簡易檢索 / 詳目顯示

研究生: 鄒春旺
Tsou, Chun-Wang
論文名稱: 影響購買易網筆電為第二台筆電意願的前置因素
Investigating the Antecedents of Intentions to Purchase a Netbook as a Second Laptop
指導教授: 廖俊雄
Liao, Chun-Hsiung
學位類別: 博士
Doctor
系所名稱: 管理學院 - 交通管理科學系
Department of Transportation and Communication Management Science
論文出版年: 2010
畢業學年度: 98
語文別: 英文
論文頁數: 139
中文關鍵詞: 易網筆電產品屬性認知知覺樂趣個人創新特性
外文關鍵詞: Netbook, Product Attributes, Perceptions, Perceived Enjoyment, Personal Innovativeness
相關次數: 點閱:104下載:1
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報
  • 無所不在的無線傳輸網路,如Wi-Fi或3G等無線網路基礎建設由電信業者或通信服務業者提供個人或商業所需要的創新資料與語音服務,導致使用易網筆電的使用者增加,成為他們生活中不可缺少的部份。一種精巧、負擔得起以及網路驅動連接的易網筆電在近年來年推出以後,廣受使用者的喜愛,同時其總銷售量已超過一般筆電型電腦。
    本文的研究建構一個觀念性研究架構,並實證消費者接受易網筆電產品。透過回顧目前的模式,本文提出以產品的屬性(系統特性與產品可攜性)、個人對新資訊產品的認知(易用性、適合性與相對利益)、個人創新性以及認知樂趣作為基本的架構。產品的屬性與個人對新資訊產品的認知是影響認知樂趣的兩個重要的前置因素,然後再次影響使用者對該產品的態度與使用者購買易網筆電作為第二台筆電的意向。再者,本文導入一項個人的創新特性,驗證該構面影響產品的屬性、個人對新資訊產品的認知與使用者意圖購買該產品當作第二台筆電的前置因素。
    本研究針對目前擁有筆電的使用者進行實測調查,檢驗他們對採用易網筆電作為第二台筆電的意願,尤其是資料來自於兩個不同群體,分別是272位大學生(含研究生)以及319位不同企業的員工分別做為本研究之有效群體樣本。本研究模式係由9個構面,共40項量測變數所組成。為精確計量研究模式,本文採用兩階段式模式評估方法,檢定與測試模式之建構。首先,使用驗證以驗證性因素分析評估量測變數對應至該潛在構面,以及構面的信度與校度。接著在以結構方程模式檢定假設構面之間的因果關連與統計顯著性。
    從兩個不同的群體的驗證,本文得到以下幾點發現:(1) 對不同企業員工的群體而言,產品的可攜性是正向顯著影響其使用態度,但不顯著影響其知覺樂趣。有趣的是,對學生群體而言,產品的可攜性對知覺樂趣的影響是反向顯著的,但對於態度的影響是不顯著。(2) 對兩個不同群體,兩個認知因素(適合性與相對利益)是正向顯著影響知覺樂趣,然後依序影響其態度。(3) 個人的創新特性對兩個不同群體而言,成功地扮演產品的屬性中的可攜性與個人認知中的相對利益之前置因素,但對使用者意圖購買該產品當作第二台筆電的影響僅對企業員工有顯著的關連。
    本研究提供下列的管理意涵:隨著社會人口結構、使用環境與個人對新資訊產品的認知等的差異性,不同的群體對易網筆電的認知與使用需求不同。然而,電腦廠商利用易網筆電的便利性、易用性、可支付性、可攜性、與具樂趣的創新性、精巧設計等均是有效的行銷策略,促成消費者將該產品定位成個人的第二台筆電,而不是取代一般筆電。

    Ubiquitous wireless networks such as Wi-Fi network or cellular 3G infrastructure offer individuals or businesses innovative data and voice services to by vendors or carriers, and lead to the increased users of netbook as an inevitable part of works and lives. A compactly designed and affordable netbook with Internet-enabled connections are extremely popular in computer markets, and the overall sales have surpassed that of laptop computers in recent years.
