<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Problem-solving effectiveness is key to organizational performance. To solve problems, gathering information from colleagues is critical, and positioning brokerage in communication networks is beneficial. The communication network for problem-solving is formed depending on the nature of the problem. Thus, the problem-solving network is the relational event network, and the connection of the problem-solving network dynamically changes over time depending on the problem basis. This study investigates the dynamics of brokerage in a problem-solving network and its impact on productivity in a company that provides technical support and troubleshooting for the IT system that its corporate customers use. By exploiting high-frequency data on face-to-face communication among employees collected by wearable sensors, we established the following results. First, the communication partners of each employee change weekly, which is a reasonable time to solve problems in the company. Second, with the change in the communication network, employees who position brokerage also change on a weekly basis. Third, while brokerage in a week has a positive impact on employee performance during the week, it has no impact on employee performance in the following week.</p>
</abstract>

Graduate School of Management and Information of Innovation

The Impact of Brokerage in a Communication Network on Productivity: Evidence from Sensor Data

<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Fractals describe structural details at arbitrarily small scales, but are mathematically not necessarily complex, presenting a pragmatic way of describing nature. They are also common in social settings, including the organizational space. However, attention has been devoted to temporal fractal patterns in heterarchical or networked organizations. This article leverages data on face-to-face interactions collected by the SocioPatterns collaboration in a public sector organization to investigate temporal fractal patterns in interaction networks and three types of processes have been identified in this. White noise exhibits no correlation in time with rapid, chaotic changes. Brown noise entails a diffusion process with stable, structural patterns, but no quick adaptation. Pink noise exhibits an equilibrium between the two, producing dynamics that maintain stable patterns of interactions, remaining flexible to regulate interaction. The interaction network is described with metrics of social network analysis, and analyzed with detrended fluctuation analysis (DFA) to detect temporal fractal patterns within the three largest departments as well as the whole organization. Results indicate high levels of pink noise with traces of white noise in the departments as well as pink noise with traces of brown noise on the organizational level. While previous research found pink noise processes in self-organizing networks, this article extends them to structured intraorganizational networks. The low levels of brown noise question the influence of rigid organizational structures and processes on the temporal structure of interaction. Hence, the fractal temporal structure of the interactions themselves is a factor that contributes to the stability of interactions between individuals over time.</p>
</abstract>

Fractals Beyond Hierarchy—Analyzing the Temporal Patterns of Contact Networks in a French Public Sector Organization

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Connections

Connections publishes original empirical, theoretical, and methodological articles, as well as critical reviews dealing with applications of social network analysis. From volume 2018 the journal is published in a continous format.  The research spans many disciplines and domains including: Anthropology, Sociology, Psychology, Communication, Economics, Organizational Behavior, Knowledge Management, Marketing, Social Psychology, Mathematics, Public Health, Medicine, Computer Science, and Policy.  As an official journal of the International Network for Social Network Analysis, the emphasis of the publication is to reflect the ever-growing and continually expanding community of scholars using network analytic techniques. Connections also provides an outlet for sharing news about social network concepts and techniques and new tools for research.  Rejection rate: 60%  Open Access Policy  This journal provides immediate open access to its content under the Creative Commons CC BY 4.0 license on the principle that making research freely available to the public supports a greater global exchange of knowledge. Under the Creative Commons CC BY 4.0 license users are free to share (copy and redistribute the material in any medium or format) and adapt the work (remix, transform, and build upon the material for any purpose, even commercially) if the contribution was properly attributed and all of the changes indicated.  ABOUT SOCIETY  International Network for Social Network Analysis is the professional association for researchers interested in social network analysis. The association is a non-profit organization incorporated in the state of Delaware and founded by Barry Wellman in 1977.  INSNA was founded on the premise that the behavior and lives of social entities are affected by their position in the overall social structure. By examining the etiology and consequences of structural forms overall, of the location of entities within these structures, and of the formation and dynamics of ties that make up these structures, INSNA hopes to learn about the parts of behavior that are uniquely social.  Archiving  Sciendo archives the contents of this journal in Portico - digital long-term preservation service of scholarly books, journals and collections.  Plagiarism Policy  The editorial board is participating in a growing community of Similarity Check System's users in order to ensure that the content published is original and trustworthy. Similarity Check is a medium that allows for comprehensive manuscripts screening, aimed to eliminate plagiarism and provide a high standard and quality peer-review process.

Connections

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The Impact of Brokerage in a Communication Network on Productivity: Evidence from Sensor Data

Fractals Beyond Hierarchy—Analyzing the Temporal Patterns of Contact Networks in a French Public Sector Organization

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