IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v315y2022i2d10.1007_s10479-021-04252-4.html
   My bibliography  Save this article

Reexamining nonlinear effects of intellectual capital on firm efficiency

Author

Listed:
  • Wei-han Liu

    (Southern University of Science and Technology)

  • Qian Long Kweh

    (Canadian University Dubai)

Abstract

This paper first gauges the level of firm efficiency using the Stochastic Nonparametric Envelopment of Data (StoNED) approach. Our firm efficiency score closely reflects a firm’s actual operating conditions when using the statistical foundations of both Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis. Secondly, we estimate the nonlinear effects of intellectual capital on StoNED-based firm efficiency using the Generalized Additive Model (GAM). This model lets us depict the possible nonlinear relationship between explanatory variables and the explained variables in an additive manner. Our analysis of 1898 firm-year observations for U.S.-listed firms from 1999 to 2019 indicates that (i) our sample firms generally have about 65% of room left for improvement that could transform resources into wealth, and (ii) of the three major components of intellectual capital, human capital exhibits a concave-up curve, while structural capital and relational capital both demonstrate an upward trend, with each having an inflection in the middle of that curve. The GAM results remain qualitatively similar even after we re-estimate firm efficiency using the network slacks-based measure DEA model, and (iii) we discuss these comparisons and the respective implications of the three components.