    This study constructs a conceptual model to empirically test user’s acceptance of a new information technology (IT) product, netbook. By reviewing the existing literature, a research model is proposed based on the product attributes of innovative IT, individual perceptions about a new IT, personal innovativeness and perceived enjoyment. Perceptions about a new IT product (ease of use, compatibility, and relative advantages) and its product attributes (system features and product portability) are the salient antecedents of perceived enjoyment, which, in turn, affects attitude toward use and links to user’s intentions to purchase a netbook as a second laptop. In addition, personal innovativeness is validated as the antecedent variable of product attributes, the perceptions about a new IT product and intentions to purchase a netbook as a second laptop.
    A field survey of laptop users is adopted in the study to examine the research model of users’ intention to adopt a netbook as a second laptop. In particular, the data from two distinct groups, 272 effective respondents from university students and 319 effective respondents from practitioners in various industries are collected and utilized. Nine constructs with 40 measured variables for this study are developed from prior studies and used to test the research model. To gauge the research model, a two-step approach is adopted in model construction and testing. First, confirmatory factor analysis (CFA) is used to confirm the measurement model for reliability and validity, including internal consistency, convergent validity, and discrimant validity. Second, a structural equation model (SEM) is used to examine the casual relationships and all path coefficients of statistical significance.
    There are some findings from the empirical tests of two different samples: (1) For practitioners, product portability has a positive effect on attitude toward use but does not affect on perceived enjoyment. Interestingly, for university students, product portability indicates a strongly negative effect on perceived enjoyment, but does not affect on attitude toward use. (2) For two distinct groups, two constructs of perceptions (compatibility, and relative advantage) have a significant effect on perceived enjoyment and then affect attitude toward use. (3) Personal innovativeness successfully plays an antecedent role in relative advantage of individual perceptions and product portability of perceived product attributes for the two samples, but it has a significant effect on intention to purchase an additional product only for practitioners.
    This study provides the following empirical implications. The distinct sample groups have different demands and perceptions of a netbook, which may be associated with the different social demography, usage environments and perceptions of a new IT product. Nevertheless, the attributes of convenience, ease of use, affordability, and portability, and enjoyable innovative technology and compact design are effective strategies of PC marketers to promote users’ intentions to purchase a netbook as a complement to their laptop computer, but not as a replacement.

    ABSTRACT.................................................i CHINESE ABSTRACT.......................................iii ACLKNOWLEDGES............................................v TABLE OF CONTENTS.......................................vi LIST OF TABLES...........................................x LIST OF FIGURES.........................................xi CHAPTER 1 INTRODUCTION 1.1 Background and Motivation............................1 1.2 Statement of the Problem.............................6 1.3 The Purpose of this study............................8 1.4 Research Questions..................................11 1.6 Outline of the Research.............................13 CHAPTER 2 LITERATURE REVIEW 2.1 Diffusion of Innovation Framework...................16 2.2 Personal Innovativeness in the Domain of Information Technology (PIIT).......................19 2.3 Product Attributes Associated with Enjoyment for Users’ Acceptance of a New IT.......................22 2.4 Summarizing Prior Studies of Adopting an Information Technology..................25 CHAPTER 3 MODEL DEVELOPMENT AND HYPOTHESES 3.1 Conceptual Model Development........................31 3.1.1 Relationships between System Features and Individual Perceptions......................32 3.1.2 Relationships among Intrinsic Motivation, System Attributes, Perceptions and Attitude toward Using a New IT..................34 3.1.3 Personal Innovativeness as an Individual’s Trait...........................................36 3.2 Research Model and Design...........................37 3.2.1 Product Attributes..............................38 3.2.1.1 System Features.................................40 3.2.1.2 Product Portability.............................41 3.2.2 Individual Perceptions..........................43 3.2.2.1 Ease of Use.....................................44 3.2.2.2 Compatibility...................................45 3.2.2.3 Relative Advantage..............................46 3.2.3 Personal Innovativeness.........................48 3.2.4 Perceived