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The interplay between human, social and cognitive resources of nascent entrepreneurs

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Abstract

This study integrates human, social and cognitive capital traits into a model of nascent entrepreneurial capital. We hypothesise that the cognitive traits of nascent entrepreneurs play a significant role in moderating the impact of human and social capital endowments on the outcome of the nascent entrepreneurship process. Thus, differences in cognitive traits explain why nascent entrepreneurs with similar stocks of human and social capital resources may experience different outcomes. Using data from the Panel Study of Entrepreneurial Dynamics (PSED), we find that models incorporating cognitive capital traits as moderating variables of human and social capital have a greater explanatory power of nascent entrepreneurship outcomes than models that consider these components of nascent entrepreneurial capital in isolation. The implications of our results are important for researchers, nascent entrepreneurs, venture capitalists and SME support agencies.

Plain English Summary

Nascent entrepreneurs’ cognitive abilities shape the impacts of their human and social capital on success in the new venture creation process. Entrepreneurship starts long before the actual birth of the new venture. Nascent entrepreneurs are those individuals seeking to establish a new business by discovering opportunities, conceiving strategies and obtaining resources. Human capital (the knowledge entrepreneurs derive from their education and work experience) and social capital (the networks of contacts entrepreneurs use to learn about the market and gain access to resources) are recognised as important determinants of success in launching a business. This study finds that cognitive abilities (the psychological dispositions that influence entrepreneurs’ behaviours) also affect the outcome of the nascent entrepreneurship process both directly and by boosting the impacts of human and social capital. This result has implications for researchers as it shows that human and social capital attributes do not act in isolation, but rather interact with cognitive abilities. There are also implications for venture capitalists and SME support agencies. Investment and support decisions need to consider more than the business opportunity and the resources available, as success may hinge on the cognitive abilities of the entrepreneur.

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Notes

  1. One of the measures widely used to determine the point of success in forming a business is the measure of the sales generated. However, according to Davidsson (2006), nascent ventures may generate first sales even before engaging in the business founding activities, and hence this indicator may not reflect a conclusive measure in this respect.

  2. The actual question used in the PSED was: ‘How would you classify the status of your firm? (1) operational and running; (2) you are still setting up the business; (3) you have temporarily delayed your start-up effort; (4) you have completely abandoned your start-up effort’. It is worth noting that, while such subjective measures are widely recognised and used in management studies research (e.g. Parker and Belghitar, 2006; Van Gelderen et al., 2000), variables based on self-perceptions are subject to distortion (Kessler et al., 2012).

  3. This variable is never significant throughout our estimations.

  4. Data sets stemming from large surveys using long and complex questionnaires (as is the case of the PSED) contain high-dimensional data, hindering the researcher’s ability to visualise patterns (Hair et al., 2006). Examination of a reduced dimension data set allows the researcher to spot trends, patterns and outliers in the data.

  5. We acknowledge that there are some inherent issues with this reduction technique which have caused a reduction in its use. For example, there is no guarantee that the dimensions are interpretable. Moreover, variance maximization in the dimensional space of the data under a quadratic constraint may result in a large number of variables loading on the first principal component. In order to overcome these limitations, we use Varimax and Orthomax rotation (Hair et al., 2006).

  6. The PCA analyses conducted for HC, SC and CC are summarised in Appendix 1, available from the authors upon request.

  7. The level of correlation considered worthy of a variable’s inclusion is usually r ≥ 0.3. The correlation matrix was examined for any variable that does not have at least one correlation with another variable where r ≥ 0.3 (Field, 2013).

  8. The criteria used are (a) the interpretability criterion, (b) the eigenvalue-one criterion, (c) the proportion of total variance accounted for and (d) the scree plot test. In particular, visual inspection of the scree plots indicates that four components should be retained for HC, six for SC and four for CC. The scree plots are presented in Appendix 2, available from the authors upon request.

  9. A stepwise selection procedure was used with backward elimination. The procedure starts with a complex model and removes terms sequentially until a further deletion leads to a significantly poorer fit (Field, 2013).

  10. In step 2, a list of possible pairs of variables in the main effects model that have some scientific basis to interact with each other were tested. This consists of all possible pairs. The interaction terms were added one at a time, in the model containing all the main effects.

  11. Logit regression results for human and social capital main effects are presented in Appendix 3, available from the authors upon request.

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Acknowledgements

Support from Fundação para a Ciência e a Tecnologia (FCT) through grant PDTC/EGE-OGE/31152/2017 is gratefully acknowledged.

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Authors and Affiliations

  1. Brunel Business School, Brunel University, London, UK

    Abeer Alomani

  2. DEG, CEG-IST, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001, Lisboa, Portugal

    Rui Baptista

  3. Essex Business School, University of Essex, Colchester, UK

    Suma S. Athreye

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  1. Abeer Alomani
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  2. Rui Baptista
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  3. Suma S. Athreye
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Correspondence to Rui Baptista.

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Alomani, A., Baptista, R. & Athreye, S.S. The interplay between human, social and cognitive resources of nascent entrepreneurs. Small Bus Econ 59, 1301–1326 (2022). https://doi.org/10.1007/s11187-021-00580-8

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