CC BY
0Received: 11.2.2024 Accepted: 20.4.2024
Original scientific paper
UDK: 338.48-52(497.11) 796.9
DOI: https://doi.org/10.58984/smb2401007j
Coresponding author: sasa.virijevicjovanovic@mbs.edu.rs
THE FACTORS OF SERVICE QUALITY IN SKI TOURISM ON THE EXAMPLE OF THE REPUBLIC OF SERBIA
Sasa Jovanovic 1, Goran Dokovic 2, Mirjana Gilic
3
Abstract: The aim of this paper is to provide an insight into the current models of service quality in ski tourism with a practical implication on the example of the Republic of Serbia. Nowadays, ski tourism has evolved into an important segment of the winter tourism industry in Europe. Its development was encouraged by the popularisation of skiing as a sport, as well as the growth of the number of people who ski professionally or recreationally.The studies from relevant publishers have been dealt with the concept of travellers' motivation in ski tourism from different point of views such as, the aspect of sustainable development in tourism, quality management, marketing strategy and customer satisfaction. When defining the research scope, it was noted that service quality represents an important driver of motivation in sports tourism. However, there is a certain research gap in exploring the factors that affect the service quality in winter sports, and in particular models and instruments that could provide their better understanding. In accordance with this statement, the research question in the study was to analyse the main determinants of service quality in ski tourism in the Republic of Serbia and to compare their relevance among the respondents belonging to different countries of origin and gender. The theoretical research presented in this paper was based on the application of a systematic literature review that has included relevant studies dealing with the concept of service quality in winter sport tourism. In addition, empirical research was conducted to address the research question in finding the factors that influence the service quality in ski tourism. The research was based on a sample of 208 skiers who visited the Republic of Serbia during the winter seasons in years 2023 and 2024. In the analysis and interpretation of the data, descriptive statistics, compare means and factor analysis were used.
Keywords: service quality, ski tourism, winter sports, quality management, sports tourism
1 Full professor, Modern Business School, Terazije 27, Belgrade, phone: +38163259083, https://orcid.org/0000-0002-4469-381X; E-mail: sasa.virijevicjovanovic@mbs.edu. rs
2 Associate professor, Modern Business School, Terazije 27, Belgrade, https://orcid.org/0000-0001-6842-031, E-mail: goran.djokovic@mbs.edu.rs
3 PhD Candidate, Faculty of organisational sciences, Belgrade, Serbia, E-mail: miramatic91 @gmail.com
www.smb.edu.rs
Introduction
The subject of this article deals with the research of service quality in ski tourism and the main factors that affect tourist satisfaction in ski destinations. Ski tourism has evolved into an important segment of the winter tourism industry attracting around 350 million skier visits annually (Steiger et al. 2019). Its development was encouraged by the popularisation of skiing as a sport, as well as the growth of the number of people who ski professionally or recreationally. One of the reasons for the popularization of this type of tourism is that skiing, which was once an elite sport, has now become more accessible to the wider population, which has had a positive effect on the growth of the ski tourism market.
Bieger et al. (2002) define the tourist destination of winter sports as the geographical, economic, and social unit, consisting of organisations, companies, activities and infrastructure, having as a goal to enable the satisfaction of specific needs of winter sports tourists. The most popular ski destination in the world are the Apls, with the so called "Big Four" ski countries that are situated in this region: Switzerland, Austria, Italy, and France. According to Statista (2023) around 37 percent of all ski resorts worldwide are in Alpine countries.
Literature review has recognised certain studies dealing with the concept of ski tourism from different aspects such as tourist motivation to travel, ski tourism sustainability and climate change (Prettenthaler et al., 2022), marketing strategies or ski tourism infrastructure. In addition, in some studies the concept of quality in ski tourism was examined from a perspective of seasonal employment in the sector (Ismert & Petrick, 2004). However, there is a certain research gap in exploring the determinants of service quality in winter sports. Therefore, the aim of this paper is to provide an insight into the current models of service quality in ski tourism with a practical implication on the example of the Republic of Serbia. The research question in the study was to analyse the main determinants of service quality in ski tourism in the Republic of Serbia and to compare their relevance among the respondents belonging to different countries of origin and gender.
