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Article
Publication date: 14 June 2018

Maria Madalena Paulo, Paulo Rita, Tiago Oliveira and Sérgio Moro

The purpose of this paper is to further our knowledge of what influences users to adopt mobile augmented reality in tourism (MART). A conceptual model is proposed, combining the…

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Abstract

Purpose

The purpose of this paper is to further our knowledge of what influences users to adopt mobile augmented reality in tourism (MART). A conceptual model is proposed, combining the extension of Unified Theory of Acceptance and Usage of Technology (UTAUT2) with task technology fit (TTF), to explain behavioural intention and user behaviour of MART adopters.

Design/methodology/approach

A questionnaire was completed by a sample of 335 respondents in Portugal. Both UTAUT2 and TTF were combined into a new model from which several hypotheses were drawn based upon the literature.

Findings

The results have shown that the model explains 72 per cent of the variance in behaviour intention to use MART and 45 per cent of the variance in user behaviour.

Originality/value

MART is becoming increasingly known to travellers as it provides the user diverse and useful information with a real relationship with the world. By studying behaviour and what influences consumers to use MART, this study aims to advance the research into new technologies in tourism.

研究目的

本论文旨在扩展对于消费者在旅游行业中使用移动增强现实科技(MART)的知识。本论文结合科技接受和使用全模型(UTAUT2)和任务科技配置度模型(TTF), 提出一个新型的理论模型, 用于更深度理解MART使用者的使用意图和行为。

研究设计/方法/途径

本论文采用问卷采样形式, 采样地点在葡萄牙, 一共采集335份样本数据。由UTAUT2和TTF模型整合的新模型得到了理论认证。

研究结果

本论文新模型解释了72%的MART消费者行为意图和45%消费者使用行为。

研究原创性/价值

MART如今越来越受到游客的认识, 其科技通过一种与现实更贴近的手段, 向游客提供多样且实用的信息。本论文通过研究消费者使用MART的行为, 对旅游产业新科技的应用有着很深的理论贡献。

Details

Journal of Hospitality and Tourism Technology, vol. 9 no. 2
Type: Research Article
ISSN: 1757-9880

Keywords

Article
Publication date: 5 March 2018

Paulo Rita, Tiago Oliveira, António Estorninho and Sérgio Moro

This study aims to present a model drawn on both the extension of the unified theory of acceptance and use of technology (UTAUT2) and the perceived value for explaining consumer…

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Abstract

Purpose

This study aims to present a model drawn on both the extension of the unified theory of acceptance and use of technology (UTAUT2) and the perceived value for explaining consumer behavior toward mobile hospitality services (MHS) from two perspectives: intention to use and recommendation.

Design/methodology/approach

The partial least square (PLS) was applied to data gathered from 348 validated responses to a survey to test a number of research hypotheses.

Findings

Results found that the proposed conceptual model explains 62 per cent of the intention to use of MHS and 51 per cent of the variation in the recommendation. Perceived value plays a role in explaining both the intention to use and recommend MHS, with both constructs also helping in explaining behavior intention, to which effort expectancy, facilitating conditions and performance expectancy also contribute.

Originality/value

This research goes beyond perceived value by combining it with a cornerstone model, UTAUT2, used in technology adoption studies. The paper addresses updated MHS that include but are not limited to mobile hotel reservations.

Details

International Journal of Culture, Tourism and Hospitality Research, vol. 12 no. 1
Type: Research Article
ISSN: 1750-6182

Keywords

Article
Publication date: 17 October 2018

Sérgio Moro, Paulo Rita, Cristina Oliveira, Fernando Batista and Ricardo Ribeiro

This study aims to propose a data-driven approach, based on open-source tools, that makes it possible to understand customer satisfaction of the accommodation offer of a whole…

Abstract

Purpose

This study aims to propose a data-driven approach, based on open-source tools, that makes it possible to understand customer satisfaction of the accommodation offer of a whole country.

Design/methodology/approach

The method starts by extracting information from all hotels of Portugal available at TripAdvisor through Web scraping. Then, a support vector machine is adopted for modeling the TripAdvisor score, which is considered a proxy of customer satisfaction. Finally, knowledge extraction from the model is achieved using sensitivity analysis to unveil the influence of features on the score.

Findings

The model of the TripAdvisor score achieved a mean absolute percentage error of around 5 per cent, proving the value of modeling the extracted data. The number of rooms of the unit and the minimum price are the two most relevant features, showing that customers appreciate smaller and more expensive units, whereas the location of the hotel does not hold significant relevance.

