Toward a design theory for virtual companionship

References

• Abbass, H. A. (2019). Social integration of artificial intelligence: Functions, automation allocation logic and human-autonomy trust. Cognitive Computation, 11(2), 159–171. https://doi.org/10.1007/s12559-018-9619-0
   Web of Science ®Google Scholar
• Ahmad, R., Siemon, D., Gnewuch, U., & Robra-Bissantz, S. (2021) The benefits and caveats of personality-adaptive conversational agents in mental health care. AMCIS 2021 Proceedings
   Google Scholar
• Ahmad, R., Siemon, D., Gnewuch, U., & Robra-Bissantz, S. (2022). Designing personality-adaptive conversational agents for mental health care. Inf Syst Front. https://doi.org/10.1007/s10796-022-10254-9
   Google Scholar
• Al-Natour, S., Benbasat, I., & Centefelli, R. (2010) Trustworthy virtual advisors and enjoyable interactions: Designing for expressiveness and transparency. In: Proceedings of European Conference on information systems 2010
   Google Scholar
• Altman, I., & Taylor, D. A. (1973). Social penetration: The development of interpersonal relationships. Holt, Rinehart & Winston.
   Google Scholar
• Anderson, M., & Anderson, S. L. (2011). Machine ethics. Cambridge University Press.
   Google Scholar
• Ashleigh, M. J., Higgs, M., & Dulewicz, V. (2012). A new propensity to trust scale and its relationship with individual well-being: Implications for HRM policies and practices. Human Resource Management Journal, 22, 360–376.
   Web of Science ®Google Scholar
• Asikis, T., & Pournaras, E. (2020). Optimization of privacy-utility trade-offs under informational self-determination. Future Generation Computer Systems, 109, 488–499. https://doi.org/10.1016/j.future.2018.07.018
   Google Scholar
• Baumeister, R. F., & Leary, M. R. (1995). The need to belong: Desire for interpersonal attachments as a fundamental human motivation. Psychological Bulletin, 117(3), 497. https://doi.org/10.1037/0033-2909.117.3.497
   PubMed Web of Science ®Google Scholar
• Becker, C., Kopp, S., & Wachsmuth, I. (2007). Why emotions should be integrated into conversational agents. In Conversational informatics: An engineering approach (pp. 49–67).
   Google Scholar
• Benbasat, I., & Wang, W. (2005). Trust in and adoption of online recommendation agents. Journal of the Association for Information Systems, 6(3), 72–101. https://doi.org/10.17705/1jais.00065
   Google Scholar
• Benke, I., Gnewuch, U., & Maedche, A. (2022). Understanding the impact of control levels over emotion-aware chatbots. Computers in Human Behavior, 129, 107122. https://doi.org/10.1016/j.chb.2021.107122
   Web of Science ®Google Scholar
• Berscheid, E. (1999). The greening of relationship science. American Psychologist, 54, 260–266.
   PubMed Web of Science ®Google Scholar
• Bickmore, T. W., Caruso, L., Clough-Gorr, K., & Heeren, T. (2005). ‘It’s just like you talk to a friend’ relational agents for older adults. Interacting with Computers, 17(6), 711–735. https://doi.org/10.1016/j.intcom.2005.09.002
   Web of Science ®Google Scholar
• Bickmore, T. W., & Picard, R. W. (2005). Establishing and maintaining long-term human-computer relationships. ACM Trans Comput-Hum Interact, 12, 293–327.
   Google Scholar
• Bickmore, T., Trinh, H., Asadi, R., & Olafsson, S. (2018). Safety first: Conversational agents for health care. In R. J. Moore, M. H. Szymanski, R. Arar, & G.-J. Ren (Eds.), Studies in conversational UX design (pp. 33–57). Springer International Publishing.
   Google Scholar
• Blau, P. M. (1968). Social exchange. International Encyclopedia of the Social Sciences, 7, 452–457.
   Google Scholar
• Bødker, S., & Kyng, M. (2018). Participatory design that matters—facing the big issues. ACM Trans Comput-Hum Interact, 25(4), 1–4. https://doi.org/10.1145/3152421 31
   Google Scholar
• Brown, T. B., Mann, B., Ryder, N. et al. (2020). Language models are few-shot learners. arXiv:200514165 [cs.
   Google Scholar
• Bukowski, W. M., Hoza, B., & Boivin, M. (1993). Popularity, friendship, and emotional adjustment during early adolescence. New Directions for Child and Adolescent Development, 1993(60), 23–37. https://doi.org/10.1002/cd.23219936004
   Google Scholar
• Bukowski, W. M., Hoza, B., & Boivin, M. (1994). Measuring friendship quality during pre- and early adolescence: The development and psychometric properties of the friendship qualities scale. Journal of Social and Personal Relationships, 11(3), 471–484. https://doi.org/10.1177/0265407594113011
   Web of Science ®Google Scholar
• Cacioppo, J. T., & Patrick, W. (2008). Loneliness: Human nature and the need for social connection. W. W. Norton & Company.
   Google Scholar
• Carpenter, A. M., & Greene, K. (2015). Social penetration theory.
   Google Scholar
• Carruthers, P., & Smith, P. K. (1996). Theories of theories of mind. Cambridge University Press.
