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Article
Publication date: 19 June 2019

Karen L. Xie and Young Jin Lee

When shopping for hotels online, consumers usually follow a sequential process of search, click-through and book. How to maximize consumer conversion on the path to…

Abstract

Purpose

When shopping for hotels online, consumers usually follow a sequential process of search, click-through and book. How to maximize consumer conversion on the path to purchase and prevent potential customers from giving up the online search remains an important topic to hotel marketers and online travel agents (OTAs). The purpose of this study is to understand how informational cues displayed in an online hotel search process, including quality indicators, brand affiliation, incentives (discounted price and promotion) and position in the search results, influence consumer conversion from one stage to another.

Design/methodology/approach

The authors collected clickstream data of hotel search from Expedia. The data include information on individual consumers’ click-through and booking, as well as events leading up to the conversions (or failure to convert) from search, click-through to book. It contains 940,164 hotels searched and displayed in 39,574 online search queries made by users in a regional US market between November 1, 2012 and June 20, 2013. The modeling strategy comprised the Heckman model and random effects model, which integrated sequential consumer behavior in different problem-solving stages while accounting for heterogeneity across different hotels online.

Findings

The authors find that consumers rely on informational cues displayed online to make decisions about hotel booking. Specifically, consumers tend to click through hotels with higher consumer-generated ratings and industry-endorsed ratings. However, they tend to rely on consumer-generated ratings rather than industry-endorsed ratings when committing to a booking. Moreover, consumers are strongly responsive to incentives (discounted price and promotion) when clicking-through and booking a hotel. Finally, the likelihood of consumer conversions from search to click-through and booking is higher for hotels with brand affiliation and higher positions in the search results.

Originality/value

This research provides critical managerial implications of online search for hotel marketers and OTAs. The results inform hotel marketers and OTAs on how consumers respond to informational cues displayed in their search process and how these informational cues influence consumer conversion from one stage to another. The sequential problem-solving process of search, click-through and booking disclosed in this study also helps hotel marketers to identify customer conversion opportunities using effective informational cues.

研究目的

当在线酒店预定时, 消费者往往遵循一系列流程, 搜索, 点击查询, 到最后预定。对于酒店营销商和线上旅游社(OTAs)来说, 如何最大化提高消费转化, 使得消费者不会半途中断, 最后预定酒店, 是一个重要话题。本论文的研究目的就是理解酒店在线搜索过程中, 信息线索如何影响每个阶段的消费转化, 其中涉及的因素有:信息质量、品牌、激励(折扣和促销)、以及搜索结果排名等。

研究设计/方法/途径

研究样本数据采集于Expedia酒店搜索点击流。其中包括个人消费者点击和预定信息、以及由搜索、点击查询到预定过程中的消费转化(或者中途转化失败)的各种事件。样本容量包括940,164家酒店, 其涉及到由美国局部市场消费者在2012年11月1日到2013年6月20日之间做出的39,574条搜索结果。 我们采用Heckman模型和随机效应模型来整合不同线性时间上的消费者行为, 同时考虑不同酒店的多样性。

研究结果

研究发现消费者使用在线信息线索来做酒店预订决策。具体来说, 消费者倾向于对于消费者评价高和行业认证高的酒店进行点击查询。然而, 相比行业认证, 消费者更倾向于借鉴消费者评价, 来做出最后预定决策。此外, 在点击查询和预定时, 消费者对于激励(折扣和促销)反应强烈。最后, 品牌和搜索排名靠前的酒店往往获得从搜索、点击查询到最后预定中更高的消费转化率。

研究原创性/价值

本论文对酒店营销商和OTAs有重要的在线搜索启示。研究结果向酒店营销商和OTAs证明消费者在搜索过程中对信息线索如何反应, 以及这些信息线索如何影响每个阶段之间的消费转化。本论文展示的从搜索、点击查询、到预定的线性决策过程对于酒店营销商们有着重大帮助, 帮助其使用信息线索找出各种消费转化机遇。

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Article
Publication date: 8 May 2017

Juan Liu, Xue Li and Ya Guo

This paper aims to analyze and model consumer behavior on hotel online search interest in the USA.

