Share:


Comparative analysis of multicriteria decision-making methods evaluating the efficiency of technology transfer

    Lidija Kraujalienė Affiliation

Abstract

Purpose – to find appropriate tools to measure the efficiency of the technology transfer process (TTP) in higher education institutions (HEIs). Scientific problem is a lack of methods measuring the efficiency of TTP. The objective – comparative analysis of efficiency evaluation methods.


Research methodology – the research methodology is based on a comparative analysis of the research papers on the advantages and disadvantages of methods suitable to evaluate the efficiency of TTP.


Findings – among some tools, FARE is highlighted for identifying the variables of TTP and assigning their weights, when TOPSIS – to rank the variables and identify the most important. MULTO-MOORA and COPRAS methods with ranking abilities are suitable to select the number of HEIs. DEA method is intended for the economic evaluation of TTP efficiency in HEIs. The social sciences are strengthened by suitable founded tools to measure the efficiency of TTP in HEIs.


Research limitations – this paper is providing all advantages and disadvantages (limitations) of decision-making multicriteria methods.


Practical implications – the original structure of methods enabling stakeholders (HEIs, TTOs and public authorities) for efficient allocation of an organisation’s financial resources, foresee the future goals for improving the efficiency of TTP.


Originality/Value – the original framework of methods incorporated into the one model, enabling related stakeholders (HEIs, TTOs and public authorities) allocate financial resources efficiently.

Keyword : efficiency, evaluation, technology transfer, methods

How to Cite
Kraujalienė, L. (2019). Comparative analysis of multicriteria decision-making methods evaluating the efficiency of technology transfer. Business, Management and Education, 17, 72-93. https://doi.org/10.3846/bme.2019.11014
Published in Issue
Aug 20, 2019
Abstract Views
96
PDF Downloads
56
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

References

Aghdaie, M. H., Zolfani, S. H., & Zavadskas, E. K. (2013). Market segment evaluation and selection based on application of fuzzy AHP and COPRAS-G methods. Journal of Business Economics and Management, 14(1), 213-233. https://doi.org/10.3846/16111699.2012.721392

Akkaya, G., Turanoğlu, B., & Öztaş, S. (2015). An integrated fuzzy AHP and fuzzy MOORA approach to the problem of industrial engineering sector choosing. Expert Systems with Applications, 42(24), 9565-9573. https://doi.org/10.1016/j.eswa.2015.07.061

Altuntas, S., Dereli, T., & Yilmaz, M. K. (2015). Evaluation of excavator technologies: application of data fusion based MULTIMOORA methods. Journal of Civil Engineering and Management, 21(8), 977-997. https://doi.org/10.3846/13923730.2015.1064468

Bausys, R., Zavadskas, E. K., & Kaklauskas, A. (2015). Application of neutrosophic set to multicriteria decision making by COPRAS. Infinite Study.

Beikler, T., & Flemmig, T. F. (2015). EAO consensus conference: economic evaluation of implant‐supported prostheses. Clinical Oral Implants Research, 26, 57-63. https://doi.org/10.1111/clr.12630

Banker, R. D., Charnes, A., Cooper, W. W., Swarts, J., & Thomas, D. (1989). An introduction to data envelopment analysis with some of its models and their uses. Research in Governmental and Non-profit Accounting, 5, 125-163.

Behzadian, M., Otaghsara, S. K., Yazdani, M., & Ignatius, J. (2012). A state-of the-art survey of TOPSIS applications. Expert Systems with Applications, 39(17), 13051-13069. https://doi.org/10.1016/j.eswa.2012.05.056

Brauers, W. K. M., & Zavadskas, E. K. (2010). Project management by MULTIMOORA as an instrument for transition economies. Technological and Economic Development of Economy, 16(1), 5-24. https://doi.org/10.3846/tede.2010.01

Chatterjee, P., Mondal, S., Boral, S., Banerjee, A., & Chakraborty, S. (2017). A novel hybrid method for non-traditional machining process selection using factor relationship and Multi-Attributive Border Approximation Method. Facta Universitatis, Series: Mechanical Engineering, 15(3), 439-456. https://doi.org/10.22190/FUME170508024C

Chatterjee, P., Athawale, V. M., & Chakraborty, S. (2011). Materials selection using complex proportional assessment and evaluation of mixed data methods. Materials & Design, 32(2), 851-860. https://doi.org/10.1016/j.matdes.2010.07.010

Chen, J. K., & Chen, I. (2008). VIKOR method for selecting universities for future development based on innovation. Online Submission.

