| 1. |
- Chekalina, Tatiana, 1979-
(författare)
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A Value Co-Creation Perspective on Customer-Based Brand Equity Modelling for Tourism Destinations : A case from Sweden
- 2015
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Tourism destinations all over the world increasingly embrace marketing and branding practices traditionally utilized by businesses. However, the literature on customer-based brand equity modelling and measurement for tourism destinations lacks the conceptual understanding of the complex relationships between tourists and the destination brand.Therefore, the thesis at hand addresses the existing gap in tourism literature and aims at contributing to the development of the customer-based brand equity concept in a tourism destination setting (CBDBE) by taking into account the value-co-creation approach. The components of the proposed model consist of the customers’ evaluation of the destination promise in terms of transforming functional, intangible and social destination resources into tourists’ value-in-use. Furthermore, the positive relationship between visitors’ perception of the destination and value-for-money discloses the input of tourists’ own resources into the process of value-co-creation. Moreover, destination brand awareness affects the evaluation of the destination promise, which, in turn, determines tourists’ behavioural intentions towards the destination.By implementing web-based customer surveys and using a linear structural equation modelling approach, the proposed model is empirically validated for the leading Swedish mountain destination Åre. First, the model is repeatedly tested with data regarding the winter seasons 2009/10 and 2012/13. Second, the proposed CBDBE model has been operationalized and tested also for the summer season. Findings from face-to-face interviews conducted in Åre during summer 2012 uncovered the relationships between destination resources offered in Åre, tourists’ own resources and destination value-in-use and, thus, served as the empirical fundament for the development of a destination-specific scale to measure value-in-use. Subsequently, the proposed CBDBE model has been successfully tested with web-based survey data collected after the summer season 2012, both for the total sample and separately for the main a priori tourist segments, including hiking, mountain biking and village tourists.Results show the significant contribution of destination value-in-use defined as perceived benefits from a destination stay, which, in turn, strongly affect customers’ destination loyalty. In contrast, the relationship between value-for-money and destination loyalty is less strong and even non-significant for the two customer segments hiking and mountain biking tourists. Importantly, as part of the CBDBE model operationalization, the thesis highlights the need to better understand destination-specific consumption patterns across various tourism segments by destination managers.Therefore, results demonstrate that by monitoring unique destination and tourist-specific experience dimensions, destination management can influence and better manage both the value-in-use for customers and customer loyalty. Thus, the proposed CBDBE model provides destination managers with a tool, which enables evaluation and upgrade of destination marketing strategy and, finally, assist in discovering promising innovation potentials for highly experiential tourism products.
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| 2. |
- Chekalina, Tatiana, 1979-, et al.
(författare)
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Customer-based destination brand equity modelling : The role of destination resources, value-for money and value-in-use
- 2018
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Ingår i: Journal of Travel Research. - : Sage Publications. - 0047-2875 .- 1552-6763. ; 57:1, s. 31-51
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Tidskriftsartikel (refereegranskat)abstract
- This study contributes to the development of knowledge on transferring the concept of customer-based brand equity to a tourism destination context. Keller’s (2009) brand equity pyramid is utilized as the comparison framework to reveal similarities but also overlaps, differences and gaps on both the conceptual and measurement level of existing brand equity models for destinations. Particularly, the inner core of the model depicts the complex mechanisms of how destination resources transform into benefits for tourists overlooked by prior research. This study proposes a customer-based brand equity model for destinations, which consists of five dependent constructs, including awareness, loyalty, and three destination brand promise constructs constituting the inner core of the model, namely, destination resources, value-in-use and value-for-money. The model was repeatedly tested for the leading Swedish mountain destination Åre, by using a linear structural equation modelling approach. Findings confirm the path structure of the proposed model.
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| 3. |
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| 4. |
- Hoepken, Wolfram, et al.
(författare)
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Big data analytics for tourism destinations.
