Tourism: A Knowledge-Based Activity

Abstract

Contemporary production and consumption systems increasingly integrate immaterial aspects related to knowledge or cultural values and symbols into products and services, often through processes of co-creation, leading to a personalization and adaptation of supply to the needs and motivations of consumers. Tourism plays a prominent role within this emergent creative economy, and the focus on the immaterial aspects of the experience tends to prevail over the material aspects of the destinations, while information and communication technologies appear as crucial tools for the match between differentiation of destinations and market segmentation. The intense development observed in these technologies during the last few decades contributes for the enhancement of co-created tourism experiences while opening new opportunities for the reinforcement of linkages between tourism and other creative activities, along with the potential reinforcement of regional innovation networks, potentially involving a large number of small and decentralized tourism providers. On the other hand, agglomeration effects related to recent urban development contribute for the concentration of creative activities in cities, along with the emergence of a varied supply of flexible and creative tourism products and services. This fast growth of tourism in contemporary cities also raises new challenges for urban planning, not only related to the shared use of spaces, facilities, and infrastructures but also regarding the impacts of tourism on local markets and especially on the housing markets in large-scale urban tourism destinations.

Case Study 4.1: Information and Satisfaction in an Ecotourism Destination

Neuts B, Romão J, Nijkamp P, Shikida A (2014) A quality assessment of tourist information: the case of nautical tourism at Shiretoko Peninsula. Almatourism 9:24–34

Case Study 4.2: E-Services in Urban Tourism

Romão J, Neuts B, Nijkamp P, Leeuwen ES van (2015) Tourist Loyalty and e-Services: A Comparison of Behavioral Impacts in Leipzig and Amsterdam. Journal of Urban Technology 22(2):85–101

Case Study 4.3: Tourism, Innovation, and Regional Specialization

Romão J, Nijkamp P (2017) A spatial econometric analysis of impacts of innovation, productivity and agglomeration on tourism competitiveness. Current Issues in Tourism. DOI: 10.1080/13683500.2017.1366434

Case Study 4.4: Urban Attractiveness for Tourists and Residents

Romão J, Kourtit K, Neuts B, Nijkamp P (2017) The Smart City as a Common Place for Tourists and Residents: a Structural Analysis on the Determinants of Urban Attractiveness. Cities. DOI: 10.1016/j.cities.2017.11.007

Appendices

Case Study 4.1: Information and Satisfaction in an Ecotourism Destination

Neuts B, Romão J, Nijkamp P, Shikida A (2014) A quality assessment of tourist information: the case of nautical tourism at Shiretoko Peninsula. Almatourism 9:24–34

As a consequence of the rising importance of interactive ICT tools in tourism, communication between service providers and tourists has gained renewed attention within tourism studies and entrepreneurial practices. By using a structural equations model, this work analyzes the impacts of using different information sources when booking a cruise tour in an ecotourism destination (the natural World Heritage Site of Shiretoko, in Hokkaido, Japan). Information appears as a crucial element in this type of destination, as the activities largely depend on a set of factors not controllable by tourism companies (like climate conditions influencing the visibility of natural assets, or the behavior of animals expected to observed).

Shiretoko Peninsula was classified by UNESCO as a World Heritage Site in 2005, constituting a complex ecosystem due to its biodiversity (a large variety of wildlife can be seen, including whales, dolphins, sea lions, bears, eagles, owls, and a varied set of birds), along with particular geological characteristics. Different types of boat trips (large boats, small boats, and kayaks, with options for different routes) are among the attractions offered to visitors, and the information used for this study (1170 questionnaires) was collected during 2 consecutive years among the users of these cruises, including information about the different phases of the experience (before, during, and after the trip).

It was observed that the Internet and guidebooks were the main sources of information (47.0%); recommendations from friends or family (11.1%) or local sources like hotels and tourist information centers or shops (13.4%) were much less representative. Almost one third of the visitors (33.2%) did not choose a specific cruise plan, once it was already included in the travel package acquired for the trip. A large boat (travelling relatively far from the coastline) was used by 49.4% of the visitors, while small boats (32.3%) and kayaks (18.3%) – whose routes are closer to the coast – were used by much less tourists. Regarding the routes, Cape Shiretoko (50.1%) was the most frequent option, while Kamuiwakka Fall (21.7%) and Rusha Bay (8.9%) also registered high number of visitors, when compared with the remaining alternatives.

Regarding the motivations of the visitors, observing the landscape (87.9%) or the wildlife (65.5%) was clearly more important than the boat experience itself (20%). Nevertheless, it was perceived that, after the trip, only 39.3% of the visitors were satisfied with wildlife observation, suggesting a reasonably high level of dissatisfaction (once 65.5% were motivated for this aspect). In fact, not seeing the elements (landscape or wildlife) that were expected was indicated as a reason for dissatisfaction by 23.0% of the visitors. Anyway, very high levels of loyalty were observed (95.7% of the travellers would recommend the destination, and 95.1% expressed their intention to return), probably because it was perceived that the elements of dissatisfaction were not under the control of the service providers.