   Google Scholar
• Cassell, J., Bickmore, T., Billinghurst, M. et al (1999) Embodiment in Conversational Interfaces: Rea. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, New York, NY, USA, pp 520–527
   Google Scholar
• Chandra, L., Seidel, S., & Gregor, S. (2015) Prescriptive knowledge in is research: conceptualizing design principles in terms of materiality, action, and boundary conditions. In: 2015 48th Hawaii international conference on system sciences. pp 4039–4048
   Google Scholar
• 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. https://doi.org/10.1080/10447318.2020.1841438
   Web of Science ®Google Scholar
• Choudhury, M. D., Lee, M. K., Zhu, H., & Shamma, D. A. (2020). Introduction to this special issue on unifying human computer interaction and artificial intelligence. Human–Computer Interaction, 35(5–6), 355–361. https://doi.org/10.1080/07370024.2020.1744146
   Web of Science ®Google Scholar
• Clark, H. H., & Schaefer, E. F. (1987). Collaborating on contributions to conversations. Language and Cognitive Processes, 2(1), 19–41. https://doi.org/10.1080/01690968708406350
   Google Scholar
• Clark, H. H., & Brennan, S. E. (1991). Grounding in communication. In L. B. Resnick, J. Levine, & S. D. Behrend (Eds.), Perspectives on socially shared cognition (pp. 127–149). APA.
   Google Scholar
• Clark, H. H. (1992). Arenas of language use. University of Chicago Press.
   Google Scholar
• Clark, H. H. (1996). Using language. Cambridge University Press.
   Google Scholar
• Clark, L., Doyle, P., Garaialde, D. et al (2019a). The state of speech in HCI: Trends, themes and challenges. Interacting with Computers, 31, 349–371.
   Web of Science ®Google Scholar
• Clark, L., Pantidi, N., Cooney, O. et al (2019b). what makes a good conversation? Challenges in designing truly conversational agents. In: Proceedings of the 2019 chi conference on human factors in computing systems. Association for computing machinery, New York, NY, USA, pp 1–12
   Google Scholar
• Clark, L., Ofemile, A., & Cowan, B. R. (2021). Exploring verbal uncanny valley effects with vague language in computer speech. In B. Weiss, J. Trouvain, M. Barkat-Defradas, & J. J. Ohala (Eds.), Voice attractiveness: Studies on sexy, likable, and charismatic speakers (pp. 317–330). Springer.
   Google Scholar
• Collins, E., & Ghahramani, Z. (2021) LaMDA: Our breakthrough conversation technology. In: Google. Accessed 7 Sep 2021. https://blog.google/technology/ai/lamda/
   Google Scholar
• Cornelissen, J., Höllerer, M. A., & Seidl, D. (2021). What theory is and can be: forms of theorizing in organizational scholarship. Organization Theory, 2, 26317877211020330. https://doi.org/10.1177/26317877211020328
   Google Scholar
• Danilava, S., Busemann, S., & Schommer, C. (2012). Artificial conversational companions: A requirements analysis. 282–289.
   Google Scholar
• Dautenhahn, K. (2004) Robots we like to live with - a developmental perspective on a personalized, life-long robot companion. In: RO-MAN 2004. 13th IEEE international workshop on robot and human interactive communication (IEEE catalog No.04TH8759). pp 17–22
   Google Scholar
• Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
   Web of Science ®Google Scholar
• De Angeli, A., Lynch, P., & Johnson, G. (2001) Personifying the e-market: 8th TC13 IFIP International conference on human-computer interaction. Human-computer interaction, interact ’01 198–205
   Google Scholar
• de Visser, E. J., Monfort, S. S., McKendrick, R. et al (2016). Almost human: Anthropomorphism increases trust resilience in cognitive agents. Journal of Experimental Psychology. Applied, 22, 331–349. https://doi.org/10.1037/xap0000092
   PubMed Web of Science ®Google Scholar
• Deci, E. L., & Ryan, R. M. (1985). Intrıinsic motivation and self-deternination in human behaviour. Plenum.
   Google Scholar
• Demeure, V., Niewiadomski, R., & Pelachaud, C. (2011). How is believability of a virtual agent related to warmth, competence, personification, and embodiment? Presence, 20, 431–448. https://doi.org/10.1162/PRES_a_00065
   Google Scholar
• Diederich, S., Brendel, A. B., & Kolbe, L. M. (2019a) Towards a taxonomy of platforms for conversational agent design. In: Proceedings of the international conference on Wirtschaftsinformatik. p 16
   Google Scholar
• Diederich, S., Brendel, A. B., & Kolbe, L. M. (2019b) on conversational agents in information systems research: analyzing the past to guide future work. In: Proceedings of the international conference on Wirtschaftsinformatik. p 16
   Google Scholar
• Diederich, S., Brendel, A., Morana, S., & Kolbe, L. (2022). On the design of and interaction with conversational agents: an organizing and assessing review of human-computer interaction research. Journal of the Association for Information Systems, 23(1), 96–138. https://doi.org/10.17705/1jais.00724
   Web of Science ®Google Scholar
• Doyle, P. R., Edwards, J., Dumbleton, O. et al (2019) Mapping perceptions of humanness in intelligent personal assistant interaction. In: Proceedings of the 21st international conference on human-computer interaction with mobile devices and services. association for computing machinery, New York, NY, USA, pp 1–12
   Google Scholar
• Doyle, P. R., Clark, L., & Cowan, B. R. (2021) What do we see in them? Identifying dimensions of partner models for speech interfaces using a psycholexical approach. In: Proceedings of the 2021 CHI conference on human factors in computing systems. association for computing machinery, New York, NY, USA, pp 1–14
   Google Scholar
• Elshan, E., Zierau, N., Engel, C. et al. (2022). Understanding the design elements affecting user acceptance of intelligent agents: past, present and future. Inf Syst Front, https://doi.org/10.1007/s10796-021-10230-9
   Google Scholar
• Elson, J. S., Derrick, D., & Ligon, G. (2018) Examining trust and reliance in collaborations between humans and automated agents. In: Proceedings of Hawaii international conference on system sciences 2018
   Google Scholar
• Fehr, B. (1996). Friendship processes. SAGE.
