STUDIOUS ANALYSIS OF BUSINESS INTELLIGENCE SYSTEMS IN SERBIAN ENTERPRISES

Denić, N. Marković, S. Spasić, B. Milić, M ., Identification of factors influencing growth project management ERP implementation, ANNALS OF THE ORADEA UNIVERSITY Fascicle of Management and Technological Engineering, vol.23(13)/issue 2, 2014. http://www.imtuoradea.ro/auo.fmte/.

DeLone, W., & McLean, E., The DeLone and McLean model of information system success: a ten year update, Journal of Management Information systems, vol.19 /issue 4, pp. 9–30, 2003.

Williams S., & Williams N., The Profit impact of Business Intelligence, USA, San Francisco: Morgan Kaufmann Publishers, 2007.

Olszak, C., & Ziemba, E., Business Intelligence Systems in the Holistic Infrastructure Development Supporting Decision-Making in Organizations, Interdisciplinary Journal of Information, Knowledge, and Management, vol.1/issue 1, 2006.

Wells, D., Business Analytics – Getting the Point, Beye Network, 2008. http://www.b-eye-network.com/view/7133

Turk, T., Jaklič, J., & Popovič, A., Conceptual model of business value of business intelligence systems, Management, vol.15/issue 1, pp. 5–30, 2010.

Jayanthi, R., Business intelligence: concepts, components, techniques and benefits, Journal of theoretical and Applied Information Quality, vol.9/issue 1, pp.60-70, 2009. http://www.jatit.org/volumes/research-papers/Vol9No1/9Vol9No1.pdf

Getz, A., BI insider maturity model, 2010. http://bi-insider.com/portfolio/bi- maturity-model/

Howson, C., Successful Business Intelligence: Secrets of Making BI a Killer App, USA, New York: McGraw Hill, 2008.

Barry, M., & Linoff, G., Mastering Data mining: The art of science of Customer Relationship management, USA, New York: John Wiley and Sons, 2000. 16th International Multidisciplinary Scientific GeoConference SGEM2016 www.sgem.org Informatics

Gefen, D., Straub, D., & Boudreau, M. C., Structural Equation modeling and regression: Guidelines for research practice, Communications of the Association for Information systems, vol.4/issue 7, pp. 3-67, 2000.

Ringle, C., Segmentation for path models and unobserved heterogeneity: the finite mixture partial last sqares approach, Germany, University of Hamburg, 2006. http://papers.ssrn.com/sol3/papers.cfm abstract_id=1586309

Wold, S., Eriksson, L., Trygg, J., & Kettaneh, N., The PLS model - partial last sqares projections to latent structures and its applications in industrial RDP, 2004. http://automatica.dei.unipd.it/public/Schenato/PSC/2010_2011/gruppo4Building_t ermo_identification/IdentificazioneTermodinamica20072008/Biblio/Articoli/The% 20PLS%20method%20%20partial%20least%20squares%20projections%20to%20l atent%20structures.pdf

Chin, W., Marcolin, B., & Newsted, P., A Partial Least Squares latent variable modeling: approach for measuring interaction effects: results from a monte carlo simulation study and voice mail emotion/adoption study, USA, Cleveland: Proceedings of seventeenth international conference on information systems, pp. 26-33, 1996.

Eppler, M., Managing Information Quality: Increasing the Value of Information in Knowledge – intensive Products and Processes, USA, Heidelberg: Springer, 2003.

BI maturity model research in different economies in Serbia, 2014.

Denic,N.,Stevanovic,V.,Milicevic,V.,Goran,R.“POSSIBLE BUSINESS ASPECTS OF APPLICATION OF INTELLIGENT SYSTEMS IN SMALL AND MEDIUM ENTERPRISES IN SERBIA” 15th Anniversary International Multidiscipl inary Scientific GeoConferences & EXPO - SGEM 2015, 16.06.2015 - 25.06.2015,

Wixom, B., & Todd, P., A Theoretical Integration of User Satisfaction and Technology Acceptance, Information System Research, vol.16/issue 1, pp. 85-102, 2005. 16th International Multidisciplinary Scientific GeoConference SGEM2016 www.sgem.org 16th International Multidisciplinary Scientific GeoConference SGEM 2016 16th International Multidisciplinary Scientific GeoConference SGEM2016 www.sgem.org

Denić, N. Marković, S. Spasić, B. Milić, M ., Identification of factors influencing growth project management ERP implementation, ANNALS OF THE ORADEA UNIVERSITY Fascicle of Management and Technological Engineering, vol.23(13)/issue 2, 2014. http://www.imtuoradea.ro/auo.fmte/.

