Abstract
The decision-making process is marked by two kinds of elements: organizational and technical. The organizational elements are those related to companies’ day-to-day functioning, where decisions must be made and aligned with the companies’ strategy. The technical elements include the toolset used to aid the decision making process such as information systems, data repositories, formal modeling, and analysis of decisions. This work highlights a subset of the elements combined to define an integrated model of decision making using big data, business intelligence, decision support systems, and organizational learning all working together to provide the decision maker with a reliable visualization of the decision-related opportunities. The main objective of this work is to perform a theoretical analysis and discussion about these elements, thus providing an understanding of why and how they work together.
Keywords
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Chen, M., Mao, S., Liu, Y.: Big data: a survey. Mob. Netw. Appl. 19, 171–209 (2014)
Simon, H.A.: The New Science of Management Decision. Harper and Row, New York (1960)
Renu, R.S., Mocko, G., Koneru, A.: Use of big data and knowledge discovery to create data backbones for decision support systems. Procedia Comput. Sci. 20, 446–453 (2013)
Berman, J.J.: Principles of Big Data Prepararing, Sharing, and Analyzing Complex Information. Elsevier, Waltham (2013)
Klein, D., Tran-Gia, P., Hartmann, M.: Big data. Informatik-Spektrum 36, 319–323 (2013)
Zikopoulus, P.C., Eaton, C., deRoos, D., Deutsch, T., Lapis, G.: Understanding Big Data: Analytics for Enterprise Class Hadoop and Streaming Data. McGrow Hill, New York (2012)
Grillenberger, A., Fau, F.E.: Big data and data management: a topic for secondary computing education. In: ICER 2014 – Proceedings of the 10th Annual International Conference on International Computing Education Research, pp. 147–148 (2014)
Chang, R.M., Kauffman, R.J., Kwon, Y.: Understanding the paradigm shift to computational social science in the presence of big data. Decis. Support Syst. 63, 67–80 (2014)
Dobre, C., Xhafa, F.: Intelligent services for big data science. Futur. Gener. Comput. Syst. 37, 267–281 (2014)
Liu, S., Duffy, A.H.B., Whitfield, R.I., Boyle, I.M.: Integration of decision support systems to improve decision support performance. Knowl. Inf. Syst. 22, 261–286 (2009)
Dong, C.-S.J., Srinivasan, A.: Agent-enabled service-oriented decision support systems. Decis. Support Syst. 55, 364–373 (2013)
Daas, D., Hurkmans, T., Overbeek, S., Bouwman, H.: Developing a decision support system for business model design. Electron. Mark. 23, 251–265 (2012)
Popovič, A., Hackney, R., Coelho, P.S., Jaklič, J.: Towards business intelligence systems success: effects of maturity and culture on analytical decision making. Decis. Support Syst. 54, 729–739 (2012)
Işık, Ö., Jones, M.C., Sidorova, A.: Business intelligence success: the roles of BI capabilities and decision environments. Inf. Manag. 50, 13–23 (2013)
Handzic, M., Ozlen, K., Durmic, N.: Improving customer relationship management through business intelligence. J. Inf. Knowl. Manag. 13, 1450015-1–1450015-9 (2014)
Mohamadina, A.A., Ghazali, M.R.B., Ibrahim, M.R.B., Harbawi, M.A.: Business intelligence: concepts, issues and current systems. In: 2012 International Conference on Advanced Computer Science Applications and Technologies, pp. 234–237 (2012)
Azma, F., Mostafapour, M.A.: Business intelligence as a key strategy for development organizations. Procedia Technol. 1, 102–106 (2012)
Chang, Y.-W., Hsu, P.-Y., Shiau, W.-L.: An empirical study of managers’ usage intention in BI. Cogn. Technol. Work 16, 247–258 (2013)
Handzic, M.: Integrated socio-technical knowledge management model: an empirical evaluation. J. Knowl. Manag. 15, 198–211 (2011)
Grünwald, M., Taubner, D.: Business intelligence. Informatik-Spektrum 32, 398–403 (2009)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Poleto, T., de Carvalho, V.D.H., Costa, A.P.C.S. (2015). The Roles of Big Data in the Decision-Support Process: An Empirical Investigation. In: Delibašić, B., et al. Decision Support Systems V – Big Data Analytics for Decision Making. ICDSST 2015. Lecture Notes in Business Information Processing, vol 216. Springer, Cham. https://doi.org/10.1007/978-3-319-18533-0_2
Download citation
DOI: https://doi.org/10.1007/978-3-319-18533-0_2
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-18532-3
Online ISBN: 978-3-319-18533-0
eBook Packages: Computer ScienceComputer Science (R0)