Logistic Regression Analysis of Effect of Perceived External Determinants on Memebership Churn in Professional Organizations in Kenya: A Case Study of the Kenya Institute of Management

Abstract: Membership churn brings about significant challenges to professional organizations, thus threatening their financial stability and long-term sustainability. This study investigates the perceived external determinants influence on membership churn at the Kenya Institute of Management using logistic regression. Specifically, the study evaluated the effect of economic conditions, availability of similar services and industry and professional changes on membership churn. A cross-sectional research design was employed and with data collected from 384 KIM members through structured online surveys based on quota stratified sampling. The logistic regression model identified industry changes as the most significant predictor of churn (OR = 1.51, p < 0.001) followed by economic conditions (OR = 1.28, p = 0.012). Availability of similar services was found not to be statistically significant (p = 0.071). Model evaluation by Hosmer-Lemeshow test (p = 0.8403) confirmed a good model fit supported by Nagelkerke’s R² showing that 72.2% of churn variance was explained by the perceived predictors. The findings suggest that professional organizations should strategically adapt to industry and professional shifts and economic fluctuations to reduce member churn. Implementation of flexible payment plans and differentiation of services help mitigate churn risks. This study enhances the understanding of membership dynamics in professional bodies and offering strategic insights to enhance member retention in similar organizations.