Enjoyment.............................50 3.2.5 Attitude toward Use.............................52 CHAPTER 4 METHODOLOGY 4.1Measurement Development..............................54 4.1.1 Product Attributes..............................56 4.1.1.1 System Features.................................56 4.1.1.2 Product Portability.............................58 4.1.2 Individual Perceptions..........................59 4.1.2.1 Ease of Use.....................................59 4.1.2.2 Compatibility...................................60 4.1.2.3 Relative Advantage..............................61 4.1.3 Personal Innovativeness.........................61 4.1.4 Perceived Enjoyment.............................62 4.1.5 Attitude toward Use.............................63 4.1.6 Intention to Purchase an Additional Product.....64 4.2 Pilot Study.........................................65 4.3 Data Collection.....................................66 4.4 Respondents.........................................68 CHAPTER 5 DATA ANALYSIS AND EMPIRICAL RESULTS 5.1 Measurement Model Evaluation........................72 5.1.1 Measurement Model Evaluation: The Baseline Model..............................73 5.1.2 Measurement Model Evaluation: The Student Case................................74 5.1.3 Measurement Model Evaluation: The Practitioner Case...........................75 5.1.4 Comparisons of the Measurement Model Evaluation................................76 5.2 Evaluation for Construct Reliability and Convergent Validation...........................77 5.2.1 Evaluation for Construct Reliability and Convergent Validation: The Baseline Model.......78 5.2.2 Evaluation for Construct Reliability and Convergent Validation: The Student Case.........81 5.2.3 Evaluation for Construct Reliability and Convergent Validation: The Practitioner Case....83 5.3 Structural Model Evaluation.........................85 5.3.1 Structural Model Evaluation: The Student Case................................85 5.3.2 Discussion: The Student Case....................85 5.3.3 Structural Model Evaluation: The Practitioner Case...........................89 5.3.4 Discussion: The Practitioner Case...............89 5.4 Empirical Comparisons: Student and Practitioner Models.................93 CHAPTER 6 CONCLUSIONS 6.1 Contributions.......................................97 6.2 Managerial Implications............................104 6.3 Limitations and Directions for Future Research.....108 REFERENCES.............................................110 APPENDIX A1:Studies on Consumer’s Acceptance of Desktop Computers..................................118 APPENDIX A2:Studies on Consumer’s Acceptance of Laptops....................................124 APPENDIX A3:Studies on Consumer’s Acceptance of IT-related Products........................128 APPENDIX B:The Chinese Questionnaire...................131 APPENDIX C:Survey Questionnaire........................135 List of publications...................................138 Vita...................................................139 List of Tables Table 3 Variables Definitions and Measurements..........55 Table 4 Demographic Profile of the Respondents….........70 Table 5 Comparisons of the Measurement Models...........77 Table 6a Completely Standardized Factor Loading and Construct Reliability Estimates—All Respondents....................................80 Table 6b Completely Standardized Factor Loading and Construct Reliability Estimates—Students.......82 Table 6c Completely Standardized Factor Loading and Construct Reliability Estimates—Practitioners..84 Table 7 Comparison of Parameter Estimates and Statistical Significance for Two Surveys........96 List of Figures Figure 1 Netbook Popularity in 2008......................2 Figure 2 2001 – 2008 Business Internet Subscribers in Taiwan.......................................3 Figure 3 Variables Determining the Rate of Adoption Innovations....................................18 Figure 4 Hypothesized Relationships between PIIT and Other Technology Acceptance Constructs.........20 Figure 5 Technology Acceptance Model....................23 Figure 6 Research Mode..................................39 Figure 7 SEM Results for Students.......................86 Figure 8 SEM Results for Practitioners..................90

    REFERENCES
    Agarwal, R. and Karahanna, E. (2000). Time flies when
    you’re having fun: Cognitive absorption and beliefs
    about information technology usage. MIS Quarterly, 24
    (4), 665-694.
    Agarwal, R. and Prasad, J. (1998a). A conceptual and
    operational definition of personal innovativeness in
    the domain of information technology. Information
    Systems Research, 9(2), 204-215.
    Agarwal, R. and Prasad, J. (1998b). The antecedents and
    consequents of user perceptions in information
    technology adoption. Decision Support Systems, 22(1),
    15-29.
    Ajzen, I. and Fishbein, M. (1980). Understanding attitudes
    and predicting social behavior. Englewood Cliffs,
    Practice Hall: New York.
    Al-Gahtani, S. and King, M. (1999). Attitudes,
    satisfaction and usage: Factors contributing to each in
    the acceptance of information technology. Behaviour &
    Information Technology, 18(4), 277-297.
