Capano, C D (2007) Construction operations analysis for development of historical cost databases. PhD thesis, Marquette University, USA.
Abstract
Construction companies are vast silos of information and data. The companies utilize this data for a host of processes within their organization. The ability to share this data and efficiently query across the variety of data formats and software platforms is still a complex problem that many construction companies are trying to unravel. The data can be in paper or digital forms. There is a tremendous amount of data that is accumulated and stored in the typical business enterprise of all construction companies. Estimates, construction schedules, marketing information, human resources, managerial decision-making, and a host of other functions rely on the accurate exchange of data for planning and forecasting business functions. The problem that exists is that much of this data is stored in multiple places in various formats and cannot be accessed easily when needed. This leaves a tremendous amount of information duplication and manual re-entry. It also limits the ability to query the information for use in decision analysis and forecasting. Construction operations is a key business function for any construction company and is central to completion of projects. An analysis of this function was performed for the purpose of identifying the data generated and development of data models for manipulation and storage of field data used in the process of estimating. A critical business process for a construction company is estimating. Estimating relies on experience and knowledge of past practices. The understanding and definition of the data required to produce estimates is important. This research will also explore the requirements for the estimating process and data collection and will examine how this data should be efficiently structured in a historical cost database to improve access, minimize paper forms, and be available for future estimating purposes.
| Item Type: | Thesis (Doctoral) |
|---|---|
| Thesis advisor: | Karshenas, S |
| Uncontrolled Keywords: | market; estimating; forecasting; marketing; decision analysis |
| Index terms: | forecasting, construction company, platform, human resource, data model, marketing, estimating, construction operation, database, decision-making, decision analysis, estimate |
| Subjects: | construction operations, prediction and forecasting, management, organization, decision analysis, data management, business, data science, financial and cost management, digital design |
| Topics: | Business Strategy, Site Management, Risk Management, Cost Management, Digital Applications, Human Resources, Research Practice |
| Descriptive scope: | 3 PCA |
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