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Information Systems Frontiers
Erschienen in: Information Systems Frontiers 3/2022

10.12.2021

“Don’t Neglect the User!” – Identifying Types of Human-Chatbot Interactions and their Associated Characteristics

verfasst von: Thai Ha Nguyen, Lena Waizenegger, Angsana A. Techatassanasoontorn

Erschienen in: Information Systems Frontiers | Ausgabe 3/2022

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Abstract

Interactions with conversational agents (CAs) become increasingly common in our daily life. While research on human-CA interactions provides insights into the role of CAs, the active role of users has been mostly neglected. We addressed this void by applying a thematic analysis approach and analysed 1000 interactions between a chatbot and customers of an energy provider. Informed by the concepts of social presence and social cues and using the abductive logic, we identified six human-chatbot interaction types that differ according to salient characteristics, including direction, social presence, social cues of customers and the chatbot and customer effort. We found that bi-directionality, a medium degree of social presence and selected social cues used by the chatbot and customers are associated with desirable outcomes in which customers mostly obtain requested information. The findings help us understand the nature of human-CA interactions in a customer service context and inform the design and evaluation of CAs.
Vorheriger Artikel Design and Evaluation of a Conversational Agent for Facilitating Idea Generation in Organizational Innovation Processes
Nächster Artikel Voice Assistant vs. Chatbot – Examining the Fit Between Conversational Agents’ Interaction Modalities and Information Search Tasks

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Fußnoten
1
Rapp et al. (2021) conducted a systematic literature review with a focus on how users interact with text-based chatbots and provided a summary of chatbot domains of application (See Table 5 in their study). In another study, Chaves and Gerosa (2021) surveyed the literature and developed a conceptual model of social characteristics for chatbots. They also juxtaposed domains of applications and desirable social characteristics of chatbots identified in the literature (See Table 2 in their study).
 
