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How to improve SME performance using iterative random forest in the empirical analysis of institutional complementaritty

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  • Atsushi Sannabe

    (Ryutsu Keizai University)

Abstract

Empirically investigating the workings of institutional complementarity in organisations has been a challenge in the social sciences domain for a long time. This paper examines data from the World Management Survey (WMS) using a new machine learning method termed as iterative random forest (iRF), which is used in the field of biostatistics. An empirical study of complementarity was conducted in small and medium-sized enterprises using WMS data. The effects of 18 management quality indicators on profitability, growth and viability were examined using machine learning methods (i.e. random forest [RF] and iRF). The analysis revealed the relative importance of whether high performers are properly rewarded, poor performers are reassigned and retrained and the criteria for high and low performance are well established. Furthermore, the study results revealed that the ability to set short-term goals based on a long-term perspective is complementary to many other indicators. These findings are consistent with the findings of a survey study that examined many empirical studies on the workings of institutional complementarity. This indicates that iRF is a credible and promising method for empirical research on institutional complementarity.

Suggested Citation

  • Atsushi Sannabe, 2022. "How to improve SME performance using iterative random forest in the empirical analysis of institutional complementaritty," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-9, December.
  • Handle: RePEc:pal:palcom:v:9:y:2022:i:1:d:10.1057_s41599-022-01123-6
    DOI: 10.1057/s41599-022-01123-6
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    1. Nicholas Bloom & Benn Eifert & Aprajit Mahajan & David McKenzie & John Roberts, 2013. "Does Management Matter? Evidence from India," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 128(1), pages 1-51.
    2. Burdin, Gabriel & Kato, Takao, 2021. "Complementarity in Employee Participation Systems," GLO Discussion Paper Series 968, Global Labor Organization (GLO).
    3. Nicholas Bloom & Christos Genakos & Raffaella Sadun & John Van Reenen, 2011. "Management Practices Across Firms and Countries," CEP Discussion Papers dp1109, Centre for Economic Performance, LSE.
    4. Burdin, Gabriel & Kato, Takao, 2021. "Complementarity in Employee Participation Systems: International Evidence," IZA Discussion Papers 14694, Institute of Labor Economics (IZA).
    5. Edward P. Lazear, 2000. "Performance Pay and Productivity," American Economic Review, American Economic Association, vol. 90(5), pages 1346-1361, December.
    6. Athey, Susan. & Stern, Scott, 1969-, 1998. "An empirical framework for testing theories about complementarity in orgaziational design," Working papers WP 4022-98., Massachusetts Institute of Technology (MIT), Sloan School of Management.
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    Cited by:

    1. Delin Du & Jiaoe Wang & Jianjun Li, 2024. "What drives intercity venture capital investment? A comparative analysis between multiple linear regression and random forest," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-13, December.

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