Town centres in the economically developed world have struggled in recent years to attract sufficient visitors to remain economically sustainable. However, decline has not been uniform, and there is considerable variation in how different town centres have coped with these challenges. The arrival of the coronavirus (COVID-19) pandemic public health emergency in early 2020 has provided an additional reason for people to avoid urban centres for a sustained period. This paper investigates the impact of coronavirus on footfall in six town centres in England that exhibit different characteristics. It presents individual time series intervention model results based on data collected from Wi-fi footfall monitoring equipment and secondary sources over a 2-year period to understand the significance of the pandemic on different types of town centre environment. The data show that footfall levels fell by 57%–75% as a result of the lockdown applied in March 2020 and have subsequently recovered at different rates as the restrictions have been lifted. The results indicate that the smaller centres modelled have tended to be less impacted by the pandemic, with one possible explanation being that they are much less dependent on serving longer-distance commuters and on visitors making much more discretionary trips from further afield. It also suggests that recovery might take longer than previously thought. Overall, this is the first paper to study the interplay between footfall and resilience (as opposed to vitality) within the town centre context and to provide detailed observations on the impact of the first wave of coronavirus on town centres’ activity.

The bus transport system in Dhaka is unsafe, unreliable, inefficient and struggles to cope with the day-to-day mobility of its massive population. Consequently, measuring the performance of bus service quality (SQ) from the customers’ perspective is fundamental in planning a sustainable bus transport system for Dhaka, and in developing the associated policies and regulations. Although there are some studies addressing the performance of the public transport systems in Bangladesh, little research considers how service quality attributes affect passengers’ satisfaction. The purpose of this paper is to examine a relationship between bus service quality and its influencing factors in Dhaka. Using a customer satisfaction survey with a sample size of 955, discrete choice models (e.g., multinomial logit and mixed logit) have been developed. The results indicate that the inhabitants, as expected, are dissatisfied with their bus services (less than 10% rated service quality as “excellent/good”) and service attributes such as comfort level and driver skills were found to be the most important contributors toward the “poor” and “very poor” perceptions of service quality. Other influencing factors are punctuality, safety, entry and exit processes, waiting times, and vehicle condition. One surprising finding was that the multinomial logit model provides better goodness-of-fit for the sample data relative to the mixed logit model implying that bus users in Dhaka may represent a homogeneous group as they do have access to other modes. Findings from this study can be utilized to develop policies and regulations to improve bus transport in Dhaka.

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This paper aims to highlight the impact of train and station types in the evaluation of service quality, whilst taking account of a range of relevant trip and socio-demographic factors. It applies a partial constrained proportional odds model (an extension of ordered logit model) to data extracted from the 32 nd wave of the National Rail Passenger Survey (NRPS) held in spring 2015, which comprises around 30,000 trip-level observations of passenger satisfaction of rail services across Great Britain.The results indicate that the impact of train types on service quality is significant. Thus, for type of train services the modelling results indicate that high speed rail, long distance, inter urban rail and especially open access operators are more likely to lead to satisfied customers compared to commuter and rural railway services. For stations, users of the smallest station category are more likely to be satisfied than those of larger category stations, but other station types do not significantly impact satisfaction. Next, delays have a significant negative impact on satisfaction levels. Considering passenger segments, respondents in the oldest age category are more likely to be satisfied compared to respondents in the youngest age category and commuters are less likely to be satisfied compared to respondents on a business or leisure trip. Overall these results show how TOCs (Train Operating Companies) might best focus their efforts on improving passenger satisfaction according to train type, station type, and trip stage and/or user segment.Monsuur, Enoch, Quddus, Meek 3 INTRODUCTION Delivering a quality service that meets the expectations and needs of its customers is an important commercial aspect of running a railway. This is for three reasons. First, dissatisfied passengers might switch to alternative travel modes if these are available or else decide not to travel at all, whereas satisfied passengers tend to be loyal to the railway mode (1,2,3,4). Second, satisfaction is of importance for railway companies because it is used to monitor and benchmark performance and increasingly such satisfaction measures relate directly to payments made to TOCs (Train Operating Companies) as part of their franchise agreements, e.g. the Thameslink, Great Northern and Southern franchise (5). Third, poor satisfaction might lead to reputational damage for TOCs (6), which may further lead to longer term impacts on both patronage levels and the chances of winning/retaining future franchise competitions. Taken together, underperformance in terms of passenger satisfaction can significantly impact on the profitability of a TOC, as margins are already small -with a maximum of around 5% (7). However, despite widespread recognition of the importance of passenger satisfaction across the UK rail sector, in practice improving the situation has proven difficult to achieve. For instance, the average level of passenger satisfaction in 2015 was only 80% -that is 5% lower level than in 2010 (8).In attempting to explain this, perhaps the...

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