Literature review
The modern concept of quality emphasises the customer as the only authoritative factor for the assessment of service quality (Djokovic & Celik, 2021). In accordance with this approach, the paper analyses the determinants of service quality in winter tourism from the perspective of tourist perception. Tsitskari, Tsiotras & Tsiotras (2006) define the concept of service quality in sport as a multi-dimensional structure that depends on a
socio - cultural context of a country and the type of service sector. The same conclusions were reached by Shang, Luo & Kong (2022) who stated that ski tourism is affected by multi-aspect factors. In addition, Thwaites & Chadwick (2013) indicated that service quality is the basis for differentiation on the sport tourism market and the development of competitive advantage. Another perspective of service quality in winter tourism was provided by Hallmann et al. (2015) who emphasised that the quality of accommodation, hotel staff, information management, destination policy and planning represent important indicators related to the quality standard of tourism product.
In exploring the concept of service quality in ski tourism, this paper was focused on the segment of recreational ski tourists, which has certain specificities. Theodorakis et al. (2009) in their study conducted a segmentation of recreational ski tourists according to motives, dividing them into four categories: beginners, lovers, naturalists, and tourists with multiple interests. Among the four categories of ski tourists, the authors have identified significant differences both in terms of loyalty and participation in the activities. The category of ski lovers had statistically higher results in engagement in activities compared to the remaining three groups of tourists.
Hudson & Shephard (1998) were among the first researchers who measured 10 factors of service quality at ski tourism destinations within focus groups and in-depth interviews in Switzerland. One year later, Weiermair and Fuchs (1999) conducted a study on a large sample of 1.822 tourists in Austria and Italy, demonstrating service quality indicators for ski resorts, which involved ski slopes, accommodation, restaurants, lift ticket service, employee service, and tour operator services. However, some authors used SERVQUAL model in measuring the quality of service in ski tourism. For instance, Weiermair and Fuchs (2000) have successfully applied this model for exploring tourists' judgments regarding service quality in alpine tourism.
Furthermore, Dickson and Faulks (2007) have analysed customer satisfaction in ski areas, showing that significant factors, which affect ski tourist decisions are safety and snow quality, the variety of tracks and space outside of tracks, but also other factors that are not directly related to skiing. These factors include shops, restaurants, and the possibility to participate in other recreational activities. In a study that was conducted in Alpine ski resorts, Faullant, Matzler & Füller (2008) have demonstrated that satisfaction and image rating affect the tourist's loyalty. Similar, Ferrand & Vecchiatini (2002) indicated how ski resort image, ski and non-ski service attributes impact customer satisfaction. In addition, Miragaia et al. (2016) were dealing with the satisfaction of ski tourists in ski destinations regarding the following determinants: capacities and equipment, characteristics of ski tracks, type of service in ski destination, restaurants, accommodation, and social activities, as well as the accessibility to a ski destination. Similar study was conducted by
Chua et al. (2015) who analysed the relations between "physical environmental stimuli (i.e., layout accessibility, aesthetics, cleanliness, and other visitors), perceived quality of physical environment, excitement, and behavioural intentions in ski resort". Moreover, Xiao, Yaping & Yanqin (2022) have explored ski tourism experience from the perspective of perceived value that includes four dimensions: facility value, perceived price, safety value and service value.
