2,535 research outputs found

    Algorithmic personalization and brand loyalty: An experiential perspective

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    This article explores the relationship between algorithmic personalization and brand loyalty by examining how personalization experiences are articulated within the context of music streaming consumption. Despite previous acknowledgement of the link between personalization and brand loyalty, an experientially grounded understanding of how this works has yet to be articulated. Building upon the concept of ‘experiential brand loyalty’, the Algorithmic Personalization/Depersonalization Loop highlights the development of brand loyalty through consumers’ interactions with algorithm-backed brands. Being seen and understood by the algorithm sets off an iterative, two-way learning relationship that ultimately heightens the consumers’ experience, activates positive emotions, and deepens the relational bond with the brand, leading to brand loyalty. If, however, the algorithm is unsuccessful in personalizing the service experience, a ‘depersonalization’ process can occur that erodes brand loyalty and can lead to brand switching or even consumer activism

    Multidisciplinary perspectives on Artificial Intelligence and the law

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    This open access book presents an interdisciplinary, multi-authored, edited collection of chapters on Artificial Intelligence (‘AI’) and the Law. AI technology has come to play a central role in the modern data economy. Through a combination of increased computing power, the growing availability of data and the advancement of algorithms, AI has now become an umbrella term for some of the most transformational technological breakthroughs of this age. The importance of AI stems from both the opportunities that it offers and the challenges that it entails. While AI applications hold the promise of economic growth and efficiency gains, they also create significant risks and uncertainty. The potential and perils of AI have thus come to dominate modern discussions of technology and ethics – and although AI was initially allowed to largely develop without guidelines or rules, few would deny that the law is set to play a fundamental role in shaping the future of AI. As the debate over AI is far from over, the need for rigorous analysis has never been greater. This book thus brings together contributors from different fields and backgrounds to explore how the law might provide answers to some of the most pressing questions raised by AI. An outcome of the Católica Research Centre for the Future of Law and its interdisciplinary working group on Law and Artificial Intelligence, it includes contributions by leading scholars in the fields of technology, ethics and the law.info:eu-repo/semantics/publishedVersio

    Disrupción tecnológica en la gestión del Talento Humano

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    The selection and retention of human talent are critical processes for the success of any company or organization, and talent management must adapt to the constant change in technological and social trends in the environment where it develops. This research presents the most recent publications where new technologies contribute to these processes, such as: automating repetitive and tedious tasks in the talent selection process, such as resume review and interview scheduling, identification of candidates that fit for the position and the organizational culture of the company; how they can be programmed to be "blind" to characteristics such as age, gender, race, etc., and considering ethics and diversity at all times; the risk of unconscious biases in the selection of candidates is reduced; They can help companies or organizations discover potential candidates who might otherwise have gone unnoticed by searching social media and job websites, as well as be used to assess the experience and skills of candidates based on their activity. online; online technologies allow evaluating and selecting candidates from different parts of the world, without having to physically travel, reducing costs and increasing efficiency in the selection process; virtual and augmented reality, can help companies assess technical and practical skills, especially in positions that require skills.La selección y retención del talento humano son procesos críticos para el éxito de cualquier empresa u organización, debiendo adaptarse la gestión del talento al cambio constante de las tendencias tecnológicas y sociales del entorno donde se desarrolla. En esta investigación se presentan las más recientes publicaciones donde las nuevas tecnologías contribuyen a estos procesos, como: automatizando tareas repetitivas y tediosas en el proceso de selección del talento, como la revisión de currículums y la programación de entrevistas, identificación de candidatos que se ajustan para el puesto y la cultura organizacional de la empresa; como pueden ser programadas para ser "ciegas" a características como la edad, el género, la raza, etc., y considerando en todo momento la ética y la diversidad; se reduce el riesgo de sesgos inconscientes en la selección de candidatos; pueden ayudar a las empresas u organizaciones a descubrir candidatos potenciales que de otra manera podrían haber pasado desapercibidos, buscando en redes sociales y sitios web de empleo, así como también pueden utilizarse para evaluar la experiencia y las habilidades de los candidatos en base a su actividad en línea; las tecnologías en línea, permiten evaluar y seleccionar a candidatos de diferentes partes del mundo, sin tener que desplazarse físicamente, reduciendo costos y aumentando la eficiencia en el proceso de selección; la realidad virtual y aumentada, pueden ayudar a las empresas a evaluar habilidades técnicas y prácticas, especialmente en puestos que requieren habilidades

