Abstract Following the vigorous development of the information and internet technology, the National Tax Administrations are now facing the challenges from the changes of the inner and outer environment. Due to the update of the information operating platform as well as the drive of e-government from the Executive Yuan, the government officials need to have abilities to learn new information technology; otherwise, they will fail to be qualified on their jobs. However, there are not too many studies about the degree of acceptance of officials on learning new technology. It is necessary to provide an approach to figure out acceptance degree of officials for information technology. We provide an integrated model called the Technology Acceptance Model on government officials. The model incorporates a wide variety of important factors into a theoretical framework provided by "Technology Acceptance Model, TAM" (Davis, 1989) and "Theory of Planned Behavior, TPB" (Ajzen, 1985). We collect data from a sample of staffs of the five local tax administrations and we analyze the data using the Structural Equation Modeling. The results of this research indicate that essential factors and show what factors affect the behavior of the government officials on accepting new technology and e-government. In addition, the model provides a good fit because of fit indices and explanatory powers for behavior. That is, we can use the model to predict the officials¡¦ behavior on using tax information system.

The Indian IT industry has grown at an impressive rate during the last decade. India's own competitive advantage in the software business is well known: cost-effectiveness, world-class quality, high reliability, and rapid delivery, all of it powered by state-of-the-art technologies. Software has penetrated different spheres of the Indian economy, namely Indian corporate sector, government and public sector units. Over the last decade, one of the sectors, which have felt the "heat" of software intrusion, has been the financial service. Indian banking industry, today is in the midst of an IT revolution. A combination of regulatory and competitive reasons have led to increasing importance of total banking automation in the Indian Banking Industry. The present level of computerization in Public Sector Banks is a result of these initiatives. RBI has also gone ahead in creating of nation wide and localized networks for integration of the entire financial system. The Software Packages for Banking Applications in India had their beginnings in the middle of 80s, when the Banks spurred on by RBI and the Rangarajan Committee Report, started computerizing the branches in a limited manner. A few software companies in the country have developed banking software products and most of the banks have adopted them. These products enable all the banks to automate their operations at the branches and corporate offices. The software companies develop 60% of the software in the company itself, which involves the development of modules, and the remaining 40% is done in the customer's site. This 40% is customization of the software. The success of these banking software products in the banks can be measured by studying the market share of the individual products, revenues earned by these products by the respective companies. The success of these products depends on the satisfaction of the users, using the software. To measure their satisfaction and arrive at those products that are performing well in terms of User satisfaction, the following objectives were designed in the present study. The objectives are: 1. To understand the attributes of the banking software products that are relevant to user/customer satisfaction. 2. To understand the user's perception of the above attributes. 3. To derive the key factors of user/customer satisfaction. 4. To develop an Importance-Performance map for the attributes of the software. Based on the literature review and the discussions held with the software professionals and bank employees, we identified few relevant variables like Implementation, Maintainability, Reliability, Security, User's Performance and Output which fall under the software related variables and variables like Vendor's meeting User's needs, Vendor's mktg skill, User involvement, Training and support, and Service falling under the vendor related variables. A structured questionnaire was developed based on these variables using a 5-pt likert scale and this instrument was checked for its construct and content validity and also Reliability by conducting Factor analysis and Computing Cronbach's alpha respectively on a small sample in the Pilot study. The questionnaire was modified and the final instrument was used for the main study. This questionnaire was administered on a sample of 141 in the main study. The collected data were subjected to Factor Analysis to arrive at the key factors of User satisfaction for banking software products. We obtained seven factors User's Performance, Output, and Vendor's Marketing skill, Implementation, Ease of Use, Security and Maintainability. The second part of the study plot an Importance -Performance Map for all the products on all variables which gives us the best performer. Since this was subjective analysis, we conducted ONE-WAY ANOVA on the data to arrive at the best performer. However, ANOVA could give only the top performer, but we were not able to identify the second best product. We computed the weighted scores for each of these products by giving weights to the variables and multiplying with the performance scores. The comparison of the total weighted scores of all the four products considered in the study helped us in ranking the products based on their performance. We obtained that Product 3 was on top followed by Product 4 and Product 1 and last was product 2. Based on these analyses we suggested the following to the software vendors: 1. The key factors identified in the study should be given the highest priority while developing and testing the software for conformance with the specifications. 2. Product 2 must be improved on variables like output by making the report generation more flexible and maintainability should be made easier by making additions more flexible without any errors. 3. Vendors of Product 1 and 2 should provide better user manuals using simple language and also train the bank employees in using the software, by involving employees during customization in a more informal way. 4. Vendor's of Product 3 and 4 should maintain the quality of their existing products respectively and try to improve them.

Computing / M. Sc. (Information Systems)

