Purposeful empiricism: How stochastic modeling informs industrial marketing research

It is increasingly recognized that progress can be made in the development of integrated theory for understanding, explaining and better predicting key aspects of buyer–seller relationships and industrial networks by drawing upon non-traditional research perspectives and domains. One such non-tradit...

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Bibliographic Details
Published in:Industrial marketing management 2013-04, Vol.42 (3), p.421-432
Main Authors: McCabe, James, Stern, Philip, Dacko, Scott G.
Format: Article
Language:English
Subjects:
Business networks
Collaborative purchasing
Dirichlet
Dirichlet problem
Industrial market
Industrial markets
Integration theory
Management theory
Market structure
Marketing
Marketing management
Organizational behaviour
Purposeful empiricism
Stochastic modeling
Stochastic models
Studies
Vendor supplier relations
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Summary:It is increasingly recognized that progress can be made in the development of integrated theory for understanding, explaining and better predicting key aspects of buyer–seller relationships and industrial networks by drawing upon non-traditional research perspectives and domains. One such non-traditional research perspective is stochastic modeling which has shown that large scale regularities emerge from the individual interactions between idiosyncratic actors. When these macroscopic patterns repeat across a wide range of firms, industries and business types this commonality suggests directions for further research which we pursue through a differentiated replication of the Dirichlet stochastic model. We demonstrate predictable behavioral patterns of purchase and loyalty in two distinct industrial markets for components used in critical surgical procedures. This differentiated replication supports the argument for the use of stochastic modeling techniques in industrial marketing management, not only as a management tool but also as a lens to inform and focus research towards integrated theories of the evolution of market structure and network relationships. ► Large scale regularities that emerge from aggregated individual behavior can help develop integrated theory. ► Stochastic modeling is used to describe and interpret emergent large scale patterns in two distinct industrial networks. ► The impact of market making on interdependence and connectedness is analyzed through the lens of the stochastic model. ► Deviations from our model predictions pinpoint opportunities for further investigation.
ISSN:0019-8501
1873-2062
DOI:10.1016/j.indmarman.2013.02.011