Prabandhan: Indian Journal of Management

Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Strategic Impact of Business Intelligence : A Review of Literature


Affiliations
1 Ph.D. Scholar, Amity Business School, F- 3 Block, Amity University, Sector - 125, Noida - 201 313, Uttar Pradesh, India
2 Professor, Amity Business School, F-3 Block, Amity University, Sector - 125, Noida - 201 313, Uttar Pradesh, India
3 Professor, Institute of Management Technology (IMT), Ghaziabad - 201 001, Delhi NCR, India
     

   Subscribe/Renew Journal


Review of literature is a very critical part of the research journey. The tenacity of this research was to explain a step-by-step guide to expedite understanding by presenting the critical components of the literature review process. We collected and synthesized business intelligence specific research papers from relevant journals with the help of web aggregator. This research paper discussed the strategy of analyzing 553 business intelligence research papers published from 2007-2018. We utilized exploratory research methodology to analyze the research conducted on BI solutions during the defined period. The research ripened a holistic, theoretically grounded, and relevant approach for reviewing the literature on business intelligence. It specified, defined, and positioned the existing BI solution research and helped identify the areas which need further exploration.

Keywords

Business Intelligence, Business Intelligence Solutions, Literature Review.

JEL Classification Codes : M15, O32, O33.

Paper Submission Date: January 10, 2020; Paper Sent back for Revision: February 20, 2020; Paper Acceptance Date: February 26, 2020.

User
Subscription Login to verify subscription
Notifications
Font Size

  • Aldin, L., & De Cesare, S. (2011). A literature review on business process modelling: New frontiers of reusability. Enterprise Information Systems, 5(3), 359-383. http://dx.doi.org/10.1080/17517575.2011.557443

  • Anderson, T., & Shattuck, J. (2012). Design-based research: A decade of progress in education research ? Educational Researcher, 41(1), 16-25. http://dx.doi.org/10.3102/0013189X11428813

  • Azeroual, O., & Theel, H. (2019). The effects of using business intelligence systems on an excellence management and decision-making process by start-up companies : A case study. International Journal of Management Science and Business Administration, 4(3), 30-40. http://dx.doi.org/10.18775/ijmsba.1849-5664-5419.2014.43.1004

  • Baars, H., & Kemper, H.- G. (2008). Management support with structured and unstructured data – An integrated business intelligence framework. Information Systems Management, 25(2), 132-148. http://dx.doi.org/10.1080/10580530801941058

  • Bagga, T. (2017). Accreditation compulsion or inducement: A perception study of various stakeholders. Prabandhan: Indian Journal of Management, 10(12), 7-19. http://dx.doi.org/10.17010/pijom/2017/v10i12/119977

  • Bagga, T., Bansal, S., Kumar, P., & Jain, S. (2016). New wave of accreditation in Indian higher education: Comparison of accreditation bodies for management programmes. Prabandhan: Indian Journal of Management, 9(8), 26-40. http://dx.doi.org/10.17010/pijom/2016/v9i8/99778

  • Chee,T., Chan, L.-K., Chuah, M.-H., Tan, C.-S., Wong, S.-F., & Yeoh, W. (2009). Business intelligence systems : State-of-the-art review and contemporary applications. Symposium on Progress in Information & Communication Technology. Retrieved from https://pdfs.semanticscholar.org/6572/047ad9af4143cea10849a2afda983c020860.pdf

  • Craig, I. D., Ferguson, L., & Finch, A. T. (2014). 11-Journals ranking and impact factors : How the performance of journals is measured. The Future of the Academic Journal, 2(1), 259-298. http://dx.doi.org/10.1533/9781780634647.259

  • Cronin, P., Ryan, F., & Coughlan, M. (2008). Undertaking a literature review: A step-by-step approach. British Journal of Nursing, 17(1), 38-43. http://dx.doi.org/10.12968/bjon.2008.17.1.28059

  • Dayal, U., Castellanos, M., Simitsis, A., & Wilkinson, K. (2009). Data integration flows for business intelligence. In, EDBT '09 : 12th International Conference on Extending Database Technology: Advances in Database Technology (pp. 1-11). ACM. http://dx.doi.org/10.1145/1516360.1516362