Choudhury, K. (2015). Evaluating customer-perceived service quality in business management education in India: A study in topsis modeling. Asia Pacific Journal of Marketing and Logistics, 27(2), 208-225. https://doi.org/10.1108/APJML-04-2014-0065

Cook, W. D., Tone, K., & Zhu, J. (2014). Data envelopment analysis: Prior to choosing a model. Omega, 44, 1-4. https://doi.org/10.1016/j.omega.2013.09.004

Ding, L., & Zeng, Y. (2015). Evaluation of Chinese higher education by TOPSIS and IEW – The case of 68 universities belonging to the Ministry of Education in China. China Economic Review, 36, 341-358. https://doi.org/10.1016/j.chieco.2015.05.007

Džunić, M., Stanković, J., & Janković-Milić, V. (2018). Multi-criteria approach in evaluating contribution of social entrepreneurship to the employment of socially-excluded groups. Technological and Economic Development of Economy, 24(5), 1885-1908. https://doi.org/10.3846/20294913.2017.1347906

Epanchin-Niell, R. S. (2017). Economics of invasive species policy and management. Biological Invasions, 19(11), 3333-3354. https://doi.org/10.1007/s10530-017-1406-4

Feruś, A. (2008). The dea method in managing the credit risk of companies. Ekonomika/Economics, 84.

Ghorabaee, M. K., Amiri, M., Sadaghiani, J. S., & Goodarzi, G. H. (2014). Multiple criteria group decision-making for supplier selection based on COPRAS method with interval type-2 fuzzy sets. The International Journal of Advanced Manufacturing Technology, 75(5-8), 1115-1130. https://doi.org/10.1007/s00170-014-6142-7

Ginevičius, R. (2011). A new determining method for the criteria weights in multicriteria evaluation. International Journal of Information Technology & Decision Making, 10(06), 1067-1095. https://doi.org/10.1142/S0219622011004713

Ginevičius, R. (2006). Multicriteria evaluation of the criteria weights based on their interrelationship. Business: Theory and Practice, 7, 3-13.

Ginevičius, R. (2007). A comparative analysis of the criteria weights determined by using multicriteria evaluation methods AHP and FARE. 4th International Scientific Conference “Enterpsire Management: Diagnosis, Strategy, Efficiency” (pp. 16-18). Vilnius: Technika.

Ginevičius, R. (2008). Normalisation of quantities of various dimensions. Journal of Business Economics and Management, (1), 79-86. https://doi.org/10.3846/1611-1699.2008.9.79-86

Ginting, G., Fadlina, M., Siahaan, A. P. U., & Rahim, R. (2017). Technical approach of TOPSIS in decision making. International Journal of Recent Trends in Engineering & Research, 3(8), 58-64. https://doi.org/10.23883/IJRTER.2017.3388.WPYUJ

Hafezalkotob, A., Hafezalkotob, A., & Sayadi, M. K. (2016). Extension of MULTIMOORA method with interval numbers: an application in materials selection. Applied Mathematical Modelling, 40(2), 1372-1386. https://doi.org/10.1016/j.apm.2015.07.019

Hafezalkotob, A., & Hafezalkotob, A. (2015). Comprehensive MULTIMOORA method with target-based attributes and integrated significant coefficients for materials selection in biomedical applications. Materials & Design, 87, 949-959. https://doi.org/10.1016/j.matdes.2015.08.087

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. https://doi.org/10.3846/20294913.2014.881435

