Business Intelligence as a Strategic Asset: Enhancing Decision Quality, Effectiveness and Performance in NGOs

Year 2025, Issue: 71, 221 - 238, 27.06.2025

Majd Aldin Abou Helal , Meral Dülger Taşkın

https://doi.org/10.26650/JECS2024-1552780

Abstract

The exponential growth of unstructured data has prompted organizations to adopt Business Intelligence (BI) tools. While BI adoption in profit-seeking sectors is well-studied, its use in non-governmental organizations (NGOs) remains underexplored. This study aims to fill this gap by investigating how BI technologies enhance decision-making quality, organizational effectiveness and performance in NGOs operating in Türkiye. Grounded in the Resource-Based View framework, the study posits that data quality is critical for BI to improve decision-making quality, ultimately leading to improved organizational outcomes. Survey data collected from 178 NGOs reveal findings consistent with the existing research in the for-profit sector. The results demonstrate that NGOs can leverage BI tools to optimize resource allocation and program implementation, align decision-making processes with their missions and goals, better serve their stakeholders, improve program outcomes, and enhance overall organizational effectiveness and performance. This study makes a significant contribution to the literature by highlighting the key role of BI technologies in the non-profit sector. Ultimately, this study underscores the transformative potential of BI technologies in improving decision-making and organizational outcomes in NGOs, offering a valuable foundation for future research and practical applications in the sector.

Keywords

Business Intelligence, Decision-Making Quality, Organizational Performance, Organizational Effectiveness, Non-Governmental Organizations

