Digital Marketing in the Tourism Sector: Adoption Intentions and their Determinants

Abstract

This research addresses the predictors of the intention to adopt digital marketing in the context of the tourism sector in Nepal by exploring the relationships between Social Media Marketing (SMM), Perceived Risk (PR), Tourism Business Performance (TBP), Perceived Ease of Use (PEOU), Perceived Usefulness (PU), and the intention to adopt digital marketing (ADM). With a descriptive quantitative and causal-comparative approach to research design, data was sourced from 400 tourism businesses like tour operators, travel agents, and accommodation providers. A self-administered online questionnaire was designed and shared in the field via Google Forms for data collection to analyze the variables of interest using literature review for establishing Item validity and reliability. The positive relationship ship between the variables was examined. The study found a moderate correlation between SMM and ADM (SMM; ADM, r = .412, p < .01) and strong correlational relationships between the levels of TBP and ADM (TBP; ADM, r = .513, p < .01) and PEOU and ADM (PEOU; ADM, r = .436, p < .01). Also, regression showed that SMM (β = 0.152, p = 0.001), PR (β = 0.121, p = 0.002), TBP (β = 0.229, p = 0.000), PEOU (β = 0.241, p = 0.000), and PU (β = 0.099, p = 0.005) significantly predict the intention to adopt digital marketing. These results corroborate social influence theory as social media may induce businesses to integrate digital marketing as the associated risks are lower, and the benefits to the business are higher, therefore, the integration of digital marketing within businesses is higher. This research emphasizes the necessity of tourism enterprises appropriately adopting straightforward digital systems and social media marketing to improve customer interaction. Competitive Stimulation and within the tourism sector will improve results. The research was limited to the cross-section of one industry; the authors recommend other industry cross-sections, measuring time differences, and other factors to gain greater insight into the digital marketing adoption continuum.