Ulrich Gunter
Short Bio
Ulrich Gunter is an Associate Professor (tenured) at the Department of Tourism and Service Management of MODUL University Vienna and Dean of the Graduate Degree Programs, thereby being responsible for the university's MBA and MSc programs. He holds a Diplom "with Honors" (roughly equivalent to MSc) in Economics from the University of Regensburg (2007, study program within the Elite Network of Bavaria; visiting undergraduate student at Santa Clara University in 2006), a PhD in Economics from the University of Vienna (2010, full scholarship from the University of Vienna as "Kollegassistent" for the structured PhD program Issues in the Global Economy: Dynamics, Governance, and Information), as well as an MA in Latin American Studies from the University of Vienna (2015). Following a habilitation process, Ulrich obtained his Venia Docendi (university teaching license) from MODUL University Vienna in 2017.
Ulrich was a visiting researcher at the University of Surrey (November 2013), the University of Sao Paulo (July to September 2014; conclusion of a Brazilian Pós-Doutorado), and the University of Florida (September to October 2017). Besides being one of the two founding co-editors of the MODUL University Working Paper Series, he is a member of the editorial boards of the scholarly journals Annals of Tourism Research Empirical Insights, Forecasting, Journal of Travel Research, Tourism Analysis, and Tourism Economics. Ulrich is Vice Chair of the Tourism and Hospitality Section (THS) of the International Institute of Forecasters (IIF) and a member of the Computational and Financial Econometrics Network (CFE) and the International Association for Tourism Economics (IATE). At MODUL University Vienna, he is a member of the University Senate. In the past, Ulrich also acted as the chair of the university's Merit Scholarship Committee and as the liaison officer for outgoing exchange students to the School of Tourism & Hospitality Management Sant Ignasi, the University of Florida, and the University of Surrey.
Research Interests
Ulrich's research interest is in applied econometrics, with a particular focus on time-series analysis (including forecasting) and panel-data analysis. His current primary fields of thematic interest are the economics of tourism and of sustainability, while his earlier research focused on macroeconomics, monetary policy, and financial stability. Ulrich's research has been published in leading international scholarly journals and has received external funding from various bodies, such as the European Commission, the Hochschuljubiläumsstiftung der Stadt Wien, or the Vienna Economic Chamber.
Awards
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2018 : Commendation for Emerging Scholarship in Tourism 2019 (International Academy for the Study of Tourism)
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2017 : Wirtschaftskammerpreis 2017 (Wirtschaftskammer Wien)
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2014 : Wirtschaftskammerpreis 2014 (Wirtschaftskammer Wien)
Projects
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Schätzung der CO2-Emissionen des europäischen Städtetourismus - Wien im internationalen Vergleich
This project seeks to assess the travel-induced CO2 emissions of Vienna more accurately. In doing so, a novel measure of travel-induced CO2 emissions originating from total tourist arrivals to the city is employed. The novelties of this measure relate to the inclusion of Vienna's source-market-specific characteristics such as travel distance between source market and destination, modal split, and average number of European city destinations visited per trip. This new measure also allows for changes in the city's guest mix structure as well as source-market specific lengths of stay over time. In a second step, the estimated travel-induced CO2 emissions of Vienna are benchmarked against its major European competitors.
Organisations: MODUL University Vienna, Department of Tourism and Service Management
Author: Ulrich Gunter, Karl Wöber
Date: 01.01.2020 - 31.12.2020
Managed By: MODUL University Vienna
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Carrying Capacity Methodology for Tourism
The overall goal of the service contract is to determine the carrying capacity in regions dominated by tourism. This will help local leaders in destinations to analyse and assess the impact of tourism in their regions based on indicators for the economic, social and environmental aspects affected. The focus will lie on big data, new technologies, artificial intelligence and high-performance computing. This needs to be conditioned for European tourist destinations. In the context of this service contract local, national and EU policies will be advised in managing and measuring carrying capacity in tourist destinations.
Organisations: MODUL University Vienna, Department of Sustainability, Governance, and Methods, Department of Public Governance and Sustainable Development, Department of Tourism and Service Management, Department of New Media Technology
Author: Sabine Sedlacek, Christian Weismayer, Bozana Zekan, Ulrich Gunter, Daniel Dan, Lyndon Nixon
Date: 11.11.2019 - 11.11.2020
Managed By: MODUL University Vienna
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Qualifikationsnetzwerk "Smart Data Analytics für die Hotellerie"
The purpose of the qualification network is to teach employees of tourism businesses - especially accommodation providers - the use of data and advanced methods of analysis. Data management and analysis is considered a central element of digitalization in tourism and the added value of an efficient and effective data processing is given in the companies. The aim is to teach the state of research in a way that enables businesses to explore new sources of data and to link these sources to generate better information for decision-making. With this knowledge, businesses should be better able to accompany and to consult the guest during the whole "customer-journey". For this purpose, the scientific partners MODUL University Vienna and Technical University Vienna combine their expertise in the area of data management and tourism.
