EXAMINING THE SUCCESS OF DECISION MAKING IN BUSINESS INTELLIGENCE SYSTEMS
- Business Intelligence Systems, Decision Making, Success
- İş Zekâsı Sistemleri, Karar Verme, Başarı
How to Cite
The right way for organizations to achieve sustainable success is to make the right decisions. Business intelligence systems are among the leading information systems that can produce solutions in this field. In recent years, especially large-scale organizations aim to benefit from the decision-making process thanks to the good information obtained from business intelligence systems and data. Since decision making is an important step for companies, to determine the factors that affect decision making is also an important solution. So, in this study, it is aimed to determine the factors affecting decision making by evaluating the decision making success of business intelligence systems. The data obtained from the survey conducted on top level, middle level and professional users were evaluated with structural equation modeling. The data obtained from the survey conducted on top level, middle level decision makers and professional users using business intelligence systems. The data obtained from this users were evaluated with structural equation modeling. In this study, information quality, system quality, use, perceived satisfaction and decision making structures and their relations were examined. As a result of the research, it was seen that information quality, system quality and perceived satisfaction were effective on decision making, but no effect of use structure was found.
- Aggarwal, P. "The Importance of Management Information System (MIS) and Decision Support System (DSS) in Decision-Making Process." Imperial Journal of Interdisciplinary Research 2.12 (2016):243-246 http://www.imperialjournals.com/index.php/IJIR/article/view/2849/2725 Erişim Tarihi: 15.03.2018
- Agrawal, D. "The reality of real-time business intelligence." International Workshop on Business Intelligence for the Real-Time Enterprise. Springer, Berlin, Heidelberg, (2008).
- Anameriç, H. (2005).“Bilgi Merkezlerinin Yönetiminde Bilgi Sistemlerinin Rolü.“ Bilgi Dünyası, 6(1), 15-35.
- Asemi, A., Safari, A., & Zavareh, A. A. (2011). “The role of management information system (MIS) and Decision support system (DSS) for manager’s decision making process.” International Journal of Business and Management, 6(7), 164-173.
- Aurum, A., & Wohlin, C. (2003). “The fundamental nature of requirements engineering activities as a decision-making process.” Information and Software Technology, 45(14), 945-954.
- Byrne, B. M. (2016). Structural equation modeling with AMOS: Basic concepts, applications, and programming. Routledge.
- Chan, L. K., Sim, Y. W., & Yeoh, W. (2011). “A SOA-driven business intelligence architecture”. Communications of the IBIMA, 2011(216423), 1-8..
- Chaudhuri, S., Dayal, U., & Narasayya, V. (2011). “An overview of business intelligence technology.” Communications of the ACM, 54(8), 88-98.
- Chee, C. H., Yeoh, W., & Gao, S. (2011, January). “Enhancing business intelligence traceability through an integrated metadata framework.” In ACIS 2011: Proceedings of the 22nd Australasian Conference on Information Systems: Identifying the Information Systems Discipline (pp. 1-11). ACIS.
- 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.” In Symposium on Progress in Information & Communication Technology (Vol. 2, No. 4, pp. 16-30).
- Churchill Jr, G. A. (1979). “A paradigm for developing better measures of marketing constructs.” Journal of marketing research, 64-73.
- Cortina, J. M. (1993). “What is coefficient alpha? An examination of theory and applications”. Journal of applied psychology, 78(1), 98-104.
- Costello, A. B., & Osborne, J. W. (2005). “Best practices in exploratory factor analysis: Four recommendations for getting the most from your analysis.” Practical assessment, research & evaluation, 10(7), 1-9.
- Croasmun, J. T., & Ostrom, L. (2011). “Using Likert-type scales in the social sciences.” Journal of Adult Education, 40(1), 19-22.
- DeLone W. and McLean, E. (1992) “Information systems success: The quest for the independent variable”, Information Systems Success, 3, 1, 60-95.
- DeLone, W. H., &McLean, E. R. (2003). “The DeLone and McLean model of information systems success: a ten-year update.” Journal of management information systems, 19(4), 9-30.
- 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, 135-153.
