Asia pacific journal of information systems

The Korea Society of Management Information Systems (한국경영정보학회)
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The Adoption and Diffusion of Semantic Web Technology Innovation: Qualitative Research Approach

시맨틱 웹 기술혁신의 채택과 확산: 질적연구접근법

  • Joo, Jae-Hun (Department of Information Management, Dongguk University at Gyeongju)
  • Published : 2009.03.31
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Abstract

Internet computing is a disruptive IT innovation. Semantic Web can be considered as an IT innovation because the Semantic Web technology possesses the potential to reduce information overload and enable semantic integration, using capabilities such as semantics and machine-processability. How should organizations adopt the Semantic Web? What factors affect the adoption and diffusion of Semantic Web innovation? Most studies on adoption and diffusion of innovation use empirical analysis as a quantitative research methodology in the post-implementation stage. There is criticism that the positivist requiring theoretical rigor can sacrifice relevance to practice. Rapid advances in technology require studies relevant to practice. In particular, it is realistically impossible to conduct quantitative approach for factors affecting adoption of the Semantic Web because the Semantic Web is in its infancy. However, in an early stage of introduction of the Semantic Web, it is necessary to give a model and some guidelines and for adoption and diffusion of the technology innovation to practitioners and researchers. Thus, the purpose of this study is to present a model of adoption and diffusion of the Semantic Web and to offer propositions as guidelines for successful adoption through a qualitative research method including multiple case studies and in-depth interviews. The researcher conducted interviews with 15 people based on face-to face and 2 interviews by telephone and e-mail to collect data to saturate the categories. Nine interviews including 2 telephone interviews were from nine user organizations adopting the technology innovation and the others were from three supply organizations. Semi-structured interviews were used to collect data. The interviews were recorded on digital voice recorder memory and subsequently transcribed verbatim. 196 pages of transcripts were obtained from about 12 hours interviews. Triangulation of evidence was achieved by examining each organization website and various documents, such as brochures and white papers. The researcher read the transcripts several times and underlined core words, phrases, or sentences. Then, data analysis used the procedure of open coding, in which the researcher forms initial categories of information about the phenomenon being studied by segmenting information. QSR NVivo version 8.0 was used to categorize sentences including similar concepts. 47 categories derived from interview data were grouped into 21 categories from which six factors were named. Five factors affecting adoption of the Semantic Web were identified. The first factor is demand pull including requirements for improving search and integration services of the existing systems and for creating new services. Second, environmental conduciveness, reference models, uncertainty, technology maturity, potential business value, government sponsorship programs, promising prospects for technology demand, complexity and trialability affect the adoption of the Semantic Web from the perspective of technology push. Third, absorptive capacity is an important role of the adoption. Fourth, suppler's competence includes communication with and training for users, and absorptive capacity of supply organization. Fifth, over-expectance which results in the gap between user's expectation level and perceived benefits has a negative impact on the adoption of the Semantic Web. Finally, the factor including critical mass of ontology, budget. visible effects is identified as a determinant affecting routinization and infusion. The researcher suggested a model of adoption and diffusion of the Semantic Web, representing relationships between six factors and adoption/diffusion as dependent variables. Six propositions are derived from the adoption/diffusion model to offer some guidelines to practitioners and a research model to further studies. Proposition 1 : Demand pull has an influence on the adoption of the Semantic Web. Proposition 1-1 : The stronger the degree of requirements for improving existing services, the more successfully the Semantic Web is adopted. Proposition 1-2 : The stronger the degree of requirements for new services, the more successfully the Semantic Web is adopted. Proposition 2 : Technology push has an influence on the adoption of the Semantic Web. Proposition 2-1 : From the perceptive of user organizations, the technology push forces such as environmental conduciveness, reference models, potential business value, and government sponsorship programs have a positive impact on the adoption of the Semantic Web while uncertainty and lower technology maturity have a negative impact on its adoption. Proposition 2-2 : From the perceptive of suppliers, the technology push forces such as environmental conduciveness, reference models, potential business value, government sponsorship programs, and promising prospects for technology demand have a positive impact on the adoption of the Semantic Web while uncertainty, lower technology maturity, complexity and lower trialability have a negative impact on its adoption. Proposition 3 : The absorptive capacities such as organizational formal support systems, officer's or manager's competency analyzing technology characteristics, their passion or willingness, and top management support are positively associated with successful adoption of the Semantic Web innovation from the perceptive of user organizations. Proposition 4 : Supplier's competence has a positive impact on the absorptive capacities of user organizations and technology push forces. Proposition 5 : The greater the gap of expectation between users and suppliers, the later the Semantic Web is adopted. Proposition 6 : The post-adoption activities such as budget allocation, reaching critical mass, and sharing ontology to offer sustainable services are positively associated with successful routinization and infusion of the Semantic Web innovation from the perceptive of user organizations.