   Google Scholar
• Feine, J., Gnewuch, U., Morana, S., & Maedche, A. (2019). A taxonomy of social cues for conversational agents. International Journal of Human-Computer Studies, S1071581918305238. https://doi.org/10.1016/j.ijhcs.2019.07.009
   Google Scholar
• Feine, J., Gnewuch, U., Morana, S., & Maedche, A. (2020). Gender bias in chatbot design. In A. Følstad, T. Araujo, S. Papadopoulos et al (Eds.), Chatbot research and design (pp. 79–93). Springer International Publishing.
   Google Scholar
• Fischer-Hübner, S., Angulo, J., Karegar, F., & Pulls, T. (2016). Transparency, privacy and trust – technology for tracking and controlling my data disclosures: Does this work? In S. M. Habib, J. Vassileva, S. Mauw, & M. Mühlhäuser (Eds.), Trust management X (pp. 3–14). Springer International Publishing.
   Google Scholar
• Fogg, B. J. (2002). Persuasive technology: Using computers to change what we think and do. Ubiquity, 2002. https://doi.org/10.1145/764008.763957
   Google Scholar
• Fox, J., & Gambino, A. (2021). “Relationship Development with Humanoid Social Robots: Applying Interpersonal Theories to Human/Robot Interaction,” _cyberpsychology, Behavior, and Social Networking_, Mary Ann Liebert. Inc., publishers. https://doi.org/10.1089/cyber.2020.0181
   Google Scholar
• Gnewuch, U., Morana, S., & Maedche, A. (2017) Towards designing cooperative and social conversational agents for customer service. In: Proceedings of the 38th international conference on information systems (ICIS)
   Google Scholar
• Gnewuch, U., Morana, S., Adam, M., & Maedche, A. (2018a) Faster is not always better: understanding the effect of dynamic response delays in human-chatbot interaction. In: proceedings of European conference on information systems 2018
   Google Scholar
• Gnewuch, U., Morana, S., Heckmann, C., & Maedche, A. (2018b) Designing conversational agents for energy feedback. In: International conference on design science research in information systems and technology. Springer, pp 18–33
   Google Scholar
• Gong, L. (2008). How social is social responses to computers? The function of the degree of anthropomorphism in computer representations. Computers in Human Behavior, 24, 1494–1509. https://doi.org/10.1016/j.chb.2007.05.007
   Web of Science ®Google Scholar
• Gouldner, A. W. (1960). The norm of reciprocity: A preliminary statement. American Sociological Review, 25, 161–178. https://doi.org/10.2307/2092623
   Web of Science ®Google Scholar
• Gregor, S. (2002). Design theory in information systems. In Australasian Journal of Information Systems (Vol. Vol. 10). https://doi.org/10.3127/ajis.v10i1.439.
   Google Scholar
• Gregor, S. (2006). The nature of theory in information systems. MIS Quarterly, 30(3), 611–642. https://doi.org/10.2307/25148742
   Web of Science ®Google Scholar
• Gregor, S., & Jones, D. (2007). The anatomy of a design theory. Journal of the Association for Information Systems, 8.
   Google Scholar
• Gregor, S., & Hevner, A. R. (2013). Positioning and presenting design science research for maximum impact. MIS Quarterly, 37(2), 337–355. https://doi.org/10.25300/MISQ/2013/37.2.01
   Web of Science ®Google Scholar
• Gregor, S., Kruse, L. C., & Seidel, S. (2020). Research perspectives: the anatomy of a design principle. Journal of the Association for Information Systems, 21. https://doi.org/10.17705/1jais.00649
   Google Scholar
• Guzman, A. (2017). Making AI Safe for Humans: A Conversation With Siri. In Socialbots and Their Friends (pp. 69–82). Routledge.
   Google Scholar
• Harvey, P. H., Currie, E., Daryanani, P., & Augusto, J. C. (2016). Enhancing student support with a virtual assistant. In G. Vincenti, A. Bucciero, & C. Vaz de Carvalho (Eds.), E-learning, E-education, and online training (pp. 101–109). Springer International Publishing.