References

• Aboramadan, M., & Borgonovi, E. (2016). Strategic management practices as a key determinant of superior non-governmental organizations performance. Problems of Management in the 21st Century, 11(2), 71. https://doi.org/10.33225/pmc/16.11.71 google scholar
• Abusweilem, M. A., & Abualoush, S. (2019). The impact of knowledge management process and business intelligence on organizational performance. Management Science Letters, 9(12), 2143–2156. https://doi.org/10.5267/j.msl.2019.6.020 google scholar
• Adiguzel, Z. (2019). Strategic approach to business intelligence and its impacts on organizational performance. Handbook of Research on Strategic Fit and Design in Business Ecosystems, January, 289–310. IGI Global. https://doi.org/10.4018/978-1-7998-1125-1.ch012 google scholar
• Al Shobaki, M. J., El Talla, S. A., & Al Najjar, M. T. (2023). The Level of Business Intelligence in Non-Governmental Organizations in Palestine. International Journal of Academic Multidisciplinary Research (IJAMR), 7(6), 208-220. google scholar
• Alasiri, M. M., & Salameh, A. A. (2020). The impact of business intelligence (BI) and decision support systems (DSS): Exploratory study. International Journal of Management, 11(5), 1001–1016. https://doi.org/10.34218/IJM.11.5.2020.092 google scholar
• Arefin, M. S., Hoque, M. R., & Bao, Y. (2015). The impact of business intelligence on organization’s effectiveness: An empirical study. Journal of Systems and Information Technology, 17(3), 263–285. https://doi.org/10.1108/JSIT-09-2014-0067 google scholar
• Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99-120. https://doi.org/10.1177/014920639101700108 google scholar
• Beniger, J. (2009). The control revolution: Technological and economic origins of the information society. Harvard university press. https://doi.org/10.7312/hayo18620-037 google scholar
• Benjamin, L. M., & Misra, K. (2006). Doing good work: Implications of performance accountability for practice in the nonprofit sector. International Journal of Rural Management, 2(2), 147-162. https://doi.org/10.1177/097300520600200202 google scholar
• Brown, C. V., DeHayes, D. W., Hoffer, J. A., Martin, E. W., & Perkins, W. C. (2012). Managing information technology. Prentice Hall. google scholar
• Carman, J. G. (2007). Evaluation practice among community-based organizations: Research into the reality. American Journal of evaluation, 28(1), 60-75. https://doi.org/10.1177/1098214006296245 google scholar
• Chae, B. K., Yang, C., Olson, D., & Sheu, C. (2014). The impact of advanced analytics and data accuracy on operational performance: A contingent resource based theory (RBT) perspective. Decision Support Systems, 59, 119-126. https://doi.org/10.1016/j.dss.2013. 10.012 google scholar
• Chatfield, A. T., & Bjørn-Andersen, N. (1997). The impact of IOS-enabled business process change on business outcomes: Transformation of the value chain of Japan Airlines. Journal of Management Information Systems, 14(1), 13-40. https://doi.org/10.1080/07421222. 1997.11518152 google scholar
• Cheng,C., Zhong,H., & Cao,L. (2020). Facilitating speed of internationalization: The roles of business intelligence and organizational agility. Journal of Business Research, 110, 95–103. https://doi.org/10.1016/j.jbusres.2020.01.003 google scholar
• Clark Jr, T. D., Jones, M. C., & Armstrong, C. P. (2007). The dynamic structure of management support systems: theory development, research focus, and direction. MIS Quarterly, 579-615. https://doi.org/10.2307/25148808 google scholar
• Cosgrave, J. (1996). Decision making in emergencies. Disaster Prevention and Management: An International Journal, 5(4), 28-35. https:// doi.org/10.1108/09653569610127424 google scholar
• Daft, R. (2007). Organization Theory and Design. 9th ed. Cincinnati, OH: South-Western google scholar
• Daneshvar Kakhki, M., & Palvia, P. (2016). Effect of business intelligence and analytics on business performance. Twenty-second Americas Conference on Information Systems, San Diego, USA. google scholar
• Dubey, R., Gunasekaran, A., & Childe, S. J. (2019). Big data analytics capability in supply chain agility: The moderating effect of organizational flexibility. Management Decision, 57(8), 2092-2112. https://doi.org/10.1108/md-01-2018-0119 google scholar
• Farzaneh, M., Isaai, M. T., Arasti, M. R., & Mehralian, G. (2018). A framework for developing business intelligence systems: a knowledge perspective. Management Research Review, 41(12), 1358-1374. https://doi.org/10.1108/mrr-01-2018-0007 google scholar
• Felder, C. (2012). The potential role of business intelligence in church organizations (Doctoral dissertation, Walden University). google scholar
• Ferraris, A., Mazzoleni, A., Devalle, A., & Couturier, J. (2019). Big data analytics capabilities and knowledge management: impact on firm performance. Management Decision, 57(8), 1923-1936. https://doi.org/10.1108/md-07-2018-0825 google scholar
