This chatbot is a smart one! Does perceived expertise increase willingness to interact with chatbots?

The development of artificial intelligence has led many companies to introduce computer operated chatbots that provide highly personalized services. The aim of this study is to explore the effect of perceived expertise on continuance intention to use a chatbot. Specifically, we portray that perceived trust is the mechanism behind this relationship and chatbot appearance (i.e., human-like vs. robot-like) a boundary condition for the effect. The research hypotheses were experimentally tested with a pilot study (n=89). Participants accessed to a simulated online chatbot for booking hotels: 41 were randomly assigned to a human-like chatbot and 38 to a robot-like chatbot. The perceived expertise of the service agent influences - through trust - consumers’ continuance intention to use the chatbot again. However, we do not find support for the moderating effect of perceived expertise on trust. These findings have practical implications as they encourage companies to adopt the chatbot as an effective channel for the provision of certain services. In addition, they can help developers to improve the design of online interactions mediated by robots.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Capturing Micro-Expressions on Zoom: A Promising Sales Opportunity

The subtleties of salesmanship are changing in this virtual world of online communication. This proof-ofconcept study examines the feasibility of capturing customer images at the two, ten, and thirty-second intervals following a Zoom platform's sales query. A captured image underwent a micro-expression analysis employing a computer-driven program that generates an emotional-algorithm analyzing the emotions of happy, neutral, sad, disgust, fear, surprise, and anger. This algorithm enabled researchers to predict a purchase-decision using proprietary artificial intelligence software. Findings suggest that microexpressions captured at the two-second interval exhibited a significant relationship with a customer's purchase decision. A summary table provides a detailed overview of all results using the acronym [MICRO]

Factors Influencing the Perception of Seller Credibility in Online Reputation System: an Eye-Movement Approach

The current online reputation systems for online sellers face great challenges from bad-faith behavior such as malicious negative reviews, click farming, mismatch between images and commodities, and forged commodities. To optimize the design of online reputation systems, explore the consumer utilization of credit clues, and describe the law of mutual trust, this paper puts forth three hypotheses about the influencing factors of consumer perception of online seller credibility and integrates various research methods such as an eye-movement experiment, questionnaire survey, econometric analysis, and empirical research. To evaluate the three hypotheses, the display modes of commodities on a current e-commerce platform were optimized, and eye-movement experiments were conducted on original and optimized webpages. Results show that the display of sales growth, the refinement and tagging of review content significantly impacted consumer perception of seller credibility. Further, designers of online reputation systems were advised to display sales trends, provide personalized sales queries, and tag a variety of reviews for consumers to easily ascertain credible sellers. This advice helped curb bad-faith behavior

Follow Me If You Want to Live - Understanding the Influence of Human-Like Design on Users’ Perception and Intention to Comply with COVID-19 Education Chatbots

Following recommendations and complying with behavioral attitudes is one major key in overcoming global pandemics, such as COVID-19. As the World Health Organization (WHO) highlights, there is an increased need to follow hygiene standards to prevent infections and in reducing the risk of infections transmissions (World-Health-Organization, 2021). This urgent need offers new use cases of digital services, such as conversational agents that educate and inform individuals about relevant counter measurements. Specifically, due to the increased fatigue in the population in the context of COVID-19, (Franzen and Wöhner, 2021), CAs can play a vital role in supporting and attaining user’s behavior. We conducted an experiment (n=116) to analyze the effect of a human-like-design CA on the intention to comply. Our results show a significant impact of a human-like design on the perception of humanness, source credibility, and trust, which are all (directly or indirectly) drivers of the intention to comply

Positive gender congruency effects on shopper responses: Field evidence from a gender egalitarian culture

publishedVersio

Mr. and Mrs. Conversational Agent - Gender Stereotyping in Judge-Advisor Systems and the Role of Egocentric Bias

Current technological advancements of conversational agents (CAs) promise new potentials for human-computer collaborations. Yet, both practitioners and researchers face challenges in designing these information systems, such that CAs not only increase in intelligence but also in effectiveness. Drawing on social response theory as well as literature on trust and judge-advisor systems, we examine the roles of gender stereotyping and egocentric bias in cooperative CAs. Specifically, by conducting an online experiment with 87 participants, we investigate the effects of a CA’s gender and a user’s subjective knowledge in two stereotypical male knowledge fields. The results indicate (1) that female (vs. male) CAs and stereotypical female (vs. male) traits increase a user’s perceived competence of CAs and (2) that an increase in a user’s subjective knowledge decreases trusting intentions in CAs. Thus, our contributions provide new and counterintuitive insights that are crucial for the effectiveness of cooperative CAs

EWOM CREDIBILITY, TRUST, PERCEIVED RISK, AND PURCHASE INTENTION IN THE CONTEXT OF E-COMMERCE: MODERATING ROLE OF ONLINE SHOPPING EXPERIENCE

This study aimed to investigate the impact of eWOM credibility on trust and perceived risk and its effect on purchase intention with the online shopping experience as a moderator. The empirical data were collected from 247 e-commerce consumers in Indonesia through the distribution of online questionnaires. The PLS-SEM technique was applied to perform hypothesis testing. The results of this study showed that eWOM credibility has a positive and significant effect on consumer trust toward e-retailers and purchase intentions, but not on perceived risk. In addition, the results showed that consumer trust toward e-retailers has a positive and significant effect on purchase intention. Meanwhile, perceived risk has a negative and significant effect on purchase intention. Moreover, while online shopping experience positively moderated the relationship between perceived risk and purchase intention, online shopping experience did not moderate the relationship between consumer trust toward e-retailers and purchase intention. The findings of this study make a significant contribution both to business actors in e-commerce and to policymakers.JEL: M31

Designing a Chatbot Social Cue Configuration System

Social cues (e.g., gender, age) are important design features of chatbots. However, choosing a social cue design is challenging. Although much research has empirically investigated social cues, chatbot engineers have difficulties to access this knowledge. Descriptive knowledge is usually embedded in research articles and difficult to apply as prescriptive knowledge. To address this challenge, we propose a chatbot social cue configuration system that supports chatbot engineers to access descriptive knowledge in order to make justified social cue design decisions (i.e., grounded in empirical research). We derive two design principles that describe how to extract and transform descriptive knowledge into a prescriptive and machine-executable representation. In addition, we evaluate the prototypical instantiations in an exploratory focus group and at two practitioner symposia. Our research addresses a contemporary problem and contributes with a generalizable concept to support researchers as well as practitioners to leverage existing descriptive knowledge in the design of artifacts