BibTex RIS Kaynak Göster

Determinants ofUserAcceptance of Digital Libraries

Yıl 2013, Cilt: 27 Sayı: 4, 585 - 600, 01.10.2013

Öz

Using theDecomposed Theory of Planned Behavior this research aims to determine the factors that affect the intentions of teaching staff towards using digital library services. Data are collected from 426 respondents and structural equation modeling is used to analyze the responses. Study results showed that attitude toward use and subjective norm have an important positive effect but perceived behavioral control doesnot have an effect on intention. Another finding is that compatibility is more effective than relative advantage in this context and it is seen that the system's ease of use is more related with perceivedbehavioral control rather than attitude

Kaynakça

  • Ajzen, I. (1988). Attitudes, personality, and behavior. Maidenhead: Open University Press.
  • Ajzen, I. (1991). The theory of planned behavior, Organizational Behavior and Human Decision Processes. 50 (2), 179-211.
  • Ajzen, I. (2002). Perceived behavioral control, self-efficacy, locus of control, and the theory of planned behavior.Journal of Applied Social Psychology, 32 (4), 665-683.
  • Ajzen, I. and Fishbein, M. (1980). Understanding attitudes and predicting social behavior. New Jersey: Prentice Hall, Inc, Englewood Cliffs.
  • Anderson, J.C. and Gerbing, D.W. (1988). Structural equation modeling in practice: A review and recommenden two-step approach. Psychological Bulletin, 103 (3), 411-423.
  • Armitage, C.J. and Conner, M. (1999). Distinguishing perceptions of control from self-efficacy: Predicting consumption of a low-fat diet using the theory of planned behavior. Journal of Applied Social Psychology, 29 (1), 72-90.
  • Bandura, A. (1997). Self-efficacy: The exercise of control. New York: W.H. Freeman and Company.
  • Brown, S.A. and Venkatesh, V. (2005). Model of adoption of technology in households: A baseline model test and extension incorporating household life cycle. MIS Quarterly, 29 (3), 399-426.
  • Bruner, G.C. and Kumar, A. (2005). Explaining consumer acceptance of handheld internet devices. Journal of Business Research, 58 (5), 553-558.
  • Choi, H., Choi, M., Kim, J. and Yu, H. (2003). An emprical study on the adoption of information appliances with a focus on interactive tv. Telematics and Informatics, 20 (2), 161-183.
  • Compeau D.R., Meister, D.B. and Higgins, C.A. (2007). From prediction to explanation: Reconceptualizing and extending the perceived characteristics of innovating. Journal of the Association for Information Systems JAIS, 8 (8), 409-439.
  • Compeau,D.R. and C.A. Higgins (1995). Computer Self-Efficacy: Development of a Measure and InitialTest. MIS Quarterly, 19 (2), 189-211.
  • Dabholkar, P.A. and Bagozzi, R.P. (2002). An attitudinal model of technology-based self-service: Moderating effects of consumer traits and situational factors. Academy of Marketing Science Journal, 30 (3), 184-201.
  • Davis. F.D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information Davis, technology. MIS Quarterly, 13 (3), 318-340.
  • Eastlick, M.A. (1993). Predictors of videotex adoption. Journal of Direct Marketing, 7 (3), 66-74.
  • Fishbein, M. and Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.
  • Gatignon, H. and Robertson, T.S. (1985). A propositional inventory for new diffusion research. Journal of Consumer Research, 11 (4), 849-867.
  • Hair, J.F. Jr., Ralph, E.A., Tatham, R.L. and Black, W.C. (1998). Multivariate data analysis (5th Ed.). New Jersey: Prentice Hall.
  • Higgins, S.H. and Shanklin, W.L. (1992). Seeking mass market acceptance for high-technology consumer products. The Journal of Consumer Marketing, 9 (1), 5-14.
  • Holak, S.L. and Lehmann, D.R. (1990). Purchase intentions and the dimensions of innovation: An exploratory model. Journal of Product Innovation Management, 7 (1), 59-73.
  • Hong, W.J., Thong, 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.
  • Karahanna, E., Agarwal, R. and Angst, C.M. (2006). Reconceptualizing compatibility beliefs in technology acceptance research. MIS Quarterly, 30 (4), 781-804.
