Auswahl der wissenschaftlichen Literatur zum Thema „Stochastic Actor-Oriented Modelling“

Digital technologies have been increasingly embedded in students’ everyday lives. Interest-driven socio-digital participation (ISDP) involves students’ pursuit of interests mediated by computers, social media, the internet, and mobile devices’ integrated systems. ISDP is likely to intertwine closely with young people’s social networks that has been scarcely studied quantitatively. To close this gap, the present paper investigated students’ peer selection and influence effects of the intensity of their ISDP and friendship networks. We collected two-wave data by administering a peer nomination to trace students’ friendship networks with peers and a self-reported questionnaire to examine students’ ISDP. Participants were 100 students in Finland (female: 53%; mean age = 13.48, in grade 7 in the first wave). Through stochastic actor-oriented modelling, the results showed that the students’ friendship ties with peers influenced the intensity of their ISDP practices to become more similar. Yet, students did not select peers as friends based on similar intensity levels of ISDP. Utilizing influence effect found in students’ ISDP and their peer networks, we suggest that connected learning (Ito et al., 2013) should be promoted to integrate students’ informal and formal learning in order to bridge the gap between students’ informal interest-related digital practices and formal educational practices.

Behavioural information security (InfoSec) research has studied InfoSec at workplaces through the employees’ perceptions of InfoSec climate, which is determined by observable InfoSec practices performed by their colleagues and direct supervisors. Prior studies have identified the antecedents of a positive InfoSec climate, in particular socialisation through the employees’ discussions of InfoSec-related matters to explain the formation of InfoSec climate based on the employees’ individual cognition. We conceptualise six forms of socialisation as six networks, which comprise employees’ provisions of (1) work advice, (2) organisational updates, (3) personal advice, (4) trust for expertise, (5) InfoSec advice, and (6) InfoSec troubleshooting support. The adoption of a longitudinal social network analysis (SNA), called stochastic actor-oriented modelling (SAOM), enabled us to analyse the changes in the socialising patterns and the InfoSec climate perceptions over time. Consequently, this analysis explains the forming mechanisms of the employees’ InfoSec climate perceptions as well as their socialising process in greater detail. Our findings in relation to the forming mechanisms of InfoSec-related socialisation and InfoSec climate, provide practical recommendations to improve organisational InfoSec. This includes identifying influential employees to diffuse InfoSec knowledge within a workplace. Additionally, this research proposes a novel approach for InfoSec behavioural research through the adoption of SNA methods to study InfoSec-related phenomena.

This thesis addresses the relationship between institutions and foreign direct investments (FDI). While the issue of how institutions attract FDI (selection) is quite well-researched, the empirical evidence for institutions spreading through FDI (influence) is more ambiguous. We argue that past studies have neglected issues of endogeneity and interdependence in their modelling. We amend these issues by using a Stochastic Actor-Oriented network model which allows for interdependent and endogenous processes. The thesis also addresses the mechanisms governing the general relation between FDI and institutions and what these can tell us about institutional change and the process of globalisation. The model provides no evidence that FDI helps to spread institutions from home to host countries, but it does provide evidence that the selection effect can be an important dynamic between FDI and a certain set of institutions. Finally, we argue that FDI does not seem to be a contributory factor to institutional convergence.