503
Views
3
CrossRef citations to date
0
Altmetric
Articles

What do we know about the big data researches? A systematic review from 2011 to 2017

ORCID Icon, &
Pages 368-393 | Received 23 Jun 2017, Accepted 04 Feb 2018, Published online: 13 Feb 2018

References

  • Abawajy, J. (2015). Comprehensive analysis of big data variety landscape. International Journal of Parallel, Emergent and Distributed Systems, 30(1), 5–14.10.1080/17445760.2014.925548
  • Abbasi, A., Sarker, S., & Chiang, R.H. (2016). Big data research in information systems: Toward an inclusive research agenda. Journal of the Association for Information Systems, 17(2), 3.
  • Agarwal, R., & Dhar, V. (2014). Editorial – Big data, data science, and analytics: The opportunity and challenge for IS research: INFORMS.
  • Al Jabri, H.A., Al-Badi, A.H., & Ali, O. (2017). Exploring the usage of big data analytical tools in telecommunication industry in Oman. Information Resources Management Journal (IRMJ), 30(1), 1–14.
  • Assunção, M.D., Calheiros, R.N., Bianchi, S., Netto, M.A., & Buyya, R. (2015). Big data computing and clouds: Trends and future directions. Journal of Parallel and Distributed Computing, 79, 3–15.10.1016/j.jpdc.2014.08.003
  • Bolón-Canedo, V., Sánchez-Maroño, N., & Alonso-Betanzos, A. (2015). Recent advances and emerging challenges of feature selection in the context of big data. Knowledge-Based Systems, 86, 33–45.10.1016/j.knosys.2015.05.014
  • Chen, M., Mao, S., & Liu, Y. (2014). Big data: A survey. Mobile Networks and Applications, 19(2), 171–209.10.1007/s11036-013-0489-0
  • Cheng, X.Q., Jin, X.L., Wang, Y.Z., Guo, J., Zhang, T., & Li, G. (2014). Survey on big data system and analytic technology. Journal of software, 25(9), 1889–1908.
  • Chen, C.P., & Zhang, C.-Y. (2014). Data-intensive applications, challenges, techniques and technologies: A survey on big data. Information Sciences, 275, 314–347.10.1016/j.ins.2014.01.015
  • Côrte-Real, N., Oliveira, T., & Ruivo, P. (2017). Assessing business value of big data analytics in European firms. Journal of Business Research, 70, 379–390.10.1016/j.jbusres.2016.08.011
  • Davenport, T.H., & Patil, D. (2012). Data scientist. Harvard business review, 90(5), 70–76.
  • Dhar, V. (2013). Data science and prediction. Communications of the ACM, 56(12), 64–73.10.1145/2534706
  • Dobre, C., & Xhafa, F. (2014). Intelligent services for big data science. Future Generation Computer Systems, 37, 267–281.10.1016/j.future.2013.07.014
  • Fadiya, S.O., Saydam, S., & Zira, V.V. (2014). Advancing big data for humanitarian needs. Procedia Engineering, 78, 88–95.10.1016/j.proeng.2014.07.043
  • Fan, S., Lau, R.Y., & Zhao, J.L. (2015). Demystifying big data analytics for business intelligence through the lens of marketing mix. Big Data Research, 2(1), 28–32.10.1016/j.bdr.2015.02.006
  • Guinea, A.S., Nain, G., & Le Traon, Y. (2016). A systematic review on the engineering of software for ubiquitous systems. Journal of Systems and Software, 118, 251–276.10.1016/j.jss.2016.05.024
  • Hagel, J. (2015). Bringing analytics to life. Journal of Accountancy, 219(2), 24.
  • Hashem, I.A.T., Yaqoob, I., Anuar, N.B., Mokhtar, S., Gani, A., & Khan, S.U. (2015). The rise of “big data” on cloud computing: Review and open research issues. Information Systems, 47, 98–115.10.1016/j.is.2014.07.006
  • Kambatla, K., Kollias, G., Kumar, V., & Grama, A. (2014). Trends in big data analytics. Journal of Parallel and Distributed Computing, 74(7), 2561–2573.10.1016/j.jpdc.2014.01.003
  • Kitchenham, B.A., Mendes, E., & Travassos, G.H. (2007). Cross versus within-company cost estimation studies: A systematic review. IEEE Transactions on Software Engineering, 33(5), 316–329.
  • Kitchin, R. (2014). Big data, new epistemologies and paradigm shifts. Big Data & Society, 1(1), 2053951714528481.
  • Kowalczyk, D.-W.-I.M., & Buxmann, P. (2014). Big data and information processing in organizational decision processes. Business & Information Systems Engineering, 6(5), 267–278.10.1007/s12599-014-0341-5
  • Kshetri, N. (2014). Big data׳ s impact on privacy, security and consumer welfare. Telecommunications Policy, 38(11), 1134–1145.10.1016/j.telpol.2014.10.002
