Providing a Model for Designing Financial Decision Support System Applications in Universities

Document Type : research article

Authors

1 Department of Management and Educational Planning, Faculty of Psychology and Educational Sciences, University of Tehran

2 Department of Economics - Faculty of Humanities - Zanjan University

3 Department of Management and Educational Planning - Faculty of Psychology and Educational Sciences - University of Tehran

Abstract

One of the characteristics of the modern era is the range of Information and Communication Technology in all academic activities including financial decision-making process. One of the real instances of applying information and communication technology in financial decision making, is using financial decision support application. In this regard, the current research has been carried out to provide a model for designing financial decision-making support application in universities. Thus, in order to identify and consider the capabilities, dimensions and the major elements of financial decision support applications in universities, descriptive method is applied in this research. The present research population includes scientific and executive specialists in higher-education economics, financial decision makers in universities and information technology specialists. Findings from the analysis of opinions indicate that financial decision support application can help the decision makers effectively in all levels of decision making, especially in financial strategic decisions, optimizing the process of financial decisions, proper financial management, optimal allocation of financial resources, effective, accurate and efficient use of financial resources, abolishing human limitations in decision making, evaluating the financial burden of activities, plans and projects, prioritization, integrated approach of decision-making system, increasing efficiency, effectiveness and improvement of financial decision quality, etc. this research is also seeking for identifying the essential dimensions and elements of designing a financial decision support application in universities. To this end, the researchers have emphasized data base, data warehouse, model database, knowledge base, inference engine, analysis tools, dashboards, explanatory materials and facilities, graphic features, user interference and the users.

Keywords

References

  • آذر، عادل، خدیور، آمنه، امین ناصری، محمدرضا، و انواری، رستمی، علی­اکبر (1389). ارائه معماری نظام بودجه­ریزی بر مبنای عملکرد با رویکرد سیستم پشتیبان تصمیم هوشمند. پژوهش­های مدیریت در ایران- مدرس علوم انسانی، دوره پانزدهم، شماره 3، ص 22- 1.
  • جلائیان زعفرانی، زهرا، سیف برقی، مهدی، و زندی، فرامک (1388). طراحی یک سیستم پشتبان تصمیم­گیری (DSS) برای ارزیابی عملکرد کارکنان: مطالعه موردی در بانک توسعه صادرات ایران. پایانامه کارشناسی ارشد. رشته مدیریت فناوری اطلاعات. دانشکده فنی و مهندسی. دانشگاه الزهرا.
