Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content

Persuasion-Building Fundamental Premises and Implications for Conversational Agents: A Conceptual Model in Captology

  • Conference paper
  • First Online:
Persuasive Technology (PERSUASIVE 2023)

Abstract

In the area of captology, computers as persuasive technology, conversational agent or dialogue system represent an interactive computing product as a key to changing people’s viewpoints. Our former original experimental research addressed that a virtual agent’s positive facial expressions and near-distance camera angle successfully influence participants’ thoughts during an experiment. However, fragmentation in this growing topic led to theoretical confusion. To move the field forward, this paper uncovers the evidence-based elements as the standard compliance for designing the persuasive conversational agent. First, the fundamental premises, implications, constructs, and indicators from our previous original research were generated. Second, a theory synthesis from related articles on the interaction between virtual agents to humans, with the aim of persuading, was analyzed. Thus, it derives twelve fundamental premises, two implications, three main constructs, and fifteen indicators. Third, a model elaborates on the relationships between these constructs and indicators was developed. Its foundation is based on the three related concepts of the Persuasion Knowledge Model, Stimulus-Organism-Response Theory, Fogg’s Captology Framework, and one measurement model of Partial Least Square Structural Equation Modeling. Hence, the theory synthesis provides the basis for inventing the proposed conceptual model, called the Agent-Subject Persuasion Model (ASPM), which emphasizes the originality of this research.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 59.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 79.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Al Mahmud, A., Dadlani, P., Mubin, O., Shahid, S., Midden, C., Moran, O.: iParrot: towards designing a persuasive agent for energy conservation. In: de Kort, Y., IJsselsteijn, W., Midden, C., Eggen, B., Fogg, B.J. (eds.) PERSUASIVE 2007. LNCS, vol. 4744, pp. 64–67. Springer, Heidelberg (2007). https://doi.org/10.1007/978-3-540-77006-0_8

    Chapter  Google Scholar 

  2. Albaina, I.M., Visser, T., Van Der Mast, C.A., Vastenburg, M.H.: Flowie: a persuasive virtual coach to motivate elderly individuals to walk. In: 2009 3rd International Conference on Pervasive Computing Technologies for Healthcare, pp. 1–7. IEEE (2009)

    Google Scholar 

  3. Amir, O., Kamar, E., Kolobov, A., Grosz, B.: Interactive teaching strategies for agent training. In: Proceedings of IJCAI 2016 (2016)

    Google Scholar 

  4. Andrews, P.Y.: System personality and persuasion in human-computer dialogue. ACM Trans. Interact. Intell. Syst. 2(2) (2012). https://doi.org/10.1145/2209310.2209315

  5. Anggia, P., Sensuse, D.I., Sucahyo, Y.G., Rohajawati, S.: Identifying critical success factors for knowledge management implementation in organization: a survey paper. In: 2013 International Conference on Advanced Computer Science and Information Systems (ICACSIS), pp. 83–88. IEEE (2013)

    Google Scholar 

  6. Bini, S.A.: Artificial intelligence, machine learning, deep learning, and cognitive computing: what do these terms mean and how will they impact health care? J. Arthroplasty 33(8), 2358–2361 (2018)

    Article  Google Scholar 

  7. Blanthorne, C., Jones-Farmer, L.A., Almer, E.D.: Why you should consider sem: a guide to getting started. In: Advances in Accounting Behavioral Research. Emerald Group Publishing Limited (2006)

    Google Scholar 

  8. Bradshaw, J.M.: An introduction to software agents. Softw. Agents 4, 3–46 (1997)

    Google Scholar 

  9. Decock, S., De Clerck, B., Lybaert, C., Plevoets, K.: Testing the various guises of conversational human voice: the impact of formality and personalization on customer outcomes in online complaint management. J. Internet Comm. 20(1), 1–24 (2021)

