Author Co-citation Analysis of the Technology Acceptance Model, 2005-2010
DOI:
https://doi.org/10.3989/redc.2012.2.864Keywords:
technology acceptance model (TAM), visualizing knowledge domains (VKD), author co-citation analysis (ACA), pathfinder network (PFNET), factor analysisAbstract
This paper explores the research trends of the Technology Acceptance Model (TAM) using Author co-citation analysis (ACA) methods, from January 2005 to June 2010. Through the ISI Web of Knowledge (WoK) 38 key authors were selected: a Factor Analysis was performed and different techniques of information visualization, such as Multidimensional Scaling (MDS) and Pathfinder Network (PFNET), were applied. The goal of this article is to identify the most popular research topics of TAM over the five years studied. The results obtained reveal two new research themes, as well as the existence of three constructs highlighted by researchers of TAM. The results are discussed.
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Ahlgren, P.; Jarneving, B.; Rousseau, R. (2003). Requirements for a cocitation similarity measure with special reference to Pearson’s correlation coefficient. Journal of the American Society for Information Science and Technology, 54, 550-560.
Bagozzi, R. (2007). The legacy of the Technology Acceptance Model and a Proposal for a Paradigm Shift. Journal of the Association for Information System, 8 (4), 244-254.
Benbasat, I. (2007). Quo Vadis, TAM? Journal of the Association for Information System, 8 (4), 211-218.
Bensman, S. (2004). Pearson’s r and author co-citation analysis: A commentary on the controversy. Journal of the American Society for Information Science and Technology, 55 (10), 935-936.
Brown, S. A.; Venkatesh, V.; Bala, H. (2006). Household technology use: integrating household life and the model of adoption of technology in household. Information Society, 22 (4), 205-218.
Bruer, J. (2010). Can we talk? How the cognitive neuroscience of attention emerged from neurobiology and psychology, 1980-2005. Scientometrics, 83 (3), 751-764.
Bruner, G.; Kumar, A. (2005). Explaining consumer acceptance of handheld Internet device. Journal of Bussiness Reseach, 58 (5), 553-558.
Börner, K.; Chen, C.; Boyack. K. W. (2003). Visualizing knowledge domains. Annual Review of Information Science y Technology. 37 (1), 179-255.
Burton-Jones, A.; Straub, D, W. (2006). Reconceptualizing system usage: An approach and empirical test. Information System Research, 17 (3), 228-246.
Cao, M.; Zhang, Q.; Seydel, J. (2005). B2C e-commerce web site quality: an empirical examination. Industrial Management y Data Systems, 105 (5), 645-661.
Culnan, M. (1986). Management Information System, 1972-1982: A Co-citation Analysis. Management Science, 32 (2), 156-172.
Chen, C. (1998). Generalized similarity analysis and pathfinder network scaling, Interacting with Computers, 10 (2), 107-128.
Chen, C.; Kuljis, J. (2003). The Rising Landscape: A Visual Exploration of Superstring Revolutions in Physics. Journal of the American Society for Information Science and Technology, 54 (5), 435-446.
Chen, C. (2004). Searching for intellectual turning points: Progressive knowledge domain visualization. Proceedings of the National Academy of Sciences of the United States of America, 101 (suppl. 1), 5303-5310.
Chen, T.; Lee, M. (2006). Revealing Themes and Trends in the Knowledge Domain’s Intellectual Structure. In A. Hoffman y otros (Eds.), Pacific Rim Knowledge Acquisition Workshop, PKAW 2006 (pp. 99-107). Berlin: Springer.
Cheong, J. H.; Park M. C. (2005). Mobile internet acceptance in Korea. Internet Research, 15 (2), 125-140.
Chuttur, M. Y. (2009). «Overview of the Technology Acceptance Model: Origins, Developments and Future Directions», Indiana University, USA. Sprouts: Working Papers on Information Systems, 9 (37). http://sprouts.aisnet.org/9-37.
Davis, F. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13 (3), 319-340.
Davis, F.; Bagozzi, R. P.; Warshaw, P. R. (1989). User acceptance of computer technology: a comparison of two theoretical models. Management Science, 35 (8), 982-1003.