  • حسن­زاده، علیرضا، عسکری­مقدم، رضا، اکبری، اقدس (1392). طراحی یک نظام پشتیبان تصمیم­گیری بر اساس تخصیص منابع با رویکرد الگوریتم ژنتیک (مطالعه موردی: کتابخانه مرکزی دانشگاه تربیت مدرس. فصلنامه علمی- پژوهشی پژوهشگاه علوم و فناوری اطلاعات ایران، سال بیست­و نهم، شماره 3، ص 783-801.
  • خدیور، آمنه (1390). طراحی نظام بودجه­ریزی بر مبنای عملکرد با رویکرد سیستم پشتیبان تصمیم هوشمند. رساله دوره دکتری. رشته مدیریت، گرایش سیستم. دانشکده مدیریت و اقتصاد. دانشگاه تربیت مدرس.
  • خدیور، آمنه، پاکدامن، عزال، و مجیبیان، فاطمه (1396). طراحی سیستم پشتیبان تصمیم­گیری به منظور انتخاب پروژه­ها و خدمات فناوری اطلاعات (مطالعه موردی: شرکت توسن). مدیریت فناوری اطلاعات، دوره نهم، شماره 1، ص 38- 21.
  • رضائیان، صهبا، خرازی،کمال، جمالی، احسان، و نادری، ابوالقاسم (1398). الگوی مفهومی تصمیم­گیری با رویکرد شناختی. فصلنامه­های تازه­های علوم شناختی، سال بیست­و­یکم، شماره 1، ص 20- 1.
  • سلیمی­فرد، خداکرم، و بابایی­زاده، سلمان (1390). یک نظام پشتیبانی تصمیم برای زمان­بندی کلاس­های دانشگاه (مطالعه موردی: دانشگاه خلیج فارس). مدیریت فناوری اطلاعات، سال سوم ، شماره 7، ص 77- 92.
  • عابدی جعفری، حسن، تسلیمی، محمد سعید، فقیهی، ابوالحسن، و شیخ زاده، محمد (1390). تحلیل مضمون و شبکه مضامین: روشی ساده و کارآمد برای تبیین الگوهای موجود در داده‌های کیفی. اندیشه مدیریت راهبردی، سال پنجم، شماره 10، ص 198-151.
  • عباس­زاده، محمد (1391). تاملی بر اعتبار و پایایی در تحقیقات کیفی. فصلنامه جامعه­شناسی کاربردی، سال بیست­وسوم، شماره پیاپی (45)، ص34- 19.
  • فدایی­نژاد، محمد اسماعیل، صادقی شریف، سیدجلال، و بناییان، حمید (1391). طراحی سیستم پشتبیان تصمیم­گیری جهت مدیریت بانکی از منظر تجهیز منابع (موردپژوهی بانک کشاورزی). مدیریت فناوری اطلاعات، دوره سوم، شماره 6، ص 108- 89.
  • محجوب، حسن، نادری، ابوالقاسم، خرازی، کمال، و انتظاری، یعقوب (1396). بررسی عوامل موثر بر تصمیم­گیری­های استراتژیک مالی در دانشگاه تهران. فصلنامه علمی- پژوهشی آموزش عالی ایران، سال هشتم، شماره 2، ص 111- 81.
  • محمودی، محمد، و روحانی، سعید (1391). طراحی رویکرد انتخاب سیستم اطلاعات حسابداری مدیریت مبتنی بر پشتیبان تصمیم با استفاده از الگوریتم TOPSIS فازی. فصلنامه علمی- پژوهشی دانش حسابداری و حسابرسی مدیریت، سال اول، شماره 4، ص94- 85.
  • نادری، ابوالقاسم (1392). اقتصاد شناختی: رویکردی نوین برای تبیین تصمیم­گیری­های اقتصادی. فصلنامه علمی- پژوهشی برنامه­ریزی و بودجه، سال هیجدهم، شماره 2، ص125- 99.
  • نادری، ابوالقاسم (1397). مباحث پیشرفته در اقتصاد آموزش. تهران: انتشارات دانشگاه تهران.
  • نادری، ابوالقاسم، خرازی، کمال، انتظاری، یعقوب، و محجوب عشرت آبادی، حسن (1392). سازوکارهای تامین و تخصیص منابع در آموزش عالی. فصلنامه علمی- ترویجی مطالعات منابع انسانی، سال سوم، شماره 10 (بهار)، ص120- 91.
  • نادری، ابوالقاسم، خرازی، کمال، انتظاری، یعقوب، و محجوب عشرت­آبادی، حسن (1394). تصمیم­گیری­های استراتژیک مالی با رویکرد شناختی. فصلنامه مطالعات منابع انسانی، سال پنجم، شماره 17، ص116- 85.
  • نیکومرام، هاشم، و محمودی، محمد (1391). سنجش تاثیر نظام اطلاعات حسابداری مدیریت مبتنی بر پشتیبان تصمیم و هوش تجاری در تصمیم­گیری مدیران واحدهای اقتصادی. فصلنامه علمی- پژوهشی حسابداری مدیریت، سال پنجم، شماره 13، ص 47-65.

