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One of the major problems often faced by planners, decision-makers, and practitioners is identifying the locations that need development and investments. Optimal investments in the right areas of development would help an economy to grow optimally. The spatial mix of industries and their inter-linkages across the country define the spatial structure of an economy. Freight

The study aims to model the initial international spread of Coronavirus Disease 2019 (COVID-19) and analyse the risk of early initial spread using data from 105 countries. A generalised linear model (GLM) is developed to analyse the relationship between the initial international spread and its factors. Findings showed that the countries with high tourism activity are affected early by COVID-19, and countries with a better-quality healthcare system can adequately detect the spread. Countries that have promptly restricted air passengers have experienced a delay in the initial international spread. A regression analysis of fatalities during the initial stage suggested that the countries with an early initial spread of COVID-19 coupled with a high proportion of the elderly population possess a relatively high risk of fatalities. The study provides insights into the factors influencing the initial international spread of contagious diseases and the effect of air travel restrictions on the spread. This study can aid in contingency planning during the initial spread of pandemics, especially for countries with high tourism activity.

Route choice plays a vital role in the traffic assignment and network building, as it involves decision making on part of riders. The vagueness in travellers’ perceptions of attributes of the available routes between any two locations adds to the complexities in modelling the route choice behaviour. Conventional Logit models fail to address the uncertainty in travellers’ perceptions of route characteristics (especially qualitative attributes, such as environmental effects), which can be better addressed through the theory of fuzzy sets and linguistic variables. This study thus attempts to model travellers’ route choice behaviour, using a fuzzy logic approach that is based on simple and logical ‘if-then’ linguistic rules. This approach takes into consideration the uncertainty in travellers’ perceptions of route characteristics, resembling humans’ decision-making process. Three attributes – travel time, traffic congestion, and road-side environment are adopted as factors driving people’s choice of routes, and three alternative routes between two typical locations in an Indian metropolitan city, Surat, are considered in the study. The approach to deal with multiple routes is shown by analyzing two-wheeler riders’ (e.g. motorcyclists’ and scooter drivers’) route choice behaviour during the peak-traffic time. Further, a Multinomial Logit (MNL) model is estimated, to enable a comparison of the two modelling approaches. The estimated Fuzzy Rule-Based Route Choice Model outperformed the conventional MNL model, accounting for the uncertain behaviour of travellers.