- 2018. - 4
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Ingår i: Encyclopedia of Information Science and Technology<em> </em>. - : IGI Global. ; , s. 349-363
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Bokkapitel (refereegranskat)abstract
- The objective of this chapter is to address the above deficiencies in tourism by presenting the concept of the tourism knowledge destination – a specific knowledge management architecture that supports value creation through enhanced supplier interaction and decision making. Information from heterogeneous data sources categorized into explicit feedback (e.g. tourist surveys, user ratings) and implicit information traces (navigation, transaction and tracking data) is extracted by applying semantic mapping, wrappers or text mining (Lau et al., 2005). Extracted data are stored in a central data warehouse enabling a destination-wide and all-stakeholder-encompassing data analysis approach. By using machine learning techniques interesting patterns are detected and knowledge is generated in the form of validated models (e.g. decision trees, neural networks, association rules, clustering models). These models, together with the underlying data (in the case of exploratory data analysis) are interactively visualized and made accessible to destination stakeholders.
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| 5. |
- Höpken, Wolfram, et al.
(författare)
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Google Trends data for analysing tourists’ online search behaviour and improving demand forecasting : The case of Åre, Sweden
- 2019
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Ingår i: Information Technology & Tourism. - : Springer. - 1098-3058 .- 1943-4294. ; 21:1, s. 45-62
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Tidskriftsartikel (refereegranskat)abstract
- Accurate forecasting of tourism demand is of utmost relevance for the success oftourism businesses. This paper presents a novel approach that extends autoregressiveforecasting models by considering travellers’ web search behaviour as additionalinput for predicting tourist arrivals. More precisely, the study presents a methodwith the capacity to identify relevant search terms and time lags (i.e. time differencebetween web search activities and tourist arrivals), and to aggregate these timeseries into an overall web search index with maximal forecasting power on tourismarrivals. The proposed approach enables a thorough analysis of temporal relationshipsbetween search terms and tourist arrivals, thus, identifying patterns that reflectonline planning behaviour of travellers before visiting a destination. The study isconducted at the leading Swedish mountain destination, Åre, using arrival data andGoogle web search data for the period 2005–2012. Findings demonstrate the abilityof the proposed approach to outperform traditional autoregressive approaches, byincreasing the predictive power in forecasting tourism demand.
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| 6. |
- Höpken, Wolfram, et al.
(författare)
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Search engine traffic as input for predicting tourist arrivals.
- 2018
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Ingår i: Information and Communication Technologies in Tourism 2018. - New York : Springer. - 9783319729220 - 9783319729237 ; , s. 381-393
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Konferensbidrag (refereegranskat)abstract
- Due to the perishable nature of tourism services and the limited capacity of tourism firms in serving customers, accurate forecasts of tourism demand are of utmost relevance for the success of tourism businesses. Nowadays, travellers extensively search the web to form expectations and to base their travel decision before visiting a destination. This study presents a novel approach that extends autoregressive forecasting models by considering travellers’ web search behaviour as additional input for predicting tourist arrivals. More precisely, the study presents a method with the capacity to identify relevant search terms and time lags (i.e. time difference between web search activities and corresponding tourist arrivals), and to aggregate these time series into an overall web search index with maximal effect on tourism arrivals. The study is conducted at the leading Swedish mountain destination, Åre, using arrival data and Google web search data for the period 2005-2012. Findings demonstrate the ability of the proposed approach to outperform traditional autoregressive approaches, thus, to increase the predictive power in forecasting tourism demand.
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| 7. |
- Kronenberg, Kai, et al.