    Al-Qirim, N. (2007). The adoption of eCommerce
    communications and applications technologies in small
    business in New Zealand. Electronic Commerce Research
    and Applications, 6(4), 462-473.
    Arning, K. and Ziefle, M. (2007). Understanding age
    differences in PDA acceptance and performance.
    Computers in Human Behavior, 23(6), 2904–2927.
    Anderson, J.C. and Gerbing, D.W. (1988). Structural
    equation modeling in practice: A review and recommended
    two-step approach. Psychological Bulletin, 103(3), 411-
    23.
    Assael, H. (2005). A demographic and psychographic profile
    of heavy internet users and users by type of internet
    usage. Journal of Advertising research, 45(1), 93-123.
    Atkinson, M. and Kydd, C. (1997). Individual
    characteristics associated with World Wide Web use: An
    empirical study of playfulness and motivation. The DADA
    BASE for Advances in Information Systems, 28(2), 53-62.
    Bagozzi, R.P. and Yi, Y. (1988). On the evaluation of
    structural equation models. Academy of Marketing
    Science, 16(1), 74-94.
    Barnett, L.A. (1990). Playfulness: Definition, design and
    measurement. Play and Culture, 3(4), 319-336.
    Baumgartner, H. and Steenkamp, J. E.M. (1996). Exploratory
    consumer buying behavior: Conceptualization and
    measurement. International Journal of Research in
    Marketing, 13(2) 121-137
    Benbunan-Fich, R and Truman, G.E. (2009). Multitasking
    with laptops during meetings. Communications of the
    ACM, 52(2), 139-141.
    Bentler, P.M and Bonett, D.G. (1980). Significance tests
    and goodness of fit in the analysis of covariance
    structures. Psychological Bulletin, 88(3), 588-606
    Bentler, P.M. (1990). Comparative fit indexes in
    structural models. Psychological Bulletin, 107(2), 238-
    246.
    Brown, D.G., Burg, J.J. and Dominick, J.L. (1998). A
    strategic play for ubiquitous laptop computing.
    Communications of the ACM, 40(1), 26-35.
    Browne, M.W. and Cudeck, R. (1993). Alternative ways of
    assessing model fit, In K. A. Bollen, and J. S. Long
    (eds.), Testing Structural Equation Models, Newbury
    Park, CA: Sage, 136-62.
    Bruner II, G.C. and Kumar, A. (2005). Explaining consumer
    acceptance of handheld Internet devices. Journal of
    Business Research, 58(5), 553-558.
    Byrne, B.M. (1998). PRELIS and SIMPLIS: Basic concepts,
    applications and programming, Structural Equation
    Modeling with LISREL. Lawrence Erlbaum Associates:
    London.
    Childers, T.L., Carr, C.L., Peck, J. and Carson, S.
    (2001). Hedonic and utilitarian motivations for online
    retail shopping behavior. Journal of Retailing, 77(4),
    511-535.
    Cramer, M., Beauregard, R and Sharma, M. (2009). An
    investigation of purpose built netbooks for primary
    school education. Proceedings of the 8th International
    Conference on Interaction Design and Children, 36-43,
    Como, Italy.
    Cutshall, R., Changchit, C. and Elwood, S. (2006). Campus
    Laptops: What Logistical and Technological Factors are
    Perceived Critical? Educational Technology & Society, 9
    (3), 112-121.
    Dabholkar, P.A. (1996). Consumer evaluations of new
    technology-based self-service options: An investigation
    of alternative models of service quality. International
    Journal of Research in Marketing, 13(1), 29-51.
    Davis, F.D. (1989). Perceived practical functionality,
    perceived ease-of-use and user acceptance of
    information technology. MIS Quarterly, 13(3), 319-340.
    Davis, F.D., Bagozzi, R.P. and Warshaw, P.R (1989). User
    acceptance of computer technology: A comparison of two
    theoretical models. Management Science, 35(8), 982-1003.
    Davis, F.D., Bagozzi, R.P. and Warshaw, P.R. (1992).
    Extrinsic and intrinsic motivation to use computers in
    the workplace. Journal of Applied social psychology, 22
    (14), 1111-1132.
    Dearman, D. and Pierce, J.S. (2008). It’s on my other
    computer! Computing with multiple devices. Proceeding
    of the twenty-sixth annual SIGCHI conference on Human
    factors in computing systems, Florence, Italy, 767-776.
