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This paper aims to track how ecotourism has been presented in a digital world over time using geotagged photographs and internet search data. Ecotourism photographs and Google Trends search data are used to evaluate tourist perceptions of ecotourism by developing a categorization of essential attributes, examining the relation of ecotourism and sustainable development, and measuring the popularity of the ecotourism sites.

The researchers collected geotagged photographs from Flickr.com and downloaded Google search data from Google Trends. An integrative approach of content, trend and spatial analysis was applied to develop ecotourism categories and investigate tourist perceptions of ecotourism. First, the authors investigate ecotourism geotagged photographs on a social media to comprehend tourist perceptions of ecotourism by developing a categorization of key ecotourism attributes and measuring the popularity of the ecotourism sites. Second, they examined how ecotourism has been related with sustainable development using internet search data and investigate the trends in search data. Third, spatial analysis using GIS maps was used to visualize the spatial-temporal changes of photographs and tourist views throughout the world.

This study identified three primary themes of ecotourism perceptions and 13 categories of ecotourism attributes. Interest over time about ecotourism was mostly presented as its definitions in Google Trends. The result indicates that tracked ecotourism locations and tourist footprints are not congruent with the popular regions of ecotourism Google search.

This research follows the changing trends in ecotourism over a decade using geotagged photographs and internet search data. The evaluation of the global ecotourism trend provides important insights for global sustainable tourism development and actual tourist perception. Analyzing the trend of ecotourism is a strategic approach to assess the achievement of UN sustainable development goals. Factual perspectives and insights into how tourists are likely to seek and perceive natural attractions are valuable for a range of audiences, such as tourism industries and governments.

研究目的本论文旨在探索生态旅游业在电子世界中是如何随着时间而显示出来的，文章样本为带有地理标记的图片和互联网搜索数据。本文使用生态旅游图片和谷歌趋势搜索数据来评估游客对生态旅游的感知，通过对关键要素的分类，审视生态旅游和可持续发展的关系，以及衡量生态旅游基地的受欢迎程度等方法。

本论文作者从Flickr.com上搜集地理标记图片以及从谷歌趋势上下载谷歌搜索数据。样本分析通过内容、趋势、空间上的综合分析，来开发生态旅游类别和游客对生态旅游的感知。首先，我们研究了社交媒体上的生态旅游地理标记图片以理解游客对生态旅游的感知情况，以此搭建了关键生态旅游要素的类别体系，和衡量生态旅游基地的受欢迎程度。第二，我们通过使用互联网搜索数据，检测了生态旅游如何与可持续发展相连接，以及研究了搜索数据中的趋势。第三，我们使用了GIS软件来操作空间分析，对图片的空间-时间改变和游客对世界的观点做了可视化处理。

本论文确立了三项生态旅游感知的基本主题以及13项生态旅游要素类别。生态旅游互联网随着时间演化，根据谷歌趋势上的定义，被大致地展现出来。本论文研究结果表示生态旅游地理位置和游客足迹与生态旅游谷歌搜索的热门区域不全是完全吻合的。

本论文使用地理标记图片和互联网搜索数据将生态旅游发展趋势近十年的变化描画出来。全球生态旅游趋势的评估对全球可持续旅游发展和实际游客感知方面做出重要见解启示。生态旅游趋势的分析作为一种战略方法，对UN可持续发展目标的时间起到评估作用。本论文针对游客的真实感知和意见，游客如何选择和感知自然景观，这对于很多群体，比如旅游行业和政府，都有着重要意义。

The purpose of this paper is to investigate what triggers tourist’s use of geotag as an information sharing tool in social media.

This study divided tourists’ goals into task-involved goals (enjoyment of geotags and altruism) and ego-involved goals (anticipated extrinsic reward and desire for attention), and then examined the influences of these goals on their geotag satisfaction and information-sharing behavior by using PLS-Graph 3.0.

