Karafan Journal

Karafan Journal

A Perspective on Human Interaction and Artificial Intelligence: Bibliometric Analysis with Co-occurrence Technique

Document Type : Original Article

Authors
1 Department of Entrepreneurship Development, Faculty of Entrepreneurship, University of Tehran, Tehran, Iran.
2 Department of Technological Entrepreneurship, Faculty of Entrepreneurship, University of Tehran, Tehran, Iran.
Abstract
This research delves into the complex dynamics of human-artificial intelligence interaction, a field that has been growing exponentially in recent years. This study is mixed-methods (quantitative-qualitative) research in the field of human interaction and artificial intelligence. It includes a methodical review of articles from the past five years in the Web of Science database to identify and understand the evolving dynamics in this field. The current research employed bibliometric analysis with a co-occurrence technique. After examining related theories, a conceptual model corresponding to co-occurrence clusters is presented. The article provides an integrated analysis that identifies artificial intelligence and its interaction with humans, and its relationship to perception, technology acceptance, behavior, and satisfaction. It offers an overview of human-artificial intelligence interaction studies' current state and prospects. The findings of this study indicated a significant shift towards human-centered artificial intelligence, emphasizing the importance of cognitive and social dimensions in the design and implementation of artificial intelligence systems. These insights are invaluable to researchers and designers of enterprise systems who aim to align AI advancements with human-centered approaches and ensure that AI advancements are in harmony with human needs and values.
Keywords
Subjects

