Relationship between Business Intelligence Components and Financial Reporting Quality in Firms

Document Type : Original Manuscript


1 Director of the Masters╩╣ Department, Kherad institute of Higher education, Bushehr. Iran.

2 Department of Accounting, Firoozabad Branch, Islamic Azad University, Fars. Iran.

3 Department of Industrial Management, Persian Gulf University, Bushehr, Iran.


The purpose of this research studies the impact of business intelligence on the financial reporting quality of listed companies in the Tehran Stock Exchange using structural equation modeling. The instruments of this research were the business Intelligence Questionnaire (Provich, 2012) and the financial statements of listed companies in The Tehran Stock Exchange to study of the financial reporting quality. For this purpose, the data of 182 listed companies in the Tehran Stock Exchange in 2018 was collected and processed. To analyze the data, Partial Least Squares Method and PLS-3 software were used. The findings of the research showed that each of the components of business intelligence including data integrity, analytical capabilities, information content quality, information access quality, use of information in business process, and Analytical decision - making culture has a positive and significant effect on the financial reporting quality

Graphical Abstract

Relationship between Business Intelligence Components and Financial Reporting Quality in Firms


  • Application of business intelligence in financial matters
  •  Interdisciplinary research in the field of activities of Iranian companies
  •  Retrieved from Ph.D.
  •  Used by many natural persons including managers, accountants, and legal entities such as manufacturing industries and business units


Ahmad Khan, R., & Quadri, S.M. K. (2012), Business intelligence: an integrated approach, Business Intelligence Journal, 5(1), pp. 64-70.
Alpar, P., Engler, T., & Michael, S. (2015). Influence of social software features on the reuse of Business Intelligence reports, Journal of Information Processing and Management, 51 (3), PP. 235-251.
 Cronbach, L. (1951). Coefficient Alpha and the Internal Structure of Tests. Psychometrical, 16(3), PP. 297-334.
Davari, A., & Rezazadeh, A. (2013). Structural equation modeling with PLS software. Tehran University: Jihad Publishing Organization, p. 248.
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), PP. 135-153. 
Fornell, C., & Larcker, D. (1981). Structural Equation Models with UnobservableVariables and Measurement Error. Journal of Marketing Research, 18(1), PP. 39-50.  
Francis, j., Olsson, P., & Schipper, K. (2006). Foundation and Trends in Accounting,Journal of Earnings Quality, 4 (1), PP. 259–340.
Ghazanfari, M., Jalali,A.A., Rouhani, S., & Jafari, M. (2009). Evaluation of Business Intelligence (BI) in Organizational Human Resource Planning Systems (ERP), Case Study of Iran Trade Development Organization, Conference on Organizational Resource Planning Systems, Iran, Tehran.
Ghoshal, S., & Kim, S. K. (1986). Building effective intelligence systems for competitive advantage, Journal ofSloan Management Review,28(1), PP. 49-58.
Habul. A. (2010). Business Intelligence and Customer Relationship Management, ITI.  32nd Int. Conf. on Information Technology Interfaces, 21-24 June 2010, ISBN:  978-1-4244-5732-8.
Homocianu, D,. & Dinu, A. (2018). Business Intelligence facilities with applications in audit and financial reporting. SSRN Electronic Journal, September 2018.  
Hou,C. K., & Papamichail, K. N. (2010). the impact of integrating enterprise resource planning systems with business intelligence systems on decision-making performance: An empirical study of the semiconductor industry International, Journal of Technology, Policy and Management, 10(3), PP. 201–226.
Hulland, J. (1999). Use of partial least squares (PLS) in strategic management research: A review of four recent studies, Strategic Management Journal, 20(2), PP. 195-204.
Jones, J. J. (1991). Earnings management during import relief investigation. Journal of Accounting Research, 29(2), pp. 193–228.
Kothari, S.P., Leone, A.J., & Wasley, C.E. (2005) Performance Matched Discretionary Accrual Measures. Journal of Accounting and Economics, 39(1), PP. 163-197.      
Levitt, A. (1998).The Importance of High-Quality Accounting Standards, Journal of Accounting Horizons, 12(1), PP. 79-82.
Lin, Y. H., Kune-Muh, T., Wei-Jung, S., Tsai-Chi, K., & Chih-Hung, T. (2009). Research on using ANP to establish a performance assessment model for business intelligence systems, Journal of Expert Systems with Applications, 36(2), PP. 135–146.
Luhn, H. (1958). A Business Intelligence System, IBM Journal 2(4), PP. 314-319.
Mwilu, O.S., C.W. Isabelle, and P. Nicolas. (2015). Design science research contribution to business intelligence in the cloud-A systematic literature review, Journal of Future Generation Computer Systems, 63(4), PP. 108-122.
Nunnally, J.)1978(.Psychometric theory. New York, NY: McGraw-Hill.
Olivera, M. (2009). Looking Beyond Technology: A Framework for Business Intelligence and Business Process Management Integration. 22nd Bled Conference, 14 – 17 June 2009. Bled, Slovenia.
Olson, D. L. (2004). Managerial issues of Resource Planning systems. Mac Graw–Hill, Inc. New York, NY, USA. PP. 46-51.
Pall, R., & Yigitbasioglu, O. (2018). Business intelligence and analytics in management accounting research: Status and future focus, International Journal of Accounting Information Systems, 29(3), PP. 37-58.
Petrini, M., & Pozzebon, M. (2008). What Role is "Business Intelligence" Playing in Developing Countries? Data mining applications for empowering knowledge societies, P. 241.
Popovi, A., Hackney, R., Coelho, P.S., & Jakli, J. (2012). Towards business Intelligence systems success: Effects of maturity and culture on analytical decision making, Journal of Decision Support Systems 54(1), PP. 729-739.
Popovic, A., Coelho, P.S., & Jaklic, J. (2009). The impact of business intelligence system maturity on information quality, Information Research, 14(4), P 417.
Razzazi Borujeni, H., & Kahid Basiri, M. (2015). Investigating the Impact of Using Business Intelligence on the Success of the Insurance Industry, InternationaL Conference on Information and Communication Technology, Tehran.
Rouhani, S., & Zare Ravasan, A. (2012). Business Intelligence Assessment Model in Organizational Systems, Quarterly Journal of Information Technology Management Studies. 1 (2), 105-121.
Simoes, P., Coelho, P., & Jurij, J. (2010). the Role of Business knowledge in improving information quality provided by business Intelligence systems, conference paper in communications in computer and information science, October 2010.
Turban, E., Ramesh, S., & Delen, D. (2011). Decision support and business intelligence systems, Prentice Hall, Inc. The University of Hawaii. pp.  2-11.
Verdi, R.S. (2006).Financial Reporting Quality and Efficiency.Working Paper. The University of Pennsylvania.  
Wang, C. H. (2016). A novel approach to conduct the importance-satisfaction analysis for acquiring typical user groups in business-intelligence systems, Journal of Computers in Human Behavior 54(1), PP. 673-681.
Wieder, B. Ossimitz, M. L. (2015). The impact of Business Intelligence on the quality of decision- making – a mediation Model. Available online at