The recursive-adaptive rental subscription model (R-ARSM) in the new normal: an application to the housing sector

Abstract

Background: The last three decades have witnessed a remarkable transformation from a traditional billing system to a subscription model. Many organizations have adopted the subscription models especially in the service sectors like telecommunication, internet service providers, and satellite television operators. During the lockdown occasioned by the coronavirus disease (COVID-19) pandemic, people were forced to subscribe for their daily needs, and their lifestyle was altered, and people must reset to cope with the new normal. The new normal era has exposed many people to subscribe to what they could afford based on length of time and limited resources. Unexpected daily economic challenges emerged, and people relocated to affordable places which led to rent default, rent arrears, and refund requests. This paper focused on how to solve rent default, rent arrears, and refund request problems in the public and private housing sector. Methods: Relying on this, we proposed recursive-adaptive rental subscription models (R-ARSM) that could allow tenants options to subscribe for house rent with available resources. The R-ARSM concept mimics the internet subscription, mobile phone subscription, and satellite television subscription models whereby services to customers on annually, monthly, weekly, daily, and hourly rates are terminated when the subscribed amount elapses. Results: The model based on the penalty constant showed that it is a balanced model for both landlords and tenants in the housing sector. The R-ARSM showed promising results, it is time-dependent and indicates the tenant's available balance per period. Conclusions: The analysis revealed that the R-ARSM concept would solve refund requests and rent default problems if implemented.