Geographies of Tourism and Global Change Dieter K Müller Marek Więckowski Editors Tourism in Transitions Recovering Decline, Managing Change www.ebook3000.com Geographies of Tourism and Global Change Series editors Dieter K Müller, Department of Geography and Economic History, Umeå University, Umeå, Sweden Jarkko Saarinen, Geography Research Unit, University of Oulu, Oulu, Finland Carolin Funck, Faculty of Integrated Arts and Sciences, Graduate School of Integrated Arts and Sciences, Hiroshima University, Higashihiroshima, Japan In a geographical tradition and using an integrated approach this book series addresses these issues by acknowledging the interrelationship of tourism to wider processes within society and environment This is done at local, regional, national, and global scales demonstrating links between these scales as well as outcomes of global change for individuals, communities, and societies Local and regional factors will also be considered as mediators of global change in tourism geographies affecting communities and environments Thus Geographies of Tourism and Global Change applies a truly global perspective highlighting development in different parts of the world and acknowledges tourism as a formative cause for societal and environmental change in an increasingly interconnected world The scope of the series is broad and preference will be given to crisp and highly impactful work Authors and Editors of monographs and edited volumes, from across the globe are welcome to submit proposals The series insists on a thorough and scholarly perspective, in addition authors are encouraged to consider practical relevance and matters of subject specific importance All titles are thoroughly reviewed prior to acceptance and publication, ensuring a respectable and high quality collection of publications More information about this series at http://www.springer.com/series/15123 www.ebook3000.com Dieter K Müller Marek Więckowski • Editors Tourism in Transitions Recovering Decline, Managing Change 123 Editors Dieter K Müller Department of Geography and Economic History Umeå University Umeå Sweden Marek Więckowski Institute of Geography and Spatial Organization Polish Academy of Sciences Warsaw Poland ISSN 2366-5610 ISSN 2366-5629 (electronic) Geographies of Tourism and Global Change ISBN 978-3-319-64324-3 ISBN 978-3-319-64325-0 (eBook) DOI 10.1007/978-3-319-64325-0 Library of Congress Control Number: 2017947479 © Springer International Publishing AG 2018 This work is subject to copyright All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed The use of general descriptive names, registered names, trademarks, service marks, etc in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations Printed on acid-free paper This Springer imprint is published by Springer Nature The registered company is Springer International Publishing AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland www.ebook3000.com Preface The Commission for the Geography of Tourism, Leisure and Global Change within the International Geographical Union (IGU) has a tradition dating back to the 1980s when it comes to organizing conferences and facilitating publications on tourism geographies The Commission’s objective is to examine the geographical nature of tourism, leisure and global change Tourism and leisure are seen as deeply geographical phenomena that no happen in a socio-spatial vacuum They are understood as social and cultural activities occurring in space and time This volume is an outcome of such a conference in 2014, which was organized together with the Polish Geographical Society and the Institute of Geography and Spatial Organization within the Polish Academy of Sciences around the theme Tourism and Transition in a Time of Change The local organizers Marek Więckowski and Denis Cerić from the Institute of Geography and Spatial Planning, Polish Academy of Science, had done an excellent job in selecting the Pieniny Mountains, Southern Poland, as venue for the event and about 40 geographers from Europe, North and South America, Africa, Asia and Oceania gathered in this inspiring environment to discuss the topic of the conference Following the appreciated tradition of previous events, the hosts of the conference provided excellent field trips demonstrating the conference topic in practice This was food for thoughts and contributed to making the conference a great success Marek and Denis deserve great thanks for organizing such a memorable event This volume is also the first book in the new book series Geographies of Tourism and Global Change published by Springer and edited by Dieter Müller (Umeå University), Jarkko Saarinen (University of Oulu) and Carolin Funck (University of Hiroshima) The book series is in line with the mission of the IGU Commission for the Geography of Tourism, Leisure and Global Change and it will be one channel to illustrate the activities of the commission and its members In this context, we would like to thank the team at Springer, and not least, Stefan Einarson and the production team, for accepting and facilitating this series v vi Preface Moreover, a great thanks to all authors and colleagues contributing manuscripts and comments on draft versions, respectively, and to all other colleagues who during the recent years helped to make this book become a reality Umeå, Sweden May 2017 Dieter K Müller www.ebook3000.com Contents 1 Tourism and Transition Dieter K Müller Challenges to the Resilience of Whistler’s Journey Towards Sustainability Alison M Gill 21 Maritime Cruises: Oligopoly, Centralization of Capital and Corporate Use of Brazilian Territory Rita de Cássia Ariza da Cruz 39 Cruise Tourism: From Regional Saturation Towards Global Dynamic