跳到主要內容

臺灣博碩士論文加值系統

(3.236.84.188) 您好!臺灣時間:2021/08/05 01:23
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果 :::

詳目顯示

: 
twitterline
研究生:何盈慧
研究生(外文):Ying-hui Ho
論文名稱:以結構方程模型結合TAM和IDT分析部落格使用者的使用態度之研究
論文名稱(外文):An analysis of the Blog-User'' attitude employing structural equation modeling combine TAM and IDT model
指導教授:黃昱凱黃昱凱引用關係
指導教授(外文):Yu-kai Huang
學位類別:碩士
校院名稱:南華大學
系所名稱:出版與文化事業管理研究所
學門:商業及管理學門
學類:其他商業及管理學類
論文種類:學術論文
論文出版年:2009
畢業學年度:97
語文別:英文
論文頁數:99
中文關鍵詞:部落格科技接受理論創新擴散理論重要度和滿意度分析結構方程模型
外文關鍵詞:Technology Acceptance ModelInnovation Diffusion TheoryBlogStructure Equation ModelingImportance-Performance Analysis
相關次數:
  • 被引用被引用:6
  • 點閱點閱:947
  • 評分評分:
  • 下載下載:318
  • 收藏至我的研究室書目清單書目收藏:4
  本研究探討的目的係促使顧客持續使用部落格(Blog)服務的態度的主要誘因。由許多理論的觀點集結成一個模型,假設使用者的持續行為。此模型是對部落格使用者使用經驗的廣泛調查。而科技接受模型(Technology Acceptance Model ,TAM)和創新擴散理論(Innovation Diffusion Theory, IDT)為本研究的理論基礎。本研究以結構方程模型(Structure Equation Modeling, SEM)和重要度和滿意度分析(Importance-Performance Analysis, IPA),分析有使用過部落格的使用者其有效問卷900份,並分析他們認為部落格的功能重要和滿意的地方,並對未來可能重要的部落格功能提出建議。
  
  本研究使用兩個不同的分析方法:結構方程模型和重要度和滿意度分析。顯著的結果包括:(1)部落格的有用性、易用性、可試用性和可觀察性對使用者的態度有正向的影響,而(2)重要度和滿意度的分析,部落格介面平穩、提供多樣化的功能和提供上傳精靈是是落在第一象限,(繼續保持區)。(3)部落格未來功能的重要度和滿意度則是認為間彼此可以分享資源是落在第一象限,(繼續保持區)。根據這些提供的結果來探討和研究。因此本研究最後將針對分析結果,提出建議給實務界和學術界。
  This paper examines key motivators for consumers’ attitude towards continuing the reception of existing blog services. Multiple theoretical perspectives are synthesized to hypothetically construct a model of continuance behavior, which is then empirically tested using a field survey of online blog users, and Technology Acceptance Model (TAM) and Innovation Diffusion Theory (IDT) are the study’s theoretical bases. The study uses Structure Equation Modeling (SEM) and Importance-Performance Analysis (IPA), and analyzes users who have used blogs and the 900 samplings were effectively taken as result. And this thesis also analyzes importance and performance perceived by sampled users in blogs’ functions, and gives some suggestions for blogs’ vital functions in the future.
  
  Two different analysis methods are used in this study: SEM and IPA. Salient results include: (1) blog’s usefulness, ease to use, trialability, and observability are positively affecting users’ attitude, (2) Base on Importance-Performance Analysis, if the interface is smooth, and it provides multiplicity and uploading functions belonged to quadrant 1, (keep up the good work), and (3) the most important blogs’ future functions is sharing resources between blogs associated with quadrant 1, (keep up the good work). Implications of these results for practice and research are provided as result. Finally, the result of this study is expected to serve as a useful guideline for Internet service providers and future research.
準碩士推薦 函…………………………………………… i
論文口試合格證明…………………………………………ii
謝誌………………………………………………………iii
摘要…………………………………………………………iv
Abstract…………………………………………………v
Outline……………………………………………………vi
List of Tables…………………………………………ix
List of Figures…………………………………………x
  
CHAPTER 1 INTRODUCTION 1
1-1 RESEARCH BACKGROUND AND MOTIVATION 1
1-2 RESEARCH PURPOSES AND QUESTION 3
1-3 RESEARCH OBJECTIVES AND SCOPE 4
1-4 RESEARCH PROCEDURES 5
  
