Can Socio‐Economic Household‐Level Variables Explain Slum Dwellers' Adaptation to Cyclones? A Case Study of India's First Smart City Bhubaneswar

ABSTRACT Coastal cities in the Indian subcontinent have been experiencing severe cyclonic occurrences. Therefore, slum communities are no exception, and their adaptation strategies to cope with these climatic events are less studied in practice and research. Hence, the current study seeks to study the socio‐economic variables that enhance the slum dwellers' adaptability to recurring cyclones in India's first smart city, Bhubaneswar. With the help of a structured questionnaire, a total of 200 households are randomly selected from two cyclone‐prone slums, such as ‘Kedar Palli’ and ‘Phd Sahi’. As the ‘adaptation measures’ we have considered here are ‘dichotomous’ or ‘binary’, the study uses a logistic regression model to determine the factors responsible for adaptation. The significant findings of the study are: (1) the level of education of the respondent is positive and significant in the model, implying better education leads to better cyclone adaptation; (2) if the slum household has house ownership, they are better adapted; (3) credit facility available to the slum dwellers enhances their adaptability to recurring cyclones, (4) slum dwellers have learned from previous cyclone experience, that is, there is a ‘learning effect’ as they are better adapted, (5) ‘income of the household’, ‘gender,’ ‘family type’ whether ‘nuclear or joint’ also impacts the adaptation of slum dwellers. From a policy perspective, the study illustrates that local government should upgrade the slums by enhancing their socio‐economic conditions to help the community adopt more generic and location‐specific adaptation strategies.