Methodological support for intellectual capital strategic management of the research organization
-
DOIhttp://dx.doi.org/10.21511/ppm.16(1).2018.29
-
Article InfoVolume 16 2018, Issue #1, pp. 292-308
- Cited by
- 1686 Views
-
217 Downloads
This work is licensed under a
Creative Commons Attribution-NonCommercial 4.0 International License
Making intellectual capital the strategic resource of an innovation-oriented organization under post-industrial economy formation requires improving the decision-making quality while choosing its development strategies. To a large extent, the effectiveness of strategic intellectual capital management depends on its methodological principles development, which determines the relevance of the subject chosen.
The purpose of the article is to form a methodical tool for substantiating the strategies of intellectual capital development in a research organization based on multi-criteria analysis.
As a methodological platform, the following methods for conducting research were chosen: an aggregated structural approach, in particular, the method of audit-evaluation by Brooking, to evaluate intellectual capital; SWOT analysis – to determine the strategic position of the company regarding its intellectual capital. To confirm the expert opinions consistency within the empirical studies framework, the concordance coefficient, estimated on the Pearson criterion, was calculated. The key to research is the multi-criteria analysis (SAW, TOPSIS, COPRAS) methods for evaluating, ranking and selecting strategic alternatives for the intellectual capital development of the research company.
Thus, the article takes a new view of using the scenario approach to the formation of an intellectual capital strategy. The strategy development stages are outlined, and the peculiarities of their methodological support are determined. In particular, the necessity to include into the test program for intellectual capital the estimation of its management efficiency is proved. The authors present an example of adapting SAW, TOPSIS, COPRAS methods for the evaluation and ranking of strategic alternatives to human, structural and market capital development.
Consequently, the results allowed to mathematically formalize the rating task and to form the optimal strategies portfolio of human, structural, market capital of organization, as well as to combine factors of the internal and external environment. Thus, the suggested methodological approach can be used by the heads of research organizations to develop and substantiate strategic management decisions to optimize their intellectual capital development.
- Keywords
-
JEL Classification (Paper profile tab)C44, D81, I23, O34
-
References45
-
Tables14
-
Figures0
-
- Table 1. Results of the criteria ranking for choosing strategic direction for the research organization development
- Table 2. Output data (decision matrix) on ranking strategies for human capital development using the SAW method
- Table 3. Normalized decision matrix
- Table 4. Weighted normalized decision matrix
- Table 5. Ranking alternative strategies for human capital development
- Table 6. Output data (decision matrix) on ranking the strategies for structural capital development by the TOPSIS method
- Table 7. Normalized decision matrix
- Table 8. Weighted normalized decision matrix
- Table 9. Ideal positive and ideal negative matrix solution (artificial alternatives)
- Table 10. Ranking of alternative strategies for the structural capital development of the organization
- Table 11. Output data (decision matrix) on ranking the strategies for market capital development by the COPRAS method
- Table 12. Normalized decision matrix
- Table 13. Weighted normalized decision matrix
- Table 14. Ranking of alternative strategies for market capital development
-
- Balan V., & Sitnitskiy M. (2012). The role of portfolio analysis in forming the competitive strategies of enterprise. Aktualni problemy ekonomiky, 5(131), 141-148.
- Baranov, V. V., & Zaytsev, A. V. (2009). Стратегическое управление интеллектуальным капиталом высокотехнологичного предприятия [Strategicheskoye upravleniye intellektualnym kapitalom vysokotekhnologichnogo predpriyatiya]. Kreativnaya ekonomika, 12(36), 72-86.
- 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.
- Bindu Madhuri, Ch., & Anand Chandulal, J. (2010b). Evaluating web sites using COPRAS-GRA combined with grey clustering. International Journal of Engineering Science and Technology, 2(10), 5280-5294.
- Bindu Madhuri, Ch., Anand Chandulal, J., & Padmaja, M. (2010a). Selection of best web site by applying COPRAS-G method. International Journal of Computer Science and Information Technologies, 1(2), 138-146.
- Brooking, A. (1996). Intellectual Capital: Core Asset for the Third Millennium Enterprise. London: International Thomson Business Press.
