5 sciendo Holešinská, A., Holubová, E., Čomor, M. • Future tourism development based on... Future tourism development based on the knowledge of preferential choice of HSR Andrea Holešinská1 , Eliška Holubová1 , Marián Čomor2 e-mail: holesinska@econ.muni.cz, Comor.Marian@slovakrail.sk 1 Faculty ofEconomics and Administration, Masaryk University, Brno, Czech Republic 2 Železničná spoločnosťSlovensko, a.s., Košice, Slovakia Holešinská, A., Holubová, E., & Čomor, M. (2022). Future tourism development based on the knowledge of preferential choice of HSR. Czech Journal of Tourism, 11(1-2), 33-41. DOI: 10.2478/cjot-2022-0003. Abstract The paper contributes to the extensive knowledge on the impacts of high-speed transport systems on transport-related human behaviour. The paper presents the case of the Czech Republic - a small transit country in Central Europe where the government plans to build high-speed transport systems to improve transport connectivity within Europe. This step will certainly be met with a response. So, the aim of the paper is to find out how high-speed rail (HSR) influences tourism development in the Czech Republic. Therefore, the paper focuses on behaviour of travellers and analyses its intention to switch from a certain mode of transport to HSR. In order to predict future tourism development, determinants of transport mode choice are analysed and tested to learn more about travellers' preferences and their potential change in their behaviour. The findings reveal that HSR would stimulate international tourism and for certain circumstances it would help to recover MICE tourism. Keywords HSR, determinants of transport mode choice, travellers' preferences, tourism development JEL classification: L83, L92, R41 Accepted: 12 November 2022 (33 - 41) I CZECH JOURNAL OF TOURISM 01-02/2022 | 33 Holesinska, A., Holubova, E., Comor, M. • Future tourism development based on... Introduction In terms of transportation, the Czech Republic has a strategic geographical position in Central Europe. It is considered as a transit country. However, the transport infrastructure is not sufficient. Though the density of rails is high, there are no high-speed rails (HSR) in the Czech Republic. The current rails do not enable the speed of 250 km/h or more. Even the modernisation of the rail system did not help with reaching such speed limits. Therefore, the Czech Ministry of Transportation issued the Programme for H S R development (2017) with the mission to build a new high-speed rail that would connect Germany in the West, Austria in the South, Slovakia in the East, and Poland in the North. This intention is strongly supported by the strategic political priority at the E U level. Besides connectivity, H S R is often discussed in the context of sustamability. Generally, H S R is labelled as a "green" mode of transport (Barr & Prillwitz, 2012; Le-Klahn, Gerike, & Hall, 2014; Albalete & Bel, 2017; Gross & Grimm, 2018) because it has the lowest carbon footprint worldwide (statista.com, 2018). Nevertheless, it should be highlighted as well that building and maintaining H R S is so financially demanding that the environmental benefits could not compensate for the costs (Lochman, 2014). Therefore, each government faces at least two questions I) whether H S R will be efficient, and 2) in what terms it improves the regional economy. The travellers' behaviour and their potential preferences to choose H S R can provide answers to the above stated questions. The aim of the paper is to find out whether the potential H S R will influence tourism in the Czech Republic (as a part of the regional economy). If yes, in what way? Theoretical basis The research is based on the theory of planned behaviour that studies determinants of transport choice. Ajzen (1991) identifies three independent determinants: attitudes, subjective norms, and perceived behavioural control. A different perspective is introduced by Dann (1999) who distinguished "push" factors of transport choice (characteristics of respondents), and "pull" factors that characterised the mode of transport. Going more into detail, Holubova (2022) categorizes the pull factors into technical factors, internal (emotional) factors and external factors of the mode of transport (see Figure I). Technical factors are closely connected with the technical parameters of each mode of transport. Internal factors are related to emotional perceptions of the mode of transport. And finally, external factors are determined by local conditions. (33 - 41) | CZECH JOURNAL OF TOURISM 01-02/2022 | 34 Holesinskä, A., Holubovä, E., Comor, M. • Future tourism development based on... Figure 1 Factors/characteristics of the mode of transport (Source: Holubovä, 2022) Technical factors Speed Price Frequency Reliability Flexible time of departure Safety Work on journey Service on journey Comfort Reluctant to drive for a long distance Tradition of the mode of transport in family Comfort for travelling with children Comfort for travelling with oversized luggage Intimacy External factors Accessibility destination from station Environmental friendly transport Time spent parking The knowledge of factors that determine travellers' choice is essential for the model shift. It studies the intention of travellers to switch to public transport, mainly to tram (Dickinson, Robbms, & Fletcher, 2009; Le-Klahn, Gerike, & Hall, 2014). Besides the factors related to the characteristics of the mode of transport, such as "ease of use," or being "trouble-free" (Borhan, Ibrahim, & Miskeen, 2019), there are other determinants. The intention of travellers to use a tram can be influenced by the offer of a new product (e.g., a new multi-modal ticket - Lumsdon, Downward, & Rhoden, 2006) that is integrated and designated as well (Nordlund & Wistm, 2013). Another important determinant that stimulates a willingness to switch is marketing, precisely information providing (Le-Klahn, Gerike, & Hall, 2014). Concerning destination marketing even the nature of the destination can make travellers change their preferences in the mode of transport (Dickinson, Robbms, & Fletcher, 2009). Moreover, it was found that the shift can be caused by the awareness of environmental aspects (Barr & Prillwitz, 2012). Methodology To give an answer on whether the potential H S R will influence tourism in the Czech Republic it is essential to test the probability of switching from a different mode of transport to H S R . Another step is to determinate what factors (push or pull, see Dann, 1999) make tourist-travellers choose a certain mode of transport, namely tram (HSR). Finally, on the basis of tourist-travellers' behaviour, the potential future tourism development in the Czech Republic is identified. Date was collected by face-to-face interviewing that was carried out from July to October 2019. The research was conducted as part of the long-term inter-sectoral project called "New Mobility — High-Speed Transport Systems and Transport-Related Human Behaviour." One of the research topics is "The potential for high-speed transport in tourism." The interviewing took place in three cities (Prague, Brno, and Ostrava) that are planned as the major nodes of the potential H S R system in the Czech Republic. Quantitative research based on the importance of the nodes in the Czech transport (33 - 41) I CZECH JOURNAL OF TOURISM 01-02/2022 | 35 Holesinska, A., Holubova, E., Comor, M. • Future tourism development based on... system and on the plan for the construction of H S R (Quota: Prague—800, Brno—600, and Ostrava—400) was quoted. The quota dependably reflects the importance of tourism activities in these destinations. Data sample The object of the research is a traveller who fits the definition of tourism in terms of the length of his/her stay and the purpose of travelling, i.e., one-day traveller, tourist, business trips, visitor of relatives, and transits. Another criterium for the sample was the mode of transport. For the research, car, bus and tram were relevant. Those respondents who forgot to indicate their mode of transport or used a different type were excluded. Thus, the total sample contains 1,641 respondents (see Table I). Table 1 Data sample (Source: authors, 2022) Characteristics of respondents Count Percentage Gender (#18) Male 803 48.9 Female 836 50.9 Without gender 2 0.1 Age (#19) 15-19 38 2.3 20-34 613 37.4 35-44 474 28.9 45-54 242 14.7 55-64 173 10.5 65+ 80 4.9 Without age 21 1.3 Place of residence (#2) Czech Republic 858 52.3 Austria 189 11.5 Germany 198 12.1 Poland 168 10.2 Slovakia 181 11.0 Others 47 2.9 Purpose of travel (#1) Business trip 446 27.2 One-day leisure trip 311 19.0 Overnight stay 452 27.5 Visit of relatives 361 22.0 Transit 71 4.3 Means of transport (#5) Car 699 42.6 Bus 124 7.6 Train 818 49.8 The data sample provides gender equality. From tourism perspectives, the sample consists of 858 domestic (Czech) tourist-travellers and 783 foreign tourist-travellers. A l l age categories are covered. Concerning the place of residence, the sample includes all important countries on the potential H S R corridors. (33 - 41) | CZECH JOURNAL OF TOURISM 01-02/2022 | 36 Holesinska, A., Holubova, E., Comor, M. • Future tourism development based on... Methods Date was tested based on the mode of transport. Descriptive statistics helped to analyse both the absolute and relative frequency of respondents' characteristics and their willingness to use H S R . Thus, the potential (switch to H S R ) change in travellers' behaviour was identified. The research tested "pull" factors that characterised each mode of transport. They were categorised according Holubova (2022). Respondents were asked to evaluate each of them. The evaluation statements were put into the Likert scale from "completely (slightly) important" via "neutral" to "completely (slightly) unimportant." The responses "do not know" were ignored. T o determine preferred factors of transport choice, their average and variability were analysed. To express travellers' preferences the comparison among the factors of each mode of transport (parametric data) was checked for statistical significance using the A N O V A test and the multiple comparison post hoc test. Based on these findings and with respect to the global situation (e.g., C O V I D - I 9 , Green Deal, etc.) the contextual model of the influence of H S R on tourism in the Czech Republic was extrapolated. Results Switching to HSR A willingness to use H S R instead of other means of transport was tested in the context of time savings. Time savings would make half of all respondents (see Table 2) change their choice and they would prefer H S R to the other modes of transport. One third of travellers would not switch to H S R anyway. However, there is a hidden potential in 16.9% of respondents who did not yet know whether they would use H S R . Table 2 Willingness to use HSR (Source: authors, 2022) Willingness Agree % Disagree % Not know % Total 886 54.0 478 29.1 277 16.9 Transport