Irem Onder

• Phd Tourism Management
• Professor (Associate) at University of Massachusetts Amherst

The purpose of this study is to critically review the effect of generative artificial intelligence (GAI) tools on higher education and research in the tourism and hospitality (TH) field. This manuscript identifies capabilities and implications of these GAI applications through a theoretical lens. GAI adoption in TH education can facilitate personal...

Information and Communications Technologies (ICTs) are bringing about drastic changes in people’s daily life. At the same time, the smart economy is growing to allocate resources for better efficacy. However, the effects of ICT and smart economy may vary at the regional level. This chapter aims to discover how the development of ICT and smart econo...

Generative artificial intelligence (GAI) offers important opportunities for the hospitality and tourism (HT) industry in the context of operations, design, marketing, destination management, human resources, revenue management, accounting and finance, strategic management, and beyond. However, the implementation of GAI in HT contexts comes with eth...

Purpose This study aims to use mixed methods to create a new conceptual framework to understand the unique characteristics of virtual tourism experiences (VTE), which has not been systemically examined. Design/methodology/approach Study 1 uses topic modeling with Latent Dirichlet Allocation to analyze 91,609 online reviews from the Airbnb Experien...

Overall, tourism demand forecasting is difficult due to the characteristics of the tourism industry and the unpredictability of human behavior. At the same time, it is essential for the industry for planning and scheduling as well as for the proper allocation of resources. Time series analysis is a common approach for predicting tourism demand. It...

This study explores consumers’ travel-related concerns about the COVID-19 pandemic via YouTube comments. Drawing on the risk perception theory and adopting a Markov Chain approach, this study demonstrates the topics that consumers discussed and empirically illustrates perceived risk in the tourism and hospitality industry via sentiment analysis acr...

Purpose The purpose of this study is to understand the status quo of the use of Web analytics tools by European destination management organizations (DMOs) and to provide guidelines in using these metrics for business intelligence and tourism design. In addition, the goal is to improve destination management at the city level using Web analytics da...

Employing the metadata from 627,632 Instagram posts for the Austrian capital city of Vienna over the period of October 30th, 2011 to February 7th, 2018, the present study extracts sentiment, as well as single basic emotions according to Plutchik's Wheel of Emotions, from the photo captions including hashtag terms. In doing so, an algorithm falling...

This study examines the impact of Covid-19 related information and announcements on hotel revenues on selected destinations in the USA. Daily hotel performance data from Smith Travel Research (STR) and from Google Trends for the January 2019 - September 2020 period are analyzed along with Covid-19 related announcements (CDC, national, and state). T...

This paper examines how a serious game approach could support a participatory planning process by bringing stakeholders together to discuss interventions that assist the development of sustainable urban tourism. A serious policy game was designed and played in six European cities by a total of 73 participants, reflecting a diverse array of tourism...

This study uses geotagged photos from Instagram to identify differences between the popular places in Vienna for residents and visitors. Moreover, we explore whether geotagged data can be useful in determining tourism demand in Vienna. The spatial analysis of 627,632 geotagged photos reveals the top-50 locations in Vienna for all-, local-, and visi...

Recently, blockchain and cryptocurrencies have become topics of discussion in both research and industry. Iansiti and Lakhani perceive blockchain as a foundational technology rather than a disruptive one, since potentially new economic and social systems can be based on blockchain. Therefore, understanding blockchain and contemplating its impact on...

This study, which was contracted by the European Commission and is geared towards easy replicability by practitioners, compares the accuracy of individual and combined approaches to forecasting tourism demand for the total European Union. The evaluation of the forecasting accuracies was performed recursively (i.e., based on expanding estimation win...

Using spatial panel data comprising a cross section of 1,461 continuously active Airbnb listings obtained from AirDNA, as well as time series data from NYC and Company and the OECD covering the time period September 2014 to June 2016, the present study quantifies own price, cross price, and income elasticities of Airbnb demand to New York City with...

Due to the ever-increasing importance of social media, destination management organizations (DMOs) are faced with the need to increase their presence on various digital platforms, which will ideally generate more interest in their destinations. Facebook is one such platform that is used by many DMOs nowadays, but clearly not with equal rates of suc...