A significant insight into the research of ski tourism was made by Alexandris et al. (2006) who measured the service quality in skiing resorts using Brady and Cronin's three-dimensional service quality model (physical environment quality, interaction quality, outcome quality). The staring point in their study was the fact that services are intangible which brings attentions to other aspects of satisfaction such as social interactions with the staff and hospitality, the quality of physical servicescape regarding natural environment, the ski tracks, landscape and the so called outcome quality which is related to tourist experience. The same model was used in different surveys that included 345 visitors (Kyle et al., 2010) and 129 visitors (Barlas, Mantis & Koustelios, 2010) in Greek ski centres. Their questionaries consisted of 15 items that related to: facility quality (e.g., "ski slopes are well maintained"), interaction quality (e.g., "employees are friendly"), and outcome quality. The cited studies have also pointed out the service quality dimensions that affect word-of-mouth communication. In addition, significant contribution in studying ski tourism was made by Joppe, Eliot & Durand (2013) who investigated different segments in ski tourism market including skiers, snowboarders, and ski travellers according to "service considerations such as quality, entertainment, variety and lifestyle characteristics". Another research provided by Konstantinidis et al. (2018) has pointed out the entertainment factors as important aspect of ski tourism that influence the travellers' choices. In recent studies, Oralhan, Oralhan & Kirdok (2022) analysed the criteria that affects the tourists' choice of ski resorts in Turkey based on the following factors: "facility amenities, price, accessibility, accommodation, alternative tourism, and visitors' rating score".
The survey presented in this paper has included an analysis of different determinants (variables) of service quality in ski tourism which were successfully tested in practice and presented in cited literature. Having in mind the comprehensiveness of studies, they were used as a role model in designing the questionnaire for this research. However, the survey was additionally enriched with two service quality determinants referring to servicscape and nature.
Methods and sample
The theoretical research presented in this paper was based on the application of a systematic literature review that has included relevant studies dealing with the concept of service quality in winter sport tourism. Empirical research was conducted to address the research question in finding the factors that influence the service quality in ski tourism. The survey has included a sample of 208 (N=208) recreational skiers who visited the Republic of Serbia during the winter seasons in 2023 and 2024. The questionary was designed in accordance with the models presented in the literature review and included 18 statements (variables) referring to specific determinants of service quality in ski tourism. The variables were examined in the form of closed questions using a Likert scale with the following values: 1 = disagree; 2 = slightly disagree; 3 = neither agree nor disagree; 4 = slightly agree; 5= agree. In the processing and interpretation of the data, methods of factor analysis and compared means were applied.
Table 1 represents the sample structure by gender. Respondents were equally represented in the sample (N=208), with a slight majority of the male population (51,9%).
Table 1: The sample structure by gender Gender
Frequency Percent Valid Percent Cumulative Percent
Male 108 51.9 51.9 51.9
Valid Female 100 48.1 48.1 100.0
Total 208 100.0 100.0
Source: Authors' calculation in SPSS
The age distribution of the sample (table 2) is dominated by the respondents belonged to the 36-45 age category (62.5%) followed by the 47 -56 (15,4%), 57-65 (12%) and 2035 (10.1%) age groups.
Table 2: The age categories of respondents Age
Frequency Percent Valid Percent
Cumulative Percent
Valid
20-35 21 10.1 10.1 10.1
36-46 130 62.5 62.5 72.6
47-56 32 15.4 15.4 88.0
57-65 25 12.0 12.0 100.0
Total 208 100.0 100.0
Source: Authors' calculation in SPSS
In relation to the country of residence, the respondents were from the following countries: Serbia (54.3%), Bosnia and Herzegovina (19.7%), Russia (9.1%), Montenegro (9.6%), North Macedonia (3.8%), Croatia (3,4%). Detailed data on this variable are shown in table 3.
Table 3: Respondents' countries of residence Country of residence
Frequency Percent Valid Percent
Percent
Serbia 113 54.3 54.3 54.3
Bosnia and Herzegovina 41 19.7 19.7 74.0
N.Macedonia 8 3.8 3.8 77.9
Valid Montenegro 20 9.6 9.6 87.5
Russia 19 9.1 9.1 96.6
Croatia 7 3.4 3.4 100.0
Total 208 100.0 100.0
Source: Authors' calculation in SPSS
Research results
The respondents have ranked the importance of 18 variables that affect their perception of service quality in ski tourism. The variables have included different aspects such as facilities of ski resorts, snow conditions and ski tracks, additional services including shops and restaurants, accommodation, social life, landscape, and nature. To reduce the number of variables for further exploration, the method of factor analysis was applied at the beginning of this research.
