Why is the issue of over-tourism important? According to the UNWTO (World Tourism Organization) [1
], tourism demand is increasing significantly with an increase in the number of tourists from 25 million in 1950 to 1.3 billion in 2030. There are a few side effects of rapid quantitative growth such as the influx of tourists to a region that exceeds the tourism capacity, which is called over-tourism [1
]. Tourists come and go from pre-existing spots and sometimes they visit new areas which are not prepared for over-tourism. When over-tourism occurs, residents experience its side effects in environmental, economic, and social aspects, whereas tourists experience a decrease in visit satisfaction due to crowding, and a lower likelihood of return visits [3
]. Irresponsible use of resources due to tourism development has led to conflicts between tourists and locals, creating difficulties in sustainable tourism [6
]. Side effects from over-tourism have been reported around the world, and solutions are being sought [2
Over-tourism occurs when too many people gather at any one particular place, and it is associated with over-crowding and carrying capacity [1
]. In this regard, solutions that are being considered include regulation and education, limiting visitor numbers, and distribution [2
]. However, tourism is a demand-driven activity that is difficult to regulate or educate. It is also burdensome for destinations to forcibly regulate the number of tourists which inevitably leads to quantitative reduction [8
]. On the other hand, distribution is utilizing off-peak seasons and times, distributing tourists to other regions, and changing the target tourism market [2
]. This should be based on the characteristics of the destination and an understanding of the visitors to a destination. Distribution through clear targeting not only improves the quality of tourism by easing crowding and increasing satisfaction, but can also achieve sustainable quantitative growth including balanced development during all seasons (peak or off-peak seasons) [9
]. This is not a new solution from over-tourism but is widely used in tourism and outdoor recreation [10
], and is also explained conceptually as substitutability, or alternative recreation opportunity [12
]. However, existing studies do not deal with the distribution of visitors in night tourism as a solution for over-tourism, and being mostly case studies, there is a lack of empirical research on the applicability of visitor distribution.
Thus, the present study examines visitor distribution as a solution for over-tourism, especially in night tourism. Night tourism is a form of sightseeing that takes place during the night. It is popular in its economic impact of increasing length of stay through the use of overnight accommodations [13
] Night tourism increases immersion and attraction to destinations or activities through the reduction of vision at night [14
]. In Korea, cultural assets which were previously only opened during the day due to management issues have now been opened at night. Night tourism focuses mainly on cultural assets and promotes aspects such as night views, night experience activities, night transportation, night performances, and interpretation [15
]. However, when night tourism is active and more tourists enter a limited area, crowding impairs immersion to the destination [14
]. In addition, when there are many people at night, when vision is limited, safety issues may arise [16
]. Thus, a solution for over-tourism during night tours is more important than for daytime tours.
The purpose of the present study is to find a concrete way of distributing visitors to solve over-tourism in night tourism. In order to do this, the willingness to pay of night visitors to Suwon Hwaseong Fortress, a UNESCO (United Nations Educational, Scientific and Cultural Organization) World Heritage site, was estimated for less preferred times and seasons. Less preferred times and seasons were defined as non-peak times and seasons. According to Suwon City, Suwon Hwaseong is a representative tourism destination that has 720 thousand daytime tourists per year in 2019. At that time, the night tourism program was provided during just three days and 130 thousand nighttime tourists had been visited. Since the limitations of infrastructure and place on the event days, over-tourism has been raised as a problem at night. Suwon City has considered distribution strategies as a solution to the nighttime over-tourism problem based on the experiences to temporal distribution of night tourism at heritage sites in Korea. As mentioned in previous studies [2
], this study explores the possibilities of temporal distribution as an effective solution on Suwon Hwaseong nighttime over-tourism by empirical research.
