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Stockholm Studies in Sociology New Series 67 ACTAUNIVERSITATISSTOCKHOLMIENSIS Stockholm Studies in Sociology New Series 67 Modeling Organizational Dynamics Distributions, Networks, Sequences and Mechanisms Hernan Mondani c Hernan Mondani, Stockholm University 2017 Cover image: c Hernan Mondani, 2017 Typeset in LATEX ISBN 978-91-7649-673-2 (print) ISBN 978-91-7649-674-9 (digital) ISSN 0491-0885 Printed in Sweden by US-AB, Stockholm 2017 Distributor: Department of Sociology, Stockholm University To my indomitable tenacity and my generous creativity Contents List of Figures xi List of Tables xiii List of Papers xv Acknowledgments xvii Sammanfattning xxv 1 Organizational Dynamics and the Logics of Change1 1.1 Introduction and Research Challenges . .1 1.1.1 Social Organizing and Organizational Change . .1 1.1.2 Theories on Organizational Change . .3 1.1.3 Methods for Organizational Change . .4 1.2 Organizational Dynamics . .6 1.2.1 The Logics of Change . .6 1.2.2 Aim of the Thesis . .6 1.3 Outline of the Thesis . .7 2 Modeling Organizational Dynamics9 2.1 A Phenomenology of Organizational Dynamics . .9 2.1.1 Counting and Sorting Objects . 10 2.1.2 Dependencies Between Objects . 12 2.1.3 Change Events . 13 2.2 The Modeling Process . 14 2.3 Modeling Stages . 16 2.3.1 Observation: the Realm of Data . 16 2.3.2 Abstraction: the Realm of Concepts . 16 2.3.3 Representation: the Realm of Measures and Methods . 17 2.3.4 Analysis: the Realm of Result Representations . 20 2.4 Articulating the Logics of Change . 20 vii 3 Data 25 3.1 The Database . 25 3.1.1 Brief Data Description . 25 3.1.2 Data Complexity . 26 3.1.3 Limitations . 27 3.2 Related Data Sources . 29 3.3 A Note on Simulated Data . 29 4 The Fabric of Organizational Change 31 4.1 Structures: Crystallized Change . 31 4.1.1 Multifaceted Crystallization . 31 4.1.2 Structural Compositions and Imbalances . 32 4.2 Organizational Growth: Local Change . 33 4.2.1 Multifaceted Locality . 33 4.2.2 Growth Processes . 33 4.2.3 Extreme Growth Events . 33 4.2.4 Social Space . 34 4.3 Labor Mobility: Relational Change . 35 4.3.1 Multifaceted Relations . 35 4.3.2 Transfers Between Organizations . 35 4.3.3 Organizational Communities . 35 4.3.4 Social Distance and Relations . 36 4.4 Distributions: Counting and Sorting Entities . 36 4.4.1 A Landscape of Distributions . 36 4.4.2 Method: Heavy-tailed Distribution Fitting . 38 4.4.3 Method: Homogeneity Analysis . 38 4.5 Networks: Quantifying Relational Dependencies . 39 4.5.1 A Landscape of Networks . 39 4.5.2 Method: Complex Network Analysis . 39 4.5.3 Network Centrality and Assortativity . 40 4.5.4 Network Stability and Community Structure . 40 5 The Unfolding of Organizational Change 45 5.1 Employment Trajectories: Path-dependent Change . 45 5.1.1 Multifaceted Path Dependency . 45 5.1.2 Individual Employment Trajectories . 46 5.1.3 Trajectories and Organizational Dynamics . 46 5.2 Sequences: Quantifying Path Dependence . 46 5.2.1 A Landscape of Sequences . 46 5.2.2 Method: Sequence Analysis . 47 5.2.3 Sequence Similarity and Sequence Diversity . 47 viii 5.3 Mechanisms: Exploring the Inner Workings of Change . 48 5.3.1 A Landscape of Mechanisms . 48 5.3.2 Positive Feedback and Social Influence . 48 5.3.3 Method: Agent-based Models and Simulation . 49 5.3.4 Method: Physical Analogies . 50 6 Overview of the Studies 53 7 Concluding Remarks 65 7.1 Conclusions . 65 7.1.1 The Fabric of Organizational Change . 65 7.1.2 The Unfolding of Organizational Change . 66 7.2 Further Research . 67 7.2.1 Data Challenges . 67 7.2.2 Theoretical Challenges . 67 7.2.3 Methodological Challenges . 69 7.3 Outlook . 70 Appendices 73 A Base Files for Data Representations . 73 B Reflections . 77 References 87 ix List of Figures 2.1 Phenomenological features . 11 2.2 The modeling process . 15 2.3 Data representations . 19 6.1 Study I and its articulating logic . 55 6.2 Study II and its articulating logic . 57 6.3 Study III and its articulating logic . 59 6.4 Study IV and its articulating logic . 61 6.5 Study V and its articulating logic . 63 xi List of Tables 6.1 Summary of the studies . 54 A.1 Base file layouts for data representations . 