• Gauzelin, S., & Bentz, H. (2017). An examination of the impact of business intelligence systems on organizational decision making and performance: The case of France. Journal of Intelligence Studies in Business, 7(2), 40–50. https://doi.org/10.37380/jisib.v7i2.238 google scholar
• Giovinazzo, W. (2009). BI: Only as good as its data quality. Information Management Special Reports, 1, 2009-2. google scholar
• Guarda, T., Santos, M., Pinto, F., Augusto, M., & Silva, C. (2013). Business intelligence as a competitive advantage for SMEs. International Journal of Trade, Economics and Finance, 4(4), 187. https://doi.org/10.7763/ijtef.2013.v4.283 google scholar
• Haghighat M., &. Mayani, M. (2012). Reviewing the effect of content dimensions of organization according to BI effectiveness according to role of management—Case Study: Saman Bank. (Researcher) Management Journal, 4(27), 65-84. google scholar
• Hayles, C. S. (2010). An examination of decision making in post disaster housing reconstruction. International Journal of Disaster Resilience in the Built Environment, 1(1), 103-122. https://doi.org/10.1108/17595901011026508 google scholar
• Heyse, L. (2013). Tragic choices in humanitarian aid: a framework of organizational determinants of NGO decision making. VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations, 24, 68-92. https://doi.org/10.1007/s11266-012-9292-y google scholar
• Inmyxai, S., & Takahashi, Y. (2010). Performance Contrast and Its Determinants between Male and Female Headed Firms in Lao MSMEs. google scholar
• International Journal of Business and Management, 5(4). https://doi.org/10.5539/ijbm.v5n4p37 google scholar
• Işık, Ö., Jones, M. C., & Sidorova, A. (2013). Business intelligence success: The roles of BI capabilities and decision environments. Information and Management, 50(1), 13–23. https://doi.org/10.1016/j.im.2012.12.001 google scholar
• Janssen, M., Van Der Voort, H., & Wahyudi, A. (2017). Factors influencing big data decision-making quality. Journal of Business Research, 70, 338-345. https://doi.org/10.1016/j.jbusres.2016.08.007 google scholar
• Jess, D., & Member, C. (2019). Business intelligence systems input : effects on organizational by Sherylene Shamma Naidoo MOUSSA BERETE , DBA , Faculty Mentor and Chair WILLIAM J . McKIBBIN , PhD , Committee Member Tonia Teasley , JD , ( Interim Dean ) School of Business and Technology. March. google scholar
• Juran, J.M.; Godfrey, A.B. (1999) Juran’s Quality Handbook, 5th ed.; McGraw-Hill Companies: New York, NY, USA, google scholar
• Keller, K. L., & Staelin, R. (1987). Effects of quality and quantity of information on decision effectiveness. Journal of Consumer Research, 14(2), 200-213. https://doi.org/10.1086/209106 google scholar
• Knox Clarke, P., & Campbell, L. (2020). Decision-making at the sharp end: a survey of literature related to decision-making in humanitarian contexts. Journal of International Humanitarian Action, 5(1), 1-14. https://doi.org/10.1186/s41018-020-00068-2 google scholar
• Kruesi, M. A., & Bazelmans, L. (2023). Resources, capabilities and competencies: a review of empirical hospitality and tourism research founded on the resource-based view of the firm. Journal of Hospitality and Tourism Insights, 6(2), 549-574. https://doi.org/10. 1108/jhti-10-2021-0270 google scholar
• Kulkarni, U., Robles-Flores, J. A., & Popovič, A. (2017). Business intelligence capability: The effect of top management and the mediating roles of user participation and analytical decision making orientation. Journal of the Association for Information Systems, 18(7), 516–541. https://doi.org/10.17705/1jais.00462 google scholar
• Lange, M. (2021). Multidimensional poverty in Kolkata’s slums: towards data driven decision making in a medium-sized NGO. Journal of Poverty and Social Justice, 29(1), 121-130. https://doi.org/10.1332/175982720x16034770581665 google scholar
• Llave, M. R. (2019). A review of business intelligence and analytics in small and medium-sized enterprises. International Journal of Business Intelligence Research, 10(1), 19–41. https://doi.org/10.4018/IJBIR.2019010102 google scholar
• Llave, M. R., Hustad, E., & Olsen, D. H. (2018). Creating value from business intelligence and analytics in SMEs: Insights from experts. Americas Conference on Information Systems 2018: Digital Disruption, AMCIS 2018, January 2019. google scholar
• Mata, F. J., Fuerst, W. L., & Barney, J. B. (1995). Information technology and sustained competitive advantage: A resource-based analysis. MIS Quarterly, 487-505. https://doi.org/10.2307/249630 google scholar
• Miller, H. (1996). The multiple dimensions of information quality. Information Systems Management, 13(2), 79–82. https://doi.org/10.1080/10580539608906992 google scholar
• Mohammad, H. A. (2012). The Impact of Business Intelligence and Decision Support on the Quality of Decision Making: An Empirical Study on Five Stars Hotels in Amman Capital. Master’s Thesis, Middle East University. google scholar
