Purposeful empiricism: How stochastic modeling informs industrial marketing research
Purposeful empiricism: How stochastic modeling informs industrial marketing research
复制标题
有目的的经验主义：随机建模如何为工业营销研究提供信息
DOI：
10.1016/j.indmarman.2013.02.011
复制
发表时间：
2013
影响因子：
10.3
通讯作者：
Scott G. Dacko
中科院分区：
文献类型：
--
作者：
J.D.J. McCabe;P. Stern;Scott G. Dacko
人们日益认识到，利用非传统的研究观点和领域，可以在理解、解释和更好地预测买卖双方关系和工业网络的关键方面的综合理论的发展方面取得进展。其中一种非传统的研究视角是随机建模，它表明大规模的规律来自于特殊行为者之间的个体相互作用。当这些宏观模式在大范围的公司、行业和商业类型中重复时，这种共性为我们通过对狄利克雷随机模型的差异化复制进行进一步研究提供了方向。我们在两个不同的工业市场中展示了关键外科手术中使用的组件的可预测的购买行为模式和忠诚度。这种差异化的复制支持了在工业营销管理中使用随机建模技术的论点，它不仅是一种管理工具，而且是一个镜头，为市场结构和网络关系演变的综合理论提供信息和重点研究。
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.