Simpson, Cohen
(2016)
Networks, uncertainty reduction and strategic decision-making in social movement fields.
PhD thesis, London School of Economics and Political Science.
Abstract
Organisational efforts to bring about social change are riddled with choices. What is the appropriate course of action? Who best to collaborate with? How should finite resources, economic or otherwise, be spent? In this respect, the existence of Social Movement Organisations (SMO) — those entities with goals aimed at changing the state of society or protecting the status quo — is one characterised by great uncertainty. Thus a question of critical import to understanding SMOs’ capacity to bring about change is how do they go about bridging information gaps when faced with strategic decisions?
In this thesis I argue that network structure affords SMOs a route to accessing information that may be used to manage uncertainty. My argument is built upon two simple observations: (a) populations of SMOs are constitutive of Social Movement Fields wherein these diverse organisations cooperate, compete and learn from one another through surveillance, comparison and mimicry; and (b) SMOs are embedded in rich webs of relations with peers, both online and offline, that enable and constrain their behaviour by governing access to informational resources that may be used for goal attainment.
The core novelty of this thesis arises from my recasting of SMOs’ strategic actions as types of relationship formation in inter-organisational network scenarios that are comparatively overlooked — namely, multiplex and bipartite networks. This approach has the appealing property of making clear the effect of SMOs on each other — a key aspect of the institutional perspective on which this work is built — whilst also allowing me to more squarely address how network structure might guide action. Analytically, this leads me to focus on those micro-level network locales, i.e., the “local neighbourhoods”, within which SMOs are embedded (e.g., triads) as they relate to tie formation vis-á-vis uncertainty reduction.
Methodologically, this thesis is also designed to demonstrates the sociological power of statistical models of networks in investigating the dynamics of social movement fields. The core strength of these models is their realistic handling of the constraints/benefits of social actors’ structural positions with respect to their behaviour. This is in stark contrast to the variable-centred (i.e. atomistic) statistical frameworks typical of sociological studies of SMOs (e.g., OLS or logistic regression) which fail to account for these organisations’ interdependence and thus provide poor representations of their agency as strategic actors.
Empirically, this work consists of three contained case studies of strategic action: (a) a longitudinal study of tactical implementation in the Palestinian National Movement; (b) a longitudinal study of financial patronage in the US Climate Change Countermovement; and (c) a cross-sectional study of online alliance formation amongst organisational members of the Hardest Hit Coalition, a UKbased anti-austerity issue campaign. Results overwhelmingly support my assertions that information useful in managing uncertainty with respect to strategic action is encoded into oft overlooked network structure. Extant sociological work has simply missed a number of interesting, sometimes counterintuitive, dynamics of Social Movement Fields.
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