Edwards, J. R.; Bagozzi, R. P. (2000). On the Nature and Direction of Ralationships between constructs. Psychological Methods, 5 (2), 155-174.
Egghe, L.; Leydesdorff, L. (2009). The Relation between Pearson’s correlation Coefficient r and Salton’s Cosine Measure. Journal of the American Society for Information Science and Techology, 60 (5), 1027-1036.
Fishbein, M.; Ajzen, I. (1975). [Online]: Belief, Attitude, Intention and Behavior: An introduction to theory and research. Reading, MA: Addison-Wesley. Available in: <http://www.people.umass.edu/aizen/f&a1975.html>.
Freeman, L. (1979). Centrality in networks: Conceptual clarification. Social Networks, 1, 215-239.
Freeman, L.; Borgatti, S.; White, D. (1991). Centrality in valued graphs: A measure of betweenness based on network flow. Social Networks, 13 141-154.
Garfield, E. (1955). Citation indexes for science: A new dimension in documentation through association of ideas. Science, 122 (108-111).
Garfield, E.; Sher, I.; Torpie, R. (1964). The use of citation data in writing the history of science. Philadelphia: Institute for Scientific Information.
Garfield, E. (1994). Scientography: Mapping the tracks of science. Current Contents: Social & Behavioural Sciences, 7 (45), 5-10.
Griffith, B.; Small, H.; Stonehill, J.; Dey, S. (1974). The Structure of Scientific Literatures II: Toward a Macro and Microstructure for Science. Science Studies, 4, 339-364.
Griffith, B. (Ed.) (1980). Key papers in information science (pp. vi-vii). White Plains, NY: Knowledge Industry Publications.
Ha, I.; Yoon, Y.; Choi, M. (2007). Determinants of adoption of mobile games under mobile broadband wireless access environment. Information y Management, 44 (3), 276-286.
Hanneman, R.; Riddle, M. (2005). Introduction to social network methods. Riverside, CA: University of California, Riverside (published in digital form In: <http://faculty.ucr.edu/~hanneman/>. Henderson, R. M.; Clark, K. B. (1990). Architectural innovation: The reconfiguration of existing product technologies and the failure of estableshed firms. Administrative Science Quarterly, 35, 9-30.
Hong, S. J.; Thong, J. Y. L.; Tam, K. Y. (2006). Understanding continued information technology usage behavior: A comparison of three models in the context of mobile internet. Decision Support Systems, 42, 1819-1834.
Kang, I. S.; Na, S. H.; Lee, S.; Jung, H.; Kim, P.; Sung, W. K.; Lee, J. H. (2009). On coauthorship for author disambiguation. Information Processing and Management, 45, 84-97.
Kim, S.; Malhotra, N. (2005). A longitudinal model of continued IS Use: An integrative view of four mechanisms underlying posadoption phenomena. Management science, 51 (5), 741-755.
King, W. R.; He, J. (2006). A meta-analysis of the technology acceptance model. Information and Management, 43 (6), 740-755.
Kuhn, T. (1996). The Structure of Scientific Revolutions. (3rd ed.). Chicago: The University of Chicago Press.
Kroenke, D. (2009). Using MIS. 2nd ed. Upper Saddle River, N. J.: Pearson/Prentice Hall. ISBN-10: 0138132488.
Lai, V.; Li, H. (2005). Technology acceptance model for internet banking: an invariance analysis. Information y Management, 42 (2) 373-386.
Lee, M. K. O.; Cheung, C. M. K.; Chen, Z. (2005). Acceptance of Internet-based learning medium: the role of extrinsic and intrinsic motivation. Information y Management, 42 (8), 1095-1104.
Lee, M.; Chen, T. (2009). Trends in Ubiquitous Multimedia Computing. International Journal of Multimedia and Ubiquitous Engineering, 4 (2), 115-124.
Ledezma, R.; Molina, G.; Valero, P. (2002). Análisis de consistencia interna mediante Alfa de Cronbach: un programa basado en gráficos dinámicos. Psico-USF, 7 (2), 143-152.
Legris, P.; Ingham, J.; Collerette, P. (2003). Why do people use information technology? A critical review of the technology acceptance model. Information and Management, 40 (3), 191-204.
