A study of factors influencing need for, mode of and sustainability of new urban mobility

includes bibliographical references and index

PhD; 2023; Management Studies

Globally, we are observing a paradigm shift in urban mobility enabled by the exponential growth in information and communication technologies (ICTs) leading to profound transformation from traditional mobility to other types of mobility. On the demand side, phenomena like working from home, on-demand entertainment, and online shopping could potentially reduce physical commuting – Virtual Mobility. On the supply side, ICTs enable new mobility options such as vehicle sharing and demand-responsive transport, thus potentially reducing vehicle ownership and use – Shared Mobility. Virtual and Shared mobility options accompanied by Traditional mobility modes are collectively called New Urban Mobility (NUM). Despite a large amount of empirical research over the last few decades, the fundamental issue about the influence of ICTs on mobility remains ambiguous. If all the conventional mobility needs are satisfied at home, will human beings be likely to generate new travel opportunities? If yes, the increased mobility volume can be beneficial if it leads to sustainable transport modes. This problem context requires a careful approach that gives due consideration to the attitudinal, perceptional, socio-economic, and cultural contexts. Thus, the research aims to explore the relationship between the individual, t= he ICTs, and urban mobility in three phases. First, a conceptual framework was developed for understanding mobility behavior and its antecedents in the context of NUM. Mobility behaviors are conceptualized as a function of Attitudinal Factors, Contextual Factors, Personal Capabilities, and Demographic variables. Second, using the data from the primary survey, five distinct mobility behaviors were derived from Exploratory Factor Analysis (EFA). Internalized and externalized contextual indices were calculated for each mobility behavior. EFA on the attitudinal factors revealed six factors. Thereafter, multiple linear regression analysis was used to identify key variables influencing each identified mobility behavior. In the third phase, we segmented the Indian urbanites into three groups - Pragmatic Sceptics, Innovative Access Oriented and Green travel-oriented - based on the five identified mobility behaviors. These groups were then analyzed based on attitudinal factors, personal capabilities, and demographics. Finally, based on these results, important implications for policymakers, urban planners, and transportation companies were discussed, and future research directions were proposed.