Grounded in the Stereotype Content Model, Risk Perception Theory, Technology Acceptance Model, and Relational Embeddedness Theory, this research delves into the relationship between chatbot conversation styles, customer risk, and the mediating role of chatbot acceptance and tie strength in online shopping. A 2 (warm vs. cold) * 2 (competent vs. incompetent) between-subjects experiment is conducted on 320 participants and the results obtained from two-way ANOVA and PROCESS macro revealed that: (a) customer-perceived risk decreases with conversation warmth rather than conversation competence; (b) customer acceptance of chatbots improves with conversation competence rather than conversation warmth, while not acting as an intermediary factor between the conversation styles and customer-perceived risk; (c) customer perceived tie strength increases with both conversation warmth and conversation competence. The findings contribute to the existing literature about the impact of chatbot anthropomorphism on customer cognitive processes and offer executives insights into the design of customer-friendly chatbots.
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In de afgelopen jaren hebben technologische ontwikkelingen de aard van dienstverlening ingrijpend veranderd (Huang & Rust, 2018). Technologie wordt steeds vaker ingezet om menselijke servicemedewerkers te vervangen of te ondersteunen (Larivière et al., 2017; Wirtz et al., 2018). Dit stelt dienstverleners in staat om meer klanten te bedienen met minder werknemers, waardoor de operationele efficiëntie toeneemt (Beatson et al., 2007). Deze operationele efficiëntie leidt weer tot lagere kosten en een groter concurrentievermogen. Ook voor klanten kan de inzet van technologie voordelen hebben, zoals betere toegankelijkheid en consistentie, tijd- en kostenbesparing en (de perceptie van) meer controle over het serviceproces (Curran & Meuter, 2005). Mede vanwege deze beoogde voordelen is de inzet van technologie in service-interacties de afgelopen twee decennia exponentieel gegroeid. De inzet van zogenaamde conversational agents is een van de belangrijkste manieren waarop dienstverleners technologie kunnen inzetten om menselijke servicemedewerkers te ondersteunen of vervangen (Gartner, 2021). Conversational agents zijn geautomatiseerde gesprekspartners die menselijk communicatief gedrag nabootsen (Laranjo et al., 2018; Schuetzler et al., 2018). Er bestaan grofweg drie soorten conversational agents: chatbots, avatars, en robots. Chatbots zijn applicaties die geen virtuele of fysieke belichaming hebben en voornamelijk communiceren via gesproken of geschreven verbale communicatie (Araujo, 2018;Dale, 2016). Avatars hebben een virtuele belichaming, waardoor ze ook non-verbale signalen kunnen gebruiken om te communiceren, zoals glimlachen en knikken (Cassell, 2000). Robots, ten slotte, hebben een fysieke belichaming, waardoor ze ook fysiek contact kunnen hebben met gebruikers (Fink, 2012). Conversational agents onderscheiden zich door hun vermogen om menselijk gedrag te vertonen in service-interacties, maar op de vraag ‘hoe menselijk is wenselijk?’ bestaat nog geen eenduidig antwoord. Conversational agents als sociale actoren Om succesvol te zijn als dienstverlener, is kwalitatief hoogwaardige interactie tussen servicemedewerkers en klanten van cruciaal belang (Palmatier et al., 2006). Dit komt omdat klanten hun percepties van een servicemedewerker (bijv. vriendelijkheid, bekwaamheid) ontlenen aan diens uiterlijk en verbale en non verbale gedrag (Nickson et al., 2005; Specht et al., 2007; Sundaram & Webster, 2000). Deze klantpercepties beïnvloeden belangrijke aspecten van de relatie tussen klanten en dienstverleners, zoals vertrouwen en betrokkenheid, die op hun beurt intentie tot gebruik, mond-tot-mondreclame, loyaliteit en samenwerking beïnvloeden (Hennig-Thurau, 2004; Palmatier et al., 2006).Er is groeiend bewijs dat de uiterlijke kenmerken en communicatieve gedragingen (hierna: menselijke communicatieve gedragingen) die percepties van klanten positief beïnvloeden, ook effectief zijn wanneer ze worden toegepast door conversational agents (B.R. Duffy, 2003; Holtgraves