Earticle

초록

영어

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 in-formation 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 includ-ing 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 communica-tion 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 adop-tion/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 environ-mental 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 manag-er'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 organ-izations 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.

목차

Ⅰ. 서 론
 Ⅱ. 관련연구
  2.1 시맨틱 웹 관련 연구
  2.2 혁신확산연구
 Ⅲ. 연구설계
  3.1 연구방법
  3.2 자료수집
 Ⅳ. 분석 결과
  4.1 자료 분석 절차 및 범주화
  4.2 채택과 확산의 영향요인 분석
  4.3 확산모형 및 토의
  4.4 명제 도출
 Ⅴ. 결 론
 
 <부록 1> 면접 내용의 범주화: 공급자 면접내용의 예
 <부록 2> NVivo에서 상황인지, 지능형 서비스라는 범주로 분류되어 재조합된 화면
 <부록 3> 범주화의 사례: 공급자 면접 자료분석
 About the Authors

저자

• 주재훈 [ Jaehun Joo | Professor, Department of Information Management, Dongguk University at Gyeongju, South Korea ]

참고문헌