Purpose: Previous research into online reviews in the hospitality industry has focused mainly on big companies; thus, it is not yet known whether its findings apply also to small and medium enterprises (SMEs), the most abundant in the sector. Focusing on online reviews in the hospitality sector, this study aims to analyse whether firm size moderates the relationship between online review valence and customer responses.
Design/methodology/approach: This study uses a 2 (positive vs negative online review) × 2 (SME vs big company) experimental research design conducted in two hospitality settings, hotels and restaurants.
Findings: The impact of online reviews on customer responses is less intense for smaller hospitality companies.
Originality/value: This study incorporates firm size as a moderator of the relationship between online review valence and customer responses in two hospitality settings, restaurants and hotels.

The use of artificial intelligence‐based devices, such as smart speakers, is rising in frontline services, as such devices can perform several tasks for customers. However, little is known about customer responses to interactions with smart speakers that occur during service encounters. This research encompasses three studies intended to enhance our currently scarce knowledge of how customers respond to interactions with smart speakers during service encounters. Focusing on the hospitality industry, the first study shows that smart speakers improve evaluations of the hotels that use them in terms of customer ratings and positive affects. The second study demonstrates that automated social presence and psychological ownership feelings are key mechanisms that explain the development of valuable customer responses. The third study, which uses virtual reality, suggests that better actual behaviors are exhibited by people who appreciate the incorporation of smart speakers into services. Thus, the findings indicate that smart speakers improve service experiences, especially if used to carry out hedonic tasks usually performed by employees.

<p>This project analyzes the impact of customer journey automation through Artificial intelligence on customer engagement, mediated by brand experience, social cognition and psichological ownership.</p>

<p>The dataset includes 3 files employed in the publication "Human–robot interactions in the restaurant setting: the role of social cognition, psychological ownership and anthropomorphism".</p>

<p>This project analyzes the impact of customer journey automation through Artificial intelligence on customer engagement, mediated by brand experience, social cognition and psichological ownership.</p>

<p>The dataset includes 3 files employed in the publications "Emojis and Users’ Brand Engagement in Instagram. The Case of Eco-Friendly Restaurants" (Grant AI-SERVICES PID2020-113561RB-I00/AEI/10.13039/501100011033), "Females’ customer engagement with eco-friendly restaurants in Instagram: the role of past visits" (Grant PID2019-111195RB-I00/ AEI / 10.13039/501100011033), and "Engaging consumers through firm-generated content on Instagram" (Grant UV-INV-AE19-1212255).</p>

<p>This dataset enables the analysis of the drivers of female followers' engagement -cognitive, affective and behavioral- with eco-friendly restaurants on Instagram and their influence on brand advocacy and the intention to visit the restaurant. As antecedents, the perceived originality and perceived enjoyment that followers derive from the brand-generated content posted by a restaurant on Instagram are considered. Additionally, attention is given to the moderating effects of followers' attitudes towards the use of emojis in posts and to past visits to the restaurant.</p>

<p>This project analyzes the impact of customer journey automation through Artificial intelligence on customer engagement, mediated by brand experience, social cognition and psichological ownership.</p>

<p>The dataset includes 3 files employed in the publication "Company size, online reviews and customer responses: implications for SMEs in the hospitality field".</p>

<p>This project analyzes the impact of customer journey automation through Artificial intelligence on customer engagement, mediated by brand experience, social cognition and psichological ownership.</p>

<p>The dataset includes 3 files employed in the publication "Smart speakers and customer experience in service contexts", corresponding to Studies 1, 2 and 3.</p>
<p>Study 1: Data were collected from a review platform, Tripadvisor.</p>
<p>Study 2: Data were collected through a questionnaire implemented in Qualtrics. The sample consisted of 322 Spanish participants.</p>
<p>Study 3: Data were collected from a sample consisted of 33 Portuguese participants, recruited through convenience sampling.</p>
Methodology:
<ul>
<li>Study 1: web scrapping + sentiment analysis.</li>
<li>Study 2: experiment + partial least squares modelling.</li>
<li>Study 3: survey + text analysis.</li>
</ul>

Objetivo: Este artículo tiene como objetivo entender cómo la utilidad percibida de los Asistentes de Voz (AV) se ve afectada por la calidad percibida del proceso (interacción) y el resultado (información). Asimismo, busca determinar hasta qué punto la utilidad percibida de los AVs mejora la privacidad percibida asociada con su uso y, consecuentemente, la intención de los usuarios de seguir utilizándolos. La innovación tecnológica se incluye como moderador personal para comparar los resultados entre innovadores tecnológicos y no tecnológicos. Para este propósito, utilizamos la Teoría de Usos y Gratificaciones (U&amp;GT).

Diseño
Se realizó una encuesta a 467 usuarios de AVs, y se utilizó la modelización de ecuaciones estructurales (SEM) para analizar los datos.

