ÜNİVERSİTELERDE BİLGİ SİSTEMİ SEÇİM KRİTERLERİNİN SWARA YÖNTEMİ İLE AĞIRLIKLANDIRILMASI: AMPİRİK BİR ÇALIŞMA

Yıl 2018, Cilt: 6 Sayı: 1, 59 - 85, 20.04.2018

Büşra Kutlu Karabıyık , Mehmet Erdemir Gündoğmuş

https://doi.org/10.22139/jobs.379695

Cited By: 3

Öz

Amaç: Bu çalışmada üniversitelerde
satın alınması ve kullanılması planlanan bilgi sistemleri alternatifleri
arasından en iyisinin seçilmesi için çeşitli seçim kriterlerinin önem
derecelerine göre ağırlıklandırılmaları amaçlanmaktadır.

Yöntem: Değerlendirme kriterlerinin
ağırlıklandırılmaları için Adım Adım Ağırlık Değerlendirme Oran Analizi (SWARA)
yöntemi kullanılmıştır.

Bulgular: Üniversitelerin beklentilerini karşılayan bilgi
sisteminin seçimi için kullanılan kriterler arasında en yüksek önem derecesine
sahip kriterin “Memnuniyet” kriteri olduğu ve en düşük öneme sahip kriterin ise
“Bilgi Süreçleri” olduğu sonucuna ulaşılmıştır. “Fonksiyonellik” ve
“Maliyet”  sırasıyla ikinci ve üçüncü
öneme sahip kriterler olarak bulunmuştur.

Sonuç: Üniversitelerde haberleşme, bilgi
üretme, bilgiyi paylaşma, işbirliği yapma vb. gibi hayati önem taşıyan
süreçleri kolaylaştıran bilgi sistemlerinin seçim süreci yönetilirken göz önüne
alınması gereken hususlar hiyerarşik sıraya göre aydınlatılmıştır.

Anahtar Kelimeler

Üniversite Bilgi Sistemleri, SWARA, Çok Kriterli Karar Verme

WEIGHTING UNIVERSITY INFORMATION SYSTEM SELECTION CRITERIA BY SWARA METHOD: AN EMPIRICAL STUDY

Öz

Aim: It is aimed to weight various information system selection
criteria according to their importance levels in order to select the best one among
the alternatives which is planned to be purchased and used by universities.

Method: The Step-by-Step Weighted Ratio Analysis (SWARA) method was
used to weight the evaluation criteria.

Findings: It was concluded that the criterion with the highest
degree of importance is the "Satisfaction" and the lowest criterion
is the "Information Processes" among the criteria used for selecting
the information system that meets the expectations of the universities.
"Functionality" and "Cost" were found to have the second
and third important criteria respectively.

Results: Aspects that must be considered while managing selection
process of information systems that facilitates some vital process in
universities such as communication, information generation, sharing of
information, cooperation, etc. were highlighted in a hierarchical order.