DeLone, W., & McLean, E., The DeLone and McLean model of information system success: a ten year update, Journal of Management Information systems, vol.19 /issue 4, pp. 9–30, 2003.

Williams S., & Williams N., The Profit impact of Business Intelligence, USA, San Francisco: Morgan Kaufmann Publishers, 2007.

Olszak, C., & Ziemba, E., Business Intelligence Systems in the Holistic Infrastructure Development Supporting Decision-Making in Organizations, Interdisciplinary Journal of Information, Knowledge, and Management, vol.1/issue 1, 2006.

Wells, D., Business Analytics – Getting the Point, Beye Network, 2008. http://www.b-eye-network.com/view/7133

Turk, T., Jaklič, J., & Popovič, A., Conceptual model of business value of business intelligence systems, Management, vol.15/issue 1, pp. 5–30, 2010.

Jayanthi, R., Business intelligence: concepts, components, techniques and benefits, Journal of theoretical and Applied Information Quality, vol.9/issue 1, pp.60-70, 2009. http://www.jatit.org/volumes/research-papers/Vol9No1/9Vol9No1.pdf

Getz, A., BI insider maturity model, 2010. http://bi-insider.com/portfolio/bi- maturity-model/

Howson, C., Successful Business Intelligence: Secrets of Making BI a Killer App, USA, New York: McGraw Hill, 2008.

Barry, M., & Linoff, G., Mastering Data mining: The art of science of Customer Relationship management, USA, New York: John Wiley and Sons, 2000. 16th International Multidisciplinary Scientific GeoConference SGEM2016 www.sgem.org Informatics

Gefen, D., Straub, D., & Boudreau, M. C., Structural Equation modeling and regression: Guidelines for research practice, Communications of the Association for Information systems, vol.4/issue 7, pp. 3-67, 2000.

Ringle, C., Segmentation for path models and unobserved heterogeneity: the finite mixture partial last sqares approach, Germany, University of Hamburg, 2006. http://papers.ssrn.com/sol3/papers.cfm abstract_id=1586309

Wold, S., Eriksson, L., Trygg, J., & Kettaneh, N., The PLS model - partial last sqares projections to latent structures and its applications in industrial RDP, 2004. http://automatica.dei.unipd.it/public/Schenato/PSC/2010_2011/gruppo4Building_t ermo_identification/IdentificazioneTermodinamica20072008/Biblio/Articoli/The% 20PLS%20method%20%20partial%20least%20squares%20projections%20to%20l atent%20structures.pdf

Chin, W., Marcolin, B., & Newsted, P., A Partial Least Squares latent variable modeling: approach for measuring interaction effects: results from a monte carlo simulation study and voice mail emotion/adoption study, USA, Cleveland: Proceedings of seventeenth international conference on information systems, pp. 26-33, 1996.

Eppler, M., Managing Information Quality: Increasing the Value of Information in Knowledge – intensive Products and Processes, USA, Heidelberg: Springer, 2003.

BI maturity model research in different economies in Serbia, 2014.

Denic,N.,Stevanovic,V.,Milicevic,V.,Goran,R.“POSSIBLE BUSINESS ASPECTS OF APPLICATION OF INTELLIGENT SYSTEMS IN SMALL AND MEDIUM ENTERPRISES IN SERBIA” 15th Anniversary International Multidiscipl inary Scientific GeoConferences & EXPO - SGEM 2015, 16.06.2015 - 25.06.2015,

Wixom, B., & Todd, P., A Theoretical Integration of User Satisfaction and Technology Acceptance, Information System Research, vol.16/issue 1, pp. 85-102, 2005. 16th International Multidisciplinary Scientific GeoConference SGEM2016 www.sgem.org 16th International Multidisciplinary Scientific GeoConference SGEM 2016 16th International Multidisciplinary Scientific GeoConference SGEM2016 www.sgem.org