    Descy, D.E. (2009). Netbooks: Small but Powerful Friends.
    TechTrends, 53(2), 9-10.
    DeLone, W. H. (1988). Determinants of Success for Computer
    Usage in Small Business. MIS Quarterly, 12(1), 51-61.
    Dishaw, M. T. and Strong, D. M. (1999). Extending the
    technology acceptance model with task-technology fit
    constructs. Information & Management, 36(1), 9-21.
    Donovan, R.J. and Jalleh, G. (1999). Positively versus
    negatively framed product attributes: The influence of
    involvement. Psychology and Marketing, 16(7), 613-630.
    Dwivedi, Y. and Irani, Z. (2009).Understanding the
    adopters and non-adopters of broadband. Communications
    of the ACM, 52(1), 122-125.
    Elwood, S., Changchit, C. and Cutshall, R. (2006).
    Investigating students’ perceptions on laptop
    initiative in higher education: An extension of the
    technology acceptance model. Campus-Wide Information
    Systems, 23(5), 336-349.
    Engel, J.F., Blackwell, R.D. and Miniard, P.W. (1995).
    Consumer Behavior. (8th ed). The Dryden Press: Chicago.
    Eriksson, M.J., Vuojärvi, H. and Ruokamo, H. (2009).
    Laptop computers and wireless university campus
    networks: Is flexibility and effectiveness improved?
    Australasian Journal of Educational Technology, 25(3),
    322-335.
    Eroglu, S.A., Machleit, K.A. and L.M. Davis (2001).
    Empirical testing of a model of online store
    atmospherics and shopper responses. Psychology &
    Marketing, 20(2), 139-150.
    Fornell, C. and Larcker, D.F. (1981). Evaluating
    structural equations models with unobservable variables
    and measurement error. Journal of Marketing Research 18
    (1), 39-50.
    George, J.F. (2002). Influences on the intent to make
    Internet purchase. Internet Research, 12(2), 165-180.
    Gunasekaran, V. and Harmantzis, F.C. (2008). Towards a Wi-
    Fi ecosystem: Technology integration and emerging
    service models. Telecommunications Policy, 32(3/4), 163-
    181.
    Ha, I., Yoon, Y. and Choi, M. (2007). Determinants of
    adoption of mobile games under mobile broadband
    wireless access environment. Information & Management,
    44 (3), 276-86.
    Hair J.F., Black, W.C., Babin, B.J., Anderson, R.E. and
    Tatham, R.L. (2006). Multivariate data analysis.
    Prentice Hall: Pearson Education International.
    Harrison, A. W. and Rainer, R. K. (1992). The influence of
    Individual Differences on Skill in End-User Computing.
    Journal of Management Information Systems, 9(1), 93-111.
    Hausman, A.V. and Siekpe, J.S. (2008). The effect of web
    interface features on consumer online purchase
    intentions. Journal of Business Research, 62(1), 5-13.
    Hoffman, D.L. and Novak, T.P. (1996). Marketing in
    Hypermedia Computer-Mediated Environments: Conceptual
    Foundations. Journal of Marketing, 60(3), 58-68.
    Hong, W., Thong, J.Y.L., Wong, W.M. and Tam, K.Y. (2002).
    Determinants of User Acceptance of Digital Libraries:
    An Empirical Examination of Individual Differences and
    System Characteristics. Journal of Management
    Information Systems, 18(3), 97-124.
    Igbaria, M., Schiffman, S.J. and Wieckowski (1994). The
    respective roles of perceived usefulness and perceived
    fun in the acceptance of microcomputer technology.
    Behaviour & Information Technology, 13(6), 349-361.
    Igbaria, M. and Iivari, J. (1995). The Effects of Self-
    efficacy on Computer Usage. Omega, 3(6), 587-605.
    Igbaria, M., Iivari, J., Maragahh, H. (1995a). Why do
    individuals use computer technology? A Finnish case
    study. Information & Management, 29(5), 227-238.
    Igbaria, M., Guimaraes, T. and Davis, G.B. (1995b). Test
    the determinants of microcomputer usage via a
    structural equation model. Journal of Management
    Information Systems, 11(4), 87-144.