CHAPTER 2 LITERATURE REVIEW 6
2-1 BLOG 6
2-1-1 Characteristic of blog 6
2-1-1 Summary 9
2-2 TECHNOLOGY ACCEPTANCE MODEL, (TAM) 10
2-2-1 Characteristic of TAM 10
2-2-2 Adopted variables 12
2-2-3 Summary 16
2-3 INNOVATION DIFFUSION THEORY, (IDT) 17
2-3-1 Characteristic of IDT 17
2-3-2 Adopted variables 19
2-3-3 Summary 21
2-4 CONCEPT MODEL 22
2-4-1 Summary 23
  
CHAPTER 3 METHODOLOGY 24
3-1 RELIABILITY ANALYSIS 24
3-2 AVERAGE VARIANCE EXTRACTED, (AVE) 25
3-2 CONFIRMATORY FACTOR ANALYSIS, (CFA) 25
3-3 IMPORTANCE-PERFORMANCE ANALYSIS, (IPA) 26
3-4 STRUCTURE EQUATION MODELING, (SEM) 28
3-4-1 SEM’s equation 29
  
CHAPTER 4 DATA COLLECTION 32
4-1 QUESTIONNAIRE DESIGN 32
4-1-1 TAM and IDT’s questionnaire design 33
4-1-2 IPA questionnaire design 35
4-2 DATA COLLECTION 37
  
CHAPTER 5 ANALYSIS AND RESULT 40
5-1 DESCRIPTIVE STATISTICS ANALYSIS 40
5-1-1 Demographic Characteristics 40
5-1-2 Multiple response 47
5-2 IMPORTANCE-PERFORMANCE ANALYSIS, (IPA) 52
5-2-1 All writers’ IPA analysis 52
5-2-2 Group IPA into three groups 53
5-2-3 Each blog’s importance and performance 60
5-2-4 Importance of blogs’ future functions analysis 63
5-3 STRUCTURAL EQUATION MODELING, (SEM) 66
5-3-1 Analysis of the measurement model 66
5-3-2 Moderated by Gender 72
5-3-3 Moderated by using blog’s time 74
  
CHAPTER 6 CONCLUSION 77
6-1 RESEARCH DISCOVERY 77
6-1-1 Demographic analysis 77
6-1-2 IPA results 78
6-1-3 Concept analysis 82
6-2 RESEARCH SUGGESTION 84
  
REFERENCE 86
  
APPENDIX (1)--QUESTIONNAIRE 93
網路資料:
  
1.創市際市場研究顧問公司,2007.09.21,近七成網友坐擁部落格 部落客願為空間影音上傳付費,【線上資料】:http://www.insightxplorer.com/news/news_09_21_07.html
  
2.Merriam-Webster Dictionary, Blog, source: http://www.merriam-webster.com/dictionary/blog.
  
3.Wikipedia, BLOG, source: http://en.wikipedia.org/wiki/BLOG.
  
中文書目:
  
1.邱政浩(2003)。結構方程模式。台北:雙葉書廊有限公司。
  
2.陳柏安、江今葉譯(2007)。部落格—改變世界的資訊革命。台北市:五南出版社。(原書: Hugh Hewitt (2005). Blog: understand the information reformation that’s changing your world.)
  
3.林震岩(2007)。Multivariate analysis:SPSS operation and application。台北市:智勝文化。
  
4.PCuSER研究室(2006)。Blog—不可思議部落格。台北市:電腦人文化。
  
西文書目:
  
1.Bentler, P. M. (1985). EQS Structural Equations Program Manual. Encion, CA: Multivariate Software.
  
2.Byrne, B. M. (1998). Structural Equation Modeling with LISREL, PRELIS, and SIMPLIS: Basic Concepts, Applications and Programming. Mahwah, NJ: Lawrance Erlbaum Associates.
  
3.Davis, F. D (1986). A Technology Acceptance Model for Empirically Testing New End-User Information Systems: Theory and Results, Doctoral Dissertation. MIT Sloan School of Management Cambridge MA.
  
4.Freeman, C. (1974). The economics of industrial innovation. Harmondsworth: Penguin.
  
5.Hair, J. E., Rolph, E. A., Ronald, L. T., and William, C. B. (1998). Multivariate Data Analysis. Prentice-Hall.
  
6.Joseph F. Hair, Jr., Willian C. Black, Barry J. Babin, Rolph E. Anderson, and Ronald L. Tatham (2006). MULTIVARIATE DATA ANALYSIS. New Jersey: Prentice Hall.
  
