre-construction planning and construction execution. These models demonstrate the strong relationship of project performance to a variety of process improvement initiatives including design completeness, definition of a project vision statement, testing oversight, project team stability, and project manager experience and dedication. The correlational research methodology targeted seventy-five projects representing approximately $274. 53 million in civil construction. The data collection effort considered 47 process improvement initiatives (independent variables) using 106 quantitative and qualitative measures. The modeling technique involved the use of multiple linear regression, a method that exploits available data from multiple, independent sources to focus on specific outcomes. Models were developed from both owner and contractor information and were subjected to rigorous statistical analysis. The models provide project managers with a deliberate yet practical approach to project management and productivity enhancement. The dissertation results include verification analysis of the models using project data excluded from the data base that supported model development, sensitivity analyses aiding in beneficial application and interpretation, and an extensive discussion of the models' usefulness and limitations.

Item Type: Thesis (Doctoral)
Thesis advisor: Anderson, S D
Uncontrolled Keywords: project team; construction planning; productivity; owner; project manager; project performance; statistical analysis
Index terms: model development, expected value, stability, project data, sensitivity analysis, process improvement, project team, project management, construction planning, dissertation, testing, construction productivity, modelling, project performance, research methodology, statistical analysis, pre-construction, independent variable, productivity, owner, project manager, regression model
Subjects: construction planning, analytical methods, project delivery, data science, professional practice, operations management, research design and methodology, profession, research dissemination and communication, data collection methods, statistical analysis, environmental hazards, sociology, project management theory and practice, structural engineering, management
Topics: Site Management, Business Strategy, Project Management, Research Practice, Engineering Principles, Stakeholder Management, Roles and Professions, Sustainability
Descriptive scope: 4 PCEA

N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here