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Modeling Organizational Dynamics: Distributions, Networks, Sequences and Mechanisms
Stockholm University, Faculty of Social Sciences, Department of Sociology.ORCID iD: 0000-0003-2685-9238
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 [en]
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: urn:nbn:se:su:diva-139766ISBN: 978-91-7649-673-2 (print)ISBN: 978-91-7649-674-9 (electronic)OAI: oai:DiVA.org:su-139766DiVA: diva2:1073822
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
List of papers
1. Informing organizational growth models with longitudinal individual-level data: Sector, industry and inter-organizational movement statistics in the Stockholm Region
Open this publication in new window or tab >>Informing organizational growth models with longitudinal individual-level data: Sector, industry and inter-organizational movement statistics in the Stockholm Region
(English)Manuscript (preprint) (Other academic)
Abstract [en]

Organizational growth processes exhibit interesting statistical regularities, chiefly the heavy-tailed pattern of the size and growth-rate (i.e. yearly change in size) distributions. In spite of its ubiquity, empirical studies of growth are often limited to private activities and specific sectors, and generative models on the other hand are built on simplified assumptions and only aim at reproducing stylized facts. In this study, we use a unique Swedish longitudinal database on employment in the Stockholm Region, to analyze the interplay between organizational growth statistics by ownership sector, industrial activity and inter-organizational employee movements during a period of 14 years. We fit distributions for organizational size and growth rates. We find that the body of the aggregate growth-rate distribution is dominated by public sector growth, while the private sector dominates the tails. Industries with mostly public organizations tend to have a lognormal size distribution, while privately-owned industries are better fitted by a truncated power law. Growth-rate distributions are fitted to an exponential power (Subbotin) distribution. We decompose the change in size into incoming and outgoing employee movements, and find that the distribution of aggregated movements is well approximated by a lognormal distribution. Most organizations that do not grow have however in- and outgoing movements, but these mostly cancel each other out.

Keyword
organizational growth process, heavy-tailed distributions, power-law distribution, exponential-power distribution, sector and industry dynamics, inter-organizational movements
National Category
Sociology
Research subject
Sociology
Identifiers
urn:nbn:se:su:diva-139098 (URN)
Available from: 2017-02-03 Created: 2017-02-03 Last updated: 2017-02-20Bibliographically approved
2. The evolving network of labor flows in the Stockholm Region: Sector dynamics, connectivity and stability
Open this publication in new window or tab >>The evolving network of labor flows in the Stockholm Region: Sector dynamics, connectivity and stability
2017 (English)In: Applied Network Science, ISSN 2364-8228, Vol. 2, 34Article in journal (Refereed) Published
Abstract [en]

Evolutionary theories of organizational change aim at finding processes that introduce structural variations in organizational variables and the conditions under which they can survive and be reproduced. However, the theory is limited by the lack of knowledge on interactions between organizations and the stability of interaction patterns over time. In this study, we use the network of interorganizational labor flows and tools and concepts from network science to inform the study of organizational evolution at the level of sector dynamics, in particular along the dimensions of connectivity and stability of labor flow patterns. We use a unique Swedish longitudinal register on employment in the Stockholm Region from 1990 to 2003. We find that the network is characterized by positive sector assortativity, and the public sector is relatively more tightly connected than the private one. A stability analysis shows that public organizations survive longer time in the dataset, and movements within publicly-owned organizations are the most stable while movements within the private sector are least stable. A network backbone overlap analysis shows that movements within the public sector are structurally stable over larger periods, while the ones within the private sector change quickly after a few years. We also find that the distributions for degree, interorganizational flows and betweenness centrality are highly skewed and “fat”-tailed; the public sector consistently has fatter tails than the private sector in all distributions. Implications for our understanding of how publicly and privately owned organizations are connected and react to external shocks are discussed.