Having in mind the data demonstrated in table 4 showing that KMO=0.748 is greater than 0.6, and Bartlett's Test of Sphericity is statistically significant (p=0.000), the factor analysis was considered justified in this study.
Table 4: KMO and Bartlett's Test
KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .749
Bartlett's Test of Sphericity Approx. Chi-Square 3108.259
Df 153
Sig. .000 Source: Authors' calculation in SPSS
Table 5: Total Variance Explained Total Variance Explained
Com-po-
Initial Eigenvalues
Extraction Sums of Squared Loadings
Rotation Sums of Squared Loadingsa
rieru Total %% of Variance Cumulative % Total % of Variance Cumulative % Total
1 5.609 31.163 31.163 5.609 31.163 31.163 4.112
2 3.781 21.006 52.170 3.781 21.006 52.170 4.316
3 1.896 10.531 62.701 1.896 10.531 62.701 2.753
4 1.563 8.682 71.383 1.563 8.682 71.383 3.281
5 1.088 6.045 77.428 1.088 6.045 77.428 1.327
6 .925 5.139 82.567
7 .687 3.816 86.383
8 .588 3.267 89.650
9 .385 2.140 91.790
10 .367 2.040 93.829
11 .271 1.506 95.336
12 .203 1.129 96.465
13 .167 .929 97.394
14 .132 .736 98.129
15 .121 .674 98.803
16 .096 .533 99.336
17 .067 .373 99.709
18 .052 .291 100.000
Extraction Method: Principal Component Analysis.
a. When components are correlated, sums of squared loadings cannot be added to obtain a total variance.
Source: Authors' calculation in SPSS
The table of Total Variance Explained (table 4) indicated five factors that have eigenvalues higher than 1. Together they account more than 77% of the variability in the original variables. In addition, the Eigenvalues and component numbers are demonstrated on a Scree Plot in figure 1.
Figure 1: Scree Plot
Scree Plot
Component Number
Source: Authors' calculation in SPSS Table 6: Component Matrix Component Matrixa
Component
1 2 3 4 5
Diversity of ski tracks .832 .366
Accommodation prices .820 .360
Lift maintenance and .812 -.440
functioning
Restaurants prices -.772 -.429
Quality of the slopes .756
Facilities quality .668 -.564
Meeting different people -.651 -.357
Supermarkets and shops .649 .500 .398
Nightlife .615 .556 -.325
Competence of the .453 .404
employees and hospitality
Restaurant quality .862 -.329
State of equipment -.342 -.802
Snow conditions .755 .470
Parking .548 .421 -.306
Accommodation quality .419 | -.708 .328
Health and safety services -.415 .561 .593
Nature .779
Landscape .331 .402 .406
Extraction Method: Principal Component Analysis. a. 5 components extracted.
Source: Authors' calculation in SPSS
According to the findings presented in table Component Matrix the variables were grouped within 5 factors. The first factor was highly associated with the following determinants: diversity of ski tracks, the quality of slopes, lift maintaining and functioning, the prices of accommodation and restaurants, facility quality, meeting different people and nightlife. Within the second factor the variables such as restaurant quality, state of equipment, parking and snow conditions were recognised as the most dominant. The third factor was associated with supermarket and shops and accommodation quality, while the fourth factor has the highest association with health and safety services. The fifth factor was related to nature and landscape.
