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Social Networks and Labour–Education Market System

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Agent-Based Modelling of Social Networks in Labour–Education Market System

Part of the book series: SpringerBriefs in Complexity ((BRIEFSCOMPLEXITY))

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Abstract

Two facts about human beings are widely accepted: they are social creatures and they behave in a bounded rational way. In particular, this results in substantial use of social networks in individual decision-making. Before dealing with the issues of modelling individual behaviour in the labour–education market system, we have to recall some empirical facts known from the literature about this behaviour. This is exactly what this chapter provides.

Educational choice is an outcome deeply intertwined with prior social choices negotiated through structures of constraints and possibilities.

Valentini Moniarou-Papaconstantinou et al. [192, p. 323]

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Notes

  1. 1.

    From these two terms follow two kinds of matrix representations of a graph: with an incidence matrix (M ij inc = 1 if vertex i and edge j are incident) and with an adjacency matrix (M ij adj = 1 if vertex i and vertex j are adjacent).

  2. 2.

    There are also two larger groupings: mega-band level (around 500 individuals) and large tribe level (around 1500 individuals) [99].

  3. 3.

    A clique is a set of vertices where each vertex is connected with all other vertices from the set.

  4. 4.

    The constant ensures that probabilities sum to one.

  5. 5.

    The departure of degree distribution from power law for degrees above 105 was attributed to a large number of celebrities and large corporations using Twitter.

  6. 6.

    See [190] for a lengthier treatment on the similarities between power law and log-normal distributions.

  7. 7.

    The Big Five or the Five Factor Model is a model that defines five main personality traits: openness, conscientiousness, extroversion, agreeableness and neuroticism [72]. This is considered to be the “default model of personality structure” nowadays [184, p. 15].

  8. 8.

    See also [213] and [92, p. 371, Footnote 17].

  9. 9.

    But see, e.g., [131, 205] on the antecedents of collective (group, unit or organisation-level) turnover.

  10. 10.

    Another intensively studied effect from job satisfaction is on job performance. On average, job satisfaction and job performance have a correlation of 0.30 [150], although there are several moderators of this relationship. For instance, the correlation is higher (0.52) in high complexity jobs, in part because these jobs have fewer constraints on employee behaviour [150]. It is also higher for individuals with higher affective–cognitive consistency, i.e., when the emotional feeling about something (the affective component of the attitude) is consistent with the beliefs or thoughts about it (its cognitive component) [234, 287]. Performance in itself affects turnover, as will be discussed below.

  11. 11.

    Co-workers’ job embeddedness acts in the same direction [107].

  12. 12.

    A similar result is reported in [66], where internal and external network sizes were used instead.

  13. 13.

    Some studies point at a U-shaped effect from the number of children [4, 237] and age [235, 246].

  14. 14.

    Training was also found to increase the intention to quit [94, 160].

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    Alexander Tarvid

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Tarvid, A. (2016). Social Networks and Labour–Education Market System. In: Agent-Based Modelling of Social Networks in Labour–Education Market System. SpringerBriefs in Complexity. Springer, Cham. https://doi.org/10.1007/978-3-319-26539-1_1

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