Communication with conversational agents (CA) has become increasingly important. It therefore is crucial to understand how individuals perceive interaction with CAs and how the personality of both the CA and the human can affect the interaction experience. As personality differences are manifested in language cues, we investigate whether different language style manifestations of extraversion lead to a more anthropomorphized perception (specifically perceived humanness and social presence) of the personality bots. We examine, whether individuals rate communication satisfaction of a CA similar to their own personality as higher (law of attraction). The results of our experiment indicate that highly extraverted CAs are generally better received in terms of social presence and communication satisfaction. Further, incorporating personality into CAs increases perceived humanness. Although no significant effects could be found in regard to the law of attraction, interesting findings about ambiverts could be made. The outcomes of the experiment contribute towards designing personality-adaptive CAs.
Millions of people experience mental health issues each year, increasing the necessity for health-related services. One emerging technology with the potential to help address the resulting shortage in health care providers and other barriers to treatment access are conversational agents (CAs). CAs are software-based systems designed to interact with humans through natural language. However, CAs do not live up to their full potential yet because they are unable to capture dynamic human behavior to an adequate extent to provide responses tailored to users’ personalities. To address this problem, we conducted a design science research (DSR) project to design personality-adaptive conversational agents (PACAs). Following an iterative and multi-step approach, we derive and formulate six design principles for PACAs for the domain of mental health care. The results of our evaluation with psychologists and psychiatrists suggest that PACAs can be a promising source of mental health support. With our design principles, we contribute to the body of design knowledge for CAs and provide guidance for practitioners who intend to design PACAs. Instantiating the principles may improve interaction with users who seek support for mental health issues.
ZusammenfassungDie Erwartungen von Kunden an Sach- und Dienstleistungen haben sich verändert. Einerseits stellen sie höhere Anforderungen in Bezug auf Qualität, Komfort und Personalisierung. Andererseits möchten sie gestaltend zur Erreichung dieser Werte beitragen. Um weiterhin am Markt konkurrieren zu können, müssen Unternehmen traditionelle Kunden- und Anbieterrollen ebenso hinter sich lassen, wie die Vorstellung, dass sie im Alleingang Innovationen schaffen zu können. Service-Ökosysteme werden in diesem Kontext zum Schlüssel innovativer Wertangebote und führen aktuelle Trends der Dienstleistungsentwicklung zusammen. In Symbiose mit digitalen Technologien werden sie zu einem attraktiven Instrument für die Schaffung von losen, heterogenen Partnernetzwerken, die gemeinsam innovative Dienstleistungen entwickeln und anbieten. Anhand von acht Fallbeispielen zeigt der vorliegende Beitrag auf, wie auch Unternehmen aus dem Bereich der personennahen Dienstleistungen dieses Instrument zur Aktivierung des eigenen Digitalisierungspotenzials heranziehen können. Einen Rahmen zur vergleichenden Analyse und Gestaltung kann hierbei die ‚Service Canvas‘, der vom Bundesministerium für Bildung und Forschung (BMBF) geförderten Begleitforschung BeDien, bieten. Betrachtungspunkte wie Individualisierung, Integration, Kollaboration und Digitale Services decken Stärken, Schwerpunkte und Entwicklungspotenziale von Service-Ökosystemen auf und geben so Anhaltspunkte, wie sich Digitalisierung als Grundlage für die Zusammenarbeit zielgerichtet einsetzen lässt.
Conversational agents (CAs)-software systems emulating conversations with humans through natural language-reshape our communication environment. As CAs have been widely used for applications requiring human-like interactions, a key goal in information systems (IS) research and practice is to be able to create CAs that exhibit a particular personality. However, existing research on CA personality is scattered across different fields and researchers and practitioners face difficulty in understanding the current state of the art on the design of CA personality. To address this gap, we systematically analyze existing studies and develop a framework on how to imbue CAs with personality cues and how to organize the underlying range of expressive variation regarding the Big Five personality traits. Our framework contributes to IS research by providing an overview of CA personality cues in verbal and non-verbal language and supports practitioners in designing CAs with a particular personality.
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