   Google Scholar
• Hecht, M. L. (1978). The conceptualization and measurement of interpersonal communication satisfaction. Human Communication Research, 4, 253–264. https://doi.org/10.1111/j.1468-2958.1978.tb00614.x
   Google Scholar
• Heerink, M., Kröse, B., Evers, V., & Wielinga, B. (2010). Relating conversational expressiveness to social presence and acceptance of an assistive social robot. Virtual Reality, 14, 77–84. https://doi.org/10.1007/s10055-009-0142-1
   Web of Science ®Google Scholar
• Hevner, A., March, S. T., Park, J., & Ram, S. (2004). Design science in information systems research. MIS Quarterly, 28, 75–105. https://doi.org/10.2307/25148625
   Web of Science ®Google Scholar
• Hildebrand, C., & Bergner, A. (2021). Conversational robo advisors as surrogates of trust: Onboarding experience, firm perception, and consumer financial decision making. J of the Acad Mark Sci, 49, 659–676. https://doi.org/10.1007/s11747-020-00753-z
   Web of Science ®Google Scholar
• Hinde, R. A. (1979). Towards understanding relationships. press. Academic.
   Google Scholar
• Hobert, S. (2019) Say hello to ‘coding tutor’! Design and evaluation of a chatbot-based learning system supporting students to learn to program. ICIS 2019 Proceedings
   Google Scholar
• Homans, G. C. (1958). Social behavior as exchange. American Journal of Sociology, 63(6), 597–606. https://doi.org/10.1086/222355
   Web of Science ®Google Scholar
• Horton, D., & Wohl, R. R. (1956). Mass communication and para-social interaction. Psychiatry, 19, 215–229. https://doi.org/10.1080/00332747.1956.11023049
   PubMed Web of Science ®Google Scholar
• Hu, P., Lu, Y., & Gong, Y. (Yale). (2021). Dual humanness and trust in conversational AI: A person-centered approach. Computers in Human Behavior, 119, 106727. https://doi.org/10.1016/j.chb.2021.106727
   Web of Science ®Google Scholar
• Iivari, J. (2015). Distinguishing and contrasting two strategies for design science research. European Journal of Information Systems, 24(1), 107–115. https://doi.org/10.1057/ejis.2013.35
   Web of Science ®Google Scholar
• Iivari, J. (2019). A critical look at theories in design science research.
   Google Scholar
• Kanda, T., Hirano, T., Eaton, D., & Ishiguro, H. (2004). Interactive robots as social partners and peer tutors for children: A field trial. Human–Computer Interaction, 19, 61–84. https://doi.org/10.1080/07370024.2004.9667340
   Web of Science ®Google Scholar
• Kankanhalli, A., Tan, B. C. Y., & Wei, K.-K. (2005). Contributing knowledge to electronic knowledge repositories: An empirical investigation. MIS Quarterly, 29, 113–143.
   Web of Science ®Google Scholar
• Kaplan, A., & Haenlein, M. (2019). Siri, siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence. Business Horizons, 62, 15–25. https://doi.org/10.1016/j.bushor.2018.08.004
   Web of Science ®Google Scholar
• Kapp, K. M. (2012). The gamification of learning and instruction. Wiley San Francisco.
   Google Scholar
• Kelley, H. H., & Thibaut, J. W. (1978). Interpersonal relations: A theory of interdependence. John Wiley & Sons.
   Google Scholar
• Kim, K. J., Park, E., & Shyam Sundar, S. (2013). Caregiving role in human–robot interaction: A study of the mediating effects of perceived benefit and social presence. Computers in Human Behavior, 29, 1799–1806. https://doi.org/10.1016/j.chb.2013.02.009
   Web of Science ®Google Scholar
• Knijnenburg, B. P., & Willemsen, M. C. (2016). Inferring capabilities of intelligent agents from their external traits. ACM Trans Interact Intell Syst, 6(28), 1–28:25. https://doi.org/10.1145/2963106
   Google Scholar
• Krämer, N. C., Eimler, S., von der Pütten, A., & Payr, S. (2011). Theory of companions: What can theoretical models contribute to applications and understanding of human-robot interaction? Applied Artificial Intelligence, 25, 474–502. https://doi.org/10.1080/08839514.2011.587153
   Web of Science ®Google Scholar
• Krämer, N. C., von der Pütten, A., & Eimler, S. (2012). Human-agent and human-robot interaction theory: Similarities to and differences from human-human interaction. In M. Zacarias & J. V. de Oliveira (Eds.), Human-computer interaction: The agency perspective (pp. 215–240). Springer.
   Google Scholar
• Krämer, N. C., Rosenthal-von der Pütten, A. M., & Hoffmann, L. (2015). Social effects of virtual and robot companions. In The handbook of the psychology of communication technology (pp. 137–159). John Wiley & Sons, Ltd.
   Google Scholar
• Kuechler, B., & Vaishnavi, V. (2008). On theory development in design science research: Anatomy of a research project. European Journal of Information Systems, 17(5), 489–504. https://doi.org/10.1057/ejis.2008.40
   Web of Science ®Google Scholar
• Kuechler, W., & Vaishnavi, V. (2012). A framework for theory development in design science research: Multiple perspectives. Journal of the Association for Information Systems, 13(6), 395–423. https://doi.org/10.17705/1jais.00300
   Web of Science ®Google Scholar
• L’Abbate, M., Thiel, U., & Kamps, T. (2005) Can proactive behavior turn chatterbots into conversational agents? In: IEEE/WIC/ACM international conference on intelligent agent technology. pp 173–179
   Google Scholar
• Lankton, N., McKnight, D., & Tripp, J. (2015). Technology, humanness, and trust: Rethinking trust in technology. Journal of the Association for Information Systems, 16. https://doi.org/10.17705/1jais.00411.