Despite these high levels of loyalty, the analysis revealed a mismatch between the expectations of the visitors based on the information they had collected before and the satisfaction with the concrete experience. Thus, a next step in the analysis was to identify whether different sources of information could have different impacts of the satisfaction obtained. In fact, the results obtained have shown that lower levels of satisfaction were related to the utilization of the Internet and guidebooks as main sources of information, while local sources (tourist offices, hotels, and shops) did not seem to have that negative effect. This can also be related with the timing of collecting information: as the visibility largely depends on weather conditions, it is possible that information collected in the day of the trip (local sources) can be more reliable regarding the realism of the expectations.

When observing in detail the expectations and satisfaction obtained for each combination of route and type of boat (described in detail in the article), it was also possible to identify that the mismatch between expectations and motivations shows high variations. This suggests that the information provided is too much general, not establishing a clear distinction between what can be seen and enjoyed in each type of route and each type of boat. Thus, the analysis stresses the importance of providing more accurate information about the concrete experiences that can be achieved for each of services provided, instead of offering a general perspective of the site. This lack of precise information about what to expect in each route, along with the consequences of choosing different types of boats, has clearly led to some dissatisfaction that could have been avoided by offering more accurate information.

Case Study 4.2: E-Services in Urban Tourism

Romão J, Leeuwen ES van, Neuts B, Nijkamp P (2015) Tourist loyalty and urban e-services: a comparison of behavioural impacts in Leipzig and Amsterdam. Journal of Urban Technology 22(2):85–101

Recent developments in ICT deeply transformed the tourism activities, and information became a critical tool for destination attractiveness while increasing the importance of using of e-services. Information influences the expectations of the visitors and their motivations, satisfaction, and loyalty to a destination. If the behavior of tourists during the travel can be seen as a measure of the performance of a destination, the implications on satisfaction and loyalty allow to infer about its future performance (based on the intentions to revisit or to recommend the place). By using structural models (SEM), this work analyzes the role of information for this double process of performance evaluation in two urban destinations (Leipzig, in Germany, and Amsterdam, in the Netherlands). The results emphasize the heterogeneity of tourism destinations, once different results were obtained in the two cities for most of the relations under analysis.

The first model (future performance) analyzes the characteristics, motivations, perceptions, preferences, and behaviors of tourists, identifying different segments, the most relevant motives for the visit, the main factors of satisfaction, and their implications on the loyalty to the destination. The second model (current performance) focuses on the relation between the characteristics of tourists, the type of e-services used, and the expenditures in the destination.

In the first model, it was observed that satisfaction with the immaterial assets of the cities had positive implications on the loyalty of the tourists in both destinations. The economic impact of loyalty relates to the “free of charge” and reliable promotion of the destination. Nevertheless, important differences were observed when looking at the type of loyal tourists: in Amsterdam, loyalty was higher for tourists with high education levels and low-income levels (probably related to university students visiting the city), while in Leipzig loyalty was mostly identified for business travellers with high income. For the second model (analyzing the relation between the type of e-services and the expenditures at the destination), it was observed that higher expenditures in Amsterdam were made by users of virtual tours, while in Leipzig they are linked to the utilization of personalized information; probably as a tool to find affordable services, e-forums were used by tourists with lower expenditures in both cities.

The study emphasizes the heterogeneity of tourism destinations, as very few general tendencies can be identified. Both the specific assets and services provided in each destination and the particular characteristics of the visitors they attracted to each of them have different implications on the touristic performance of the city, both in terms of the current performance (expenditures during the visit) and the future performance (intention to revisit or to recommend). Nevertheless, the heterogeneity of the behaviors of tourists regarding their preferences for the utilization of diverse e-services reveals the importance of developing specific information contents and using different channels in order to address the diverse market segments visiting the destination.

Case Study 4.3: Tourism, Innovation, and Regional Specialization

Romão J, Nijkamp P (2017) A spatial econometric analysis of impacts of innovation, productivity and agglomeration on tourism competitiveness. Current Issues in Tourism. DOI: https://doi.org/10.1080/13683500.2017.1366434

This study examines whether and how the development of regional systems of innovation influences regional tourism competitiveness (measured by the gross value added by the tourism sector), including a geographical representation of the data, an exploratory analysis based on local indicators of spatial association and an econometric spatial panel data model, providing a quantified analysis of the impacts of each explanatory variable on regional tourism performance, along with the identification of spatial effects. The study covers a large number (237) of NUTS 2 regions in the European Union, which are relevant for the purposes of the study, as they generally have a specific institutional framework for regional and tourism policies while also exhibiting some territorial coherence (although, in a strict sense, they cannot exactly be considered a tourism destination, once normally, there is more than one destination in each NUTS 2 region).

The determinants of the regional tourism performance considered reflect the territorial capital of each region, and they relate to the regional specialization in tourism (share of tourism in regional employment and gross value added), tourism demand (nights spent at regional tourism accommodation establishments), production factors (human capital, measured by the level of education of the work force, and physical capital, measured by the gross fixed capital formation in the tourism sector), and immaterial regional resources (productivity and regional investment in research and development).

