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Vol.4 No.1

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Study on Decision-Making Factors of Big Data Application in Enterprises: Using Company S as an Example

East Asian Journal of Business Economics / East Asian Journal of Business Economics, (E)2288-2766
2016, v.4 no.1, pp.5-15
https://doi.org/10.20498/eajbe.2016.4.1.5
Yun Kuei Huang (Takming University of Science and Technology)
Wen I. Yang (Takming University of Science and Technology)
Ching Sen Chan (Takming University of Science and Technology)
Yun, K. H. , Wen, I. Y. , & Ching, S. C. (2016). Study on Decision-Making Factors of Big Data Application in Enterprises: Using Company S as an Example. East Asian Journal of Business Economics, 4(1), 5-15, https://doi.org/10.20498/eajbe.2016.4.1.5

Abstract

With vigorous development of global network community, smart phones and mobile devices, enterprises can rapidly collect various kinds of data from internal and external environments. How to discover valuable information and transform it into new business opportunities from big data which grow rapidly is an extremely important issue for current enterprises. This study treats Company S as the subject and tries to find the factors of big data application in enterprises by a modified Decision Making Trial and Evaluation Laboratory (DEMATEL) and perceived benefits ─ perceived barriers relation matrix as reference for big data application and management of managers or marketing personnel in other organizations or related industry.

keywords
Informational Technology, Big Data, A Modified DEMATEL, Decision-Making Factors

Reference

1.

Biesdorf, S., Court, D., & Willmott, P. (2013). Big data: What's your plan? Mckinsey Quarterly, 2 , 40-51.

2.

Deloitte (2012). CIO Survey 2012. Retrieved February 6, 2015, Available at: http://www.deloitte.com/view/en_IE/ie/services/consulting/cio-survey-2012/index.htm.

3.

Einav, L. & Levin, J. (2013). The data revolution and economic analysis. Stanford University and NBER.

4.

. IDC iView, Retrieved November 22, 2013, Available at: http://www.emc.com/collateral/analyst-reports/idc-extracting-value-from-chaos-ar.pdf.

5.

Gartner Inc. (2012). Gartner says big data will drive $28 billion of IT spending in 2012. Retrieved February 2, 2015, Available at: http://www.gartner.com/newsroom/id/2200815

6.

Gantz, J., & Reinsel, D. (2011). Extracting Value from Chaos

7.

Ginsberg, J., Mohebbi, M., Patel, R., Brammer, L., Smolinski, M., & Brilliant, L. (2009). Detecting influenza epidemics using search engine query data. Nature, 457, 1012-1014.

8.

ISACA (2013). Big Data: Impacts and benefits. Retrieved February 20, 2015, Available at: http://www.isaca.org/Knowledge-Center/Research/ResearchDeliverables/Pages/Big-Data-Impacts-and-Benefits.aspx

9.

IBM. (2013). Watson in healthcare. Retrieved February 20, 2015, Available at:http://www-03.ibm.com/innovation/us/watson/watson_in_healthcare.shtml.

10.

Kwon, O., & Sim, J. (2013). Effects of data set features on the performances of classification algorithms. Expert Systems with Applications, 40(5), 1847-1857.

11.

Lovell, J. (2007). Left-Hand-Turn elimination. New York Times, Retrieved February 20, 2015, Available at: http://www.nytimes.com/2007/12/09/magazine/09left-handturn.html?_r=0.

12.

Lee, M.Y., Lee, A.S., & Sohn, S.Y. (2013). Behavior scoring model for coalition loyalty programs by using summary variables of transaction data. Expert Systems with Applications, 40(5), 1564-1570.

13.

McAfee, A. & Brynjolfsson, E. (2012). Big data: The management revolution. Harvard Business Review, Retrieved February 20, 2015, Available at: http://hbr.org/2012/10/big-data-the-management-revolution/ar/1.

14.

Marks, R. (2013). The big opportunity: Audience research meets big data: A report for the IPA. Research The Media Ltd. , pp. 1-36.

15.

Miele, S., & Shockley, R. (2012). Analytics: The real-world use of big data. Retrieved February 20, 2015, Available at: http://public.dhe.ibm.com/common/ssi/ecm/en/gbe03550usen/GBE03550USEN.PDF.

16.

MIC (Market Intelligence & consulting Institute, 2012). Analysis of Application Trend of Big Data and Solution. Retrieved February 20, 2015, Available at: http://mic.iii.org.tw/intelligence.

17.

Oliver, D., Evans, M., Zhou, X., Jiang, Z., & Shekhar, S. (2013). Space-Time big data: An analytics perspective. International Journal of Geographical Information Science, 0(0), 1-18.

18.

Russom, P. (2013). Managing big data. TDWI best practices Report.

19.

Olavsrud, T. (2013). 4 barriers stand between you and big data insight. CIO, Retrieved February 20, 2015, Available at:http://www.cio.com/article/731503/4_Barriers_Stand_Between_You_and_Big_Data_Insight.

20.

Scherer, M. (2012). Time: Inside the secret world of the data crunchers who helped Obama win. Retrieved February 20, 2015, Available at:http://swampland.time.com/2012/11/07/inside-the-secret-world-of-quants-and-data-crunchers-who-helped-obama-win/.

21.

Spakes, G. (2013). Four ways big data can benefit your business. SAS, Retrieved February 20, 2015, Available at: http://www.sas.com/news/feature/big-data-benefits.html.

22.

Venkatraman, A. (2013). Inadequate data centre infrastructure is a barrier to big data analytics. Computer Weekly, Retrieved February 20, 2015, Available at: http://www.computerweekly.com/news/2240186002/Inadequate-datacentre-infrastructure-is-a-barrier-to-big-data-analytics.

23.

Vesset, D., Woo, B., Morris, H., Villars, R., Little, G., Bozman, J., Borovick, L., Olofson, C., Feldman, S., Conway, S., Eastwood, M., & Yezhkova, N. (2012). Worldwide big data technology and services 2012-2015 forecast. IDC.

24.

Wu, W.W., Lan, L.W., & Lee, Y.T. (2011). Exploring decisive factors affecting anorganization's SaaS adoption: A case study. International Journal of Information Management, 31(6), 556-563.

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