75 xiii List of Papers The following papers are included in this thesis. Study I Informing organizational growth models with longitudinal individual- level data. Sector, industry and inter-organizational movement statistics in the Stockholm Region Hernan Mondani Under review. Study II The evolving network of labor flows in the Stockholm Region. Sector dynamics, connectivity and stability Hernan Mondani Under review. Study III The underlying geometry of organizational dynamics: Similarity- based social space and labor flow network communities Hernan Mondani Submitted manuscript. Study IV The sequence approach to organizational dynamics: Quantify- ing positive feedback mechanisms in employment trajectories Hernan Mondani Submitted manuscript. Study V Fat-Tailed Fluctuations in the Size of Organizations: the Role of Social Influence Hernan Mondani, Petter Holme and Fredrik Liljeros PLoS ONE 9(7), e100527 (2014). DOI: 10.1371/journal.pone.0100527 Study V is partly based on the doctoral candidate’s master’s thesis (Mondani, 2012). xv Acknowledgments This thesis is about models of organizational change and the logics articulating them. So it is only fair for the acknowledgments section to begin with a small exercise in logic. It goes like this. The narrative structure of acknowledg- ment sections in sociology theses at the Department of Sociology, Stockholm University, during the last 5 years, boils down to the following logic. Let D be a doctoral candidate on the verge of defending her thesis. The process of writing a thesis, just like any other social process, unfolds in a dy- namic social space, a field of interaction spanned by the candidate’s social properties and those of her contacts. Upon the time of acknowledgment writ- ing ta, and provided that the narrative structure is known to D, the need arises to choose a proper narrative instance, which implies the selection of people, actions and events within a reasonable period of time that are worthy of recog- nition. D proceeds consequently to probe her social space for information, where B(D;r;tA) is a social space neighborhood centered around her with ra- dius r. The social space neighborhood is further partitioned into classes, which induce a naming order typically in a priority scale N ={supervisor/s ! col- league/s ! friend/s ! family (peripheral) ! family (nuclear)}. The people in the neighborhood can be associated with a set of actions deemed worthy of being acknowledged A(pjD) on the basis of a certain cri- teria that are either universally accepted within the time period of writing, or derived from the latest theses using a suitable heuristic. The acknowledgment text can thus be written with the help of an algorithm of the form: for every o in N: u := random number for every p in B(D;r;tAjo): write "To " + p for every a in A(pjD): write "thanks for doing " + a + phr[u] where phr is a set of standard phrases presumably suited for the occasion, for instance: phr = f"I will never forget you.", "You are simply the best.", "I couldn’t have done it without you.", :::g. The random number is intended to add variation to an otherwise totally deterministic text. xvii So now we are ready to move on to the particular narrative instance of this thesis. When I— doctoral candidate H— look around in my social space neighborhood B(H;r;tA), I notice that throughout the years I have been priv- ileged in various ways. Today, after a somehow long journey, I believe my greatest privilege has been to be able to create, bound only by my own limita- tions, to allow myself to be engulfed by my own ghosts, and reinvent myself as I see fit. To waste as much time as I wanted and to explore new opportunities as I deemed necessary. This freedom is not naturally given, though; someone has to pay for it. So my first acknowledgments go to everyone who has contributed to financing my current social space state B(H;r;tA). Since I believe important things should be named first, I introduce a reverse naming order N˜ = flip(N) here (which also translates into exploring the social space neighborhood from the center and outwards, in the direction of increasing r, a procedure somehow more appealing, mathematically speaking). I would first like to thank my family: my father Luis Pedro, my mother Adriana Angela and my brother Mariano. You have always been relentlessly supportive of my projects, and in particular of my decision to start anew in Sweden. My mom should be especially commended for her strength and pa- tience, and not the least for suggesting that I should look for some social sci- ence application to my modeling interests. To both my parents: thanks for always putting me and my brother above everything else. You have taught us many important things, and have been wise and good-willed enough to do it in the only way fundamental things can be taught: by subtle, consistent, exem- plifying insinuation. A good example has to do with my relationship to books and reading. There was never a formal moment, not that I can remember any- how, where the importance of books was pointed out to me. But books have always been around at home: many topics in many rooms. And besides your bed, so that even after a hard day’s work a page or two should precede your decent into the dark unknown.
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