Online news media coverage regarding a destination, a form of big data, can affect destination image and influence the number of tourist arrivals. Sentiment analysis extracts the valence of an author's perception about a topic by rating a segment of text as either positive or negative. The sentiment of online news media can be viewed as a leading i...

The objective of this paper was to evaluate the scientific value of econometric tourism demand studies. Based on a questionnaire answered by ourselves we analyzed articles published in Annals of Tourism Research, Journal of Travel Research, Tourism Management, and Tourism Economics during the period 2007 to 2017. The evaluation showed that current...

Facebook is a popular social media platform used by both the demand and the supply sides of the tourism industry. Since there is a huge amount of information on the Internet, which can lead to information overload, individuals tend to apply the principle of least effort in attempting to obtain useful information as quickly and easily as possible. O...

To date, there exists a dearth of scholarly literature in tourism-related journals exploring the phenomenon in great detail and helping to lay the theoretical foundation for future studies in this area. In this paper we will help to close this gap. We argue that through systematic research academia can help the industry to better understand how to...

Airbnb is arguably the world’s most popular accommodation sharing platform. Its impact on demand and supply within the tourism and hospitality industry is nowadays unquestionable. The present study delves into inspecting the efficiency of Airbnb listings of European cities, as, in spite of the success of Airbnb as a whole, it cannot be presupposed...

This article illustrates how drawing has been employed as a stand-alone method to research destination image. Despite arguments for unstructured approaches to learn about how people conceive places, few tourism researchers have explored the potential of the drawing technique. We sought to address this methodological gap by collecting visual data th...

The emergence of peer-to-peer (P2P) accommodation (e.g. Airbnb) has steadily increased the pressure on the traditional accommodation sector. Although Airbnb listings are perceived as being more affordable than hotels, this has not yet been conclusively demonstrated. Therefore, the aim of this study is to investigate whether significant price depend...

Using data for the period 2010M06-2017M02, this study investigates the possibility of predicting total tourist arrivals to four Austrian cities (Graz, Innsbruck, Salzburg, and Vienna) from LIKES of posts on the Facebook pages of the destination management organizations of these cities. Google Trends data are also incorporated in investigating wheth...

In this paper, we speculate that new advances in technologies will reshape tourism planning and residents engagement in many ways which subsequently will help cities to work towards sustainable urban planning practices. The paper addresses the question how should destinations prepare themselves for being ‘smart’ and responsive to co-participative t...

This study identifies key determinants of Airbnb demand and quantifies their marginal contributions in terms of demand elasticities. A comprehensive cross-sectional data set of all Viennese Airbnb listings active between July 2015 and June 2016 is examined. Estimation results, which are obtained by cluster-robust OLS, show that Airbnb demand in Vie...

In this research note we present three high-level propositions which are intended to be further refined and elaborated by the tourism research community. These propositions are closely interwoven, with the first two focusing more on the consumer perspective and the latter investigating market implications.

Previously, Google Trends indices have been found to be useful in improving the tourism demand forecast accuracy relative to a purely autoregressive baseline model. The purpose of this study is to extend previous research in terms of comparing the forecasting accuracy of cities and countries using Google Trends Web and image indices. The study comp...

The development of indicators and metrics systems has been identified as being of paramount importance by many tourism boards and international tourism organizations. This article discusses the bottom-up, micro-level approach of TourMIS, which is a platform for exchanging tourism statistics among tourism organizations, for collecting measures of su...

Destination image is one of the main decision factors for tourists' destination choice. The aim of this study is to compare the perception of consumers' destination image and the actual projected image of DMOs. Two studies are conducted to reach this aim. The first study was an online survey regarding the destination image of selected US cities fro...

Multi-destination trips are interesting for research in order to see which destinations are combined into one leisure trip. The aim of this study is to classify multi-destination trips in Austria based on geotagged photos on Flickr. The study sample includes tourists in Austria who visited at least two different cities based on the geolocations of...

The ability of 10 Google Analytics website traffic indicators from the Viennese DMO website to predict actual tourist arrivals to Vienna is investigated within the VAR model class. To prevent overparameterization, big data shrinkage methods are applied: Bayesian estimation of the VAR, reduction to a factor-augmented VAR, and application of Bayesian...