Organisations: Department of Tourism and Service Management, MODUL University Vienna, Department of New Media Technology
Author: Hannes Antonschmidt, Astrid Dickinger, Ulrich Gunter, Lyndon Nixon, Daniel Dan, Arno Scharl
Date: 01.07.2019 - 31.12.2020
Managed By: Department of Tourism and Service Management
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Well-known public places and 'hidden gems' in Vienna – Estimating and forecasting visitor numbers with geotagged photos
Organisations: MODUL University Vienna, Department of Tourism and Service Management
Author: Ulrich Gunter, Irem Önder
Date: 01.12.2017 - 30.11.2018
Managed By: Department of Tourism and Service Management
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Sharing Economy: The Competitive Standing of Viennese Airbnb Accommodations
Organisations: MODUL University Vienna, Department of Tourism and Service Management
Author: Bozana Zekan, Irem Önder, Ulrich Gunter
Date: 01.10.2017 - 30.09.2018
Managed By: MODUL University Vienna
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Status Quo of Airbnb in Vienna and in its Main Competitors
Organisations: MODUL University Vienna, Department of Tourism and Service Management
Author: Ulrich Gunter, Irem Önder, Bozana Zekan
Date: 01.08.2016 - 31.01.2017
Managed By: MODUL University Vienna
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The Tourism Research, Innovation and Next Generation Learning Experience
The Tourism Research, Innovation And Next Generation Learning Experience (TRIANGLE) Program is creating a Knowledge Alliance of HEIs and businesses across Europe, delivering a common sustainable tourism training system for protected area and green tourism destinations. Within the framework of the EU’s Erasmus Knowledge Alliance program, the European-wide Ecotrans Network for Sustainable Tourism has teamed up with leading universities (Algarve, Eberswalde, Sorbonne, Vienna), and businesses with core ICT and tourism interests (Eau de Web, Forum Anders Reisen) to create a European-wide collaborative online learning system for Higher Education Institutes (HEIs) to offer quality sustainability training and education to tourism destination administrators, SMEs workforce individuals and students linked to tourism activity in Europe’s protected areas and green destinations.
Organisations: MODUL University Vienna, Department of Tourism and Service Management
Author: Ulrich Gunter, Dagmar Lund-Durlacher
Date: 01.11.2016 - 31.10.2019
Managed By: Department of Tourism and Service Management
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Statistical Report on Tourism Accommodation Establishments
Organisations: MODUL University Vienna, Department of Tourism and Service Management
Author: Egon Smeral, Irem Önder, Ulrich Gunter
Date: 01.01.2016 - 31.12.2017
Managed By: MODUL University Vienna
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Forecasting Tourism Demand for Vienna with Google Trends
The purpose of this study is to investigate whether using Google Trends indices for web and image searches 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 evaluated at the total demand and at the source market levels. The effect of the search query language on predictability of arrivals is considered and differences between seasonal and seasonally-adjusted data are investigated. The results confirm that the forecast accuracy is improved when Google Trends data are included across source markets and forecast horizons for seasonal and seasonally-adjusted data, leaning towards native-language searches. This outperformance not only holds relative to purely autoregressive baseline specifications, but also relative to time-series models such as Holt-Winters and naïve benchmarks, where the latter are significantly outperformed on a regular basis.
Organisations: MODUL University Vienna, Department of Tourism and Service Management
Author: Ulrich Gunter, Irem Önder
Date: 01.10.2014 - 30.06.2015
Managed By: MODUL University Vienna
Research Output
- 2021
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"Improving Hotel Room Demand Forecasts for Vienna across Hotel Classes and Forecast Horizons: Single Models and Combination Techniques Based on Encompassing Tests"2021 in: Forecasting. Volume: 3. Issue number: 4 Pages: 884-919
The present study employs daily data made available by the STR SHARE Center covering the period from 1 January 2010 to 31 January 2020 for six Viennese hotel classes and their total. The forecast variable of interest is hotel room demand. As forecast models, (1) Seasonal Naïve, (2) Error Trend Seasonal (ETS), (3) Seasonal Autoregressive Integrated Moving Average (SARIMA), (4) Trigonometric Seasonality, Box–Cox Transformation, ARMA Errors, Trend and Seasonal Components (TBATS), (5) Seasonal Neural Network Autoregression (Seasonal NNAR), and (6) Seasonal NNAR with an external regressor (seasonal naïve forecast of the inflation-adjusted ADR) are employed. Forecast evaluation is carried out for forecast horizons h = 1, 7, 30, and 90 days ahead based on rolling windows. After conducting forecast encompassing tests, (a) mean, (b) median, (c) regression-based weights, (d) Bates–Granger weights, and (e) Bates–Granger ranks are used as forecast combination techniques. In the relative majority of cases (i.e., in 13 of 28), combined forecasts based on Bates–Granger weights and on Bates–Granger ranks provide the highest level of forecast accuracy in terms of typical measures. Finally, the employed methodology represents a fully replicable toolkit for practitioners in terms of both forecast models and forecast combination techniques.