  • Kwon, O., Lee, N., & Shin, B. (2014). Data quality management, data usage experience and acquisition intention of big data analytics. International Journal of Information Management, 34(3), 387–394.10.1016/j.ijinfomgt.2014.02.002
  • LaValle, S., Lesser, E., Shockley, R., Hopkins, M.S., & Kruschwitz, N. (2011). Big data, analytics and the path from insights to value. MIT sloan management review, 52(2), 21.
  • Maciejewski, M. (2017). To do more, better, faster and more cheaply: Using big data in public administration. International Review of Administrative Sciences, 83(1_suppl), 120–135.10.1177/0020852316640058
  • Marshall, A., Mueck, S., & Shockley, R. (2015). How leading organizations use big data and analytics to innovate. Strategy & Leadership, 43(5), 32–39.10.1108/SL-06-2015-0054
  • McAfee, A., Brynjolfsson, E., Davenport, T.H., Patil, D., & Barton, D. (2012). Big data. The management revolution. Harvard Business Review, 90(10), 61–67.
  • Murthy, D., & Bowman, S.A. (2014). Big data solutions on a small scale: Evaluating accessible high-performance computing for social research. Big Data & Society, 1(2), 2053951714559105.
  • Phillips-Wren, G., & Hoskisson, A. (2015). An analytical journey towards big data. Journal of Decision Systems, 24(1), 87–102.10.1080/12460125.2015.994333
  • Rekha, J., & Parvathi, R. (2015). Survey on software project risks and big data analytics. Procedia Computer Science, 50, 295–300.10.1016/j.procs.2015.04.045
  • Seddon, J.J., & Currie, W.L. (2017). A model for unpacking big data analytics in high-frequency trading. Journal of Business Research, 70, 300–307.10.1016/j.jbusres.2016.08.003
  • Shmueli, G., & Koppius, O.R. (2011). Predictive analytics in information systems research. MIS Quarterly, 553–572.10.2307/23042796
  • Silva, R.A., de Souza, S.R.S., & de Souza, P.S.L. (2017). A systematic review on search based mutation testing. Information and Software Technology, 81, 19–35.10.1016/j.infsof.2016.01.017
  • Sivarajah, U., Kamal, M.M., Irani, Z., & Weerakkody, V. (2017). Critical analysis of big data challenges and analytical methods. Journal of Business Research, 70, 263–286.10.1016/j.jbusres.2016.08.001
  • Steed, C.A., Ricciuto, D.M., Shipman, G., Smith, B., Thornton, P.E., Wang, D., & Williams, D.N. (2013). Big data visual analytics for exploratory earth system simulation analysis. Computers & Geosciences, 61, 71–82.10.1016/j.cageo.2013.07.025
  • Vasarhelyi, M.A., Kogan, A., & Tuttle, B.M. (2015). Big data in accounting: An overview. Accounting Horizons, 29(2), 381–396.10.2308/acch-51071
  • Wamba, S.F., Gunasekaran, A., Akter, S., Ren, S.J.-F., Dubey, R., & Childe, S.J. (2017). Big data analytics and firm performance: Effects of dynamic capabilities. Journal of Business Research, 70, 356–365.10.1016/j.jbusres.2016.08.009
  • Wang, Y., & Hajli, N. (2017). Exploring the path to big data analytics success in healthcare. Journal of Business Research, 70, 287–299.10.1016/j.jbusres.2016.08.002
  • Wang, S., & Yuan, H. (2014). Spatial data mining: A perspective of big data. International Journal of Data Warehousing and Mining (IJDWM), 10(4), 50–70.10.4018/IJDWM
  • Wang, C., Schwan, K., Talwar, V., Eisenhauer, G., Hu, L., & Wolf, M. (2011). A flexible architecture integrating monitoring and analytics for managing large-scale data centers. Paper presented at the Proceedings of the 8th ACM international conference on Autonomic computing.
  • Ward, M.J., Marsolo, K.A., & Froehle, C.M. (2014). Applications of business analytics in healthcare. Business Horizons, 57(5), 571–582.10.1016/j.bushor.2014.06.003
  • Wen, J., Li, S., Lin, Z., Hu, Y., & Huang, C. (2012). Systematic literature review of machine learning based software development effort estimation models. Information and Software Technology, 54(1), 41–59.10.1016/j.infsof.2011.09.002
  • Wu, X., Zhu, X., Wu, G.-Q., & Ding, W. (2014). Data mining with big data. IEEE transactions on knowledge and data engineering, 26(1), 97–107.
  • Xin, J., Wang, Z., Qu, L., & Wang, G. (2015). Elastic extreme learning machine for big data classification. Neurocomputing, 149, 464–471.10.1016/j.neucom.2013.09.075

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.