Keywords

References

  1. Al-Qirim, N., "A Research Trilogy into E-Commerce Adoption in Small Businesses in New Zealand," Electronic Markets, Vol. 17, No. 4, 2007a, pp. 263-285 https://doi.org/10.1080/10196780701635872
  2. Al-Qirim, N. "The Adoption and Diffusion of e-Commerce in Developing Countries:The Case of an NGO in Jordan," InformationTechnology for Development， Vol. 13, No. 2, 2007b, pp. 107-131
  3. Antoniou, G. and Van Harmelen, F., A Semantic Web Primer. Cambridge, Mass: MIT Press, 2004
  4. Attewell, P., "Technology Diffusion and Organizational Learning: The Case of Business Computing ", Organization Science, Vol.3, No. 1, 1992, pp. 1-19 https://doi.org/10.1287/orsc.3.1.1
  5. Baek, S. and Park, K., "A Qualitative Study on the Process of Knowledge Creation at the Infusion Stage in IT Implementation," The Journal of Information Systems, Vol. 15 No.2, 2006, pp. 125-152
  6. Baskerille，R., and Pries-Heje, J., "A Multiple- theory Analysis of a Diffusion of Information Technology Case," Information Systems Journal, Vol. 11, No. 3, 2001, pp. 181-212 https://doi.org/10.1046/j.1365-2575.2001.00106.x
  7. Berners-Lee, T., Hendler, J., and Lassila, O., "The Semantic Web," Scientific American，Vol. 284, No. 5, 2001, pp. 34-43 https://doi.org/10.1038/scientificamerican0501-34
  8. Bessant, J.R., "Influential Factors in Manufacturing Innovation," Research Policy, Vol. 11, 1982, pp. 165-176
  9. Bharadwaj, A., "Integrating Positivist and Interpretive Approaches to Information Systems Research: A Lakatosian Model, Foundations of Information Systems," September 2000, Available http://www.bus.ucf.edu/jcourtney/FIS/Bharadwaj.htm
  10. Brancheau, J.c. and Wetherbe, J., ’The Adoption of Spreadsheet Software: Testing Innovation Diffusion Theory in the Context of End-user Computing", Information Systems Research, Vol. 1, No. 2, 1990, pp. 115-143 https://doi.org/10.1287/isre.1.2.115
  11. Caldeira, M.M. and Ward, J.M., "Understanding the Successful Adoption and Use of IS/IT in SMEs: An Explanation from Portuguese Manufacturing Industries," Information Systems Journal, Vol. 12, 2002, pp. 121- 152 https://doi.org/10.1046/j.1365-2575.2002.00119.x
  12. Chan, S.C.H. and Ngai, E.W.T., "A Qualitative Study of Information Technology Adoption: How Ten Organizations Adopted Web-Based Training,"Information Systems Journal, Vol. 17, 2007, pp. 289-315 https://doi.org/10.1111/j.1365-2575.2007.00250.x
  13. Chau, P.Y.K. and Tam, K.Y. "Factors Affecting the Adoption of Open Systems: An Exploratory Study," MIS Quarterly, Vol. 21. No.1, 1997, pp. 1-24 https://doi.org/10.2307/249740
  14. Chau， P.Y.K. and Tam K. Y., "Organizational Adoption of Open Systems: A 'Technology-Push, Need-Pull' Perspective," Information and Management, Vol. 37, 2000, pp. 229-239 https://doi.org/10.1016/S0378-7206(99)00050-6
  15. Chen，M., "Factors Affecting the Adoption and Diffusion of XML and Web Services Standards for E-business Systems," Int. J. Human-Computer Studies, Vol. 58, 2003, 259- 279 https://doi.org/10.1016/S1071-5819(02)00140-4
  16. Cohen, W.M. and Levinthal, D.A., "Absorptive Capacity: A New Perspective onLearning and Innovation," Administrative Science Quarterly, Vol. 35, No. 1, 1990 pp.128-152 https://doi.org/10.2307/2393553
  17. Cooper, R.B. and Zmud, R.W., "Information Technology Implementation Research: A Technological Diffusion Approach," Management Science, Vol. 36, No. 2, 1990, pp. 123-139 https://doi.org/10.1287/mnsc.36.2.123
  18. Creswell, J.W., Qualitative Inquiry and Research Design-Choosing among Five Traditions, SAGE Publications: Thousand Oaks, 1998
