Trends and challenges of e-government chatbots: Advances in exploring open government data and citizen participation content

This work was supported by the Spanish Ministry of Science and Innovation (PID2019-108965GB-I00) and the Regional Government of Andalusia (P20_00314 and B-SEJ-556-UGR20). The authors thank all people who participated in the reported studies.In this paper, we propose a conceptual framework composed of a number of e-government, implementation and evaluation-oriented variables, with which we jointly analyze chatbots presented in the research literature and chatbots deployed as public services in Spain at national, regional and local levels. As a result of our holistic analysis, we identify and discuss current trends and challenges in the development and evaluation of chatbots in the public administration sector, such as focusing the use of the conversational agents on the search for government information, documents and services –leaving citizen consultation and collaboration aside–, and conducting preliminary evaluations of prototypes in limited studies, lacking experiments on deployed systems, with metrics beyond effectiveness and usability –e.g., metrics related to the generation of public values. Addressing some of the identified challenges, we build and evaluate two novel chatbots that present advances in the access to open government data and citizen participation content. Moreover, we come up with additional, potential research lines that may be considered in the future for a new generation of e-government chatbots.Spanish Ministry of Science and Innovation (PID2019-108965GB-I00)Regional Government of Andalusia (P20_00314 and B-SEJ-556-UGR20

Chatbots for Modelling, Modelling of Chatbots

Tesis Doctoral inédita leída en la Universidad Autónoma de Madrid, Escuela Politécnica Superior, Departamento de Ingeniería Informática. Fecha de Lectura: 28-03-202

Marketing Intelligence: Boom or Bust of Service Marketing?

Marketing intelligence fosters two major developments within digital service marketing. On the one hand, a boom of services seems to have evolved, accelerated by the opportunities of marketing intelligence. It has contributed to the optimization of customer experiences, e.g., supported by mobile, personalized, and customized marketing services. On the other hand, (digital) self-services are likely to pervert the term “service”. Lifecycle marketing, including annoying marketing communication in real-time, automated price adjustment and programmatic advertising based on artificial intelligence, affects the vision of fully standardized marketing automation. Additionally, there are incentives to pollute the digital information in order to manufacture opinions. Fake news is one popular example. This leads to the (open) question if marketing intelligence means service boom or bust of marketing. This contribution aims to elaborate the boom-and-bust aspects of marketing intelligence and suggests a trade-off. The method applied in this paper will be a descriptive and conceptual literature review, through which the paradigmatic thoughts will be juxtaposed from the perspective of service

Information and Communication Technologies in Tourism 2022

This open access book presents the proceedings of the International Federation for IT and Travel & Tourism (IFITT)’s 29th Annual International eTourism Conference, which assembles the latest research presented at the ENTER2022 conference, which will be held on January 11–14, 2022. The book provides an extensive overview of how information and communication technologies can be used to develop tourism and hospitality. It covers the latest research on various topics within the field, including augmented and virtual reality, website development, social media use, e-learning, big data, analytics, and recommendation systems. The readers will gain insights and ideas on how information and communication technologies can be used in tourism and hospitality. Academics working in the eTourism field, as well as students and practitioners, will find up-to-date information on the status of research

Using and Interacting with AI-Based Intelligent Technologies: Practical Applications on Autonomous Cars and Chatbots