Leydesdorff, L.; Wouters, P. (1999). Between texts and contexts: advances in theories of citation. Scientometrics, 44 (2),173-92.
Leydesdorff, L.; Vaughan, L. (2006). Co-occurrence matrices and their applications in information science: Extending ACA to the Web environment. Journal of the American Society for Information Science and Technology, 57, 1616-1628.
Leydesdorff, L. (2008). On the Normalization and Visualization of Author Co-Citation Data: Salton’s Cosine versus the Jaccard Index. Journal of the American Society for Information Science and Technology, 59 (1),77-85.
Lin, C, S.; Wu, S.; Tsai, R. J. (2005). Integrating perceived playfulness into expectation-confirmation model for web portal context. Information and Management, 42 (5), 683-693.
Luarn, P.; Lin, H. H. (2005). Toward an understanding of the behavioral intention to use mobile banking. Computers in Human Behavior, 21 (6), 873-891.
Ma, Z.; Yu, K. (2009). Research paradigms of contemporary knowledge management studies: 1998-2007. Journal of Knowledge Management, 14 (2), 175-189.
Malin, B.; Caley, K. (2007). A longitudinal social network analysis of the editorials boards of medical informatics and bioinformatics journals. Journal of the American Medical Informatics Association, 14 (3), 340-348.
Miguel, S.; Moya-Anegón, F.; Solana-Herrero, V. (2007). El análisis de co-citas como método de investigación en Bibliotecología y Ciencia de la Información. Investigación Bibliotecológica, 21 (43), 139-155.
Moya-Anegon, F.; Herrero-Solana, V.; Jimenez-Contreras, E. (2006). A connectionist and multivariate approach to science maps: the SOM, clustering and MDS applied to library science research and information. Journal of Information Science, 32 (1), 63-77.
McCain, K. (1990). Mapping Authors in Intellectual Space: A Technical Overview. Journal of the American Society for Information Science, 41 (6), 433-443.
McCain, K.; Verner, J.; Hislop, G.; Evanco, W.; y Cole, V. (2005). The use of bibliometric and knowledge elicitation techniques to map a knowledge domain: Software Engineering in the 1990s. Scientometrics, 65 (1), 131-144.
Ngai, E.; Poon, J.; Chan, I. H. (2007). Empirical examination of the adoption of WebCT using TAM. Computers and Education, 48 (2), 250-267.
Nielsen, J. (1993). Usability Enginnering. First Edition. San Francisco, USA: Elsevier. ISBN: 0-12-518406-9.
Nooy, W.; Mrvar, A.; Batagelj, V. (2005). Exploratory social network analysis with Pajek. New York: Cambridge University Press.
Noyons, E.; Van Raan, A. (1998). Monitoring scientific developments from a dynamic perspective: Self-organized structuring to map neural network research. Journal of the American Society for Information Science, 49 (1), 68-81.
Noyons, E.; Moed, H.; Luwel, M. (1999). Combining mapping and citation analysis for evaluative bibliometric purposes: A bibliometric study. Journal of the American Society for Information Science, 50 (2), 115-131.
Nysveen, H.; Pedersen, P.; Thorbjornsen, H. (2005). Intentions to Use Mobile Services: Antecedents and Cross-Service Comparisons. Journal of the Academy of Marketing Science, 33 (3), 330-346.
Peay, E. (1976). A note concerning the connectivity of social networks. Journal of Mathematical Sociology, 4, 319-321.
Petter, S.; Straub, D.; Rai, A. (2007). Specifycing formative constructs in Information System research. MIS Quartery, 31 (4), 623-656.
Pilkington, A.; Meredith, J. (2009). The evolution of the intellectual structure of operations management 1980-2006: A co-citation analysis. Journal of Operations Management, 27(3), 185-202.
Price, D. (1961). Science since Babylon. New Haven: Yale University Press.
Price, D. (1965). Networks of scientific papers. Science, 149, 510-515.
Raghupathi, W.; Nerur, S. (2008). Research and Trends in Health Information Systems. Methods of Information in Medicine, 47 (5), 435-442.
Rosenthal, S.; DiMatteo, M. R. (2001). Meta-analysis: recent developments in quantitative methods form literature reviews, Annual Review of Psychology, 52 (1), 59-82.