 

  • Aktaş, E., €Ulengin, F., & Şahin, Ş.€O. (2007). A Decision Support System to Improve the Efficiency of Resource Allocation in Healthcare Management. Socio Econ. Plan. Sci, 41(2), 130–146.
  • Anthony, R.N. (1965). Planning and Control Systems: A Framework for Analysis. Harvard University Graduate School of Business Administration, Boston.
  • Arnott, D.R. (1998). A Framework for Understanding Decision Support Systems Evolution. Melbourne: School of Information Management & Systems Monash University.
  • Arrow, K. J. (1984). The Economics of Information. Oxford: Basil Blackwell Ltd.
  • Bendoly, E. (2008). Excel Basics to Black belt. An Accelerated Guide to Decision Support Designs, Cambridge University Press.
  • Bhayat, I., Manuguerra, M., & Baldock, C. (2015). A Decision Support Model and Tool to Assist Financial Decision-Making in Universities. Higher Educ. Policy Manag, 37 (1), 69–82.
  • Bonczek, R.H., Holsapple, C.W., & Whinston, A.B. (1981). Foundations of Decision Support Systems, New York: Academic Press.
  • Brandas, C. (2007). DSS Model Based on Rules and OLAP for Management by Budgets, Account. Information System. 22, 97–103.
  • Burke E.K., McCollum, B., Meisels, A., Petrovic, S, & Qu, R. (2007). A Graph-Based Hyper-Heuristic for Educational Timetabling Problems. European Journal of Operational Research, 176, 177-192.
  • Chan, S.W.K., & Franklin, J. (2011). A Text-Based Decision Support System for Financial Sequence Prediction. Decision Support Systems, 52, 189–198.
  • Chen, T. L. (2014). Decision Support System Based on Distributed Simulation Optimization for Medical Resource Allocation in Emergency Department. HCI in Business, Springer International Publishing, Cham.
  • Choi, B., Simon, K. P., and Joseph, G. D. (2008). Effects of Knowledge Management Strategy on Organizational Performance: A Complentarity Theory-Based Approach, Omega, 36, 235-251.
  • Conlisk, J. (1996). Why Bounded Rationality. Journal of Economic Literature, XXXIV (June), 669- 700.
  • Creswell, J. (2012). Educational Research: Planning Conducting and Evaluation quantitative and qualitative Research. (4ht ed). Boston: Pearson.
  • Elton, E.J., & Gruber, M.J. (1995). Modern Portfolio Theory and Investment Analysis. 5th Edition. New York: Wiley.
  • Floyd, S.A., Turner, C.F., & Davis, K.R. (1989). Model Based Decision Support System. Compute Operations Research, 16) 5(, 481-491
  • Ghaedamini Asadabadi, R., Amerion, A., Tofighi, SH., Azizian, F., Fayazi, A., & Malmir, E., et al. (2012). Design Model Decision Support Information System (DSIS) for Field hospital. Proceedings of the 5th International Congress on Health and Crisis Management in Disaster; 2012 Jan 16-18; Tehran, Iran, [In Persian]
  • Goonatilake, S., & Treleaven, P. (1995). Intelligent Systems for Finance and Business. Wiley: New York.
  • Gorgan, V. (2015). Requirement Analysis for A Higher Education Decision Support System. Evidence from A Romanian University: 7th World Conference on Educational Sciences, Procedia - Social and Behavioral Sciences, 197, 450 – 455.
  • Gorry G.A., & Scott Morton, M.S. (1971). A Framework for Management Information Systems. Sloan Management Review, 13 (1), 55-70.
  • Graham, J., &Harvey, C. (2001). The Theory and Practice of Corporate Finance: Evidence from the Field. Journal of Financ Economic, 60.
  • Hedelin, L., & Allwood, C. M. (2002). IT and Strategic Decision Making. Journal of Industrial Management and Data System. 102(3), 125.
  • Hinkin, T.R., & Thompson, G.M. (2002). Schedule Expert: Scheduling Courses in the Cornell University School of Hotel Administration, 32)6(,45-57.
  • Huang, H. C. (2009). Designing a Knowledge-Based System for Strategic Planning: A BSC Perspective; Expert Systems with Applications. 36, 209-218.
  • V. J., & Sarukest, K. (2004). Decision Support Systems. New Delhi: Prentice Hall of India Pvt.Ltd, 6-24.
  • Johnson, R. B., & Onwuegbuzie, A. J. (2004). Mixed Methods Research Paradigm Whose Time Has Come. Educational Researcher, 33( 7), 14- 26.
  • Keen, P. G. W. (1978). Decision Support Systems: an Organizational Perspective. Reading, Mass., Addison Wesley Pub. Co. ISBN 0-201-03667.
  • Keen, P.G.W., & Scott Morton, M. S. (1987). Decision Support Systems: An Organizational Perspective. Reading, MA: Addison-Wesley.
  • King, J., & Slovic, P. (2014). The Affect Heuristic in Early Judgments of Product Innovations. Journal of Consumer Behaviour, 13(6), 411-28.
  • Klein, M. (1989). Finsim Expert; a KB/DSS for Financial Analysis and Planning. Eng. Costs Prod. 17(1–4), 359–367.