Originality/value

National tourist offices can use the proposed approach to understand what drives tourists’ satisfaction, helping to shape a country’s strategy. For example, licensing new hotels may take into account the unit size and other characteristics that make it more attractive to tourists. Furthermore, the procedure can be replicated at any time and in any country, making it a valuable tool for data-driven decision support on a national scale.

Details

International Journal of Culture, Tourism and Hospitality Research, vol. 12 no. 4
Type: Research Article
ISSN: 1750-6182

Keywords

Article
Publication date: 5 December 2016

Sérgio Moro and Paulo Rita

This study aims to present a very recent literature review on tourism demand forecasting based on 50 relevant articles published between 2013 and June 2016.

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Abstract

Purpose

This study aims to present a very recent literature review on tourism demand forecasting based on 50 relevant articles published between 2013 and June 2016.

Design/methodology/approach

For searching the literature, the 50 most relevant articles according to Google Scholar ranking were selected and collected. Then, each of the articles were scrutinized according to three main dimensions: the method or technique used for analyzing data; the location of the study; and the covered timeframe.

Findings

The most widely used modeling technique continues to be time series, confirming a trend identified prior to 2011. Nevertheless, artificial intelligence techniques, and most notably neural networks, are clearly becoming more used in recent years for tourism forecasting. This is a relevant subject for journals related to other social sciences, such as Economics, and also tourism data constitute an excellent source for developing novel modeling techniques.

Originality/value

The present literature review offers recent insights on tourism forecasting scientific literature, providing evidences on current trends and revealing interesting research gaps.

Details

Worldwide Hospitality and Tourism Themes, vol. 8 no. 6
Type: Research Article
ISSN: 1755-4217

Keywords

Article
Publication date: 2 May 2019

Sérgio Moro and Paulo Rita

National tourism offices worldwide implement marketing strategies to influence tourists’ choices. However, there is more than meets the eye when it comes to choosing a city as a…

Abstract

Purpose

National tourism offices worldwide implement marketing strategies to influence tourists’ choices. However, there is more than meets the eye when it comes to choosing a city as a tourism destination. The purpose of this paper is to answer which are the characteristics that play a key role in room occupancy.

Design/methodology/approach

Diverse characteristics such as the city offer, demographics, natural amenities (e.g. number of beaches) and also politics (e.g. type of government) are combined into a decision tree model to unveil the relevance of each in determining room occupancy. The empirical experiments used data known in 2015 from 43 cities from Europe and the rest of the World to model room occupancy rate in 2016.

Findings

While the seasonality effect plays the most significant role, other less studied features such as the type of political party prior to current government were found to have an impact in room occupancy.

Originality/value

This study unveiled that center–right and right governments are generally more sensitive to promote its city as a tourism destination.

Details

International Journal of Tourism Cities, vol. 5 no. 3
Type: Research Article
ISSN: 2056-5607

Keywords

Open Access

Abstract

Details

European Journal of Management and Business Economics, vol. 27 no. 1
Type: Research Article
ISSN: 2444-8451

Article
Publication date: 3 December 2018

Paulo Rita, Nicole Rita and Cristina Oliveira

This paper aims to embrace the challenge of performing a state-of-the-art scientific literature analysis in data science for hospitality and tourism. This is important because…

Abstract

Purpose

This paper aims to embrace the challenge of performing a state-of-the-art scientific literature analysis in data science for hospitality and tourism. This is important because relatively little contemporary analysis has been published.

Design/methodology/approach

Data on over 800 publications were collected from the Scopus database and analyzed by the differing types of publications, evolution of publications across time, top publishers and outlets, publications per area and per topic, top keywords used, most cited papers and most productive authors.

Findings

Conclusions are drawn and some suggestions are offered regarding topics that are likely to provide opportunities for future research.

Originality/value

This paper identifies the need for analysis on state-of-the-art academic research published to-date on the application of methods and techniques relating to data science in hospitality and tourism.

Details

Worldwide Hospitality and Tourism Themes, vol. 10 no. 6
Type: Research Article
ISSN: 1755-4217

Keywords

Article
Publication date: 8 January 2018

Sérgio Moro and Paulo Rita

This paper aims to present an automated literature analysis to unveil the drivers for incorporating social media in tourism and hospitality brand strategies.

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Abstract

Purpose

This paper aims to present an automated literature analysis to unveil the drivers for incorporating social media in tourism and hospitality brand strategies.

