Applying behavioral economics in predictive analytics for B2B churn: Findings from service quality data

作者:

Highlights:

• The paper presents an approach that integrates behavioral economics and predictive analytics in a B2B churn modeling context.

• Assumed rationality of organizations plays a significant role in explaining and predicting B2B churn.

• Boundedly rational decision rules might cause somatic states that exacerbate the effect of rational service pain evaluation.

摘要

Motivated by the long-standing debate on rationality in behavioral economics and the potential of theory-driven predictive analytics, this paper examines the link between service quality and B2B churn. Using longitudinal B2B transactional data with service quality indicators provided by a large company, we present evidence that both rationality and bounded-rationality assumptions play significant roles in predicting organizational decisions on churn. Specifically, variables that relate to the assumed rationality of organizations appear to provide accurate predictions while, at the same time, variables that capture boundedly rational decision rules appear to play a role through “somatic states” that make organizations more sensitive to the rational variables. In addition to presenting a novel approach for predicting organizational decisions on churn, this paper offers theoretical and managerial insights as well as opportunities for future research at the intersection of behavioral economics and predictive analytics for decision-making.

论文关键词:Organizational decision analytics,B2B service operations,Churn,Service quality,Decision-making,Rationality,Bounded rationality,Heuristics,Adaptive toolbox,Somatic states

论文评审过程:Received 15 November 2016, Revised 17 June 2017, Accepted 26 June 2017, Available online 28 June 2017, Version of Record 19 August 2017.

论文官网地址:https://doi.org/10.1016/j.dss.2017.06.006