Anahtar Kelimeler

University Information Systems, SWARA, Multi-Criteria Decision Making

Kaynakça

• Abu-sarhan, Z. (2011). Application Of Analytic Hierarchy Process ( AHP ) In The Evaluation and Selection Of an Information System Reengineering Projects. International Journal of Computer Science and Network Security, 11(1), 172–177.
• Aghdaie, M. H., Zolfani, S. H., & Zavadskas, E. K. (2014). Synergies of data mining and multiple attribute decision making. Procedia-Social and Behavioral Sciences, 110, 767-776.
• Aghdaie, M. H., Zolfani, S. H., & Zavadskas, E. K. (2014). Synergies of data mining and multiple attribute decision making. Procedia-Social and Behavioral Sciences, 110, 767-776.
• Argote, L., & Ingram, P. (2000). Knowledge Transfer: A Basis for Competitive Advantage in Firms. Organizational Behavior and Human Decision Processes, 82(1), 150–169. http://doi.org/10.1006/obhd.2000.2893
• Alimardani, M., Hashemkhani Zolfani, S., Aghdaie, M. H., & Tamošaitienė, J. (2013). A novel hybrid SWARA and VIKOR methodology for supplier selection in an agile environment. Technological and Economic Development of Economy, 19(3), 533-548.
• Ayyıldız, E., & Demirci, E. (2018). Türkiye’de Yer Alan Şehirlerin Yaşam Kalitelerinin SWARA Entegreli TOPSIS Yöntemi ile Belirlenmesi. Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi.30. 67-87.
• Chang Lee, K., Lee, S., & Kang, I. (2005). KMPI: measuring knowledge management performance. Information & Management. http://doi.org/10.1016/j.im.2004.02.003
• Çakır, E., & Akel, G. (2017). EVALUATION OF SERVICE QUALITY OF HOTEL AND HOLIDAY RESERVATION WEB SITES IN TURKEY BY INTEGRATED SWARA-GRAY RELATIONSHIP ANALYSIS METHOD. PressAcademia Procedia, 3(1), 81-95.
• ÇAKIR, E. (2017). Kriter Ağırlıklarının SWARA–Copeland Yöntemi ile Belirlenmesi: Bir Üretim İşletmesinde Uygulama. Adnan Menderes Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 4(3), 42-56
• ÇAKIR, E., & KARABIYIK, B. K. (2017). Bütünleşik SWARA-COPRAS Yöntemi Kullanarak Bulut Depolama Hizmet Sağlayıcılarının Değerlendirilmesi. Bilişim Teknolojileri Dergisi, 10(4), 417-434.
• Darr, E. D., & Kurtzberg, T. R. (2000). An Investigation of Partner Similarity Dimensions on Knowledge Transfer. Organizational Behavior and Human Decision Processes, 82(1), 28–44. http://doi.org/10.1006/obhd.2000.2885
• Dehnavi, A., Aghdam, I. N., Pradhan, B., & Varzandeh, M. H. M. (2015). A new hybrid model using step-wise weight assessment ratio analysis (SWARA) technique and adaptive neuro-fuzzy inference system (ANFIS) for regional landslide hazard assessment in Iran. Catena, 135, 122-148.
• Droege, S. B., & Hoobler, J. M. (2003). Employee Turnover And Tacit Knowledge Diffusion: A Network Perspective. JOURNAL OF MANAGERIAL ISSUS, 15(1), 50–64. Erdem, İ. (2013). Yöneylem Araştırması ve WinQSB Uygulamaları. Ankara: Seçkin Yayıncılık.
• Ernst, D., & Kim, L. (2002). Global production networks, knowledge diffusion, and local capability formation. Research Policy, 31(8–9), 1417–1429. http://doi.org/10.1016/S0048-7333(02)00072-0
• Fasanghari, M., & Roudsari, F. H. (2008). Optimized ICT Project Selection Utilizing Fuzzy System. World Applied Sciences, 4(1), 44–49.
• Ghorshi Nezhad, M. R., Zolfani, S. H., Moztarzadeh, F., Zavadskas, E. K., & Bahrami, M. (2015). Planning the priority of high tech industries based on SWARA-WASPAS methodology: The case of the nanotechnology industry in Iran. Economic research-Ekonomska istraživanja, 28(1), 1111-1137.
• Guimaraes, T., & McKeen, J. D. (1988). Organizational bias in the selection of MIS projects. Omega, 16(4), 297–307. http://doi.org/10.1016/0305-0483(88)90066-7 Gupta, S., Woodside, A., Dubelaar, C., & Bradmore, D. (2009). Diffusing knowledge-based core competencies for leveraging innovation strategies: Modelling outsourcing to knowledge process organizations (KPOs) in pharmaceutical networks. Industrial Marketing Management, 38(2), 219–227. http://doi.org/10.1016/j.indmarman.2008.12.010
• Hasan Aghdaie, M., Hashemkhani Zolfani, S., & Zavadskas, E. K. (2013). Decision making in machine tool selection: An integrated approach with SWARA and COPRAS-G methods. Engineering Economics, 24(1), 5-17.
• Hashemkhani Zolfani, S., & Bahrami, M. (2014). Investment prioritizing in high tech industries based on SWARA-COPRAS approach. Technological and Economic Development of Economy, 20(3), 534-553.
• Hasselbring, W. (2000). Information system integration. Communications of the ACM, 43(6), 32–38. http://doi.org/10.1145/336460.336472
• He, W., Qiao, Q., & Wei, K. K. (2009). Social relationship and its role in knowledge management systems usage. Information and Management, 46(3), 175–180. http://doi.org/10.1016/j.im.2007.11.005
