Iranian Journal of Information Management

Proposing an educational Business Intelligence model for university by using interpretive structuring modelling (Case of study: Ferdowsi University of Mashhad)

Document Type : Original Article

Authors

1 Assistant Professor, Department of Management, Ferdowsi University of Mashhad, Mashhad, Iran

2 Software Engineering, Ferdowsi University of Mashhad, Mashhad, Iran

3 Msc. IT Management, Ferdowsi University of Mashhad, Mashhad, Iran

Abstract

Higher education institutions have a huge amount of data in student domains, curriculum and human resources that contain useful information for planning and decision making. Universities can use such information to increase their competitive advantage through Business Intelligence systems. For these reasons, the present study attempts to investigate a model for the business intelligence of universities. To achieve the desired model, after studying and reviewing the literature, the effective components on the design of the model were identified and then the elements and components of business intelligence in the university based on the opinions of the educational expert panel were extracted. The proposed model includes five sections: registration management, student support, improvement of student's academic status, improving the content of the course, improving the teaching methodology and management of the graduates. After identifying the main elements of the proposed and conceptual model for the business intelligence of the university, by using the Structural Modeling Interpretative Method, the elements of the proposed conceptual model, a hierarchical model were obtained. Based on this hierarchical model, the graduate management has a high penetration power and is at the highest level, and the development of teaching skills and improvement of the content of the courses, have high and moderate influence and affiliation, but improvement of students’ education and enrollment is high and they are at the lowest level. These levels can be used to configure the university business intelligence system along with the components of each section.
 
 

Keywords

منصوری، سعیده، و کاترین ریاضی. 1392. بررسی مدل‎های زنجیره ارزش در صنعت آموزش الکترونیکی و ارائه مدل بهینه (مطالعه موردی: یکی از دانشگاه‎های تهران). فصلنامه علمی-پژوهشی مدیریت فناوری اطلاعات. 5(3): 191-202.
ناصحی فر، وحید، و هانیه آرزمجو، و محمدتقی تقوی فرد. 1394. طراحی الگوی یکپارچه تغییرات در سازمان‌های ایرانی با استفاده از رویکرد دلفی فازی. پژوهش‌های مدیریت منابع انسانی. 7(2): 237-266.
Abramowitz S. 2000. The Knowledge Factory: dismantling the corporate university and creating true higher learning. Boston: Beacon Press.
Alzoabi, Z., F. Diko. and S. Hanna. 2011. Suggested Model for Business Intelligence in Higher Education. Business intelligence and agile methodologies for knowledge-Based organizations: Cross-Disciplinary Applications, 223-239.
Baepler, P. and C. J. Murdoch. 2010. Academic analytics and data mining in higher education. International Journal for the Scholarship of Teaching and Learning, 4(2), Article 17.
Brown, M. 2011. Learning analytics: The coming third wave. EDUCAUSE Learning Initiative Brief, 1(4), 1-4.
Campbell, J. P., P. B. DeBlois and D. G. Oblinger. 2007. Academic analytics: A new tool for a new era. EDUCAUSE review, 42(4), 41-57.
Carver A. and M. Ritacco. 2006. The Business Value of Business Intelligence. A Framework for Measuring the Benefits of Business Intelligence. Business Objects, 33.
Chen H., R. H. Chiang and V. C. Storey. 2012. Business intelligence and analytics: From big data to big impact. MIS quarterly, 36(4), 1165-1188.
Clegg S., A. Hudson and J. Steel. 2003. The Emperor's New Clothes: globalization and e-learning in Higher Education. British Journal of Sociology of Education, 24(1), 39-53.
Forest J.F. 2002. Learning organizations: Higher education institutions can work smarter too. Connection, 17(2), 31-33.
Fritz J. 2009. Using Course Activity Data to Raise Awareness of Underperforming College Students. In E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education (pp. 2586-2589). Association for the Advancement of Computing in Education (AACE).
Goodman L.A. 1961. Snowball sampling. Annual Mathematics and Statistics, 32, 148–170.
Hočevar B. and J. Jaklič.  2010. Assessing benefits of business intelligence systems–a case study. Management: Journal of Contemporary Management Issues, 15(1), 87-119.
Hutaibat K. A. 2011. Value chain for strategic management accounting in higher education. International Journal of Business and Management, 6(11), 206-218.
Išljamović S. and S. Lalić. 2014. Academic Dashboard for Tracking Students' Efficiency. In Proceeding of the XIV international symposium SYMORG 2014: New business models and sustainable competitiveness.
Johnson L., R. H. Smith, H. Willis, A. Levine and K. Haywood. 2011. The 2011 horizon report. Austin, TX: The New Media Consortium.
Ludwig, L. and S. Starr. 2005. Library as place: results of a Delphi study. Journal of the Medical Library Association, 93(3), 315-327.
Lyotrad J.F. 2004. Anamnesis: Of the Visible. Theory, Culture and Society, 21 (1), 107-119.
Olszak C. M. and E. Ziemba. 2007. Approach to building and implementing business intelligence systems. Interdisciplinary Journal of Information, Knowledge and Management, 2, 135-148.
Pathak V. and K. Pathak. 2010. Reconfiguring the higher education value chain. Management in Education, 24(4), 166-171.
Power D. J. 2007. A brief history of decision support systems. DSS Resources, World Wide Web. Available in: http://DSSResources. COM/ history/dsshistory.html, version 4.
Rathee R. and P. Rajain. 2013. Service value chain models in higher education. International Journal of Emerging Research in Management andTechnology, 2(7), 2278-9359.
Readings B. 1996. The University in Ruins. Cambridge, Massachusetts: Harvard University Press.
Schmidt R.C. 1997. Managing Delphi surveys using nonparametric statistical techniques. Decision Sciences, 28(3), 763–774.
Shamizanjani M. and Shahri S. (2014). Proposing a Model for Successful Application of Knowledge Sharing II (Social Knowledge Sharing) within Organizations, Iranian journal of Information Processing and Management, 29 (4), 903-930.
Skulmoski, G. J, F. T. Hartman, and j. Krahn. 2007. The Delphi Method for Graduate Research.. Journal of Information Technology Education  6: 1-21.
Strober, M. 2006. Habits of the Mind: Challenges for Multidisciplinary Engagement. Social Epistemology, 20 (3), 315-331.
Turban, E., J. E Aronson., T. P. Liang and R. Sharda, 2007. Decision support and business intelligence systems. Pearson Prentice Hall, New Jersey.
Warfield, J. N. 1974. Structuring complex systems, Battelle Monograph No 4, Battelle Memorial Institute. Columbus. Ohio, USA.
Iranian Journal of Information Management
Volume 3, Issue 1 - Serial Number 4
September 2017
Pages 1-30
  • Receive Date: 23 March 2017
  • Revise Date: 24 May 2017
  • Accept Date: 25 July 2017