Abstract

Purpose

This paper aims to analyze and model consumer behavior on hotel online search interest in the USA.

Design/methodology/approach

Discrete Fourier transform was used to analyze the periodicity of hotel search behavior in the USA by using Google Trends data. Based on the obtained frequency components, a model structure was proposed to describe the search interest. A separable nonlinear least squares algorithm was developed to fit the data.

Findings

It was found that the major dynamics of the search interest was composed of nine frequency components. The developed separable nonlinear least squares algorithm significantly reduced the number of model parameters that needed to be estimated. The fitting results indicated that the model structure could fit the data well (average error 0.575 per cent).

Practical implications

Knowledge of consumer behavior on online search is critical to marketing decision because search engine has become an important tool for customers to find hotels. This work is thus very useful to marketing strategy.

Originality/value

This research is the first work on analyzing and modeling consumer behavior on hotel online search interest.

Details

International Journal of Contemporary Hospitality Management, vol. 29 no. 5
Type: Research Article
ISSN: 0959-6119

Keywords

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Article
Publication date: 8 February 2016

Asunur Cezar and Hulisi Ögüt

The aim of this paper is to examine the impact of three main technologies on converting browsers into customers: impact of review rating (location rating and service…

Abstract

Purpose

The aim of this paper is to examine the impact of three main technologies on converting browsers into customers: impact of review rating (location rating and service rating), recommendation and search listings.

Design/methodology/approach

This paper estimates conversion rate model parameters using a quasi-likelihood method with the Bernoulli log-likelihood function and parametric regression model based on the beta distribution.

Findings

The results show that a high rank in search listings, a high number of recommendations and location rating have a significant and positive impact on conversion rates. However, service rating and star rating do not have a significant effect on conversion rate. Furthermore, room price and hotel size are negatively associated with conversion rate. It was also found that a high rank in search listings, a high number of recommendations and location rating increase online hotel bookings. Furthermore, it was found that a high number of recommendations increase the conversion rate of hotels with low ranks.

Practical implications

The findings show that hotels’ location ratings are more important than both star and service ratings for the conversion of visitors into customers. Thus, hotels that are located in convenient locations can charge higher prices. The results may also help entrepreneurs who are planning to open new hotels to forecast the conversion rates and demand for specific locations. It was found that a high number of recommendations help to increase the conversion rate of hotels with low ranks. This result suggests that a high numbers of recommendations mitigate the adverse effect of a low rank in search listings on the conversion rate.

Originality/value

This paper contributes to the understanding of the drivers of conversion rates in online channels for the successful implementation of hotel marketing.

Details

International Journal of Contemporary Hospitality Management, vol. 28 no. 2
Type: Research Article
ISSN: 0959-6119

Keywords

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Article
Publication date: 8 June 2015

HyeRyeon Lee and Shane C. Blum

– The purpose of this paper is to investigate how hotels respond to online reviews on a third-party Web site (such as TripAdvisor) based on the hotel’s star rating.

Abstract

Purpose

The purpose of this paper is to investigate how hotels respond to online reviews on a third-party Web site (such as TripAdvisor) based on the hotel’s star rating.

Design/methodology/approach

Content analysis was used to compare responses to online hotel reviews at five different levels of hotel based on a star-rating system ranging from one star to five stars.

Findings

Most hotel managers’ response rates were low, and they paid the most attention to positive comments. Managers at four- and five-star hotels more often responded to negative online reviews. Guest service manager was the most common job title of managers who responded to guests’ reviews.

Research limitations/implications

This paper is limited to an analysis of ten hotels, two for each of the five-star ratings. More hotel cases with long-term data collection involving the use of the star-rating system may provide more insights on this discussion.

