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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

The Effect of Consumer Decision Environment, Involvement and Knowledge to the Professional Service¡¦s Choice Model¡XTake EMBA for Example.

Hsiao, Shu-wen 13 July 2004 (has links)
This research takes the Executive Master of Business Administrator¡]EMBA¡^, a kind of higher education, as an example to discuss the consumer¡¦s choice models in the professional service. The main purpose of the research is to realize whether consumer¡¦s decision environment, involvement and knowledge of EMBA service as well as their personal difference will have connection with their choice models. About the research method, subjects were EMBA graduate students who ever had chosen experience. The sample came from north and south Taiwan where got more choices of EMBA school and received 192 valid questionnaires. For statistic analysis, the sample was separated into two groups by the number of decision environment¡¦s alternative and attribute quantity, and distinguished by both involvement and knowledge into low, median and high groups. The factor analysis, reliability analysis, chi-square test, discriminant analysis and one-way ANOVA are used as statistical analysis methods. The results are presented below: 1. When consumers choose EMBA, the number of alternatives has the connection with choice models. But there is no obvious connection between the number of attributes and the choice models. 2. When the degree of consumer involvement is different, the connection between alternative numbers and choice models will be different. 3. When the degree of consumer knowledge is different, the connection between alternative numbers and choice models will be different. 4. The difference of consumer personal factors only exist the connection with the consumer involvement of EMBA, but has no obvious connection with choice models and the knowledge of EMBA. Comparing to the other related researches, most of them are based on such as EKB model, analyzing all consumer decision or purchase processes. But those researches didn¡¦t investigate deep enough about consumer purchasing behavior¡¦s final secret process of professional services. Thus, this is an exploratory research, trying to describe the consumer decision situation of internal EMBA. And that is this research¡¦s contribution and value.
2

Business Intelligence Success: An Empirical Evaluation of the Role of BI Capabilities and the Decision Environment

Işik, Öykü 08 1900 (has links)
Since the concept of business intelligence (BI) was introduced in the late 1980s, many organizations have implemented BI to improve performance but not all BI initiatives have been successful. Practitioners and academicians have discussed the reasons for success and failure, yet, a consistent picture about how to achieve BI success has not yet emerged. The purpose of this dissertation is to help fill the gap in research and provide a better understanding of BI success by examining the impact of BI capabilities on BI success, in the presence of different decision environments. The decision environment is a composition of the decision types and the way the required information is processed to aid in decision making. BI capabilities are defined as critical functionalities that help an organization improve its performance, and they are examined in terms of organizational and technological capabilities. An online survey is used to obtain the data and partial least squares path modeling (PLS) is used for analysis. The results of this dissertation suggest that all technological capabilities as well as one of the organizational capabilities, flexibility, significantly impact BI success. Results also indicate that the moderating effect of decision environment is significant for quantitative data quality. These findings provide richer insight in the role of the decision environment in BI success and a framework with which future research on the relationship between BI capabilities and BI success can be conducted. Findings may also contribute to practice by presenting information for managers and users of BI to consider about their decision environment in assessing BI success.

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