Specifically, this study aims were first, to estimate visitors’ willingness to pay for non-peak times and compare it to the willingness to pay for peak times, and see if the temporal distribution was possible. Second, the study aimed to compare visitors’ willingness to pay for non-peak seasons with the willingness to pay for peak seasons, and to see if the seasonal distribution was possible. Third, the study aimed to compare the willingness to pay for night tourism attributes using the choice experiment method. We examined which attributes should be given more emphasis on establishing strategies for temporal and seasonal distribution of night tourists. The present study aims to empirically examine the application of visitor distribution as a solution for over-tourism in night tourism, with an emphasis on sustainable tourism development through mitigation of over-tourism.
4.1. Sample Characteristics
Of all 563 respondents, demographic characteristics of the sample included more women (n = 343, 60.9%) than men (n = 220, 39.1%). The average age of participants was 39.9 years (SD = 12.57), with more visitors older than 30 (n =159, 28.2%) than those in their 40s (n = 155, 27.5%) or 20s (n = 120, 21.3%). Residents from the Suwon area (i.e., within 30 min; n = 280, 49.7%) and the Gyeonggi Province (i.e., 30 min to 1 h; n = 175, 31.1%) accounted for more than three-quarters of the sample (80.8%), indicating that visit rate was highest among residents within one hour travel time (i.e., local visitors). College attendance/graduation was the most common educational level (n = 347, 61.6%) and household income was more than 4 thousand dollars a month (n = 323, 57.4%), which indicated a high proportion of highly educated and high-income visitors. 48.3% of visitors had visited Suwon Hwaseong Fortress three times or more during the past year (i.e., excluding first visit and one-time revisit). In relation to night tourism, 80.2% of respondents preferred night tourism between 6 and 10 p.m., and 10.8% for 10 –12 a.m., and 7–9 a.m. In terms of seasons, 67.7% of respondents only preferred the peak seasons of spring and fall, and 32.3% also preferred the non-peak seasons of summer and winter.
4.2. Visitors’ WTP for Less Preferred Times
Groups were divided according to their preferred times for night tourism, with Group A’s preference for peak times of 6 –10 p.m., and Group B’s preference for non-peak times of 7–9 a.m. and 10 p.m. to 12 a.m. (Table 2
). A comparison of the frequency of visits did not show a large difference in that 48.2% of Group A visitors who prefer peak times visited Suwon Hwaseong Fortress more than three times in the past year, whereas 49.2% of Group A visitors who prefer non-peak times visited more than three times.
showed the conditional logit model estimation results of the selection experiments for each group. First, the coefficient estimates of payment amount are negative and statistically significant at the p < 0.01 significance level. Thus, when other conditions are held constant, the larger the amount of payment, the lower the probability of selection, indicating rational decision-making has occurred in the experiment. Again, the coefficient estimates by attribute and level were positive and statistically significant (except for interpretation). That is, when other conditions are constant, the probability of choosing another alternative (level 2 or level 3) increases compared to the baseline (level 1).
MWTP estimation results for each group are summarized in Table 4
. Overall, MWTP increases from level 2 to level 3, but not at a statistically significant level. Group B that prefers non-peak times has a relatively lower MWTP, except for rides. However, as the differences are small, Group B still demonstrates the willingness to pay, and the dispersion of visitors to non-peak times would be possible through discounts and product differentiation.
The order of preference for attributes differs between the two groups with MWTP for level 3 in Group A that prefers peak times in the order of Performance > Experience activities > Paid rides > Night views > Interpretation. In contrast, Group B’s order of preference is Tourism vehicles > Performance > Experience activities > Night view > Interpretation. Thus, willingness to pay for performances and rides varies the most depending on the preferred time of visits. Group B visitors who prefer non-peak times have a relatively lower willingness to pay. However, considering the margin of error, the differences in payment amount in willingness to pay are not statistically significant at the 0.10 level. Group B also indicated a higher willingness to pay for Tourism vehicles, and this difference was statistically significant.
