PurposeTheme park experiences ubiquitously unfold in the presence of others. In acknowledgement of this important part of theme park consumption, this research set out to examine if other visitors help create an immersive environment and, in turn, memorable experiences for theme park visitors.Design/methodology/approachAn online survey was distributed to 561 theme park visitors. Structural equation modeling (AMOS 26) was used for testing the hypotheses in the proposed framework.FindingsResults of SEM analyses reveal the positive impact of perceived similarity on visitors' sense of immersion at theme parks and the memorability of the experience. In turn, memorable experiences further drive behavioral intentions (i.e., return intention and willingness to pay premiums).Practical implicationsThe findings provide suggestions for theme parks to leverage customer-to-customer interactions in order to create immersive and memorable visitor experiences.Originality/valueThis research marks one of the first attempts to approach customer-to-customer interactions (CCIs) at theme parks by empirically examining the impact of the perceived similarity of others on focal visitors' emotions and experiences.
PurposeThis study reviews existing research and current applications of artificial intelligence (AI) in the hospitality and tourism industry. It further proposes a new evaluation framework to inform the susceptibility of AI adoptions.Design/methodology/approachThis is a synthesis and evaluation study that qualitatively summarizes and presents findings on AI applications in the hospitality and tourism industry. Current AI applications are rated using a seven-dimensional framework based on Rogers' (2003) diffusion theory.FindingsAI adoption susceptibility in the hospitality and tourism industry varies based on the type of AI. Search/booking engines, virtual agents and chatbots rank high in the adoption susceptibility.Research limitations/implicationsThis study bridges innovation diffusion theoretical underpinnings and AI applications. The findings support researchers, developers and managers in evaluating the adoption susceptibility of AI technologies in the hospitality and tourism industry.Originality/valueThis paper is among the few that focus on assessing AI adoption susceptibility in the hospitality and tourism industry. This paper develops a theory-based framework for systematically evaluating AI innovations in hospitality and tourism.
PurposeThis study aimed to bibliometrically and visually analyze and review hospitality and tourism marketing studies published from 2000–2020.Design/methodology/approachA total of 3,942 articles collected from the databases of Social Science Citation Index (SSCI) and Science Citation Index Expanded (SCI-E) in the Web of Science (WoS) along with their references were used for analyses. The bibliometric software HistCiteTM and literature measurement visualization tools, VOSviewer and CiteSpace, were employed to analyze the selected articles.FindingsThe results of the study demonstrated top influential scholars and institutions, intellectual structure and emerging trends of the study topics, and future research opportunities in the field of hospitality and tourism marketing.Research limitations/implicationsFirst, academic influence of a scholar was evaluated by citations of his/her publications, which did not take the order of authorship into consideration. Second, this study was restricted to the English language journals. Third, other types of published documents related to the studied field such as review papers were not considered by this research.Originality/valueIn comparison to traditional qualitative analysis such as content analysis, bibliometric analysis is a more objective approach to vividly demonstrate trends and performance of a research field, offers unique insights for its advancement with wider inclusiveness of a larger amount of data.
Classical gardens offer ample cultural and natural landscapes for visitors to appreciate. Taking the tourist gaze as a theoretical lens, this study assumes a netnographic approach and conducts narrative analysis on travel blogs to explore visitors’ experiences at Chinese classical gardens. Findings revealed key domains of the gaze object (i.e., macro-level structural design and micro-level elements) and the way of gaze (i.e., spatial and temporal), which formed the Chinese gaze in the tourism context. Results further showed how gaze contributed to Yijing development, a unique Chinese aesthetic concept. This study enriches the tourism and aesthetics literature by positioning a classical aesthetic concept (Yijing) within a modern tourism practice (gaze). Practical implications for tourism development and destination marketing are provided.
Systemic shifts in consumer preferences and expectations are not new, and can often be accelerated by major environmental events. Early evidence suggests that the events of 2020 to 2021 may have created that acceleration to fundamentally alter future consumer preferences. In this study, we argue that consumer expectations are on the path to being essentially transformed. If so, such transformations will require a renewed focus on consumer preferences in the context of an ecosystem comprised of the macro-, meso-, and micro-level factors impacting these changes. Changing consumer expectations will also need to be articulated and incorporated more comprehensively to include physical, mental, and social wellbeing. In this study, we argue that consumer behavior research will need to incorporate these fundamental shifts in factors impacting consumer preferences. We present a conceptual framework that incorporates the changing landscape of factors influencing this transformation along with suggestions for future research, and theoretical and practical implications.
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