    Igbaria, M., Parasuraman, S. and Baroudi, J. (1996). A
    motivational model of microcomputer usage. Journal of
    Management Information Systems, 13(1), 127-143.
    Igbaria, M. and Zviran, M. (1996). Comparison of end-user
    computing characteristics in the U.S., Israel and
    Taiwan. Information & Management, 30(1), 1-13
    III-FIND, (2009). Available at:
    http://www.find.org.tw/eng/news.asp?
    Imhof, M., Vollmeyer, R. and Beierlein, C. (2007).
    Computer use and the gender gap: The issue of access,
    use, motivation, and performance, Computers in Human
    Behavior, 23(6), 2823-2837.
    Jiang, Z. and Benbasat, I. (2007). Investigating the
    influence of the functional mechanisms of online
    product presentations. Information System Research, 18
    (4), 454-470.
    Jöreskog, K.G. and Sörbom, D. (1996). LISREL 8: User’s
    reference guide. Scientific Software International:
    Chicago.
    Karahanna, E., Ahuja, M., Srite, M. and Galvin, J. (2002).
    Individual differences and relative advantage: The case
    of GSS. Decision Support Systems, 32(4), 327-341.
    Kay, R. (2006). Addressing gender differences in computer
    ability, attitudes and use: The laptop effect. Journal
    of Educational computing research, 34(2), 187-211.
    Kendall, J.D., Tung, L.L., Chua, K.H., Hong, C., Ng, D.
    and Tan, S.M. (2001). Receptivity of Singapore’s SMEs
    to electronic commerce adoption. Journal of Strategic
    Information Systems, 10(3), 223-242.
    Koufair, M. (2002). Applying the technology acceptance
    model and flow theory to online consumer behavior.
    Information Systems Research, 13(2), 205-223.
    Laforet, S. and Li, X. (2005). Consumers’ attitudes
    towards online and mobile banking in China.
    International Journal of Bank Marketing. 23(5), 362-380
    Lee, D.M.S. (1986). Usage patterns and sources of
    assistance for personal computer users. MIS Quarterly,
    10(4), 293-304.
    Lee, S.M., Kim, I., Rhee, S. and Trimi, S. (2006). The
    role of exogenous factors in technology acceptance: The
    case of object-oriented technology. Information &
    Management, 43(4), 469–480.
    Legris P. J., Ingham, J. and Collerette, P. (2003). Why do
    people use information technology? A critical review of
    the technology acceptance model. Information &
    Management, 40(3), 191-204.
    Levine, T. and Donitsa-Schmidt, S. (1998). Computer use,
    confidence, attitudes, and knowledge: A causal
    analysis. Computers in Human Behavior, 14(1), 125-146
    Lewis W., Agarwal, R. and Sambamurthy, V. (2003). Sources
    of influence on beliefs about information technology
    use: An empirical study of knowledge workers. MIS
    Quarterly, 27(4), 657-678.
    Lian, J.W. and Lin, T.Z. (2008). Effects of consumer
    characteristics on their acceptance of online shopping:
    Comparisons among different product types. Computer in
    Human Behavioral, 24(1), 48-65.
    Liang, H., Xue, Y. and Byrd, T.A. (2003). PDA usage in
    healthcare professionals: testing an extended
    technology acceptance model. International Journal of
    Mobile Communications, 1(4), 372-389.
    Liao, Z. and Cheung, M.T. (2002). Internet-based e-banking
    and consumer attitudes: An empirical study. Information
    & Management, 39(4), 283-295.
    Liao, C.H., Tsou, C.W and Huang, M.F. (2007). Factor
    influencing the usage of 3G mobile services in Taiwan.
    Online Information Review, 31(6), 759-774.
    Lin, C.A. (1998). Exploring personal computer adoption
    dynamics. Journal of Broadcasting & Electronic Media, 42
    (1), 95-112.
    Lu, J., Yao, J.E. and Yu, C.S. (2005). Personal
    innovativeness, social influences and adoption of
    wireless Internet services via mobile technology.
    Journal of Strategic Information System, 14(3), 245-
    268.
    Lu, J., Liu, C., Yu, S.S. and Wang, K. (2008).
    Determinants of accepting wireless mobile data services
    in China. Information & Management, 45(1), 52-64.
