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Methodology and Statistical Modeling of Social Capital Influence on Employees’ Individual Innovativeness in a Company

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  • Ekaterina V. Orlova

    (Department of Economics and Management, Ufa State Aviation Technical University, 450000 Ufa, Russia)

Abstract

The research deals with the problem of identification and substantiation of mechanisms of social capital influence on individual innovativeness of employees, which increases the positive innovation effect in companies. The study proposes a new methodological approach and technology for assessing the social capital of employees, taking into account the factors of interpersonal and institutional trust, involvement in social networks, social norms, and its impact on the employee’s innovativeness. The methodology uses methods of system analysis and synthesis, expert assessments, statistical modeling, and survey. Numerical experiments are carried out using collected data from special surveys of employees of a machine-building company. An assessment of social capital and its impact on the employee’s innovativeness is determined and a statistically significant influence of the factors of “trust” and “social networks and connections” on social capital is set. It is revealed that the main determinant of innovativeness is the risk appetite. It is proved that the innovativeness model includes factors of “trust” and “social networks and connections”. The cumulative effect of social capital on innovativeness is positive and statistically significant.

Suggested Citation

  • Ekaterina V. Orlova, 2022. "Methodology and Statistical Modeling of Social Capital Influence on Employees’ Individual Innovativeness in a Company," Mathematics, MDPI, vol. 10(11), pages 1-22, May.
  • Handle: RePEc:gam:jmathe:v:10:y:2022:i:11:p:1809-:d:823661
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    Cited by:

    1. Ekaterina V. Orlova, 2022. "Design Technology and AI-Based Decision Making Model for Digital Twin Engineering," Future Internet, MDPI, vol. 14(9), pages 1-14, August.
    2. Ekaterina V. Orlova, 2023. "Inference of Factors for Labor Productivity Growth Used Randomized Experiment and Statistical Causality," Mathematics, MDPI, vol. 11(4), pages 1-22, February.
    3. Ekaterina V. Orlova, 2023. "Dynamic Regimes for Corporate Human Capital Development Used Reinforcement Learning Methods," Mathematics, MDPI, vol. 11(18), pages 1-22, September.

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