  • Karahanna, E., Straub, D.W. and Chervany, N.L. (1999). Information technology adoption across time: Across-sectional comparison of pre-adoption and post-adoption beliefs. MIS Quarterly, 23 (2), 183-213.
  • Kline,R.B. (1998).Principles and practice of structural equation modeling. New York: The Guilford Press.
  • Kurulgan, M. and Özata, F.Z. (2010). Elektronik kütüphane hizmetlerinin öğretim elemanları tarafından benimsenmesinde etkili olan faktörler: Anadolu Üniversitesi öğretim elemanları üzerinde bir araştırma. Bilgi Dünyası, 11 (2), 243-262.
  • Lee, Y., Kozar, K.A. and Larsen, K.R.T. (2003). The technology acceptance model: Past, present, and future. Communications of the Association for Information Systems, 12 (50), 752-780.
  • Limayem, M., Khalifa, M. and Frini, A. (2000). What makes consumers buy from internet? A longitudinal study of online shopping. IEEE Transactions On Systems, Man, And Cybernetics - Part A: Systems And Humans, 30 (4), 421-432.
  • Manstead, A.S.R. and Eekelen, S.A.M. Van. (1998). Distinguishing between perceived behavioral control and self-efficacy in the domain of academic achievement intentions and behaviors. Journal of Applied Social Psychology, 28 (15), 1375-1392.
  • Mathieson, K. (1991). Predicting user intentions: Comparing the technology acceptance model with the theory of planned behavior. Information Systems Research 2 (3), 173-191.
  • 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.
  • Nov, O. and Ye, C. (2008). Users' personality and perceived ease of use of digital libraries: The casefor resistance to change. Journal of the American Society for Information Science and Technology, 59 (5), 845-851.
  • Ostlund, L.E. (1974). Perceived innovation attributes as predictors of innovativeness. Journal of Consumer Research, 1 (2), 23-29.
  • Ram, S. and Sheth, J.N. (1989). Consumer resistance to innovations: The marketing problem and its solutions. The Journal of Consumer Marketing, 6 (2), 5-14.
  • Rogers,E.M.(2003). Diffusion of innovations (5th Ed.). New York: The Free Press.
  • Schepers, J. and Wetzels, M. (2007). A meta-analysis of the technology acceptance model: Investigating subjective norm and moderation effects. Information & Management, 44 (1), 90-103.
  • Shiri, A. (2003). Digital library research: current developments and trends. Library Review, 52(5), 198­ 202.
  • Sparks, P., Guthrie, C.A. and Shepherd, R. (1997). The dimensional structure of the perceived behavioral control construct.Journal of Applied Social Psychology, 27 (5), 418-438.
  • Taylor, S. and Todd, P. (1995a). Decomposition and crossover effects in the theory of planned behavior: A study of consumer adoption intentions. International Journal of Research in Marketing, 12 (2), 137-155.
  • Taylor,S. and Todd, P. (1995b). Understanding information technology usage: A test of competing models. Information Systems Research, 6 (2), 144-176.
  • Tonta,Y. (2009). Dijital yerliler, sosyal ağlar ve kütüphanelerin geleceği. Türk Kütüphaneciliği, 23 (4), 742-768.
  • Tornatzky, L.G. and Klein, K.J. (1982). Innovation characteristics and innovation-adoption implementation: A meta-analysis of findings. IEEE Transactions on Engineering Management, 29(1), 28-43.
  • Venkatesh, V. and Brown, S. A. (2001). Longitudinal investigation of personal computers in homes: Adoption determinants and emerging challenges. MIS Quarterly, 25(1), 71-102.
  • Venkatesh, V. and Davis, F.D. (1996). A Model of the Antecedents of Perceived Ease of Use: Development and Test. Decision Sciences, 27 (3), 451-481.
  • Venkatesh, V. and Davis, F.D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46 (2), 186-204.
  • Venkatesh, V., Morris, M.G., Davis, G.B. and Davis, F.D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27 (3), 425-478.
  • Vishwanath, A. and Goldhaber, G.M. (2003). An examination of the factors contributing to adoption decisions among late-diffused technology products. New Media Society, 5 (4), 547-572.
  • Wee, T.T.T. (2003). Factors affecting new product adoption in the consumer electronics industry. SingaporeManagement Review, 25 (2), 51-71.