• Heidary Dahooie, J., Beheshti Jazan Abadi, E., Vanaki, A. S., & Firoozfar, H. R. (2018). Competency‐based IT personnel selection using a hybrid SWARA and ARAS‐G methodology. Human Factors and Ergonomics in Manufacturing & Service Industries
• Hillier, F. S., & Lieberman, G. J. (2001). Introduction to Operational Research. New York: McGraw-Hill.
• Huang, J. (2008). Combining entropy weight and TOPSIS method for information system selection. In Proceedings of the IEEE International Conference on Automation and Logistics, ICAL 2008 (pp. 1281–1284). http://doi.org/10.1109/ICAL.2008.4636483
• Işık, A., & Adalı, E. (2016). A comparative study for the agricultural tractor selection problem. Decision Science Letters, 5(4), 569-580.
• Jiang, J. J., & Klein, G. (1999). Information system project-selection criteria variations within strategic classes. IEEE Transactions on Engineering Management, 46(2), 171–176. http://doi.org/10.1109/17.759145
• Juodagalvienė, B., Turskis, Z., Šaparauskas, J., & Endriukaitytė, A. (2017). Integrated multi-criteria evaluation of house’s plan shape based on the EDAS and SWARA methods. Engineering Structures and Technologies, 9(3), 117-125.
• Karabasevic, D., Stanujkic, D., Urosevic, S., & Maksimovic, M. (2015). Selection of candidates in the mining industry based on the application of the SWARA and the MULTIMOORA methods. Acta Montanistica Slovaca, 20(2).
• Karabašević, D., Stanujkić, D., Urošević, S., & Maksimović, M. (2016). An approach to personnel selection based on Swara and Waspas methods. BizInfo (Blace) Journal of Economics, Management and Informatics, 7(1), 1-11.
• Karabasevic, D., Paunkovic, J., & Stanujkic, D. (2016). Ranking of companies according to the indicators of corporate social responsibility based on SWARA and ARAS methods. Serbian Journal of Management, 11(1), 43-53
• Kayrak, M. (2007). BİLİŞİM SİSTEMLERİ STRATEJİSİNİN ÖNEMİ VE SAYIŞTAY DENEYİMİ. SAYIŞTAY DERGİSİ ●, 65, 199–208.
• Keršuliene, V., Zavadskas, E. K., & Turskis, Z. (2010). Selection of Rational Dispute Resolution Method by Applying New Step-Wise Weight Assessment Ratio Analysis (Swara). Journal of Business Economics and Management, 11(2), 243–258.
• Keršulienė, V., & Turskis, Z. (2011). Integrated fuzzy multiple criteria decision making model for architect selection. Technological and Economic Development of Economy, 17(4), 645-666.
• Kim, I., Shin, S., Choi, Y., Manh Thang, N., Ramos, E., & Hwang, W.-J. (2009). Development of a Project Selection Method on Information System Using ANP and Fuzzy Logic. World Academy of Science, Engineering and Technology, 29(5), 411–416.
• Koutsabasis, P., Stavrakis, M., Viorres, N., Darzentas, J. S., Spyrou, T., & Darzentas, J. (2008). A descriptive reference framework for the personalisation of e-business applications. Electronic Commerce Research, 8(3), 173–192. http://doi.org/10.1007/s10660-008-9021-1
• Kutlu, B., & Alkaya, A. (2015). MEASURING THE DELONE AND MCLEAN MODEL OF INFORMATION SYSTEMS SUCCESS APPLIED TO BANKING SECTOR OF TURKEY. International Journal of Advanced Computational Engineering and Networking, 3(8), 2320–2106.
• Lee, H., & Choi, B. (2000). Knowledge Management Enablers, Processes, and Organizational Performance: An Integration and Empirical Examination. Journal of Management Information Systems, 20(1), 179–228.
• Lee, J. W., & Kim, S. H. (2001). An integrated approach for interdependent information system project selection. International Journal of Project Management, 19(2), 111–118. http://doi.org/10.1016/S0263-7863(99)00053-8
• Liang, C., & Li, Q. (2008). Enterprise information system project selection with regard to BOCR. International Journal of Project Management, 26(8), 810–820. http://doi.org/10.1016/j.ijproman.2007.11.001
• Lien, C., & Chan, H.-L. (2007). A selection model for ERP system by applying fuzzy AHP approach. International Journal of the Computer, the Internet, 58–72. Lin, H. F., & Lee, G. G. (2005). Impact of organizational learning and knowledge management factors on e-business adoption. Management Decision, 43(2), 171–188. http://doi.org/10.1108/00251740510581902
• Lin, H. Y., Hsu, P. Y., & Sheen, G. J. (2007). A fuzzy-based decision-making procedure for data warehouse system selection. Expert Systems with Applications, 32(3), 939–953. http://doi.org/10.1016/j.eswa.2006.01.031
• Livio, C., Grimaldi, M., & Hanandi, M. (2014). Decision making in choosing information systems An empirical study in Jordan. The Journal of Information and Knowledge Management Systems Vol., 44(2), 162–184.
• Mudambi, S. M., & Tallman, S. (2010). Make, buy or ally? Theoretical perspectives on knowledge process outsourcing through alliances. Journal of Management Studies, 47(8), 1434–1456. http://doi.org/10.1111/j.1467-6486.2010.00944.x
