The size and complexity of large and diverse data sources in semantic analysis, organization and interpretation from the help of machines are fast growing on the extent of human direct understanding with high-ranking order and its strategic value to publish. Due to the volume, speed, style, and accuracy, the number of data integration creates a major challenge for the traditional methods and brings many opportunities to integrate. Semantic Web technology has the potential in data integration and has become an important means of solving big data technology. Although it is important to manage the large amount of data, only a few studies focused on the determinants of the Semantic Web’s application. Based on the theory of organization in the scope of the technical environment, this study failed in some factors of the research model, which are the technical applications seen by professionals, especially in the computing environment of commercial companies. We have affirmed the model thanks to the researchers of modern technology, especially information technology, their experiments have conducted the results in the development of some sections such as management, architecture systems, software, and web design. The results show that the utility, usability, organizational innovation, data organization, and data management are perceived as important factors of the application software. This study provides new insights into the application of organization theory from the perspective of professionals, and the Semantic Web has to match the technical base.
How to cite this paper
Ngo, Q & Tao, N. (2020). Retracted: Determinants of semantic web technology adoption from IT professionals’ perspective: Industry competition, organization innovativeness, and data management capability.International Journal of Data and Network Science, 4(3), 271-288.
Refrences
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Choi, J., Nazareth, D. L., & Jain, H. K. (2010). Implementing service-oriented architecture in organizations. Journal of Management Information Systems, 26(4), 253-286.
Chou, C.-H., Zahedi, F. M., & Zhao, H. (2014). Ontology-Based Evaluation of Natural Disaster Management Websites: A Multistakeholder Perspective. Mis Quarterly, 38(4), 997-1016.
Chwelos, P., Benbasat, I., & Dexter, A. S. (2001). Empirical test of an EDI adoption model. Information systems research, 12(3), 304-321.
D'Aubeterre, F., Singh, R., & Iyer, L. (2008). A Semantic Approach to Secure Collaborative Inter-Organizational eBusiness Processes*(SSCIOBP). Journal of the Association for Information Systems, 9(3/4), 231.
Danneels, E. (2002). The dynamics of product innovation and firm competences. Strategic management journal, 23(12), 1095-1121.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340.
Dean, M., & Schreiber, G. (2004). OWL Web Ontology Language Reference: http://www. w3. org. Retrieved from
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Forman, C. (2005). The corporate digital divide: Determinants of Internet adoption. Management Science, 51(4), 641-654.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
Gagnon, M. (2007). Ontology-based integration of data sources. Paper presented at the 2007 10th International Conference on Information Fusion.
Gliozzo, A., Biran, O., Patwardhan, S., & McKeown, K. (2013). Semantic technologies in IBM Watson. Paper presented at the Proceedings of the Fourth Workshop on Teaching NLP and CL.
Hair Jr, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2016). A primer on partial least squares structural equation modeling (PLS-SEM): Sage publications.
Hepp, M. (2008). Goodrelations: An ontology for describing products and services offers on the web. Paper presented at the International Conference on Knowledge Engineering and Knowledge Management.
Hong, S.-J., & Tam, K. Y. (2006). Understanding the adoption of multipurpose information appliances: The case of mobile data services. Information Systems Research, 17(2), 162-179.
Hsu, C.-L., Lu, H.-P., & Hsu, H.-H. (2007). Adoption of the mobile Internet: An empirical study of multimedia message service (MMS). Omega, 35(6), 715-726.
Hsu, I.-C. (2013). Personalized web feeds based on ontology technologies. Information Systems Frontiers, 15(3), 465-479.
Iacovou, C. L., Benbasat, I., & Dexter, A. S. (1995). Electronic data interchange and small organizations: adoption and impact of technology. MIS Quarterly, 465-485.
Igbaria, M., Zinatelli, N., Cragg, P., & Cavaye, A. L. (1997). Personal computing acceptance factors in small firms: A structural equation model. MIS quarterly, 21(3).
Jeyaraj, A., Rottman, J. W., & Lacity, M. C. (2006). A review of the predictors, linkages, and biases in IT innovation adoption research. Journal of Information Technology, 21(1), 1-23.
Khoumbati, K., Themistocleous, M., & Irani, Z. (2006). Evaluating the adoption of enterprise application integration in health-care organizations. Journal of Management Information Systems, 22(4), 69-108.
Kim, G., & Suh, Y. (2011). Semantic business process space for intelligent management of sales order business processes. Information Systems Frontiers, 13(4), 515-542.