• Mwai, G. (2018). Influence of Strategy Implementation on Organizational Effectiveness of Non-Governmental Organizations in Kenya (Doctoral dissertation, United States International University-Africa). google scholar
• Naidoo, S.S. (2019). Business intelligence systems input: effects on organizational decision-making. PhD. Dissertation, Capella University google scholar
• Nunnally J. C. (1978), Psychometric Theory, 2nd ed., New- York, McGraw-Hill google scholar
• Obeidat, B. Y., Abdallah, A. B., Aqqad, N. O., Akhoershiedah, A. H. O. M., & Maqableh, M. (2016). The effect of intellectual capital on organizational performance: The mediating role of knowledge sharing. Communications and Network, 9(1), 1-27. https://doi.org/ 10.4236/cn.2017.91001 google scholar
• Olaru, C. (2014). Business intelligence in telecommunications industry. International Journal of Economic Practices and Theories, 4(1), 89-100. google scholar
• Olszak, C. M. (2016). Toward Better Understanding and Use of Business Intelligence in Organizations. Information Systems Management, 33(2), 105–123. https://doi.org/10.1080/10580530.2016.1155946 google scholar
• O'Reilly, C. A. (1982). Variations in decision makers’ use of information sources: The impact of quality and accessibility of information. Academy of Management Journal, 25(4), 756-771. https://doi.org/10.5465/256097 google scholar
• Owda, R. O., Owda, M., Abed, M. N., Abdalmenem, S. A., Abu-Naser, S. S., & Al Shobaki, M. J. (2019a). The Reality of Decision Making in NGOs in Gaza Strip. International Journal of Academic Multidisciplinary Research (IJAISR), 3(8), 1-10. google scholar
• Owda, R. O., Owda, M. O., Abed, M. N., Abdalmenem, S. A., Abu-Naser, S. S., & Al Shobaki, M. J. (2019b). Design Thinking and Its Impact on Decision Making In NGOs. International Journal of Academic Multidisciplinary Research (IJAMR), 3(7): 41-52. google scholar
• 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. https://doi.org/10.1016/j.dss.2012.08.017 google scholar
• Popovič, A., Puklavec, B., & Oliveira, T. (2019). Justifying business intelligence systems adoption in SMEs: Impact of systems use on firm performance. Industrial Management and Data Systems, 119(1), 210–228. https://doi.org/10.1108/IMDS-02-2018-0085 google scholar
• Power, D. J., & Sharda, R. (2007). Model-driven decision support systems: Concepts and research directions. Decision Support Systems, 43(3), 1044–1061. https://doi.org/10.1016/j.dss.2005.05.030 google scholar
• Pranjić, G. (2018). Decision Making Process in the Business Intelligence 3.0 Context. Ekonomska Misao i Praksa, 2, 603–619. google scholar
• Raghunathan, S. (1999). Impact of information quality and decision-maker quality on decision quality: a theoretical model and simulation analysis. Decision Support Systems, 26(4), 275-286. https://doi.org/10.1016/s0167-9236(99)00060-3 google scholar
• Redman, T. C. (1998). The impact of poor data quality on the typical enterprise. Communications of the ACM, 41(2), 79-82. https://doi. org/10.1145/269012.269025 google scholar
• Kelidbari, H. R. R., & Rayat, M. (2017). The Effects of Business Intelligence on the Effectiveness of the Organization (Case Study: Airline Companies in Iran). Review of European Studies, 9(3), 176. https://doi.org/10.5539/res.v9n3p176 google scholar
• Ross, J. W., Beath, C. M., & Goodhue, D. L. (1996). Develop long-term competitiveness through IT assets. MIT Sloan Management Review, 38(1), 31-42. google scholar
• Sabanovic, A. (2008). Business Intelligence Software Customers’ Understanding, Expectations and Needs. University of Kristianstad. Thesis for the Master’s Degree in Business Administration. google scholar
• Sanz de Acedo Lizarraga, M. L., Sanz de Acedo Baquedano, M. T., Soria Oliver, M., & Closas, A. (2009). Development and validation of a decision-making questionnaire. British Journal of Guidance & Counselling, 37(3), 357-373. https://doi.org/10.1080/03069880902956959 google scholar
• Saucedo-Martínez, J. A., Pérez-Lara, M., Marmolejo-Saucedo, J. A., Salais-Fierro, T. E., & Vasant, P. (2018). Industry 4.0 framework for management and operations: a review. Journal of Ambient Intelligence and Humanized Computing, 9, 789-801. google scholar
• Scholtz, B., Calitz, A., & Haupt, R. (2018). A business intelligence framework for sustainability information management in higher education. International Journal of Sustainability in Higher Education, 19(2), 266-290. https://doi.org/10.1108/ijshe-06-2016-0118 google scholar
• Schulze, W.S. (1992). The two Resource-Based Models of the firm: Definitions and implications for research. Academy of Management Best Papers Proceedings, 37-41. https://doi.org/10.5465/ambpp.1992.4976714 google scholar
• Sharda, R., Delen, D., & Turban, E. (2014). Business intelligence and analytics: systems for decision support. Pearson. google scholar
• Shollo, A. D. (2013). The Role of Business Intelligence in Organizational Decision-making. PhD Thesis, Copenhagen Business School. google scholar
