Henri Knoesen
Lisa F. Seymour
ABSTRACT
The importance of Business Intelligence (BI) within organisations is increasing with insights being used across organisations for tasks ranging from daily management decision support to executive strategic planning. With the increasingly important role the internet plays in consumers' lives, an abundance of valuable data is to be found online. This data can be used to enhance the ability of BI to deliver important information to all levels within the organisation. Yet including web data in traditional BI practice has not yet delivered value seamlessly. Hence the primary question asked in this paper is: What are the organisational barriers which prevent the inclusion of unstructured web data in BI practice? By means of a single case study within an Insurance company in the Western Cape, and by using a hybrid inductive and deductive research approach, this research identifies the key barriers in this organisation to the adoption of this advanced BI innovation. The major factors were found to be the lack of management support, poor understanding of the potential benefits of using web data, the reliability and privacy concerns related to this data, and no innovation champion driving the adoption. The resultant causal model of barriers can be used by organisations wanting to adopt this BI innovation to suggest possible actions which can be undertaken to eliminate some of the barriers.
- Almquist, E., Senior, J. & Springer, T. (2015). Three promises and perils of big data. Retrieved from http://www.bain.com/publications/articles/three-promises-and-perils-of-big-data.aspx on 12th August 2015.Google Scholar
- Askarany, D. (2003). An overview of the diffusion of advanced techniques. Advanced Topics in Global Information, 2, 225--250. Google ScholarDigital Library
- Askarany, D., & Smith, M. (2000). The impact of contextual factors on the diffusion of accounting innovation: Australian evidence. Sixth Interdisciplinary Perspectives on Accounting Conference, Manchester, UK.Google Scholar
- Baumgartner, R., Frölich, O., Gottlob, G., Harz, P., Herzog, M., Lehmann, P., & Wien, T. (2005). Web data extraction for business intelligence: The lixto approach. Datenbanksysteme in Business, Technologie Und Web, 11, 30--47.Google Scholar
- Beatty, R. C., Shim, J., & Jones, M. C. (2001). Factors influencing corporate web site adoption: A time-based assessment. Information & Management, 38(6), 337--354.Google ScholarCross Ref
- Bélanger, F., & Carter, L. (2008). Trust and risk in e-government adoption. The Journal of Strategic Information Systems, 17(2), 165--176. Google ScholarDigital Library
- Bevins, T., & Haque, N. (2010). Data enabled collaborative decision-making: A guide for next generation enterprise decision processes. Moxie Insight, 2010.Google Scholar
- Bhatnagar, A. (2009). Web analytics for business intelligence: Beyond hits and sessions. Online, 33(6), 32--35.Google Scholar
- Blackman Jr, A. W. (1972). A mathematical model for trend forecasts. Technological Forecasting and Social Change, 3, 441--452.Google ScholarCross Ref
- Blumberg, R., & Atre, S. (2003). The problem with unstructured data. DM Review, 13, 42--49.Google Scholar
- Brown, L. A. (1981). Innovation diffusion; a new perspective. New York: Methuen and Co. Ltd.Google Scholar
- Buhl, H. U., Röglinger, M., Moser, D. F., & Heidemann, J. (2013). Big data. Wirtschaftsinformatik, 55(2), 63--68.Google ScholarCross Ref
- Caudill, E. M., & Murphy, P. E. (2000). Consumer online privacy: Legal and ethical issues. Journal of Public Policy & Marketing, 19(1), 7--19.Google ScholarCross Ref
- Chen, H., Chiang, R. H., & Storey, V. C. (2011). Business intelligence research. MISQ Special Issue.Google Scholar
- Chen, H., Chiang, R. H., & Storey, V. C. (2012). Business intelligence and analytics: From big data to big impact. MIS Quarterly, 36(4), 1165--1188. Google ScholarDigital Library
