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This study aims to understand the lapse behavior of life insurance policyholders. Despite being accessible for nearly two centuries, only a small fraction of individuals purchase such policies and many of those who do let them lapse. The belief hypothesis model (BHM) is introduced to elucidate the correlation between policyholders' beliefs and their decisions regarding life insurance lapses.

BHM establishes a comprehensive linkage between core beliefs, external data and the lapse behavior exhibited by policyholders. To derive policyholders’ core beliefs about life insurance lapses, the authors conducted a semistructured, in-depth interview with 42 policyholders and 11 insurance advisors, using a grounded theory approach with zero-order, first-order and second-order coding.

The study's findings reveal that policy lapsation is influenced by various factors such as policyholders' beliefs about life insurance, process-related attitudes, trust in insurers and advisors and personal financial viewpoints. Policyholders who consider life insurance unnecessary or misunderstand its purpose are likelier to lapse their policies. Cumbersome documentation processes and technical issues also contribute to policy lapsation, emphasizing the significance of simplified procedures. Trust in insurers and advisors, personal financial literacy and payment preferences influence policy lapsation.

The findings of this research can be practically applied by companies to improve customer retention and by regulatory bodies to encourage policyholders to honor their insurance commitments.

Distinguishing itself from conventional hypotheses-driven and factor-centric models, BHM integrates consumer beliefs, thus enriching comprehension and decision-making insights.

The purpose of this study is to identify the causative factors of metro construction safety accidents, analyze the correlation between accidents and causative factors and assist in developing safety management strategies for improving safety performance in the context of the Chinese construction industry.

To achieve these objectives, 13 types and 48 causations were determined based on 274 construction safety accidents in China. Then, 204 cause-and-effect relationships among accidents and causations were identified based on data mining. Next, network theory was employed to develop and analyze the metro construction accident causation network (MCACN).

The topological characteristics of MCACN were obtained, it is both a small-world network and a scale-free network. Controlling critical causative factors can effectively control the occurrence of metro construction accidents. Degree centrality strategy is better than closeness centrality strategy and betweenness centrality strategy.

In practice, it is very difficult to quantitatively identify and determine the importance of different accidents and causative factors. The weights of nodes and edges are failed to be assigned when constructing MCACN.

This study provides a theoretical basis and feasible management reference for construction enterprises in China to control construction risks and reduce safety accidents. More safety resources should be allocated to control critical risks. It is recommended that safety managers implement degree centrality strategy when making safety-related decisions.

This paper establishes the MCACN model based on data mining and network theory, identifies the properties and clarifies the mechanism of metro construction accidents and causations.