    The Development of Human Personality: A Comprehensive Overview

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    The complex relationship between physical and psychological disorders can pose challenges for effective treatment. Both aspects often require a multidisciplinary approach to address their interconnectedness. An individual's personality is shaped by their mentality, psyche, and values, which must be in harmony for a well-ordered and disciplined personality. While medical interventions are important, incorporating non-medical interventions can be crucial for managing and treating these disorders. This includes lifestyle changes such as exercise and diet, as well as incorporating values that promote overall well-being. Neglecting our psyche can lead to negative traits and mental health issues. Therefore, nurturing our personality through positive experiences, healthy relationships, self-care and self-reflection is necessary to promote mental and emotional health. It is important to create a balance between material and non-material values to have a harmonious and stable life. Choosing a lifestyle that aligns with our values and needs allows us to create a compatible system, which in turn allows us to make informed decisions and realize our full potential

    Three levels at which the user's cognition can be represented in artificial intelligence

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    Artificial intelligence (AI) plays an important role in modern society. AI applications are omnipresent and assist many decisions we make in daily life. A common and important feature of such AI applications are user models. These models allow an AI application to adapt to a specific user. Here, we argue that user models in AI can be optimized by modeling these user models more closely to models of human cognition. We identify three levels at which insights from human cognition can be—and have been—integrated in user models. Such integration can be very loose with user models only being inspired by general knowledge of human cognition or very tight with user models implementing specific cognitive processes. Using AI-based applications in the context of education as a case study, we demonstrate that user models that are more deeply rooted in models of cognition offer more valid and more fine-grained adaptations to an individual user. We propose that such user models can also advance the development of explainable AI

    Relationship Between Country Culture, Country Demographics, and Restaurant Electronic Word-of-Mouth Valence Ratings

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    Researchers have documented that country culture and country demographics influence electronic word-of-mouth (eWOM) within various industries. Although past research has shown the importance of eWOM to restaurants as a measure of consumer satisfaction, researchers have not established the effect of country culture and country demographics on eWOM within the restaurant industry. Thus, the specific management problem addressed in this quantitative correlational study was the lack of knowledge and understanding regarding the relationship between country culture, country demographics, and restaurant eWOM valence ratings. Grounded in Hofstede’s cultural dimensions theory, the research questions addressed six measures of country culture, 12 measures of country demographics, and their relationship with restaurant eWOM valence ratings. With a purposive sample from the Yelp social media platform, eWOM ratings from 3,659 restaurants in 21 countries were analyzed with correlation analyses and multiple linear regression. Results indicated that a model of five variables and eight two-factor interactions statistically and significantly explained 14.4% of the variance in restaurant eWOM valence ratings. This study may promote positive social change by informing restaurant managers about which aspects of country culture and country demographics relate to restaurant eWOM valence ratings. Restaurant leaders may improve their eWOM response strategies by focusing on the most relevant country culture and country demographic constructs when developing eWOM communication

    Unique Experiences:Designing Warm Technology to Support Personal Dynamics in Dementia

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    Understanding Agreement and Disagreement in Listeners’ Perceived Emotion in Live Music Performance

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    Emotion perception of music is subjective and time dependent. Most computational music emotion recognition (MER) systems overlook time- and listener-dependent factors by averaging emotion judgments across listeners. In this work, we investigate the influence of music, setting (live vs lab vs online), and individual factors on music emotion perception over time. In an initial study, we explore changes in perceived music emotions among audience members during live classical music performances. Fifteen audience members used a mobile application to annotate time-varying emotion judgments based on the valence-arousal model. Inter-rater reliability analyses indicate that consistency in emotion judgments varies significantly across rehearsal segments, with systematic disagreements in certain segments. In a follow-up study, we examine listeners' reasons for their ratings in segments with high and low agreement. We relate these reasons to acoustic features and individual differences. Twenty-one listeners annotated perceived emotions while watching a recorded video of the live performance. They then reflected on their judgments and provided explanations retrospectively. Disagreements were attributed to listeners attending to different musical features or being uncertain about the expressed emotions. Emotion judgments were significantly associated with personality traits, gender, cultural background, and music preference. Thematic analysis of explanations revealed cognitive processes underlying music emotion perception, highlighting attributes less frequently discussed in MER studies, such as instrumentation, arrangement, musical structure, and multimodal factors related to performer expression. Exploratory models incorporating these semantic features and individual factors were developed to predict perceived music emotion over time. Regression analyses confirmed the significance of listener-informed semantic features as independent variables, with individual factors acting as moderators between loudness, pitch range, and arousal. In our final study, we analyzed the effects of individual differences on music emotion perception among 128 participants with diverse backgrounds. Participants annotated perceived emotions for 51 piano performances of different compositions from the Western canon, spanning various era. Linear mixed effects models revealed significant variations in valence and arousal ratings, as well as the frequency of emotion ratings, with regard to several individual factors: music sophistication, music preferences, personality traits, and mood states. Additionally, participants' ratings of arousal, valence, and emotional agreement were significantly associated to the historical time periods of the examined clips. This research highlights the complexity of music emotion perception, revealing it to be a dynamic, individual and context-dependent process. It paves the way for the development of more individually nuanced, time-based models in music psychology, opening up new avenues for personalised music emotion recognition and recommendation, music emotion-driven generation and therapeutic applications
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