Suggested Citation

  • Wei-han Liu & Qian Long Kweh, 2022. "Reexamining nonlinear effects of intellectual capital on firm efficiency," Annals of Operations Research, Springer, vol. 315(2), pages 1319-1344, August.
  • Handle: RePEc:spr:annopr:v:315:y:2022:i:2:d:10.1007_s10479-021-04252-4
    DOI: 10.1007/s10479-021-04252-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-021-04252-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10479-021-04252-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Jian Xu & Yue Shang & Weizhen Yu & Feng Liu, 2019. "Intellectual Capital, Technological Innovation and Firm Performance: Evidence from China’s Manufacturing Sector," Sustainability, MDPI, vol. 11(19), pages 1-16, September.
    2. Tone, Kaoru & Tsutsui, Miki, 2009. "Network DEA: A slacks-based measure approach," European Journal of Operational Research, Elsevier, vol. 197(1), pages 243-252, August.
    3. Kuosmanen, Timo, 2012. "Stochastic semi-nonparametric frontier estimation of electricity distribution networks: Application of the StoNED method in the Finnish regulatory model," Energy Economics, Elsevier, vol. 34(6), pages 2189-2199.
    4. Michalis Doumpos & Alexis Guyot & Emilios Galariotis & Constantin Zopounidis, 2020. "Assessing the quality of life in French municipalities: a multidimensional approach," Annals of Operations Research, Springer, vol. 293(2), pages 789-808, October.
    5. Léopold Simar & Paul Wilson, 2011. "Two-stage DEA: caveat emptor," Journal of Productivity Analysis, Springer, vol. 36(2), pages 205-218, October.
    6. Daniel Hoechle, 2007. "Robust standard errors for panel regressions with cross-sectional dependence," Stata Journal, StataCorp LP, vol. 7(3), pages 281-312, September.
    7. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-838, May.
    8. Bontis, Nick & Dragonetti, Nicola C. & Jacobsen, Kristine & Roos, Göran, 1999. "The knowledge toolbox:: A review of the tools available to measure and manage intangible resources," European Management Journal, Elsevier, vol. 17(4), pages 391-402, August.
    9. Johnson, Andrew L. & Kuosmanen, Timo, 2012. "One-stage and two-stage DEA estimation of the effects of contextual variables," European Journal of Operational Research, Elsevier, vol. 220(2), pages 559-570.
    10. Tone, Kaoru & Kweh, Qian Long & Lu, Wen-Min & Ting, Irene Wei Kiong, 2019. "Modeling investments in the dynamic network performance of insurance companies," Omega, Elsevier, vol. 88(C), pages 237-247.
    11. Banker, Rajiv & Natarajan, Ram & Zhang, Daqun, 2019. "Two-stage estimation of the impact of contextual variables in stochastic frontier production function models using Data Envelopment Analysis: Second stage OLS versus bootstrap approaches," European Journal of Operational Research, Elsevier, vol. 278(2), pages 368-384.
    12. McDonald, John, 2009. "Using least squares and tobit in second stage DEA efficiency analyses," European Journal of Operational Research, Elsevier, vol. 197(2), pages 792-798, September.
    13. Birger Wernerfelt, 1984. "A resource‐based view of the firm," Strategic Management Journal, Wiley Blackwell, vol. 5(2), pages 171-180, April.
    14. Suryanarayan Mohapatra & Sangram Keshari Jena & Amarnath Mitra & Aviral Kumar Tiwari, 2019. "Intellectual capital and firm performance: evidence from Indian banking sector," Applied Economics, Taylor & Francis Journals, vol. 51(57), pages 6054-6067, December.
    15. Birger Wernerfelt, 1995. "The resource‐based view of the firm: Ten years after," Strategic Management Journal, Wiley Blackwell, vol. 16(3), pages 171-174.
    16. Lawrence Seiford, 1997. "A bibliography for Data Envelopment Analysis (1978-1996)," Annals of Operations Research, Springer, vol. 73(0), pages 393-438, October.
    17. Timo Kuosmanen & Andrew Johnson & Antti Saastamoinen, 2015. "Stochastic Nonparametric Approach to Efficiency Analysis: A Unified Framework," International Series in Operations Research & Management Science, in: Joe Zhu (ed.), Data Envelopment Analysis, edition 127, chapter 7, pages 191-244, Springer.
    18. Chang, Shao-Chi & Chen, Sheng-Syan & Lai, Jung-Ho, 2008. "The effect of alliance experience and intellectual capital on the value creation of international strategic alliances," Omega, Elsevier, vol. 36(2), pages 298-316, April.
    19. Michalis Doumpos & Alexis Guyot & Emilios Galariotis & Constantin Zopounidis, 2020. "Assessing the quality of life in French municipalities: a multidimensional approach," Post-Print hal-02961701, HAL.
    20. Kianto, Aino & Sáenz, Josune & Aramburu, Nekane, 2017. "Knowledge-based human resource management practices, intellectual capital and innovation," Journal of Business Research, Elsevier, vol. 81(C), pages 11-20.
    21. Timo Kuosmanen, 2008. "Representation theorem for convex nonparametric least squares," Econometrics Journal, Royal Economic Society, vol. 11(2), pages 308-325, July.
    22. Muhammad Nadeem & Christopher Gan & Cuong Nguyen, 2018. "The Importance of Intellectual Capital for Firm Performance: Evidence from Australia," Australian Accounting Review, CPA Australia, vol. 28(3), pages 334-344, September.
    23. Chen, Fu-Chiang & Liu, Z.-John & Kweh, Qian Long, 2014. "Intellectual capital and productivity of Malaysian general insurers," Economic Modelling, Elsevier, vol. 36(C), pages 413-420.
    24. Simar, Leopold & Wilson, Paul W., 2007. "Estimation and inference in two-stage, semi-parametric models of production processes," Journal of Econometrics, Elsevier, vol. 136(1), pages 31-64, January.
    25. Qian Long Kweh & Wen-Min Lu & Wei-Kang Wang & Meng-Hsu Su, 2014. "Life Insurance Companies' Performance and Intellectual Capital: A long-term perspective," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 13(04), pages 755-777.