4.3. Visitors’ WTP for Less Preferred Seasons
Based on preferred seasons for night tourism, groups were divided into Group C that prefers only peak seasons (spring, fall), and Group D that also prefers non-peak seasons (summer, winter). Due to seasonal characteristics of Korea, visitors are mainly concentrated during the seasons of spring and fall which are the most pleasant times to enjoy night sightseeing. Considering the frequency of visits, 46.5% of Group C visitors who only prefer peak seasons had more than three nights visits to Suwon Hwaseong Fortress, whereas 52.2% of Group D visitors who also prefer non-peak seasons had more than three visits. This indicates that many visitors who also prefer non-peak seasons are loyal visitors to tourist attractions. In contrast to the results of the MWTP for less preferred times, the MWTP in the group that also prefers non-peak seasons may be higher.
The conditional logit model estimation results of the CE for each group are summarized in Table 5
. The coefficient estimates of the payment amount in both groups are negative and statistically significant at the 0.01 level, indicating rational decision making occurred. All attribute and level coefficient estimates in both groups were positive and statistically significant.
The difference in MWTP in groups divided according to preferred seasons was greater than in groups divided according to preferred times. Group D that also prefers non-peak seasons was more willing to pay than Group C that only prefers peak seasons. In particular, MWTP was 1.7–2.8 times larger for paid experience activities, tourism vehicles, and interpretation, and these differences were statistically significant. The payment amount that visitors were willing to pay at level 3 were highest in the order of Performance > Experience activities > Tourism vehicles > Night view > Interpretation.
The present study was an empirical examination of temporal and seasonal distribution that is considered to be a possible solution for over-tourism. The possibility of distribution was tested by comparing willingness to pay between peak and non-peak times during night tourism activities at Suwon Hwaseong Fortress, a UNESCO World Heritage site. The contribution of this study is to expand the scope of the study of over-tourism to the overlooked field of night tourism.
The results and implications are as follows. First, in terms of frequency of night tourism visits, the group that also preferred the non-peak seasons group had higher visiting frequency compared to the group that only preferred peak seasons. There was, however, no difference between peak time preferred group and non-peak time preferred group. The result of the temporal comparison indicates that, regardless of preferred time zones, night tourism activities can only be offered until 10 p.m. That is, visitors to the study site are not familiar with various night zones. However, considering Mont-Shell Michel in France and the Taj Mahal in India, which are open from sunset to sunrise, it will be necessary to examine the possibility of expanding opening hours. The result of the seasonal comparison is in line with substitutability that local residents and regional visitors can be made to visit during non-peak times (i.e., mornings, evenings, and weekdays) rather than at peak times [12
Second, the comparison of willingness to pay for night tourism products between the group that preferred peak times and the group that preferred non-peak times showed that the willingness to pay was lower for all products except for tourism vehicles in the non-peak times group. The reason why willingness to pay of the non-peak times preferred group was high for tourism vehicles is that non-peak times are non-operating time zones at this site. Also, the number of seats and operating time zones of tourism vehicles are also fixed. Thus, there is an additional willingness to pay for currently non-operating time zones and to reduce inconveniences caused by overcrowding. There was also a positive willingness to pay for all attributes in the case of non-peak times preferred group. This suggests that visitors will still visit even if they are distributed to different time zones. It is thus necessary to expand gradually from the provision of services that do not cost a lot even during non-peak times. Tourism vehicles for which visitors indicate a high willingness to pay maybe a key product to attract tourists during non-peak times. This study expands the scope of night tourism with an expansion of temporal range, supporting previous studies which propose an expansion of night tourism targets [14
Third, in relation to seasonal distribution, a comparison of the group that prefers only peak seasons and the group that also prefers non-peak seasons showed that the latter group showed a higher willingness to pay for all attributes. Specifically, willingness to pay was high for experience activities, tourism vehicles, and interpretation, suggesting a high preference for the avoidance of overcrowding inconveniences that occur during peak seasons for these contents. The high frequency of visits of the group that also prefers non-peak seasons seems to be influencing their high willingness to pay. These findings expand Hospers’ [5
] examination of the usefulness of temporal distribution by comparing visitors’ willingness to pay, and provide practical implications for the applicability of temporal distribution.