  19. Davies, N.J., Fensel, D., and Harmelen, F.V.(ed)., Toward the Semantic Web: Ontology-Based Knowledge Management，Hoboken, NJ:John Wiley and Sons, 2003
  20. Dedrick， J. and West, J., "Why Firms Adopt Open Source Platforms: A Grounded Theory of Innovation and Standards Adoption," MIS Quarterly Special Issue Workshop on Standard Making: A Critical Research Frontier for Information Systems, 2003, pp. 236-257
  21. Doolin, B. and Troshani, I.,"Organizational Adoption of XBRL," Electronic Markets, Vol. 17, No. 3, 2007, pp. 199-209 https://doi.org/10.1080/10196780701503195
  22. D' Aquin, M., Bouthier, c., Brachais, S., Lieber, J., and Napoli, A., ,’Knowledge Editing and Maintenance Tools for a Semantic Portal in Oncology,'’ Int. J. Human-Computer Studies, Vol. 62, 2005, pp. 619-638 https://doi.org/10.1016/j.ijhcs.2005.02.003
  23. Edgington, T., Choi, B., Henson, K., Raghu, T.S., and Vinze, A., "Adopting Ontology to Facilitate Knowledge Sharing." Communications of the ACM, Vol. 47 No. 11, 2004, pp.85-90 https://doi.org/10.1145/1029496.1029499
  24. Fenn, J. and Linden, A., "Gartner's Hype Cycle Special Report for 2005,'’ Gartner ID Number G00130115, 2005, pp. 1-7
  25. Fichman R.G., "Going Beyond the Domin-ant Paradigm for Information Technology Innovation Research: Emerging Concepts and Methods," journal of the Association for Information Systems, Vol. 5, No. 8, 2004, pp. 314-355
  26. Fichman, R.G., "Information Technology Diffusion: A Review of Empirical Research，" in Proceedings of Thirteenth Intemational Conference on Information Systems, Dallas, December 1992, pp. 195-206
  27. Gallivan, M., "Organizational Adoption and Assimilation of Complex Technological Innovations: Development and Application of a New Framework," The Data Base for Advances Information Systems, Vol. 32, No. 3, 2001, pp. 51-85 https://doi.org/10.1145/506724.506729
  28. Glaser, B.G. and A.L. Strauss, The Discovery of Grounded Theory: Strategies，for Qualitative Research, 1967, Chicago: Aldine
  29. Glaser, B.G., Basics of Grounded Theory Analysis, Sociology Press: Mill Valley, CA, 1992
  30. Grandon，E.E. and Pearson, J.M., "Electronic Commerce Adoption: An Empirical Study of Small and Medium US Business," Information and Management, Vol. 42, 2004, pp.197-216 https://doi.org/10.1016/j.im.2003.12.010
  31. Hevner, A.R., March, S.T., Park, J., and Ram, S.,"Design Science in Information Systems Research," MIS Quarterly, Vol. 28, No. 1, 2004, pp. 75-105
  32. Karahanna， E., Straub, D.W., and Chervany, N.L. "Information Technology Adoption Across Time: A Cross-Sectional Comparison of Pre-Adoption and Post-Adoption Briefs," MIS Quarterly, Vol. 23, No. 2, 1999, pp. 183-213
  33. Khoumbati, K., Information Systems and Healthcare XXIV: Factors Affecting the EAIAdoption in the Healthcare Sector," Communications of the Association for Information Systems, Vol. 22, No. 5, 2008, pp. 87-102
  34. Kim, Y., "Technological Collaboration Unkages and the Innovation Output in Small and Medium-sized Firms: A Study on the Moderating Effects of Absorptive Capacity," Korean Management Review, Vol. 34, No. 5, 2005, pp. 1365-1390
  35. King, J.L., Kraemer, K.L., MaFarlan, F.w., and Yap, C.S., Institutional Factors inf ormation Technology Innovation," Information Systems Research, Vol. 5, No. 2, 1994, pp. 139-169 https://doi.org/10.1287/isre.5.2.139
  36. Lee, D., M. chang and J. Yoo,"Factors Influ-encing Adoption of Corporate Web Site over Time: Innovation Diffusion Theory Perspective," The Journal of MIS Research, Vol. 13, No. 4, 2003, pp. 257-277