- Chung, W., Chen, H., & Nunamaker Jr, J. F. (2005). A visual framework for knowledge discovery on the web: An empirical study of business intelligence exploration. Journal of Management Information Systems, 21(4), 57--84. Google ScholarDigital Library
- Clark, G. (1984). Innovation diffusion: Contemporary geographical approaches. Geo Books.Google Scholar
- Costa, P. R., Souza, F. F., Times, V. C., & Benevenuto, F. (2012). Towards integrating online social networks and business intelligence. Proceedings of the IADIS International Conference on Web Based Communities and Social Media (WBC'12), Lisbon, Portugal.Google Scholar
- Damanpour, F., & Schneider, M. (2006). Phases of the adoption of innovation in organisations: Effects of environment, organization and top Managers. British Journal of Management, 17(3), 215--236.Google ScholarCross Ref
- Dayal, U., Castellanos, M., Simitsis, A., & Wilkinson, K. (2009). Data integration flows for business intelligence. Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology, Lausanne, Switzerland. 1--11. Google ScholarDigital Library
- Dew, N. (2007). Abduction: A pre-condition for the intelligent design of strategy. Journal of Business Strategy, 28(4), 38--45.Google ScholarCross Ref
- Dhar, V., & Chang, E. A. (2009). Does chatter matter? The impact of user-generated content on music sales. Journal of Interactive Marketing, 23(4), 300--307.Google ScholarCross Ref
- Fereday, J., & Muir-Cochrane, E. (2006). The role of performance feedback in the self-assessment of competence: A research study with nursing clinicians. Collegian, 13(1), 10--15.Google ScholarCross Ref
- Frambach, R. T., & Schillewaert, N. (2002). Organizational innovation adoption: A multi-level framework of determinants and opportunities for future research. Journal of Business Research, 55(2), 163--176.Google ScholarCross Ref
- Fried, C. (1968). Privacy. Yale Law Journal, (77), 203--222.Google Scholar
- Ghose, A. & Panagiotos, I. (2010). The economining project at NYU: Studying the economic value of user-generated content on the internet. Journal of Revenue and Pricing Management, 8, 241--246.Google ScholarCross Ref
- Gregg, D. G., & Walczak, S. (2006). Adaptive web information extraction. Communications of the ACM, 49(5), 78--84. Google ScholarDigital Library
- Heijnen, J. (2012). Social business intelligence - how and where firms can use social media data for performance measurement, an exploratory study. (Unpublished Masters). Delft University of Technology, Holland.Google Scholar
- Howell, J. M., & Higgins, C. A. (1990). Champions of technological innovation. Administrative Science Quarterly, 35, 317--341.Google ScholarCross Ref
- Kearns, G., & Lederer, A. (2001). Strategic IT alignment: a model for competitive advantage. ICIS 2001 Proceedings, 2.Google Scholar
- Kettinger, W. J., & Lee, C. C. (2002). Understanding the IS-user divide in IT innovation. Communications of the ACM, 45(2), 79--84. Google ScholarDigital Library
- Kimberly, J. R., & de Pouvourville, G. (1993). The migration of managerial innovation: Diagnosis-related groups and health care administration in Western Europe. Jossey-Bass Publishers.Google Scholar
- Linstone, H. A., & Sahal, D. (1976). Technological substitution: Forecasting techniques and applications. Elsevier Publishing Company.Google Scholar
- Mansfield, E. (1993). The diffusion of flexible manufacturing systems in Japan, Europe and the United States. Management Science, 39(2), 149--159. Google ScholarDigital Library
- Markus, M. L. (1987). Toward a "critical mass" theory of interactive media universal access, interdependence and diffusion. Communication Research, 14(5), 491--511.Google ScholarCross Ref
- Mikroyannidis, A., & Theodoulidis, B. (2010). Ontology management and evolution for business intelligence. International Journal of Information Management, 30(6), 559--566. Google ScholarDigital Library
- 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.Google ScholarDigital Library
- Nambisan, S., & Wang, Y. (2000). Web technology adoption and knowledge barriers. Journal of Organizational Computing and Electronic Commerce, 10(2), 129--147.Google ScholarCross Ref
