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Fat-Tailed Fluctuations in the Size of Organizations: The Role of Social Influence
Stockholm University, Faculty of Social Sciences, Department of Sociology.
Stockholm University, Faculty of Social Sciences, Department of Sociology. Sungkyunkwan University, South Korea; Umeå University, Sweden; Institute for Future Studies, Sweden.
Stockholm University, Faculty of Social Sciences, Department of Sociology. Institute for Future Studies, Sweden.
2014 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 9, no 7, e100527Article in journal (Refereed) Published
Abstract [en]

Organizational growth processes have consistently been shown to exhibit a fatter-than-Gaussian growth-rate distribution in a variety of settings. Long periods of relatively small changes are interrupted by sudden changes in all size scales. This kind of extreme events can have important consequences for the development of biological and socio-economic systems. Existing models do not derive this aggregated pattern from agent actions at the micro level. We develop an agent-based simulation model on a social network. We take our departure in a model by a Schwarzkopf et al. on a scale-free network. We reproduce the fat-tailed pattern out of internal dynamics alone, and also find that it is robust with respect to network topology. Thus, the social network and the local interactions are a prerequisite for generating the pattern, but not the network topology itself. We further extend the model with a parameter delta that weights the relative fraction of an individual's neighbours belonging to a given organization, representing a contextual aspect of social influence. In the lower limit of this parameter, the fraction is irrelevant and choice of organization is random. In the upper limit of the parameter, the largest fraction quickly dominates, leading to a winner-takes-all situation. We recover the real pattern as an intermediate case between these two extremes.

Place, publisher, year, edition, pages
2014. Vol. 9, no 7, e100527
National Category
Sociology
Research subject
Sociology
Identifiers
URN: urn:nbn:se:su:diva-107036DOI: 10.1371/journal.pone.0100527ISI: 000339615200008OAI: oai:DiVA.org:su-107036DiVA: diva2:743063
Note

AuthorCount:3;

Available from: 2014-09-03 Created: 2014-09-02 Last updated: 2017-12-05Bibliographically approved
In thesis
1. Modeling Organizational Dynamics: Distributions, Networks, Sequences and Mechanisms
Open this publication in new window or tab >>Modeling Organizational Dynamics: Distributions, Networks, Sequences and Mechanisms
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The study of how social organizations work, change and develop is central to sociology and to our understanding of the social world and its transformations. At the same time, the underlying principles of organizational dynamics are extremely difficult to investigate. This is partly due to the difficulties of tracking organizations, individuals and their interactions over relatively long periods of time. But it is also due to limitations in the kinds of quantitative methods used to tackle these questions, which are for the most part based on regression analysis.

This thesis seeks to improve our understanding of social organizing by using models to explore and describe the logics of the structures and mechanisms underlying organizational change. Particular emphasis is given to the modeling process, the use of new concepts and analogies, and the application of interdisciplinary methods to get new insights into classical sociological questions.

The thesis consists of an introductory part and five studies (I-V). Using Swedish longitudinal data on employment in the Stockholm Region, the studies tackle different dimensions of organizational dynamics, from organizational structures and growth processes to labor mobility and employment trajectories. The introductory chapters contextualize the studies by providing an overview of theories, concepts and quantitative methods that are relevant for the modeling of organizational dynamics. 

The five studies look into various aspects of organizational dynamics with the help of complementary data representations and non-traditional quantitative methods. Study I analyzes organizational growth statistics for different sectors and industries. The typically observed heavy-tailed statistical patterns for the size and growth rate distributions are broken down into a superposition of interorganizational movements. Study II models interorganizational movements as a labor flow network. Organizations tend to be more tightly linked if they belong to the same ownership sector. Additionally, public organizations have a more stable connection structure. Study III uses a similarity-based method called homogeneity analysis to map out the social space of large organizations in the Stockholm Region. A social distance is then derived within this space, and we find that the interorganizational movements analyzed in Studies I and II take place more often between organizations that are closer in social space and in the same network community. Study IV presents an approach to organizational dynamics based on sequences of employment states. Evidence for a positive feedback mechanism is found for large and highly sequence-diverse public organizations. Finally, Study V features an agent-based model where we simulate a social influence mechanism for organizational membership dynamics. We introduce a parameter analogous to a physical temperature to model contextual influence, and the familiar growth distributions are recovered as an intermediate case between extreme parameter values.

The thesis as a whole provides suggestions for a more process-oriented modeling approach to social organizing that gives a more prominent role to the logics of organizational change. Finally, the series of methodological tools discussed can be useful for the analysis of many other social processes and more broadly for the development of quantitative sociological methods.

Place, publisher, year, edition, pages
Stockholm: Department of Sociology, Stockholm University, 2017. 101 p.
Series
Stockholm studies in sociology, ISSN 0491-0885 ; 67
Keyword
organizational dynamics, social organizing, organizational change, modeling, organizational growth, process stability, labor flow network, employment trajectories, heavy-tailed distributions, complex network analysis, sequence analysis, agent-based modeling, sociophysics
National Category
Sociology
Research subject
Sociology
Identifiers
urn:nbn:se:su:diva-139766 (URN)978-91-7649-673-2 (ISBN)978-91-7649-674-9 (ISBN)
Public defence
2017-03-31, hörsal 11, hus F, Universitetsvägen 10 F, Stockholm, 10:00 (English)
Opponent
Supervisors
Note

At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 1: Manuscript. Paper 2: Manuscript. Paper 3: Manuscript. Paper 4: Manuscript.

 

Available from: 2017-03-08 Created: 2017-02-13 Last updated: 2017-11-13Bibliographically approved

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