[1] Ren, F., & Bao, Y. (2020). A Review on Human-Computer Interaction and Intelligent Robots. International Journal of Information Technology & Decision Making, 19(01), 5-47. https://doi.org/10.1142/s0219622019300052
[2] Rai, A., Constantinides, P., & Sarker, S. (2019). Next generation digital platforms: toward human-AI hybrids. Management Information Systems quarterly, 43(1), iii-ix. https:/ /wrap.warwick.ac.uk/id/eprint/113653/
[3] Brynjolfsson, E., & Mitchell, T. (2017). What can machine learning do? Workforce implications. Science, 358(6370), 1530-1534. https://doi.org/10.1126/science.aap8062
[4] Li, N. L., & Zhang, P. (2005). The intellectual development of human-computer interaction research: A critical assessment of the MIS literature (1990-2002). Journal of the Association for information Systems, 6(11), 227-292. https://doi.org/10.17705/1jais.00070
[5] Rzepka, C., & Berger, B. (2018, December 13-16). User interaction with AI-enabled systems: A systematic review of IS research [Conference session]. Thirty Ninth International Conference on Information Systems, San Francisco, California. https://www.researc hgate.net/publication/329269262_User_Interaction_with_AI-enabled_Systems_A_ Systematic_Review_of_IS_Research
[6] Rapp, A. (2023). Human–Computer Interaction. In Oxford Research Encyclopedia of Psychology. Oxford University Press. https://doi.org/10.1093/acrefore/9780190236557.013.47
[7] Sivakumar, N., K. K, C., Easwaran, B., & Tabassum, H. (2023, May 11-12). Design And Analysis of Human Computer Interaction Using AI Intelligence [Conference session]. 2023 International Conference on Disruptive Technologies, Greater Noida, India. ht tps://doi.org/10.1109/ICDT57929.2023.10150705
[8] Sreedharan, S. (2023). Human-aware AI —A foundational framework for human–AI interaction. Artificial Intelligence Magazine, 44(4), 460-466. https://doi.org/10.1002/aaai.12142
[9] LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521(7553), 436-444. https://doi.org/10.1038/nature14539
[10] Horvitz, E. (1999, May 15-20). Principles of mixed-initiative user interfaces [Conference session]. Proceedings of the Special Interest Group on Computer-Human Interaction conference on Human Factors in Computing Systems, Pittsburgh, Pennsylvania, USA. https://doi.org/10.1145/302979.303030
[11] Fügener, A., Grahl, J., Gupta, A., & Ketter, W. (2022). Cognitive Challenges in Human–Artificial Intelligence Collaboration: Investigating the Path Toward Productive Delegation. Information Systems Research, 33(2), 678-696. https://doi.org/10.1287/isre.2021.1079
[12] Kim, J., Merrill Jr, K., & Collins, C. (2021). AI as a friend or assistant: The mediating role of perceived usefulness in social AI vs. functional AI. Telematics and Informatics, 64(1), 101694. https://doi.org/10.1016/j.tele.2021.101694
[13] Jin, S. V., & Youn, S. (2023). Social Presence and Imagery Processing as Predictors of Chatbot Continuance Intention in Human-AI-Interaction. International Journal of Human–Computer Interaction, 39(9), 1874-1886. https://doi.org/10.1080/1044731 8.2022.2129277
[14] Samanta, D. P. S., Patnaik, B., Satpathy, I., & Panda, L. (2024). A Bibliometric Analysis on Application of Artificial Intelligence (AI) in Workforce Management. In A. Khang, S. Rani, R. Gujrati, H. Uygun, & S. Gupta (Eds.), Designing Workforce Management Systems for Industry 4.0 (pp. 217-234). CRC Press. https://doi.org/10.1201/9781003 357070-14
[15] Jiang, J., Karran, A. J., Coursaris, C. K., Léger, P-M., & Beringer, J. (2023). A Situation Awareness Perspective on Human-AI Interaction: Tensions and Opportunities. International Journal of Human–Computer Interaction, 39(9), 1789-1806. https://doi.org/10.108 0/10447318.2022.2093863
[16] Buzydlowski, J. W. (2015). Co-occurrence analysis as a framework for data mining. Journal of Technology Research, 6, 1-19. https://www.semanticscholar.org/paper/Co-occurr ence-analysis-as-a-framework-for-data-Buzydlowski/f17632a4388a924ed406462c 7f1e374ab236df4a
[17] Hendijani Fard, M., Arasti, Z., Imanipour, N., & Chitsaz, E. (2024). Business Failure: A Bibliometric Co-occurrence and Content Analysis. Quarterly Scientific Journal of National University of Skills, 20(Special Issue), 35-62. https://doi.org/10.48301/kss a.2023.353332.2214
[18] Chandran, R. (2022). Human-Computer Interaction in Robotics: A bibliometric evaluation using Web of Science. Metaverse Basic and Applied Research, 1, 22. https://doi.org/ 10.56294/mr202222
