What influences Vietnamese Airbnb travelers’ positive electronic word-of-mouth intentions? An extension of the Mehrabian – Russell model

Abstract

Purpose This study aims to investigate the relationship between environmental stimuli of Airbnb experience, customers’ perceived enjoyment and positive electronic word-of-mouth (eWOM) intentions through an extension of the Mehrabian–Russell model. Design/methodology/approach A quantitative methodology was adopted using a web-based survey. Data were collected from a sample of 162 Vietnamese Airbnb consumers who had stayed at the platform accommodations. A two-stage procedure with the partial least squares approach to structural equation modeling was conducted to evaluate the measurement model and structural model. Findings The results confirmed the significant positive effect of home benefits and social interaction on Airbnb customers’ perceived enjoyment, which subsequently inspires them to develop intentions to spread positive comments toward this platform. Moreover, these relationships remain unchanged among the different groups of customers, except Airbnb travelers with business purposes. Practical implications The findings will provide Airbnb stakeholders in emerging markets with insights into identifying the important environmental factors that are more likely to stimulate consumers’ enjoyment and encourage them to spread positive WOM on social network outlets. Originality/value This research provides a deeper comprehension of Airbnb users’ emotional states and positive eWOM intentions by exploring the possible antecedents. Moreover, to the best of the authors’ knowledge, this is the first study to propose the moderating role of gender, purpose of the trip and type of accommodation in the hypothesized relationships. The contradictory findings of this study also highlight the cultural difference in Airbnb customers’ perception and behavioral intentions.

Examining Relationships Among Emotional Experience, Place Identity, and Destination Loyalty

“…In contrast, avoidance behavior encompasses opposite actions, such as leaving the environment and disregarding attempts at communication from others (Mehrabian & Russell, 1974). The M-R model has been utilized and validated in service domains in various domains such as restaurants (Tan et al, 2022), themed hotels (Sun et al, 2021), Airbnb (Do et al, 2022) and consumer events (Manthiou et al, 2017).…”

Investigating the dynamic mechanism of user willingness to actively publish travel-related Electronic Word-of-Mouth (eWOM) on tourism platforms

“…This study aims to fill this gap by using a combination of system dynamics causality diagrams and technology acceptance models to measure and understand the dynamic mechanism behind tourists’ willingness to actively publish eWOM on tourism platforms. Additionally, as the literature review suggests that previous studies have used system dynamics and technology acceptance model separately to investigate willingness to publish eWOM [ 25 ], it is unclear how these two models interact and influence each other in our context. We use structural equation modeling to determine the path coefficients and the degree of influence among the dynamics factors.…”