  37. 나e， J., Upadhyaya, S.J., Rao, H.R. and Sharman, R., "Secure Knowledge Management and the Semantic Web," Communications of ACM, Vol. 48, No. 12, 2005, pp. 48-54 https://doi.org/10.1145/1101779.1101808
  38. Lee, S., M. Kang and B. Kim, "An Analytical Study of ICT Adoption Based on Diffusion Innovation," The Journal of Information Systems, V이 .14， No. 2, 2005,pp.257-276
  39. Lyytinen, K. and Rose, G.M., ''The Disruptive Nature of Wormation Technology Innovations: The Case of Intemet Computing in Systems Development Organizations，"MIS Quarterly, Vol. 27, No. 4, pp. 557-595,2003
  40. Maedche, A., Motik, B., Stojanovic, L.,Studer, R., and Voltz, R., "Ontologies forEnterprise Knowledge Management," IEEE Intelligent Systems, Vol. 18, No. 2, 2003, pp.26-33 https://doi.org/10.1109/MIS.2003.1193654
  41. Melville, N. and Ramirez, R.,Information Technology Innovation Diffusion: An Information Requirements Paradigm，Information Systems Journal, Vol. 18, 2008, pp. 247-273 https://doi.org/10.1111/j.1365-2575.2007.00260.x
  42. Meyer, A. and Goes, J., "Organizational Assimilation of Innovations: A Multilevel Contextual Analysis," Academy of Management Journal, Vol. 31, No. 4, 1988, pp. 897-923 https://doi.org/10.2307/256344
  43. Moore, G.C. and Benbasat, I., "Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation," Information Systems Research, Vol. 2, No. 3, 1991, pp. 192-222 https://doi.org/10.1287/isre.2.3.192
  44. Munro, H. and Noori, H., "Measuring Commitment to New Manufacturing Technology: Integrating Technological Push and Marketing Pull Concepts," IEEE Transactions on Engineering Management, Vol. 35, No. 2, 1988, pp. 63-70 https://doi.org/10.1109/17.6006
  45. Nambisan, 5. and Wang, Y., "Web Technology Adoption and Knowledge Barriers, "Journal of Organizational Computing and Electronic Commerce, Vol. 10, No. 2, 2000, pp.129-147 https://doi.org/10.1207/S15327744JOCE1002_4
  46. Nolan, R.L., "Managing the Four Stages of EDP Growth,'' Harvard Business Review,Vol.52,1974
  47. Noy, N.F., Sintek, M., Decker, S., Crubezy, M., Fergerson, R.W., and Musen, M.A., "Creating Semantic Web Contents with Pro-tege-2000," IEEE Intelligent Systems, Vol. 16, No. 2, 2001, pp. 60-71 https://doi.org/10.1109/5254.920601
  48. Premkumar， G., Ramamurthy, K. and Nilakanta，S., "Implementation of Electronic Data Interchange: An Innovation Diffusion Perspective, "Journal of Management Information Systems, Vol. 11, No. 2, 2001, pp. 157-186
  49. Rai, A. and Patnayakuni, R., "A Structural Model for CASE Adoption Behavior," Journal of Management Information Systems, Vol. 13, No. 1, 1996, pp. 37-46
  50. Ranganathan, C., Dhaliwal, J.S., and Teo,T.S.H., "Assimilation and Diffusion of Web Technologies in Supply-Chain Management: An Examination of Key Drivers and Performance Impact " International Journal of Electronic Commerce, Vol. 9, No. 1, 2004， pp. 127-161
  51. Ravichandran，T., "Organizational Assimilation of Complex Technologies: An Empirical Study of Component-Based Software Development," IEEE Transactions on Engineering Management, Vol. 52, No. 2, 2005, pp. 249-268 https://doi.org/10.1109/TEM.2005.844925
  52. Rogers, E.M., Diffusion of Innovation, 5th ed., Free Press: New York, NY, 2003
  53. Rosemann, M. and Vessey, I., "Toward Improving the Relevance of Information Systerns Research to Practice: The Role of Applicability Checks,'' MIS Quarterly, Vol.32, No. 1, 2008, pp. 1-22
