2.1. Online Cash Register Data in Hungary
The challenges faced by statistics in the 21st century are manifold. We are surrounded by systems that are becoming substantially more and more complex. With the emergence of new phenomena (e.g., globalisation, global demographic trends or sustainable development) and complex realities that need to be meaningfully and timely captured by statistics, new types of data have also been emerging, offering opportunities to improve the relevance of statistics.
Fortunately, there is currently an abundance of data sources: questionnaire-based statistical data, census data, big data, smart data, machine data, administrative data, privately held data, etc. In many cases, statistical domains are based on traditional data sources that are reaching their limits with respect to timeliness, relevance and compliance.
For the purpose of reducing the abuses committed during the retail trade turnover, the government of Hungary decided to introduce an online connection of cash registers with the National Tax Authority in October 2014. According to the OECD [
2], electronic cash registers are used (among others) in Argentina, Austria, Belgium, the Czech Republic, Hungary, Italy, the Netherlands, Portugal, Russia and Sweden. As such, cash machines involved in the online cash register system send online retail chain sales information to the National Tax Authority. This means that data concerning the sales of retail stores can be accessed in real time from the NTCA (National Tax and Customs Administration) database. Immediately after the purchase of goods or services, invoice details are automatically sent online to the National Tax and Customs Administration. The Hungarian Central Statistical Office receives this in full. The database contains the OCR number, the date of commissioning, the period of validity, the tax number of the company, the name and address of the business, the economic activity of the company, the number and turnover value of invoices, cancellation and returns for the given period.
In this paper, we use OCR data from 2018, 2019 and 2020 to illustrate methodological approaches that map out the crystallisation points of transit traffic in Hungary. While the study primarily aims to capture the phenomenon of transit at the municipal level, we draw attention to the fact that the impacts are economy-wide in their multiplier effect.
The OCR data are available up-to-date, with the added advantage of being disaggregated by economic activity and geographical location. The advantage of online cash registers is that tax authorities can determine the amount of tax payable more accurately and quickly based on the data they receive, and if they see suspicious traffic data, they will be able to filter out fraudsters in a matter of seconds. The system developed from a tax point of view also provides much more accurate data for analysis, so we used this data source. According to the OECD [
2], the use of online cash registers has the following advantages: better tax compliance, protection of fair competition, reduction of compliance burdens, and enhanced consumer protection. The other advantage of OCR is that we have quasi-real-time information about retail processes, the time to market is much faster than the classic questionnaire survey, and it reduces the statistical reporting burden on businesses.
The disadvantage of OCR data is that due to possible failures of the cash machines, NTCA will not receive data for another 11 months, so the first data transmission cannot be considered as final information. However, the differences between data sets are now negligible.
Transiting is a relatively rarely analysed part of tourism, despite the unquestionable importance of connectivity in tourism systems [
3]. One of the reasons for this, according to certain opinions, is that transit is partly seen as a low revenue generator and partly as a necessary inconvenience for tourists [
4].
2.2. Theoretical Background
Although transit is a phenomenon that affects many countries in Europe, the study of this kind of mobility is not part of mainstream national and international research on transport, migration and tourism. Some of the studies on transit issues focus on freight transport infrastructure and its development [
5,
6] and logistics [
7], while others focus on cost implications [
8,
9,
10,
11], environmental issues [
12] and geopolitical aspects [
13,
14]. Researchers are much more interested in exploring the specificities of traffic flowing through large cities [
15,
16,
17] than that between national borders.
Transiting is a specific form of mobility, as its main purpose is to cover the distance between the origin and the destination in the shortest possible time, while travellers usually do not consider the tourist experiences they may have on the way. However, transit does not exclude the use of the tourist services of the areas concerned, since transit passengers may interrupt their journey to buy fuel or to visit retail shops, but we should not forget the possibility of visiting certain tourist attractions and, in some cases, of using accommodation facilities [
18,
19,
20,
21]. Same-day movements are distinguished more by their duration and less by their radius. With minimal investment, same-day trips will meet tourist demand, and thus contribute to the development of tourism in general [
22].
Tourism researchers have a surprisingly lenient approach to the issue of transit, which is certainly related to the statistical interpretation of the concept [
23]. There are hardly any studies that have recognised the tourism implications of the behaviour of transit passengers. This topic is mainly addressed in studies on tourism in the former socialist countries of Central and Eastern Europe and South-Eastern Europe, where the flow of guest workers to the West is also highlighted [
24,
25,
26].