7.Moore, G.C. & Benbasat, I. (1996). Integrating diffusion of innovations and theory of reasoned action models to predict utilization of information technology by end-users. In K. Kautz and J. Pries-Heje (Eds.), In Diffusion and Adoption of Information Technology, 132-146. London: Chpman & Hall.
  
8.Rogers, E. M. (1983). Diffusion of innovations (3th. ed.). New York: The Free Press.
  
9.Rogers, E. M. (1995). Diffusion of innovations (4th. ed.). New York: The Free Press.
  
10.Schumpeter, J. A. (1984). Business cycles: A theoretical, historical and statistical analysis of the capitalist process (vols. 1-2). New York: McGraw-Hill.
  
中文論文:
  
1.王東澤〈2006〉。電子書市場認知與消費傾向之探討。成功大學高階管理學系碩士論文,未出版,台南市。
  
2.張彥淳〈2006〉。影響消費者採用行動付款因素之研究。中央大學資訊管理學系碩士在職專班碩士論文,未出版,桃園縣。
  
3.黃應欽(2006)。創新科技產品採用之研究—以往路電話為例。成功大學企業管理學系碩士論文,未出版,台南市。
  
4.黃耀民〈2006〉。人格差異特質對BLOG感受與使用研究。交通大學管理學院碩士在職專班國際經貿組碩士論文,未出版,新竹市。
  
5.廖御超〈2006〉。影響採用創新產品之相關因素探討—以3G手機為例。國立東華大學企業管理學系碩士論文,未出版,花蓮市。
  
6.鄭曉薇(2008)。應用劇變理論模型評估網路書店服務品質策略。南華大學出版與文化事業管理學系碩士論文,未出版,嘉義縣。
  
7.蔡明融〈2007〉。創新產品與服務特性、消費者個人特徵對知覺價值和態度影響之研究-以數位電視與電子現金為例。東吳大學國際貿易學系碩士論文,未出版,台北市。
  
8.謝政勳(2004),「應用分解式計劃行為理論探討消費者採用第三代行動通訊服務意願之研究」,未出版之碩士論文,樹德科技大學資訊管理系碩士班。
  
西文期刊:
  
1.Bagozzi, R. P., and L. W. Phillips (1982). Representing and Testing Organizational Theories: A Holistic Construal. Administrative Science Quarterly, 27(3), 459-89.
  
2.Bagozzi, R. P. and Yi, Y. (1998). “On the Evaluation of Structural Equation Models,” Journal of the Academy of Marketing Science, 16(1), 74-94.
  
3.Chin-Lung Hsu, Judy Chuan-Chuan Lin (2008). Acceptance of blog usage: The roles of technology acceptance, social influence and knowledge sharing motivation. Information & Management, 45, 65–74.
  
4.Carolina Lo’pez-Nicola’s , Francisco J. Molina-Castillo, Harry Bouwman. (2008). An assessment of advanced mobile services acceptance: Contributions from TAM and diffusion theory models. Information & Management, 45, 359–364.
  
5.Darley, J. M. & Beniger, J. R. (1981). Diffusion of energy conserving innovations. Journal of Social Issues, 37, 150-171.
  
6.Davis, F. D., R. P. Bagozzi and P. R. Warshaw (1989). User Acceptance of Computer Technology: A Comparison of Two theoretical Models. Management Science, 35(8), 982-1003.
  
7.D. A. Adams, R. R. Nelson, P. A. Todd (1992). Perceived usefulness, ease of use, and usage of information technology: a replication. MIS Quarterly, 16(2), 227-248.
  
8.Erik M. van Raaij, Jeroen J.L. Schepers (2008). The acceptance and use of a virtual learning environment in China. Computers & Education, 50, 838–852.
  
9.G. Premkumar, K. Ramamurthy, Hsin-Nan Liu (2008). Internet messaging: An examination of the impact of attitudinal, normative, and control belief systems. Information & Management ,45, 451–457.
  
10.Hansen, E., & Bush, R. J. (1999). Understanding customer quality requirements: model and application. Industrial Marketing Management, 28(2), 119–130.
  
11.Hu, L. and Bentler, P. L. (1999). Cutoff Criteria for Fit Index in Covariance Structural Equation Modeling. Structural Equation Modeling, 6(1), 1-55.
  
12.Hyoung-Yong Lee, Hyunchul Ahn, Ingoo Han (2007). VCR: Virtual community recommender using the technology acceptance model and the user’s needs type. Expert Systems with Applications, 33, 984–995.
  
13.I. Ajzen. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50 (2), 179–211.
  
