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Tourism reconfigures the metropolitan dynamics and the patterns of use of the urban systems. The seasonal nature of tourism produces an impact on the urban hierarchies, since it affects the labor, residential, and recreational markets. As a result, people move to and in the destination and it challenges the supply of sustainable modes of transport such as public transport. This research is set within the context of three demanding challenges that tourist destinations need to face-up: to increase environmental sustainability, to enhance destination competitiveness, and finally to assure quality and comfort of public transport services for the local resident population. Camp de Tarragona region, where Costa Daurada (one of the most important Spanish tourist brands) is located, is analyzed to illustrate how different data sources can aid to confront the aforementioned challenges. Given that seasonality is a dynamic phenomenon, suitable data should be flexible in terms of its time framework. To this end data from smart travel cards provided by the consortium that manages the public transport system in the region has been analyzed. Data unveiled the impact of seasonality on the evolution of demand throughout the year, the type of transport tickets used, or changes occurred in the geographical distribution of the mobility Alternative data sources such as surveys and passive mobile positioning data have also been examined, and their pros and cons have been addressed.

Preedip Balaji B holds a masters degree in library and information science from Bishop Heber College, Bharathidasan University, Trichy in 2007. He worked as information professional in different positions at Indian School of Business and IKP Knowledge Park, Hyderabad in Andhra Pradesh, South India. Having received his Junior Research Fellow award in 2009 from the University Grants Commission, New Delhi, currently, he is pursuing doctoral studies at Documentation Research and Training Centre, Indian Statistical Institute, Bangalore. His research interests are in natural language processing, faceted analysis and classification. He has to his credit 10 national and international publications, published in journals, workshop manual and conference proceedings.

The proceedings of the 17 editions of the conference of the Spanish Association of Scientific Experts in Tourism constitute a valuable archival resource within the research on Spanish tourism. But so far their contents have not been analyzed. The aim of this chapter is to examine the research that has been presented at its conference by means of a bibliometric analysis of the proceedings of 17 editions. The study focuses on the origin of the research (countries, regions, institutions, and authors), as well as its characteristics in terms of themes dealt with, geographical areas researched, methodologies, disciplinary areas, and attitudes toward tourism. Implications for the evolution of the research are discussed in terms of knowledge contributions and the shaping of major tourism research traditions.

Neural networks, which provide the basis for deep learning, are a class of machine learning methods that are being applied to a diverse array of fields in business, health, technology, and research. In this chapter, we survey some of the key features of deep neural networks and aspects of their design and architecture. We give an overview of some of the different kinds of networks and their applications and highlight how these architectures are used for business applications such as recommender systems. We also provide a summary of some of the considerations needed for using neural network models and future directions in the field.

The growth of social media and the sharing economy is generating abundant unstructured image and video data. Computer vision techniques can derive rich insights from unstructured data and can inform recommendations for increasing profits and consumer utility – if only the model outputs are interpretable enough to earn the trust of consumers and buy-in from companies. To build a foundation for understanding the importance of model interpretation in image analytics, the first section of this article reviews the existing work along three dimensions: the data type (image data vs. video data), model structure (feature-level vs. pixel-level), and primary application (to increase company profits vs. to maximize consumer utility). The second section discusses how the “black box” of pixel-level models leads to legal and ethical problems, but interpretability can be improved with eXplainable Artificial Intelligence (XAI) methods. We classify and review XAI methods based on transparency, the scope of interpretability (global vs. local), and model specificity (model-specific vs. model-agnostic); in marketing research, transparent, local, and model-agnostic methods are most common. The third section proposes three promising future research directions related to model interpretability: the economic value of augmented reality in 3D product tracking and visualization, field experiments to compare human judgments with the outputs of machine vision systems, and XAI methods to test strategies for mitigating algorithmic bias.

Pressing sustainability issues face the 21st century, as identified by the Millennium Development Goals and its post initiatives, and ethical principles related to fairness, equity, and justice are increasingly important to address climate change and resource scarcities. Yet, such ethical dimensions remain surprisingly little addressed in the tourism literature. Ecofeminist critique offers insights into this gap, identifying historical antecedents in patriarchal, Enlightenment-driven discourses of science where positivistic approaches facilitate the control and use of nature and women. This chapter draws from this critique to propose a preliminary, justice-oriented framework to resituate sustainable tourism within an embodied paradigm that covers intangibles such as emotions, feelings, and an ethic of care.

This chapter explores the potential for and value of imagining a humanist paradigm for tourism studies. It explores how the idea of a “paradigm” in tourism can be conceptualized, arguing that dominant thoughtlines in other fields regarding the meaning of a paradigm are not sufficient for making sense of this idea in the context of tourism studies. The chapter introduces humanism as a philosophical position in the academy and as a lived cultural practice, explores examples of extant work in tourism studies that might be seen to provide the seeds of a humanist paradigm, and offers reflections on the value of imagining such a paradigm for our field.

In the Western thought tradition, the tourist has not been a subject worthy of intellectual musings and philosophical deliberations. Indeed, the tourist has been portrayed in primarily derisive ways. Nietzsche’s remark, “Tourists—they climb mountains like animals, stupid and perspiring, no one has told them that there are beautiful views on the way,” epitomizes the dominant attitude. Why does the figure of the tourist elicit such negative reactions? Do the sentiments perhaps imply something else, or is the tourist a doppelgänger, not anomalous or marginal but normative—a paradigmatic figure? If so, then what can be said of the poetics and politics of the tourist conceptualized as a paradigmatic subject?

The purpose of this chapter is to propose a theory which may lead to a holistic description of the mechanism of touristic phenomena. In so doing, the central discussion is to provide descriptive answers to basic questions. It will not be a sociological or anthropological discourse. Instead, it will use perspectives from environmental psychology, genetics, and a theory of information energy in elementary particle physics. The study of tourism, though it is not a distinct disciplinary field, must provide a grand theory. In this chapter, the discussions mainly focus on the concept of tourist to provide several ideas to amend its definition, which may directly correspond to an overall view of touristic phenomena.