Decision-Making Processes in Social Contexts

Bruch, Elizabeth E.; Feinberg, Fred M.

doi:10.1146/annurev-soc-060116-053622

Cited by 213 publications

(162 citation statements)

References 194 publications

(167 reference statements)

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“…We conducted an additional set of model runs by using a more realistic “2-phase” decision rule, 33 in which agents decided from which retailer to purchase tobacco products after ruling out some retailers on the basis of maximum acceptable price, maximum acceptable distance, or type of retailer. Both density reduction and cost increase results showed very similar patterns to the main model runs (see Table B-1 and Figure B-1 in Appendix B, available as a supplement to the online version of this article at http://www.ajph.org).…”

Section: Resultsmentioning

confidence: 99%

Tobacco Town: Computational Modeling of Policy Options to Reduce Tobacco Retailer Density

et al. 2017

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Objectives To identify the behavioral mechanisms and effects of tobacco control policies designed to reduce tobacco retailer density. Methods We developed the Tobacco Town agent-based simulation model to examine 4 types of retailer reduction policies: (1) random retailer reduction, (2) restriction by type of retailer, (3) limiting proximity of retailers to schools, and (4) limiting proximity of retailers to each other. The model examined the effects of these policies alone and in combination across 4 different types of towns, defined by 2 levels of population density (urban vs suburban) and 2 levels of income (higher vs lower). Results Model results indicated that reduction of retailer density has the potential to decrease accessibility of tobacco products by driving up search and purchase costs. Policy effects varied by town type: proximity policies worked better in dense, urban towns whereas retailer type and random retailer reduction worked better in less-dense, suburban settings. Conclusions Comprehensive retailer density reduction policies have excellent potential to reduce the public health burden of tobacco use in communities.

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Section: Resultsmentioning

confidence: 99%

Tobacco Town: Computational Modeling of Policy Options to Reduce Tobacco Retailer Density

et al. 2017

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“…This type of data identifies not only the choices of individuals but also how individuals consider alternatives, learn, adjust, and ultimately decide against certain options [27]. From the standpoint of causal inference, these datasets permit longitudinal analyses of infinitesimal period length and high-dimensional matching relying not only on a handful of sociodemographic variables but hundreds or thousands of individual and contextual attributes.…”

Section: Computational Tools As the Econometrics Of Sociologymentioning

confidence: 99%

“…Although it is true that largescale and fine-grained data leave less room for researchers own interpretations of empirical findings, and that direct tests of the underlying causes of observed phenomena sometimes are possible [27], interpretations of causal effects and the transportability of results from one domain to another require that the type of generative mechanism is identified. If results cannot be traced back to general mechanisms, understanding remains incomplete and generalization beyond the specific case becomes hard to attain [5,67,68].…”

Section: Computational Tools As the Econometrics Of Sociologymentioning

confidence: 99%

Analytical sociology and computational social science

2017

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Analytical sociology focuses on social interactions among individuals and the hard-to-predict aggregate outcomes they bring about. It seeks to identify generalizable mechanisms giving rise to emergent properties of social systems which, in turn, feed back on individual decision-making. This research program benefits from computational tools such as agent-based simulations, machine learning, and large-scale web experiments, and has considerable overlap with the nascent field of computational social science. By providing relevant analytical tools to rigorously address sociology's core questions, computational social science has the potential to advance sociology in a similar way that the introduction of econometrics advanced economics during the last half century. Computational social scientists from computer science and physics often see as their main task to establish empirical regularities which they view as ''social laws.'' From the perspective of the social sciences, references to social laws appear unfounded and misplaced, however, and in this article we outline how analytical sociology, with its theory-grounded approach to computational social science, can help to move the field forward from mere descriptions and predictions to the explanation of social phenomena.

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“…In extant literature, this elimination process is labeled partitioning (Moorthy, Ratchford and Talukdar, 1997): Actors try to reduce the amount of information processing involved in complex decision making, adopting search and decision strategies that eliminate some of the available alternatives as quickly as possible, based on limited information (i.e. in reduced search space) (Bruch and Feinberg, 2017;Payne, 1976). While empirical evidence indicates that both embeddedness and proximity have a positive influence on tie formation (Balland, De Vaan, and Boschma, 2013), their complementarity and relative explanatory power are understudied.…”

Section: Introductionmentioning

confidence: 99%

With whom do firms form ties? A meta-analysis on the influence of embeddedness and proximity on inter-organizational tie formation

Zelst¹,

Mannak²,

Oerlemans³

2017

Preprint

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We meta-analyze the influence of various forms of embeddedness and proximity on interorganizational tie formation with a dataset that encompasses 256,529 ties from 73 studies.First, we uncover the unparalleled importance of relational embeddedness, while the influence of structural and positional embeddedness turns out to be highly dependent on the context. Second, we show that various forms of proximity positively influence tie formation and have unique explanatory power in addition to the embeddedness dimensions. Last, we explore to what extent these effects are contingent on the type of tie, resource munificence, status orientation, level of individuality, and intellectual property regimes. Our study introduces a preliminary contingency theory of interorganizational tie formation and provides directions for future research.

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Decision-Making Processes in Social Contexts

Cited by 213 publications

References 194 publications

Tobacco Town: Computational Modeling of Policy Options to Reduce Tobacco Retailer Density

Tobacco Town: Computational Modeling of Policy Options to Reduce Tobacco Retailer Density

Analytical sociology and computational social science

With whom do firms form ties? A meta-analysis on the influence of embeddedness and proximity on inter-organizational tie formation

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