Further research was conducted to compare the respondents' answers regarding the variables that were highly associated with the first factor. The data presented in table 7 demonstrate the compared means in variables between the ski tourists from different countries of residence. When interpreting the data it should be noted that higher representation of domestic tourists (54.3%) was represented in the sample, The highest mean values in answers were registered for variables "diversity of ski tracks" (Total M=4.89), "facilities quality" (Total M=3.93) and "quality of the slopes" (Total M=3.53).
For variable "lift maintenance and functioning" the highest mean was recorded among the respondents from Serbia (M=3.08, SD=0.73) in comparison with the lowest mean value among the respondents from North Macedonia (M=2.25, SD=0.46). Diversity of ski tracks was recognised as the most important determinant, with the highest mean values between the tourists from Bosnia and Herzegovina (M=4.97, SD=15), Montenegro (M=4.95, SD=0.22), Serbia (M=4.94, SD=0.22) and Russia (M=4.84, SD=0.37). Furthermore, respondents from Montenegro had the highest means for variables "quality of the slopes" (M=3.75, SD= 0.55) and "nightlife" (M=3.7, SD=0.73). Ski tourists from North Macedonia had highest mean values for variables "restaurants prices" (M=4.5, SD=0.92) and "meeting different people" (M=4, SD=0), while respondents from Serbia highly appreciated "facilities quality" (M=4.12, SD=0.66) as a determinant of service quality in ski tourism. The findings presented in table 7 are statistically significant according to ANOVA table (p=0.00) for selected variables.
Table 7: Compared Means regarding the country of residence
Report
Country of residence
Lift maintenance and functioning
Diversity of Quality of ski tracks the slopes
Restau- Meeting
rants Night-life different prices people
Facilities quality
ai Mean 3.0885 4.9469 3.6814 3.0619 2.7345 3.5752 4.1239
-Q r e N 113 113 113 113 113 113 113
Std. Deviation.73869 .22523 1.06289 .65850 1.00905 .51418 .66992
1 A Mean 2.9756 4.9756 3.4878 3.4878 2.9512 3.0244 3.6829
ag ae N 41 41 41 41 41 41 41
> se .S ^ CO Std. Deviation.15617 .15617 .55326 .92526 .31235 .15617 .47112
8 ™ (Ü c s o Mean 2.2500 4.2500 2.2500 4.5000 1.5000 4.0000 2.7500
N 8 8 8 8 8 8 8
. T3 z Std. Deviation.46291 .46291 .46291 .92582 .92582 .00000 1.03510
(Ù o Mean 2.9500 4.9500 3.7500 2.4500 3.7000 3.0500 3.8500
tr ng oe N 20 20 20 20 20 20 20
Mn Std. Deviation.22361 .22361 .55012 .94451 .73270 .22361 .36635
ia si Mean 3.2632 4.8421 3.4211 3.3158 2.4737 3.1579 4.2105
s u N 19 19 19 19 19 19 19
R Std. Deviation.73349 .37463 .76853 1.05686 .90483 .37463 .63060
ai Mean 2.2857 4.2857 2.5714 4.1429 1.8571 3.7143 3.1429
at or N 7 7 7 7 7 7 7
u Std. Deviation.48795 .48795 .97590 1.46385 1.46385 .48795 1.06904
al Mean 3.0096 4.8942 3.5337 3.2019 2.7692 3.3990 3.9327
t o N 208 208 208 208 208 208 208
1— Std. Deviation.64449 .30828 .94732 .92083 .98521 .50063 .71916
Source: Authors' calculation in SPSS
Table 8: ANOVA table regarding countries of residence
ANOVA Table
Sum of Squares
df
Mean Square
Sig.