- Emhan, A. (2007). “Karar Verme Süreci Ve Bu Süreçte Bilişim Sistemlerinin Kullanılması.” Elektronik Sosyal Bilimler Dergisi, 6(21), 212-224.
- Eroglu, E., Yildirim, B. F., & Özdemir, M. (2014). “Çok Kriterli Karar Vermede Oreste Yöntemi Ve Personel Seçiminde Uygulanmasi.” İstanbul Üniversitesi İşletme Fakültesi İşletme İktisadı Enstitüsü Yönetim Dergisi, 25(76).
- Field, A. (2009). “Discovering statistics using SPSS”. Sage publications.124
- Fornell, C., & Larcker, D. F. (1981). “Evaluating structural equation models with unobservable variables and measurement error”. Journal of marketing research, 39-50.
- Fuglseth, A. M., & Grønhaug, K. (2003). “Can computerised market models improve strategic decision-making? An exploratory study. “The Journal of Socio-Economics, 32(5), 503-520.
- Gaardboe, R., Nyvang, T., & Sandalgaard, N. (2017). “Business intelligence success applied to healthcare information systems.” Procedia computer science, 121, 483-490.
- Gibson, M., Arnott, D., Jagielska, I., & Melbourne, A. (2004). “Evaluating the intangible benefits of business intelligence: Review & research agenda”. In Proceedings of the 2004 IFIP International Conference on Decision Support Systems (DSS2004): Decision Support in an Uncertain and Complex World (pp. 295-305). Prato, Italy.
- Gonzales, R., Wareham, J., & Serida, J. (2015). “Measuring the impact of data warehouse and business intelligence on enterprise performance in Peru: A developing country.” Journal of Global Information Technology Management, 18(3), 162-187.
- Hair, J. F., Black Jr, W. C., Babin, B. J., & Anderson, R. E. (2010). “Multivariate Data Analysis”, Pearson PrenticeHall,USA. https://edisciplinas.usp.br/pluginfile.php/2022219/mod_folder/content/0/Multivariate%20D ata%20Analysis%207th%20Edition.%20Hair%2C%20Black%2C%20Babin%2C%20Anderson.pd f, Erişim Tarihi: 13.03.2018
- Hair J.F., J., Sarstedt, M., Hopkins, L., & G. Kuppelwieser, V. (2014). “Partial least squares structural equation modeling (PLS-SEM) An emerging tool in business research”. European Business Review, 26(2), 106-121.
- Hoe, S. L. (2008). “Issues and procedures in adopting structural equation modeling technique.” Journal of applied quantitative methods, 3(1), 76-83.
- Hooper, D., Coughlan, J., & Mullen, M. R. (2008). “Structural Equation Modelling: Guidelines for Determining Model Fit.” Electronic Journal of Business Research Methods, 6(1), 53-60.
- 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.
- Igbaria, M., & Tan, M. (1997). “The consequences of information technology acceptance on subsequent individual performance.” Information & management, 32(3), 113-121.
- Kline, R. B. (2011). Principles and Practice of Structural Equation Modeling, 3rd edn Guilford Press. New York, ftp://18.104.22.168/suzuki/PP_SEM_3e.pdf , Erişim Tarihi: 15.10.2018.
- Leidner, D. E., & Elam, J. J. (1995). “The impact of executive information systems on organizational design, intelligence, and decision making”. Organization Science, 6(6), 645-664.
- Lin, Y. H., Tsai, K. M., Shiang, W. J., Kuo, T. C., & Tsai, C. H. (2009). “Research on using ANP to establish a performance assessment model for business intelligence systems.” Expert Systems with Applications, 36(2), 4135-4146.
- Lunenburg, F. C. (2010, September). “The Decision Making Process”. In National Forum of Educational Administration & Supervision Journal (Vol. 27, No. 4).
- Mudzana, T., & Maharaj, M. (2015). “Measuring the success of business-intelligence systems in South Africa: An empirical investigation applying the DeLone and McLean Model.” South African Journal of Information Management, 17(1), 1-7.
- Muller, R.M., Linders, S., and Pires, L.F. (2010), “Business intelligence and service-oriented architecture: a Delphi study”, Information Systems Management, Vol. 27, pp. 168-187.