  • De Mesquita Fetzner, M., & Freitas, H. (2011). Business intelligence (BI) implementation from the perspective of individual change. Journal of Information Systems and Technology Management, 8(1), 25-50. http://dx.doi.org/10.4301/S1807-17752011000100002

  • El Mohadab, M., Bouikhalene, B., & Safi, S. (2018). Predicting rank for scientific research papers using supervised learning. Applied Computing and Informatics, 15(2), 182-190. http://dx.doi.org/10.1016/j.aci.2018.02.002

  • Elbashir, M. Z., Collier, P. A., & Davern, M. J. (2008). Measuring the effects of business intelligence systems : The relationship between business process and organizational performance. International Journal of Accounting Information Systems, 9(3), 135-153. http://dx.doi.org/10.1016/j.accinf.2008.03.001

  • Fitriana, R., Eriyatno, & Djatna, T. (2011). Progress in business intelligence system research : A literature review. International Journal of Basic & Applied Sciences, 11(3), 96-105.

  • Gantz, J., & Reinsel, D. (2012, December 29). The digital universe in 2020 : Big data, bigger digital shadows, and biggest growth in the Far East. IDC iView: IDC Analyze the Future 2007, No 2012, 1-16.

  • Ghazanfari , M., Jafari, M., & Rouhani, S. (2011). A tool to evaluate the business intelligence of enterprise systems. Scientia Iranica , 18(6), 1579-1590. http://dx.doi.org/10.1016/j.scient.2011.11.011

  • Greenhoot, A. F., & Dowsett, C. (2012). Secondary data analysis: An important tool for addressing developmental questions. Journal of Cognition and Development, 13(1), 13-18. http://dx.doi.org/10.1080/15248372.2012.646613

  • Gupta, P., Seetharaman, A., & Raj, J. R. (2013). The usage and adoption of cloud computing by small and medium businesses. International Journal of Information Management, 33(5), 861-874. http://dx.doi.org/10.1016/j.ijinfomgt.2013.07.001

  • Han, J., Kamber, M., & Pei, J. (2012). Data mining concepts and techniques (3rd ed.). Waltham, MA, USA: Morgan Kaufmann Publishers.

  • Hawking, P., & Sellitto, C. (2010). Business intelligence (BI) critical success factors. In, 21st Australasian Conference on Information Systems Proceedings (pp. 1-3). Brisbane: Association for Information Systems AIS Electronic Library (AISeL).

  • Hedgebeth, D. (2007). Data-driven decision making for the enterprise: An overview of business intelligence applications. Vine Journal of Information and Knowledge Management Systems, 37(4), 414-420. http://dx.doi.org/10.1108/03055720710838498

  • Horlach, B., Drews, P., & Schirmer, I. (2016). Bimodal IT : Business-IT alignment in the age of digital transformation. In, Multikonferenz Wirtschaftsinformatik (MKWI) (pp. 1417-1428). Publons.

  • Hou, C.-K. (2012). Examining the effect of user satisfaction on system usage and individual performance with business intelligence systems : An empirical study of Taiwan's electronics industry. International Journal of Information Management, 32(6), 560-573. http://dx.doi.org/10.1016/j.ijinfomgt.2012.03.001

  • Indulska, M., Green, P., Recker, J., & Rosemann, M. (2009). Business process modeling: Perceived benefits. In, A. H. F. Laender et al. (eds.), International Conference on Conceptual Modeling (5829, pp. 458-471). Springer. http://dx.doi.org/10.1007/978-3-642-04840-1_34

  • Ionescu, A. B., & Podaru, S. (2014). Business intelligence. A presentation of the current lead solutions and a comparative analysis of the main providers. Database Systems Journal, 5(2), 60-69.

  • Isenberg, P., Isenberg, T., Sedlmair, M., Chen, J., & Möller, T. (2014). Visualization according to research paper keywords. IEEE Conference on Visualization (VIS). Los Alamitos, United States : IEEE.