    MacCallum, R.C., Browne, M.W. and Sugawara, H.M. (1996).
    Power analysis and determination of sample size for
    covariance structure modeling. Psychological Methods, 1
    (2), 130-49.
    Mallat, N. (2007). Exploring consumer adoption of mobile
    payments - A qualitative study. Journal of Strategic
    Information Systems, 16(4), 413-432.
    Maxham, J.G. (2001). Service recovery’s influence on
    consumer satisfaction, positive word-of-mouth, and
    purchase intentions. Journal of Business Research, 54
    (1), 11-24.
    McMahon, M. and Pospisil, R. (2005). Laptops for a digital
    lifestyle: Millennial students and wireless mobile
    technologies. Retrieved November 1, 2004, from
    http://www.ascilite.org.au/conferences/brisbane05
    /blogs/proceedings/49_McMahon%20&%20Pospisil.pdf.
    McVay, G.J., Snyder, K.D. and Graetz, K.A. (2005).
    Evolution of a laptop university: A case study. British
    Journal of Educational Technology, 36(3), 513–524
    Moon, J. W. and Kim, Y.G. (2001). Extending the TAM for a
    World-Wide-Web context. Information and Management, 38
    (4), 217-230.
    Moore, G.C. and Benbasat, I. (1991). Development of an
    instrument to measure the perceptions of adopting an
    information technology innovation. Information Systems
    Research, 2(3), 192-222.
    Moses, P., Khambari, M.N.M. and Luan, W.S. (2008). Laptop
    use and its antecedents among educators: A review of
    the literature. European Journal of Social Sciences, 7
    (1), 104-114.
    Ni, X. and Branch, R. M. (2004). Experience of Using
    Laptop in Higher Education Institutions: Effects with
    and of Ubiquitous Computing under Natural Conditions.
    The 27th Association for Educational Communications and
    Technology, Chicago, IL, Oct 19-23, 663-672.
    Ondrusek, A.L. (2004). The attributes of research on end-
    user online searching behavior: A retrospective review
    and analysis. Library & Information Science Research, 26
    (2), 221–265
    Ozok, A. A., Benson, D., Chakraborty, J. and Norcio, A.F.
    (2008). A Comparative Study Between Tablet and Laptop
    PCs: User Satisfaction and Preferences. International
    Journal of Human-Computer Interaction, 24(3), 329–352.
    PriceGrabber, (2009). Available at:
    https://mr.pricegrabber.com/Netbook_Trends_and
    _SolidState_Technology_ January_2009_CBR.pdf.
    Pituch, K.A. and Lee, Y. K. (2006). The influence of
    system characteristics on e-learning use. Computers &
    Education, 47(2), 222–244
    Prescod, F. and Dong, L (2008). Learning style trends and
    laptop use patterns: Implication for students in an IT
    business school. Information Systems Education Journal,
    6(4), 3-13.
    Quester, P.G. and Smart, J. (1998). The influence of
    consumption situation and product involvement over
    consumers’ use of product attribute. Journal of
    Consumer Marketing, 15(3), 220-238.
    Richard, M.O. (2005). Modeling the impact of Internet
    atmospherics on surfer behavior. Journal of Business
    Research, 58(12), 1632-1642.
    Richard, M.O. and Chandra, R. (2005). A model of consumer
    web navigational behavior: Conceptual development and
    application. Journal of Business Research, 58(8), 1019-
    1029.
    Roa, B. and Parikh. M.A. (2003). Wireless Broadband
    Networks: The U.S. Experience. International Journal of
    Electronic Commerce, 8(1), 37–53.
    Rogers, E.M. (1983). The diffusion of innovations (3rd
    ed.). The Free Press: New York.
    Rogers, E.M. (1995). The diffusion of innovations (4th
    ed.). The Free Press: New York.
    Saker, S. and Wells, J.D. (2003). Understanding mobile
    handheld devices use and adoption. Communications of
    the ACM, 46(13), 35-40.
    Sautter, P., Hyman, M.R. and Lukosius, V. (2004). E-Retail
    Atmospherics: A critique of the literature and model
    extension. Journal of Electronic Commerce Research, 5
    (1), 14-24.
    Straker, L., Jones, K.J. and Miller, J. (1997). A
    comparison of the postures assumed when using laptop
    computers and desktop computers. Applied Ergonomics, 28
    (4), 263-268.