[19] Liu, Y-X., Zhu, C., Wu, Z-X., Lu, L-J., & Yu, Y-T. (2022). A bibliometric analysis of the application of artificial intelligence to advance individualized diagnosis and treatment of critical illness. Annals of Translational Medicine, 10(16), 854. https://doi.org/10. 21037/atm-22-913
[20] Gao, F., Jia, X., Zhao, Z., Chen, C-C., Xu, F., Geng, Z., & Song, X. (2021). Bibliometric analysis on tendency and topics of artificial intelligence over last decade. Microsystem Technologies, 27(4), 1545-1557. https://doi.org/10.1007/s00542-019-04426-y
[21] Huang, P., Feng, Z., Shu, X., Wu, A., Wang, Z., Hu, T., Cao, Y., Tu, Y., & Li, Z. (2023). A bibliometric and visual analysis of publications on artificial intelligence in colorectal cancer (2002-2022). Frontiers in Oncology, 13, 1-15. https://doi.org/10.3389/fonc.2 023.1077539
[22] Hajizadeh, M., Alaeddini, M., & Reaidy, P. (2023). Bibliometric Analysis on the Convergence of Artificial Intelligence and Blockchain. In J. Prieto, F. L. Benítez Martínez, S. Ferretti, D. Arroyo Guardeño, & P. Tomás Nevado-Batalla (Eds.), Blockchain and Applications, 4th International Congress (pp. 334-344). Springer International Publishing. https:// doi.org/10.1007/978-3-031-21229-1_31
[23] Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. Management Information Systems quarterly, 13(3), 319-340. https://doi.org/10.2307/249008
[24] Hosseinpour, M., Fathi Zolmabadi, B., Heshmati, H., & Khodaei, A. (2023). Factors Accepting the Electronic Procurement System and User Satisfaction in Small and Medium Rural Businesses in Kermanshah Province. Quarterly Scientific Journal of National University of Skills, 20(Special Issue), 499-520. https://doi.org/10.48301/kssa.2021.276821.1424
[25] Emerson, R. M. (1976). Social Exchange Theory. Annual Review of Sociology, 2(1), 335-362. https://doi.org/10.1146/annurev.so.02.080176.002003
[26] Foa, E. B., & Foa, U. G. (1980). Resource Theory. In K. J. Gergen, M. S. Greenberg, & R. H. Willis (Eds.), Social Exchange: Advances in Theory and Research (pp. 77-94). Springer https://doi.org/10.1007/978-1-4613-3087-5_4
[27] Blau, P. M. (2017). Exchange and Power in Social Life (2 ed.). Transaction Publishers. https://doi.org/10.4324/9780203792643
[28] Cropanzano, R., & Mitchell, M. S. (2005). Social Exchange Theory: An Interdisciplinary Review. Journal of Management, 31(6), 874-900. https://doi.org/10.1177/01492063 05279602
[29] Etemadi, M., Chitsaz, E., & Abolghasemi Dehaghani, M. (2023, May 6). The Myth of Rewards and Creative Performance: Should Companies Use Incentives to Boost Creativity in Personnel Performance? [Conference session]. 3rd Iran Business Watch Conference, 2023, Tehran, Iran. https://civilica.com/doc/1720016/
[30] Coleman, J. S. (1990). Foundations of Social Theory. Belknap Press of Harvard University Press. https://books.google.com/books?id=XgC2AAAAIAAJ
[31] Skvoretz, J. (1998). Coercive Power in Social Exchange. Social Forces, 76(3), 1135-1137. https://doi.org/10.2307/3005707
[32] Etemadi, M., Chitsaz, E., & Abolghasemi Dehaghani, M. (2023, May 6). Unveiling the Complexity of the Reward, Creativity, and Performance Relationship: When Does Behavioral Theories Reward Backfire? [Conference session]. 3rd Iran Business Watch Conference, 2023, Tehran, Iran. https://civilica.com/doc/1720035/
[33] Tsarouchi, P., Makris, S., & Chryssolouris, G. (2016). Human–robot interaction review and challenges on task planning and programming. International Journal of Computer Integrated Manufacturing, 29(8), 916-931. https://doi.org/10.1080/0951192X.2015 .1130251
[34] Farouk, M. (2022). Studying human robot interaction and its characteristics. International Journal of Computations, Information and Manufacturing, 2(1), 38-49. https://doi.o rg/10.54489/ijcim.v2i1.73
[35] Etemadi, M., & Yadollahi Farsi, J. (2023, June 7). The potential of blockchain technology in building the decentralized world of Metaverse: A scientometric study and study clusters in the metaverse field [Conference session]. 7th International Conference on Interdisciplinary Studies in Management & Engineering, Tehran, Iran. http://dx.doi.org/10.2139/ssrn .4547579
[36] Zamora, J. (2017, October 17 - 20). I'm Sorry, Dave, I'm Afraid I Can't Do That: Chatbot Perception and Expectations [Conference session]. Proceedings of the 5th International Conference on Human Agent Interaction, Bielefeld, Germany. https://doi.org/10.11 45/3125739.3125766
Volume 21, Issue 3
Technical and Engineering
Autumn 2024
Pages 13-33

  • Receive Date 24 December 2023
  • Revise Date 24 April 2024
  • Accept Date 13 August 2024