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The purpose of this paper is to perform an analysis of how pets in general and dogs in particular condition the planning and realisation of people’s trips. Similarly, the motivations that lead families to travel with their pets in Spain are analysed.

The methodology used in this research consisted of carrying out fieldwork based on surveys of 1,696 dog owners in Spain. The data analysis was carried out using a Partial Least Squares methodology (PLS-SEM) to test the relationship of the families with their pets, the motivations they have for travelling with their pets and the assessment of the destination by both the family and the pet itself.

The main results of this research focus on analysing how and when a family plans a trip with their pet, except for their second home, there are several motivations for both families themselves and their pets, which condition this trip and that must be considered by tourist destinations. Similarly, it is also concluded that the motivations are closely related to the attachment that the family has to the pet.

The originality of this research focuses on including the relationship of the family with their dog and the adequacy of the destination to the needs of their pet as motivation to make a certain trip or choose a certain destination.

Tourism in Coimbra today is influenced by the fact that the Univer(s)city was distinguished as a World Heritage Site in 2013. The number of visits has grown very significantly in recent years, but the diversification of the tourist offer is still weak and unable to take advantage of existing resources. This paper aims to present genealogy tourism as an alternative urban cultural tourism in Coimbra.

Methodology involved mapping the Jewish culture elements in the city of Coimbra, and a route was outlined and proposed.

Genealogy tourism resources are identified in the historic centre of the city. These alternative spaces need urban rehabilitation and (re)functionalisation, which allowed the authors to rethink tourism in Coimbra. They are the motivation to visit for all urban cultural tourists, especially Israelis/Jews, and provide contact with places where the experiences of ancestors combine with the history and memory of places, with recent discoveries and the elements of Jewish culture in the city.

It is concluded that the quantity, diversity, authenticity and singularity of the heritage resources that bear witness to the Jewish presence in Coimbra are sufficient assets to create a route, to enrich the tourist experience in the city and to include the destination in the Sephardic routes.

The purpose of this study was to uncover representative emergent areas and to examine the research area of marketing, tourism and big data (BD) to assess how these thematic areas have developed over a 27-year time period from 1996 to 2022. This study analyzed 1,152 studies to identify the principal thematic areas and emergent topics, principal theories used, predominant forms of analysis and the most productive authors in terms of research.

The articles for this research were all selected from the Web of Science database. A systematic and quantitative literature review was performed. This study used SciMAT software to extract indicators. Specifically, this study analyzed productivity and produced a science map.

The findings suggest that interest in this area has increased gradually. The outputs also reveal the innovative effort of industry in new technologies for developing models for tourism marketing. Ten research areas were identified: “destination marketing,” “mobility patterns,” “co-creation,” “gastronomy,” “sustainability,” “tourist behavior,” “market segmentation,” “artificial neural networks,” “pricing” and “tourist satisfaction.”

This work is unique in proposing an agenda for future research into tourism marketing research with new technologies such as BD and artificial intelligence techniques. In addition, the results presented here fill the current gap in the research since while there have been literature reviews covering tourism with BD or marketing, these areas have not been studied as a whole.

El objetivo de esta investigación fue descubrir nichos representativos de áreas emergentes y examinar el área de Marketing, Turismo y Big Data, evaluando cómo han evolucionado estas áreas temáticas durante un período de 27 años desde 1996–2022. Analizamos 1.152 investigaciones para identificar las principales áreas temáticas y temas emergentes, las principales teorías utilizadas, las formas de análisis predominantes y los autores más productivos en términos de investigación.

Todos los artículos para esta investigación fueron seleccionados de la base de datos Web of Science. Realizamos una revisión sistemática y cuantitativa de la literatura. Utilizamos el software SciMAT para extraer indicadores. Específicamente, analizamos la productividad y elaboramos un mapeo científico.

Los hallazgos sugieren que el interés en esta área ha aumentado gradualmente. Los resultados también revelan el esfuerzo innovador de la industria en nuevas tecnologías para desarrollar modelos de marketing turístico. Se identificaron diez áreas de investigación (“marketing de destinos”, “patrones de movilidad”, “co-creación”, “gastronomía”, “sostenibilidad”, “comportamiento turístico”, “segmentación de mercado”, “redes neuronales artificiales”, “precios”, y “satisfacción del turista”).

Este trabajo es único al proponer una agenda para futuras investigaciones en investigación de Marketing Turístico con nuevas tecnologías como Big Data y técnicas de Inteligencia Artificial. Además, los resultados presentados aquí llenan el vacío actual en la investigación ya que si bien se han realizado revisiones de literatura que cubren Turismo con Big Data o Marketing, estas áreas no se han estudiado como un conjunto.

这一特定研究领域的目标是发现具有代表性的新兴领域, 并考察市场营销、旅游和大数据研究领域, 以评估这些主题领域在1996年至2022年的27年间是如何发展的。我们分析了1152项研究, 以确定主要专题领域和新兴主题、使用的主要理论、主要的分析形式以及在研究方面最有成效的作者。

本研究的文章都是从Web of Science数据库中选出的。我们进行了系统化的定量文献审查, 并使用SciMAT软件来提取指标。具体来说, 我们分析了生产力并制作了一个科学研究地图。

研究结果表明, 人们对这一领域的兴趣已经逐渐增加。本文也揭示了工业界在开发旅游营销模式的新技术方面的创新努力。研究确定了十个研究领域：“目的地营销”、“流动模式”、“共同创造”、“美食”、“可持续性”、“游客行为”、“市场细分”、“人工神经网络”、“定价 “和游客满意度”。

这项研究的独特之处在于提出了未来利用大数据和人工智能技术等新技术进行旅游营销研究的议程。此外, 本文的结果填补了目前的研究空白, 因为虽然有文献综述涉及旅游与大数据或市场营销, 但这些领域还没有被作为一个整体来研究。