• Solberg Søilen, K. (2015). A place for intelligence studies as a scientific discipline. Journal of Intelligence Studies in Business, 5(3), 35-46. https://doi.org/10.37380/jisib.v5i3.136 google scholar
• Soltani, Z. K., & Siadati, S. (2019). The impact of business intelligence on increasing the efficiency and health quality of surgical centers. Journal of Economic and Social Research, 18(5), 895–904. google scholar
• Sorensen, C. (2020). Business Intelligence vs. Business Analytics. Retrived from https://us.hitachi-solutions.com/blog/business-intelligence-vs-business-analytics/ google scholar
• Sousa, M. J., & Dias, I. (2020). Business intelligence for human capital management. International Journal of Business Intelligence Research, 11(1), 38–49. https://doi.org/10.4018/IJBIR.2020010103 google scholar
• Southekal, P. (2023). Data Quality: Empowering Businesses with Analytics and AI. John Wiley & Sons. google scholar
• Strong, D. M., Lee, Y. W., & Wang, R. Y. (1997). Data quality in context. Communications of the ACM, 40(5), 103–110. google scholar
• Tayi, G. K., & Ballou, D. P. (1998). Examining data quality. Communications of the ACM, 41(2), 54-57. https://doi.org/10.1145/269012.269021 google scholar
• Teegen, H., Doh, J. P., & Vachani, S. (2004). The importance of nongovernmental organizations (NGOs) in global governance and value creation: An international business research agenda. Journal of International Business Studies, 35, 463-483. https://doi.org/10. 1057/palgrave.jibs.8400112 google scholar
• Teoh, A. P., Rajendran, M., & Lim, E. K. (2014). Predictors and Outcome of Business Intelligence System Implementation: A Perspective of Manufacturers in Malaysia. Research Journal of Applied Sciences, Engineering and Technology, 8(18), 1980-1993. https://doi.org/ 10.19026/rjaset.8.1190 google scholar
• Torres, R., Sidorova, A., & Jones, M. C. (2018). Enabling firm performance through business intelligence and analytics: A dynamic capabilities perspective. Information and Management, 55(7), 822–839. https://doi.org/10.1016/j.im.2018.03.010 google scholar
• Turban, E., Sharda, R., Aronson, J. E., & King, D. (2008). Business intelligence: A managerial approach (pp. 58-59). Upper Saddle River, NJ: Pearson Prentice Hall. google scholar
• 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. https://doi.org/10.1080/08874417.2016.1181494 google scholar
• Vukovic, N. (2020). Aligning BI with Corporate Strategy in SME: A case study based on the BISC Framework. Master’s Thesis. Uppsala University google scholar
• Wamba, S. F., Akter, S., Edwards, A., Chopin, G., & Gnanzou, D. (2015). How ‘big data’ can make big impact: Findings from a systematic review and a longitudinal case study. International Journal of Production Economics, 165, 234-246. https://doi.org/10.1016/j.ijpe. 2014.12.031 google scholar
• Wamba, S. F., Gunasekaran, A., Akter, S., Ren, S. J. F., Dubey, R., & Childe, S. J. (2017). Big data analytics and firm performance: Effects of dynamic capabilities. Journal of Business Research, 70, 356-365. https://doi.org/10.1016/j.jbusres.2016.08.009 google scholar
• Wang, R. Y., & Strong, D. M. (1996). Beyond accuracy: What data quality means to data consumers. Journal of Management Information Systems, 12(4), 5-33. https://doi.org/10.1080/07421222.1996.11518099 google scholar
• Warth, J., Kaiser, G., & Kügler, M. (2011). The impact of data quality and analytical capabilities on planning performance: insights from the automotive industry. Proceedings of the 10th International Conference on Wirtschaftsinformatik, WI 2.011, Volume 1, 322-331. google scholar
• Wixom, B., & Watson, H. (2010). The BI-based organization. International Journal of Business Intelligence Research (IJBIR), 1(1), 13-28. https://doi.org/10.4018/978-1-4666-0279-3.ch014 google scholar
• Watts, S., Shankaranarayanan, G., & Even, A. (2009). Data quality assessment in context: A cognitive perspective. Decision Support Systems, 48(1), 202-211. https://doi.org/10.1016/j.dss.2009.07.012 google scholar
• Wieder, B., & Ossimitz, M. L. (2015). The impact of Business Intelligence on the quality of decision making–a mediation model. Procedia Computer Science, 64, 1163-1171. https://doi.org/10.1016/j.procs.2015.08.599 google scholar
• Wieder, B., Ossimitz, M., & Chamoni, P. (2012). The impact of business intelligence tools on performance: a user satisfaction paradox?. International Journal of Economic Sciences and Applied Research, 5(3), 7-32. google scholar
• Yeoh, W., & Popovič, A. (2016). Extending the understanding of critical success factors for implementing business intelligence systems. Journal of the Association for Information Science and Technology, 67(1), 134–147. https://doi.org/10.1002/asi.23366 google scholar
• Yu, L. and Lai, K. K. (2011). A distance-based group decision-making methodology for multi-person multi-criteria emergency decision support. Decision Support Systems, 51(2), 307-315. https://doi.org/10.1016/j.dss.2010.11.024 google scholar