## 1 Introduction  
Traditional public transport is facing growing challenges to meet the mobility needs, especially in the developing countries. Deteriorating quality of public transport creates space for alternative transport services. One such alternative transport service is demand-responsive transport (DRT). It is a flexible transport service where operation is determined by the demand generated by the users. Typically, users register their demand through a calling service, which helps in planning the routes for pick and drop. Its usage is higher at places where public transport is either not available [1] or in developing countries where public transport is not able to meet the demand ([2]. The DRT service is useful for areas with a low demand for transport (such as suburbs), but recently, due to the COVID-19 pandemic in some countries, this service has become of paramount importance as severe restrictions have been placed on the number of passengers on board public and private transport to avoid possible contagion in addition to the declined use of public transport [3, 4, 5, 6]. Several studies have supported the potential of DRT services to provide sustainable local public transport. Some of the DRT schemes in use worldwide meet social needs, such as access to commercial facilities or hospitals, but face cost problems. Furthermore, institutional barriers for new DRT schemes have to be overcome in order to develop a sustainable local public transport system [7]. Recent advances in technology have made it possible for the passengers to register their demand through Smartphone apps using an internet connection. Such app-based DRT services are operating in several countries and are more accessible, comfortable, and affordable for the passengers [8]. It is important for the operators to know if the DRT services can attract existing and future users. User satisfaction levels can provide valuable information to the operators about what aspect of the service needs to be improved. Reliability, frequency, comfort, on-time performance, travel speed, and service frequency are important factors of user satisfaction [9; 10]. A common technique to measure user satisfaction levels is through user satisfaction surveys. App-based DRT services are gradually emerging in Lahore because of deteriorating quality of public transport. SWVL (choice A) and Airlift (choice B) bus services are two popular examples of such service in Lahore. Both choice A and choice B are operating along several routes across Lahore. Users have the option to suggest new routes through the apps. The services then prioritize the launch of new routes after proper planning and analysis. There is a need to determine the satisfaction levels of the users of these app-based DRT services as well as the elements of these services that are most valued by the users. Earlier studies did not put much emphasis on perceptions about spatial coverage and easiness in booking ride through an App, driver's behavior, and ambiance of the vehicles. In addition, it is essential to assess the overall satisfaction with these App-based DRT services since they are likely to affect already deteriorating public transport ridership. The current study addresses this gap and is among the first of its kind in the context of app-based DRT services in Lahore. The primary objective of this study was to explore passengers' satisfaction with app-based DRT services in Lahore, namely SWVL and Airlift. A questionnaire was developed to collect the required data. Exploratory factor analysis was then conducted to explore the factors affecting passengers' satisfaction levels. Factor scores were calculated, and further statistical analysis was carried out. Finally, ordinal regression models were developed to model the relationship between overall satisfaction level and the explanatory variables. The rest of this paper is organized as follows: the next section will discuss the relevant literature on determining passenger satisfaction levels regarding public transport through user satisfaction surveys.