et al., 2007). Het zogenaamde ‘Computers Als Sociale Actoren’ (CASA paradigma vertrekt vanuit de aanname dat mensen de neiging hebben om onbewust sociale regels en gedragingen toe te passen in interacties met computers, ondanks het feit dat ze weten dat deze computers levenloos zijn (Nass et al., 1994). Dit kan verder worden verklaard door het fenomeen antropomorfisme (Epley et al., 2007; Novak & Hoffman, 2019). Antropomorfisme houdt in dat de aanwezigheid van mensachtige kenmerken of gedragingen in niet-menselijke agenten, onbewust cognitieve schema's voor menselijke interactie activeert (Aggarwal & McGill, 2007; M.K. Lee et al., 2010). Door computers te antropomorfiseren komen mensen tegemoet aan hun eigen behoefte aan sociale verbinding en begrip van de sociale omgeving (Epley et al., 2007; Waytz et al., 2010). Dit heeft echter ook tot gevolg dat mensen cognitieve schema’s voor sociale perceptie toepassen op conversational agents.
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This article describes the relation between mental health and academic performance during the start of college and how AI-enhanced chatbot interventions could prevent both study problems and mental health problems.
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In this paper, we explore the design of web-based advice robots to enhance users' confidence in acting upon the provided advice. Drawing from research on algorithm acceptance and explainable AI, we hypothesise four design principles that may encourage interactivity and exploration, thus fostering users' confidence to act. Through a value-oriented prototype experiment and value-oriented semi-structured interviews, we tested these principles, confirming three of them and identifying an additional principle. The four resulting principles: (1) put context questions and resulting advice on one page and allow live, iterative exploration, (2) use action or change oriented questions to adjust the input parameters, (3) actively offer alternative scenarios based on counterfactuals, and (4) show all options instead of only the recommended one(s), appear to contribute to the values of agency and trust. Our study integrates the Design Science Research approach with a Value Sensitive Design approach.
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Purpose: This study, a conceptual paper, analyses the growth of curation in tourism and hospitality and the curator role in selecting and framing products and experiences. It considers the growth of expert, algorithmic, social and co-creative curation modes and their effects. Design/methodology/approach: Narrative and integrative reviews of literature on curation and tourism and hospitality are used to develop a typology of curation and identify different curation modes. Findings: Curational techniques are increasingly used to organise experience supply and distribution in mainstream fields, including media, retailing and fashion. In tourism and hospitality, curated tourism, curated hospitality brands and food offerings and place curation by destination marketing organisations are growing. Curation is undertaken by experts, algorithms and social groups and involves many of destination-related actors, producing a trend towards “hybrid curation” of places. Research limitations/implications: Research is needed on different forms of curation, their differential effects and the power roles of different curational modes. Practical implications: Curation is a widespread intermediary function in tourism and hospitality, supporting better consumer choice. New curators influence experience supply and the distribution of consumer attention, shaping markets and co-creative activities. Increased curatorial activity should stimulate aesthetic and stylistic innovation and provide the basis for storytelling and narrative in tourism and hospitality. Originality/value: This is the first study of curational strategies in tourism and hospitality, providing a definition and typology of curation, and linking micro and macro levels of analysis. It suggests the growth of choice-based logic alongside service-dominant logic in tourism and hospitality.