Lift maintenance Between (Combined) 10.327 5 2.065 5.515 .000
and functioning * Groups
Country of Within Groups 75.653 202 .375
residence Total 85.981 207
Diversity of ski tracks * Country of residence Between (Combined) Groups 6.611 5 1.322 20.448 .000
Within Groups 13.062 202 .065
Total 19.673 207
Quality of the slopes * Country of residence Between (Combined) Groups 23.394 5 4.679 5.821 .000
Within Groups 162.371 202 .804
Total 185.764 207
Restaurants prices * Country of residence Between (Combined) Groups 36.797 5 7.359 10.716 .000
Within Groups 138.723 202 .687
Total 175.519 207
Between (Combined) 39.191 5 7.838 9.790 .000
Nightlife * Country Groups
of residence Within Groups 161.732 202 .801
Total 200.923 207
Meeting different Between (Combined) Groups 16.389 5 3.278 18.655 .000
people * Country of residence
Within Groups 35.491 202 .176
Total 51.880 207
Facilities quality * Country of residence Between (Combined) Groups 23.849 5 4.770 11.579 .000
Within Groups 83.209 202 .412
Total 107.058 207
Source: Authors' calculation in SPSS
F
The analysis of ski tourist decisions related to countries of residence was also considered to be important aspect in a study based on a panel data covering 28 Austrian ski resorts conducted by Falk (2010). Furthermore, Tj0rve et al. (2018) indicated the correlation between the country of respondent's residence and repeated tourist visits of winter destinations. The comparison between the respondents' countries of
residence was also provided by Praet et al. (2015) who explored the perceptions among international ski visitors in Japan.
To address the Research Question in this study an additional analysis between the respondents' gender was performed. Compared means among the respondents' gender (table 9) have showed higher mean values in male answers related to variables "lift maintenance and functioning" (M=3.04, SD=0.21), "diversity of ski tracks" (M=5, SD=0.92), "nightlife" (M=3.31, SD=0.42) in compare to female respondents with higher means referring to "restaurants prices" (M=3.46, SD=0.84), "meeting different people" (M=3.62, SD=0.48) and "facilities quality" (M=4.05, SD=0.94). However, the differences in answers regarding "lift maintenance and functioning" and "quality of the slopes" were not statistically significant (p>0.05), while other findings match the values of statistical significance (p<0.05), which is demonstrated in ANOVA table 10.
Table 9: Compared means between the gender Report
Gender
Lift maintenance and functioning
Diversity of Quality of Restaurants
ski the slopes prices tracks
Nightlife
Meeting different people
Facilities quality
Mean 3.0463 5.0000 3.5370 2.9630 3.3148 3.1944 3.8241
u N 108 108 108 108 108 108 108
£ Std. Deviation .21111 .00000 .50095 .92651 .46661 .42047 .38253
Mean 2.9700 4.7800 3.5300 3.4600 2.1800 3.6200 4.0500
rä N 100 100 100 100 100 100 100
J Std. Deviation .90403 .41633 1.26695 .84591 1.05773 .48783 .94682
Mean 3.0096 4.8942 3.5337 3.2019 2.7692 3.3990 3.9327
S N 208 208 208 208 208 208 208
° Std. .64449 .30828 .94732 .92083 .98521 .50063 .71916
Deviation
Source: Authors' calculation in SPSS
Table 10: ANOVA table regarding respondents' gender
ANOVA Table
Sum of Squares
df
Mean Square
Sig.
