Bibliometric Analysis of Rental Housing Research Through the Lens of Sustainable Urbanization
摘要
This work critically explores the research landscape of the extant literature, both academic and non-academic, that looks at the potential contribution of rental housing to the achievement of Sustainable Development Goal 11 (SDG 11) within India's rapidly urbanizing landscape. Recognizing the growing dependence on rental housing and how the rapid unfettered urbanization may clash with SDG targets that the country has set for itself, this research investigates how diverse rental housing models can contribute to the SDG 11 target of ‘adequate, safe, and affordable housing’ while addressing existing challenges [United Nations (2016) Goal 11 | Department of Economic and Social Affairs. https://sdgs.un.org/goals/goal11 ]. This structured literature review, thus, examines existing research on rental housing in India, analysing its contributions and limitations in the context of sustainable urbanization. With rising prices of housing everywhere, especially closer to employment centres, a regulated rental market with an organized housing supply would benefit all concerned actors. As per the existing research on urban housing and tenancy regulations in India, however, the need for an organized rental housing market is not limited to temporary/seasonal migration only but affects most non-residents of a city. But an impetus also needs to be directed towards the demand side factors which are affected by consumer behaviour. Understanding the needs, preferences, and decision-making processes of renters is critical for landlords, property managers, real estate developers, and policy makers. Moreover, such multifaceted and inter-disciplinary research is needed at the nexus of urbanization and sustainability. The research examines factors such as, but not limited to, affordability and accessibility, livability and quality of life, environmental sustainability, economic development, governance and policy, etc., by employing a bibliometric analysis, searching academic databases and relevant websites for research published between 2010 and 2024. Several models like bibliometric coupling, co-citation analysis, and keyword analysis have been used to arrive at the conclusions.