The results of the econometric model revealed the expected positive impacts on regional tourism performance of tourism demand, investment, and productivity in the tourism sector, along with the qualifications of the regional work force and the regional investment in research and development. Nevertheless, when the impacts of specialization in tourism are considered, a positive impact is found when this is measured through the share of the gross value added in tourism in the regional economy, but a negative impact is observed when the measure is the share of employment in tourism. This explains the lower levels of productivity where tourism services are more labor-intensive, suggesting that tourism supply in those regions is based on products with low value added.

In fact, the exploratory spatial analysis performed had revealed a large number of Southern European regions with high levels of specialization in tourism and relatively low achievements in terms of value added, suggesting high pressure on local resources, with low impact on the regional economy. Adequate policies oriented to increase the value added of these services (through the diversification of local supply, integrating other types of endogenous resources into the tourism services, and developing a strategy of product diversification) are proposed.

These problems are also reflected in the distribution of the spatial clusters relating tourism performance to education, innovation, and productivity. Despite the overall positive correlation between these factors and tourism performance observed in the econometric model, the exploratory analysis revealed the existence of a very limited number of clusters of regions where high levels of tourism performance relate to high levels observed in any of those factors. On the contrary, a large number of regions show low values for the gross value added in tourism while revealing high scores for productivity, education, and R&D. In fact, the results reveal a modest importance of research and development activities in regions where tourism specialization is high, suggesting a low contribution of the knowledge sector for the regional economy, despite the potential of tourism services to integrate knowledge and new technologies.

This result clearly shows the importance of a balanced and diversified regional economic structure, in which tourism can develop close and more intense links to other (related) sectors, along with the integration of knowledge into innovation processes, as proposed by the recent conceptual developments related to the smart tourism approach or to the policy guidelines related to the smart specialization strategies.

Case Study 4.4: Urban Attractiveness for Tourists and Residents

Romão J, Kourtit K, Neuts B, Nijkamp P (2017) The Smart City as a Common Place for Tourists and Residents: a Structural Analysis on the Determinants of Urban Attractiveness. Cities. DOI: https://doi.org/10.1016/j.cities.2017.11.007

This article analyzes the determinants of urban attractiveness, both for the resident population and international tourism demand, in 40 global cities, by using a latent growth curve model. The impacts of a diverse set of drivers of urban value creation and attractiveness are taken into account, acknowledging that the dynamics and growth processes related to these urban functions may have different impacts on different types of stakeholders (in this case, resident population and international visitors), potentially leading to the emergence of conflicts between them.

The conceptual framework of the study adopts the concept of “Sustainable Smart Cities,” linking the idea of sustainability (to assess social and environmental questions), with the idea of “smartness” (or creativity), reflecting the role of knowledge, technologies, and innovation within the economic context of modern cities. By using an extensive dataset (including 70 indicators), the model assesses the impacts of factors related to both contemporary smart economies (general economic conditions, cultural interaction, and research and development) and urban sustainability (livability, accessibility, and environmental conditions), offering a comprehensive analysis of the determinants of urban attractiveness.

The results obtained suggest that cultural dynamics appears to be a major determinant for attracting new residents while supporting a strong international tourism industry. On the other hand, economic strength (in terms of the absolute growth of GDP) appears to contribute for the attractiveness of residents, while the dynamics observed in research and development activities influences the quality of their employment. The social aspects of sustainability (framed under the concept of livability) and the urban environment seem to exert high impacts on urban attractiveness both for residents and tourists, while accessibility appears mostly relevant for visitors. The results also suggest a difficult relation between livability and environment and the growth of population and volume of visitors. A detailed analysis of the results suggests that cities with a dynamic economy offer opportunities for current and new residents, contributing to increase the city size and its growth rates, without relevant impacts on tourism demand. Moreover, the dynamics in research and development environment appears as benefiting the resident population, but the model shows different relations regarding population growth rates and absolute size.

A strong effect of the aspects related to cultural interaction was also confirmed, especially in their implications for the attractiveness of visitors, as the cities with high scores on this item are also attractive destinations with above-average international tourism demand. Moreover, it is also clear that residents benefit from attraction factors such as shopping and dining opportunities, world heritage sites, museums, theatres, or concert halls, which leads to the identification of a positive effect of cultural interaction on population growth.

Finally, it was noteworthy that problems of livability can be identified in populous urban centers with strong tourism demand. Livability appears as strongly associated with a favorable environment for residents (including positive aspects related to creative industries, working environment, and living conditions). As it was observed, the cities with the highest score on livability were Paris, Vienna, Vancouver, Berlin, Barcelona, and Amsterdam, which are perceived as having a competitive attractiveness advantage. However, the results of the models also reveal a negative relationship between population growth and livability, which may create a vicious circle: livability is an important residential attractor, but when facing an excessive growth, some negative consequences can emerge, like those related to house rents or price levels. Regarding the aspects related to tourism dynamics, it was observed that higher scores on livability were related to a below-average total tourism demand, coexisting with an accelerated growth over the 5-year period. This suggests that urban functionalities can be attractive for residents and visitors while potentially causing conflicts in the long run.