Effects of Team Collaboration on Sharing Information Security Advice

Active sharing of information security advice among the employees has undeniable implications for developing a sustainable security environment. This research examines this topic from the network perspective, and focuses on the work relationships that promote sharing security advice. Exponential random graph modeling technique was employed to evaluate the relationship between team collaborative activities and sharing security advice. The findings revealed that those who share security advice also tend to give work- and IT-related knowledge. Moreover, employees who have similar tenure tend to exchange security advice with each other more. Furthermore, the network of sharing security advice is transitive and has a tendency to form separate clusters. Security managers are suggested to take into account the research findings to identify key employees who frequently share security advice in the workplace and devise appropriate strategies to manage them.

Pillanatkép a Budapesti Értéktőzsde tulajdonviszonyainak hálózatáról

Tanulmányomban a hálózatkutatás eszköztárával tárom fel a Budapesti Értéktőzsdén a 2020-ban kibocsátóként jelen lévő entitások tulajdonviszonyainak hálózatát, statikus módszerek, valamint exponential random graph modeling (ERGM) elemzés alapján. A hálózat pillanatkép-tipológiája és szimuláció alapú megragadása során nem pusztán a tőzsdén jelen levő kibocsátók közötti kapcsolathálózat kerül elemzésre, hanem a hálózathoz kapcsolódó, ám a tőzsdén nem jegyzett cégek tulajdonviszonyai is, így a tanulmány teljes egészében kezeli az értéktőzsdéhez kapcsolódó tulajdonosi hálózatot. A kutatás eredményeként pontos válasszal rendelkezünk a hálózat morfológiai tulajdonságáról, a centralitást meghatározó hálózati faktorokról, a hálózat hierarchiájáról, valamint a szimulációk segítségével a hálózat kialakulásáról. A tanulmány hozzásegíthet ahhoz, hogy tisztább képet kapjunk a tőzsdén jegyzett cégek kapcsolódási pontjairól, klasztereiről, amelyek későbbi longitudinális elemzésekhez adhatnak támpontot.

Health coalition collaboration network, perceived satisfaction and success

PurposeThe health equity and prosperity of communities is closely linked to the effectiveness and success of local health coalitions. Social network analysis (SNA) is one mechanism to quantify and understand the factors leading to collaboration and effectiveness within these coalitions. This study aims to investigate network characteristics associated with perceived success and satisfaction in a health coalition and determine significant factors related to organizational collaborations.Design/methodology/approachThis study examined the Olympic Peninsula Healthy Community Coalition (OPHCC) which aims to prevent chronic disease in rural Clallam County, Washington. Representatives (n = 21) from member organizations (n = 18) were asked to report on organization characteristics, perceived satisfaction in coalition activities, perceived success toward coalition's mission, and collaborations with other organizations in the coalition. Multilevel modeling used to analyze whether an organization's position within the coalition network was associated with their perceived satisfaction and perceived success. Exponential random graph modeling was used to examine what factors may impact collaboration ties between coalition members.FindingsOrganization representatives reported a total of 252 collaboration ties. In multilevel models, organization characteristics and network centrality scores accounted for between 61 and 68% of variance displayed in satisfaction scores and 45–61% of variance in perceived success scores. Exponential random graph modeling revealed activity level, for-profit status, and transitivity as significant factors in collaborative tie presence.Originality/valueEncouraging consistent active participation, a balance of organizational type, and projects which require more than two collaborators may provide an environment for collaborative ties between organizations.

The Big Bird Gets the Worm? How Size Influences Social Networking by Charitable Organizations

Current evidence suggests that nonprofits’ use of Twitter is not strongly related to organizational size, unlike other technological developments. However, this evidence is primarily based on studies of large nonprofit organizations. This study uses a random sample of charities, stratified by size, to present evidence that organization size is a significant factor in multiple dimensions of social media use: the percentage of charities owning a Twitter handle, activity on the site, and popularity within the charities’ network. Many charities are using Twitter, but larger charities are making more effective use of the platform to connect to other organizations. The very largest charities exhibit an overwhelming popularity effect in the network, whereas small charities are notably less active than their larger counterparts. Besides the substantive findings, we further demonstrate the methodological potential of using exponential random graph modeling to gain a deeper understanding of the characteristics of nonprofits’ social media networks.

Marginality and team building in collaborative crowdsourcing

PurposeExisting studies on crowdsourcing have focused on analyzing isolated contributions by individual participants and thus collaboration dynamics among them are under-investigated. The value of implementing crowdsourcing in problem solving lies in the aggregation of wisdom from a crowd. This study examines how marginality affects collaboration in crowdsourcing.Design/methodology/approachWith population level data collected from a global crowdsourcing community (openideo.com), this study applied social network analysis and in particular bipartite exponential random graph modeling (ERGM) to examine how individual level marginality variables (measured as the degree of being located at the margin) affect the team formation in collaboration crowdsourcing.FindingsSignificant effects of marginality are attributed to collaboration skills, number of projects won, community tenure and geolocation. Marginality effects remain significant after controlling for individual level and team level attributes. However, marginality alone cannot explain collaboration dynamics. Participants with leadership experience or more winning ideas are also more likely to be selected as team members.Originality/valueThe core contribution this research makes is the conceptualization and definition of marginality as a mechanism in influencing collaborative crowdsourcing. This study conceptualizes marginality as a multidimensional concept and empirically examines its effect on team collaboration, connecting the literature on crowdsourcing to online collaboration.

Network Structural Equivalence and Public Sectors’ Organizational level of Influence in Information Sharing Network:a Social Network Methodology

Structural equivalence has been a fascinating topic for industry and academia due to its connection with network embeddedness. This study investigates the network assumption that structural equivalence is a major determinant of influence derives largely from the frequent finding that organizations that are embedded with influential connections are at an increased likelihood of becoming influential themselves. It is suggested that the strong and consistent structural equivalence position is at least partially responsible for factors of reputational influence among directors of government agencies. The contribution of this study continues to enrich the literature of the network and provide the solution for the industry since earlier research is neglecting the impact of relations upon the level of influence. Using exploratory social network methodology and statistical evaluation of Exponential Random Graph Modeling, this research found that, directors of government agencies may gain greater influence via its structural equivalence position in an informal network. It is also, argued that social network methodology is an appropriate method for researching influence development use in the context of networked organizations. The contribution of this study to industry and theory are discussed.