2
Social cues are referred to as anthropomorphic design cues in some studies on CAs (e.g., Adam et al., 2020).
 
3
Social cues are presented with bold texts.
 
Literatur
Adam, M., Wessel, M., & Benlian, A. (2020). AI-based chatbots in customer service and their effects on user compliance. Electronic Markets, 31(2), 427–445.CrossRef
Adamopoulou, E., & Moussiades, L. (2020). Chatbots: History, technology, and applications. Machine Learning with Applications, 2, 100006.
Araujo, T. (2018). Living up to the chatbot hype: The influence of anthropomorphic design cues and communicative agency framing on conversational agent and company perceptions. Computers in Human Behavior, 85, 183–189.CrossRef
Biocca, F. (1997). The cyborg’s dilemma: Progressive embodiment in virtual environments. Journal of Computer-Mediated Communication, 3(2), JCMC324.
Biocca, F., Harms, C., & Burgoon, J. K. (2003). Toward a more robust theory and measure of social presence: Review and suggested criteria. Presence: Teleoperators & Virtual Environments, 12(5), 456–480.CrossRef
Bitner, J., Brown, S. W., & Meuter, M. L. (2000). Technology infusion in service encounters. Journal of the Academy of Marketing Science, 28(1), 138–149.CrossRef
Brandtzaeg, P. B., & Folstad, A. (2017). Why people use Chatbots. In International Conference on Internet Science (pp. 377–392).
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101.CrossRef
Brink, H. (1993). Validity and reliability in qualitative research. Curationis, 16(2), 35–38.CrossRef
Bulu, S. T. (2012). Place presence, social presence, co-presence, and satisfaction in virtual worlds. Computers & Education, 58(1), 154–161.CrossRef
Car, L. T., Dhinagaran, D. A., Kyaw, B. M., Kowatsch, T., Joty, S., Theng, Y. L., & Atun, R. (2020). Conversational agents in health care: Scoping review and conceptual analysis. Journal of Medical Internet Research, 22(8), e17158.CrossRef
Carolus, A., Schmidt, C., Schneider, F., Mayr, J., & Muench, R. (2018). Are people polite to smartphones? Lecture Notes in Computer Science, 10902, 500–511.CrossRef
Cassell, J. (2000). More than just another pretty face: Embodied conversational interface agents. Communications of the ACM, 43(4), 70–78.CrossRef
Chai, Y., & Liu, G. (2018). Utterance censorship of online reinforcement learning chatbot. In International Conference on Tools with Artificial Intelligence (pp. 358–362). IEEE.
Chaves, A. P., & Gerosa, M. A. (2021). How should my Chatbot interact? A Survey on social characteristics in human–chatbot interaction design. International Journal of Human-Computer Interaction, 37(8), 729–758.CrossRef
Choi, J., Lee, H. J., & Kim, Y. C. (2011). The influence of social presence on customer intention to reuse online recommender systems: The roles of personalisation and product type. International Journal of Electronic Commerce, 16(1), 129–154.CrossRef
Choque-Diaz, M., Armas-Aguirre, J., &, Shiguihara-Juarez, P. (2018). Cognitive technology model to enhanced academic support services with chatbots. In 2018 IEEE XXV International Conference on Electronics, Electrical Engineering and Computing (INTERCON) (pp. 1–4).
Ciechanowski, L., Przegalinska, A., Magnuski, M., & Gloor, P. (2019). In the shades of the uncanny valley: An experimental study of human-chatbot interaction. Future Generation Computer Systems, 92, 539–548.CrossRef
Denzin, N. K. (1970). The research act: A theoretical introduction to sociological methods. Aldine Publishing Co.
Diederich, S., Brendel, A. B., Lichtenberg, S., & Kolbe, L. (2019a). Design for fast request fulfillment or natural interaction? Insights from an experiment with a conversational agent. In Proceedings of the 27th European Conference on Information Systems (ECIS) (pp. 1–17).
Diederich, S., Janben-Müller, M., Brendel, A., & Morana, S. (2019b). Emulating empathetic behavior in online service encounters with sentiment-adaptive responses: Insights from an experiment with a conversational agent. In the 40th International Conference on Information Systems.
Diederich, S., Lembcke, T., Brendel, A. B., & Kolbe, L. M. (2020). Not human after all: Exploring the impact of response failure on user perception of anthropomorphic conversational service agents. In The 28th European Conference on Information Systems (ECIS2020) (pp. 110–126).
Diederich, S., Lembcke, T., Brendel, A. B., & Kolbe, L. (2021). Understanding the impact that response failure has on how users perceive anthropomorphic conversational service agents: Insights from an online experiment. AIS Transactions on Human-Computer Interaction, 13(1), 82–103.CrossRef
Dinakar, C., Aaltonen, V., Rämö, A., & Vilermo, M. (2010). Talk to me: The influence of audio quality on the perception of social presence. In Proceedings of the 24th BCS Interaction Specialist Group Conference.
Elvir, M., Gonzalez, A. J., Walls, C., & Wilder, B. (2017). Remembering a conversation – A conversational memory architecture for embodied conversational agents. Journal of Intelligent Systems, 26(1), 1–21.CrossRef
Feine, J., Gnewuch, U., Morana, S., & Maedche, A. (2019a). A taxonomy of social cues for conversational agents. International Journal of Human-Computer Studies, 132, 138–161.CrossRef