Practical implications

The exploratory study sought to identify strategies for managing online reviews in the lodging industry. Hotel managers should respond to negative online reviews with appreciation, apology and an explanation of what went wrong. Moreover, hotels may need a designated person to observe and respond to guest comments on their Web sites and third-party Web sites. A designated person is also needed to monitor online comments and communicate with guests to better manage the hotel’s online reputation.

Originality/value

As an exploratory research project, this paper expands the understanding of hotel managers’ responses to their guests’ online reviews in an attempt to identify best practices for the industry.

Details

Worldwide Hospitality and Tourism Themes, vol. 7 no. 3
Type: Research Article
ISSN: 1755-4217

Keywords

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Article
Publication date: 26 July 2012

Thomas A. Maier

In the hotel industry today, web site marketing and third party distribution metrics are of critical importance in understanding the effectiveness of hotel revenue…

Abstract

Purpose

In the hotel industry today, web site marketing and third party distribution metrics are of critical importance in understanding the effectiveness of hotel revenue management objectives. The purpose of this paper is to propose a new model which tests hotel web‐effectiveness using the following variables: reach, content, consistency and price parity (RCO2P).

Design/methodology/approach

For the current RCO2P study, the hotel sample was broken down into two segment groupings of five hotels: luxury; and upper‐upscale. The ten full‐service hotels were monitored over a 90‐day period using room rate quotations and ordinal values across 14 dimensions based on three pre‐selected arrival dates.

Findings

Results of the RCO2P study indicated preferential display sequencing emerged as a significant factor in the reach category among all hotel properties reviewed. Only six of ten properties were measured as having achieved optimal web‐effectiveness, while poor price‐parity competency reflected the most situation‐critical performance among sampled hotel properties.

Originality/value

International comparative research methodologies were examined and determined to be effective models of certain hotel web‐effectiveness dimensions; however, a comprehensive hotel web‐effectiveness measurement model is still lacking which can better inform hotel industry executives. Therefore, future research should incorporate a best practice research approach combining the current RCO2P study elements with other web‐effectiveness measurement criteria based on the collective best practices identified among the research studies reviewed.

Details

Journal of Hospitality and Tourism Technology, vol. 3 no. 2
Type: Research Article
ISSN: 1757-9880

Keywords

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Article
Publication date: 10 August 2015

Xinyuan (Roy) Zhao, Liang Wang, Xiao Guo and Rob Law

– This study aims to investigate the impacts of online review and source features upon travelers’ online hotel booking intentions.

Abstract

Purpose

This study aims to investigate the impacts of online review and source features upon travelers’ online hotel booking intentions.

Design/methodology/approach

This study developed a research model and empirically examined the model by collecting data from business travelers in the Mainland China. Factor analysis was adopted to identify features of online reviews content and source attribute. Regression analysis was used to examine impacts of these attributes upon travelers’ online booking intention.

Findings

Six features of online reviews content and one source attribute were identified, namely, usefulness, reviewer expertise, timeliness, volume, valence (negative and positive) and comprehensiveness. Regression analysis results testified positive causal relationships between usefulness, reviewer expertise, timeliness, volume and comprehensiveness and respondents’ online booking intentions. A significantly negative relation between negative online reviews and online booking intentions was identified, whereas impacts from positive online reviews upon booking intentions were not statistically significant.

Research limitations/implications

The major limitation of this study is that interrelationships among features of online reviews, which were discussed in other similar studies, were not considered. Still, this study benefited researchers from scrutinizing features of online reviews, rather than several of them. As such, it offered more comprehensive suggestions for practitioners in how to better utilize online reviews as a marketing tool.

Practical implications

Hospitality practitioners could enhance consumer review management by applying the six underlying factors of online review in the present study to find out the ways of increasing consumers’ booking intentions in the specific hotel contexts.

Originality/value

A major theoretical contribution of this paper is its comprehensiveness in examining features of review content as well as its source simultaneously. This study also offered areas worthy of more research efforts from perspectives of practitioners and researchers.