資訊管理文獻中，對於電子商務環境的顧客資訊滿意度衡量模式甚少探討。目前文獻中的使用者資訊滿意度(UIS)，以及使用者自建系統滿意度(EUCS)兩種衡量模式，主要是適用於「傳統資料處理環境」或是「使用者自建系統環境」。因此，本研究將發展一個適用於「數位產品網路行銷環境」的顧客資訊滿意度衡量模式。首先，本研究探討了網站顧客資訊滿意度(WCIS)的概念性定義，作者從文獻中歸納出初步的顧客資訊滿意度衡量構面與問項，並透過訪談、焦點群體、先導研究等方法來加以補充與調整。再者，本研究也說明了量表問項產生過程、資料蒐集方法、以及純化測量的步驟。作者並運用兩個配額樣本來進行探索性因素分析以及驗證性因素分析，其中嚴謹地檢驗了顧客資訊滿意度衡量模式的信度、內容效度、效標關聯效度、收歛效度、區別效度，以及法理效度。最後，本研究探討了顧客資訊滿意度衡量模式在實務界與學術界的應用方式，並討論了本研究所面臨的若干限制，同時提出一些未來可以進一步研究的方向。作者希望本研究所提出的顧客資訊滿意度衡量模式，未來可以被其他研究人員用來發展網路行銷或電子商務理論。 CHAPTER 1. INTRODUCTION….………………………………………….….…1 CHAPTER 2. DOMAIN OF WEB CUSTOMER INFORMATION SATISFACTION ……………………………………………………………………..4 2.1 The Focus of This Study…………………………………………….…..…….4 2.2 The Impact of E-commerce on the Business Process of DPSPs….……….…..5 2.3 Instruments for Measuring User Information Satisfaction (UIS) and End-User Computing Satisfaction (EUCS)…….……………..……………….6 2.4 The Conceptual Definition of Web Customer Information Satisfaction ….…..9 2.5 The Theoretical Framework for Assessing WCIS……………………….…..12 2.6 Service Quality versus Customer Satisfaction………………………….……14 CHAPTER 3. GENERATION OF SCALE ITEMS……….……………………...16 3.1 Generation of Initial Item List……………………………………………...16 3.2 Pilot Study…………………………………………………………………....17 CHAPTER 4. SCALE PURIFICATION AND EXPLORATORY FACTOR ANALYSIS…...…………………………………………………………..19 4.1 Sample and Procedure……………………………………………………….19 4.2 Item Analysis and Reliability Estimates……………………………………..20 4.3 Identifying the Factor Structure of the WCIS Construct…..…………………21 4.4 Reliability…………………………………………………………………….23 4.5 Content Validity………………………………………………………………25 4.6 Criterion-Related Validity……………………………………………………25 4.7 Reliability and Criterion-Related Validity by Type of Web Site……………..26 4.8 Discriminant and Convergent Validity……………………………………….27 4.9 Nomological Validity………………………………………………………...28 CHAPTER 5. THE CONFIRMATORY FACTOR ANALYSIS OF THE WCIS INSTRUMENT………………………………………………...……………30 5.1 Need for Confirmatory Analysis………………………………………….….30 5.2 Methods……………………………………………………………………....33 5.3 Data Collection for Confirmatory Analysis………………………………….41 5.4 Alternative Models…………………………………………………..……….43 5.5 Criteria for Comparing Model-Data Fit…..………………………………….46 5.6 Checks for Statistical Assumptions………………………………………….49 5.7 Estimation Method…………………………………………………………...50 5.8 Results………………………………………………………………………..50 5.9 Assessment of Reliability and Validity………………………………………55 5.10 The Measurement of Service Quality……………………………………….60 5.10.1 The Development of SERVQUAL and IS-adapted SERVQUAL………61 5.10.2 Refinement of an EC-adapted SERVQUAL…………………………...66 5.11 Research Findings for Confirmatory Analysis……………………………...72 5.11.1 Findings for Question One……………………………………………72 5.11.1 Findings for Question Two……………………………………………74 5.12 Comparison of Underlying Dimensions Between UIS, EUCS and WCIS…………………………………………………………………..76 CHAPTER 6. IMPLICATIONS………….………………………………………..77 6.1 Implications for Practice……………………………………………….....….77 6.2 Implications for Research.……………………………………………………79 CHAPTER 7. CONCLUSION……..………………………………………………81 REFERENCE……………...………………………………………………………..83 GLOSSARY…………………………………………………………………………95 APPENDIX A Measurement of Web Customer Information Satisfaction – Forty-Three Items Used in the Pilot Study…………………………………………...97 APPENDIX B Observed Correlation Matrix of WCIS Instrument in Confirmatory Analysis..……………………………………………………………....99 APPENDIX C Observed Correlation Matrix of Initial EC-SERVQUAL Instrument…………….……………………...………………………………………100 APPENDIX D The LISREL Program for WCIS Model 1……..…………………...101 APPENDIX E The LISREL Program for WCIS Model 2.……….………………...102 APPENDIX F The LISREL Program for WCIS Model 3...………………………...104 APPENDIX G The LISREL Program for WCIS Model 4..………………………...105 APPENDIX H The LISREL Program for EC-SERVQUAL Model 1.…………….106 APPENDIX I The LISREL Program for EC-SERVQUAL Model 2.…………….107 APPENDIX J The LISREL Program for The Structural Model Between WCIS and EC-SERVQUAL Measures………………………………..………………...108 ABOUT THE AUTHOR…………………………………………………………...110 / MIS literature has not addressed the measurement of web customer information satisfaction (WCIS) in electronic commerce. Current models for measuring user information satisfaction (UIS) and end-user computing satisfaction (EUCS) are perceived as inapplicable as they are targeted primarily towards either conventional data processing or the end-user computing environment. This study develops a comprehensive model and instrument for measuring customer information satisfaction for web sites that market digital products and services. This paper first discusses the concepts and definitions of WCIS construct from the literature. The researcher summarizes his findings in a theoretical framework. Based on this framework, the researcher develops a measurement instrument to measure web customer information satisfaction. The procedures used in generating items, collecting data, and purifying a multiple-item scale are described. The researcher has carefully examined evidences of reliability, content validity, criterion-related validity, convergent validity, discriminant validity, and nomological validity by analyzing data from two quota samples. The potential applications for practitioners and researchers are then explored. Finally, the researcher concludes this study by discussing limitations and potential future research. The researcher hopes that the proposed WCIS instrument with good reliability and validity can be used by other researchers to develop and test Internet marketing and EC theories in the future.

Computing / M. Sc. (Information Systems)