For sustainable night tourism, the management of over-tourism is important. This study examined the possibility of temporal and seasonal distribution as a solution for over-tourism in night tourism by estimating the willingness to pay for peak and non-peak times of visitors to a World Heritage site. This is important in terms of sustainable development of night tourism, and the implications of this study are as follows.
First, temporal and seasonal distribution were proposed as a solution for over-tourism in night tourism. Existing over-tourism research has been conducted in a case-by-case manner without empirical testing of methods that have been carried out under the general concepts of crowding or displacement, rather than considering site or visitor characteristics [2
]. However, distribution criteria should be based on an understanding of both the characteristics of the destination and its tourism resources, as well as the target market. This study thus proposed a specific distribution method based on characteristics of night tourism. Night tourism refers to tourism at all other times during which day tourism occurs. With developments in transportation, one can easily leave destinations, and the benefits of night tourism such as overnight lodging do not always occur. Late night times (i.e., after 10 p.m.) or early morning times (i.e., earlier opening times) may be effective ways of temporal distribution. Seasonal distribution methods were also presented by comparing visitors who prefer non-peak seasons in addition to general peak seasons. These solutions can be effective in attracting additional tourists by providing differentiated tourism products that consider seasonal characteristics.
Second, the choice experiment method was used to examine in more detail the distribution of night tourism visitors. Choice experiments allow estimations of the MWTP according to each attribute and level of night tourism products. The findings suggest that there are restrictions on service provision for temporal and seasonal distribution, and that emphasis should be placed on interpretation, tourism vehicles, and experience activities during which the inconveniences of overcrowding are especially felt.
Third, the applicability of temporal and seasonal distribution was tested through an examination of visitors’ willingness to pay during peak or non-peak times. The distribution of visitors to non-peak times is aimed at sustainable development of target resources [9
] in terms of preventing peak season crowding, improving satisfaction, and reducing fluctuations in demand, through an easing of over-tourism in night tourism. In addition, it is possible to broaden the field of night tourism by targeting time zones during which night tourism content is not yet provided. Thus, in order to avoid crowding during peak times and lower quality tourism experiences, there is a need to provide both pleasant and differentiated experience activities during non-peak times for visitors.
Finally, similar to previous studies that examined the characteristics of potentially distributable groups [11
], this study examined characteristics of the group of visitors that preferred non-peak times. According to Manning [12
], visit frequency may still be high for local residents and regional visitors even if time zones are changed. Providing support for this, visitors who also preferred non-peak seasons had a high number of night tourism experiences at the study site (22.4 average visits vs. 13.2 average visits for peak times). The non-peak preference group can be seen as loyal customers for whom various strategies such as discounts, and time zone or season specific services and product development are needed. The results of this study indicated a high willingness to pay for night tourism experience activities, tourism vehicles, and interpretation, allowing specific distribution strategies to be established.
Given the exploratory nature of this study in which just the possibility of distribution was tested, the intention to visit based on specific services/products was not directly examined. For actualization of distribution, more detailed research is needed on so-called loyal customers who are likely to visit frequently. Through big data analysis, visit patterns by times/seasons should be obtained, and basic distribution data should be prepared in order to break down time zones and seasons in more detail. Since this study is about the specific case on over-tourism of night tourism, to generalize the results more researches are needed in other cases. In addition, to introduce a temporal distribution as a solution for over-tourism, the incentives for workers and local residents, who provide the services, should be considered. Despite theoretical and practical limitations, the present study is meaningful in that it pursues sustainable development through elimination of over-tourism in night tourism at a World Heritage site by testing the possibility of distribution in more detail using visitors’ willingness to pay.