Details

International Journal of Contemporary Hospitality Management, vol. 27 no. 6
Type: Research Article
ISSN: 0959-6119

Keywords

Content available
Article
Publication date: 24 July 2020

Misuk Lee

Over the past two decades, online booking has become a predominant distribution channel of tourism products. As online sales have become more important, understanding…

Abstract

Purpose

Over the past two decades, online booking has become a predominant distribution channel of tourism products. As online sales have become more important, understanding booking conversion behavior remains a critical topic in the tourism industry. The purpose of this study is to model airline search and booking activities of anonymous visitors.

Design/methodology/approach

This study proposes a stochastic approach to explicitly model dynamics of airline customers’ search, revisit and booking activities. A Markov chain model simultaneously captures transition probabilities and the timing of search, revisit and booking decisions. The suggested model is demonstrated on clickstream data from an airline booking website.

Findings

Empirical results show that low prices (captured as discount rates) lead to not only booking propensities but also overall stickiness to a website, increasing search and revisit probabilities. From the decision timing of search and revisit activities, the author observes customers’ learning effect on browsing time and heterogeneous intentions of website visits.

Originality/value

This study presents both theoretical and managerial implications of online search and booking behavior for airline and tourism marketing. The dynamic Markov chain model provides a systematic framework to predict online search, revisit and booking conversion and the time of the online activities.

Details

Journal of Tourism Analysis: Revista de Análisis Turístico, vol. 27 no. 2
Type: Research Article
ISSN: 2254-0644

Keywords

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Book part
Publication date: 11 July 2018

Catherine Papetti, Sylvie Christofle and Vanessa Guerrier-Buisine

The aim of this chapter is to present in a pedagogical way the main digital tools used by tourism-related businesses, especially by hospitality businesses. The main…

Abstract

Purpose

The aim of this chapter is to present in a pedagogical way the main digital tools used by tourism-related businesses, especially by hospitality businesses. The main purpose of this chapter is to illustrate our discussion with concrete examples and to give a set of advices for efficient use of those tools.

Methodology/approach

Literature review was conducted on conceptual issues, as well as managerial and marketing aspects of digital tools, their value and use in the hospitality industry.

Findings

This chapter highlights the fact that needs in terms of digitalisation depend on the size of the hotel. The main differences can be explained by differences in terms of hotel capacity, and digital technologies should be customised to different types of structures.

Research limitations/implications

This chapter is exploratory in nature, based on a literature review.

Practical implications

It provides clear and practical guidance about the way independent hospitality businesses could use digital tools for marketing purposes. It also suggests the most efficient digital technologies to improve their performance in the field of marketing and customer relationship management.

Originality/value

The chapter demonstrates the huge gap between best practices in the hospitality industry and the way independent enterprises really use, in practice, the digital tools for marketing purposes. It shows how digital technologies could be used in a more efficient way, to take advantage of their full potential.

Details

The Emerald Handbook of Entrepreneurship in Tourism, Travel and Hospitality
Type: Book
ISBN: 978-1-78743-529-2

Keywords

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Article
Publication date: 11 May 2015

Ajay Aluri, Lisa Slevitch and Robert Larzelere

The main purpose of this study was to examine the effectiveness of embedded social media channels and determine whether the embedded social media channels enhance the…

Abstract

Purpose

The main purpose of this study was to examine the effectiveness of embedded social media channels and determine whether the embedded social media channels enhance the overall experience of travelers using the hotel Web sites.

Design/methodology/approach

A true-experimental, between-group and post-test-only design was used to address the primary research questions. Two privately accessible complete versions of the Web site (one with embedded social media channels and one without them) were designed for the experiment. The uses and gratifications approach was used to test the proposed hypotheses. Data were analyzed using ANOVA.

Findings

The results of this study revealed that embedded social media channels on the hotel Web site enhanced travelers’ social gratifications of perceived social interaction. Apart from these benefits for travelers seeking social gratifications, embedded social media channels did not enhance the overall experience (content and process gratifications) of travelers using the Web site.