- Chatterjee, P., Athawale, V. M., & Chakraborty, S. (2011). Materials selection using complex propoptional assessment and evaluation of mixed data methods. Matherials & Design, 32(2), 851-860.
- Chen, C. T. (2000). Extension of the TOPSIS for group decision-making under fuzzy environment. Fuzzy Setsand Systems, 114, 1-9.
- Chu, M. T., Shyu, J., Tzeng, G. H., & Khosla, R. (2007). Comparison among three analytical methods for knowledge communities group-decision analysis. Expert systems with applications, 33(4), 1011-1024.
- Chupryna, O. O., & Chupryn, K. S. (2013). Методологічні підходи до оцінювання інтелектуального капіталу [Metodolohichni pidkhody do otsiniuvannia intelektualnoho kapitalu]. Visnyk Natsionalnoho universytetu “Yurydychna akademiia Ukrainy imeni Yaroslava Mudroho”, 3, 22-33.
- Datta, S., Beriha, G. S., Patnaik, B., & Mahapatra, S. S. (2009). Use of compromise ranking method for supervisor selection: A multi-criteria decision making (MCDM) approach. International Journal of Vocational and Technical Education, 1(1), 7-13.
- Edvinsson, L. (2000). Some perspectives on intangibles and intellectual capital. Journal of Intellectual Capital, 1(1), 12-16.
- Ghorabaee Mehdi Keshavarz, Amiri Maghsoud, Sadaghiani Jamshid Salehi, & Goodarzi Golnoosh Hassani (2014). Multiple criteria groupdecision-making for supplier selection based on COPRAS method with interval type-2 fuzzy sets. The International Journal of Advanced Manufacturing Technology, 75, 1115-1130.
- Ginevicius, R., & Podvezko, V. (2008). Housing in the context of economic and social development of Lithuanian regions. International Journal of Environment and Pollution, 35(2/3/4), 309-330.
- Hofer, N. L. (2009). An evaluation of neighborhood sustainability assessment frameworks using ecosystems resilience as the evaluation criteria. Master Science in Planning (217 p.). The University of British Columbia (Vancouver).
- Hwang, C. L., & Yoon, K. P. (1981). Multiple Attribute Decision Making: Methods and Applications (259 р.). New York: Springer-Varlag.
- Kaklauskas, A., Zavadskas, E. K., & Raslanas, S. (2005). Multivariant design and multiple criteria analysis of building refurbishments. Energy and Buildings, 37(4), 361-372.
- Kaplan, R. S., & Norton, D. P. (1996). The Balanced Scorecard: Translating Strategy Into Action. Harward Business School Press.
- Kendall, M. G. (1995). Rank Correlation Methods (196 p.). N.Y.: Hafner Publishing Company.
- Klee, A. J. (1971). The Role of Decision Models in the Evaluation of Competing Environmental Health Alternatives. Management Science, 18(2), 52-67.
- Kornilova, I., Bilorus, T., & Firsova, S. (2016). Види стратегій розвитку інтелектуального капіталу підприємства: підходи до систематизації [Vydy stratehii rozvytku intelektualnoho kapitalu pidpryiemstva: pidkhody do systematyzatsii]. Skhid, 6(146), 34-42.
- Kravchenko, S. I., & Kornieva, O. V. (2011). Оцінювання інтелектуального капіталу вищих навчальних закладів [Otsiniuvannia intelektualnoho kapitalu vyshchykh navchalnykh zakladiv]. Marketynh i menedzhment innovatsii, 3,55-61.
- Liashenko, N. Ye. (2012). Методичні підходи удосконалення аналізу моделей вимірювання інтелектуального капіталу підприємства [Metodychni pidkhody udoskonalennia analizu modelei vymiriuvannia intelektualnoho kapitalu pidpryiemstva]. Nauk. pratsi Poltav. derzh. ahrar. akad.,151-160.
- MacCrimmon, K. R. (1968). Decision making among multiple – attribute alternatives: A Survey and Consolidated Approach. RAND Memorandum, RM-4823-ARPA.