Design/methodology/approach

To gather relevant literature, Google Scholar was queried with “brand”/“branding” and “social media” for articles in ten top-ranked tourism and hospitality journals, resulting in a total of 479 collected articles. The methodology adopted for the analysis is based on text mining and topic modeling procedures. The topics discovered are characterized by terms belonging to a dictionary previously compiled and provide a segmentation of the articles in coherent sets of the literature.

Findings

Most of the 213 articles that encompass a strong relation between social media and branding are mentioning mainly brand building stages. A large research gap was found in hospitality and tourism considering that, besides advertising, no topic was discovered related to known brand strategies such as co-branding or franchising.

Practical implications

The present analysis concludes that specialized tourism and hospitality literature needs to keep pace with research that is being conducted on a wide range of industries to assess the influence of social media.

Originality/value

The automated analysis approach used has no precedent in tourism and hospitality research. By including an innovative topical concept map, it led to identifying and summarizing the topics, providing a clear picture on the findings. This study calls for research by specialized tourism and hospitality publications, eventually leading to special issues on this vibrant subject.

Details

International Journal of Contemporary Hospitality Management, vol. 30 no. 1
Type: Research Article
ISSN: 0959-6119

Keywords

Article
Publication date: 26 September 2019

Sérgio Moro, Paulo Rita, Joaquim Esmerado and Cristina Oliveira

Airbnb Experiences is a new type of service launched by Airbnb in November 2016, where users can offer travellers a wide range of activities. This study devotes attention to…

Abstract

Purpose

Airbnb Experiences is a new type of service launched by Airbnb in November 2016, where users can offer travellers a wide range of activities. This study devotes attention to analysing customer feedback expressed in online reviews published in Airbnb to evaluate those experiences.

Design/methodology/approach

A total of 1,110 reviews were collected from 12 categories, including 111 experiences, resulting in 10 reviews per experience. First, the sentiment score was computed based on the text of the reviews. Second, 17 quantitative features encompassing user, Airbnb experience and review information were used to model the score through a support vector machine. Third, a sensitivity analysis was performed to extract knowledge on the most relevant features influencing the sentiment score.

Findings

Tourists writing online reviews are not only influenced by their tourist experience but also by their own online experience with the booking and online review platform. The number of reviews made by the user accounted for more than 20 per cent of relevance, while users with more reviews tended to grant more positive reviews.

Originality/value

Current literature is enhanced with a conceptual model grounded on existing studies that assess tourist satisfaction with tour services. Both services online visibility and user characteristics have shown significant importance to tourist satisfaction, adding to the existing body of knowledge.

Details

International Journal of Culture, Tourism and Hospitality Research, vol. 13 no. 4
Type: Research Article
ISSN: 1750-6182

Keywords

Article
Publication date: 9 April 2018

Carolina Leana Santos, Paulo Rita and João Guerreiro

The increasing competition among higher education institutions (HEI) has led students to conduct a more in-depth analysis to choose where to study abroad. Since students are…

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Abstract

Purpose

The increasing competition among higher education institutions (HEI) has led students to conduct a more in-depth analysis to choose where to study abroad. Since students are usually unable to visit each HEIs before making their decision, they are strongly influenced by what is written by former international students (IS) on the internet. HEIs also benefit from such information online. The purpose of this paper is to provide an understanding of the drivers of HEIs success online.

Design/methodology/approach

Due to the increasing amount of information published online, HEIs have to use automatic techniques to search for patterns instead of analysing such information manually. The present paper uses text mining (TM) and sentiment analysis (SA) to study online reviews of IS about their HEIs. The paper studied 1938 reviews from 65 different business schools with Association to Advance Collegiate Schools of Business accreditation.

Findings

Results show that HEIs may become more attractive online if they financially support students cost of living, provide courses in English, and promote an international environment.

Research limitations/implications

Despite the use of a major platform with a broad number of reviews from students around the world, other sources focussed on other types of HEIs may have been used to reinforce the findings in the current paper.

Originality/value

The study pioneers the use of TM and SA to highlight topics and sentiments mentioned in online reviews by students attending HEIs, clarifying how such opinions are correlated with satisfaction. Using such information, HEIs’ managers may focus their efforts on promoting international attractiveness of their institutions.

Details

International Journal of Educational Management, vol. 32 no. 3
Type: Research Article
ISSN: 0951-354X

Keywords

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