Description
Online travel agencies (OTA) are online marketplaces that allow potential consumers to plan and book travel products and services such as tours (Shi, Leung, & Munelli, 2022). To make customer experience more diverse and engaging, OTA heavily features tours that comprise sequence of episodes or events (Peluso, Pino, & Mileti, 2022). For instance, one-day tour in Sydney, Australia may consist of episodes that unfold sequentially: a wildlife park, a rainforest visit, wine tasting and a scenic coastline escape. Such arrangements in a single tour are expected to leave long-lasting memories in tourist via having them interacted with different attractions in a destination (Kim, Ritchie, & McCormick, 2012). When making decisions, tourists browsing such tours often intuitively visualize themselves attending each event listed and make predictions about how they will feel in that situation (Karl, Kock, Ritchie, & Gauss, 2021).
It is established that consumer’s anticipated emotional responses to the mental representation of a future event significantly affect their current decisions and behaviors (Ahn & Kwon, 2019; Karl et al., 2021). However, emotion rarely exists at a single point in time (Li, Walters, Packer, & Scott, 2018). This characteristic complicates the assessment of multi-episode tours since it might not solely depend on individuals’ anticipated emotion towards each single episode or multi-episode tour as a whole (Montgomery & Unnava, 2009). Rather, individuals may generate differentiated anticipated emotions towards various events within a tour, resulting into the dynamic succession of their anticipated emotion that extends over the course of tour product exposure. Yet, existing research mainly examines tourist’s anticipated emotion as a static construct and primarily focuses on their overall predicted feelings towards the destination or experiences (Qiu, Wang, Wei, Morrison, & Wu, 2022; Zhao, Wang, & Ji, 2020), leaving the impact of anticipated emotional variability on their travel intention unexplored.
Against this backdrop, the current research aims to examine whether, why, and under which types of tourists multiple-episode tour featuring a high (vs. low) anticipated variability generates greater booking intention based on cognitive appraisal theory. The research questions addressed are as follows: 1) Do multiple-episode tour with a high (vs. low) anticipated emotional variability result in greater travel intention? 2) If so, why? 3) Does this effect hold for different types of tourists, such as high verse low variety seekers?
To achieve these objectives, we employed a mixed-method approach incorporating secondary data collected in OTA and four scenario-based online experiments. Study 1(a) aims to examine and compare the actual sales of multiple-episode tour with a high (vs. low) anticipated emotional variability in Ctrip – the largest online travel agency platform in China. To establish the casual relationship between anticipated emotional variability and booking intention, Study 1 (b) and (c) proceed to test consumers’ response to manipulated multiple-episode tour with either a high or anticipated emotional variability. Study 2 examined the mediating role of perceived novelty and interest in the relationship between anticipated emotional variability and booking intention. Finally, in Study 3, we further explore the role of variety seeking tendency in moderating the impact of anticipated emotional variability on perceived novelty.
Our study is expected to contribute to the literature in several ways. First, this study adds to the literature on affective forecasting by identifying anticipated emotional variability as a key and distinct emotion-related feature that influences tourist’s decision making. Second, this study contributes to literature on temporal sequence by applying cognitive appraisal theory to elucidate the underlying mechanism of the rollercoaster effects. In particular, we find that multi-episode tours with more volatile sequence induce greater perceived novelty and interest, thereby enhancing tourist’s willingness to book the tour. Last, this study adds to the literature on variety seeking tendency (VST) by demonstrating VST as unique boundary condition for the rollercoaster effects. Tourist with high VST respond more favorably to tour featuring more dynamic sequence, whereas such effect diminishes among low variety seekers.
Reference:
Ahn, J., & Kwon, J. (2019). Green hotel brands in Malaysia: perceived value, cost, anticipated emotion, and revisit intention. Current Issues in Tourism, 23(12), 1559-1574. doi:10.1080/13683500.2019.1646715
Karl, M., Kock, F., Ritchie, B. W., & Gauss, J. (2021). Affective forecasting and travel decision-making: An investigation in times of a pandemic. Annals of Tourism Research, 87. doi:10.1016/j.annals.2021.103139
Li, S., Walters, G., Packer, J., & Scott, N. (2018). Using skin conductance and facial electromyography to measure emotional responses to tourism advertising. Current Issues in Tourism, 21(15), 1761-1783. doi:10.1080/13683500.2016.1223023
Montgomery, N. V., & Unnava, H. R. (2009). Temporal Sequence Effects: A Memory Framework. Journal of Consumer Research, 36(1), 83-92.
Peluso, A. M., Pino, G., & Mileti, A. (2022). The interplay of hedonic trend and time pressure in the evaluation of multi-episode tour experiences. Tourism Management, 90, 104459. doi:https://doi.org/10.1016/j.tourman.2021.104459
Qiu, H., Wang, X., Wei, W., Morrison, A. M., & Wu, M.-Y. (2022). Breaking bad: how anticipated emotions and perceived severity shape tourist civility? Journal of Sustainable Tourism, 1-21. doi:10.1080/09669582.2022.2108039
Shi, S., Leung, W. K. S., & Munelli, F. (2022). Gamification in OTA platforms: A mixed-methods research involving online shopping carnival. Tourism Management, 88, 104426. doi:https://doi.org/10.1016/j.tourman.2021.104426
Zhao, X., Wang, X., & Ji, L. (2020). Evaluating the effect of anticipated emotion on forming environmentally responsible behavior in heritage tourism: developing an extended model of norm activation theory. Asia Pacific Journal of Tourism Research, 25(11), 1185-1198. doi:10.1080/10941665.2020.1837892
