Environmental attitudes (environmental knowledge, awareness, and concern) are important drivers of pro-environmental behaviour for key destination stakeholder groups, including tourists, tourism ...business staff and residents. However, limited attention has been given to how individual attitudes within each role collectively contribute to the environmental sustainability of tourism destinations.The goal of the study is to fill this gap by conceptually and empirically linking the micro- and macro-levels of analysis, respectively focused on individuals and the destination. First, the concept of Destination Environmental Orientation (DEO) is proposed to indicate the collective attitude of a touristic place or destination towards the environment having micro-foundations in individuals' cognition, evaluation and affect. Then, focusing on local hotels' staff as a key destination stakeholder category, the study shows the methodological potential of Symbolic Data Analysis (SDA) to measure DEO based on underlying individual-level data about environmental knowledge, awareness, and concern. Survey-based data are collected among employees in thirty-three hotels located in eleven tourism municipalities of Naples, a province in the Campania region (Italy). The research identifies three groups of tourism municipalities with significant differences in the level of environmental orientation. The findings suggest that these groups exhibit different patterns of functioning and three models are identified based on context-related factors, i.e., the level of tourism developement, the reliance of tourism areas on natural resources, and geograhical and functional proximity among tourism municipalities: the "Mature tourism destination" model, the "Island tourism destination" model, and the "Strategically positioned touristic place" model. The implications to sustainable tourism theory and practice are discussed.
Many of the current Quality of Service (QoS) based web service selection systems assume that users will formulate QoS queries accurately. However, this may not always be the case. It would be helpful ...if users could browse through the QoS data of the service repository before they start the searching process. In this way, they could know what the actual QoS value distributions are, so that they could put down reasonable numbers in their QoS queries. The browsing process performed on QoS queries, on the other hand, could help service providers understand the actual QoS demands from users. In this paper, we propose to use the Scatter/Gather model—a well-known browsing model for large document collections, to implement QoS browsing. We modified the original model to make it fit QoS data and implemented a few variations of the model. We tested and compared performance on both synthetic and real QoS datasets, mainly focusing on the ability to handle real time interaction with users while balancing efficiency and accuracy.
► QoS browsing is important for understanding QoS value distribution of web services. ► Scatter/Gather model can be used to implement QoS browsing. ► Symbolic clustering algorithm is the main component of our QoS browsing system. ► Improved LAIR2 implementation of Scatter/Gather model achieves both high accuracy and efficiency.
Clustering of symbolic data, using different validity indices, is proposed for determining the optimal number of meaningful clusters. Symbolic objects include linguistic, nominal, boolean, and ...interval-type of features, along with quantitative attributes. Clustering in this domain involves the use of symbolic dissimilarity between the objects. The novelty of the method lies in transforming the different clustering validity indices, like Normalized Modified Hubert’s statistic, Davies–Bouldin index and Dunn’s index, from the quantitative domain to the symbolic framework. The effectiveness of symbolic clustering is demonstrated on several real life benchmark data sets.
A novel ISODATA clustering procedure for symbolic objects is presented using distributed genetic algorithms where in a structured organisation in the distribution of the population is introduced and ...selection and mating are made within locally distributed subgroups of individuals rather than the whole population.
A new approach to clustering of symbolic objects which makes use of both similarity and dissimilarity measures is proposed. The proposed modified new similarity and dissimilarity measures will take ...into consideration the position, span and content of symbolic objects. The similarity and dissimilarity measures used are of new type. The advantages of the proposed modified measures are presented. A divisive clustering algorithm which makes use of both similarity and dissimilarity is proposed. The results obtained by the proposed method is compared with other methods.
A hierarchical, agglomerative clustering methodology is presented in which composite symbolic objects are formed using a cartesian join operator whenever symbolic objects are selected for ...agglomeration based on both similarity and dissimilarity.
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