Dijital Kütüphanelerin Kullanıcı Kabul Belirleyicileri

Yıl 2013, Cilt: 27 Sayı: 4, 585 - 600, 01.10.2013

Öz

Bu çalışma, Parçalara Bölünmüş Planlı Davranış Teorisini kullanarak öğretim üyelerinin dijital kütüphane hizmetlerini benimseme niyetlerini belirlemeyi amaçlamaktadır. 426 katılımcıdan toplanan verinin analizi için yapısal eşitlik modellemesinden yararlanılmıştır. Çalışma sonuçları kullanıma yönelik tutum ve öznel normun niyet üzerinde olumlu yönde önemli bir etkiye sahip olduğunu, algılanan davranış denetiminin ise bir etkisi olmadığını göstermektedir. Diğer bir bulgu ise, bu bağlamda uyumun göreli üstünlük değişkeninden daha etkili olduğu ve sistemin kullanım kolaylığı değişkeninin de tutum yerine algılanan davranış denetimi ile daha ilişkili olduğudur.

Kaynakça

  • Ajzen, I. (1988). Attitudes, personality, and behavior. Maidenhead: Open University Press.
  • Ajzen, I. (1991). The theory of planned behavior, Organizational Behavior and Human Decision Processes. 50 (2), 179-211.
  • Ajzen, I. (2002). Perceived behavioral control, self-efficacy, locus of control, and the theory of planned behavior.Journal of Applied Social Psychology, 32 (4), 665-683.
  • Ajzen, I. and Fishbein, M. (1980). Understanding attitudes and predicting social behavior. New Jersey: Prentice Hall, Inc, Englewood Cliffs.
  • Anderson, J.C. and Gerbing, D.W. (1988). Structural equation modeling in practice: A review and recommenden two-step approach. Psychological Bulletin, 103 (3), 411-423.
  • Armitage, C.J. and Conner, M. (1999). Distinguishing perceptions of control from self-efficacy: Predicting consumption of a low-fat diet using the theory of planned behavior. Journal of Applied Social Psychology, 29 (1), 72-90.
  • Bandura, A. (1997). Self-efficacy: The exercise of control. New York: W.H. Freeman and Company.
  • Brown, S.A. and Venkatesh, V. (2005). Model of adoption of technology in households: A baseline model test and extension incorporating household life cycle. MIS Quarterly, 29 (3), 399-426.
  • Bruner, G.C. and Kumar, A. (2005). Explaining consumer acceptance of handheld internet devices. Journal of Business Research, 58 (5), 553-558.
  • Choi, H., Choi, M., Kim, J. and Yu, H. (2003). An emprical study on the adoption of information appliances with a focus on interactive tv. Telematics and Informatics, 20 (2), 161-183.
  • Compeau D.R., Meister, D.B. and Higgins, C.A. (2007). From prediction to explanation: Reconceptualizing and extending the perceived characteristics of innovating. Journal of the Association for Information Systems JAIS, 8 (8), 409-439.
  • Compeau,D.R. and C.A. Higgins (1995). Computer Self-Efficacy: Development of a Measure and InitialTest. MIS Quarterly, 19 (2), 189-211.
  • Dabholkar, P.A. and Bagozzi, R.P. (2002). An attitudinal model of technology-based self-service: Moderating effects of consumer traits and situational factors. Academy of Marketing Science Journal, 30 (3), 184-201.
  • Davis. F.D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information Davis, technology. MIS Quarterly, 13 (3), 318-340.
  • Eastlick, M.A. (1993). Predictors of videotex adoption. Journal of Direct Marketing, 7 (3), 66-74.
  • Fishbein, M. and Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.
  • Gatignon, H. and Robertson, T.S. (1985). A propositional inventory for new diffusion research. Journal of Consumer Research, 11 (4), 849-867.
  • Hair, J.F. Jr., Ralph, E.A., Tatham, R.L. and Black, W.C. (1998). Multivariate data analysis (5th Ed.). New Jersey: Prentice Hall.
  • Higgins, S.H. and Shanklin, W.L. (1992). Seeking mass market acceptance for high-technology consumer products. The Journal of Consumer Marketing, 9 (1), 5-14.
  • Holak, S.L. and Lehmann, D.R. (1990). Purchase intentions and the dimensions of innovation: An exploratory model. Journal of Product Innovation Management, 7 (1), 59-73.
  • Hong, W.J., Thong, 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.
  • Karahanna, E., Agarwal, R. and Angst, C.M. (2006). Reconceptualizing compatibility beliefs in technology acceptance research. MIS Quarterly, 30 (4), 781-804.
  • Karahanna, E., Straub, D.W. and Chervany, N.L. (1999). Information technology adoption across time: Across-sectional comparison of pre-adoption and post-adoption beliefs. MIS Quarterly, 23 (2), 183-213.