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In 2019, the first "Atelier Book" was published . Since then, a few years have passed and numerous new Ateliers have emerged. With this new atelier book, through more than 30 portraits, the richness and variety of ateliers within our college are shown. The portraits are divided as follows: ateliers at the NHL Stenden locations, external ateliers and ateliers which the facilities are a strong determinant. These portraits show which issues are being worked on, how they cooperate with the field and researchers and what the added value of the Ateliers is. This atelier book also contains a number of in-depth articles that talk about working and learning in ateliers. The contribution in chapter 1 is about: what NHL Stenden aims at with ateliers, where do the ateliers differ and some experiences with ateliers. After the portraits in chapter 2, chapter 3 presents the 'Atelier Value Creation Model' and a model with design dimensions. Both provide tools for designing and evaluating ateliers. Chapter 4 zooms in on the effects of physical space on learning. Then, Chapter 5 discusses the outcomes of (current) research on ateliers.
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The design of health game rewards for preadolescents Videogames are a promising strategy for child health interventions, but their impact can vary depending on the game mechanics used. This study investigated achievement-based ‘rewards’ and their design among preadolescents (8-12 years) to assess their effect and explain how they work. In a 2 (game reward achievement system: social vs. personal) x 2 (game reward context: in-game vs. out-game) between-subjects design, 178 children were randomly assigned to one of four conditions. Findings indicated that a ‘personal’ achievement system (showing one’s own high scores) led to more attention and less frustration than a ‘social’ achievement system (showing also high scores of others) which, in turn, increased children’s motivation to make healthy food choices. Furthermore, ‘out’-game rewards (tangible stickers allocated outside the game environment) were liked more than ‘in’-game rewards (virtual stickers allocated in the game environment), leading to greater satisfaction and, in turn, a higher motivation to make healthy food choices.
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As artificial intelligence (AI) reshapes hiring, organizations increasingly rely on AI-enhanced selection methods such as chatbot-led interviews and algorithmic resume screening. While AI offers efficiency and scalability, concerns persist regarding fairness, transparency, and trust. This qualitative study applies the Artificially Intelligent Device Use Acceptance (AIDUA) model to examine how job applicants perceive and respond to AI-driven hiring. Drawing on semi-structured interviews with 15 professionals, the study explores how social influence, anthropomorphism, and performance expectancy shape applicant acceptance, while concerns about transparency and fairness emerge as key barriers. Participants expressed a strong preference for hybrid AI-human hiring models, emphasizing the importance of explainability and human oversight. The study refines the AIDUA model in the recruitment context and offers practical recommendations for organizations seeking to implement AI ethically and effectively in selection processes.
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Light profoundly impacts many aspects of human physiology and behaviour, including the synchronization of the circadian clock, the production of melatonin, and cognition. These effects of light, termed the non-visual effects of light, have been primarily investigated in laboratory settings, where light intensity, spectrum and timing can be carefully controlled to draw associations with physiological outcomes of interest. Recently, the increasing availability of wearable light loggers has opened the possibility of studying personal light exposure in free-living conditions where people engage in activities of daily living, yielding findings associating aspects of light exposure and health outcomes, supporting the importance of adequate light exposure at appropriate times for human health. However, comprehensive protocols capturing environmental (e.g., geographical location, season, climate, photoperiod) and individual factors (e.g., culture, personal habits, behaviour, commute type, profession) contributing to the measured light exposure are currently lacking. Here, we present a protocol that combines smartphone-based experience sampling (experience sampling implementing Karolinska Sleepiness Scale, KSS ratings) and high-quality light exposure data collection at three body sites (near-corneal plane between the two eyes mounted on spectacle, neck-worn pendant/badge, and wrist-worn watch-like design) to capture daily factors related to individuals’ light exposure. We will implement the protocol in an international multi-centre study to investigate the environmental and socio-cultural factors influencing light exposure patterns in Germany, Ghana, Netherlands, Spain, Sweden, and Turkey (minimum n = 15, target n = 30 per site, minimum n = 90, target n = 180 across all sites). With the resulting dataset, lifestyle and context-specific factors that contribute to healthy light exposure will be identified. This information is essential in designing effective public health interventions.
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