Resultados
La calidad del proceso y la calidad del resultado son antecedentes claros de la utilidad percibida de los AVs, que afecta a la intención de los usuarios de seguir usándolos. La influencia de ambos factores difiere entre usuarios según su nivel de innovación tecnológica. Los resultados muestran que los innovadores tecnológicos valoran más la experiencia interactiva y la calidad del proceso, mientras que los no innovadores tecnológicos se enfocan en obtener respuestas satisfactorias de los AVs. Además, la influencia positiva de la utilidad percibida en la privacidad percibida es más pronunciada en los innovadores tecnológicos.

Originalidad
Este estudio enriquece la literatura sobre la utilidad percibida de los AVs dentro del marco de la U&amp;GT. Identifica dos factores previos (calidad del proceso y calidad del resultado) de la utilidad percibida y observa diferencias significativas basadas en la innovación tecnológica., Purpose: This paper aims to understand how the perceived usefulness of voice assistants (VAs) is affected by the perceived quality of the process (interaction) and the outcome (information). The authors also aim to determine the extent to which the perceived usefulness of VAs improves the perceived privacy associated with their use and increases users’ intention to continue using them. Consumer technology innovativeness is included as a personal trait moderator, to compare the results between tech and nontech innovators. For this purpose, the authors use the framework of the uses and gratifications theory (U&amp;GT).
Design/methodology/approach: A survey of 467 VA users was conducted and structural equation modeling was used to analyze the data.
Findings: The authors identify two main determinants of the perceived usefulness of VAs that influence users’ intention to continue using this technology, process quality and outcome quality. These two factors influence the continued use of VAs in different ways depending on the technology innovativeness of the consumers. The results show that tech innovators are oriented toward the interactive experience, and therefore, mainly value the process quality. In addition, nontech innovators are oriented toward a satisfactory response from VAs, and therefore, primarily value the outcome quality. In addition, the positive effect of perceived usefulness on perceived privacy is higher for tech innovators.
Originality/value: This study enhances the literature on the perceived usefulness of VAs within the framework of U&amp;GT. It identifies two antecedents (process quality and outcome quality) of perceived usefulness and observes significant differences based on technological innovativeness., AI-SERVICES PID2020-113561RB-I00 is funded by MCIN/AEI/10.13039/501100011033. Also, this
work is part of the project PID2019-108554RB-I00, funded by AEI 10.13039/501100011033.

Esta tesis se centra en el estudio de la interacción de los consumidores con los asistentes virtuales, analizando las formas de interacción posibles: voz, texto y gestos. El comportamiento de los consumidores es crucial en marketing, y la llegada de los asistentes virtuales requiere examinar las diversas formas de interacción. La tesis inicia con un enfoque utilitario y progresa hacia los aspectos sociales y emocionales de la interacción. En el Capítulo 1 se investiga la importancia de la calidad de la interacción y la respuesta de los asistentes de voz como principales antecedentes de los beneficios utilitarios, así como la privacidad percibida y la intención de uso continuado. Para esto, se aplica la Teoría de Usos y Gratificaciones, enfocándose en el beneficio utilitario, e incorporando la personalidad innovadora tecnológica del consumidor como variable moderadora. Los resultados muestran que los consumidores innovadores valoran la calidad de la interacción, mientras que los no innovadores priorizan la calidad de la respuesta. El Capítulo 2 examina la diferencia entre el lenguaje social y socioemocional, analizando cómo impactan en las competencias del chatbot (cognitiva, social y emocional), formando una percepción global de su competencia. Este capítulo se basa en el Modelo del Contenido Estereotipado, explicando cómo las personas estereotipan a los chatbots según su competencia. Los resultados demuestran que el lenguaje social es relacional, atractivo y receptivo, con baja implicación emocional, mientras que el lenguaje socioemocional es solidario, empático y compasivo, con alta implicación emocional. Los resultados determinan que el lenguaje social influye en la competencia social del chatbot, mientras que el lenguaje socioemocional afecta su competencia emocional. La competencia cognitiva y social influye en la competencia global, pero la competencia emocional está mediada por la competencia social. Finalmente, en el Capítulo 3 se explora la interacción mediante gestos faciales, utilizando un enfoque exploratorio debido a las innovaciones en Computación Afectiva, que permite comprender y responder a las emociones del usuario. Se analizan las actitudes (afectivas, cognitivas y comportamentales) de los consumidores hacia esta tecnología bajo la Teoría del Comportamiento Planificado, empleando técnicas de neurociencia del consumidor. Los principales resultados muestran la importancia del compromiso y el impacto emocional en la interacción., This thesis focuses on the study of consumer interaction with virtual assistants, analyzing the different forms of interaction: voice, text, and gestures. Consumer behavior is crucial in marketing, and the advent of virtual assistants necessitates an examination of diverse interactions. The thesis begins with a utilitarian approach and progresses towards the social and emotional aspects of interaction. Chapter 1 investigates the importance of interaction quality and voice assistant responses as primary antecedents of utilitarian benefits, as well as perceived privacy and intention to continue use. For this, the Uses and Gratifications Theory is applied, focusing on utilitarian benefits, and incorporating consumers&apos; innovative technological personality as a moderating variable. The results show that innovative consumers value interaction quality, while non-innovative consumers prioritize response quality. Chapter 2 examines the difference between social and socioemotional language, analyzing how they impact the chatbot&apos;s competencies (cognitive, social, and emotional), shaping a global perception of its competence. This chapter is based on the Stereotype Content Model, explaining how people stereotype chatbots based on their competence. The results demonstrate that social language is relational, engaging, and responsive, with low emotional involvement, while socioemotional language is supportive, empathetic, and compassionate, with high emotional involvement. The results determine that social language influences the chatbot&apos;s social competence, while socioemotional language affects its emotional competence. Cognitive and social competence influence global competence, but emotional competence is mediated by social competence. Finally, Chapter 3 explores interaction through facial gestures, using an exploratory approach due to innovations in Affective Computing, which allows understanding and responding to user emotions. Consumer attitudes (affective, cognitive, and behavioral) towards this technology are explored within the framework of the Theory of Planned Behavior, employing consumer neuroscience techniques. The main results highlight the importance of engagement and emotional impact in interaction., Se agradece el apoyo parcial de los proyectos PID2019-108554RB-I00, TED2021-129513B-C21, TED2021-129513B-C22 y PID2020-113561RB-100 financiados por el Ministerio de Ciencia e Innovación – Agencia Española de Investigación, Se agradece el apoyo parcial de los proyectos PID2019-108554RB-I00, TED2021-129513B-C21, TED2021-129513B-C22 y PID2020-113561RB-100 financiados por el Ministerio de Ciencia e Innovación – Agencia Española de Investigación., Programa de Doctorado en Economía, Empresa y Derecho (RD 99/2011), Ekonomiako, Enpresako eta Zuzenbideko Doktoretza Programa (ED 99/2011)