  • Kotsiantis, S., Kanellopoulos, D., & Tampakas, V. (2006). On Implementing a Financial Decision Support System. International Journal of Computer Science and Network Security, 6 (1),103- 112.
  • Kozhukhivska, O. A., Fefelov A. O., Bidyuk P. I., & Kozhukhivskyi, A. D. (2014). Decision Support System Archtecture for Forcasting of Nonstationary Fonancial Processes and Corresponding Risks. ПРОГРЕСИВНІ ІНФОРМАЦІЙНІ ТЕХНОЛОГІЇ, (1), ISSN 1607-3274, 158- 195.
  • Laitinen, E.K. (1999). Du Pont Decision Support System (DSS) for Expenditure Budgeting. J. Appl. Qual. Manag. 2(1), 75–99.
  • Larissa, T.M., & Atre, S. (2003). Business Intelligence Roadmap: The Complete Project Lifecycle for Decision-Support Applications. Addison Wesley.
  • Li, J. (2001). A Genetic Programming Based Tool for Financial Forecastin. Thesis. University of Essex. UK.
  • Lilien, G.L. et al. (2004). DSS Effectiveness in Marketing Resource Allocation Decisions: reality vs. perception, Syst. Res. 15 (3), 216–235.
  • Marakas, G. M. (1999). Decision Support Systems in The Twenty-First Century, Upper Saddle River, N.J., Prentice Hall.
  • Marek, J. D., & Roger, R. F. (2002). Decision Support System. Encyclopedia of Library and Information Science, Second Edition, Allen Kent [ed], New York: Marcel Dekker, Inc.
  • N. F. (2002). CCAS: An Intelligent Decision Support System for Credit Card Assessment. J Multicrit Decis Anal, 11(4–5), 213–235.
  • McIntosh, B.S., Jeffrey, P., Lemon, M., & Winder, N. (2005). On the Design of Computer Based Models for Integrated Environmental Science. Environmental Management, 35, 741-752.
  • Meisinger, R. (1994). College and University Budgeting: An Introduction for Faculty and Academic Administrators (2nd ed). Washington, DC: National Association of College and University Business Officers.
  • Minli, Z., Yueran, G., & Junwu, Z. (2009). Analysis of the Framework for Financial Decision Support System. International Conference on Wireless Networks and Information Systems,241- 244
  • Mintzberg, H. (2007). Tracking Strategies: Toward a General Theory. Oxford University Press.
  • Moribayashi, M., & Wu, C. Y. (1990). A Decision Support System for Capital Budgeting and Allocation. Ind. Eng.19(1–4), 524–528.
  • Mosmans, A., Praet, J. C., & Dumont, C. (2002). A Decision Support System for the Budgeting of the Belgian health care system. J. Oper. Res.139(2), 449–460.
  • Nelson, F. (1985). Decision Support Systems and Expert Systems: A Comparison. Inf Manag, 8(1), 21–26.
  • Oliver, C. D., & Twery, M. J. (1999). Decision Support Systems / Models and Analyses. In: Sexton, W.T., Malk, A.J., Szaro, R.C., Johnson, N.C. (Eds.), Ecological Stewardship - a Common Reference for Ecosystem Management, Vol. III. Elsevier, Oxford, 661-686
  • Othman, S.B., et al. (2017). An Agent-Based Decision Support System for Resources’ Scheduling in Emergency Supply Chains, Control”. Pract. 59, 27–43.
  • Ott, J., JY., & Shafritz J. (2011). Classic Readings in Organization Theory. Belmont, Calif: Wadsworth;
  • Palma-dos-Reis, A., & Zahedi, F.M. (1999). Designing Personalized Intelligent Financial Decision Support Systems. Decision Support System, 31−47.
  • Raeisi, D., &Vahedi, M. (2015). A Study on the Effects of Decision Support Systems in the Performance of Auditing System of Payam Noor University of East Azerbaijan. Journal of Novel Applied Sciences. 4(7), 820- 823.
  • Rogers, R. D., Everitt, B., Baldacchino, A., Blackshaw, A., Swainson, R., & Wynne, K., et al. (1999). Dissociable Deficits in the Decision-Making Cognition of Chronic Amphetamine Abusers, Opiate Abusers, Patients with Focal Damage to Prefrontal Cortex, and Tryptophandepleted Normal Volunteers: Evidence for Monoaminergic Mechanisms. Neuropsychopharmacology. 20(2), 322-39.
  • Ruland, C.M., & Ravn, I.H. (2001). An Information System to Improve Financial Management, Resource Allocation and Activity Planning: Evaluation Results, Study. Health Technol. Inform. 2, 1203–1206.
  • Schuff, D., Paradice, D., & Burstein, F. (2011). Decision Support System an examination the DSS discipline. New York, springer.
  • Shimizu, T., de Carvalho, M.M., & Laurindo, F.J.B. (2006). Strategic Alignment Process and Decision Support Systems: Theory and Case Studies. Idea Group Inc.
  • Simon, H. (1960). The New Science of Management Decision Making. New York: Harper & Row.
  • Simon, H. A. (1977). The New Science of Management Decision. New York: Harper Brothers.
  • Simon, H. A. (1979). Rational Decision-Making in Business Organizations. American Economic Review, 69(4), 493- 513.