Whereas the anticipated extrinsic rewards, altruism, and enjoyment of geotags were found to influence their geotag satisfaction, desire for attention was not. Enjoyment of geotags was found to be the strongest predictor of tourists’ geotag satisfaction, which in turn affected their information-sharing behaviors. Based on these findings, the authors present theoretical and practical implications with suggestions for future research.

Geotag services are not identical in all social media, so study participants might have perceived the characteristics of geotags differently depending on which social media they use.

The enjoyment of geotags, altruism, and anticipated reward were found to influence geotag satisfaction; however, desire for attention was not. The results imply that enjoyment of geotags and anticipated reward strongly predict geotag satisfaction.

On October 2019, the Rubjerg Knude lighthouse (Denmark) was moved 70 metres from the cliff edge. The Danish Government spent €700,000 on the rescue operation. Using the zonal travel cost method (ZTCM), this paper aims to estimate the recreational value of this (im)movable maritime heritage building, to assess whether it was worthwhile to incur that public expenditure. This valuation is complemented by a digital reputation analysis.

A Flickr application programming interface search method extracted 795 public photos with the “Rubjerg and Knude” tags, taken between 2004 and 2019. The ZTCM analysis included 148 photographers who provided information about their residence location.

Depending on the regression models and assumptions made, the estimated economic value of the lighthouse (measured by the consumer surplus) varies between 5.5m and 133m euros. That means that the operation’s cost is only a small percentage of the expected economic recreational value.

The sample of Flickr photographers is a proxy to estimate the zonal visitation rate for a specific destination. Zonal travel cost calculations are always based on some assumptions defined by researchers.

The paper frames the role of lighthouses as an (im)movable heritage element, which provides several cultural ecosystem services – in particular aesthetic, recreational, cultural/educational, bequest and sense of place values/benefits for tourists and residents.

This study supports the political decision of preserving an identity symbol of a specific place, based solely on its recreational value.

This paper combines a monetary approach (ZTCM) with a digital reputation analysis of this iconic attraction.

Geotechnologies have a long tradition in several areas of society and research. The recent development of the ‘Internet of Everything’ (IoE) and Geographic Information Systems (GIS) technologies opened several doors to the contribution of tourism. Emergent technologies contributions to tourism and planning such as web mapping, augmented reality (AR), crowdsourcing and crowdsensing are relatively recent, and there is a lack of research around their potential for Creative Tourism enhancement. For example, combining web mapping with AR or storytelling can be an excellent contribution to operators, planners and tourists. For research purposes, new opportunities are open, particularly by integrating community-shared data. It is well known for the popularity of social networks, the exponential growth of photo sharing, but few studies have been implemented to understand their contribution to research. This chapter focuses on emerging geotechnologies concerning cultural mapping, Creative Tourism and sustainability. Since it is a new growing niche, more research is needed to develop and understand the potential of new approaches. Besides traditional techniques such as quantitative (e.g. surveys) and qualitative ones (e.g. interviews, focus groups and world café), it revises the role of geotechnologies on Creative Tourism development and growing activities. Results from case studies from Europe are analysed.

The chapter aims to highlight developments in photography over the last two centuries, with an emphasis on the switch from analog to digital, and the emergence of Web 2.0 technologies, online photo management sites, and camera phones.

The chapter is a culmination of some of the key literature and research papers on photography, Web 2.0, Flickr, camera phones, and tagging, and is based on the author’s opinion and interpretation.

The chapter reports on how the switch from analog to digital has changed the methods for capturing, organizing, and sharing photographs. In addition, the emergence of Web 2.0 technologies and camera phones have begun to fundamentally change the way that people think about images and the kinds of things that people take photographs of.

The originality of the chapter lies in its predictions about the future direction of photography. The chapter will be of value to those interested in photography, and also to those responsible for the future development of photographic technology.

The purpose of this study is to analyse the suitability of photo-sharing platforms, such as Flickr, to extract relevant knowledge on tourists’ spatial movement and point of interest (POI) visitation behaviour and compare the most prominent clustering approaches to identify POIs in various application scenarios.