Kaklauskas, A., Zavadskas, E. K., Naimavicienė, J., Krutinis, M., Plakys, V., & Venskus, D. (2010). Model for a complex analysis of intelligent built environment. Automation in Construction, 19(3), 326-340. https://doi.org/10.1016/j.autcon.2009.12.006

Kaklauskas, A., Zavadskas, E. K., Raslanas, S., Ginevičius, R., Komka, A., & Malinauskas, P. (2006). Selection of low-e windows in retrofit of public buildings by applying multiple criteria method COPRAS: A Lithuanian case. Energy and Buildings, 38(5), 454-462. https://doi.org/10.1016/j.enbuild.2005.08.005

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).

Kazan, H., Özçelik, S., & Hobikoğlu, E. H. (2015). Election of deputy candidates for nomination with AHP-PROMETHEE methods. Procedia-Social and Behavioral Sciences, 195, 603-613. https://doi.org/10.1016/j.sbspro.2015.06.141

Kracka, M., Brauers, W. K. M., & Zavadskas, E. K. (2010). Ranking heating losses in a building by applying the MULTIMOORA. Engineering Economics, 21(4), 352-359.

Kildienė, S., Zavadskas, E. K., & Tamošaitienė, J. (2014). Complex assessment model for advanced technology deployment. Journal of Civil Engineering and Management, 20(2), 280-290. https://doi.org/10.3846/13923730.2014.904813

Kurgonaitė, K. (2015). Technologijų perdavimo proceso kūrimas, kaip viena iš priemonių efektyvesniam mokslo ir verslo bendradarbiavimui skatinti. JPP Kurk Lietuvai.

Lazauskas, M., Kutut, V., & Zavadskas, E.-K. (2015b). Multicriteria assessment of unfinished construction projects. Gradevinar, 67(4), 319-328.

Lazauskas, M., Zavadskas, E.-K., & Saparauskas, J. (2015a). Ranking of priorities among the Baltic capital cities for the development of sustainable construction. E and M Ekonomie a Management, 18(2), 15-24. https://doi.org/10.15240/tul/001/2015-2-002

Liou, J.-J., Tamošaitienė, J., Zavadskas, E.-K., & Tzeng, G.-H. (2016). New hybrid COP-RAS-G MADM Model for improving and selecting suppliers in green supply chain management. International Journal of Production Research, 54(1), 114-134.

Liu, P., & Wang, M. (2011). An extended VIKOR method for multiple attribute group decision making based on generalized interval-valued trapezoidal fuzzy numbers. Scientific Research and Essays, 6(4), 765-776.

Liu, H. C., Fan, X. J., Li, P., & Chen, Y. Z. (2014). Evaluating the risk of failure modes with extended MULTIMOORA method under fuzzy environment. Engineering Applications of Artificial Intelligence, 34, 168-177. https://doi.org/10.1016/j.engappai.2014.04.011

Liu, H. C., You, J. X., Lu, C., & Chen, Y. Z. (2015). Evaluating health-care waste treatment technologies using a hybrid multi-criteria decision making model. Renewable and Sustainable Energy Reviews, 41, 932-942. https://doi.org/10.1016/j.rser.2014.08.061

Liu, J. S., Lu, L. Y., Lu, W. M., & Lin, B. J. (2013). A survey of DEA applications. Omega, 41(5), 893-902. https://doi.org/10.1016/j.omega.2012.11.004

Mousavi-Nasab, S. H., & Sotoudeh-Anvari, A. (2017). A comprehensive MCDM-based approach using TOPSIS, COPRAS and DEA as an auxiliary tool for material selection problems. Materials & Design, 121, 237-253. https://doi.org/10.1016/j.matdes.2017.02.041

Mulliner, E., Malys, N., & Maliene, V. (2016). Comparative analysis of MCDM methods for the assessment of sustainable housing affordability. Omega, 59, 146-156. https://doi.org/10.1016/j.omega.2015.05.013

Nazarko, J., & Šaparauskas, J. (2014). Application of DEA method in efficiency evaluation of public higher education institutions. Technological and Economic Development of Economy, 20(1), 25-44. https://doi.org/10.3846/20294913.2014.837116