Equilibrium Denis Cerić 59 Island in Transition: Tourists, Volunteers and Migrants Attracted by an Art-Based Revitalization Project in the Seto Inland Sea Carolin Funck and Nan Chang Second Home Tourism: Social and Economic Change in Developing Countries like South Africa Anette Hay 81 97 Tourism Development Cooperation in a Changing Economic Environment—Impacts and Challenges in Lao P.D.R 117 Diana Marquardt Tourism Development in Riga: Resident Attitudes Toward Tourism 137 Aija van der Steina and Maija Rozite Spatial Structure of Tourism in a City After Transition: The Case of Warsaw, Poland 157 Marta Derek vii viii Contents 10 From Periphery and the Doubled National Trails to the CrossBorder Thematic Trails: New Cross-Border Tourism in Poland 173 Marek Więckowski 11 Ski Areas’ Competitiveness in the Light of Climate Change: Comparative Analysis in the Eastern Alps 187 Robert Steiger and Bruno Abegg Index 201 www.ebook3000.com Editors and Contributors About the Editors Dieter K Müller is Professor of Social and Economic Geography at the Department of Geography and Economic History, Umeå University He has published widely within the fields of tourism and local/regional development in northern areas, indigenous tourism, and tourism and mobility A particular interest relates to the geography of second homes Müller is currently the chair of the International Geographical Union (IGU) Commission for the Geography of Tourism, Leisure and Global Change and the co-editor of the Springer book series on Tourism and Global Change Marek Więckowski is Professor at the Institute of Geography and Spatial Organization of the Polish Academy of Sciences Previously he was director of research at the Institute of Geography of Cities and Population of IGiPZ PAN (2013–2014) and the director of Scientific Center of the Polish Academy of Sciences in Paris (2014–2017) Moreover, Marek is Vice-president of the Polish Geographical Society and editor of Geographia Polonica He is also a member of the IGU Commission for the Geography of Tourism, Recreation and Global Change His field of research is political geography (frontiers and cross-border collaboration), geography of tourism, mobility, geography of transport, regional development, and territorial marketing Contributors Bruno Abegg Institute of Geography, University of Innsbruck, Innsbruck, Austria Denis Cerić Department of Urban and Population Studies, Institute of Geography and Spatial Organization, Polish Academy of Sciences, Warsaw, Poland Nan Chang Graduate School of Integrated Arts and Sciences, Hiroshima University, HigashiHiroshima, Japan Rita de Cássia Ariza da Cruz Department of Geography, University of São Paulo, São Paulo, Brazil Marta Derek University of Warsaw, Warsaw, Poland Carolin Funck Graduate School of Integrated Arts and Sciences, Hiroshima University, HigashiHiroshima, Japan ix 188 R Steiger and B Abegg used Furthermore, only some of the impact studies include snowmaking in their models, an adaptation measure that can effectively improve snow reliability (Scott et al 2003) More recently, it was tried to standardize methodological approaches to conduct supra-regional and transnational studies Dawson and Scott (2013) applied the SkiSim1 model to investigate climate change impacts on ski areas in the US Northeast; Hendrikx et al (2013) compared the relative vulnerability of ski areas in Australia and New Zealand; Scott et al (2015) applied the SkiSim2 model to all 19 former Winter Olympic Games host regions For the European Alps, one comprehensive study exists (Abegg et al 2007), but the impact analysis is limited to natural snow only However, there are several regional studies incorporating snowmaking (Southern Germany: Steiger 2013; Grisons/Switzerland: Abegg et al 2013; Austria: Steiger and Abegg 2013; Northern Italy: Steiger and Stötter 2013) Although the same snow model was used in all these applications (SkiSim2) some model parameters (e.g., for snowmaking) and the climate scenarios used differed The first objective of this chapter is therefore to model and analyse the snow reliability of 310 ski areas in the Eastern Alps using the same parameters By doing so, relative vulnerability of ski areas—in terms of snow reliability—can be assessed Snow conditions and snow reliability are among the most important factors for ski destination choice The attractiveness of ski areas though consists of several other factors, as market surveys and internet portals show (Österreich Werbung 2012; WKO 2014; www.skiresort.de) In a survey conducted in 55 ski areas across the Alps with 41,864 respondents (Partel 2012), the top factors relevant for destination choice were: the size of the ski area and the variety of ski slopes, followed by snow reliability, slope grooming, the accommodation and ski lift comfort To assess the attractiveness and competitiveness of ski areas in times of climate change, it is thus important to not only model snow conditions but to include additional factors In existing studies, this is usually not the case Factors like ski area size, or business indicators like skier days and turnover are not or only rarely mentioned, e.g., within the qualitative interpretation of modeling results The focus on snow reliability and neglecting other important factors limits the assessment of the industry’s future: For example, what does it mean when a certain share of ski areas in a region is not snow reliable anymore? Will all these ski areas disappear and can be assumed that overall supply declines proportionately? Rather not, as remaining ski areas could take advantage of that situation and enlarge their offer and attract new guests For this reason, the second objective of this paper is to analyse