   Google Scholar
• Lee, S., & Choi, J. (2017). Enhancing user experience with conversational agent for movie recommendation. Int J Hum-Comput Stud, 103, 95–105. https://doi.org/10.1016/j.ijhcs.2017.02.005
   Web of Science ®Google Scholar
• Lee, S. K., Kavya, P., & Lasser, S. (2021). Social interactions and relationships with an intelligent virtual agent. International Journal of Human-Computer Studies, 102608. https://doi.org/10.1016/j.ijhcs.2021.102608
   Google Scholar
• Li, Y., Tee, K. P., Ge, S. S., & Li, H. (2013). Building companionship through human-robot collaboration. In Social Robotics (pp. 1–7). Springer International Publishing.
   Google Scholar
• Luger, E., & Sellen, A. (2016) Like having a really bad PA: The gulf between user expectation and experience of conversational agents. In: Proceedings of the 2016 CHI conference on human factors in computing systems. ACM, pp 5286–5297
   Google Scholar
• Maedche, A., Morana, S., Schacht, S., Werth, D., & Krumeich, J. (2016). Advanced user assistance systems. Business & Information Systems Engineering, 58(5), 367–370. https://doi.org/10.1007/s12599-016-0444-2
   Web of Science ®Google Scholar
• March, S. T., & Smith, G. F. (1995). Design and natural science research on information technology. Decision Support Systems, 15(4), 251–266. https://doi.org/10.1016/0167-9236(94)00041-2
   Web of Science ®Google Scholar
• McCrae, R. R., & John, O. P. (1992). An introduction to the five-factor model and its applications. Journal of Personality, 60(2), 175–215. https://doi.org/10.1111/j.1467-6494.1992.tb00970.x
   PubMed Web of Science ®Google Scholar
• McTear, M., Callejas, Z., & Griol, D. (2016). The conversational interface (Vol. 10, pp. 978). Springer.
   Google Scholar
• McTear, M. F. (2017). The rise of the conversational interface: A new kid on the block? Lecture Notes in Computer Science 10341 LNAI, 38–49. https://doi.org/10.1007/978-3-319-69365-1_3
   Google Scholar
• McTear, M. (2018) Conversational modelling for ChatBots: Current approaches and future directions. Technical report, Ulster University
   Google Scholar
• Mendelson, M. J., & Aboud, F. (2012). McGill friendship questionnaire-respondent’s affection (MFQ-RA). Measurement Instrument Database for the Social Science.
   Google Scholar
• Meth, H., Mueller, B., University of Groningen, et al. (2015). Designing a requirement mining system. Journal of the Association for Information Systems, 16, 799–837
   Web of Science ®Google Scholar
• Miles, M. B., & Huberman, A. M. (1994). Qualitative data analysis: An expanded sourcebook. sage
   Google Scholar
• Möller, F., Guggenberger, T. M., & Otto, B. (2020). Towards a Method for Design Principle Development in Information Systems. In S. Hofmann, O. Müller, & M. Rossi (Eds.), Designing for digital transformation. Co-creating services with citizens and industry (pp. 208–220). Springer International Publishing.
   Google Scholar
• Moon, Y. (2000). Intimate exchanges: Using computers to elicit self-disclosure from consumers. Journal of Consumer Research, 26(4), 323–339. https://doi.org/10.1086/209566
   Web of Science ®Google Scholar
• Morana, S., Friemel, C., Gnewuch, U., Maedche, A., & Pfeiffer, J. (2017). Interaktion mit smarten Systemen — Aktueller Stand und zukünftige Entwicklungen im Bereich der Nutzerassistenz. Wirtschaftsinformatik & Management, 9(5), 42–51. https://doi.org/10.1007/s35764-017-0101-7
   Google Scholar
• Mori, M. (2012). The uncanny valley: The original essay by Masahiro Mori. In: IEEE Spectrum: Technology, Engineering, and Science News. Accessed 26 Jun 2019. https://spectrum.ieee.org/automaton/robotics/humanoids/the-uncanny-valley
   Google Scholar
• Murphy, M. (2019) This app is trying to replicate you. Quartz. Accessed 25 Jan 2022. https://qz.com/1698337/replika-this-app-is-trying-to-replicate-you/
   Google Scholar
• Nass, C., Steuer, J., & Tauber, E. R. (1994) Computers are social actors. In: Proceedings of the SIGCHI conference on human factors in computing systems. ACM, pp 72–78
   Google Scholar
• Nass, C., Moon, Y., Fogg, B. J., Reeves, B., & Dryer, D. C. (1995). Can computer personalities be human personalities? International Journal of Human-Computer Studies, 43(2), 223–239. https://doi.org/10.1006/ijhc.1995.1042
   Web of Science ®Google Scholar
• Nass, C., & Moon, Y. (2000). Machines and mindlessness: Social responses to computers. Journal of Social Issues, 56(1), 81–103. https://doi.org/10.1111/0022-4537.00153
   Web of Science ®Google Scholar
• Nißen, M., Selimi, D., Janssen, A. et al. (2021). See you soon again, chatbot? A design taxonomy to characterize user-chatbot relationships with different time horizons. Computers in Human Behavior:107043. https://doi.org/10.1016/j.chb.2021.107043
   Google Scholar
• Park, E., Jin, D., & Del Pobil Ap. (2012). The law of attraction in human-robot interaction. International Journal of Advanced Robotic Systems, 9, 35.