Keyword
Interorganizational labor flows, Labor market dynamics, Sector dynamics, Network science, Network stability, Centrality, Assortativity, Network backbone overlap
National Category
Sociology (excluding Social Work, Social Psychology and Social Anthropology)
Research subject
Sociology
Identifiers
urn:nbn:se:su:diva-148747 (URN)10.1007/s41109-017-0056-x (DOI)
Available from: 2017-11-07 Created: 2017-11-07 Last updated: 2017-11-08Bibliographically approved
3. The underlying geometry of organizational dynamics: similarity-based social space and labor flow network communities
Open this publication in new window or tab >>The underlying geometry of organizational dynamics: similarity-based social space and labor flow network communities
2017 (English)In: Computational and mathematical organization theory, ISSN 1381-298X, E-ISSN 1572-9346, 1-23 p.Article in journal (Refereed) Epub ahead of print
Abstract [en]

In this article, we use Swedish longitudinal register data to study the effect that similarity in organizational properties has on the interaction between organizations. We map out the social space of large organizations in the Stockholm Region and the interplay between social distance and the network communities of employee movements between organizations. We firstly use homogeneity analysis to describe the dynamics of organizations in terms of the time evolution of their similarity. Our results show that most categorical variables are quite stable over time. Organizations linked through employee movement edges have a lower average distance in social space than non-linked organizations. Secondly, we look at network community dynamics in social space. Employee flows between organizations in different communities exhibit a so-called gravity law from spatial statistics, decaying more slowly than observed geographical networks, meaning that employees reach out regions of social space further than of physical space. Finally, the rate of change of distance in homogeneity space exhibits a statistical distribution similar to the ones found in various other growth processes in natural and man-made systems.

Keyword
Organizational dynamics, Similarity, Social space, Social distance, Homogeneity analysis, Network community structure, Growth process
National Category
Sociology (excluding Social Work, Social Psychology and Social Anthropology)
Research subject
Sociology
Identifiers
urn:nbn:se:su:diva-148930 (URN)10.1007/s10588-017-9260-6 (DOI)
Available from: 2017-11-13 Created: 2017-11-13 Last updated: 2017-11-13
4. The sequence approach to organizational dynamics: Quantifying positive feedback mechanisms in employment trajectories
Open this publication in new window or tab >>The sequence approach to organizational dynamics: Quantifying positive feedback mechanisms in employment trajectories
(English)Manuscript (preprint) (Other academic)
Abstract [en]

In this study, we use Swedish longitudinal data on employment in the Stockholm Region to study the extent of positive feedback mechanisms in the structure and change of employment trajectories. We represent employment trajectories as sequences of yearly employment states, and describe them with the tools of sequence analysis. Firstly, our descriptive results show that employment patterns are generally not stable in time. At least a quarter of the employed population spends the whole time period in one state. Sequence diversity measured by an entropy index is shown to be high and quite stable. There is more female participation in large public sector organizations, and women have larger mean time in those organizations too. Men's participation and mean time is higher in private sector organizations and more equally distributed. A sequence clustering reveals four distinct groupings. One cluster is always dominated by full sequences in large organizations of the public sector. Secondly, we use the sequence clusters as input to quantify positive feedback effects on the likelihood for an employee to stay in an organization. We find indication for a positive feedback mechanism only in a limited number of cases, mainly at the beginning of the 1990s for large highly diverse public organizations. Gender differences exist but are not very pronounced.

Keyword
organizational dynamics, employment careers, sequence analysis, social mechanism, positive feedback mechanism
National Category
Sociology
Research subject
Sociology
Identifiers
urn:nbn:se:su:diva-139157 (URN)
Available from: 2017-02-05 Created: 2017-02-03 Last updated: 2017-02-20Bibliographically approved
5. Fat-Tailed Fluctuations in the Size of Organizations: The Role of Social Influence
Open this publication in new window or tab >>Fat-Tailed Fluctuations in the Size of Organizations: The Role of Social Influence
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.

National Category
Sociology
Research subject
Sociology
Identifiers
urn:nbn:se:su:diva-107036 (URN)10.1371/journal.pone.0100527 (DOI)000339615200008 ()
Note

AuthorCount:3;

Available from: 2014-09-03 Created: 2014-09-02 Last updated: 2017-12-05Bibliographically approved

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