additional factors like ski area size, comfort of transport facilities and snowmaking coverage This will constitute a step towards a broader base for interpretation of snow-modelling results 11 Ski Areas’ Competitiveness in the Light of Climate Change … 11.2 189 Methods Our research area consists of 310 ski areas in the following regions: Grisons (Switzerland); Allgäu and Upper Bavaria (Germany); Vorarlberg, Tyrol, Salzburg, Lower and Upper Austria, Styria and Carinthia (Austria); and South Tyrol (Italy) The following factors were included to assess the attractiveness of ski areas: ski area size, comfort of transport facilities, snowmaking coverage and snow reliability For ski area size, the length of ski slopes (in km) was used as an indicator The comfort of transport facilities is represented by the share of ski lifts (t-bars) Both indicators were derived from the online portal Bergfex (http://www.bergfex.at) It should be noted that the length measurement of ski slopes was reworked in Austria in 2013 leading to a shortening of total slope length in most ski areas As this update is on a voluntary basis, it might be the case that some ski areas still publish slope lengths using the old method, overestimating their slope length Snow reliability was analysed using the indicators “snowmaking coverage” and “number of snow reliable ski areas” The former was derived from reports of several regional associations and offices (see Table 11.1), the latter is based on the number of potential skiing days per ski area modeled by SkiSim2 (see Steiger 2010) The snow model simulates snow depth on a daily basis in 100 m bands with daily minimum and maximum temperature and precipitation from weather stations Table 11.1 Share of t-bar lifts and share of ski slopes covered with snowmaking facilities Region Share of t-bar lifts (%)a 2013 Snowmakingb Share of ski slopes with snowmaking (%) 2006 2012 Relative change 2006–2012 Rel (%) Grisons 60 21 37 +76 67 13 18 +46 Bavarian Alpsc 33 75 80 +6 South Tyrold Vorarlberg 58 34 50 +47 Tyrol 52 60 90 +50 Salzburg 55 56 80 +43 Upper Austria 71 43 52 +21 Lower Austria 60 57 – – Carinthia 73 73 90 +23 Styria 73 62 83 +34 a Source Bergfex (2016) b Source Astat (2010), Bergbahnen Graubünden (2006, 2012), BLfU (2013), Lebensministerium (2013), VDS (2013), Wieser (2006) c 2007/08 d 2008 www.ebook3000.com 190 R Steiger and B Abegg For this study 80 weather stations could be used in the research area To account for the altitudinal difference between the weather station and a 100 m band in the ski area, temperature and precipitation need to be interpolated High altitude stations are used to calculate monthly temperature lapse rates for each weather station It is distinguished between dry and wet days to account for days with thermal inversion Precipitation is extrapolated with a gradient of 3%/100 m (Fliri 1975) SkiSim2 is calibrated for each weather station aiming at minimizing the difference between modeled and observed cumulative snowfall and snow cover days (days with snow depth cm) Snowmaking is possible at temperatures −4 °C and is calculated on an hourly basis by linearly interpolating daily minimum and maximum temperature Maximum snowmaking capacity per day is 10 cm representing state-of-the-art snowmaking systems (Steiger and Abegg 2013) Base-layer snowmaking (Steiger and Mayer 2008) is conducted in the beginning of the season, producing 40 cm of snow regardless of natural snowfalls and snow conditions In reality, subsequent improvement snowmaking is regulated by experiences of the staff responsible for snowmaking with the aim to remain in operation until the scheduled season closing (Steiger and Mayer 2008) In the model this scheduled season closing was set to March 31 Real season closing differs between ski areas, depending on their altitude and location, and is between mid-march in low altitude ski areas in the alpine foothills and May in high altitude non-glacier ski areas Our uniform date is thus a simplification being necessary for reasons of comparability However, March 31 represents the end of the peak season where about 90% of turnover is generated (Steiger 2010) Improvement snowmaking is calibrated in order to reach this defined season closing date in 90% of all seasons within a 30-year period, provided that climatic conditions are sufficient This rule shall represent the staff’s long-year experience, how much snow is required Further details on the snow model can be found in Steiger (2010, 2013), Steiger and Abegg (2013) and Steiger and Stötter (2013) For each ski area the closest weather station is chosen to best represent the climatic conditions in the ski area Snow reliability is analysed at the mean altitude of each ski area (=mean of lowest and highest lift station, only including lift stations with ski slope access) Snow reliability is divided into three classes and is based on two indicators: (1) the 100-day rule, where ski areas are considered snow reliable if a ski season of at least 100 days (with a minimum snow depth of 30 cm) is reached in at least out of 10 seasons (Abegg 1996) (2) the Christmas rule, where ski areas are snow reliable if snow depth is sufficient ( 30 cm) for operation during 14 days in the Christmas/New Years school holidays in out of 10 seasons (Steiger and Abegg 2013) The Christmas holiday period is very important for ski areas as a high share of turnover is generated in these two weeks (e.g., 25% in Grisons, 30% in Tyrol) (Abegg 1996; Steiger 2010) These two indicators provide three classes of snow reliability: snow reliable ski areas fulfill the 100-day rule and the Christmas rule; partly snow reliable ski areas only fulfill the 100-day rule; and the remaining ski areas are defined as not