The hybrid intellectual capital valuation method

References

• Bontis, N. (2001). Assessing knowledge assets: A review of the models used to measure intellectual capital. International Journal of Management Reviews, 3(1), 41–60. https://doi.org/https://doi.org/10.1111/1468-2370.00053
   Web of Science ®Google Scholar
• Chang, Y. (2013). Performance measurement of the fourth party logistics providers. iBusiness, 05(02), 7–10. https://doi.org/https://doi.org/10.4236/ib.2013.52B002
   Google Scholar
• Dash, M. (2016). Banking performance measurement using multi-criteria decision models ELECTRE and PROMETHEE: The case of Indian banks. International Journal of Operations and Quantitative Management, 22(1), 29–37.
   Google Scholar
• Deventer, V. & Johanna, M. (2002). Introducing intellectual capital management in an information support services environment: Measuring intellectual capital [Doctoral dissertation]. Retrieved from http://upetd.up.ac.za/thesis/available/etd-08012003-162454/unrestricted/04chapter4.pdf
   Google Scholar
• Diaz-Balteiro, L., & Romero, C. (2004). Sustainability of forest management plans: A discrete goal programming approach. Journal of Environmental Management, 71(4), 351–359. https://doi.org/https://doi.org/10.1016/j.jenvman.2004.04.001
   PubMed Web of Science ®Google Scholar
• Dinçer, H., Hacıoğlu, Ü., & Yüksel, S. (2017). Balanced scorecard based performance measurement of European airlines using a hybrid multicriteria decision making approach under the fuzzy environment. Journal of Air Transport Management, 63(1), 17–33. https://doi.org/https://doi.org/10.1016/j.jairtraman.2017.05.005
   Web of Science ®Google Scholar
• Gross-Gołacka, E., Kusterka-Jefmańska, M., & Jefmański, B. (2020). Can elements of intellectual capital improve business sustainability?-The perspective of managers of SMEs in Poland. Sustainability, 12(4), 1545. https://doi.org/https://doi.org/10.3390/su12041545
   Web of Science ®Google Scholar
• Hwang, K., & Yoon, K. (1981). Multiple attribute decision making: Methods and applications. Springer.
   Google Scholar
• Karadayi, M., & Karsak, E. (2014). Fuzzy MCDM approach for health-care performance assessment. In N. Callaos, S. Hashimoto, A. V. Rutkauskas, B. Sánchez, & C. D. Zinn (Eds.), WMSCI 2014. Proceedings of 18th World Multi-Conference on Systemics, Cybernetics and Informatics (pp. 228–233). International Institute of Informatics and Systemics.
   Google Scholar
• Kianto, A., Ritala, P., Vanhala, M., & Hussinki, H. (2020). Reflections on the criteria for the sound measurement of intellectual capital: A knowledge-based perspective. Critical Perspectives on Accounting, 70(1), 102046–102015. https://doi.org/https://doi.org/10.1016/j.cpa.2018.05.002
   Web of Science ®Google Scholar
• Lee, Y., Chung, P., & Shyu, J. (2017). Performance evaluation of medical device manufacturers using a hybrid fuzzy MCDM. Journal of Scientific & Industrial Research, 76(1), 28–31.
   Web of Science ®Google Scholar
• Lu, M., Hsu, C., Liou, J., & Lo, H. (2018). A hybrid MCDM and sustainability-balanced scorecard model to establish sustainable performance evaluation for international airports. Journal of Air Transport Management, 71(1), 9–19. https://doi.org/https://doi.org/10.1016/j.jairtraman.2018.05.008
   Web of Science ®Google Scholar
• Nazari, J. (2015). Intellectual capital measurement and reporting models. In P., Ordoñezde Pablos, L. J., Turró, R. D. Tennyson & J., Zhao (Eds.), Knowledge Management for Competitive Advantage During Economic Crisis (pp. 117–139). IGI Global. https://doi.org/10.4018/978-1-4666-6457-9.ch008
   Google Scholar
• Nimtrakoon, S. (2015). The relationship between intellectual capital, firms’ market value and financial performance: Empirical evidence from the ASEAN. Journal of Intellectual Capital, 16(3), 587–618. https://doi.org/https://doi.org/10.1108/JIC-09-2014-0104
   Web of Science ®Google Scholar
• Marsetio, S., Octavian, A., Sumantri, S., Ahmadi, R., Ritonga, R. & Supartono, (2017). The combination of DEMATEL, ANP, and IPMS methods for performance measurement system design: A case study in KOLAT KOARMATIM. International Journal of Control and Automation, 10(8), 155–170.