Author(s): Ulrich Gunter
Publication date: 27. 11. 2021
Volume: 3
Issue number: 4
Pages: 884-919
Electronic version(s), related files and links: http://dx.doi.org/doi.org/10.3390/forecast3040054
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"Zooming into Airbnb listings of European cities: Further investigation of the sector’s competitiveness"2021 in: Tourism Economics.
Airbnb has a major role to play in the competitiveness of the overall accommodation sector of individual destinations and it is rather unlikely that this role will diminish in the post-COVID-19 recovery of the tourism industry. Therefore, the present study motivates the Airbnb sector to look back at its past performance for insights that can be used in setting post-pandemic targets. In particular, this research assesses competitiveness of the Airbnb listings of 28 European cities by including hotel-related data as uncontrollable input variables within interactive data envelopment analysis modeling. The contribution lies in joining Airbnb listings and hotels into the benchmarking discussion and efficiency analysis, along with looking beyond the cumulative number of listings by dissecting the overall sector into commercial and private listings—something that has not been attempted as of yet, in spite of the ever-growing body of literature on the sharing economy.
Author(s): Bozana Zekan, Ulrich Gunter
Publication date: 7. 10. 2021
Electronic version(s), related files and links: http://dx.doi.org/https://doi.org/10.1177/13548166211044889
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"Estimating transportation-related CO2 emissions of European city tourism"2021 in: Journal of Sustainable Tourism.
The present study develops a methodology to assess transportation-related CO2 emissions of European city tourism. In doing so, not only is travel distance considered, but also the chosen transportation modes and the particularities of the different cities’ source markets. The major contribution of this study is the implementation of this learning methodology into a decision support system for destination management organizations of cities. Based on a sample from 2018 of 48 European cities with at least 40 source markets, the range of aggregate transportation-related CO2 emissions of European city tourism is estimated. Moreover, a longitudinal analysis of the exemplary city of Vienna covering the period of 1990 to 2018 is carried out. Finally, some policy recommendations of how destination management organizations can contribute to make the estimated transportation-related CO2 emissions even more precise and on how to make European city tourism more environmentally sustainable are drawn.
Author(s): Ulrich Gunter, Karl Wöber
Publication date: 21. 6. 2021
Electronic version(s), related files and links: http://dx.doi.org/10.1080/09669582.2021.1939708
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"Temporal variability of emotions in social media posts"2021 in: Technological Forecasting and Social Change. Volume: 167.
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 into the category of dictionary-based approaches to study emotions contained in written text was developed and applied. Not only are the overall polarity and the single emotions contained in Instagram posts within Vienna investigated, but also the top 54 Viennese Instagram locations. A particular novelty of this study is the measurement of longitudinal developments from emotive text and the fine-grained analysis of single emotions in addition to the overall polarity. One crucial empirical result of the study is that more experience and self-confidence in Instagram posting, as well as increasing expectations, seem to result in becoming a more critical poster over time. Companies interested in the use of influencer marketing to promote their products and services via Instagram should take this finding into consideration in order to be successful.
Author(s): Christian Weismayer, Ulrich Gunter, Irem Önder
Publication date: 20. 2. 2021
Volume: 167
Electronic version(s), related files and links: http://dx.doi.org/10.1016/j.techfore.2021.120699
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"Forecasting air passenger numbers with a GVAR model"2021 in: Annals of Tourism Research. Volume: 89.
This study employs a GVAR model on the passenger numbers of the top 20 busiest airports of the world and the Asia-Pacific and Latin America-Caribbean regions. With air passenger numbers representing a demand measure, country-level proxies for economic drivers are included as domestic and foreign variables. In terms of ex-ante forecast accuracy, the GVAR model performs best for several airports – yet not for the entirety of airports – compared to four benchmarks for horizons one and three quarters ahead. It also achieves several second and third ranks for these and two other horizons and when all horizons are evaluated jointly. Considering the connectivity of airports is worthwhile to achieve accurate and economically interpretable air passenger demand forecasts.
Author(s): Ulrich Gunter, Bozana Zekan
Publication date: 2021
Volume: 89
Electronic version(s), related files and links: http://dx.doi.org/10.1016/j.annals.2021.103252
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