snow reliable 11 Ski Areas’ Competitiveness in the Light of Climate Change … 191 Arbitrary climate scenarios were used by increasing temperature in 0.5 °C increments up to +4 °C compared to the reference period 1981–2010 In contrast to using climate model data, this approach allows to relate snow reliability to a specific temperature increase, improving communication with stakeholders A °C warming can be expected by 2030, +2 °C by 2050 and +4 °C towards the end of the century, although the latter is dependent on the greenhouse gas emissions in the upcoming decades Modelling of indicators and data collection—except snowmaking coverage— were conducted at the level of ski areas Snowmaking coverage was only available at a regional level (share of ski slopes equipped with snowmaking) The following analysis and interpretation were conducted at the regional scale Nevertheless, the maps also allow further analysis on a sub-regional level Due to the high snowmaking coverage in most of the regions, and the trend of further expansions of snowmaking facilities, results for natural snow reliability are only shown for the reference period We limit our analysis to the and °C scenario, thus presenting a future outlook approximately until the middle of the century 11.3 Results The size of the ski areas differs greatly between our study regions (Fig 11.1) In Grisons, there is a balanced mix of small, medium, large and very large ski areas, with the latter being the only category that is seen as internationally visible and competitive The Bavarian Alps, Lower and Upper Austria and Styria have a high share of small to medium ski areas, illustrating the limited topographic suitability for ski slopes in these regions Tyrol has the highest number of ski areas, with many small but also with the highest number of very large ski areas Generally, a considerable disparity in ski areas size exists between the inner alpine regions and the Prealps South Tyrol has by far the highest comfort of transport facilities, as measured by the lowest share of t-bar lifts (Table 11.1) The share continuously declined from 71% in 1980 to 63% (1990), 58% (2000) (Astat 2013) and 33% (2013) (Bergfex 2016) Possible reasons could be the snow dependency of t-bar lift tracks and the higher interannual snow variability south of the main alpine divide, leading to an earlier replacement of t-bar lifts with floor-independent transport facilities Styria, Upper Austria and Carinthia have the highest share of t-bar lifts, comparable with South Tyrol 30 years ago This could be due to the high share of small ski areas with less financial capacity to invest into expensive transport facilities The regions also differ greatly in the share of ski slopes equipped with snowmaking: snowmaking coverage is highest in Tyrol, South Tyrol, Carinthia, Salzburg and Styria The lowest snowmaking coverage is found in the Bavarian Alps, followed by Grisons In the latter region though, the extension of snowmaking coverage was the highest between 2006 and 2012 (+76%) These differing values cannot be fully explained with natural snow reliability While in Grisons, natural www.ebook3000.com 192 R Steiger and B Abegg Fig 11.1 Ski areas classified by size Source Bergfex (2014); own illustration snow reliability (fulfilling the 100-days and the Christmas rule) in the current climate is given for 97% of ski areas (Abegg et al 2013), this is the case for only 44% of ski areas in the Bavarian Alps (Steiger 2013) Natural snow reliability is even worse in Lower and Upper Austria, Styria and Carinthia (Fig 11.2) But, due to better snowmaking coverage in these regions, natural snow reliability is only of little importance Similarly to ski area size, a clear difference in natural snow reliability from the Prealps to the inner alpine regions can be seen Including snowmaking though in ski season modeling, leads to a markable increase of snow reliability in the entire research area: almost all ski areas (301 out of 310) could be made snow reliable in the reference period A warming of °C would lead to a reduction of snow reliable ski areas to 281 (91%) Non and partly snow reliable ski areas are concentrated in the northern parts of Salzburg, the Eastern Bavarian Alps and Upper Austria (Fig 11.3) Mostly small ski area fall in this category 17 ski areas turn from snow reliable to party snow reliable, eight become unreliable One very large ski area in Tyrol turns from snow reliable to party snow reliable A warming of °C reduces the number of snow reliable ski areas to 214 (69% of ski areas) Non snow-reliable ski areas are concentrated in Upper and Lower Austria, Styria, Eastern Tyrol and the Bavarian Alps (Fig 11.3) Again, small ski areas are affected the most 69 small ski areas lose snow reliability in the Christmas holidays, 33 not even fulfill the 100 days rule 13 medium sized ski areas are only partly snow reliable, another five are not snow reliable anymore Two large (Tyrol) and two very large ski areas (Tyrol and Styria) turn from snow reliable to partly snow reliable, one large (Upper Austria) and one very large ski area (Tyrol) are not snow reliable 11 Ski Areas’ Competitiveness in the Light of Climate Change … 193 Fig 11.2 Snow reliability of ski areas today (1981–2010) without (top) and with snowmaking (bottom) Source Own research The picture is very diverse with regions where the majority of ski areas would turn non snow reliable in a °C scenario, i.e., the northern and eastern parts of the research area, and regions with mostly unchanged snow reliability, i.e., across the main alpine divide Thus the foothills of the Alps could lose most of today’s existing ski areas, while the situation is less urgent in the center of the Alps However, if