Nelsen, L. L. (2005). The role of research institutions in the formation of the biotech cluster in Massachusetts: The MIT experience. Journal of Commercial Biotechnology, 11(4), 330-336. https://doi.org/10.1057/palgrave.jcb.3040134

Nguyen, H. T., Dawal, S. Z. M., Nukman, Y., Aoyama, H., & Case, K. (2015). An integrated approach of fuzzy linguistic preference based AHP and fuzzy COPRAS for machine tool evaluation. PloS One, 10(9), e0133599. https://doi.org/10.1371/journal.pone.0133599

Obayiuwana, E., & Falowo, O. (2015, September). A multimoora approach to access network selection process in heterogeneous wireless networks. In AFRICON 2015 (pp. 1-5). IEEE. https://doi.org/10.1109/AFRCON.2015.7331973

Order of the Ministry of Education and Science of the Republic of Lithuania. (2009). Regarding recommendations for Lithuanian research and study institutions to approve the rights resulting from the intellectual activities, Nr. ISAK-2462. Retrieved from https://e-seimas.lrs.lt/portal/legalActPrint/lt?jfwid=ky1aszbvn&documentId=TAIS.360411&category=TAD

Palecková, I. (2016, May 12-13). Cost efficiency of the Czech and Slovak banking sectors: an application of the data envelopment analysis. 9th International Scientific Conference of “Business and Management 2016”. Vilnius, Lithuania. https://doi.org/10.3846/bm.2016.14

Pitchipoo, P., Vincent, D. S., Rajini, N., & Rajakarunakaran, S. (2014). COPRAS decision model to optimize blind spot in heavy vehicles: A comparative perspective. Procedia Engineering, 97, 1049-1059. https://doi.org/10.1016/j.proeng.2014.12.383

Podvezko, V. (2011). Comparative analysis of MCDA methods SAW and COPRAS. Inžinerinė ekonomika, 134-146. https://doi.org/10.5755/j01.ee.22.2.310

Podviezko, A., & Podvezko, V. (2014). Absolute and relative evaluation of socio-economic objects based on multiple criteria decision making methods. Engineering Economics, 25(5), 522-529. https://doi.org/10.5755/j01.ee.25.5.6624

Rezazadeh, M. H., Sancholi, B., Rad, S. S., Feyzabadi, A. N., & Kadkhodaei, M. (2017). Ranking of Zahedan’s five districts in order to fulfill the creative city. Journal of History Culture and Art Research, 6(1), 703-719. https://doi.org/10.7596/taksad.v6i1.776

Rivera, E. D., Fajardo, C. A., Ávila, A. J., Ávila, C. F., & Martinez-Gómez, J. (2017). Material selection of induction cookware based on multi criteria decision making methods (MCDM). Rev Técn Energıa.

Simar, L., & Wilson, P. W. (2007). Estimation and inference in two-stage, semi-parametric models of production processes. Journal of Econometrics, 136(1), 31-64. https://doi.org/10.1016/j.jeconom.2005.07.009

Song, J., & Zheng, J. (2015). The application of Grey-TOPSIS method on teaching quality evaluation of the higher education. International Journal of Emerging Technologies in Learning (iJET), 10(8), 42-45. https://doi.org/10.3991/ijet.v10i8.5219

Shen, B., Han, Y., Price, L., Lu, H., & Liu, M. (2017). Techno-economic evaluation of strategies for addressing energy and environmental challenges of industrial boilers in China. Energy, 118, 526-533. https://doi.org/10.1016/j.energy.2016.10.083

Stanujkic, D. (2016). An extension of the ratio system approach of MOORA method for group decision-making based on interval-valued triangular fuzzy numbers. Technological and Economic Development of Economy, 22(1), 122-141. https://doi.org/10.3846/20294913.2015.1070771

Stanujkic, D. (2015a). Extension of the ARAS method for decision-making problems with interval-valued triangular fuzzy numbers. Informatica, 26(2), 335-355. https://doi.org/10.15388/Informatica.2015.51

Stanujkic, D., Zavadskas, E.-K., Brauers, W.-K.-M, & Karabasevic, D. (2015b). An extension of the MULTIMOORA method for solving complex decision-making problems based on the use of interval-valued triangular fuzzy numbers. Transformations in Business & Economics, 14(2B), 355-375.