- Negash, S. (2004). “Business Intelligence.” Communications of the AIS, 13(1), 177-195.
- Ong, I. L., Siew, P. H., & Wong, S. F. (2011). “A five-layered business intelligence architecture.” Communications of the IBIMA, 2011, 1-11..
- Petter, S., DeLone, W., &McLean, E. (2008). “Measuring information systems success: models, dimensions, measures, and interrelationships.” European journal of information systems, 17(3), 236-263.
- Popovič, A., Hackney, R., Coelho, P. S., & Jaklič, J. (2014). “How information-sharing values influence the use of information systems: An investigation in the business intelligence systems context.” The Journal of Strategic Information Systems, 23(4), 270-283.
- Power, D. J. (2008). “Decision support systems: a historical overview.” In Handbook on Decision Support Systems 1 (pp. 121-140). Springer, Berlin, Heidelberg.
- Rai, A., Lang, S. S., & Welker, R. B. (2002). “Assessing the validity of IS success models: An empirical test and theoretical analysis.” Information systems research, 13(1), 50-69.
- Ranjan, J. (2009). “Business intelligence: Concepts, components, techniques and benefits.” Journal of Theoretical and Applied Information Technology, 9(1), 60-70.
- Roldán, J. L., & Leal, A. (2003). “A validation test of an adaptation of the DeLone and McLean’s model in the Spanish EIS field.” Critical reflections on information systems: A systemic approach, 66-84.
- Rotter, J. B. (1967). “A new scale for the measurement of interpersonal trust” 1. Journal of personality, 35(4), 651-665.
- Salmeron, J. L., & Herrero, I. (2005). “An AHP-based methodology to rank critical success factors of executive information systems.” Computer Standards & Interfaces, 28(1), 1-12.
- Sangari, M. S., & Razmi, J. (2015). “Business intelligence competence, agile capabilities, and agile performance in supply chain: An empirical study.” The International Journal of Logistics Management, 26(2), 356-380.
- Saunders, M. N. (2011). “Research methods for business students”, 5/e. Pearson Education India.
- Schermelleh-Engel, K., Moosbrugger, H., & Müller, H. (2003). “Evaluating the fit of structural equation models: Tests of significance and descriptive goodness-of-fit measures.” Methods of psychological research online, 8(2), 23-74.
- Seddon, P., & Kiew, M. Y. (1996). “A partial test and development of DeLone and McLean's model of IS success.” Australasian Journal of Information Systems, 4(1), 90-109.
- Seddon, P. B. (1997). “A respecification and extension of the DeLone and McLean model of IS success.” Information systems research, 8(3), 240-253.
- Straub, D., Boudreau, M. C., & Gefen, D. (2004). “Validation guidelines for IS positivist research.” The Communications of the Association for Information Systems, 13(1), 63.
- Tutunea, M. F., & Rus, R. V. (2012). “Business intelligence solutions for SME's.” Procedia Economics and Finance, 3, 865-870.
- Visinescu, L. L., Jones, M. C., & Sidorova, A. (2017). “Improving decision quality: the role of business intelligence.” Journal of Computer Information Systems, 57(1), 58-66.
- Wang, Y. S., & Liao, Y. W. (2008). “Assessing eGovernment systems success: A validation of the DeLone and McLean model of information systems success” Government Information Quarterly, 25(4), 717-733.
- Wang, Y. S., Wang, H. Y., & Shee, D. Y. (2007). “Measuring e-learning systems success in an organizational context: Scale development and validation.” Computers in Human Behavior, 23(4), 1792-1808.
- Watson, H. J. (2010). “BI-based Organizations.” Business Intelligence Journal, 15(2), 4-6.
- Williams, S., & Williams, N. (2010). The profit impact of business intelligence. Elsevier.
- Wixom, B. H., & Watson, H. J. (2001). “An empirical investigation of the factors affecting data warehousing success”. MIS quarterly, 17-41.
- Wu, J. H., & Wang, Y. M. (2006). “Measuring KMS success: A respecification of the DeLone and McLean's model.” Information & Management, 43(6), 728-739.
- Yang, B. (2005). “Factor analysis methods.” Research in organizations: Foundations and methods of inquiry, 181-199.