Transiting is a key phenomenon not only in land transport but also in water [
27] and air transport, with retail stores available from airport transit lounges, serving both to spend time and to encourage spending by transit passengers [
28,
29,
30,
31]. Researchers are also interested in the measurement of transit traffic, which, while not a potential substitute for classical traffic counting, can provide a useful complementary source of information from the spatial- and time-based recording of call volumes over a wide range of mobile communication devices [
32]. Last, but not least, the specific tourist behaviour of caravans and motorhomes is unexplored in the relationship between tourism and transit [
33].
Although our study tries to delimit the range of settlements that primarily benefit from transit tourism, we also consider it important to mention that transit has its drawbacks, the management of which is definitely a challenge for decision-makers. Such a challenge could be increased traffic, the resulting congestion, high levels of pollution, etc. This, in turn, leads us to the issue of tourism penetration [
34], which may be the subject of further research.
2.3. Transiting as a Crypto Mobility Activity
The tourism aspects of this phenomenon have also been recognised by relevant EU experts, who have suggested, among other things, the need to measure transit travel. Recital 5 of the EU regulation (Regulation (EU) No 692/2011 of the European Parliament and of the Council of 6 July 2011 concerning European statistics on tourism and repealing Council Directive 95/57/EC) to modernise the methodology of tourism statistics states that:
“The changing nature of tourism behaviour … with the growing importance of short trips and same-day visits contributing substantially in many regions or countries to the income from tourism […] means that the production of tourism statistics should be adapted.”
The previous definition of tourism, which assumed a minimum one-night stay, therefore needs to be amended to take into account not only so-called “excursion” traffic (shopping, visiting relatives), which is mainly concentrated in border areas and lasts less than 24 h, but also transit traffic. Since the paradigm of thinking about tourism [
35] excludes the discussion of the demand arising from the needs of freight transport actors and the supply created to satisfy them under the umbrella of tourism, it is still appropriate to ignore freight transport.
However, it should be noted that road corridors for freight transport include a number of infrastructure and suprastructure objects that are also used by lorry drivers. Thus, petrol stations offering complex services, roadside accommodation and catering outlets meet the demand not only of passengers but also of freight transport. Therefore, in a certain context, it is appropriate to carry out an analysis in this respect, even if the demand generated by freight transport is not considered as tourism expenditure.
If passenger transit is discussed as part of tourism, it is assumed that similar to conventional tourist mobility; it has its clear manifestations. However, while the fact of staying in a registered accommodation is included in tourism statistics, services used in unconventional tourism mobility rarely become part of a database that can be compared over space and time. The exploration of the territorial aspects of transiting, therefore, requires the creation of a methodological approach which, on the one hand, takes into consideration the specificities of the phenomenon under study and, on the other hand, is based on some statistically measurable fact. The challenge is not a minor one, as we need to make visible a crypto mobility, a quasi-invisible travel phenomenon. In our approach, we consider areas that are covered by official statistical data collection as visible tourism areas, and those that are not covered by official data collection as invisible tourism areas (for example: trips shorter than 24 h, border trips, the use of friendly accommodation). Within these, the present study deals mainly with the issue of transit.
For this, it is worth starting with the characteristic feature of transit that captures the moment of stopping for whatever reason. Buying fuel or shopping in retail stores is definitely one of them, but we should also bear in mind visiting certain tourist attractions and, in some cases, staying in accommodation. However, there is no statistical data on the number of visitors to each municipality, so in these cases only the OCR can provide a useful indication.
2.4. Delineation of the Municipalities Involved in Transiting Using GIS Methods
The first step of the analysis was to identify the Hungarian settlements that could be affected by transit traffic. The delineation was carried out using geographic information methods and taking into account the following criteria:
- (a)
When a transit traveller enters Hungary at a road border crossing point, he or she does not leave Hungary at the same border crossing point from which he or she arrived.
- (b)
Due to the nature of transit, it was also assumed that a person transiting through Hungary would use the shortest route in time between the entry and exit points.
Based on these criteria, the shortest travel time to all border crossing points in all neighbouring countries was determined. The municipalities affected by the intersection of each route were selected and summarised. The possibility was considered that transit traffic might benefit not only the settlements directly affected by transport routes, but also neighbouring settlements. However, we considered this to be an isolated and ad hoc phenomenon and the original delineation was therefore considered sufficient. Based on this delineation, 956 of Hungary’s 3152 settlements were included in the scope of the study, i.e., this was the number of municipalities considered as potential crystallisation points for transit traffic, and further investigations were carried out on this population of municipalities.