  • Simon, H. A., et al. (1987). Decision Making and Problem solving. INTERFACES, 17(5), 11-31.
  • Siskos, Y., Zopounidis, C., & Pouliezos, A. (1994). An Integrated DSS for Financing Firms by an Industrial Development Bank in Greece. Decision Support System, 12(2), 151–168.
  • Spivakovska, E., Osipova, N., Vinnik, M., & Tarasich, Y. (2014). Information Competence of University Students in Ukraine: Development Status and Prospects. In: Ermolayev, V., Mayr, H.C., Nikitchenko, M., Spivakovsky, A., Zholtkevych, G. (eds.) Information and Communication Technologies in Education, Research and Industrial Applications. CCIS,469, (Springer), 194-216, Heidelberg.
  • Sprague Jr. R. H. (1980). A Framework for the Development of Decision Support Systems. MIS Quarterly, 4(4),1-26.
  • Sprague R. H., & Carlson, E. (1982). Building Effective Decision Support Systems. (Englewood Cliffs: Prentice-Hall).
  • Srinivasan, V., & Ruparel, B. (1990). CGX: An Expert Support System for Credit Granting. Euroupian Journal Operational Reseearch, 45(2–3), 293–308.
  • Stevens, J.M., & LaPlante, J.M. (1986). Factors Associated with Financial-Decision Support Systems in State Government: An Empirical Exploration. Public Administration Review,46, 522-531.
  • Stiglitz, J. E. (2002). Information and the Change in the Paradigm in Economics. American Economic Review, 92(3), 460- 501.
  • Strauss, A., & Corbin, J.M. (1998). Basics of Qualitative Research: Techniques and Procedures for Developing Grounded Theory. SAGE Publications.
  • Subramanian, V., et al. (2016). Sustainable Nanotechnology Decision Support System: Bridging Risk Management, Sustainable Innovation and Risk Governance. Nanopart. Res, 18(4), 89.
  • Susnea, E. (2013). Improving Decision Making Process in Universities: A Conceptual Model of Intelligent Decision Support System. Social and Behavioral Sciences, 76, 795 – 800.
  • Tsang, E., Yung, P., & Li, J. (2004). EDDIE-Automation, A Decision Support Tool for Financial Forecasting. Decision Support System, 37(4), 559–565.
  • Tudor, L., Popescu, M. E., & Andreica, M. (2015). A Decision Support System to Predict Financial Distress: The Case OF Romania. Romanian Journal of Economic F 170 orecasting –XVIII, (4), 170- 179
  • Turban, E. (1993). Decision Support and Expert Systems: management support systems. 3rd edn. Macmillan. New York.
  • Turban, E. (1995). Decision Support and Expert Systems: Management Support Systems. Englewood Cliffs. N.J.: Prentice Hall.
  • Turban, E. (2001). Decision Support Systems and Intelligent Systems. Prentice Hall
  • Turban, E., & Aronson, j.E. (1998). Decision Support Systems. 5th Edition, Prentice
  • Turban, , Aronson, J.E., & Liang, T.P. (2007). Decision Support Systems and Intelligent systems. Prentice Hall, Seven Edition,
  • E., & Aronson, J.E. (2005). Decision Support Systems and Intelligent Systems. 5th Ed., Prentice Hall.
  • Tyagi, , Laurence, J. Moore, Bernard W., & Taylor, III. (1988). A Decision Support System for Funds Management in a Public University. Operations Research, 36(6), 864-881. https://doi.org/10.1287/opre.36.6.864.
  • Van Der Werf, M. (2000). The Death of a Small College. The Chronicle of Higher Education,
  • Wen, W., Wang, W. K., & Wang, C. (2005). A Knowledge-Based Intelligent Decision Support System for National Defense Budget Planning. Expert Syst. Appl. 28(1), 55–66.
  • Wen, W., Wang, W.K., & Wang, C. (2005). knowledge-based intelligent decision support system for national defense budget planning”. Expert Systems with Applications, 28(1), 55-66.
  • Yada, K., & Ichikawa, K. (2011). Decision Support System for Policy Making during a Financial Crisis. IEEE International Conference on Granular Computing.
  • Yousefi Tabari, M., Memariani, A., & Ebadati, O. M. (2019). Developing a Decision Support System for Big Data Analysis and Cost Allocation in National Healthcare.
  • Zamfirescu, L., & Zamfirescu, C. B. (2013). Goal Programming as a Decision model for performance-based budgeting. Procedia Comput. Sci. 17, 426–433.
  • Zopounidis C., & Micheal, D. (2002). Multi-Criteria Decision Aid in Financial Decision Journal of Multi - Criteria Decision Analysis.
  • Zopounidis, C., Doumpos. M., & Matsatsinis, N.F. (1997). On the Use of Knowledge-Based Decision Support Systems in Financial Management: A Survey. Decision Support System, 20(3), 259–277.
Journal of Educational Planning Studies
Volume 9, Issue 17
March 2021
Pages 121-152

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  • Receive Date: 14 March 2021
  • Accept Date: 14 March 2021

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