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Title: The use of decision support systems in making strategic decisions in local authorities : a comparative study of Egypt and the UK
Author: Elbeltagi, Ibrahim M.
Awarding Body: University of Huddersfield
Current Institution: University of Huddersfield
Date of Award: 2002
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The application of a modified Technology Acceptance Model (TAM) to determine the factors affecting the use of Decision Support Systems (DSS) in strategic decisionmaking in local authorities in both the UK and Egypt was the main core of this research. Although the use of DSS has become widespread in recent years for operational control its use in strategic decision-making has only rarely been seen. This research explores the problems which cause decision-makers not to use DSS effectively in making strategic decisions. Both the UK and Egypt have long histories of implementing IT in general and DSS in particular in local government. Although the UK has longer experience in adopting IT, both countries have failed to achieve the goals from this technology in a strategic context; however its operational use is quite good. The results of this research showed that the percentage of DSS usage in both the UK and Egypt were 40% and 30% respectively which means more than half of the investments in this kind of technology have not yet been used properly. This research has examined the strategic use of DSS and defined the most severe problems that could face decision makers when they use DSS strategically. To define the factors that affect DSS usage in making strategic decisions the researcher used the TAM which was first introduced in 1986 by F. Davis. This model enjoys a rich base of academic acceptance. Many subsequent studies have proven reliability of the measures and validity of the constructs and overall model. This study argues that TAM could be applicable to the context of the strategic use of DSS in local government in developing countries as it is successfully applied in developed countries in different kinds of technologies. This dissertation outlines a framework for the different factors that affect the strategic use of DSS in both the UK and Egypt. Also this research tries to find answers to the following questions: 1. What are the problems related to DSS usage in making strategic decisions? 2. What is the relative severity of these problems in both the UK and Egypt? 3. What are the differences between the UK and Egypt relating to the problems that decision-makers encounter? The hypotheses of this research were tested using a questionnaire as the main datagathering instrument in addition to interviews made mainly to validate and support the results of the quantitative approach. Rigorous validation procedures and statistical analysis methods were performed on the data, including face and content validity, alpha Chronbach and Factor analysis. The questionnaire was tested for reliability and validity and proved to be highly valid and reliable. The results of the analysis supported all hypothesised relationships. The results of this research showed that Perceived Usefulness (PU) made a significant direct effect on DSS usage in the UK group while Perceived Ease of Use (PEU) showed no significant effect in both countries in all variables apart from the internal support which was significant in the UK group. Also the results of this research showed that there was some similarity in both countries regarding the problems of strategic use of DSS, which were: absence of training for decision-makers to use DSS and failure to commit the required resources. These results indicate that if DSS is to be effectively used strategically by decision makers, local government in both developed and developing countries needs to apply greater funds to training, to making top-level decision makers comfortable with the use of DSS in hybrid (quantitative/qualitative) problem contexts and to providing those decision makers with DSS which target mainly strategic problems.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: HD28 Management. Industrial Management Political science Public administration Management Artificial intelligence