Feine, J., Morana, S., & Gnewuch, U. (2019b). Measuring service encounter satisfaction with customer service chatbots using sentiment analysis. In The 14th International Conference on Wirtschaftsinformatik (pp. 1115–1129).
Fernández, W. D. (2004). Using the Glaserian approach in grounded studies of emerging business practices. Electronic Journal of Business Research Methods, 2(2), 83–94.
Følstad, A., Nordheim, C. B., & Bjørkli, C. A. (2018). What makes users trust a chatbot for customer service? An exploratory interview study. In International Conference on Internet Science (pp. 194–208).
Gambino, A., Fox, J., & Ratan, R. A. (2020). Building a stronger CASA: Extending the computers are social actors paradigm. Human-Machine Communication, 1, 71–85.CrossRef
Gnewuch, U., Morana, S., Adam, M., & Maedche, A. (2018). Faster is not always better: Understanding the effect of dynamic response delays in human-chatbot interaction. In The 26th European Conference on Information Systems (ECIS2018), UK.
Goel, L., Johnson, N., Junglas, I., & Ives, B. (2013). Predicting users’ return to virtual worlds: A social perspective. Information Systems Journal, 23(1), 35–63.CrossRef
Goofman, E. (1963). Behavior in public places: Notes on the social organization of gatherings. Free Press.
Graesser, A. C., Li, H., & Forsyth, C. (2014). Learning by communicating in natural language with conversational agents. Current Directions in Psychological Science, 23(5), 374–380.CrossRef
Gunawardena, C. N. (1995). Social presence theory and implications for interaction and collaborative learning in computer conferences. International Journal of Educational Telecommunications, 1(2/3), 147–166.
Hess, T. J., Fuller, M., & Campbell, D. E. (2009). Designing interfaces with social presence: Using vividness and extraversion to create social recommendation agents. Journal of the Association for Information Systems, 10(12), 889–919.CrossRef
Hill, J., Ford, W. R., & Farreras, I. G. (2015). Real conversations with artificial intelligence: A comparison between human–human online conversations and human–chatbot conversations. Computers in Human Behavior, 49, 245–250.
Hurwitz, J. S., Kaufman, M., & Bowles, A. (2015). Cognitive computing and big data analytics. Wiley.
Janssen, A., Passlick, J., Cardona, D. R., & Breitner, M. H. (2020). Virtual assistance in any context: A taxonomy of design elements for domain-specific chatbots. Business and Information Systems Engineering, 62(3), 211–225.
Larivière, B., Bowen, D., Andreassen, T. W., Kunz, W., Sirianni, N. J., Voss, C., Wunderlich, N. V., & De Keyer, A. (2017). “Service encounter 2.0”: An investigation into the roles of technology, employees and customers. Journal of Business Research, 79, 238–246.CrossRef
Lee, S. A., & Liang, Y. (2019). Robotic foot-in-the-door: Using sequential-request persuasive strategies in human-robot interaction. Computers in Human Behavior, 90, 351–356.CrossRef
Lee, K. M., & Nass, C. (2003). Designing social presence of social actors in human computer interaction. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 289–296).
Lewicki, R. J., & Litterer, R. (1995). Negotiation. Irwin.
Li, M., & Mao, J. (2015). Hedonic and utilitarian? Exploring the impact of communication style alignment on user’s perception of virtual health advisory services. International Journal of Information Management, 35, 229–243.CrossRef
Liu, B., Xu, Z., Sun, C., Wang, B., Wang, Z., Wong, D. F., & Zhang, M. (2018). Content-oriented user modeling for personalized response ranking. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 26(1), 122–133.
Meuter, M. L., Ostrom, A. L., Roundtree, R. I., & Bitner, M. J. (2000). Self-service technologies: Understanding customer satisfaction with technology-based service encounters. Journal of Marketing, 64, 50–64.CrossRef
Michaud, L. N. (2018). Observations of a new chatbot: Drawing conclusions from early interactions with users. IT Professional, 20(5), 40–47.CrossRef
Moore, R. J., Ducheneaut, N., & Nickell, E. (2007). Doing virtually nothing: Awareness and accountability in massively multiplayer online worlds. Computer Supported Cooperative Work, 16(3), 265–305.
Morana, S., Gnewuch, U., Jung, D., & Granig, C. (2020). The effect of anthropomorphism on investment decision-making with robo-advisor chatbots. In The 28th European Conference on Information Systems (ECIS2020), Marrakech, Morocco.
Mori, M., MacDorman, K. F., & Kageki, N. (2012). The uncanny valley [from the field]. IEEE Robotics & Automation Magazine, 19(2), 98–100.CrossRef
Nass, C., & Moon, Y. (2000). Machines and mindlessness: Social responses to computers. Journal of Social Issues, 56(1), 81–103.CrossRef
Nass, C., & Steuer, J. (1993). Voices, boxes, and sources of messages: Computers and social actors. Human Communication Research, 19, 504–527.CrossRef
Nowak, K. L., & Biocca, F. (2003). The effect of the agency and anthropomorphism on users’ sense of telepresence, copresence, and social presence in virtual environments. Presence: Teleoperators & Virtual Environments, 12(5), 481–494.CrossRef
Nuruzzaman, M., & Hussain, O. K. (2018). A survey on chatbot implementation in customer service industry through deep neural networks. In 2018 IEEE 15th International Conference on E-Business Engineering (ICEBE) (pp. 54–61).