Practical implications

In the case of embedded social media on hotel Web sites, this study suggests that hotel managers measure return on engagement to examine the effectiveness of embedded social media, instead of return on investment.

Social implications

The study revealed that the emergence of embedded social media channels and their integration on hotel Web sites will have significant influence on travelers who seek social gratifications.

Originality/value

The findings of this study offer new empirical evidence that embedded social media channels enhance only travelers’ perceived social interaction during their first visit to the hotel Web site.

Details

International Journal of Contemporary Hospitality Management, vol. 27 no. 4
Type: Research Article
ISSN: 0959-6119

Keywords

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Article
Publication date: 28 August 2019

Gorete Dinis, Zélia Breda, Carlos Costa and Osvaldo Pacheco

This paper aims to conduct a review of the literature published, between 2006 and 2018, that used search engine data on tourism and hospitality research, namely, Google…

Abstract

Purpose

This paper aims to conduct a review of the literature published, between 2006 and 2018, that used search engine data on tourism and hospitality research, namely, Google Insights for Search and Google Trends. More specifically, it intends to identify the purpose and context of the data use, ascertaining the main findings and reviewing the methodological approaches.

Design/methodology/approach

A systematic literature review of Scopus indexed research has been carried out. Given the novelty of search engine data use in tourism and hospitality research and the relatively low number of search results in Scopus, other databases were used to broaden the scope of analysis, namely, EBSCO and Google Scholar. The papers selected were subjected to content and statistical analyses.

Findings

Google Trends data use in tourism and hospitality research has increased significantly from 2012 to 2017, mainly for tourism forecasting/nowcasting; knowing the interest of users’ searches for tourist attractions or destinations; showing the relationship between the official tourism statistics and the search volume index of Google Trends; and estimating the effect of one event on tourism demand. The categories and search terms used vary with the purpose of the study; however, they mostly focus on the travel category and use the country as the search term.

Originality/value

Google Trends has been increasingly used in research publications in tourism and hospitality, but the range of its applications and methods used has not yet been reviewed. Therefore, a systematic review of the existing literature increases awareness of its potential uses in tourism and hospitality research and facilitates a better understanding of its strengths and weaknesses as a research tool.

研究目的

本文回顾2006年至2018年发表文献使用酒店旅游相关的搜索引擎数据, 即Google Insights for Search 以及Google Trends。确切地说, 本文旨在研究数据使用目的和背景, 归纳主要研究成果和研究方法。

研究设计/方法/途径

本文采用Scopus索引, 由于旅游酒店领域使用搜索引擎数据的文献较少, Scopus搜索结果样本量较低, 本文扩展到其他数据库, 即EBSCO以及Google Scholar。选定的样本文献采用文本分析和统计分析法。

研究结果

旅游酒店领域中对Google Trends数据使用的增加主要集中在2012年到2017年, 主要研究领域有(1)旅游预测/即时预报;(2)了解用户搜索旅游景点或目的地的需求;(3)官方旅游数据和Google Trends搜索量索引之间的关系;以及(4)评估大事件对旅游需求的影响。文献归类和搜索名词根据研究目的而不同。然而, 大多数文章使用‘旅游’归类以及使用国家作为搜索关键词。

研究原创性/价值

Google Trends在酒店旅游领域研究中的使用逐渐增加, 但是据作者所知, 其应用的范畴和方法仍处在起步阶段。因此, 对现有文献的系统回顾可以提高对其在旅游酒店领域中应用的认知, 并且本文结果使其作为研究工具的优劣分析更深理解。

关键词

Google Trends, Google insights for search, 搜索引擎数据, 旅游酒店研究, 系统文献回顾

Details

Journal of Hospitality and Tourism Technology, vol. 10 no. 4
Type: Research Article
ISSN: 1757-9880

Keywords

1 – 10 of over 6000