  • Kline,R.B. (1998).Principles and practice of structural equation modeling. New York: The Guilford Press.
  • Kurulgan, M. and Özata, F.Z. (2010). Elektronik kütüphane hizmetlerinin öğretim elemanları tarafından benimsenmesinde etkili olan faktörler: Anadolu Üniversitesi öğretim elemanları üzerinde bir araştırma. Bilgi Dünyası, 11 (2), 243-262.
  • Lee, Y., Kozar, K.A. and Larsen, K.R.T. (2003). The technology acceptance model: Past, present, and future. Communications of the Association for Information Systems, 12 (50), 752-780.
  • Limayem, M., Khalifa, M. and Frini, A. (2000). What makes consumers buy from internet? A longitudinal study of online shopping. IEEE Transactions On Systems, Man, And Cybernetics - Part A: Systems And Humans, 30 (4), 421-432.
  • Manstead, A.S.R. and Eekelen, S.A.M. Van. (1998). Distinguishing between perceived behavioral control and self-efficacy in the domain of academic achievement intentions and behaviors. Journal of Applied Social Psychology, 28 (15), 1375-1392.
  • Mathieson, K. (1991). Predicting user intentions: Comparing the technology acceptance model with the theory of planned behavior. Information Systems Research 2 (3), 173-191.
  • 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.
  • Nov, O. and Ye, C. (2008). Users' personality and perceived ease of use of digital libraries: The casefor resistance to change. Journal of the American Society for Information Science and Technology, 59 (5), 845-851.
  • Ostlund, L.E. (1974). Perceived innovation attributes as predictors of innovativeness. Journal of Consumer Research, 1 (2), 23-29.
  • Ram, S. and Sheth, J.N. (1989). Consumer resistance to innovations: The marketing problem and its solutions. The Journal of Consumer Marketing, 6 (2), 5-14.
  • Rogers,E.M.(2003). Diffusion of innovations (5th Ed.). New York: The Free Press.
  • Schepers, J. and Wetzels, M. (2007). A meta-analysis of the technology acceptance model: Investigating subjective norm and moderation effects. Information & Management, 44 (1), 90-103.
  • Shiri, A. (2003). Digital library research: current developments and trends. Library Review, 52(5), 198­ 202.
  • Sparks, P., Guthrie, C.A. and Shepherd, R. (1997). The dimensional structure of the perceived behavioral control construct.Journal of Applied Social Psychology, 27 (5), 418-438.
  • Taylor, S. and Todd, P. (1995a). Decomposition and crossover effects in the theory of planned behavior: A study of consumer adoption intentions. International Journal of Research in Marketing, 12 (2), 137-155.
  • Taylor,S. and Todd, P. (1995b). Understanding information technology usage: A test of competing models. Information Systems Research, 6 (2), 144-176.
  • Tonta,Y. (2009). Dijital yerliler, sosyal ağlar ve kütüphanelerin geleceği. Türk Kütüphaneciliği, 23 (4), 742-768.
  • Tornatzky, L.G. and Klein, K.J. (1982). Innovation characteristics and innovation-adoption implementation: A meta-analysis of findings. IEEE Transactions on Engineering Management, 29(1), 28-43.
  • Venkatesh, V. and Brown, S. A. (2001). Longitudinal investigation of personal computers in homes: Adoption determinants and emerging challenges. MIS Quarterly, 25(1), 71-102.
  • Venkatesh, V. and Davis, F.D. (1996). A Model of the Antecedents of Perceived Ease of Use: Development and Test. Decision Sciences, 27 (3), 451-481.
  • Venkatesh, V. and Davis, F.D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46 (2), 186-204.
  • Venkatesh, V., Morris, M.G., Davis, G.B. and Davis, F.D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27 (3), 425-478.
  • Vishwanath, A. and Goldhaber, G.M. (2003). An examination of the factors contributing to adoption decisions among late-diffused technology products. New Media Society, 5 (4), 547-572.
  • Wee, T.T.T. (2003). Factors affecting new product adoption in the consumer electronics industry. SingaporeManagement Review, 25 (2), 51-71.
Toplam 47 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Bölüm Research Article
Yazarlar

F. Zeynep Özata

Mesut Kurulgan

Yayımlanma Tarihi 1 Ekim 2013
Yayımlandığı Sayı Yıl 2013 Cilt: 27 Sayı: 4

Kaynak Göster

APA Özata, F. Z., & Kurulgan, M. (2013). Determinants ofUserAcceptance of Digital Libraries. Türk Kütüphaneciliği, 27(4), 585-600.

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