Philosophiae Doctor - PhD (Information Systems)

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https://hdl.handle.net/10566/12625

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Browsing by Subject "Data and Information"

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    A Conceptual Model for determining the Value of Business Intelligence Systems
    (University of the Western Cape, 2014) Budree, Adheesh; Fourie, Louis CH.
    Business Intelligence refers to the use of Information Systems to enable raw data to be collated into information that can be reported, with the end goal of using this information to enhance the business decision-making process. Business Intelligence is enabled by making use of information that is complete, relevant, accurate, timely and accessible. There are currently a number of documented perspectives that can be used to gauge the value of Business Intelligence systems; however, from an overall business value perspective the most robust method would be to identify and analyse the most commonly identified factors that impact the value assigned to Business Intelligence Systems by a company, and the correlation of each of these factors to calculate the overall value. The importance of deriving a conceptual model, representing the major factors identified from literature and moderated by the quantitative research conducted, lies in its enabling companies and government bodies to assess the true value addition of Business Intelligence systems, and to understand the return on investment of these systems for organisations. In doing so, companies can justify or reject any further expenditure on Business Intelligence. The quantitative research for this thesis was conducted together with a project that was run between the University of the Western Cape and the Hochschule Neu-Ulm University of Applied Sciences in Germany. The research was conducted simultaneously across organisations in South Africa and Germany on the use of BI Systems and Corporate Performance Management. The respondents for the research were Chief Executive Officers, Chief Information Officers and Business Intelligence Managers in selected organisations. A Direct Oblimin-factor analysis was conducted on the online survey responses. The survey was conducted on a sample of approximately 1500 Business Intelligence specialists across South Africa and Germany; and 113 responses were gathered. The factor analysis reduced the key factors identified in the literature to a few major factors, namely: Information Quality, Management and Accessibility, Information Usage, and Knowledge-sharing Culture. Thereafter, a Structural-Equation-Modelling analysis was completed using the Partial-least-Squares method. The results indicate that there is a strong relationship between the factor-Information Quality, Management and Accessibility, and the Value of Business Intelligence. It was found that while there was no strong impact from Information Usage and Culture, there was a strong correlation between Information Usage and Culture and Information Quality, Management and Accessibility The research findings are significant for academic researchers, information technology experts, Business Intelligence specialists and Business Intelligence users. This study contributes to the body of knowledge by bringing together disparate factors that have been identified in academic journals; and assessing the relationship each has on the value of Business Intelligence, as well as the correlations that exist between these factors. From this, the final conceptual model was derived using factors that were identified and tested through the Factor Analysis and the PLS-SEM. The following conclusions can be drawn from the research: (1) The assurance of quality information in the form of complete, accurate, relevant and timeous information that is efficiently managed is the most paramount factor to an organisation deriving value from Business Intelligence systems; (2) information accessibility is key, in order to realise the value of Business Intelligence systems in organisations; and (3) Business Intelligence systems cannot add value to an organisation if a culture of information use and sharing is absent within that organisation. The derived model can be practically implemented as a checklist for organisations to assess Business Intelligence system investments as well as current implementations
  • Thumbnail Image
    Item
    A Conceptual Model for determining the Value of Business Intelligence Systems
    (University of the Western Cape, 2014) Budree, Adheesh; Fourie, Louis CH.
    Business Intelligence refers to the use of Information Systems to enable raw data to be collated into information that can be reported, with the end goal of using this information to enhance the business decision-making process. Business Intelligence is enabled by making use of information that is complete, relevant, accurate, timely and accessible. There are currently a number of documented perspectives that can be used to gauge the value of Business Intelligence systems; however, from an overall business value perspective the most robust method would be to identify and analyse the most commonly identified factors that impact the value assigned to Business Intelligence Systems by a company, and the correlation of each of these factors to calculate the overall value. The importance of deriving a conceptual model, representing the major factors identified from literature and moderated by the quantitative research conducted, lies in its enabling companies and government bodies to assess the true value addition of Business Intelligence systems, and to understand the return on investment of these systems for organisations. In doing so, companies can justify or reject any further expenditure on Business Intelligence. The quantitative research for this thesis was conducted together with a project that was run between the University of the Western Cape and the Hochschule Neu-Ulm University of Applied Sciences in Germany. The research was conducted simultaneously across organisations in South Africa and Germany on the use of BI Systems and Corporate Performance Management. The respondents for the research were Chief Executive Officers, Chief Information Officers and Business Intelligence Managers in selected organisations. A Direct Oblimin-factor analysis was conducted on the online survey responses. The survey was conducted on a sample of approximately 1500 Business Intelligence specialists across South Africa and Germany; and 113 responses were gathered. The factor analysis reduced the key factors identified in the literature to a few major factors, namely: Information Quality, Management and Accessibility, Information Usage, and Knowledge-sharing Culture. Thereafter, a Structural-Equation-Modelling analysis was completed using the Partial-least-Squares method. The results indicate that there is a strong relationship between the factor-Information Quality, Management and Accessibility, and the Value of Business Intelligence. It was found that while there was no strong impact from Information Usage and Culture, there was a strong correlation between Information Usage and Culture and Information Quality, Management and Accessibility The research findings are significant for academic researchers, information technology experts, Business Intelligence specialists and Business Intelligence users. This study contributes to the body of knowledge by bringing together disparate factors that have been identified in academic journals; and assessing the relationship each has on the value of Business Intelligence, as well as the correlations that exist between these factors. From this, the final conceptual model was derived using factors that were identified and tested through the Factor Analysis and the PLS-SEM. The following conclusions can be drawn from the research: (1) The assurance of quality information in the form of complete, accurate, relevant and timeous information that is efficiently managed is the most paramount factor to an organisation deriving value from Business Intelligence systems; (2) information accessibility is key, in order to realise the value of Business Intelligence systems in organisations; and (3) Business Intelligence systems cannot add value to an organisation if a culture of information use and sharing is absent within that organisation. The derived model can be practically implemented as a checklist for organisations to assess Business Intelligence system investments as well as current implementations