large and very large ski areas experience severe problems with snow reliability as suggested by the model results, this could have a negative impact on the image of an entire region In order to maintain a 100-day season, the amount of technically produced snow needs to be increased substantially In a °C scenario, ski areas would need to www.ebook3000.com 194 R Steiger and B Abegg Fig 11.3 Snow reliability of ski areas with snowmaking in a +1 °C (top) and +2 °C scenario (bottom) Source Own research increase snow production by a third in most of the regions (Table 11.2) With a warming of °C, average snow production almost doubles (88%) in the Bavarian Alps and Upper Austria, while in Grisons the average increase is considerably lower with 29% Note that these simulated increases are rather underestimating real increases, as we already assume a 100% snowmaking coverage in all ski areas in the reference period, which is obviously not the case in reality (see Table 11.1) Furthermore, these increases refer to the required snow volumes to maintain a 100-day season In contrast to the snow reliability analysis, climatic limits of snow production are not considered in this indicator 11 Ski Areas’ Competitiveness in the Light of Climate Change … 195 Table 11.2 Change of snow demand Scenario/Region 0.5 °C (%) 1.0 °C (%) 1.5 °C (%) 2.0 °C (%) Bavarian Alps Vorarlberg Tyrol Salzburg Upper Austria Lower Austria Styria Carinthia Grisons South Tyrol 15 14 10 13 16 14 14 12 34 29 23 29 36 36 31 25 11 19 55 46 39 48 71 48 51 41 20 35 88 74 60 72 88 66 72 60 29 54 11.4 Discussion Considering more factors than just snow reliability, like ski area size, comfort of transport facilities and snowmaking coverage, is a first step towards a broader assessment of climate change impacts on the ski tourism industry Data collection though turned out to be difficult due to (1) a variety of different sources with (2) in part contradictory information, and (3) differing units (e.g., snowmaking coverage published in km of ski slopes, in hectares or in percent) The accuracy of some data (e.g., length of ski slopes) is unknown and can be questioned A challenge is also to harmonize the data in terms of reporting periods Some data are available on the business level, but only for selected ski areas; other data is only available on a regional aggregated level, although it is not always clear how the data was aggregated This complicates the preparation of consistent and regionally comparable time series Data compilation becomes even more challenging when looking at economic data (e.g., skier days, investments, etc.) For this reason, we did not include such economic and demand data The market potential, accessibility and winter dependency of destinations could also be insightful indicators Not all factors have the same relevance for all ski areas Internationally renowned ski areas target other tourist groups than small family ski areas Consequently, factors being important for international ski areas (e.g., size, comfort) might not be that relevant for ski areas acting predominantly in a regional market The results show that especially smaller ski areas at the rim of the Alps are affected by climate change Due to the small size, these ski areas only have a small share of skier visits It could thus be concluded that their exit from the market would not lead to significant overall losses On the other hand, it should be considered that these ski areas have an important function as rather inexpensive, easily accessible alternatives to large, expensive ski areas in the inner alpine regions This is an important aspect especially for beginners and families with kids living in metropolitan areas in vicinity to the www.ebook3000.com 196 R Steiger and B Abegg alpine foothills (e.g., Munich, Vienna) If these ski areas would vanish, the larger ski areas in the center of the Alps could lose some of their market potential as less people go skiing due to higher entry barriers to this activity The last four winter seasons 2013/14–2016/17 were extraordinary warm and snow deficient It was evident that ski areas with state-of-the-art snowmaking systems were more successful than ski areas with no or little snowmaking Nevertheless, too warm temperatures to produce snow in December threatened the important Christmas period throughout the Alps And although ski area managers were satisfied with snow conditions (due to snowmaking) they also complained about a decline of demand especially from day-visitors Skier surveys in snow deficient winter seasons showed that possible reasons for fewer skiing days are anticipated bad snow conditions, lack of winter feeling in the source markets, but also be non-snow related like time or financial constraints (Steiger et al 2015) This suggests that there is a number of aspects affecting the demand side still being insufficiently understood (see e.g., Dawson et al 2011; Pons-Pons et al 2012; Rutty et al 2015a, b; Scott and Steiger 2013; Steiger 2012) Experiences from past snow-deficient winter seasons and modeling results show a considerable potential of snowmaking, but the technical and climatic limits are also evident In order to remain snow reliable, more snow needs to be produced in shorter time windows being suitable for snowmaking, resulting in higher resource consumption and costs Apart from technical or climatic limits, the ecological and economic impacts of snowmaking and the resource consumption need to be better analysed (Pickering and Buckley 2010; Rixen et al 2011; Abegg 2012) The regions analyzed in this chapter show a greatly differing attractiveness for skiers It is likely that these differences become even more accentuated in the future Challenges originating from change—not restricted to climatic change but also considering demographic change, etc.