Mega-sporting events often contribute to both financial and nonfinancial aspects of a destination. Nonetheless, several problematic issues (e.g. risk/safety issues, high travel costs, and online broadcasting) require a hosting destination focusing more on marketing and promotion strategies to boost event attendance. As such, this study aims to understand the optimal bundling package strategy for a mega-sporting event by investigating the effect of customers’ life cycle stage on their preferences in purchasing an event-related package. Several event package features used in this study are important determinants of mega-sporting event participation. More important, respondents in different family life cycle stages showed different levels of sensitivity to each package attribute, thereby constructing different preferences. The result of this study would be useful information for designing more attractive mega-sporting event packages and/or target marketing strategies focusing on different life stages.
As travel activity has gained attention as one of the essential ways of understanding the sustainable growth of social tourism, a growing number of research projects have been conducted to elucidate the relationship between residents’ travel quantity (frequency) and quality (experience) in both macro and micro perspectives. Yet, very little research has highlighted that travel opportunities are not equally available to residents, especially a longitudinal perspective. The current study classified domestic travelers into four distinct classes using four years of longitudinal data from 5054 Korean residents. Latent growth curve modeling (LGCM) and growth mixture modeling (GMM) were employed to find out (1) the optimal number of classes, (2) the longitudinal travel frequency trajectory of each class, and (3) the distinctive demographic and travel characteristics of the four classes. This study provides some practical implications for policymakers when optimizing available resources for sustainable travel opportunities to relevant target sub-populations. Furthermore, detailed step-by-step analytic tutorials are also introduced for the extended application of longitudinal latent variable analysis in the tourism and hospitality fields, providing additional insights for relevant stakeholders.
Online customer reviews increasingly influence customer purchase decisions. Indeed, many customers have highlighted the significance of online reviews as an influential source of information. This study reports an investigation of the differential effects of online reviews, such as valence and volume, on the customer share of visits. Our findings suggest that valence (i.e., star rating) had more effect, giving a higher average check size to restaurants on the share of visits, while number reviews (volume) did not drive the share of visits to restaurants regardless of the average check size. Therefore, the ideal for casual dining restaurant brands would be to manage highly positive ratings to retain their customers.
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