(författare)
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A multi-period perspective on tourism’s economic contribution : A regional input-output analysis for Sweden
- 2018
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Ingår i: Tourism Review. - 1660-5373 .- 1759-8451. ; 73:1, s. 94-110
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: Previous studies on tourism input-output (IO) primarily focus on a single year’s snapshot or utilize outdated IO coefficients. The purpose of this paper is to analyze the multi-period development of regional tourism capacities and its influence on the magnitude of the industry’s regional economic contribution. The paper highlights the importance of applying up-to-date IO coefficients to avoid estimation bias typically found in previous studies on tourism’s economic contribution.Design/methodology/approach: For the period 2008-2014, national IO tables are regionalized to estimate direct and indirect economic effects for output, employment, income and other value-added effects. A comparison of Leontief inverse matrices is conducted to quantify estimation bias when using outdated models for analyzing tourism’s economic contribution.Findings: On the one hand, economic linkages strengthened, especially for labour-intensive sectors. On the other hand, sectoral recessions in 2012 and 2014 led to an economy-wide decline of indirect effects, although tourists’ consumption was still increasing. Finally, estimation bias observed after applying an outdated IO model is quantified by approximately US$4.1m output, 986 jobs full-time equivalents, US$24.8m income and US$14.8m other value-added effects.Research limitations/implications: Prevailing assumptions on IO modelling and regionalization techniques aim for more precise survey-based approaches and computable general equilibrium models to incorporate net changes in economic output. Results should be cross-validated by means of qualitative interviews with industry representatives.Practical implications: Additional costs for generating IO tables on an annual base clearly pay off when considering the improved accuracy of estimates on tourism’s economic contribution.Originality/value: This study shows that tourism IO studies should apply up-to-date IO models when estimating the industry’s economic contribution. It provides evidence that applying outdated models involve the risk of estimation biases, because annual changes of multipliers substantially influence the magnitude of effects.
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| 8. |
- Kronenberg, Kai
(författare)
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A quantity-quality framework for measuring the regional socio-economic impact of tourism : The case of Jämtland Härjedalen
- 2019
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Measuring the economic effects of tourism has always been a high priority for private and public actors in the regional economy (Stabler et al 2009). These estimates provide insights about the generation of sales, jobs, and income associated with tourism, but also support industry officials in the regional development agenda. Measuring tourism’s economic impact in a region typically involves economic impact models that capture both primary and secondary effects (Comerio and Strozzi 2019). However, results gained from these models are limited in regards to highly aggregated and growth-oriented indicators on the macro-level.These economic impact models ‘fulfil’ their purpose in incorporating the assumptions of mainstream economics and in focusing on macro-level indicators related to economic growth (Elsner 2017). That involves the risk that important socio-economic aspects, such as the distribution of income, are less considered in regional tourism development agendas. Even so-called ‘advanced’ models neglect distributional dimensions in estimating the impact of tourism (Lee 2009). Accordingly, a growing body of literature starts criticizing mainstream economics’ modelling assumptions and its narrow view on economic growth (Söderbaum 2017). Instead, economic analyses should put more focus multi-dimensional perspectives, including the institutional (i.e. meso-level) perspective in addition to the traditional macro- and micro view (Dopfer et al. 2004). Furthermore, various forms of inequalities are identified to typically hamper regional development from a socio-economic point of view (Moulaert and Nussbaumer 2005a).Against this background, the aim of this thesis is to propose a framework that extends traditional economic impact approaches and allows the measurement of tourism impact from a broader socio-economic perspective. The approach in this thesis comprises a macro as well as a meso level analysis and utilizes a mixed-method approach (Dopfer et al. 2004; Khoo-Lattimore et al. 2017). More concretely, the traditional economic impact methodology is further developed in order to estimate disaggregated employment and income effects for specific occupations, and to estimate the income distribution across occupations in major tourism sectors.This analysis is conducted for the county of Jämtland and comprises the period + time (Daniels et al. 2004). A series of interviews with major regional industry- and policy representatives complements the impact analysis from the meso-level perspective. By doing so, the institutional perspectives helped identifying potential reasons for variations in occupation and income developments in tourism.Findings show that the traditional way of analysing tourism’s impacts does not only provide the full picture of the impacts, but also even gives potentially misleading information. While, in general, the tourism industry benefits from annually growing arrival numbers in terms of sales, the income level of the tourism workforce remains among the lowest in the entire regional economy. In addition, the income inequality across occupations in the main tourism sector accommodation & food is increasing, indicating a negative trend in the industry. This can be partly attributed to decreasing union membership rates, short-term career perspectives, and increasing shares of occupations without requirements for higher education. Like in other branches, the role of education in the tourism industry is particularly important to overcome these trends.This study shows that extending traditional ways of analysing the economic impact of tourism by incorporating additional socio-economic dimensions contributes to a better understanding the socio-economic sustainability of the regional tourism industry. By putting the focus away from pure growth-driven indicators, this approach proposes an alternative way for measuring tourism’s impacts, which can, hopefully, be implemented and institutionalized in the future.