Kim, H., Fox, M. S., & Sengupta, A. (2007). How To Build Enterprise Data Models To Achieve Compliance To Standards Or Regulatory Requirements (and share data). Journal of the Association for Information Systems, 8(2), 5.
Klein, M., Broekstra, J., Fensel, D., van Harmelen, F., & Horrocks, I. (2003). Ontologies and schema languages on the web. Spinning the Semantic Web: Bringing the World Wide Web to its full potential, 95-140.
Kuan, K. K., & Chau, P. Y. (2001). A perception-based model for EDI adoption in small businesses using a technology–organization–environment framework. Information & Management, 38(8), 507-521.
Lee, C.-P., & Shim, J. P. (2007). An exploratory study of radio frequency identification (RFID) adoption in the healthcare industry. European Journal of Information Systems, 16(6), 712-724.
Lee, J. (2004). Discriminant analysis of technology adoption behavior: a case of internet technologies in small businesses. Journal of Computer Information Systems, 44(4), 57-66.
Lim, K. H. (2009). Knowledge management systems diffusion in Chinese enterprises: A multistage approach using the technology-organization-environment framework. Journal of Global Information Management (JGIM), 17(1), 70-84.
Lin, A., & Chen, N.-C. (2012). Cloud computing as an innovation: Percepetion, attitude, and adoption. International Journal of Information Management, 32(6), 533-540.
Livenson, I., & Laure, E. (2011). Towards transparent integration of heterogeneous cloud storage platforms. Paper presented at the Proceedings of the fourth international workshop on Data-intensive distributed computing.
MacKenzie, S. B., & Podsakoff, P. M. (2012). Common method bias in marketing: causes, mechanisms, and procedural remedies. Journal of Retailing, 88(4), 542-555.
Mishra, A. N., & Agarwal, R. (2010). Technological frames, organizational capabilities, and IT use: An empirical investigation of electronic procurement. Information Systems Research, 21(2), 249-270.
Mishra, A. N., Konana, P., & Barua, A. (2007). Antecedents and consequences of internet use in procurement: an empirical investigation of US manufacturing firms. Information Systems Research, 18(1), 103-120.
Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2(3), 192-222.
Oliveira, T., & Martins, M. F. (2010). Understanding e-business adoption across industries in European countries. Industrial Management & Data Systems, 110(9), 1337-1354.
Oliveira, T., Thomas, M., & Espadanal, M. (2014). Assessing the determinants of cloud computing adoption: An analysis of the manufacturing and services sectors. Information & Management, 51(5), 497-510.
Pan, M.-J., & Jang, W.-Y. (2008). Determinants of the adoption of enterprise resource planning within the technology-organization-environment framework: Taiwan's communications industry. Journal of Computer information systems, 48(3), 94-102.
Petty, R. E., & Cacioppo, J. T. (1981). Attitudes and persuasion: classic and contemporary approaches, Wm. C. Brown, Dubuque, IA.
Pick, J. B., & Azari, R. (2011). A global model of technological utilization based on governmental, business-investment, social, and economic factors. Journal of Management Information Systems, 28(1), 49-84.
Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879.
Porter, M. E. (1985). Competitive advantage. New York.
Premkumar, G., Ramamurthy, K., & Nilakanta, S. (1994). Implementation of electronic data interchange: an innovation diffusion perspective. Journal of Management Information Systems, 11(2), 157-186.
Premkumar, G., & Roberts, M. (1999). Adoption of new information technologies in rural small businesses. Omega, 27(4), 467-484.
Rahi, S., Ghani, M., Alnaser, F., & Ngah, A. (2018). Investigating the role of unified theory of acceptance and use of technology (UTAUT) in internet banking adoption context. Management Science Letters, 8(3), 173-186.
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 & Management, 42(2), 317-327.
Shih, D.-H., Chiu, Y.-W., Chang, S.-I., & Yen, D. C. (2008). An empirical study of factors affecting RFID's adoption in Taiwan. Journal of Global Information Management (JGIM), 16(2), 58-80.
Simon, K. D. (2005). The value of open standards and open-source software in government environments. IBM Systems Journal, 44(2), 227-238.
Tan, M., & Teo, T. S. (2000). Factors influencing the adoption of Internet banking. Journal of the Association for information Systems, 1(1), 5.
Teo, T. S., & Pian, Y. (2003). A contingency perspective on Internet adoption and competitive advantage. European Journal of Information Systems, 12(2), 78-92.
Themistocleous, M. (2004). Justifying the decisions for EAI implementations: a validated proposition of influential factors. Journal of Enterprise Information Management, 17(2), 85-104.
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