   Google Scholar
• Pfeuffer, N., Adam, M., Toutaoui, J. et al. (2019a). Mr. and Mrs. Conversational agent - gender stereotyping in judge-advisor systems and the role of egocentric bias. ICIS 2019 proceedings
   Google Scholar
• Pfeuffer, N., Benlian, A., Gimpel, H., & Hinz, O. (2019b). Anthropomorphic information systems. Bus Inf Syst Eng, 61, 523–533.
   Web of Science ®Google Scholar
• Porcheron, M., Fischer, J. E., Reeves, S., & Sharples, S. (2018). Voice interfaces in everyday life. In: Proceedings of the 2018 CHI conference on human factors in computing systems. association for computing machinery, New York, NY, USA, pp 1–12
   Google Scholar
• Premack, D., & Woodruff, G. (1978). Does the chimpanzee have a theory of mind? Behavioral and Brain Sciences, 1, 515–526.
   Web of Science ®Google Scholar
• Purao, S., Chandra Kruse, L., & Maedche, A. (2020). The origins of design principles: Where do … they all come from?
   Google Scholar
• Qiu, L., & Benbasat, I. (2009). Evaluating anthropomorphic product recommendation agents: A social relationship perspective to designing information systems. Journal of Management Information Systems, 25(4), 145–182. https://doi.org/10.2753/MIS0742-1222250405
   Web of Science ®Google Scholar
• Qiu, L., & Benbasat, I. (2010). A study of demographic embodiments of product recommendation agents in electronic commerce. International Journal of Human-Computer Studies, 68, 669–688. https://doi.org/10.1016/j.ijhcs.2010.05.005
   Web of Science ®Google Scholar
• Randrup, N., Druckenmiller, D., & Briggs, R. O. (2016) Philosophy of collaboration. In: System sciences (HICSS), 2016 49th Hawaii international conference on. IEEE, pp 898–907
   Google Scholar
• Ransbotham, S., Gerbert, P., Reeves, M. et al. (2018). Artificial intelligence in business gets real. MIT Sloan Management Review, 60280.
   Google Scholar
• Rawlins, W. (2017). Friendship matters. Routledge.
   Google Scholar
• Reeves, S., Porcheron, M., & Fischer, J. (2018). “This is not what we wanted”: Designing for conversation with voice interfaces. Interactions, 26, 46–51. https://doi.org/10.1145/3296699
   Google Scholar
• Rheu, M., Shin, J. Y., Peng, W., & Huh-Yoo, J. (2021). Systematic review: Trust-building factors and implications for conversational agent design. International Journal of Human–Computer Interaction, 37, 81–96. https://doi.org/10.1080/10447318.2020.1807710
   Web of Science ®Google Scholar
• Robert, L. P., Pierce, C., Marquis, L., Kim, S., & Alahmad, R. (2020). Designing fair AI for managing employees in organizations: A review, critique, and design agenda. Human–Computer Interaction, 35(5–6), 545–575. https://doi.org/10.1080/07370024.2020.1735391
   Web of Science ®Google Scholar
• Rook, K. S. (1987). Social support versus companionship: Effects on life stress, loneliness, and evaluations by others. Journal of Personality and Social Psychology, 52(6), 1132–1147. https://doi.org/10.1037/0022-3514.52.6.1132
   PubMed Web of Science ®Google Scholar
• Rotter, J. B. (1980). Interpersonal trust, trustworthiness, and gullibility. American Psychologist, 35, 1–7.
   Web of Science ®Google Scholar
• Rzepka, C., & Berger, B. (2018) User interaction with AI-enabled systems: A systematic review of IS research. ICIS 2018 Proceedings
   Google Scholar
• Saffarizadeh, K., Boodraj, M., & Alashoor, T. M. (2017). Conversational assistants: Investigating privacy concerns, trust, and self-disclosure. In: ICIS 2017 Proceedings
   Google Scholar
• Saldaña, J. (2015). The coding manual for qualitative researchers. SAGE.
   Google Scholar
• Sandberg, J., & Alvesson, M. (2021). Meanings of theory: Clarifying theory through typification. Journal of Management Studies, 58, 487–516. https://doi.org/10.1111/joms.12587
   Web of Science ®Google Scholar
• Schroeder, J., & Schroeder, M. (2018). Trusting in machines: How mode of interaction affects willingness to share personal information with machines. In: Proceedings of the 51st Hawaii international conference on system sciences
   Google Scholar
• Seeber, I., Bittner, E., Briggs, R. O. et al. (2019). Machines as teammates: A research Agenda on AI in team collaboration. Information & Management: 103174. https://doi.org/10.1016/j.im.2019.103174
   Google Scholar
• Seeger, A.-M., Pfeiffer, J., & Heinzl, A. (2018) Designing anthropomorphic conversational agents: Development and empirical evaluation of a design framework. In: ICIS 2018 Proceedings
   Google Scholar
• Seymour, M., Riemer, K., & Kay, J. (2018). Actors, avatars and agents: Potentials and implications of natural face technology for the creation of realistic visual presence. Journal of the Association for Information Systems, 19.
