New unconventional sources of information for transport analysis. The case of a model for public transport services in Majorca

Abstract

Most transport modeling requires the use of data available in official sources plus complementary information that helps to fill gaps. This later information is mostly obtained with the help of private data and field data collection. But sometimes this field data collection is not possible for several reasons. On the other hand, there are more and more sources of information readily available, which may provide indirect clues about users’ behavior. Within the framework of a bidding process, a modelling of Majorca’s public transport was carried out in order to ascertain elasticities of demand to several parameters of supply that were expected to change. For that purpose, there appeared a need of getting detailed information on tourist activities, which are a huge share of total mobility in summertime. Official information on population is rather detailed, but tourism data are available only on an aggregated basis. Some indirect sources of information were analyzed. The easiest and most useful ones were TripAdvisor and Booking. The former is sort of a macro-survey of popularity and it seems logical that those nuclei with more opinions are those most visited, thus acting as an indicator of attraction. The latter provides information on location of accommodation offered, thus providing a tool for the geographical distribution of trip generation on a very detailed basis. In total, 933,934 opinions for 198 nuclei from TripAdvisor, and 2,114 accommodation assets for 51 Municipalities from Booking were used. With this information it was possible to calibrate different models for the whole Island, this opening the door to further analyses in the field of transportation and mobility. The Transport Consortium of Majorca (CTM), entity in charge of planning and management of scheduled public transport services on that island, published in March 2019 the call for tenders for all intercity public passenger transport services by bus. It opened a scenario of important changes (CTM 2017a and 2017b) that sought to increase the total demand of the intercity bus network by 25% between 2015 and 2028, by means of a substantial variation in the supply side (travel times, timetables, connectivity between lines, etc.). For example, an increase in supply between 35.8% and 73.1% of vehicle-km was planned, with different figures for each of the three packs into which the tender was divided. In addition, a new fare system was introduced, with a very complex structure that imposed a heavy surcharge when purchasing the ticket on the bus. However, no technical study with more information on the expected demand figures was released. Under these circumstances, any projection of the historical data was irrelevant and one of the bidding companies, which also operated a good part of the existing services, felt the need of calculating the expected demand with scientific tools. The analysis of the problem in question faced, fundamentally, an important lack of detail of the available information:  As for transport supply or demand, the official information was limited to total figures by line (CTM, 2017 and “Open Data” site).  In terms of demand factors, the greatest disaggregation available in official sources (ibestat) was at municipal level. The following sections focus on the cross-section analysis of the general services, without dealing with other issues analyzed at the time, such as the new lines to the airport and the time-series modeling.