modes Car 214 30.6 327 46.8 158 22.6 Bus 61 49.2 28 22.6 35 28.2 Train 611 74.7 123 15.0 84 10.3 Place of residence Czech Republic 471 54.9 260 30.3 127 14.8 Austria 140 74.1 37 19.6 12 6.3 Germany 110 55.6 60 30.3 28 14.1 Poland 53 31.6 75 44.6 40 23.8 Slovakia 86 47.5 -> -> 18.2 62 34.3 Others 26 55.3 13 27.7 8 17.0 Purpose of travel Business trip 258 57.8 124 27.8 64 14.3 One-day leisure trip 140 45.0 108 34.7 63 20.3 Overnight stay 268 59.3 131 29.0 53 11.7 Visit of relatives 173 47.9 103 28.5 85 23.5 Transit 47 66.2 12 16.9 12 16.9 (33 - 41) | CZECH JOURNAL OF TOURISM 01-02/2022 | 37 Holesinska, A., Holubova, E., Comor, M. • Future tourism development based on... The research discovered that the most willing to switch to H S R are the users who prefer tram for their travelling in tourism, and their purpose of travel is either business trip or overnight stay. Foreigners dominate among tram-users who would prefer H S R , mainly travellers from Austria. Transit travellers also exhibited a high probability to use H S R (66.2%). Concerning bus-users, there is positive potential (49.2%) to change their mode of transport to H S R as well. Czechs are typical bus-users. Therefore, there is potential demand for H S R in domestic tourism. O n the other hand, car-users expressed that their preference for travel by car would probably not change. The explanation is in the purpose of their travelling — overnight stay. Most of the disagree statements come from Czech and Polish travellers. The results show that the youngest generation (15-19) and travellers in the age of 45-54 are more likely determined to use H S R . Factors influencing the choice of the mode of transport From a descriptive statistics perspective, technical factors demonstrate more objective evaluation contrary to the internal and external category of factors. These factors are considered more personal (subjective). There is evidence that technical factors do not show significant differences in evaluation across age groups, gender, or place of residence. However, the evaluation of external, and internal factors varies. For example, the factor comtort shows that female concern tram as the most comfortable mode of transport, whereas male prefer car. The analysis of the averages (u.) and variability (o) of each factor (see Table 3) and their comparison provide interesting results. Table 3 Evaluation of factors (Source: authors, 2022) Transport mode factors Car (n==664) Bus (n==122) Train (n==804) o H o o Technical factors Speed 1.620 0.854 1.926 0.970 1.827 0.845 Price 2.334 1.790 1.694 0.890 1.858 1.155 Frequency - - 1.926 0.970 1.885 0.966 Reliability 1.686 0.889 1.746 0.845 1.798 0.809 Flexible time of departure 1.468 0.698 2.041 1.048 1.990 0.953 Safety 2.065 1.514 2.075 1.269 1.916 1.222 Work on journey 3.088 2.317 3.391 2.272 2.571 2.048 Service on journey - - 3.132 2.379 2.252 1.595 Internal factors Comfort 1.646 0.842 1.943 0.906 1.746 0.834 Reluctant to drive for a long distance - - 3.096 2.210 2.538 1.850 Tradition of the mode of transport in family 2.825 2.191 3.774 1.844 3.359 2.079 Comfort for travelling with children 3.084 2.596 3.704 1.686 3.469 2.309 Comfort for travelling with oversized luggage 2.426 2.116 3.108 1.780 2.468 1.993 Intimacy 1.666 1.140 - - - External factors Accessibility of destination from station - - 2.067 1.162 2.079 1.812 Environmentally friendly - - 2.487 1.363 2.312 1.790 Time spent parking 2.498 1.708 - - - (33 - 41) | CZECH JOURNAL OF TOURISM 01-02/2022 | 38 Holesinska, A., Holubova, E., Comor, M. • Future tourism development based on... For car-users, the most important factor isflexibletime of departure (u.= 1.468). Its variability is the lowest (o=0.698) and at the same time it is the biggest advantage of that mode of transport. Other factors that motivate travellers to choose a car are speed, comfort, intimacy, and reliability. O n the other hand, disadvantages in comparison to other modes of transport are price, and time spentparking. Those who travelled by bus consider price as, the most completely important factor (u=1.694) for their decision. According to the results, the bus is the best price mode of transport in general. Tram-users highly evaluate safety (yi—1.916) contrary to car and bus-users' choice. Factors of reliability (a=0.809) and comfort (G=0.834) show a low variability of all factors even across the modes of transport. Although the factors of work on journey and service on journey do not dominate in travellers' choice, in the future they might be an advantage for trains and potentially H S R in comparison to other modes of transport. In general, factors, such as reluctance to drive a long distance, tradition of the mode of transport in the family, comfort tor travelling with children, and comfort tor travelling with oversizedluggage, show high variability. Thus, these factors are irrelevant for the process of choosing a certain mode of transport in this research. From a statistical point of view, the most significant factor is reliability (p=0.0665540). The A N O V A test reveals that it is the only factor independent of the chosen mode of transport (see Table 4). Concerning multiple comparisons the most significant preferential factors of train (resp. H S R ) are price and safety m comparison to car — the mode of transport. Table 4 (In)dependence of transport mode factors (Source: authors, 2022) Transport mode factors ANOVA j) a=0.05 Technical factors Speed 0.0000112 pa Flexible time of departure 0.0 p