Saadé, R.; Bahli, B. (2005). The impact of cognitive absorption on perceived usefulness and perceived ease of use in on-line learning: an extension of the technology acceptance model. Information y Management, 42 (2), 317-327.
Sanchez-Franco, M. J.; Roldan, J. L. (2005). Web acceptance and usage model. A comparison between goal-directed and experiential web users. Internet Research, 15 (1), 21-24.
Sircar, S.; Nerur, P.; Mahapatra, R. (2001). Revolution or Evolution? A Comparison of Object-Oriented and Structured System Development Methods. MIS Quarterly, 25 (4), 457-471.
Shang, R. A.; Chen, Y-C.; Shen, L. (2005). Extrinsic versus intrinsic motivations for consumers to shop on-line. Information y Management, 42 (3), 401-413.
Schepers, J.; Wetzels, M. (2007). A meta-analysis of the technology acceptance model: Investigating subjective norm and moderation effects. Information and Management, 44, 90-103.
Small, H., y Griffith, B. (1974). The Structure of Scientific Literatures I: Identifying and graphing Specialties. Science Studies, 4, 17-40.
Su, Y. M.; Yang, S. C.; Hsu, P. Y.; Shiau W. L. (2009). Extending co-citation analysis to discover authors with multiple expertise. Expert Systems with Applications, 36, 4287-4295.
Sun, H.; Zhang, P. (2006). The role of moderating factors in user technology acceptance. International Journal of Human-Computer Studies, 64 (2), 53-78.
Tang, L.; Walsh, J. (2010). Bibliometric fingerprints: name disambiguation based on approximate structure equivalence of cognitive maps. Scientometrics, 84 (3), 763-784.
Thomson Reuters (2009). Top topics research from map – August 2009. Technology Acceptance Model. Retrieved November, 2010. In: <http://www.vvenkatesh.com/Files/Sciencewatch.pdf>.
Turel, O.; Serenko, A.; Bontis, N. (2007). User acceptance of wireless short messaging services: deconstructing perceived value. Information y Management, 44 (1), 63-73.
Vargas-Quesada, B.; Doménech, I.; García, G., Sanchez, C.; Extremeño, A.; Zulueta, M. (2007). La identificación temática a partir de la visualización de la información: una aproximación mediante el caso de women en Medline. Revista Española de Documentación Científica, 30 (2), 163-177.
Venkatesh, V.; Davis, F. (1996). A model of the antecedents of perceived ease of use: development and test. Decision Sciences, 27 (3), 451-481.
Venkatesh, V.; Morris, M.; Davis, G.; Davis, F. (2003). User acceptance of information technology: towards a unified view. MIS Quarterly, 27 (3), 479-501.
White, H. (1981). Cocited Author Retrieval Online: An Experiment with the Social Indicators Literature. Journal of the American Society for Information Science, 32, 16-22.
White, H.; Griffith, B. (1981). Author Co-citation: A literature Measure of Intellectual Structure. Journal of the American Society for Information Science, 32 (3), 163-172.
White, H.; Griffith, B. (1982). Authors as markers of intellectual space: Co-citation in studies of science, technology and society. Journal of Documentation, 38 (4), 255-272.
White, H.; McCain (1998). Visualizing a Discipline: An Author Co-Citation Analysis of Information Science, 1972-1995. Journal of the American Society for Information Science, 49 (4), 327-355.
White, H. (2003a). Pathfinder Networks and Author Co-citation Analysis: A Remapping of Paradigmatic Information Scientists. Journal of the American Society for Information Science and Technology, 54 (5), 423-434.
White, H. (2003b). Author Co-citation Analysis and Pearson’s r, Journal of the American Society for Information Science and Technology, 54 (13), 1250-1259.
Wixon, B. H.; Todd, P. A. (2005). A Theoretical integration of user satisfaction and technology acceptance. Information Systems Research, 16 (1), 85-102.
Wu, J. H.; Wang, S. C. (2005). What drives mobile commerce? An empirical evaluation of the revised technology acceptance model. Information and Management, 42 (5), 719-729.
Yan, X. (1988). On fuzzy cliques in fuzzy networks. Journal of Mathematical Sociology, 13, 359-389.
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