L'intelligence artificielle (IA) est souvent considérée comme l'une des innovations les plus prometteuses et perturbatrices de notre époque. Malgré son développement rapide, il existe encore un haut niveau d'incertitude quant à la manière dont les consommateurs vont adopter l'IA. Dans ce contexte, cette thèse de quatre articles vise à comprendre comment les consommateurs utilisent et interagissent avec les technologies intelligentes, en se concentrant en particulier sur deux applications: les chatbots et les véhicules autonomes (VA). Dans un premier temps, nous effectuons une analyse approfondie de la littérature marketing existante en adoptant les approches scientométriques et la méthode Theory-Context-Characteristics-Methodology. Ainsi, nous définissons nos questions de recherche concernant 1) les réactions cognitives et émotionnelles des consommateurs lorsqu'ils interagissent avec des technologies basées sur l'IA capables de simuler des conversations de type humain ; 2) les facteurs affectant l'intention des consommateurs d'utiliser des technologies basées sur l'IA, et leur évolution à travers les niveaux d'automatisation ; 3) les préoccupations éthiques des consommateurs envers les produits IA et leur effet sur la confiance et les intentions d'utilisation. En mettant en œuvre trois plans expérimentaux inter-sujets, nous répondons à notre première question de recherche en comparant les interactions humain-humain et humain-chatbot et les interactions avec des chatbots hautement anthropomorphes et faiblement anthropomorphes. Nous nous appuyons principalement sur la Théorie de l'Evaluation Cognitive des Emotions (Roseman et al. 1990), la Théorie de l'Attribution (Weiner 2000) et la Théorie de l'Anthropomorphisme (Aggarwal and McGill 2007 ; Epley et al. 2018), en montrant que les réponses des consommateurs diffèrent lorsqu'ils interagissent avec un humain et un chatbot, en fonction des différentes attributions de responsabilité et des différents niveaux d'anthropomorphisme. Ensuite, nous étudions la manière dont l'expérience des consommateurs avec différents niveaux d'automatisation affecte les perceptions des technologies basées sur l'IA. Nous utilisons les VA comme unité d'analyse, en intégrant le cadre UTAUT avec la Théorie de la Confiance (Mcknight et al. 2011), la Théorie du Calcul de la Vie Privée (Dinev et Hart 2006) et la Théorie du Bien-être (Diener 1999). Après la mise en œuvre d'un design intra-sujet avec des études sur le terrain et sur simulateur, les résultats suggèrent que la différenciation entre les différents niveaux d'automatisation joue un rôle clé pour mieux comprendre les facteurs d’adoption ainsi que les réactions cognitives lors de l'utilisation d'applications intelligentes. Enfin, nous étudions les préoccupations éthiques des consommateurs concernant les chatbots et les VA. Nous utilisons une approche mixte, en utilisant la modélisation thématique et la modélisation par équation structurelle. Nous montrons que pour les chatbots, la composante interactionnelle et émotionnelle de la technologie est prédominante, les consommateurs soulignant, entre autres, le design émotionnel et le manque d'adaptabilité comme principaux soucis éthiques. En revanche, pour les VA, les préoccupations éthiques concernent plutôt des perceptions cognitives liées à la transparence des algorithmes, à la sécurité de la technologie et à l'accessibilité. Notre recherche offre des contributions à la littérature émergente sur les comportements des consommateurs liés aux produits intelligents en soulignant la nécessité de prendre en compte la complexité des technologies d'IA à travers leurs différents niveaux d'automatisation et en fonction de leurs caractéristiques. Nous offrons également des contributions méthodologiques grâce à la mise en œuvre de plans de recherche expérimentaux innovants, utilisant des outils avancés et combinant des approches qualitatives et quantitatives. […]Artificial Intelligence (AI) is often considered as one of the most promising and disruptive innovation of our times. Despite its rapid development, there is still a high level of uncertainty about how consumers are going to adopt AI. In this context, this four-article dissertation aims to comprehend how consumers use and interact with intelligent technologies, in particular focusing on two current applications: chatbots and autonomous vehicles (AVs). First, we conduct an in-depth analysis of the existing marketing literature adopting Scientometric and Theory-Context-Characteristics-Methodology approaches. Thus, we define our research questions related to 1) consumers ‘cognitive and emotional reactions when interacting with AI-based technologies that are able to simulate human-like conversations; 2) factors affecting consumers ‘intention to use AI-based technologies able to make decision in critical situations, and their evolution across levels of automation; 3) consumers ethical concerns towards AI products and their effect on trust and usage intentions. By applying three between-subject experimental designs, we answer our first research question comparing human–human versus human–chatbot interactions and highly anthropomorphic versus lowly anthropomorphic chatbots. We leverage insights mainly from Cognitive Appraisal Theory of Emotions (Roseman et al. 1990), Attribution Theory (Weiner 2000) and Theory of Anthropomorphism (Aggarwal and McGill 2007; Epley et al. 2018), showing that consumers’ responses differ when interacting with a human and a chatbot, according to the different attributions of responsibility and the different levels of anthropomorphism of the service agent. Next, we investigate the way consumers’ experience with different levels of automation affect perceptions of AI-based technologies. We use AVs as unit of analysis, integrating the UTAUT framework with Trust Theory (Mcknight et al. 2011), Privacy Calculus Theory (Dinev and Hart 2006) and Theory of Well-being (Diener 1999; Diener and Chan 2011). After implementing a within subject-design with field and simulator studies, results suggest that differentiating between the different automation levels play a key role to better understand the potential drivers of adoption as well as the cognitive reactions when using intelligent applications. Finally, we investigate consumers’ ethical concerns surrounding chatbots and AVs. We employ a mixed methods approach, using topic modeling and structural equation modeling. We show that for chatbots, the interactional and emotional component of the technology is predominant, as consumers highlight, between others, the emotional design and the lack of adaptability as main ethical issues. However, for autonomous cars, the ethical concerns rather involve cognitive perceptions related to the transparency of the algorithms, the ethical design, the safety of the technology and the accessibility. Our research offers contributions to the emerging literature on consumer behaviors related to intelligent products by highlighting the need to take into account the complexity of AI technologies across their different levels of automation and according to their intrinsic characteristics. We also offer methodological contributions thanks to the implementation of innovative experimental research designs, using advanced tools and combining qualitative and quantitative approaches. To conclude, we present implications for both managers and policymakers who want to implement AIbased disruptive technologies, such as chatbots and AVs

