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UNT Theses and Dissertations
Business Intelligence Success: An Empirical Evaluation of the Role of BI Capabilities and the Decision Environment
Date: August 2010
Creator: Işik, Öykü
Description: 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 ...
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Comparing Latent Dirichlet Allocation and Latent Semantic Analysis as Classifiers
Date: December 2011
Creator: Anaya, Leticia H.
Description: In the Information Age, a proliferation of unstructured text electronic documents exists. Processing these documents by humans is a daunting task as humans have limited cognitive abilities for processing large volumes of documents that can often be extremely lengthy. To address this problem, text data computer algorithms are being developed. Latent Semantic Analysis (LSA) and Latent Dirichlet Allocation (LDA) are two text data computer algorithms that have received much attention individually in the text data literature for topic extraction studies but not for document classification nor for comparison studies. Since classification is considered an important human function and has been studied in the areas of cognitive science and information science, in this dissertation a research study was performed to compare LDA, LSA and humans as document classifiers. The research questions posed in this study are: R1: How accurate is LDA and LSA in classifying documents in a corpus of textual data over a known set of topics? R2: How accurate are humans in performing the same classification task? R3: How does LDA classification performance compare to LSA classification performance? To address these questions, a classification study involving human subjects was designed where humans were asked to generate and classify documents ...
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Factors Influencing BI Data Collection Strategies: An Empirical Investigation
Date: August 2010
Creator: Ramakrishnan, Thiagarajan
Description: The purpose of this dissertation is to examine the external factors that influence an organizations' business intelligence (BI) data collection strategy when mediated by BI attributes. In this dissertation, data warehousing strategies are used as the basis on which to frame the exploration of BI data collection strategies. The attributes include BI insightfulness, BI consistency, and the organizational transformation attribute of BI. The research population consisted of IT professionals and top level managers involved in developing and managing BI. Data was collected from a range of industries and organizations within the United States. An online survey was used to collect the data to empirically test the proposed relationships. Data was analyzed using partial least square path modeling (PLS). The results of this study suggest that there exists a positive relationship between institutional isomorphism and BI consistency. The results also indicate that there exists a positive relationship between BI consistency and BI comprehensive data collection strategy, and the organizational transformation attribute of BI and BI comprehensive data collection strategy. These findings provide a theoretical lens to better understand the motivators and the success factors related to collecting the huge amounts of data required for BI. This study also provides managers with ...
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Impact of Forecasting Method Selection and Information Sharing on Supply Chain Performance.
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Date: December 2009
Creator: Pan, Youqin
Description: Effective supply chain management gains much attention from industry and academia because it helps firms across a supply chain to reduce cost and improve customer service level efficiently. Focusing on one of the key challenges of the supply chains, namely, demand uncertainty, this dissertation extends the work of Zhao, Xie, and Leung so as to examine the effects of forecasting method selection coupled with information sharing on supply chain performance in a dynamic business environment. The results of this study showed that under various scenarios, advanced forecasting methods such as neural network and GARCH models play a more significant role when capacity tightness increases and is more important to the retailers than to the supplier under certain circumstances in terms of supply chain costs. Thus, advanced forecasting models should be promoted in supply chain management. However, this study also demonstrated that forecasting methods not capable of modeling features of certain demand patterns significantly impact a supply chain's performance. That is, a forecasting method misspecified for characteristics of the demand pattern usually results in higher supply chain costs. Thus, in practice, supply chain managers should be cognizant of the cost impact of selecting commonly used traditional forecasting methods, such as moving ...
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The Impact of IT Capability on Employee Capability, Customer Value, Customer Satisfaction, and Business Performance
Date: August 2009
Creator: Chae, Ho-Chang
Description: This study empirically examines the impact of IT capability on firms' performance and evaluates whether firms' IT capabilities play a role in improving employee capability, customer value, customer satisfaction, and ultimately business performance. The results were based on comparing the business performance of the IT leader companies with that of control companies of similar size and industry. The IT leader companies were selected from the Information Week 500 list published annually from 2001 to 2004. For a company to be selected as IT leaders, it needed to be listed at least twice during the period. Furthermore, it had to be listed in the American Customer Satisfaction Index (ACSI) so that its customer satisfaction level could be assessed. Standard & Poor's Compustat and the ACSI scores were used to test for changes in business performance. The study found that the IT leaders had a raw material cost measured by cost-of-goods-sold to sales ratio (COGS/S) than the control companies. However, it found no evidence that firms' IT capability affects employee capability, customer value, customer satisfaction, and profit. An important implication from this study is that IT becomes a commodity and an attempt to gain a competitive advantage by overinvesting in IT may ...
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The Impact of Quality on Customer Behavioral Intentions Based on the Consumer Decision Making Process As Applied in E-commerce
Date: August 2012
Creator: Wen, Chao
Description: Perceived quality in the context of e-commerce was defined and examined in numerous studies, but, to date, there are no consistent definitions and measurement scales. Instruments that measure quality in e-commerce industries primarily focus on website quality or service quality during the transaction and delivery phases. Even though some scholars have proposed instruments from different perspectives, these scales do not fully evaluate the level of quality perceived by customers during the entire decision-making process. This dissertation purports to provide five main contributions for the e-commerce, service quality, and decision science literature: (1) development of a comprehensive instrument to measure how online customers perceive the quality of the shopping channel, website, transaction and recovery based on the customer decision making process; (2) identification of the determinants of customer satisfaction and the key dimensions of customer behavioral intentions in e-commerce; (3) examination of the relationships among perceived quality, customer satisfaction and loyalty intention using empirical data; (4) application of different statistical packages (LISREL and PLS-Graph) for data analysis and comparison of how these methods impact the results; and (5) examination of the moderating effects of control variables. A survey was designed and distributed to a total of 1126 college students in a ...
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