• Muralidhar, K., Santhanam, R., & Wilson, R. L. (1990). Using the analytic hierarchy process for information system project selection. Information & Management, 18(2), 87–95. http://doi.org/10.1016/0378-7206(90)90055-M
• Narasimhaiah, G., & Chen, K. (1998). Information System Project Selection Using Fuzzy Logic. IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, 28(6), 849–855. http://doi.org/10.1109/3468.725355
• Nonaka, I. (1994). A dynamic theory of organizational knowledge creation. Organization Science, 1(5), 14–37. http://doi.org/10.1287/orsc.5.1.14
• Nonaka, I., & Toyama, R. (2003). The knowledge-creating theory revisited: knowledge creation as a synthesizing process. Knowledge Management Research & Practice, 1, 2–10. http://doi.org/10.1057/
• Oztaysi, B. (2014). A decision model for information technology selection using AHP integrated TOPSIS-Grey: The case of content management systems. Knowledge-Based Systems, 70, 44–54. http://doi.org/10.1016/j.knosys.2014.02.010
• Rhee, S. K., Jin, H., Lee, J., Kwon, M., Park, M., & Ha, S. (2008). Information Modelling for Adaptive Composition in Collaborative Work Environment. International Journal of Computer, Electrical, Automation, Control and Information Engineering, 2(2), 825–830.
• Sheth, A. P., Georgakopoulos, D., Joosten, S., Rusinkiewicz, M., Scacchi, W., Wileden, J. C., & Wolf, A. L. (1996). Report from the NSF Workshop on Workflow and Process Automation in Information Systems. SIGMOD Record, 25(December 1996), 55–67. http://doi.org/10.1145/245882.245903
• Shukla, S., Mishra, P. K., Jain, R., & Yadav, H. C. (2016). An integrated decision making approach for ERP system selection using SWARA and PROMETHEE method. International Journal of Intelligent Enterprise, 3(2), 120-147.
• Soo, C., Devinney, T., Midgley, D., France, F., & Deering, A. (2002). Knowledge Management : Philosophy , Process , Pitfalls , and Performance. California Management Review, 44(4), 129-. http://doi.org/10.1177/026638202761175374
• Stanujkic, D., Karabasevic, D., & Zavadskas, E. K. (2015). A framework for the selection of a packaging design based on the SWARA method. Engineering Economics, 26(2), 181–187. http://doi.org/10.5755/j01.ee.26.2.8820
• Stewart, R., & Mohamed, S. (2002). IT/IS projects selection using multi-criteria utility theory. Logistics Information Management, 15(4), 254–270. http://doi.org/10.1108/09576050210436101
• Tecim, V., & Gökşen, Y. (2009). BİLİŞİM TEKNOLOJİLERİNİN ÜNİVERSİTELERDE ETKİN KULLANIMI ÜZERİNE BİR ÇALIŞMA. Journal of Yaşar University, 4(14), 2237–2256.
• Tekin, M. (2008). Sayısal Yöntemler. Konya: Selçuk Üniversitesi İİBF.
• Timor, M. (2010). Yöneylem Araştırması. İstanbul: Türkmen Kitabevi.
• Vafaeipour, M., Zolfani, S. H., Varzandeh, M. H. M., Derakhti, A., & Eshkalag, M. K. (2014). Assessment of regions priority for implementation of solar projects in Iran: New application of a hybrid multi-criteria decision making approach. Energy Conversion and Management, 86, 653-663.
• Yazdani, M., Zavadskas, E. K., Ignatius, J., & Abad, M. D. (2016). Sensitivity analysis in MADM methods: application of material selection. Engineering Economics, 27(4), 382-391.
• Yeh, C., Deng, H., Wibowo, S., & Xu, Y. (2010). Fuzzy Multicriteria Decision Support for Information Systems Project Selection. International Journal, 12(2), 170–179. Yıldırım, B. F., & Önder, E. (2014). İşletmeciler, Mühendisler ve Yöneticiler için Operasyonel, Yönetsel ve Stratejik Problemlerin Çözümünde Çok Kriterli Karar Verme Yöntemleri. Bursa: Dora Yayınları.
• Zolfani, S. H., & Banihashemi, S. S. A. (2014, May). Personnel selection based on a novel model of game theory and MCDM approaches. In Proc. of 8th International Scientific Conference" Business and Management (pp. 15-16).
• Zolfani, S. H., & Saparauskas, J. (2013). New Application of SWARA Method in Prioritizing Sustainability Assessment Indicators of Energy System. Engineering Economics, 24(5), 408–414.
• Zolfani, S. H., Zavadskas, E. K., & Turskis, Z. (2013). Design of Products with Both International and Local Perspectives Based on Yin-Yang Balance Theory and SWARA Method. Economic Research, 26(2), 153–166. http://doi.org/10.1080/1331677X.2013.11517613
• Zolfani, S. H., Esfahani, M. H., Bitarafan, M., Zavadskas, E. K., & Arefi, S. L. (2013). Developing a new hybrid MCDM method for selection of the optimal alternative of mechanical longitudinal ventilation of tunnel pollutants during automobile accidents. Transport, 28(1), 89-96.
• Zolfani, S. H., Pourhossein, M., Yazdani, M., & Zavadskas, E. K. (2017). Evaluating construction projects of hotels based on environmental sustainability with MCDM framework. Alexandria Engineering Journal.