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Close encounters with the virtual kind: Defining a human-virtual agent coexistence framework

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  • Arsenyan, Jbid
  • Mirowska, Agata
  • Piepenbrink, Anke

Abstract

Virtual agent research has evolved into a substantial body of work, albeit one with a fragmented structure and overlapping, and at times inconsistent, definitions and results. The current paper presents a computational literature review of 1865 academic journal publications and conference proceedings from 1995 to 2022 using Latent Dirichlet Allocation to understand the publication trends in the field, its intellectual structure, and how topics within virtual agent research have evolved and relate to each other. Our results point to a model of 16 topics as best representing the current state of the research landscape. We present descriptions of these topics, as well as topic dynamics and networks, in order to provide a clear picture of the current state of the field. We then organise these topics into a Human-Virtual Agent Coexistence Framework, identifying current trends and opportunities for future research.

Suggested Citation

  • Arsenyan, Jbid & Mirowska, Agata & Piepenbrink, Anke, 2023. "Close encounters with the virtual kind: Defining a human-virtual agent coexistence framework," Technological Forecasting and Social Change, Elsevier, vol. 193(C).
  • Handle: RePEc:eee:tefoso:v:193:y:2023:i:c:s0040162523003293
    DOI: 10.1016/j.techfore.2023.122644
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    1. Chiang, Ai-Hsuan & Trimi, Silvana & Lo, Yu-Ju, 2022. "Emotion and service quality of anthropomorphic robots," Technological Forecasting and Social Change, Elsevier, vol. 177(C).
    2. Khaksar, Seyed Mohammad Sadegh & Khosla, Rajiv & Chu, Mei Tai & Shahmehr, Fatemeh S., 2016. "Service Innovation Using Social Robot to Reduce Social Vulnerability among Older People in Residential Care Facilities," Technological Forecasting and Social Change, Elsevier, vol. 113(PB), pages 438-453.
    3. Guanghui Zhou & Chao Zhang & Zhi Li & Kai Ding & Chuang Wang, 2020. "Knowledge-driven digital twin manufacturing cell towards intelligent manufacturing," International Journal of Production Research, Taylor & Francis Journals, vol. 58(4), pages 1034-1051, February.
    4. Marilyn Giroux & Jungkeun Kim & Jacob C. Lee & Jongwon Park, 2022. "Artificial Intelligence and Declined Guilt: Retailing Morality Comparison Between Human and AI," Journal of Business Ethics, Springer, vol. 178(4), pages 1027-1041, July.
    5. Baabdullah, Abdullah M. & Alalwan, Ali Abdallah & Algharabat, Raed S. & Metri, Bhimaraya & Rana, Nripendra P., 2022. "Virtual agents and flow experience: An empirical examination of AI-powered chatbots," Technological Forecasting and Social Change, Elsevier, vol. 181(C).
    6. Rabassa, Valérie & Sabri, Ouidade & Spaletta, Claire, 2022. "Conversational commerce: Do biased choices offered by voice assistants’ technology constrain its appropriation?," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    7. Grün, Bettina & Hornik, Kurt, 2011. "topicmodels: An R Package for Fitting Topic Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 40(i13).
    8. Fosso Wamba, Samuel & Bawack, Ransome Epie & Guthrie, Cameron & Queiroz, Maciel M. & Carillo, Kevin Daniel André, 2021. "Are we preparing for a good AI society? A bibliometric review and research agenda," Technological Forecasting and Social Change, Elsevier, vol. 164(C).
    9. Ben Mimoun, Mohammed Slim & Poncin, Ingrid & Garnier, Marion, 2012. "Case study—Embodied virtual agents: An analysis on reasons for failure," Journal of Retailing and Consumer Services, Elsevier, vol. 19(6), pages 605-612.
    10. Stahl, Bernd Carsten & McBride, Neil & Wakunuma, Kutoma & Flick, Catherine, 2014. "The empathic care robot: A prototype of responsible research and innovation," Technological Forecasting and Social Change, Elsevier, vol. 84(C), pages 74-85.
    11. Tan, Si Ying & Taeihagh, Araz & Tripathi, Abhas, 2021. "Tensions and antagonistic interactions of risks and ethics of using robotics and autonomous systems in long-term care," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    12. Kumar, Naveen & Lee, Seul Chan, 2022. "Human-machine interface in smart factory: A systematic literature review," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    13. Zsófia Tóth & Robert Caruana & Thorsten Gruber & Claudia Loebbecke, 2022. "The Dawn of the AI Robots: Towards a New Framework of AI Robot Accountability," Journal of Business Ethics, Springer, vol. 178(4), pages 895-916, July.
    14. Naeini, Ali Bonyadi & Zamani, Mehdi & Daim, Tugrul U. & Sharma, Mahak & Yalcin, Haydar, 2022. "Conceptual structure and perspectives on “innovation management”: A bibliometric review," Technological Forecasting and Social Change, Elsevier, vol. 185(C).
    15. Nørskov, Sladjana & Damholdt, Malene F. & Ulhøi, John P. & Jensen, Morten Berg & Mathiasen, Mia Krogager & Ess, Charles M. & Seibt, Johanna, 2022. "Employers’ and applicants’ fairness perceptions in job interviews: using a teleoperated robot as a fair proxy," Technological Forecasting and Social Change, Elsevier, vol. 179(C).
    16. Yulia W. Sullivan & Samuel Fosso Wamba, 2022. "Moral Judgments in the Age of Artificial Intelligence," Journal of Business Ethics, Springer, vol. 178(4), pages 917-943, July.
    17. Kim, Daewon & Kim, Suwon, 2021. "A model for user acceptance of robot journalism: Influence of positive disconfirmation and uncertainty avoidance," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    18. Mahmud, Hasan & Islam, A.K.M. Najmul & Ahmed, Syed Ishtiaque & Smolander, Kari, 2022. "What influences algorithmic decision-making? A systematic literature review on algorithm aversion," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    19. Søraa, Roger Andre & Nyvoll, Pernille & Tøndel, Gunhild & Fosch-Villaronga, Eduard & Serrano, J. Artur, 2021. "The social dimension of domesticating technology: Interactions between older adults, caregivers, and robots in the home," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    20. Li, Jian & Huang, Jin-Song, 2020. "Dimensions of artificial intelligence anxiety based on the integrated fear acquisition theory," Technology in Society, Elsevier, vol. 63(C).
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