A Study of Tourists’ Holiday Rush-Hour Avoidance Travel Behavior Considering Psychographic Segmentation

Abstract

Tourists are confronted with congestion caused by concentrated travel during public holidays. In order to guide tourists to make voluntary changes regarding their travel times during holidays, this paper focuses on exploring holiday rush-hour avoidance travel behavior (HRATB) considering psychological factors. First, based on the theory of planned behavior, the effects of psychological factors including attitude, subjective norm, and perceived behavior control on holiday avoidance travel intention and behavior were quantitatively analyzed by the structural equation model. Second, according to those three subjective psychological factors and the three objective factors of age, monthly income, and tourist group, the segmentation method of the latent class model was adopted to explore tourists' preferences with regard to HRATB. Finally, an empirical analysis was carried out through questionnaire data. The results show that attitude, subjective norm, and perceived behavior control have significant impacts on intention and behavior with regard to holiday avoidance travel. There are significant differences in psychological observation variables such as rush-hour avoidance travel intention, attitude and subjective norm among the four segments of tourists, and cost sensitivity. In addition, this paper puts forward some countermeasures and suggestions for the four types of tourists. Conclusions provide a theoretical basis for formulating travel measures to attract different types of tourists.

Can Road Toll Convince Car Travelers to Adjust Their Departure Times? Accounting for the Effect of Choice Behavior under Long and Short Holidays

“…2 The impact coefficient of travel time is positive, indicating that travelers with longer travel time are more likely to travel before the holiday. 3 The influence coefficient of the last departure time is positive, indicating that the previous travel experience has a positive influence on the choice of departure time.…”

“…This may be a response to traffic congestion on the first day of the holiday, which may lead to the loss of more time with more waiting when there are multiple travelers, and there is greater mutual influence and restriction. 3 The influence coefficient of the relationship between travelers is positive and indicates that a tourist who travels with family or friends tends to depart before the holiday. 4 The impact coefficient of the number of previous trips is negative, and it indicates that the greater the number of previous trips (3 times or more), the less inclined tourists are to set out on a peak travel day, which suggests that individuals who have traveled more in the past are more focused on the experience of travel.…”

“…6 The influence coefficient of whether seniors accompany travelers is positive, which indicates that individuals lacking the accompaniment of older people tend to travel during holidays. (3) Travel characteristics: 1 The influence coefficient of travel range is positive, indicating that the travelers in the city or suburb are more likely to travel on the second or third day of the holiday during the short vacation. 2 The impact coefficient of travel time is positive, indicating that travelers with longer travel time are more likely to travel before the holiday.…”

Spatial-Temporal Response Patterns of Tourist Flow under Real-Time Tourist Flow Diversion Scheme

“…Some scholars focus on the factors which affect tourists' congestion perception and behavior adjustment. Based on the structural equation model, Zhu et al pointed out that tourists' attitude, subjective norm (e.g., family and friends, new media), and perceived behavior control (e.g., lacking of abundant time, preferential travel costs) have significant influence on the intention and behavior of avoiding travel during rush-hour on holidays [9]. Han et al discussed the feedback mechanism among tourism information release mode, tourists' congestion perception and behavior adjustment.…”

“…The "over-tourism" problem should not only be regarded as a tourism problem or a city problem, but also be observed and solved by researchers in various disciplines from a perspective of broader social and urban development [7]. In the disciplines of traffic engineering and science of decision making, some scholars and management departments have carried out some research to adjust and control tourists' decision-making behavior and balance tourists' spatial-temporal distribution, such as redistributing the existing parking resources, releasing the information of staggered shifts, adjusting the road toll discount on holidays, and implementing tourist flow control schemes (TFCS) [8][9][10][11][12][13].…”