- Ostlund, L. E. (1974). Perceived innovation attributes as predictors of innovativeness. Journal of Consumer Research,1, 23--29.Google ScholarCross Ref
- Pajo, K., & Wallace, C. (2007). Barriers to the uptake of web-based technology by university teachers. International Journal of E-Learning & Distance Education, 16(1), 70--84.Google Scholar
- Park, B., & Song, I. (2011). Toward total business intelligence incorporating structured and unstructured data. Proceedings of the 2nd International Workshop on Business intelligencE and the WEB, 12--19. Google ScholarDigital Library
- Robinson, W. T. (1990). Product innovation and start-up business market share performance. Management Science, 36(10), 1279--1289. Google ScholarDigital Library
- Robertson, T. S., & Gatignon, H. (1986). Competitive effects on technology diffusion. The Journal of Marketing, 50(7), 1--12.Google ScholarCross Ref
- Robertson, T. S., & Wind, Y. (1980). Organizational psychographics and innovativeness. Journal of Consumer Research, 7(6), 24--31.Google ScholarCross Ref
- Rogers, E. (1995). Diffusion of innovations. New York: Free Press.Google Scholar
- Schon, D. A. (1963). Champions for radical new inventions. Harvard Business Review, 41(2), 77--86.Google Scholar
- Szulanski, G. (2000). The process of knowledge transfer: A diachronic analysis of stickiness. Organizational Behavior and Human Decision Processes, 82(1), 9--27.Google ScholarCross Ref
- Thomas, D. R. (2006). A general inductive approach for analyzing qualitative evaluation data. American Journal of Evaluation, 27(2), 237--246.Google ScholarCross Ref
- Tien, J. M. (2013). Big data: Unleashing information. Journal of Systems Science and Systems Engineering, 22(2), 127--151.Google ScholarCross Ref
- Tornatzky, L. G., & Klein, K. J. (1982). Innovation characteristics and innovation adoption-implementation: A meta-analysis of findings. Engineering Management, IEEE Transactions on, (1), 28--45.Google Scholar
- Waarts, E., Everdingen, Y. M., & Hillegersberg, J. (2002). The dynamics of factors affecting the adoption of innovations. Journal of Product Innovation Management, 19(6), 412--423.Google ScholarCross Ref
- Wang, Y. M., Wang, Y. S., & Yang, Y. F. (2010). Understanding the determinants of RFID adoption in the manufacturing industry. Technological forecasting and social change, 77(5), 803--815.Google Scholar
- Watson, H. J., & Wixom, B. H. (2007). The current state of business intelligence. Computer, 40(9), 96--99. Google ScholarDigital Library
- Weiss, P. (2003). Adoption of product and process innovations in differentiated markets: The impact of competition. Review of Industrial Organization, 23(3--4), 301--314.Google Scholar
- Zaltman, G., Duncan, R., & Holbek, J. (1973). Innovations and organizations. Wiley New York.Google Scholar
Recommendations
BI or no BI?: Presence and Future of BI in Small and Medium-sized Enterprises from South Central Bulgaria
BCI'19: Proceedings of the 9th Balkan Conference on InformaticsSmall and medium-sized enterprises represent 99% of all enterprises in the EU and in Bulgaria and generate about two thirds of gross value added. This makes small business competitiveness of utmost importance for the economies of both the Union and the ...
Data Analytics and BI Framework based on Collective Intelligence and the Industry 4.0
ICISS '19: Proceedings of the 2nd International Conference on Information Science and SystemsNow a days, business is subject to frequent changes in operations because of the continuous alignment of changes in strategies and business environment due to rapid changes in human and business resources considering the complexity of businesses. ...
Business Intelligence (BI) Success And The Role Of BI Capabilities
Business intelligence (BI) has become the top priority for many organizations who have implemented BI solutions to improve their decision-making process. Yet, not all BI initiatives have fulfilled the expectations. We suggest that one of the reasons for ...
Comments