  54. Scherer, F.M., "Demand-Pull and Technological Innovation, Schmookler Revisited," J. Ind. Econ., Vol. 30, 1982, pp. 225-237 https://doi.org/10.2307/2098216
  55. Sherif, K. and Vinze, A., "Barriers to Adoption of Software Reuse: A Qualitative Study,'’ Information and Management, Vol. 41, 2003, pp. 159-175 https://doi.org/10.1016/S0378-7206(03)00045-4
  56. Shih, H., "Technology-Push and Communication- Pull Forces Driving Message-Based Coordination Performance, "Journal of Strategic Information Systems, Vol. 15, 2006, pp.105-123 https://doi.org/10.1016/j.jsis.2005.08.004
  57. Sora, K. and Kym, H., "Knowledge Transfer for Me and Us Theory: A Grounded Theory Describing the Psychological State of Organizational Members Transferring Knowledge," Korean Management Review, Vol. 34, No. 3, 2005, pp. 739-781
  58. Strauss, A. and Corbin, J., "Grounded Theory Methodology: An Overview," In N. Denzin and Y. Lindoln(Eds.), Handbook of Qualitative Research, Sage: Thousand Oaks,CA, 1994, pp. 273-285
  59. Strauss, A. and Corbin, J., Basics of Qualitative Research: Grounded Theory Procedures and Techniques, Sage: Newbury Park, CA, 1990
  60. Suh， H., J. Park, H. Yang and K. Shin, "Individual Absorptive Capacity and the Performance of Using ERP: Knowledge Transfer Perspective," Korean Management Review, Vol. 34, No. 3, 2005, pp. 651-681
  61. Sung W., Jung, H., Park, D.,"OntoFrame-K: A Platform of Sharing and Distributing Knowledge and Inforrnation Based on Semantic Web for Supporting Collaborative Research," Communications of the Korea inforrnation Science Society, Vol. 24, No.4,2006, pp. 65-72
  62. Swanson, E.B., "Inforrnation Systerns Innovation among Organizations," Management Science, Vol. 40, No. 9, 1994, pp. 1069-1092 https://doi.org/10.1287/mnsc.40.9.1069
  63. Tonatzky, L.G. and Fleischer, M., The Process of Technological Innovation, 1990, Lexington Books: Lexington, MA
  64. Utterback, J.M. and Abernathy, w.J., "A Dynamic Model of Process and ProductInnovation," Omega, Vol. 3, No. 6, 1975, pp.639-656 https://doi.org/10.1016/0305-0483(75)90068-7
  65. Utterback, J.M., "Innovation in Industry and the Diffusion of Technology," Science, Vol. 183. No. 4125, 1974, pp. 620-626 https://doi.org/10.1126/science.183.4125.620
  66. Wang, S., Archer, N.P., and Zheng, W., "An Exploratory Study of Electronic Marketplace Adoption: A Multiple Perspective Views," Electronic Market, Vol. 16, No. 4, 2006, pp.337-348 https://doi.org/10.1080/10196780600999775
  67. White, A., Daniel, E., Ward, J., and Wilson,H., "The Adoption of Consortium B2B eMarketplaces: An Exploratory Study," Journal of Strategic，Information Systems, Vol. 16, 2007, pp. 71-103 https://doi.org/10.1016/j.jsis.2007.01.004
  68. Zhu, K. and Kraemer, K.L., "Post Adoption Variations in Usage and Value of E-Business by Organizations: Cross-Country Evidence from the Retail Industry," Information Systems Research, Vol. 16, No. 1, 2005, pp. 61-84 https://doi.org/10.1287/isre.1050.0045
  69. Zhu, K., Kraemer, K.L., and Xu, S., "The Process of Innovation Assimilation by Firms in Different Countries: A Technology Diffusion Perspective on E-Business," Management Science, Vol. 52, No. 10, 2006, pp. 1557 -1576 https://doi.org/10.1287/mnsc.1050.0487
  70. Zmud, R.W. and Apple, L.E., "Measuring Information Technology Infusion," Unpublished Manuscript, 1989
  71. Zmud, R. w., "An Examination of ’Push-Pull’ Theory Applied to Process Innovation in Knowledge Work," Management Science, Vol. 30, No. 6, 1984, pp. 727-738 https://doi.org/10.1287/mnsc.30.6.727