The study, first, extracts photo metadata from Flickr, such as upload time, location and user. Then, photo uploads are assigned to latent POIs by density-based spatial clustering of applications with noise (DBSCAN) and k-means clustering algorithms. Finally, association rule analysis (FP-growth algorithm) and sequential pattern mining (generalised sequential pattern algorithm) are used to identify tourists’ behavioural patterns.

The approach has been demonstrated for the city of Munich, extracting 13,545 photos for the year 2015. POIs, identified by DBSCAN and k-means clustering, could be meaningfully assigned to well-known POIs. By doing so, both techniques show specific advantages for different usage scenarios. Association rule analysis revealed strong rules (support: 1.0-4.6 per cent; lift: 1.4-32.1 per cent), and sequential pattern mining identified relevant frequent visitation sequences (support: 0.6-1.7 per cent).

As a theoretic contribution, this study comparatively analyses the suitability of different clustering techniques to appropriately identify POIs based on photo upload data as an input to association rule analysis and sequential pattern mining as an alternative but also complementary techniques to analyse tourists’ spatial behaviour.

From a practical perspective, the study highlights that big data sources, such as Flickr, show the potential to effectively substitute traditional data sources for analysing tourists’ spatial behaviour and movement patterns within a destination. Especially, the approach offers the advantage of being fully automatic and executable in a real-time environment.

The study presents an approach to identify POIs by clustering photo uploads on social media platforms and to analyse tourists’ spatial behaviour by association rule analysis and sequential pattern mining. The study gains novel insights into the suitability of different clustering techniques to identify POIs in different application scenarios.

本论文旨在分析图片分享平台Flickr对截取游客空间动线信息和景点（POI）游览行为的适用性, 并且对比最知名的几种聚类分析手段, 以确定不同情况下的POI。

本论文首先从Flickr上摘录下图片大数据, 比如上传时间、地点、用户等。其次, 本论文使用DBSCAN和k-means聚类分析参数来将上传图片分配给POI隐性变量。最后, 本论文采用关联规则挖掘分析（FP-growth参数）和序列样式勘探分析（GSP参数）以确认游客行为模式。

本论文以慕尼黑城市为样本, 截取2015年13,545张图片。POIs由DBSCAN和k-means聚类分析将其分配到有名的POIs。由此, 本论文证明了两种技术对不同用法的各自优势。关联规则挖掘分析显示了显著联系（support：1%−4.6%；lift：1.4%−32.1%）, 序列样式勘探分析确立了相关频率游览次序（support：0.6%−1.7%。

本论文的理论贡献在于, 根据图片数据, 通过对比分析不同聚类分析技术对确立POIs, 并且证明关联规则挖掘分析和序列样式勘探分析各有千秋又互相补充的分析技术以确立游客空间行为。

本论文的现实意义在于, 强调了大数据的来源, 比如Flickr,证明了其对于有效代替传统数据的潜力, 以分析在游客在一个旅游目的地的空间行为和动线模式。特别是这种方法实现了实时自动可操作性等优势。

本论文展示了一种方法, 这种方法通过聚类分析社交媒体上的上传图片以确立POIs, 以及通过关联规则挖掘分析和序列样式勘探分析来分析游客空间行为。本论文对于不同聚类分析以确立不同适用情况下的POIs的确立提出了独到见解。

This paper aims to examine the extent to which Business Intelligence and Big Data feature within academic research in hospitality and tourism published until 2016, by identifying research gaps and future developments and designing an agenda for future research.

The study consists of a systematic quantitative literature review of academic articles indexed on the Scopus and Web of Science databases. The articles were reviewed based on the following features: research topic; conceptual and theoretical characterization; sources of data; type of data and size; data collection methods; data analysis techniques; and data reporting and visualization.