Keystroke-Level Model to Evaluate Chatbot Interface for Reservation System

The tour package reservation system is an important part of improving tourism services. Reservations must be able to meet the information needs of prospective customers and can serve the desired tour package bookings. A reservation system is usually a form that must be filled in sequence by prospective visitors. This paper discusses the evaluation of the application of the chatbot interface on the reservation system with the keystroke-level model. Changing the interaction design that previously did the task fills out the form into a conversation interaction. The aim is to increase the speed of the ordering process through the system. Prospective visitors do not need to fill in the form, they only need to have a conversation with the system while entering the order data. The evaluation results using the keystroke-level model show that the chatbot interface can increase the speed of the process by shortening steps

In Search of the Perfect Prompt

The study investigates the efficacy of soft and hard prompt strategies in the scientific domain, namely in the tasks of conversational abstract generation. The proposed approach incorporates two distinct methods, prompt engineering and prompt tuning, within a Conversational Recommender System (CRS). The primary objective of this system is to aid users in generating abstracts for their research. The present study employs an evaluation approach that integrates user research with objective performance criteria. This study examines the strengths and disadvantages associated with both categories of prompts, commencing with an analysis of existing literature on CRS and prompting studies, and subsequently conducting original research tests. This study makes three primary contributions. Initially, a compilation of prerequisites and hypothetical situations is formed by an examination of the issue at hand. This wish list presents a range of potential technological, user, and functional views that have the potential to contribute to future studies in this area. Furthermore, the examination of user studies is an integral element of our evaluation methodology. During this process, we analyze many factors pertaining to the 6 participants, including their cognitive load, response time, and overall happiness while applying challenging prompts within the CRS. In our investigation, we examine the behavior and needs of the target demographic, consisting of academics and researchers. Our findings suggest a tendency among this group to favor interactions that are focused on factual information and question-and-answer exchanges, as opposed to more expansive and conversational encounters. Thirdly, our study delves into the comprehensibility and relevance of the generated abstracts, utilizing well-established criteria such as Rouge and F1 scores. In our research, the anticipated effect of combining prompts with text-generation tasks is to produce scientific abstracts that are imprecise and broader in nature. However, this objective contradicts the expectations of the users. The research findings shed light on the difficulties and advantages that arise from implementing prompting techniques with a CRS. This study makes a valuable contribution by recognizing the importance of contextual comprehension and employing prompting strategies from both technical and user-centric viewpoints. One of the primary findings is that it is crucial to customize prompt tactics in accordance with user preferences and domain demands. The given findings contribute to the existing body of knowledge on conversational recommender systems and their applications in the field of natural language processing

Information and Communication Technologies in Tourism 2022

This open access book presents the proceedings of the International Federation for IT and Travel & Tourism (IFITT)’s 29th Annual International eTourism Conference, which assembles the latest research presented at the ENTER2022 conference, which will be held on January 11–14, 2022. The book provides an extensive overview of how information and communication technologies can be used to develop tourism and hospitality. It covers the latest research on various topics within the field, including augmented and virtual reality, website development, social media use, e-learning, big data, analytics, and recommendation systems. The readers will gain insights and ideas on how information and communication technologies can be used in tourism and hospitality. Academics working in the eTourism field, as well as students and practitioners, will find up-to-date information on the status of research