Stefano, N. M., Casarotto Filho, N., Vergara, L. G. L., & da Rocha, R. U. G. (2015). COPRAS (complex proportional assessment): State of the art research and its applications. IEEE Latin America Transactions, 13(12), 3899-3906. https://doi.org/10.1109/TLA.2015.7404925

Tamošaitienė, J., Zavadskas, E. K., Liou, J. J., & Tzeng, G. H. (2014). Selecting suppliers in green supply chain management. In 8th International Scientific Conference Business and Management 2014 (pp. 770-776). Vilnius, Lithuania. https://doi.org/10.3846/bm.2014.093

Tavana, M., Momeni, E., Rezaeiniya, N., Mirhedayatian, S. M., & Rezaeiniya, H. (2013). A novel hybrid social media platform selection model using fuzzy ANP and COPRAS-G. Expert Systems with Applications, 40(14), 5694-5702. https://doi.org/10.1016/j.eswa.2013.05.015

Tupenaite, L., Zavadskas, E. K., Kaklauskas, A., Turskis, Z., & Seniut, M. (2010). Multiple criteria assessment of alternatives for built and human environment renovation. Journal of Civil Engineering and Management, 16(2), 257-266. https://doi.org/10.3846/jcem.2010.30

Turskis, Z., Zavadskas, E. K., & Peldschus, F. (2009). Multi-criteria optimization system for decision making in construction design and management. Engineering Economics, 61(1).

Velasquez, M., & Hester, P. T. (2013). An analysis of multi-criteria decision making methods. International Journal of Operations Research, 10(2), 56-66.

Wang, K., Wei, Y. M., & Zhang, X. (2013). Energy and emissions efficiency patterns of Chinese regions: a multi-directional efficiency analysis. Applied Energy, 104, 105-116. https://doi.org/10.1016/j.apenergy.2012.11.039

Xue, Y. X., You, J. X., Zhao, X., & Liu, H. C. (2016). An integrated linguistic MCDM approach for robot evaluation and selection with incomplete weight information. International Journal of Production Research, 54(18), 5452-5467. https://doi.org/10.1080/00207543.2016.1146418

Zavadskas, E. K., Turskis, Z., & Kildienė, S. (2014). State of art surveys of overviews on MCDM/MADM methods. Technological and Economic Development of Economy, 20(1), 165-179. https://doi.org/10.3846/20294913.2014.892037

Zavadskas, E. K., Mardani, A., Turskis, Z., Jusoh, A., & Nor, K. M. (2016). Development of TOPSIS method to solve complicated decision-making problems – An overview on developments from 2000 to 2015. International Journal of Information Technology & Decision Making, 15(03), 645-682. https://doi.org/10.1142/S0219622016300019

Zhang, N., & Choi, Y. (2013a). Total-factor carbon emission performance of fossil fuel power plants in China: A metafrontier non-radial Malmquist index analysis. Energy Economics, 40, 549-559. https://doi.org/10.1016/j.eneco.2013.08.012

Zhang, N., Zhou, P., & Choi, Y. (2013b). Energy efficiency, CO2 emission performance and technology gaps in fossil fuel electricity generation in Korea: A meta-frontier non-radial directional distance-function analysis. Energy Policy, 56, 653-662. https://doi.org/10.1016/j.enpol.2013.01.033

Zolfani, S. H., Pourhossein, M., Yazdani, M., & Zavadskas, E. K. (2018). Evaluating construction projects of hotels based on environmental sustainability with MCDM framework. Alexandria Engineering Journal, 57(1), 357-365. https://doi.org/10.1016/j.aej.2016.11.002