Lift Between (Combined) .302 1 .302 .727 .395
maintenance Groups
and Within Groups 85.679 206 .416
functioning * Total 85.981 207
Gender
Diversity of ski tracks * Gender Between Groups (Combined) 2.513 1 2.513 30.169 .000
Within Groups 17.160 206 .083
Total 19.673 207
Quality of the slopes * Gender Between Groups (Combined) .003 1 .003 .003 .957
Within Groups 185.762 206 .902
Total 185.764 207
Restaurants Between Groups (Combined) 12.827 1 12.827 16.242 .000
prices * Gender Within Groups 162.692 206 .790
Total 175.519 207
Between (Combined) 66.867 1 66.867 102.752 .000
Nightlife * Groups
Gender Within Groups 134.056 206 .651
Total 200.923 207
Meeting Between (Combined) 9.403 1 9.403 45.603 .000
different Groups
people * Within Groups 42.477 206 .206
Gender Total 51.880 207
Facilities quality * Gender Between Groups (Combined) 2.650 1 2.650 5.229 .023
Within Groups 104.407 206 .507
Total 107.058 207
Source: Authors' calculation in SPSS
These findings can be compared with the studies conducted by Glaes (2009), Pomfret & Doran (2015), which have also confirmed that gender presents an important variable in ski tourism. A significant contribution in studying the gender perspective of ski tourism was made by Williams & Lattey (1994) who recognised the importance of female skiers as tourists and their decisions in developing marketing strategies. Furthermore, Konu et
F
al. (2011) have also analysed the gender perspective of ski destination choice on the sample of Finnish ski resort customers. In exploring the outdoor recreational tourism in Sweeden, Godtman et al. (2020) have identified the existence of gender inequality. Additionally, Mirehie & Gibson (2020) indicated three dimensions in female skiers that affect their travel decisions such as resort amenities and activities, snow-sport conditions and quality, and price.
Conclusion
The paper provides an insight into the most significant scientific approaches and models that deal with the quality of services in ski tourism. Based on the literature review, it was indicated that important determinants of service quality in winter tourism relate to three aspects: physical environment quality, interaction quality, and outcome quality. The cited models and theoretical approaches were used as an example in designing the questionnaire that was applied in this study and consisted of 18 variables relating to different aspects of service quality in ski tourism. The findings of empirical research that was conducted on a sample of recreational skiers (N=208) in winter destinations in the Republic of Serbia indicated the existence of five different factor that affect the perception of service quality in ski tourism. The first factor was associated with the highest number of variables such as the diversity of ski tracks, the quality of slopes, lift maintaining and functioning, the prices of accommodation and restaurants, facility quality, meeting different people and nightlife. In accordance with this findings, further research was focused on exploring the identified variables among the respondents' gender and countries of residence. The highest mean values in respondent answers were registered for variables "diversity of ski tracks" (M=4.89), "facilities quality" (M=3.93) and "quality of the slopes" (M=3.53). Diversity of ski tracks was recognised as the most important determinant, with the highest mean values between the tourists from Bosnia and Herzegovina (M=4.97, SD=15), Montenegro (M=4.95, SD=0.22), Serbia (M=4.94, SD=0.22) and Russia (M=4.84, SD=0.37), which was statistically significant (p=0.00). Compared means among the respondents' gender have demonstrated higher mean values in male answers related to variables "lift maintenance and functioning" (M=3.04, SD=0.21), "diversity of ski tracks" (M=5, SD=0.92), "nightlife" (M=3.31, SD=0.42) in compare to female respondents with higher means referring to "restaurants prices" (M=3.46, SD=0.84), "meeting different people" (M=3.62, SD=0.48) and "facilities quality" (M=4.05, SD=0.94). The differences in answers regarding "lift maintenance and functioning" and "quality of the slopes" were not statistically significant (p>0.05), while other findings match the values of statistical significance (p<0.05).
The results presented in this article provide additional insight into the conceptualization of service quality in ski tourism and indicate the importance of its measurement. Furthermore, the empirical study conducted in the Republic of Serbia contributes to the clarification of the practical analysis of service quality determinants in ski tourism from the perspective of tourist gender and country of residence. However, certain limitations of this research should be emphasised, which relate to the significantly larger share of domestic tourists in the sample, as well as the fact that the respondents (except Russia) were from the same region, which indicates the existence of cultural and social similarities in quality perception.
Conflict of interests
The authors declare no conflict of interest. Author Contributions
Conceptualization: Djokovic, G. Investigation: J. S., Dj. G., Theoretical framework: G. M., Data curation: J. S., Resources: J. S., Gilic, M., Writing - original draft: Dj. G., J. S., Writing - review& editing: J. S. All authors have read and agreed to the published version of the manuscript.
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