—will have regionally differing impacts Therefore, strategies and visions need to be tailored to regional or local conditions Currently, the main strategy in the less developed regions is trying to catch up, although the framework conditions (e.g., financial, climatic, topographic, market potential) are not always suitable for such a development path A rethinking process can hardly be seen On the contrary: where ski areas are not profitable anymore, the public domain grants subsidies or even takes over and operates these ski areas Bearing in mind a stagnating skier market and increasing deficits of public budgets, this preservation of structures needs to be questioned In light of climate change, such strategies not appear to be future-oriented References Abegg, B (1996) Klimaänderung und Tourismus: Klimafolgenforschung am Beispiel des Wintertourismus in den Schweizer Alpen Zürich: Vdf Zürich Abegg, B., Agrawala, S., Crick, F., & de Montfalcon, A (2007) Climate change impacts and adaptation in winter tourism In S Agrawala (Ed.), Climate change in the European Alps (pp 25–60) Paris: OECD-Publishing 11 Ski Areas’ Competitiveness in the Light of Climate Change … 197 Abegg, B (2012) Natürliche und technische Schneesicherheit in einer wärmeren Zukunft In W S L Eidgenössische Forschungsanstalt (Ed.), Alpine Schnee- und Wasserressourcen gestern, heute und morgen (pp 29–35) Davos: Forum für Wissen Abegg, B., Steiger, R., & Walser, R (2013) Herausforderung Klimawandel: Chancen und Risiken für dem Tourismus in Graubünden Chur: Lantsch/Lenz Astat (2010) Seilbahnen in Südtirol 2009 Bozen: Amt für Seilbahnen, Autonome Provinz Bozen-Südtirol Astat (2013) Seilbahnen in Südtirol 2012 Bozen: Amt für Seilbahnen, Autonome Provinz Bozen-Südtirol Bergbahnen Graubünden (2006) Annual report Chur: Lantsch/Lenz Bergbahnen Graubünden (2012) Annual report Chur: Diverse Jahrgänge, Lantsch/Lenz Bergfex (2016) Data base of ski areas http://www.bergfex.at/ BLfU (Bayerisches Landesamt für Umwelt) (2013) Beschneiungsanlagen und Kunstschnee Augsburg Dawson, J., Havitz, M., & Scott, D (2011) Behavioral adaptation of alpine skiers to climate change: Examining activity involvement and place loyalty Journal of Tourism & Travel Marketing, 28, 388–404 Dawson, J., & Scott, D (2013) Managing for climate change in the alpine ski sector Tourism Management, 35, 244–254 Fliri, F (1975) Das Klima der Alpen im Raume von Tirol Monographien zur Landeskunde Tirols Vol Innsbruck: Universitätsverlag Wagner Fukushima, T., Kureha, M., Ozaki, N., Fukimori, Y., & Harasawa, H (2002) Influences of air temperature change on leisure industries: Case study on ski activities Mitigation and Adaptation Strategies for Climate Change, 7, 173–189 doi:10.1023/A:1022803405470 Hendrikx, J., & Hreinsson, E (2012) The potential impact of climate change on seasonal snow in New Zealand: Part II—Industry vulnerability and future snowmaking potential Theoretical and Applied Climatology, 110(4), 619–630 doi:10.1007/s00704-012-0713-z Hendrikx, J., Zammit, C., Hreinsson, E Ö., & Becken, S (2013) A comparative assessment of the potential impact of climate change on the ski industry in New Zealand and Australia Climate Change, 119, 965–978 doi:10.1007/s10584-013-0741-4 Hennessy, K L., Whetton, P H., Walsh, K., Smith, I N., Bathols, J M., Hutchinson, M., et al (2008) Climate change effects on snow conditions in mainland Australia and adaptation at ski resorts through snow making Climate Research, 3, 255–270 doi:10.3354/cr00706 Lebensministerium (2013) BM für Land- und Forstwirtschaft, Umwelt und Wasserwirtschaft Anfragebeantwortung Februar 2013 Wien Mayer, M., & Steiger, R (2013) Skitourismus in den Bayerischen Alpen - Entwicklung und Zukunftsperspektiven In H Job & M Mayer (Eds.), Tourismus und Regionalentwicklung in Bayern Arbeitsberichte der ARL (pp 164–212) Hannover: Verlag der ARL Partel, M (2012) Best ski resort report 2012 Bregenz: Mountain Management Pickering, C M., & Buckley, R C (2010) Climate response by the ski industry: The shortcomings of snowmaking for Australian resorts Ambio, 39, 430–438 doi:10.1007/s13280010-0039-y Pons-Pons, M., Johnson, P A., Rosas-Casals, M., Sureda, B., & Jover, E (2012) Modeling climate change effects on winter ski tourism in Andorra Climate Research, 54(3), 197–207 doi:10.3354/cr01117 Rixen, C., Teich, M., Lardelli, C., Gallati, D., Pohl, M., Pütz, M., et al (2011) Winter tourism and climate change in the Alps: An assessment of resource consumption, snow reliability, and future snowmaking potential Mountain Research and Development, 31(3), 229–236 doi:10 1659/MRD-JOURNAL-D-10-00112.1 Rutty, M., Scott, D., Johnson, P., Jover, E., Pons, M., & Steiger, R (2015a) Behavioural adaptation of skiers to climatic variability and change in Ontario, Canada Journal of Outdoor Recreation and Tourism, 11, 13–21 doi:10.1016/j.jort.2015.07.002 www.ebook3000.com 198 R Steiger and B Abegg Rutty, M., Scott, D., Johnson, P., Jover, E., Pons, M., & Steiger, R (2015b) The geography of skier adaptation to adverse conditions in the Ontario ski market The Canadian Geographer, 59 (4), 391–403 doi:10.1111/cag.12220 Scott, D., Hall, C M., & Gössling, S (2012) Tourism and climate change: Impacts, adaptation & mitigation London-New York: Routledge Scott, D., McBoyle, G., & Mills, B (2003) Climate change and the skiing industry in Southern Ontario (Canada): Exploring the importance of snowmaking as a technical Adaptation Climate Research, 23, 171–181 doi:10.3354/cr023171 Scott, D., McBoyle, G., & Minogue, A (2007) Climate change and Quebec’s ski industry Global Environmental Change, 17, 181–190 doi:10.1016/j.gloenvcha.2006.05.004 