  • Işık, Ö., Jones, M. C., & Sidorova, A. (2013). Business intelligence success : The roles of BI capabilities and decision environments. Information & Management, 50(1), 13-23. http://dx.doi.org/10.1016/j.im.2012.12.001

  • Jesson, J., & Lacey, F. (2006). How to do (or not to do) a critical literature review. Pharmacy Education, 6(2), 139-148. http://dx.doi.org/10.1080/15602210600616218

  • Jourdan, Z., Rainer, R. K., & Marshall, T. E. (2008). Business intelligence: An analysis of the literature. Information Systems Management, 25(2), 121-131. http://dx.doi.org/10.1080/10580530801941512

  • Katal, A., Wazid, M., & Goudar, R. H. (2013). Big data: Issues, challenges, tools and good practices. In, 2013 Sixth International Conference on Contemporary Computing (IC3) (pp. 404-409). IEEE : Noida. http://dx.doi.org/10.1109/IC3.2013.6612229

  • Kownatzki, M., Walter, J., Floyd, S. W., & Lechner, C. (2013). Corporate control and the speed of strategic business unit decision making. Academy of Management Journal, 56(5), 1295-1324. http://dx.doi.org/10.5465/amj.2011.0804

  • Küng, P., & Hagen, C. (2007). The fruits of business process management: An experience report from a Swiss bank. Business Process Management Journal, 13(4), 477-487. http://dx.doi.org/10.1108/14637150710763522

  • Kurniawan, Y., Gunawan, A., & Kurnia, S. G. (2014). Application of business intelligence to support marketing strategies : A case study approach. Journal of Theoretical and Applied Information Technology, 64(1), 240-248.

  • López-Cózar, E., Orduna-Malea, E., & Martín-Martín, A. (2017). Google Scholar as a data source for research assessment. SocArXiv Papers. http://dx.doi.org/10.31235/osf.io/pqr53

  • Lu, R., & Sadiq, S. (2007). A survey of comparative business process modeling approaches. In, W. Abramowicz (ed.), Business Information Systems. BIS 2007. Lecture Notes in Computer Science, Vol. 4439. Berlin, Heidelberg : Springer. http://dx.doi.org/10.1007/978-3-540-72035-5_7

  • Lückmann, P., & Feldmann, C. (2017). Success factors for business process improvement projects in small and medium sized enterprises-Empirical evidence. Procedia Computer Science, 121, 439-445. http://dx.doi.org/10.1016/j.procs.2017.11.059

  • Masli, A., Richardson, V. J., Sanchez, J. M., & Smith, R. E. (2011). The business value of IT : A synthesis and framework of Archival Research. Journal of Information Systems, 25(2), 81-116. http://dx.doi.org/10.2308/isys-10117

  • McGrath, J. (1982). Dilemmatics : The study of research choices and dilemmas. In J. E. McGrath, J. Martin, & R. A. Kulka (eds.), Judgment calls in research (pp. 69-102). Newhury Park, GA: Sage.

  • Moro, S., Cortez, P., & Rita, P. (2015). Business intelligence in banking: A literature analysis from 2002 to 2013 using text mining and latent Dirichlet allocation. Expert Systems with Applications, 42(3), 1314-1324. http://dx.doi.org/10.1016/j.eswa.2014.09.024

  • Olszak, C. M., & Ziemba, E. (2007). Approach to building and implementing business intelligence systems. Interdisciplinary Journal of Information, Knowledge, and Management, 2, 135-148. http://dx.doi.org/10.28945/105

  • Olszak, C. M., & Ziemba, E. (2012). Critical success factors for implementing business intelligence systems in small and medium enterprises on the example of Upper Silesia, Poland. Interdisciplinary Journal of Information, Knowledge and Management, 7, 12-150. http://dx.doi.org/10.28945/1584

  • Oswaldo, M.-Z., Sergio , L.-M., Cáceres, C., & Schweimanns, N. (2016). Knowledge management framework using enterprise architecture and business intelligence. In, ICEIS 2016 : Proceedings of the 18th International Conference on Enterprise Information Systems (pp. 244-249). http://dx.doi.org/10.5220/0005916002440249

  • Phillips-Wren, G., Iyer, L. S., Kulkarni, U., & Ariyachandra, T. (2015). Business analytics in the context of big data : A roadmap for research. Communications of the Association for Information Systems, 37, 448-472. http://dx.doi.org/10.17705/1CAIS.03723

  • Popovič, A., Coelho, P. S., & Jaklič, J. (2009). The impact of business intelligence system maturity on information quality. Information Research, 14(4), 23-42.