    26. Rajiv D. Banker & Ram Natarajan, 2008. "Evaluating Contextual Variables Affecting Productivity Using Data Envelopment Analysis," Operations Research, INFORMS, vol. 56(1), pages 48-58, February.
    27. Adesina, Kolade Sunday, 2019. "Bank technical, allocative and cost efficiencies in Africa: The influence of intellectual capital," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 419-433.
    28. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    29. Harishankar Vidyarthi, 2019. "Dynamics of intellectual capitals and bank efficiency in India," The Service Industries Journal, Taylor & Francis Journals, vol. 39(1), pages 1-24, January.
    30. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min, 2016. "Research fronts in data envelopment analysis," Omega, Elsevier, vol. 58(C), pages 33-45.
    2. Johnson, Andrew L. & Kuosmanen, Timo, 2012. "One-stage and two-stage DEA estimation of the effects of contextual variables," European Journal of Operational Research, Elsevier, vol. 220(2), pages 559-570.
    3. Christopher F. Parmeter & Valentin Zelenyuk, 2019. "Combining the Virtues of Stochastic Frontier and Data Envelopment Analysis," Operations Research, INFORMS, vol. 67(6), pages 1628-1658, November.
    4. Ioannis E. Tsolas, 2020. "Financial Performance Assessment of Construction Firms by Means of RAM-Based Composite Indicators," Mathematics, MDPI, vol. 8(8), pages 1-16, August.
    5. Afsharian, Mohsen & Kamali, Sara & Ahn, Heinz & Bogetoft, Peter, 2024. "Individualized second stage corrections in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 317(2), pages 563-577.
    6. Wen-Min Lu & Qian Long Kweh & Kai-Chu Yang, 2022. "Multiplicative efficiency aggregation to evaluate Taiwanese local auditing institutions performance," Annals of Operations Research, Springer, vol. 315(2), pages 1243-1262, August.
    7. Banker, Rajiv & Natarajan, Ram & Zhang, Daqun, 2019. "Two-stage estimation of the impact of contextual variables in stochastic frontier production function models using Data Envelopment Analysis: Second stage OLS versus bootstrap approaches," European Journal of Operational Research, Elsevier, vol. 278(2), pages 368-384.
    8. Touati-Tliba, Mohamed, 2024. "Comparative performance of Algeria's education districts: The Influence of colonial legacy through cultural capital," Socio-Economic Planning Sciences, Elsevier, vol. 91(C).
    9. Alessandro Fiorini, 2016. "Technical efficiency in a technological innovation system perspective: The case of bioenergy technologies R&D resources mobilisation in a sample from EU-28," ECONOMICS AND POLICY OF ENERGY AND THE ENVIRONMENT, FrancoAngeli Editore, vol. 2016(2), pages 107-127.
    10. Andrew Johnson & Timo Kuosmanen, 2011. "One-stage estimation of the effects of operational conditions and practices on productive performance: asymptotically normal and efficient, root-n consistent StoNEZD method," Journal of Productivity Analysis, Springer, vol. 36(2), pages 219-230, October.
    11. Lampe, Hannes W. & Hilgers, Dennis, 2015. "Trajectories of efficiency measurement: A bibliometric analysis of DEA and SFA," European Journal of Operational Research, Elsevier, vol. 240(1), pages 1-21.
    12. Calogero Guccio & Marco Ferdinando Martorana & Isidoro Mazza & Giacomo Pignataro & Ilde Rizzo, 2022. "Is innovation in ICT valuable for the efficiency of Italian museums?," European Planning Studies, Taylor & Francis Journals, vol. 30(9), pages 1695-1716, September.
    13. Irene Wei Kiong Ting & Imen Tebourbi & Wen-Min Lu & Qian Long Kweh, 2021. "The effects of managerial ability on firm performance and the mediating role of capital structure: evidence from Taiwan," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-23, December.
    14. Subal C. Kumbhakar & Christopher F. Parmeter & Valentin Zelenyuk, 2022. "Stochastic Frontier Analysis: Foundations and Advances I," Springer Books, in: Subhash C. Ray & Robert G. Chambers & Subal C. Kumbhakar (ed.), Handbook of Production Economics, chapter 8, pages 331-370, Springer.
    15. Yang, Guo-liang & Fukuyama, Hirofumi & Chen, Kun, 2019. "Investigating the regional sustainable performance of the Chinese real estate industry: A slack-based DEA approach," Omega, Elsevier, vol. 84(C), pages 141-159.
    16. Veronese da Silva, Aline & Costa, Marcelo Azevedo & Lopes-Ahn, Ana Lúcia, 2022. "Accounting multiple environmental variables in DEA energy transmission benchmarking modelling: The 2019 Brazilian case," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
    17. Amir Moradi-Motlagh & Ali Emrouznejad, 2022. "The origins and development of statistical approaches in non-parametric frontier models: a survey of the first two decades of scholarly literature (1998–2020)," Annals of Operations Research, Springer, vol. 318(1), pages 713-741, November.
    18. Kosycarz, Ewa & Dędys, Monika & Ekes, Maria & Wranik, Wiesława Dominika, 2023. "The effects of provider contract types and fiscal decentralization on the efficiency of the Polish hospital sector: A data envelopment analysis across 16 health regions," Health Policy, Elsevier, vol. 129(C).
    19. da Silva e Souza, Geraldo & Gomes, Eliane Gonçalves, 2015. "Management of agricultural research centers in Brazil: A DEA application using a dynamic GMM approach," European Journal of Operational Research, Elsevier, vol. 240(3), pages 819-824.
    20. Tsolas, Ioannis E., 2014. "Precious metal mutual fund performance appraisal using DEA modeling," Resources Policy, Elsevier, vol. 39(C), pages 54-60.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:annopr:v:315:y:2022:i:2:d:10.1007_s10479-021-04252-4. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.