Business intelligence and SMEs: Bridging the gap
DOI:
https://doi.org/10.37380/jisib.v7i1.216Keywords:
Business intelligence, competitive intelligence, SMEsAbstract
According to research findings, small and medium enterprises (SMEs) are facing
problems such as an excessively large volume of data, lack of information and lack of knowledge. Therefore, in order to make decisions on time, the managers of SMEs use mainly their experience, which implies a high risk of failure. Business intelligence (BI) is a useful and helpful tool, which brings many advantages and benefits to businesses. However, like any technology,
it is accompanied by some limitations that must be overcome in order to help businesses to develop. This paper summarizes current research findings addressing the issue of the development and application of business intelligence systems for SMEs. The issues addressed are models for the estimation of the readiness of a SME to establish BI tools, alternative BI solutions for SMEs, benefits and challenges of BI in SMEs, implementation methods for BI
systems in SMEs and finally, BI systems in cloud computing platforms. Research papers dealing with these issues are analyzed and the results are presented. This paper contributes to the understanding of problems and potentials regarding the development and application of BI systems in SMEs.
References
Agostino, A., Solberg Søilen, K., & Gerritsen, B.
(2013). Cloud solution in Business Intelligence
for SMEs -vendor and costumer
perspectives. Journal of Intelligence Studies in
Business, 3, 5-28.
Atre, S. (2003). The Top 10 Critical Challenges for
Business Intelligence Success. Atre Group Inc.
Bernstein, J. H. (2009). The Data-Information-
Knowledge-Wisdom Hierarchy and its
Antithesis. In Proceedings of the 2009 North
American Symposium on Knowledge
Organization, 68-75.
B
ryman, A., & Bell, E. (2011). Business Research
methods. Third Edition. Oxford University
Press Inc.
Cheng, C.H. (1997). Evaluating Naval Tactical
Missile Systems by Fuzzy AHP Based on The
Grade Value of Membership Function.
European Journal of Operational Research,
(2), 343-350. DOI: 10.1016/s0377-
(96)00026-4
Fowler, J.F. (2001). Survey Research Methods.
Third Edition. Sage Publications.
Frion, P., & Yzquierdo-Hombrecher, J. (2009).
How to implement competitive intelligence in
smes?. In Proceedings of the Third VISIO
Conference, 162-173.
Godse, M., & Mulik, S. (2009). An approach for
selecting software-as-a-service (SaaS)
product. In Cloud Computing, 2009.
CLOUD'09. IEEE International Conference
on, 155-158
Henning B, & Kemper, H.G. (2010). Business
intelligence in the cloud?. In Proceedings of
the PACIS 2010, 1528–1539.
Hidayanto, A.N., Kristianto, R., & Shihab, M.R.
(2012). Business intelligence implementation
readiness: A framework development and its
application to small medium enterprises
(SMEs). In 3rd International Research
Symposium in Service Management (IRSSM).
Kaiser, H.F., & Rice, J. (1974). Little Jiffy, Mark
IV. Educational and Psychological
Measurement, 34(1), 111–117.
Nenzhelele, T. (2014). Competitive Intelligence
Location in Small and Medium-Sized
Enterprises. Mediterranean Journal of Social
Sciences, 5(23), 608-615.
Nenzhelele, T., & Pellissier, R. (2014).
Competitive Intelligence Implementation
Challenges of Small and Medium-Sized
Enterprises. Mediterranean Journal of Social
Sciences, 5(16), 92-99.
Scholz, P., Schieder, C., Kurze, C., Gluchowski,
P., & Bohringer, M. (2010). Benefits and
Challenges of Business Intelligence Adoption
in Small and Medium-Sized Enterprises. In
Proceedings of the 18th European Conference
on Information Systems.
Sheshasaayee, A., & Swetha, M.T. (2015). The
Challenges of Business Intelligence in Cloud
Computing. Indian Journal Of Science And
Technology, 8(36).
Taylor, B. W. (2005). Introduction to Management
Science. 8th Ed. Prentice Hall.
Thompson, B., & Daniel, L.G. (1996). Factor
analytic evidence for the construct validity of
scores: A historical overview and some
guidelines. Educational and Psychological
Measurement, 56(2), 197–208.
Toms, M.L., Cummings-Hill, M.A., Curry, D.G.,
& Cone, S.M. (2001). Using cluster analysis for
deriving menu structures for automotive
mobile multimedia applications. In SAE
Technical Paper Series 2001-01-0359,
Warrendale, PA.
Tutunea, M., & Rus, R. (2012). Business
Intelligence Solutions for SME's. Procedia
Economics and Finance, 3, 865-870.
Williams, S., & Williams, N. (2004). Assessing BI
Readiness: The Key to BI ROI. Business
Intelligence Journal, 9(3), 15-23.
Yeoh, W., & Koronios, A. (2010). Critical Success
Factor for Business Intelligence Systems.
Journal of Computer Information System,
(3), 23-32.
Downloads
Published
Issue
Section
License
Authors who publish with this journal agree to the following terms:- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).