Understanding Organizational Approach towards End User Privacy

This research employed a longitudinal social network analysis (SNA) method, called stochastic actor-oriented modelling (SAOM), to analyse the inter-relationship between the employees’ socialisation and information security (IS) climate perceptions which are the employees’ perceptions of their colleagues and supervisors’ IS practices. Unlike prior studies, we conceptualised socialisation in the form of six networks: the exchange of work advice and of organisational updates, the provision of personal advice, interpersonal trust in expertise, the provision of IS advice, and support for IS troubleshooting. The adoption of the SAOM method enabled not only analysis of why an employee chooses to interact with or to send a network tie to another employee, but also how an employee’s perception of IS climate is affected by the ties that they possess in the network. This research suggests new directions for IS behavioural research based on the adoption of SNA methods to study IS-related perceptions and behaviours, while findings about the selection and influence mechanisms offer theoretical insights and practical methods to enhance IS in the workplace

Understanding the Formation of Information Security Climate Perceptions: A Longitudinal Social Network Analysis

Business process capture is a first step in the larger endeavour of business process management. In this paper we view business process capture as a knowledge conversion process. We explore the conversion of knowledge when business analysts capture information about business processes from domain experts. We identify seven process capture activities in a thematic analysis of comments made by business analysts in response to open-ended questions in an online survey. The seven activities are involving, simplifying, tailoring, training, combining, confirming, and engaging soft skills. We show how these activities involve the transfer of tacit and explicit knowledge between the business analyst and the domain expert and how the transfer conforms to the SECI modes of knowledge conversion, well known in the research domain of knowledge management. The paper contributes a SECI-based knowledge conversion model of business process capture and insight for business analysts about business process capture activities

The dynamics of social networks:Towards a better understanding of selection and influence mechanisms in social capital building

This chapter discusses how longitudinal network analysis can be useful for theory development, especially social capital theory. Established social capital theories refer to the access and use of resources (e.g., information, knowledge) in the network. Various resources enable individuals to achieve their individual goals, such as passing exams and obtaining a job. A longitudinal social network approach provides a better understanding of how networks change over time and how the underlying selection and influence mechanisms contribute to social capital formation and, hence, to performance or attitude changes. Selection and social influence are crucial social network mechanisms, but these mechanisms are not explicitly addressed in social capital theory. The longitudinal social network approach, stochastic actor-oriented modelling (SAOM), enables us to disentangle selection from influence. This is illustrated by students’ social capital building in peer networks in higher education. Higher education students establish social capital when they interact with their peers within the learning context. They select each other when they need academic help (selection) or the academic help relationships may impact students’ grades (social influence). Overall, SAOM can provide a better understanding of social network dynamics and advance social theories, such as the social capital theory.</p

Peer selection and influence: Students’ interest-driven socio-digital participation and friendship networks

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.</p

Peer selection and influence

Peer reviewe

Cluster analysis of regional innovation activity in Russia in 2010-2015

In this article, the indicators of innovation activity in Russian regions are discussed and the regions are divided into five groups, according to their performance in these indicators. Our cluster analysis is based on the recent research and includes several groups of indicators such as innovation activity of enterprises, training of highly qualified personnel, research and development, state support for innovation, and application of innovative technologies. We used the data provided by Rosstat (Federal State Statistics Service) for 83 Russian regions in the period between 2010 and 2015. In terms of their innovation activity, Russian regions can be divided into five groups, two of which are Moscow and St.Petersburg, the two biggest Russian cities that play a special role in Russian economy. Overall, the level of innovation activity in Russia can be assessed as lower middle, although in the given period some regions managed to improve their performance in this sphere. The average level of innovation activity varies considerably across regions, which means that the state innovation policy should be more diversified. Moscow, St.Petersburg, Nizhny Novgorod and Sverdlovsk regions have demonstrated consistent high-level performance and can thus be regarded as prospective centres of innovation. These centres can positively influence the neighbouring areas through the knowledge and technology spillover effect. Although no definitive conclusion can be drawn about the connection between the regions' geographical location and their innovation activity, there is evidence that the most active Russian regions tend to concentrate in the European part of the country. Our findings can be used as guidelines for devising and modifying federal and regional innovation policies.This research was supported by RFBR, research project 18-010-01190 А ' Models of innovation development factors and comparative advantages analysis in the Russian economy’

Middle manager’s innovative work behavior and their social network position:A search on slippery ice

Central to this dissertation is the question why some middle managers are more innovative than others. This question has been examined from three related perspectives. A primary role of middle managers consists of analyzing, processing and passing on information. Middle managers maintain intensive contacts with, among others, other middle managers. Therefore it has been investigated how the structure of a social network facilitates or limits innovative behavior. Secondly, it was investigated to what extent individual characteristics influence innovative behavior. Individual characteristics determine how a middle manager deals with opportunities and restraints. The third factor focuses on the complexity of modern organizations. Middle managers often operate in organizations with multiple locations that are at a certain distance from the head office and in complex partnerships such as franchising or joint ventures. Such complex structures influence the autonomy and thus possibly the innovative behavior of middle managers. Three empirical studies have been carried out: Students of a business school, an international company with a complex organizational structure and multiple locations, and the administration of a municipality in Mexico City. In addition, a simulation study was carried out to determine an optimal strategy for dealing with missing data in the network analyses carried out. The results suggest that innovative behavior of middle managers is likely to be influenced by individual differences in personality and goal orientation. Potential influences of network position were not found. Influence of organizational factors related to autonomy could not be identified

How do teachers exercise relational agency for supporting migrant students within social networks in schools from Scotland, Finland, and Sweden?

This study examines how teachers exercise relational agency - working flexibly with other actors in their social networks to support migrant students. Teachers and other staff members from 7 schools in Scotland, Finland and Sweden participated in social network surveys (n = 1116), online logs (n = 275) and interviews (n = 82). A mixed-method social network analysis shows how networks facilitate relational agency as teachers reach out to others to mobilise resources and tacit knowledge within their school communities. The findings point to the critical role of professional collaboration and suggest that social networks shape how teachers work with specialists to support migrant students.</p