   Google Scholar
• Seymour, M., Yuan, L., Dennis, A., & Riemer, K. (2019). Crossing the uncanny valley? Understanding affinity, trustworthiness, and preference for more realistic virtual humans in immersive environments. In: HICSS 2019 Proceedings
   Google Scholar
• Seymour, M., Yuan, L., Dennis, A., & Riemer, K. (2021). Have we crossed the uncanny valley? Understanding affinity, trustworthiness, and preference for realistic digital humans in immersive environments. Journal of the Association for Information Systems, 22. https://doi.org/10.17705/1jais.00674.
   Google Scholar
• Shah, H., Warwick, K., Vallverdú, J., & Wu, D. (2016). Can machines talk? Comparison of Eliza with modern dialogue systems. Computers in Human Behavior, 58, 278–295. https://doi.org/10.1016/j.chb.2016.01.004
   Web of Science ®Google Scholar
• Shapiro, S. S., & Wilk, M. B. (1965). An analysis of variance test for normality (complete samples). Biometrika, 52, 591–611.
   Web of Science ®Google Scholar
• Shawar, B. A., & Atwell, E. (2007). Chatbots: Are they really useful? In: Ldv forum. pp 29–49
   Google Scholar
• Siemon, D., Becker, F., Eckardt, L., & Robra-Bissantz, S. (2017). One for all and all for one - towards a framework for collaboration support systems. Education and Information Technologies. https://doi.org/10.1007/s10639-017-9651-9
   Google Scholar
• Siemon, D., & Jusmann, S. (2021). Preferred appearance of embodied conversational agents in knowledge management. AMCIS 2021 Proceedings
   Google Scholar
• Sin, J., & Munteanu, C. (2020). An empirically grounded sociotechnical perspective on designing virtual agents for older adults. Human–Computer Interaction, 35, 481–510. https://doi.org/10.1080/07370024.2020.1731690
   Web of Science ®Google Scholar
• Skjuve, M., Følstad, A., Fostervold, K. I., & Brandtzaeg, P. B. (2021). My chatbot companion - A study of human-chatbot relationships. International Journal of Human-Computer Studies, 149, 102601. https://doi.org/10.1016/j.ijhcs.2021.102601
   Web of Science ®Google Scholar
• Söllner, M., Hoffmann, A., Hoffmann, H., & Leimeister, J. M. (2012). Vertrauensunterstützung für sozio-technische ubiquitäre Systeme. Z Betriebswirtsch, 82(4), 109–140. https://doi.org/10.1007/s11573-012-0584-x
   Google Scholar
• Söllner, M., Hoffmann, A., & Leimeister, J. M. (2016). Why different trust relationships matter for information systems users. European Journal of Information Systems, 25, 274–287. https://doi.org/10.1057/ejis.2015.17
   Web of Science ®Google Scholar
• Solove, D. J. (2004). The digital person: technology and privacy in the information age. NYU Press.
   Google Scholar
• Sprecher, S. (1986). The relation between inequity and emotions in close relationships. Social Psychology Quarterly, 49, 309–321. https://doi.org/10.2307/2786770
   Web of Science ®Google Scholar
• Stever, G. S. (2017). Parasocial theory: Concepts and measures. The International Encyclopedia of Media Effects. American Cancer Society, 1–12.
   Google Scholar
• Strohmann, T., Siemon, D., & Robra-Bissantz, S. (2019). Designing virtual in-vehicle assistants: Design guidelines for creating a convincing user experience. AIS Transactions on Human-Computer Interaction, 11, 54–78. https://doi.org/10.17705/1thci.00113
   Google Scholar
• Sunyaev, A., Dehling, T., Taylor, P. L., & Mandl, K. D. (2015). Availability and quality of mobile health app privacy policies. Journal of the American Medical Informatics Association, 22(e1), e28–e33. https://doi.org/10.1136/amiajnl-2013-002605
   PubMedGoogle Scholar
• Svennevig, J. (2000). Getting acquainted in conversation: A study of initial interactions. John Benjamins Publishing.
   Google Scholar
• Ta, V., Griffith, C., Boatfield, C., Wang, X., Civitello, M., Bader, H., DeCero, E., & Loggarakis, A. (2020). User experiences of social support from companion chatbots in everyday contexts: Thematic analysis. Journal of Medical Internet Research, 22(3), e16235. https://doi.org/10.2196/16235
   PubMed Web of Science ®Google Scholar
• Taddei, S., & Contena, B. (2013). Privacy, trust and control: Which relationships with online self-disclosure? Computers in Human Behavior, 29(3), 821–826. https://doi.org/10.1016/j.chb.2012.11.022
   Web of Science ®Google Scholar
• Tavanapour, N., Poser, M., & Bittner, E. A. C. (2019) Supporting the idea generation process in citizen participation - toward an interactive system with a conversational agent as facilitator. ECIS 2019 Proceedings 18
   Google Scholar
• Thuan, N., Drechsler, A., & Antunes, P. (2019). Construction of design science research questions. Communications of the Association for Information Systems, 44. https://doi.org/10.17705/1CAIS.04420
   Google Scholar
• Tsiourti, C. (2018). Artificial agents as social companions: Design guidelines for emotional interactions. University of Geneva.