La proliferación de plataformas peer to peer (P2P) de alojamiento turístico extrahotelero (Airbnb, Vrbo, HouseTrip, etc.) ha promovido la turistificación de muchos barrios en gran un número de ciudades, que se han visto afectados por un considerable incremento de la oferta de estos alojamientos. En este artículo se analizan los alojamientos turísticos extrahoteleros de Airbnb en el territorio de Madrid. Para medir el impacto de Airbnb en Madrid se realizan diversas agrupaciones de los distritos de la ciudad mediante análisis clúster en base a tres indicadores cuantitativos referidos a los alojamientos de la plataforma (nº de alojamientos, nº de alojamientos/𝑘𝑚2 y precio medio de los alojamientos). Se complementa el análisis de los alquileres turísticos, agrupando los distritos en función del precio medio de los alquileres destinados a uso permanente (Fotocasa), a fin de tener una imagen más fidedigna de la vivienda de alquiler en la capital española. Por último, se sugieren distintas soluciones para la descongestión de determinados distritos, resaltando la posibilidad del uso de inteligencia artificial mediante algoritmos para una gestión eficaz de los destinos; así como se acentúa la importancia de guiar las actuaciones gubernamentales hacia la sostenibilidad del destino.

This study develops and validates the Smart Destination Perception Scale (SDPS), a tool designed to assess perceptions of smart destinations among tourists and residents. Grounded in a comprehensive literature review and refined through expert evaluation and pretesting, the SDPS identifies four main dimensions: Innovation, Connectivity, Market Intelligence, and Social and Environmental Responsibility. Market Intelligence integrates Intelligence Systems and Information and Promotion Systems, while Social and Environmental Responsibility integrates Accessibility and Sustainability. Data were collected from 1200 participants (600 tourists and 600 residents), and exploratory and confirmatory factor analyses confirmed the scale's reliability, validity, and dimensional structure. Madrid was selected as the empirical context due to its consolidated status as a leading smart destination in Spain and its relevance as a major European urban tourism hub, underscoring the real-world applicability of the SDPS within a mature smart destination. Findings identify Market Intelligence as the most influential dimension, highlighting the importance of intelligence systems and information and promotion mechanisms in shaping effective smart destination strategies. The Social and Environmental Responsibility dimension also emerges as pivotal by integrating accessibility and sustainability, emphasizing the need for inclusive and environmentally conscious practices. This study contributes to smart destination research by introducing a robust, multidimensional 29-item scale aligned with stakeholder theory and supportive of both strategic planning and practical application. By providing standardized measurements, the SDPS enables authorities to compare destinations and evaluate perceptions from both tourists and residents, fostering a comprehensive approach to smart destination management.