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Title: The use of structured data analysis as a construction management research tool.
Author: Fisher, N.
ISNI:       0000 0001 3467 3674
Awarding Body: University of Reading
Current Institution: University of Reading
Date of Award: 1987
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Despite a large volume of published work in the area of construction management, few of the large number of publications examined as a result of a worldwide search describe work that involves the gathering of testable data that is, data in a form that will allow attempts to refute or test current theories or explanations. In this thesis criteria for good scientific research, that meet the current scientific paradigm, are established. A search is then made to find an appropriate technique, which will enable construction management research to adopt scientific criteria. Structured Data Analysis is identified as a possible and suitable technique that appears to meet the established scientific criteria, and to allow a degree of the testing which such criteria require. It is demonstrated that Structured Data Analysis makes some progress towards "refutation as a result of repeatability". The technique is applied in an area of considerable importance to management - that of the handling and management of information. As a systems-based technique, Structured Data Analysis takes a holistic perspective, and thus is capable of mapping and modelling the flow of data in and around an organisation, and of viewing the construction industry (or connected parts of it) as a single entity despite its traditional fragmentation. After a comprehensive description of Structured Data Analysis and its adaptation and development, from an electronic data processing system engineering tool to a management systems research tool, four areas are identified that are suitable for field testing. The field tests are then described. The conclusions drawn from the results of the field tests are discussed, in particular the suggestion that the technique could well make a useful and important contribution to: the process of testing current theories about and explanations of construction management practice, and the development of new or more complete theories or explanations that will contribute to the scientific discipline of construction management.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: nD modelling ; fragmentation ; information management ; scientific discipline ; field testing ; structured data analysis