   Google Scholar
• Medel-González, F., Salomon, V., & García-Ávila, L. (2015). Multi-criteria sustainability performance measurement: An application in Cuba. International Journal of Business and Systems Research, 9(4), 394–411. https://doi.org/https://doi.org/10.1504/IJBSR.2015.072586
   Google Scholar
• Rabbani, A., Zamani, M., Yazdani-Chamzini, A., & Zavadskas, E. (2014). Proposing a new integrated model based on sustainability balanced scorecard (SBSC) and MCDM approaches by using linguistic variables for the performance evaluation of oil producing companies. Expert Systems with Applications, 41(16), 7316–7327. https://doi.org/https://doi.org/10.1016/j.eswa.2014.05.023
   Web of Science ®Google Scholar
• Ramanauskaitė, A., & Rudžionienė, K. (2013). Intellectual capital valuation: methods and their classification. Ekonomika, 93(2), 79–92.
   Google Scholar
• Roos, J., Roos, G., Dragonetti, N., & Edvinsson, L. (1997). Intellectual capital: Navigating in the new business landscape. New York University Press.
   Google Scholar
• Saaty, T. (1996). The analytic network process. RWS Publications.
   Google Scholar
• Saaty, T. (2004). Decision making-the analytic hierarchy and network processes (AHP/ANP). Journal of Systems Science and Systems Engineering, 13(1), 1–35. https://doi.org/https://doi.org/10.1007/s11518-006-0151-5
   Google Scholar
• Senvar, O., Tuzkaya, U., & Kahraman, C. (2014). Supply chain performance measurement: an integrated DEMATEL and fuzzy-ANP approach. In C. Kahraman & B. Öztayşi (Eds.), Supply chain management under fuzziness (pp. 143–165). Springer.
   Google Scholar
• Shaik, M., & Abdul-Kader, W. (2018). A hybrid multiple criteria decision making approach for measuring comprehensive performance of reverse logistics enterprises. Computers & Industrial Engineering, 123(1), 9–25.
   Web of Science ®Google Scholar
• Sveiby, K. E. (2010). Methods for measuring intangible assets. Retrieved from http://www.sveiby.com
   Google Scholar
• Visalakshmi, S., Lakshmi, P., Shama, M. S., & Vijayakumar, K. (2015). An integrated fuzzy DEMATEL-TOPSIS approach for financial performance evaluation of GREENEX industries. International Journal of Operational Research, 23(3), 340–362. https://doi.org/https://doi.org/10.1504/IJOR.2015.069626
   Google Scholar
• Wu, Y., & Chou, Y. (2007). A new look at logistics business performance: intellectual capital perspective. International Journal of Logistics Management, 18(1), 41–63.
   Google Scholar
• Wudhikarn, R., Chakpitak, N., & Neubert, G. (2018). A literature review on performance measures of logistics management: An intellectual capital perspective. International Journal of Production Research, 56(13), 4490–4520. https://doi.org/https://doi.org/10.1080/00207543.2018.1431414
   Web of Science ®Google Scholar
• Yurdakul, M., & İç, Y. (2009). Analysis of the benefit generated by using fuzzy numbers in a TOPSIS model developed for machine tool selection problems. Journal of Materials Processing Technology, 209(1), 310–317. https://doi.org/https://doi.org/10.1016/j.jmatprotec.2008.02.006
   Web of Science ®Google Scholar