  • Popovič, A., Hackney, R., Coelho, P. S., & Jaklič, J. (2012). Towards business intelligence systems success : Effects of maturity and culture on analytical decision making. Decision Support Systems, 54(1), 729-739. http://dx.doi.org/10.1016/j.dss.2012.08.017

  • Power, D. (2007, May 31, 2003). A brief history of decision support systems. Retrieved from DSSResources.com : http://dssresources.com/history/dsshistoryv28.html

  • Pratt, M. K. (2017, September 1). What is BI? Business intelligence strategies and solutions (IDG Communication). Retrieved from https://www.cio.com/article/2439504/business-intelligence/business-intelligencedefinitionand-solutions.html

  • Preko, M., & Kester, Q. A. (2015). The study of the impact of business intelligence in the banking industry of Ghana. International Journal of Emerging Research in Management & Technology, 4(8), 31-36.

  • Provost, F., & Fawcett, T. (2013). Data science and its relationship to big data and data-driven decision making. Big Data, 1(1), 51-59. http://dx.doi.org/10.1089/big.2013.1508

  • Ranjan, J. (2008). Business justification with business intelligence. VINE, 38(4), 461-475. http://dx.doi.org/10.1108/03055720810917714

  • Ranjan, J. (2009). Business intelligence: Concepts, components, techniques and benefits. Journal of Theoretical and Applied Information Technology, 9(1), 60-70.

  • Rashid Al-Azmi, A.-A. (2013). Data, text, and web mining for business intelligence : A survey. International Journal of Data Mining & Knowledge Management Process (IJDKP), 3(2), 1-21. http://dx.doi.org/10.5121/ijdkp.2013.3201

  • Rouhani , S., Ashrafi, A., Zare Ravasan, A., & Afshari , S. (2016). The impact model of business intelligence on decision support and organizational benefits. Journal of Enterprise Information Management, 29(1), 19-50. http://dx.doi.org/10.1108/JEIM-12-2014-0126

  • Rouhani, S., Asgari, S., & Mirhosseini, S. V. (2012). Review study: Business intelligence concepts and approaches. American Journal of Scientific Research, 50, 62-75.

  • Sahay, B., & Ranjan, J. (2008). Real time business intelligence in supply chain analytics. Information Management & Computer Security, 16(1), 28-48. http://dx.doi.org/10.1108/09685220810862733

  • Sangar, A. B., & Iahad, N. B. (2013). Critical factors that affect the success of business intelligence systems (BIS) implementation in an organization. International Journal of Scientific & Technology Research, 2(2), 176-180.

  • Scandura, T. A., & Williams, E. A. (2000). Research methodology in management : Current practices, trends, and implications for future research. Academy of Management Journal, 43(6), 1248-1264. http://dx.doi.org/10.2307/1556348

  • Sekaran, U., & Roger , B. (2016). Research methods for business: A skill building approach (Vol. 7). Chichester, West Sussex, United Kingdom: John Wiley & Sons.

  • Soper, D. S., & Turel, O. (2012). An n-Gram analysis of Communications 2000-2010. Communications of the ACM, 55(5), 81-87. http://dx.doi.org/10.1145/2160718.2160737

  • Sriramoju, S. B. (2017). Opportunities and security implications of big data mining. International Journal of Research in Science & Engineering, 3(6), 44-58.

  • Srivasatava, S., & Bagga, T. (2014). A comparative study on the usage of HRIS in the IT/ITES, services, and manufacturing sectors in the Indian scenario. Prabandhan: Indian Journal of Management, 7(6), 21-36. http://dx.doi.org/10.17010/pijom/2014/v7i6/59325

  • Straub, D. W. (1989). Validating instruments in MIS research. MIS Quarterly, 13(2), 147-169. http://dx.doi.org/10.2307/248922

  • Taheriyan, M. (2011). Classification of research papers based on interrelationships analysis. In, Proceedings of the 2011 Workshop on Knowledge Discovery, Modeling, and Simulation (KDMS ’11) (pp. 39 – 44). New York, NY : Association for Computing Machinery. http://dx.doi.org/10.1145/2023568.2023579

