Journal of Enterprise and Business Intelligence


Prioritizing Intellectual Capital Assets for Strategic Investment Using an Analytic Network Process Approach



Journal of Enterprise and Business Intelligence

Received On : 10 January 2024

Revised On : 02 March 2024

Accepted On : 20 March 2024

Published On : 05 July 2024

Volume 04, Issue 03

Pages : 126-136


Abstract


Intellectual Capital Assets (ICAs) refer to the intangible resources that are critical to the creation of organizational value out of human, customer, innovation and process capital. High impact ICAs should be identified and prioritized for investment in by organizations as they strive to increase their value. This research aims at assessing and ranking ICAs by using Analytic Network Process (ANP) model for capturing the interactions between the assets. The method used to gather the pairwise data aimed at supervising CEOs, scientific supervisors, shareholders, employees and customers in order to determine the relative value each ICA contributes to value creation. A mathematical model is employed to translate qualitative assessments into quantitative results with regard to Consistency Index (CI) and Consistency Ratio (CR) to check the reliability of the judgments. Cost benefit analysis shows the ICAs which yield the greatest return on investment. Our findings suggest that knowledge sharing and innovation are the most dominant ICA that positively and significantly affects value creation. These assets involve moderate investment but have huge returns, while other assets such as employee training and customer relations also have greater potential but involve high investment. The results offer practical guidance to organizations in terms of how to effectively prioritize ICAs to support their achievement of strategic objectives in creating innovative value.


Keywords


Intellectual Capital Assets, Analytic Network Process, Knowledge Sharing, Consistency Ratio, Consistency Index, Value Creation Process.


  1. S. Hess and R. Y. Siegwart, “University Technology Incubator: Technology Transfer of Early Stage Technologies in Cross-Border Collaboration with Industry,” Business and Management Research, vol. 2, no. 2, May 2013, doi: 10.5430/bmr.v2n2p22.
  2. U. E. Hansen and R. Lema, “The co-evolution of learning mechanisms and technological capabilities: Lessons from energy technologies in emerging economies,” Technological Forecasting and Social Change, vol. 140, pp. 241–257, Jan. 2019, doi: 10.1016/j.techfore.2018.12.007.
  3. A. Bahoo‐Torodi, “Spawned by opportunity or out of necessity? Organizational antecedents and the choice of industry and technology in employee spinouts,” Strategic Entrepreneurship Journal, Jun. 2024, doi: 10.1002/sej.1511.
  4. L. Cricelli, M. Greco, and M. Grimaldi, “The assessment of the intellectual capital impact on the value creation process: a decision support framework for top management,” International Journal of Management and Decision Making, vol. 12, no. 2, p. 146, Jan. 2013, doi: 10.1504/ijmdm.2013.054460.
  5. A. M. Asfahani, “The Complementary Relationship between Human Resources Accounting and Human Resources Information System,” Open Journal of Accounting, vol. 10, no. 02, pp. 30–41, Jan. 2021, doi: 10.4236/ojacct.2021.102004.
  6. L. Edvinsson and P. Sullivan, “Developing a model for managing intellectual capital,” European Management Journal, vol. 14, no. 4, pp. 356–364, Aug. 1996, doi: 10.1016/0263-2373(96)00022-9.
  7. C.-J. Chen, H.-A. Shih, and S.-Y. Yang, “The role of intellectual capital in knowledge transfer,” IEEE Transactions on Engineering Management, vol. 56, no. 3, pp. 402–411, Jun. 2009, doi: 10.1109/tem.2009.2023086.
  8. S. Jackson, “Organizational culture and information systems adoption: A three-perspective approach,” Information and Organization, vol. 21, no. 2, pp. 57–83, Apr. 2011, doi: 10.1016/j.infoandorg.2011.03.003.
  9. O. Lentjušenkova and I. Lapina, “The transformation of the organization’s intellectual capital: from resource to capital,” Journal of Intellectual Capital, vol. 17, no. 4, pp. 610–631, Sep. 2016, doi: 10.1108/jic-03-2016-0031.
  10. C. Wang, J. Xuan, I.-M. Shih, R. Clarke, and Y. Wang, “Regulatory component analysis: A semi-blind extraction approach to infer gene regulatory networks with imperfect biological knowledge,” Signal Processing, vol. 92, no. 8, pp. 1902–1915, Dec. 2011, doi: 10.1016/j.sigpro.2011.11.028.
  11. J. L. Volakis, T. F. Eibert, D. S. Filipovic, Y. E. Erdemli, and E. Topsakal, “Hybrid finite element methods for array and FSS analysis using multiresolution elements and fast integral techniques,” Electromagnetics, vol. 22, no. 4, pp. 297–313, May 2002, doi: 10.1080/02726340290083905.
  12. T. L. Saaty and L. T. Tran, “On the invalidity of fuzzifying numerical judgments in the Analytic Hierarchy Process,” Mathematical and Computer Modelling, vol. 46, no. 7–8, pp. 962–975, Apr. 2007, doi: 10.1016/j.mcm.2007.03.022.
  13. E. Morse et al., “Tolerancing: Managing uncertainty from conceptual design to final product,” CIRP Annals, vol. 67, no. 2, pp. 695–717, Jan. 2018, doi: 10.1016/j.cirp.2018.05.009.
  14. L. Sepulveda, “Social enterprise – a new phenomenon in the field of economic and social welfare?,” Social Policy and Administration, vol. 49, no. 7, pp. 842–861, Nov. 2014, doi: 10.1111/spol.12106.
  15. S. L. Albrecht, A. B. Bakker, J. A. Gruman, W. H. Macey, and A. M. Saks, “Employee engagement, human resource management practices and competitive advantage,” Journal of Organizational Effectiveness People and Performance, vol. 2, no. 1, pp. 7–35, Mar. 2015, doi: 10.1108/joepp-08-2014-0042.
  16. D. J. Teece, “Technological innovation and the theory of the firm,” in Handbook of the economics of innovation, 2010, pp. 679–730. doi: 10.1016/s0169-7218(10)01016-6.
  17. G. M. Spreitzer, “Quinn, Robert E.: The Paradoxical Mind that Inspires Positive Change,” in Springer eBooks, 2020, pp. 1–19. doi: 10.1007/978-3-319-49820-1_54-2.

Acknowledgements


Authors thank Reviewers for taking the time and effort necessary to review the manuscript.


Funding


No funding was received to assist with the preparation of this manuscript.


Ethics declarations


Conflict of interest

The authors have no conflicts of interest to declare that are relevant to the content of this article.


Availability of data and materials


No data available for above study.


Author information


Contributions

All authors have equal contribution in the paper and all authors have read and agreed to the published version of the manuscript.


Corresponding author


Rights and permissions


Open Access This article is licensed under a Creative Commons Attribution NoDerivs is a more restrictive license. It allows you to redistribute the material commercially or non-commercially but the user cannot make any changes whatsoever to the original, i.e. no derivatives of the original work. To view a copy of this license, visit https://creativecommons.org/licenses/by-nc-nd/4.0/


Cite this article


Mafanasy Eva, “Prioritizing Intellectual Capital Assets for Strategic Investment Using an Analytic Network Process Approach”, Journal of Enterprise and Business Intelligence, vol.4, no.3, pp. 126-136, July 2024. doi: 10.53759/5181/JEBI202404013.


Copyright


© 2024 Mafanasy Eva. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.