14.Irwin Brown, Zaheeda Cajee, Douglas Davies, Shaun Stroebel (2003).” Cell phone banking: predictors of adoption in South Africa—an exploratory study” Information management, 381–394.
  
15.Il Im, Yongbeom Kim, Hyo-Joo Han. (2008). The effects of perceived risk and technology type on users’ acceptance of technologies. Information & Management, 45, 1–9.
  
16.Jarunee Wonglimpiyarat, and Napaporn Yuberk (2005). In support of innovation management and Roger’s Innovation Diffusion theory. Government Information Quarterly, 22, 411-422.
  
17.Jeroen Schepers, Martin Wetzels. (2007). A meta-analysis of the technology acceptance model: Investigating subjective norm and moderation effects. Information & Management, 44, 90–103.
  
18.June Lu, Chang Liu, Chun-Sheng Yu, Kanliang Wang. (2008). Determinants of accepting wireless mobiledata services in China. Information & Management, 45, 52–64.
  
19.Jo Williams (2008). Predicting an American future for cohousing. Futures, 40, 268–286.
  
20.Martilla, J. A., & James, J. C. (1977). Importance–performance analysis. Journal of Marketing, 41(1), 77–79.
  
21.Moore, G.C. & Benbasat, I. (1991). Development of an Instrument to Measure the Perceptions Adopting an Information Innovation. Institute of Management Sciences, 2(3), 192-222.
  
22.Matzler, K., Bailom, F., Hinterhuber, H. H., Renzl, B., & Pichler, J. (2004). The asymmetric relationship between attribute-level performance and overall customer satisfaction: a reconsideration of the importance–performance analysis. Industrial Marketing Management, 33(4), 271–277.
  
23.Marko P. Hekkert, Robert Harmsen, Arjen de Jong (2007). Explaining the rapid diffusion of Dutch cogeneration by innovation system functioning. Energy Policy, 35, 4677-4687.
  
24.Pavitt, K. (1984). Sectoral patterns of technical change: Towards a taxonomy and a theory. Research Policy, 13(6), 343-374.
  
25.P. Legris, J. Ingham, P. Collerette (2003). Why do people use information technology? A critical review of the technology acceptance model. Information & Management, 40, 191–204.
  
26.Raymond K.S. Chu, Tat Choi. (2000). An importance-performance analysis of hotel selection factors in the Hong Kong hotel industry: a comparison of business and leisure travelers. Tourism Management, 21, 363-377.
  
27.Rogers, E.M. (2002). Diffusion of preventive innovations. Addictive Behaviors, 27, 989–993.
  
28.Rita Walczuch, Jos Lemmink, Sandra Streukens. (2007). The effect of service employees’ technology readiness on technology acceptance. Information & Management, 44, 206–215.
  
29.Shin-ichi Todoroki, Tomoya Konishi, Satoru Inoue (2005). Blog-based research notebook: Personal informatics workbench for high-throughput experimentation. Applied Surface Science, 252, 2640–2645.
  
30.Sugato Chakravarty, Alan Dubinsky (2005). Individual investors’ reactions to decimalization: Innovation diffusion in financial markets. Journal of Economic Psychology, 26, 89–103.
  
31.Trijntje Vollink, Ree Meertens and Cees J. H. Midden (2002). Innovation ‘Diffusion of innovation’ theory: innovation characteristics and the intention of utility companies to adopt energy conservation interventions. Journal of Environmental Psychology, 22, 333-344.
  
32.Tae Goo Kim, Jae Hyoung Lee, Rob Law (2008). An empirical examination of the acceptance behaviour of hotel front office systems: An extended technology acceptance model. Tourism Management, 29, 500–513.
  
33.Vidhya Mellarkod, Radha Appan, Donald R. Jones, Karma Sherif (2007). A multi-level analysis of factors affecting software developers’ intention to reuse software assets: An empirical investigation. Information & Management, 44, 613–625.
  
34.Walter J. (2000). Technology adaptation and “Learning by cooperation”. A case study of a successful onshore technology transfer in Tierra del Fuego. Journal of Technology Transfer, 25, 13-20.
  
35.Weijaw Deng (2007). Using a revised importance–performance analysis approach:The case of Taiwanese hot springs tourism. Tourism Management, 28, 1274–1284.
  
36.Wei-Jaw Deng, Wen-Chin Chen and Wen Pei (2008). Back-propagation neural network based importance–performance analysis for determining critical service attributes. Expert Systems with Applications, 34, 1115–1125.
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top
無相關期刊