  • Tracy, R. P. (2007). IT security management and business process automation: Challenges, approaches, and rewards. Information Systems Security, 16(2), 114-122. http://dx.doi.org/10.1080/10658980601051706

  • Trkman, P. (2010). The critical success factors of business process management. International Journal of Information Management, 30(2), 125-134. http://dx.doi.org/10.1016/j.ijinfomgt.2009.07.003

  • Turban, E., Aronson, J. E., & Liang, T. P. (2005). Decision support systems and intelligent systems (Vol. 7). New Jersey, USA: Prentice-Hall, Inc.

  • Turban, E., Sharda, R., & Delen, D. (2010). Decision support and business intelligence systems. Upper Saddle River, NJ : Prentice Hall Press.

  • Vishnoi, S. K., Bagga, T., Sharma, A., & Wani, S. N. (2018). Artificial intelligence enabled marketing solutions : A review. Indian Journal of Economics & Business, 17 (4), 167-177.

  • Vishnoi, S. K., Tripathi, A., & Bagga, T. (2019). Intelligent automation, planning & implementation : A review of constraints. International Journal on Emerging Technologies, 10 (1a), 174-178.

  • Viswanath, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204. http://dx.doi.org/10.1287/mnsc.46.2.186.11926

  • Vom Brocke, J., Simons, A., Niehaves, B., Niehaves, B., Reimer, K., Plattfaut, R., & Cleven, A. (2009). Reconstructing the giant: On the importance of rigour in documenting the literature search process. In, ECIS 2009 Proceedings. 161. https://aisel.aisnet.org/ecis2009/161

  • Wang, Y., Kung, L. A., & Byrd, T. A. (2018). Big data analytics: Understanding its capabilities and potential benefits for health care organizations. Science Direct, 126, 3-13. http://dx.doi.org/10.1016/j.techfore.2015.12.019

  • Webster , J., & Watson , R. T. (2002). Analyzing the past to prepare for the future : Writing a literature review. MIS Quarterly, 26(2), 13-23.

  • Witten, I. H., & Frank, E. (2005). Data mining: Practical machine learning tools and technique. San Francisco, CA, USA: Morgan Kaufmann Publishers.

  • Zhang, H., Wang, S., Lou, J.- G., & Zhang, D. (2015). Codehow: Effective code search based on API understanding and extended boolean model (E). IEEE/ACM International Conference on IEEE (pp. 260-270). China : School of Software, Shanghai Jiao Tong University.


Abstract Views: 252

PDF Views: 0




  • Strategic Impact of Business Intelligence : A Review of Literature

Abstract Views: 252  |  PDF Views: 0

Authors

Anuj Tripathi
Ph.D. Scholar, Amity Business School, F- 3 Block, Amity University, Sector - 125, Noida - 201 313, Uttar Pradesh, India
Teena Bagga
Professor, Amity Business School, F-3 Block, Amity University, Sector - 125, Noida - 201 313, Uttar Pradesh, India
Rashmi K. Aggarwal
Professor, Institute of Management Technology (IMT), Ghaziabad - 201 001, Delhi NCR, India

Abstract


Review of literature is a very critical part of the research journey. The tenacity of this research was to explain a step-by-step guide to expedite understanding by presenting the critical components of the literature review process. We collected and synthesized business intelligence specific research papers from relevant journals with the help of web aggregator. This research paper discussed the strategy of analyzing 553 business intelligence research papers published from 2007-2018. We utilized exploratory research methodology to analyze the research conducted on BI solutions during the defined period. The research ripened a holistic, theoretically grounded, and relevant approach for reviewing the literature on business intelligence. It specified, defined, and positioned the existing BI solution research and helped identify the areas which need further exploration.

Keywords


Business Intelligence, Business Intelligence Solutions, Literature Review.

JEL Classification Codes : M15, O32, O33.

Paper Submission Date: January 10, 2020; Paper Sent back for Revision: February 20, 2020; Paper Acceptance Date: February 26, 2020.


References





DOI: https://doi.org/10.17010/pijom%2F2020%2Fv13i3%2F151175