Scott, D., Dawson, J., & Jones, B (2008) Climate change vulnerability of the US Northeast winter recreation—tourism sector Mitigation and Adaptation Strategies for Global Change, 13, 577– 596 doi:10.1007/s11027-007-9136-z Scott, D., & Steiger, R (2013) Vulnerability of the Ski Industry In A Pielke (Ed.), Climate vulnerability: Understanding and addressing threats to essential resources (pp 305–313) Amsterdam: Elsevier Scott, D., Steiger, R., Rutty, M., & Johnson, P (2015) The future of the Olympic Winter Games in an era of climate change Current Issues in Tourism, 15, 913–930 doi:10.1080/13683500 2014.887664 Scott, D., Steiger, R., Rutty, M., Pons, M., & Johnson, P (2017) The differential futures of ski tourism in Ontario (Canada) under climate change: The limits of snowmaking adaptation Current Issues in Tourism (accepted) Steiger, R (2010) The impact of climate change on ski season length and snowmaking requirements Climate Research, 43(3), 251–262 doi:10.3354/cr00941 Steiger, R (2012) Scenarios for skiing tourism in Austria: Integrating demographics with an analysis of climate change Journal of Sustainable Tourism, 20(6), 867–882 doi:10.1080/ 09669582.2012.680464 Steiger, R (2013) Auswirkungen des Klimawandels auf Skigebiete im bayerischen Alpenraum Deutscher Alpenverein, München: Projektabschlussbericht Steiger, R., & Abegg, B (2013) The sensitivity of Austrian ski areas to climate change Tourism Planning and Development, 10(4), 480–493 doi:10.1080/21568316.2013.804431 Steiger, R., & Mayer, M (2008) Snowmaking and climate change: Future options for snow production in Tyrolean ski resorts Mountain Research and Development, 28(3/4), 292–298 doi:10.1659/mrd.0978 Steiger, R., Peters, M., & Abegg, B (2015) Weather preferences and sensitivity of alpine skiers In O C Demiroğlu, C de Freitas, D Scott, M.L Kurnaz, & D Ünalan (Eds.), Proceedings of the 4th International Conference on Climate, Tourism and Recreation—CCTR2015 (pp 52– 56) Istanbul: Istanbul Policy Center, Sabanci University, http://ipc.sabanciuniv.edu/en/wpcontent/uploads/2015/11/ProceedingsRaporENG.25.11.15.web_.pdf Steiger, R., Scott, D., Abegg, B., Pons, M., & Aall, C (2017) A critical review of climate change risk for ski tourism Current Issues in Tourism (accepted) Steiger, R., & Stötter, J (2013) Climate change impact assessment of ski tourism in Tyrol Tourism Geographies, 15(4), 577–600 doi:10.1080/14616688.2012.762539 VDS (Verband Deutscher Seilbahnen und Schlepplifte) (2013) Nur fliegen ist hưher…: Zahlen, Daten, Fakten München Ưsterreich Werbung (2012) T-MONA Urlauber Winter 2011/12 Wien: Reiseverhalten der Gäste in Österreich Wieser, K (2006) Quo vadis, Schnee? Präsentation Schnei-Akademie 2006 (https://www.yumpu com/de/document/view/6636707/technische-und-ideologische-die-osterreichische-schneiakademie Visited 2017-05-01 WKO (2014) Fachverband Seilbahnen Aktuelle Themen Wien: Wirtschaftskammer Österreich 11 Ski Areas’ Competitiveness in the Light of Climate Change … 199 Author Biographies Robert Steiger is Assistant Professor at the Institute of Public Finance at the University of Innsbruck/Austria, with strong background in climate change impacts on tourism systems He has contributed to the National Climate Change Assessment Reports of Austria and Switzerland and has research experience in the Alps, Canada and Scandinavia His current research focus is regional development and tourism, and transformation of tourism systems Bruno Abegg is Professor for Human Geography and head of the Alpine Tourism Geography group at the University of Innsbruck/Austria He is one of the pioneers in the field of climate change and mountain tourism with 20+ years of experience His research interest includes: weather— climate—tourism, climate change and tourism (impacts, adaptation and mitigation), tourism— energy, regional development, transformation of alpine destinations and trans-disciplinary research approaches www.ebook3000.com Index A Adaptation, 2, 3, 5, 11, 12, 30, 51 Africa, 12 Agriculture, Alps, Architecture, 81, 82, 84, 88–90, 138 Art tourism, 13 Asia, 12 Attractions, 4, Austria, 188, 189, 191, 192, 194, 195 B Bavarian alps, 187, 191, 192, 194 Borderlands, 173, 175–178, 180, 184 Borders, 13, 14 Boundaries, 3, 10, 27 Brazil, 39–42, 50, 52, 56 Business, 13, 21, 26, 29–31, 49 C Capital, 9, 39, 44, 53 Caribbean, 40 Case study, 13 Change, 2–5, 7, 8, 10, 11, 13, 21–24, 28, 33, 39, 42, 43, 56 City, 4, 13, 14, 53 Climate, 5, 11, 14, 22, 34 Climate change, 4, 11, 14, 34 Community, 11, 12, 14, 22, 25–28, 30, 32, 33 Company, 11, 32, 40, 43, 44, 48, 52, 53 Consumption, 6, 8, 9, 14, 41 Cooperation, 13 Country, 12, 13, 39, 49, 53, 56 Countryside, 13 Crisis, 4, 7, 8, 10, 12, 14, 31, 44, 56 Cross-border tourism, 14 Cruise, 12, 13, 39–44, 50–54, 56 Cruise company, 67, 68 Cruise ships, 39, 41, 42, 48, 49, 52, 55 Cultural impact, 82, 122, 142, 145 Culture, 9, 14, 33 D Destination, 2, 4, 6–9, 11, 13, 22, 24, 25, 31, 41, 56 Development, 2, 4, 5, 10, 12–14, 25, 27, 28, 30, 34, 42 Development cooperation, 13 Development path, 196 Donors, 13 Dynamics, 13, 23, 52 E Economic development, 13, 27, 28 Economy, 2, 6, 7, 12–14, 32, 33, 39, 56 Environment, 2–4, 13, 26, 32, 33, 41 Europe, 12, 43, 49 Events, 3, 5–11, 23, 24, 31 Evolution, 22, 25 F Farming, 13 Festival, 81, 84, 85, 87, 89, 90, 120 First nations, 26, 28, 32, 34 G Global, 4, 7, 8, 11, 12, 25, 31, 34, 39–42, 44, 49, 51, 52, 54–56 Governance, 12, 21, 22, 24–26, 28, 29, 32, 33 Government, 7, 13, 22, 25, 26, 31, 33, 49, 52, 117, 123, 124, 126, 129, 132 Growth, 7, 12, 13, 23–25, 28, 29, 32, 42 © Springer International Publishing AG 2018 D.K Müller and M Więckowski (eds.), Tourism in Transitions, Geographies of Tourism and Global Change, DOI 10.1007/978-3-319-64325-0 