Findings indicate an increase in hospitality and tourism management literature applying analytical techniques to large quantities of data. However, this research field is fairly fragmented in scope and limited in methodologies and displays several gaps. A conceptual framework that helps to identify critical business problems and links the domains of business intelligence and big data to tourism and hospitality management and development is missing. Moreover, epistemological dilemmas and consequences for theory development of big data-driven knowledge are still a terra incognita. Last, despite calls for more integration of management and data science, cross-disciplinary collaborations with computer and data scientists are rather episodic and related to specific types of work and research.

This work is based on academic articles published before 2017; hence, scientific outputs published after the moment of writing have not been included. A rich research agenda is designed.

This study contributes to explore in depth and systematically to what extent hospitality and tourism scholars are aware of and working intendedly on business intelligence and big data. To the best of the authors’ knowledge, it is the first systematic literature review within hospitality and tourism research dealing with business intelligence and big data.

This paper aims to introduce the concept of storygiving as a co-creation tool and provides a guideline for its successful use by luxury brand managers.

A study of Tiffany and Co.’s social media-based site and its use of stories as co-created marketing content provides us with managerial strategies applicable to luxury brands in general. The authors emphasize how luxury brands deal with co-created brand images compared to mainstream brands.

Storygiving enables consumers to share their personal experiences through narratives and provides contextualized connections among community members through shared experiences. One successful example of storygiving is Tiffany & Co.’s ‘What Makes Love True’ campaign.

Only one luxury brand was used in this case study of online co-creation and storygiving. Further research, especially comparative case studies, would expand understanding of brand image management in the age of social media and consumer empowerment.

This paper presents a strategic guideline for luxury brand managers highlighting a customer-centric insight into ways luxury brands can develop marketing strategies incorporating co-creation.

To differentiate it from storytelling, the co-creation of brand stories through consumer-generated content is known as storygiving. The use of social media marketing in the process of storygiving is a powerful tool for luxury brands. The changed narrative from the brand’s point of view to that of the brand’s community is a major point made in this research.

The purpose of this study is to investigate the potential for environmental and social impacts from university-level educational travel programs.

This study analyzes the sites visited by 17 education travel programs to the Westfjords (Iceland) from 2014 to 2016. It uses a geographic information system (GIS) project to examine the potential for environmental and social impacts from these programs on local communities and environments. It compares them with similar data on general tourism to the region.

The results reveal that educational travel programs visit sites that are generally in moderately sensitive areas environmentally and socially. They visit different sites from general tourists and sites that are more sensitive environmentally and socially.

The research area was limited to the Westfjords of Iceland, and thus, the results may not apply globally to all educational travel destinations.

These findings suggest that education travel programs carried out by and for universities the potential to have negative effects on the locations they visit. Universities need to design their educational travel programs so as to limit such impacts to host environments and communities and explicitly educate student participants about sustainable travel behaviors.

This is the first study to combine GIS with several environmental and social metrics to assess impacts from educational travel programs. Further, it is the first study to map the frontstage–backstage continuum as a quantitative metric.

Tourism reconfigures the metropolitan dynamics and the patterns of use of the urban systems. The seasonal nature of tourism produces an impact on the urban hierarchies, since it affects the labor, residential, and recreational markets. As a result, people move to and in the destination and it challenges the supply of sustainable modes of transport such as public transport. This research is set within the context of three demanding challenges that tourist destinations need to face-up: to increase environmental sustainability, to enhance destination competitiveness, and finally to assure quality and comfort of public transport services for the local resident population. Camp de Tarragona region, where Costa Daurada (one of the most important Spanish tourist brands) is located, is analyzed to illustrate how different data sources can aid to confront the aforementioned challenges. Given that seasonality is a dynamic phenomenon, suitable data should be flexible in terms of its time framework. To this end data from smart travel cards provided by the consortium that manages the public transport system in the region has been analyzed. Data unveiled the impact of seasonality on the evolution of demand throughout the year, the type of transport tickets used, or changes occurred in the geographical distribution of the mobility Alternative data sources such as surveys and passive mobile positioning data have also been examined, and their pros and cons have been addressed.