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| 9. |
- Kronenberg, Kai, et al.
(författare)
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Socio-economic effects of tourism : An occupation-based modelling approach from Sweden
- 2019
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Ingår i: BOOK OF ABSTRACTS.
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Konferensbidrag (refereegranskat)abstract
- Planners and developers in regions showing touristic activities are typically interested in measuring the economic impact of tourism (Dwyer et al. 2004; Klijs et al. 2012; Kim & Kim 2015). However, even ‘advanced’ economic impact models neglect major societal dimensions, such as income equality or the type and quality of occupations in the various tourism-related sectors (Mazumder et al. 2012; Kronenberg et al. 2018). While neo-classic economics is still representing the dominant paradigm (Dobusch & Kapeller 2009), economic impact models ‘fulfill’ their purpose in incorporating the assumptions of mainstream economics and in focusing on macro-level indicators related to economic growth (Elsner 2017). However, a growing body of literature starts criticizing mainstream economics’ modelling assumptions and its narrow view of ‘monetary reductionism’, thus hampering advanced approaches able to consider socio-economic effects (Söderbaum 2017). In their seminal paper on the Social Region, Moulaert & Nussbaumer (2005) argue that the focus of regional development theories should turn away from market competition towards concepts that effectively incorporate dimensions of a region’s social, political, cultural and community development. By doing so, the authors highlight various forms of inequality that typically impede the path towards the Social Region (ibid, 2005b).Behind this background, the aim of this study is to propose a new approach that allows the measurement of tourism impact from a broader socio-economic perspective. In order to overcome the predominant growth focus, the study of tourism’s socio-economic impact comprises a macro as well as a meso level analysis and utilizes a mixed-method approach (Dopfer et al. 2004). More concretely, the macro level analysis of tourism’s socio-economic impact, first, includes the regionalization of the national Input-Output model to estimate primary and secondary employment and income effects for the Swedish region of Jämtland (Flegg & Tohmo 2011). In contrast to typical economic impact studies in tourism (Mazumder et al. 2012) and in order to estimate employment and income effects for various occupational domains individually and within various tourism-related sub-sectors, we extend the analysis by applying the occupation-based modelling (OBM) approach (Daniels et al. 2004). This approach allows estimating income inequalities and its variations over time (in our case from 2008 to 2015) for major tourism sectors, expressed by Gini coefficients and Lorenz curves, respectively (Lee & Kang 1998). Findings highlight that the incomes in the accommodation & food sector fall below the regional average - the lowest among all tourism-related industries. Interestingly, compared to others sectors (e.g. recreation & entertainment, retail), income inequality within this sector is relatively low (i.e. Gini coefficient = 0.15). However, growing coefficients are pointing at a negative trend over time: Between 2008 and 2013, the income of the top 15% earning occupations increased by 8%, while income of the bottom 15% earning occupations grew only by 1%. The latter occupations comprise seasonal workers, cleaning personal and kitchen assistants. We further analyze and critically discuss occupational developments and related income distributions (i.e. Gini coefficient trends) for major tourism-related sub-sectors of the Swedish region of Jämtland.The second part of the analysis relates to the meso-level (Dopfer et al. 2004). A series of qualitative interviews with major regional industry and policy representatives (e.g. labor unions, hotel association, etc.) helped identifying potential reasons for variations in occupation and income developments in tourism. Findings show that large parts of low income workers stay in their job for only a short time, implying that newly employed workers are continuously hired at low (i.e. entry-level) wages. Furthermore, because of their expected short-term employment, tourism workers consider union memberships as unnecessary (Kjellberg 2017). Interestingly, the interviews helped identify also promising career opportunities showing steadily increasing income levels. These jobs, however, require higher educational profiles. Like in other branches, only higher education levels seem to overcome the low-income situation in tourism. To conclude, the interviewed industry-representatives perceived the proposed approach of occupation-based modelling and its related findings from measuring income inequalities particularly well. This gives reason for hope that in tourism regions new methods of socio-economic impact analysis will be implemented and institutionalized in the future.
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