201 202 Index H Housing, 25, 27, 32, 33 N Naoshima, 13, 81–88, 91, 93, 94 Nations, 27 I Impacts, 4, 6, 7, 12, 14, 31, 51, 56, 97, 103, 109, 118, 127–129, 138, 145, 146, 148, 150, 151, 188, 196 Infrastructure, 4–6, 11, 27, 41, 119, 122–124, 127, 130, 145, 151, 169, 173, 180 Inhabitants, 64, 81, 83, 85, 91, 93, 101, 122, 124, 137, 143, 144, 148, 149, 151, 164, 165, 168, 177 In-migrants, 13, 81, 85, 91, 92, 94 Innovation, 5, 7–9, 12, 24, 30, 34, 131, 175, 180, 182, 185 Integration, 7, 14, 23, 62, 119, 173–176, 178, 182, 184 Interaction, 81, 138, 143, 145, 146, 149–151, 162, 174, 176, 181, 182 Investment, 7, 9, 12, 14, 44, 52, 54, 118–120, 123, 124, 132, 146, 161, 163, 169, 195 Involvement, 43, 81, 82, 86, 87, 91, 94, 108, 143, 145, 149 Island, 13, 54, 81–83, 85–87, 89–91, 94 J Japan, 13, 49, 81–85, 87, 89, 91, 94, 187 L Land use, 32, 34, 102, 111, 158, 164, 168, 169, 180 Laos, 13, 117–121, 128, 132 Latvia, 13, 137–141 Local, 7–9, 11, 14, 21, 26, 30, 31, 33, 53, 81–84, 86, 87, 89, 90, 93, 100, 102, 103, 108–111, 123, 125–127, 130, 131, 137, 138, 140, 142, 144, 146, 149, 150, 158, 164, 166, 168, 177, 182 Luang Prabang, 121, 122, 124, 129, 131 M Market, 5, 7, 8, 11–14, 30, 39, 40, 42, 44, 49, 50, 55, 56, 60, 62, 64, 68, 71, 76, 84, 117, 119, 123, 126, 127, 130, 132, 137, 138, 141, 157, 164, 167, 177, 187, 188, 195, 196 Mediterranean, 13, 60, 63, 66–71, 73–76, 142 Migrants, 13, 94 Municipality, 22, 25, 27–29, 33, 100, 108, 109 Museum, 71, 84, 86, 88, 92, 138, 158, 161, 162, 164, 165, 167, 184 O Olympic games, 9, 21, 31, 188 Operators, 26, 33, 40, 44, 51, 52, 54, 56, 126 P Passengers, 39–43, 48, 50, 51, 53, 55, 56, 60–65, 68, 69, 71, 73–75 Places, 4, 9, 42, 51, 52, 101, 146, 149, 151, 157, 161, 164, 165, 176 Planning, 3, 8, 13, 22, 25–27, 31, 32, 118, 120, 123, 124, 126, 127, 129, 142, 181, 184 Poland, 14, 159, 164, 173, 177–180, 182, 184, 185 Political, 4–8, 12, 13, 21, 24, 25, 27, 32, 39, 44, 71, 76, 97, 117, 126, 132, 143, 150, 157, 162, 173, 175, 176 Ports, 12, 41, 42, 52, 53, 59, 68, 69, 72, 76 Post-productivism, 97, 102, 103, 110, 111 Potential, 5, 32, 56, 60, 62, 64, 65, 71, 73, 74, 76, 122, 124, 130, 132, 175, 176, 187, 189, 195, 196 Poverty, 13, 118, 119, 124, 128, 131 Poverty reduction, 13, 118, 120, 124, 127, 133 Prefecture, 81–84, 86, 87, 89 Problems, 11, 29, 86, 93, 118, 120, 122, 123, 126, 128, 130, 132, 139, 142, 151, 157, 164, 168, 187, 193 Production, 5, 8, 9, 55, 101–103, 110, 111, 131, 194 Pro-poor tourism, 125, 127, 132 Q Quality, 25, 26, 29, 33, 98, 119, 123, 129–131, 138, 146, 180, 185 R Region, 6–8, 10, 54, 71–73, 119, 124, 127, 138, 142, 163, 173, 175, 176, 178, 181, 187, 192, 195 Residents, 25, 26, 32, 100, 104, 108, 109, 137–140, 142–151, 161, 165, 182 Residents’ attitudes, 142, 144, 150 Resilience, 3, 12, 21–24, 28, 33, 34, 76, 98 Resort, 12, 21, 22, 25, 26, 28, 30, 31, 142 Riga, 13, 137–141, 145–147, 149, 151 Rural, 13, 81, 94, 97, 98, 100, 101, 103, 108, 110–112, 124, 128 www.ebook3000.com Index S Season, 8, 39, 50, 53, 75, 109, 144, 167, 181, 190, 193, 194 Second homes, 7, 97, 98, 101, 102, 106, 108, 112 Services, 11, 25, 33, 44, 83, 94, 100, 102, 108, 131, 146, 158, 159, 162, 165, 167, 174, 181, 184 Seto Inland sea, 13, 82, 87 Ship building, 61 Ships, 40, 42, 51, 180 Shopping, 81, 160, 162, 173, 176, 178–181, 184 Ski area, 14, 188–190, 192, 194–196 Skills, 91, 108, 119, 127, 129, 149, 180 Snow making, 14, 188–191, 196 Snow reliability, 14, 188–192, 194 Social, 5, 8, 21, 23, 52, 53, 56, 97, 106, 109, 118, 119, 143, 149, 167, 177 Socio-economic, 11, 13, 97, 98, 103, 124, 132, 143, 173, 175, 177 South Africa, 13, 68, 97, 98, 101–103, 109 Strategy, 30, 81, 124, 127, 130, 196 Styria, 187, 189, 191, 192 Supply, 8, 44, 63, 64, 68, 71, 121, 158, 188 Support, 8, 12, 21, 27, 29, 31, 42, 108, 111, 117, 123, 125, 129, 131, 147, 149, 182, 185 Sustainability, 3, 12, 21–24, 26–29, 31–34, 94, 118, 126–128 Sustainable development, 12, 31, 103, 132, 138 T Territory, 26, 39–41, 51, 52, 99, 174 Tourism, 2, 4–9, 12, 14, 28, 31, 42 Tourism development, 4, 6, 8, 9, 13, 14, 84, 85, 92, 123, 124, 126–128, 132, 137–139, 142–146, 149, 150 203 Tourism impact, 1, 138, 139, 142, 144, 146, 148 Tourism industry, 2, 6, 7, 29, 56, 91, 92, 108, 124, 130, 131, 138, 139, 142, 176, 195 Tourism management, 3, 8, 22, 23, 25, 29, 86, 87, 89, 90, 123, 126–128, 130 Tourism organizations, 59 Tourism system, 2, 5, 7, 9, 11 Tourist demand, 4, 159, 169 Tourist infrastructure, 175, 177–179, 182, 184 Tourists, 4, 13, 60, 81, 82, 86, 87, 89, 90, 121, 125, 138–141, 145, 149, 150, 161, 168, 175, 178, 179, 182 Tourist space, 157, 173, 176, 179, 180, 182, 184 Tourist traffic, 178–181, 184 Transition, 2, 4, 5, 8, 11–13, 24, 30, 118, 120, 125, 150, 157, 159, 164, 169, 174, 187 Transport, 39–43, 53, 119, 164, 188, 191, 195 Tyrol, 187, 189, 191, 192 U Urban environment, 137, 145, 146, 149, 151 Urban tourism, 101, 141, 157, 158, 168 V Vessels, 13, 40–42, 48, 49, 53, 55, 61, 65, 67, 69, 76 Vietnam, 117, 121 Visitors, 13, 25, 81, 82, 87, 121, 139, 160, 163–167, 179 Volunteers, 81, 82, 86, 89, 90, 94 W Warsaw, 5, 14, 157, 159, 161, 162, 164, 165, 168, 169 Whistler, 12, 21, 22, 25, 27, 28, 30, 31, 33 ... Editors Tourism in Transitions Recovering Decline, Managing Change 123 Editors Dieter K Müller Department of Geography and Economic History Umeå University Umeå Sweden Marek Więckowski Institute... 2014) Finally, a major trigger for change is innovation Although researchers argued that innovation in tourism is limited there are multiple examples of how innovation in tourism also changed... regulations and institutions as well as economic decision-making influencing investments are other factors capable of altering tourism systems Finally, innovation is a major reason for transitions