Understanding dynamic changes in tourist perceptions and analyzing user-generated content to assess the impact of campaigns and promotional activities are among the key questions facing many destination management organizations. Web intelligence platforms help to answer these questions, particularly when they are scalable enough to analyze and visu...

The complexity of the social, political and economical settings in which tourism enterprises operate, increasingly require them to perform data analytics tasks that rely on data from various domains (e.g., economy, environmental sustainability). A survey of tourism practitioners performed in this study showed that although such cross-domain analyti...

In today’s global economy, tourism managers need to consider a range of factors when making important decisions. Besides traditional tourism indicators (such as arrivals or bednights) they also need to take into account indicators from other domains, for example, economy and sustainability. From a technology perspective, building decision support s...

In today’s global economy, tourism managers need to consider a range of factors when making important decisions. Besides traditional tourism indicators (such as arrivals or bednights) they also need to take into account indicators from other domains, for example, economy and sustainability. From a technology perspective, building decision support s...

The majority of the studies on destination image have so far mainly focused on the cognitive and affective components, and there is still a lack of research on the conative component of destination image (i.e., the declaration of a behavioral intention). Moreover, less research has been done on verbally reported self-perception on the baseline imag...

The purpose of this study is to compare the predictive accuracy of various uni- and multivariate models in forecasting international city tourism demand for Paris from its five most important foreign source markets (Germany, Italy, Japan, UK and US). In order to achieve this, seven different forecast models are applied: EC-ADLM, classical and Bayes...

The purpose of this study is to investigate whether using Google Trends indices for web and image search improves tourism demand forecast accuracy relative to a purely autoregressive baseline model. To this end, Vienna, one of the top-10 European city destinations, is chosen as a case example, for which the predictive power of Google Trends is eval...

The complexity of the socio-, political- and economical settings in which tourism enterprises operate, increasingly require them to make decisions that take into account data from various domains (e.g., economy, environmental sustainability). Based on a practitioners' survey that we performed, we conclude that although such cross-domain decisions a...

Traditional tourism data collection includes surveys, interviews and focus groups. However, these methods are both expensive and time consuming. Moreover, there is a lag between the time of data collection and the receipt of that data for analysis. Today, almost all individuals leave digital footprints on the Internet, which can also be used for to...

Benchmarking tourism destinations is essential to improve and also observe what others are doing right. This process has different steps and choosing the right partners is a crucial one. Although there are many studies about how to benchmark destinations, there are no clear steps that explain how to choose destination partners. Tourists who visit t...

The TourMISLOD dataset exposes as linked data a significant portion of the content of TourMIS, a key source of Eu-ropean tourism statistics data. TourMISLOD contains information about the Arrivals, Bednights and Capacity tourism indicators, recorded from 1985 onwards, about over 150 European cities and in connection to 19 major markets. Due to lice...

European Marketing Academy 42nd Annual conference

Tourism data are important for destinations, especially for planning, forecasting tourism demand, marketing, measuring economic impacts and benchmarking. There are different ways to collect tourism data. Traditional methods include guest surveys and data from accommodation providers, which are time consuming and expensive. Today, everyone leaves di...

Decision makers in the tourism domain routinely need to combine and compare statistical indicators about tourism and other related areas (e.g., economic). While many organizations offer relevant data sets, their automatic access and reuse is hampered (i) by them being offered as data dumps in non-semantic encodings; (ii) by them assuming some impli...

Prior research regarding residents and tourists has focused on their commonalities and interactions occurring on-site. What is missing from the literature is an examination of residents as information sources to potential tourists. Online travel communities offer such a viable venue. This study has two main purposes. The first is to examine the inf...

This chapter continues the focus on city tourism, by assessing the significance of city tourism in Europe compared to European tourism overall. In doing so, the focus is not only on the current situation but also on possible future developments, thus the chapter follows two distinct objectives. Firstly, to provide a comprehensive analysis of the ro...

The purpose of this research was to investigate member reputation in an online travel community and its influence on different types of travel decisions. The research design employed a case study approach. In order to examine the influence of member reputation on travel decisions in this community, the members were divided into three groups accordi...

Influence of online community member’s postings on travel decisions were analyzed using thematic networks. Tremapper was used to discover which country postings to be analyzed and resulted in analysis of 8 countries. This study identified 8 organizing themes from an analysis of 81 communication threads that consisted of 713 members and 1691 posting...