   Google Scholar
• Turilli, M., & Floridi, L. (2009). The ethics of information transparency. Ethics and Information Technology, 11(2), 105–112. https://doi.org/10.1007/s10676-009-9187-9
   Web of Science ®Google Scholar
• Turkle, S. (2010). In good company? Close Engagements with Artificial Companions. John Benjamins, 3–10.
   Google Scholar
• Vardoulakis, L. P., Ring, L., Barry, B. et al. (2012). Designing relational agents as long term social companions for older adults. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 7502 LNAI:289–302. https://doi.org/10.1007/978-3-642-33197-8-30
   Google Scholar
• Vaswani, A., Shazeer, N., Parmar, N. et al. (2017). Attention is all you need. In Advances in neural information processing systems. Curran associates. Inc.
   Google Scholar
• Venable, J., Pries-Heje, J., & Baskerville, R. (2016). FEDS: A framework for evaluation in design science research. European Journal of Information Systems, 25(1), 77–89. https://doi.org/10.1057/ejis.2014.36
   Web of Science ®Google Scholar
• Venkatesh, V., Morris, M. G., Davis, D., & Davis, F. D. User acceptance of information technology: Toward a unified view. (2003). MIS Quarterly, 27(3), 425. 425–478. https://doi.org/10.2307/30036540
   Web of Science ®Google Scholar
• Venkatesh, V., Brown, S. A., & Bala, H. (2013). Bridging the qualitative-quantitative divide: guidelines for conducting mixed methods research in information systems. MIS Quarterly, 37(1), 21–54. https://doi.org/10.25300/MISQ/2013/37.1.02
   Web of Science ®Google Scholar
• Veruggio, G., Operto, F., & Bekey, G. (2016). Roboethics: Social and ethical implications. In Springer handbook of robotics (pp. 2135–2160). Springer.
   Google Scholar
• Walls, J. G., Widmeyer, G. R., & El Sawy, O. A. (1992). Building an information system design theory for vigilant EIS. Information Systems Research, 3(1), 36–59. https://doi.org/10.1287/isre.3.1.36
   Web of Science ®Google Scholar
• Walster, E., Walster, G. W., & Berscheid, E. (1978). Equity: Theory and research. https://doi.org/10.1007/BF01542062
   Google Scholar
• Wambsganss, T., Janson, A., Soellner, M., & Leimeister, J. M. (2021) AI-based argumentation tutoring – a novel system class to improve learners’ Argumentation Skills. Proceedings 2021:10233. https://doi.org/10.5465/AMBPP.2021.10233abstract
   Google Scholar
• Webster, J., & Watson, R. T. (2002). Analyzing the past to prepare for the future: Writing a literature review. MIS Quarterly, xiii–xxiii.
   Web of Science ®Google Scholar
• Weizenbaum, J. (1966). ELIZA—a computer program for the study of natural language communication between man and machine. Communications of the ACM, 9(1), 36–45. https://doi.org/10.1145/365153.365168
   Web of Science ®Google Scholar
• Wilks, Y. (2005). Artificial companions. Lecture Notes in Computer Science, 36–45.
   Google Scholar
• Winkle, K., Melsión, G. I., McMillan, D., & Leite, I. (2021) Boosting robot credibility and challenging gender norms in responding to abusive behaviour: a case for feminist robots. In: Companion of the 2021 ACM/IEEE international conference on human-robot interaction. Association for computing machinery, New York, NY, USA, pp 29–37
   Google Scholar
• Woolf, B. P., Arroyo, I., & Muldner, K. (2010). The effect of motivational learning companions on low achieving students and students with disabilities. In V. Aleven, J. Kay, J. Mostow et al (Eds.), Intelligent tutoring systems (pp. 327–337). Springer.
   Google Scholar
• Xiao, J., Stasko, J., & Catrambone, R. (2007) The role of choice and customization on users’ interaction with embodied conversational agents: Effects on perception and performance. In: Proceedings of the SIGCHI conference on human factors in computing systems. Association for computing machinery, New York, NY, USA, pp 1293–1302
   Google Scholar
• Young, J. E., Hawkins, R., Sharlin, E., & Igarashi, T. (2008). Toward acceptable domestic robots: Applying insights from social psychology. International Journal of Social Robotics, 1(1), 95. https://doi.org/10.1007/s12369-008-0006-y
   Google Scholar
• Yu, H., Shen, Z., Miao, C. et al. (2018). Building ethics into artificial intelligence. In: Proceedings of the 27th international joint conference on artificial intelligence
   Google Scholar
• Zhou, L., Gao, J., Li, D., & Shum, H.-Y. (2020). The design and implementation of XiaoIce, an empathetic social chatbot. Computational Linguistics, 46(1), 53–93. https://doi.org/10.1162/coli_a_00368
   Web of Science ®Google Scholar