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An introduction to an old acquaintance: using Bayesian inference in sales research
Journal of Personal Selling & Sales Management Pub Date : 2019-11-04 , DOI: 10.1080/08853134.2019.1680294
Maria Rouziou 1 , Riley Dugan 2
Affiliation  

Abstract Given the scant attention paid to Bayesian inference in the academic sales literature, researchers could be forgiven for believing that frequentist methods provide the only feasible way for sales researchers to derive important insights for both theory and practice. The purpose of this research is to demonstrate that this belief overlooks the considerable value that Bayesian inference can provide to sales theory and practice. In so doing, we outline fundamental differences between Bayesian and frequentist methods, and describe how these differences can lead to different empirical insights. We review the extant literature that employs Bayesian methods, with an emphasis on how these studies provide insight that may elude frequentist methods. Then, using a sample of 146 B2B salespeople, we empirically demonstrate that the use of Bayesian methods is both within the methodological reach of the vast majority of sales researchers, and can also provide different empirical insights using the same dataset, than would frequentist methods. We then provide some future research ideas to encourage sales researchers to employ Bayesian methods in their own research. Finally, in hopes that readers do not view Bayesian inference as a “silver bullet”, we examine some drawbacks and limitations of this intriguing method of statistical inference.

中文翻译:

老熟人介绍:在销售研究中使用贝叶斯推理

摘要 鉴于学术销售文献中对贝叶斯推理的关注很少,研究人员认为频率论方法是销售研究人员从理论和实践中获得重要见解的唯一可行方法,这是可以原谅的。这项研究的目的是证明这种信念忽略了贝叶斯推理可以为销售理论和实践提供的巨大价值。在此过程中,我们概述了贝叶斯方法和频率论方法之间的根本差异,并描述了这些差异如何导致不同的经验见解。我们回顾了使用贝叶斯方法的现有文献,重点是这些研究如何提供可能无法避开频率论方法的洞察力。然后,使用 146 名 B2B 销售人员的样本,我们凭经验证明,贝叶斯方法的使用既在绝大多数销售研究人员的方法论范围内,也可以使用相同的数据集提供与频率论方法不同的经验见解。然后我们提供了一些未来的研究思路,以鼓励销售研究人员在他们自己的研究中采用贝叶斯方法。最后,希望读者不要将贝叶斯推理视为“灵丹妙药”,我们检查了这种有趣的统计推理方法的一些缺点和局限性。然后我们提供了一些未来的研究思路,以鼓励销售研究人员在他们自己的研究中采用贝叶斯方法。最后,希望读者不要将贝叶斯推理视为“灵丹妙药”,我们检查了这种有趣的统计推理方法的一些缺点和局限性。然后我们提供了一些未来的研究思路,以鼓励销售研究人员在他们自己的研究中采用贝叶斯方法。最后,希望读者不要将贝叶斯推理视为“灵丹妙药”,我们检查了这种有趣的统计推理方法的一些缺点和局限性。
更新日期:2019-11-04
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