Oh, C. S., Bailenson, J. N., & Welch, G. F. (2018). A systematic review of social presence: Definition, antecedents, and implications. Frontiers in Robotics and AI, 5, 114.
Poser, M., Singh, S., & Bittner, E. A. (2021). Hybrid service recovery: Design for seamless inquiry handovers between conversational agents and human service agents. In The 54th Hawaii International Conference on System Sciences (pp. 1181–1190).
Ramesh, K., Ravishankaran, S., Joshi, A., & Chandrasekaran, K. (2017). A survey of design techniques for conversational agents. In International Conference on Information, Communication and Computing Technology (pp. 336–350).
Rapp, A., Curti, L., & Boldi, A. (2021). The human side of human-chatbot interaction: A systematic literature review of ten years of research on text-based chatbots. International Journal of Human-Computer Studies, 151, 1–24.CrossRef
Rettie, R. (2005). Presence and embodiment in mobile phone communication. PsychNology Journal, 3(1), 16–34.
Riva, G., & Mantovani, F. (2014). Extending the self through the tools and the others: A general framework for presence and social presence in mediated interactions. In G. Riva, J. Waterworth, & D. Murray (Eds.), Interacting with presence (pp. 9–31). De Gruyter Open Poland.
Salomonson, N., Allwood, J., Lind, M., & Alm, H. (2013). Comparing human-to-human and human-to-AEA communication in service encounters. Journal of Business Communication, 50(1), 87–116.
Sangaiah, A. K., Thangavelu, A., & Sundaram, V. M. (2018). Cognitive computing for big data systems over IoT: Frameworks, tools and applications. Springer.CrossRef
Sarker, S., Xiao, X., Beaulieu, T., & Lee, A. S. (2018). Learning from first-generation qualitative approaches in the IS discipline: An evolutionary view and some implications for authors and evaluators (PART 1/2). Journal of the Association for Information Systems, 19(8), 752–774.CrossRef
Schuetzler, R. M., Grimes, G. M., Giboney, J. S., & Nunamaker Jr., J. F. (2018). The influence of conversational agents on socially desirable responding. In 2018 Proceedings of the 51st Hawaii International Conference on System Sciences (pp. 283–292).
Schultze, U., & Brooks, J. A. M. (2019). An interactional view of social presence: Making the virtual other “real”. Information Systems Journal, 29(3), 707–737.CrossRef
Short, J., Williams, E., & Christie, B. (1976). The social psychology of telecommunications. Wiley.
Srinivasan, V., & Takayama, L. (2016). Help me please: Robot politeness strategies for soliciting help from people. In Proceedings of the SIGCHI ‘16 Human Factors in Computing Systems (pp. 4945–4955).
Valtolina, S., Barricelli, B. R., & Gaetano, S. D. (2019). Communicability of traditional interfaces VS chatbots in healthcare and smart home domains. Behaviour & Information Technology, 39(1), 108–132.CrossRef
Van Hoek, R., Aronsson, H., Kovács, G., & Spens, K. M. (2005). Abductive reasoning in logistics research. International Journal of Physical Distribution & Logistics Management, 35(2), 132–144.CrossRef
Wagner, K., Nimmermann, F., & Schramm-Klein, H. (2019). Is it human? The role of anthropomorphism as a driver for the successful acceptance of digital voice assistants. In Proceedings of the 52nd Hawaii International Conference on System Sciences (pp. 1386–1395).
Waizenegger, L., Seeber, I., Dawson, G., & Desouza, K. C. (2020). Conversational agents – Exploring generative mechanisms and second-hand effects of actualized technology affordances. In Proceedings of the 53rd Hawaii International Conference on System Sciences (pp. 5180–5189).
Walsham, G. (1995). The emergence of interpretivism in IS research. Information Systems Research, 6(4), 376–394.CrossRef
Xu, A., Liu, Z., Guo, Y., Sinha, V., & Akkiraju, R. (2017). A new chatbot for customer service on social media. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (pp. 3506–3510).
Yang, L., Qiu, M., Qu, C., Guo, J., Zhang, Y., Croft, W. B., Huang, J., & Chen, H. (2018). Response ranking with deep matching networks and external knowledge in information-seeking conversation systems. In The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval (pp. 245–254).
Zamora, J. (2017). I’m sorry, Dave, I’m afraid I can’t do that: Chatbot perception and expectations. In Proceedings of the 5th International Conference on Human Agent Interaction (pp. 253–260).
Zhao, S. (2003). Toward a taxonomy of copresence. Presence: Teleoperators & Virtual Environments, 12(5), 445–455.CrossRef
Zierau, N., Wambsganss, T., Janson, A., Schöbel, S., & Leimeister, J. M. (2020). The anatomy of user experience with conversational agents: A taxonomy and propositions of service clues. In The 41st International Conference on Information Systems (pp. 1–17).
Metadaten
Titel
“Don’t Neglect the User!” – Identifying Types of Human-Chatbot Interactions and their Associated Characteristics
verfasst von
Thai Ha Nguyen
Lena Waizenegger
Angsana A. Techatassanasoontorn
Publikationsdatum
10.12.2021
Verlag
Springer US
Erschienen in
Information Systems Frontiers / Ausgabe 3/2022
Print ISSN: 1387-3326
Elektronische ISSN: 1572-9419
DOI
https://doi.org/10.1007/s10796-021-10212-x

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