User
Short Bio
Ulrich Gunter is an Associate Professor (with tenure) at the Department of Tourism and Service Management of MODUL University Vienna. 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 Tourism Analysis and Tourism Economics. At MODUL University Vienna, he acts as the chair of the Merit Scholarship Committee and as the liaison officer for outgoing exchange students to the University of Florida and the University of Surrey. Ulrich is a member of the International Association for Tourism Economics (IATE) and the International Institute of Forecasters (IIF).
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 Chamber of Commerce and Industry.
Awards
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2017 : Wirtschaftskammerpreis 2017 (Wirtschaftskammer Wien)
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2014 : Wirtschaftskammerpreis 2014 (Wirtschaftskammer Wien)
Projects
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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
- 2018
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"Benchmarking of Airbnb listings: How competitive is the sharing economy sector of European cities?"2018 in: Tourism Economics.
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 that all listings are equally successful. More specifically, data envelopment analysis (DEA) is employed in this first comprehensive benchmarking attempt within the domain of the sharing economy to date. This article also makes a contribution to robustness by introducing an interactivity note to the base model, thus, inspecting the results for corroboration/discrepancies and going beyond the static analyses that are common in DEA modeling. Ultimately, this is done with the goal of highlighting opportunities for inefficient Airbnb listings to properly utilize their inputs and therefore become more competitive.
Author(s): Bozana Zekan, Irem Önder, Ulrich Gunter
Publication date: 11. 12. 2018
Electronic version(s), related files and links: http://dx.doi.org/10.1177/1354816618814349
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"Exploring the predictive ability of LIKES of posts on the Facebook pages of four major city DMOs in Austria"2018 in: Tourism Economics.
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 whether forecast models with LIKES and/or with Google Trends deliver more accurate forecasts. To capture the dynamics in the data, the autoregressive distributed lag (ADL) model class is employed. Taking into account the daily frequency of the original LIKES data, the mixed data sampling (MIDAS) model class is employed as well. While time-series benchmarks from the naive, error–trend–seasonal, and autoregressive moving average model classes perform best for Graz and Innsbruck across forecast horizons and forecast accuracy measures, ADL models incorporating only LIKES or both LIKES and Google Trends generally outperform their competitors for Salzburg. For Vienna, the MIDAS model including both LIKES and Google Trends produces the smallest forecast accuracy measure values for most forecast horizons.
Author(s): Ulrich Gunter, Irem Önder, Stefan Gindl
Publication date: 16. 8. 2018
Electronic version(s), related files and links: http://dx.doi.org/10.1177/1354816618793765
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"Contribution of international ecotourism to comprehensive economic development and convergence in the Central American and Caribbean region"2018 in: Applied Economics. Pages: 1-16
Drawing on the positive experience from Costa Rica, the study examines whether international ecotourism makes a significant contribution to comprehensive economic development for the Central American and Caribbean region and contributes to comprehensive economic convergence. Following a standard empirical growth model, a dynamic panel regression model is estimated using time-series data from 1995 until 2012 for a cross section of seven countries. The interaction of international tourism and various established sustainability indicators is employed allowing ecotourism to be consistently quantified across countries, while numerous country-specific structural characteristics are controlled for. The estimation results show that international ecotourism has a statistically significant positive effect on both traditional economic development (real GDP per capita) and comprehensive economic development (adjusted net savings; ANS per capita), which is a measure of a society’s potential future well-being, thus providing evidence in support of the tourism-led growth hypothesis and pointing towards an important role for ecotourism in driving comprehensive economic convergence.
Author(s): Ulrich Gunter, Graziano M. Ceddia, David Leonard, Bernhard Tröster
Publication date: 23. 1. 2018
Pages: 1-16
Electronic version(s), related files and links: http://dx.doi.org/10.1080/00036846.2018.1430339
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"Determinants of Airbnb demand in Vienna and their implications for the traditional accommodation industry"2018 in: Tourism Economics. Volume: 24. Pages: 270-293
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 that were active between July 2015 and June 2016 is examined. Estimation results, which are obtained by cluster-robust ordinary least squares, show that Airbnb demand in Vienna is price-inelastic. Significant positive drivers include listing size, number of photos, and responsiveness of the host. Significant negative drivers include listing price, distance from the city center, and response time of the host. Implications for the traditional accommodation industry are that, on the one hand, it should better communicate its sought-after advantages (e.g. lower average minimum duration of stay). On the other hand, it should increase its offer of bigger and better equipped hotel rooms since hosting more than two guests at a time is one of the major benefits of Airbnb.
Author(s): Ulrich Gunter, Irem Önder
Publication date: 2018
Volume: 24
Pages: 270-293
Electronic version(s), related files and links: http://dx.doi.org/10.1177/1354816617731196
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"Spatial price dependencies between the traditional accommodation sector and the sharing economy"2018 in: Tourism Economics. Pages: 1
Author(s): Irem Önder, Christian Weismayer, Ulrich Gunter
Publication date: 2018
Pages: 1
Electronic version(s), related files and links: http://dx.doi.org/10.1177/1354816618805860
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