    Tan, C.L. and Morris, J.S. (2005). Undergraduate college
    students, laptop computers, and lifelong learning. The
    Journal of General Education, 54(4), 316-338.
    Teo, T.S.H. and Lim, V.K.G. (1996). Factors influencing
    personal computer usage: The gender gap. Women in
    Management Review, 11(8), 18-26.
    Teo, T.S.H. and Pok, S.H. (2003). Adoption of WAP-enabled
    mobile phones among Internet users. Omega, 3(6), 483-
    498.
    Thompson, R. L., Higgins, C.A. and Howell, J.M. (1991).
    Personal Computing: Toward a Conceptual Model of
    Utilization. MIS Quarterly, 15(1), 125-143.
    Thompson, R.L., Higgins, C.A. and Howell, J.M. (1994).
    Influence of experience on personal computer
    utilization: Testing a conceptual Model. Journal of
    Management Information Systems, 11(1), 167-187.
    Torkzadeh, G. and van Dyke, T.P. (2002) Effects of
    training on Internet self-efficacy and computer user
    attitudes. Computers in Human Behavior, 18(5), 479-494
    Trevino, L.K. and Webster, J. (1992). Flow in Computer-
    mediated Communication: Electronic mail and voice Mail
    evaluation and impacts. Communication Research, 19(5),
    539-573.
    Triandis, H.C. (1980). Values, Attitudes, and
    Interpersonal Behavior. Nebraska Symposium on
    Motivation, 1979: Beliefs, Attitudes, and Values,
    University of Nebraska Press, Lincoln, NE. 195-259.
    Tsou, C.W. and Liao, H. (2009). Understanding computer-
    mediated communication usage: A perspective MSN
    services. Advances in Consumer Research, VIII, 267-282.
    van der Heijden, H. (2003). Factors influencing the usage
    of websites: The case of a generic portal in the
    Netherlands, Information & Management, 40(6), 541-549.
    van Raaij, E.M. and Schepers, J.J.L. (2008). The
    acceptance and use of a virtual learning environment in
    China. Computers & Education, 50(3), 838-852.
    Venkatesh, V. and Brown, S.A. (2001). A longitudinal
    investigation of personal computers in homes: Adoption
    determinants and emerging challenges. MIS Quarterly, 25
    (1), 71-102.
    Vijayasarathy, L.R. (2004). Predicting consumer intentions
    to use on-line shopping: The case for an augmented
    technology acceptance model. Information & Management,
    41(6), 747-762.
    Ward S. and Huff, S. L. (1988). Factors of Success for End-
    User Computing. Communications of the ACM, 31(5), 552-
    561.
    Winter, S.J., Chudoba, K.M. and Gutek, B.A. (1998).
    Attitudes toward computers: When do they predict
    computer use? Information & Management, 34(5), 275-284.
    Wiredu, G.O. (2007). User appropriation of mobile
    technologies: Motives, conditions and design
    properties. Information and Organization, 17(2), 110-
    129.
    Wu, I.L. and Wu, K.W. (2005). A hybrid technology
    acceptance approach for exploring e-CRM adoption on
    organizations. Behaviour & Information Technology, 24
    (4), 303-316.
    Wu, J.H., Chen, Y.C. and Lin, L.M. (2007). Empirical
    evaluation of the revised end user computing acceptance
    model. Computers in Human Behavior, 23(1), 162-174.
    Yi, M.Y. and Hwang, Y. (2003). Predicting the use of web-
    based information systems: Self-efficacy, enjoyment,
    learning goal orientation, and the technology
    acceptance model. International Journal of Human-
    Computer Studies, 59(4), 431-449.
    Yiu, C.S., Grant, K. and Edgar, D. (2007). Factors
    affecting the adoption of Internet Banking in Hong Kong—
    implications for the banking sector. International
    Journal of Information Management, 27(5), 336-351.
    Yen, D.C. and Chou, D.C. (2001). Wireless communication:
    The next wave of Internet technology. Technology in
    Society, 23(2), 217-226.

    無法下載圖示 校內:2012-02-22公開
    校外:不公開
    電子論文尚未授權公開,紙本請查館藏目錄
    QR CODE