Consumer engagement in e-Tourism: Micro-panel data models for the case of Spain

Muñoz, Teresa Garín; Pérez–Amaral, Teodosio; López, Rafael

doi:10.1177/1354816619852880

Cited by 11 publications

(6 citation statements)

References 34 publications

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“…This variable reflects the consumer's digital skills and the habit of using online shopping channels. These findings are in line with Garín-Muñoz et al (2020) and confirm that digital consumer skills are a determinant factor of e-Tourism adoption. On the other hand, airlines were the pioneers in introducing this type of online sales and have generated great confidence among consumers, favouring the adoption of electronic commerce.…”

Section: Prediction Of E-tourist Behavioursupporting

confidence: 86%

“…Previous studies support that sociodemographic and economic factors, such as gender, age, education, income level, and digital skills, among others, mainly determine the adoption of the Internet as a shopping channel in tourism (Aeknarajindawat, 2019;Amaro & Duarte, 2015;Garín-Muñoz et al, 2020). Some other research examines the effect that certain travel characteristics may have on online tourism consumption.…”

Section: Brief Literature Reviewmentioning

confidence: 99%

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Consumer behaviour in e-Tourism: Exploring new applications of machine learning in tourism studies

Mendieta-Aragón

Muñoz²

2023

invest. tur

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Digital markets have altered how economic agents interact and have changed the behaviour of tourists. In addition, the COVID-19 pandemic has shown that it is necessary to constantly monitor the evolution of digital consumer behaviour and the factors that influence it, as they are dynamic elements that evolve over time. This paper analyses digital inequalities and validates the main factors influencing tourists to book online tourism services. This research uses a set of microdata with 69,752 and 23,779 observations to analyse the booking mode of accommodation and transportation services, respectively, obtained from the Resident Travel Survey of the National Statistics Institute of Spain during the period 2016-2021. The article confirms variations in the online consumer profile and in the trip's characteristics. One of the most relevant findings is the narrowing of the generational gap in the online contracting of tourist services. However, there are remaining digital inequalities, such as regional inequalities and others based on the education level and income of tourists. It is also highlighted that different types of trips, depending on the destination, the type of accommodation or transport have a different propensity to be booked through digital purchase channels. The accessibility to big data sources and recent advances in machine learning models have also made the methodologies for analysing digital consumer behaviour evolve and must be incorporated into tourism studies. This study compares the predictive performance of different methodologies in the context of e Tourism. In particular, we evaluate the potential predictive power that could be obtained using machine learning techniques to explain consumer behaviour in e-Tourism and use it as a benchmark to compare it with the results obtained using traditional statistical methods. The selected predictive evaluation metrics show that the logistic regression statistical model outperforms the predictive power of the Multilayer Perceptron neural network and presents values very close to the maximum predictive power achieved by the Random Forest algorithm.

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Section: Prediction Of E-tourist Behavioursupporting

confidence: 86%

Section: Brief Literature Reviewmentioning

confidence: 99%

Consumer behaviour in e-Tourism: Exploring new applications of machine learning in tourism studies

Mendieta-Aragón

Muñoz²

2023

invest. tur

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“…In summary, the literature supports a relationship between eGov usage, demographics, and socio-economic variables (Reddick, 2005; Hung et al , 2006; Garín-Muñoz et al , 2019; Colesca and Dobrica, 2008), but regional-level disparities require further investigation.…”

Section: Theoretical Frameworkmentioning

confidence: 94%

European regional inequalities in citizens’ digital interaction with government

Rodriguez-Hevía

Rodríguez-Fernández

Ruiz-Gómez

2022

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Purpose The purpose of this research is to study what factors influence European citizens in their interaction with government in the EU regions. It analyses the differences across European regions, taking account of each region’s degree of economic development and incorporating different spatially tailored approaches into the analysis. Design/methodology/approach A logistic regression analysis was used to establish whether the profiles of e-Government users differ according to the development tier they live in and other explanatory variables: socio-demographic, digital skills and type of internet connection. Findings This research identifies regional inequalities in EU citizens’ digital behaviour with public administration. This statistical study of European regions allows to better apprehend the profile of the EU’s e-citizens and offers conclusions to explain citizens’ behaviour, highlighting the influence of several variables. Originality/value Given the lack of pan-European e-government studies at a regional level, this article provides a comparative analysis for the European Union and gives insights into the behaviour of European e-citizens, highlighting the presence of digital inequalities in Europe depending on the region where citizens reside.

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“…More particularly, on the supply side, digitalization has encouraged travel trade and hotel suppliers to optimize their business processes [11], explore new opportunities and business models to improve profitability [12], promote and market their services [13], and increase customers' added value and their satisfaction. On the demand side, digitization has changed the way tourists plan their trips and holidays, purchase products/services, and experience destinations [14,15]. Online reviews on interactive travel websites have become an essential source of information for tourists [16], providing them with helpful information in making travel decisions.…”

Section: Introductionmentioning

confidence: 99%

Exploring and Evaluating the Impact of ICTs on Culture and Tourism Industries’ Convergence: Evidence from China

ChunBo

Sotiriadis

2021

Sustainability

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Information and communications technologies (ICTs) have been driving the digital revolution of all industries worldwide. Industrial convergence constitutes a new feature and trend of contemporary industrial development and has received extensive attention from the media and public. However, the interrelationship between the two concepts—industrial convergence and ICTs—remains under-researched. This paper aims to explore and evaluate the ICTs’ impact on industrial convergence by focusing on the interrelationship between culture and tourism. The study takes an industrial economics perspective with a specific focus on the multi-dimensional (direct, moderated, and threshold) effects. A research framework was suggested synthesizing three econometric models and encompassing three hypotheses. The research model was then empirically tested and validated through quantitative research using China’s provincial panel data from 2004 to 2018. The study’s findings indicate a positive influence/relationship between ICTs and market-oriented reforms in the culture and tourism industries’ convergence. Moreover, a positive labor-convergence relationship was found, while the negative government–convergence relationship was uncovered in control variables. Regarding the moderating effect, the interaction of ICTs and market-oriented reforms is positively correlated with industrial convergence. In addition, there is a single-threshold effect of consumer demand on the ICTs–convergence relationship. This article extends our knowledge in two ways by addressing the knowledge gap regarding the interrelationship between culture and tourism and by providing new insights into the influence of ICTs on this industrial convergence that has theoretical and practical implications.

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Consumer engagement in e-Tourism: Micro-panel data models for the case of Spain

Cited by 11 publications

References 34 publications

Consumer behaviour in e-Tourism: Exploring new applications of machine learning in tourism studies

Consumer behaviour in e-Tourism: Exploring new applications of machine learning in tourism studies

European regional inequalities in citizens’ digital interaction with government

Exploring and Evaluating the Impact of ICTs on Culture and Tourism Industries’ Convergence: Evidence from China

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