- Mardani, A., Jusoh, A., & Zavadskas, E. K. (2015). Fuzzy multiple criteria decision-making techniques and applications – Two decades review from 1994 to 2014. Expert Systems with Applications, 42(8), 4126-4148.
- Mazumdar, A., Datta, S., & Mahapatra, S. S. (2010). Multicriteria decision-making models for the evaluation and appraisal of teacher’ performance. International Journal of Productity and Quality Management, 6(2), 213-230.
- Podvezko, V. (2005). Development of expert estimates. Technological and Economic Development of Economy, 11(2), 101-107.
- Podvezko, V. (2011). The comparative analysis of MCDA methods SAW and COPRAS. Inzinerine Ekonomika-Engineering Economics, 22(2), 134-146.
- Qin, X., Huang, G., Chakma, A., Nie, X., & Lin, Q. (2008). A MCDM-based expert system for climate-change impact assessment and adaptation planning – A case study for the Georgia Basin, Canada. Expert Systems with Applications, 34(3), 2164-2179.
- Rahman, S., Odeyinka, H., Perera S., & Bi, Y., (2012). Product-cost modelling approach for the development of a decision support system for optimal roofing material selection. Expert Systems with Applications, 39, 6857-6871.
- Razavi Hajiagha, S. H., Hashemi, S. S., & Zavadskas, E. K. (2013). A complex proportional assessment method for group decision making in an interval-valued intuitionistic fuzzy environment. Technol. Econ. Dev. Econ., 19(1), 22-37.
- Stuart, Т. А. (1997). Intellectual Capital: The New Wealth of Organizations (115 р.). London.
- Sveiby, K. E. (2005). Methods for Measuring Intangible Assets.
- Triantaphyllou, E., & Lin, C. T. (1996). Development and evaluation of five fuzzy multi-attribute decision-making methods. International Journal of Approximate Reasoning, 14, 281-310.
- Tzeng, G. H. & Huang, J. J. (2011). Multiple Attribute Decision Making methods and Applications (337 p.). United States of America: CRC Press, Taylor & FrancisGroup.
- Ustinovichius, L., Zavadskas, E. K., & Podvezko, V. (2007). Application of a quantitative multiple criteria decision making (MCDM-1) approach to the analysis of investments in construction. Control and Cybernetics, 36(1), 251-268.
- Uzsilaityte, L., & Martinaitis, V. (2010). Search for optimal solution of public building renovation in terms of life cycle. Journal of Environment Engineering and Landscape Management, 18(2), 102-110.
- Velasquez, M., & Hester, P. T. (2013). An analysis of multi-criteria decision making methods. International Journal of Operations Research, 10(2), 56-66.
- Wang, Y. J. (2015). A fuzzy multi-criteria decision-making model based on simple additive weighting method and relative preference relation. Applied Soft Computing, 30, 412-420.
- Yang, Z. L., Bonsall, S., & Wang, J. (2011). Approximate TOPSIS for vessel selection under uncertain environment. Expert Systems with Applications, 38(12), 14523-14534.
- Zavadskas, E. K., Mardani A., Turskis Z., Jusoh A., & Nor, Kh. (2016). Development of TOPSIS Method to Solve Complicated Decision-Making Problems – An Overview on Developments from 2000 to 2015. International Journal of Technology & Decision Making, 645-682.
- Zavadskas, E. K., & Kaklauskas, A. (1996). Multicriteria Evaluation of Building (Pastatų sistemotechninis įvertinimas) (280 p.). Vilnius: Technika [in Lithuanian].
- Zavadskas, E. K., Turskis, Z., Dejus, T., & Viteikiene, M. (2007). Sensitivity analysis of a simple additive weight method. International Journal of Management and Decision Making, 8(5/6), 555-574.
- Zavadskas, E. K., & Vilutiene, T. (2006) A multiple criteria evaluation of multi-family apartment block’s maintenance contractors: I-model for maintenance contractor evaluation and the determination of its selection criteria. Building and Environment, 41(5), 621-632.
- Zyoud, S. H., & Fuchs-Hanusch, D. (2017). A bibliometric-based survey on AHP and TOPSIS techniques. Expert Systems with Applications, 78(15), 158-181.