    Article  Google Scholar 

  10. Dormann, C.: Designing electronic shops, persuading consumers to buy. In: Proceedings of the 26th Euromicro Conference. EUROMICRO 2000. Informatics: Inventing the Future, vol. 2, pp. 140–147. IEEE (2000)

    Google Scholar 

  11. Etzioni, O., Weld, D.S.: Intelligent agents on the internet: fact, fiction, and forecast. IEEE Expert 10(4), 44–49 (1995)

    Article  Google Scholar 

  12. Fogg, B.J.: Creating persuasive technologies: an eight-step design process. In: Proceedings of the 4th International Conference on Persuasive Technology, pp. 1–6 (2009)

    Google Scholar 

  13. Fogg, B.J.: Captology: the study of computers as persuasive technologies. In: CHI 98 Conference Summary on Human Factors in Computing Systems, p. 385 (1998)

    Google Scholar 

  14. Fogg, B.J.: Persuasive computers: perspectives and research directions. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 225–232 (1998)

    Google Scholar 

  15. Fogg, B.J.: Persuasive technology: using computers to change what we think and do. Ubiquity 2002(December), 2 (2002)

    Article  Google Scholar 

  16. Fossa, F., Sucameli, I.: Gender bias and conversational agents: an ethical perspective on social robotics. Sci. Eng. Ethics 28(3), 1–23 (2022)

    Google Scholar 

  17. Franklin, S., Graesser, A.: Is it an agent, or just a program?: a taxonomy for autonomous agents. In: International Workshop on Agent Theories, Architectures, and Languages, pp. 21–35. Springer, Heidelberg (1996). https://doi.org/10.1007/bfb0013570

  18. Friestad, M., Wright, P.: The persuasion knowledge model: how people cope with persuasion attempts. J. Cons. Res. 21(1), 1–31 (1994)

    Article  Google Scholar 

  19. Hair Jr, J.F., Hult, G.T.M., Ringle, C.M., Sarstedt, M., Danks, N.P., Ray, S.: Partial least squares structural equation modeling (pls-sem) using r: a workbook (2021)

    Google Scholar 

  20. Hidayanto, A.N., Ovirza, M., Anggia, P., Budi, N.F.A., Phusavat, K.: The roles of electronic word of mouth and information searching in the promotion of a new e-commerce strategy: a case of online group buying in Indonesia. J. Theor. Appl. Electron. Commer. Res. 12(3), 69–85 (2017)

    Article  Google Scholar 

  21. Hui, C.: Personality’s influence on the relationship between online word-of-mouth and consumers’ trust in shopping website. J. Softw. 6(2), 265–272 (2011)

    Google Scholar 

  22. Jaakkola, E.: Designing conceptual articles: four approaches. AMS Rev. 10(1–2), 18–26 (2020)

    Article  Google Scholar 

  23. Jani, D., Han, H.: Influence of environmental stimuli on hotel customer emotional loyalty response: testing the moderating effect of the big five personality factors. Int. J. Hosp. Manag. 44, 48–57 (2015)

    Article  Google Scholar 

  24. Johnson, M., Ghuman, P.: Blindsight: The (Mostly) Hidden Ways Marketing Reshapes Our Brains. BenBella Books (2020)

    Google Scholar 

  25. Kantharaju, R.B., De Franco, D., Pease, A., Pelachaud, C.: Is two better than one? effects of multiple agents on user persuasion. In: Proceedings of the 18th International Conference on Intelligent Virtual Agents, pp. 255–262 (2018)

    Google Scholar 

  26. Khan, R.F., Sutcliffe, A.: Attractive agents are more persuasive. Int. J. Hum.-Comput. Interact. 30(2), 142–150 (2014)

    Article  Google Scholar 

  27. Kim, M.J., Lee, C.K., Jung, T.: Exploring consumer behavior in virtual reality tourism using an extended stimulus-organism-response model. J. Travel Res. 59(1), 69–89 (2020)

    Article  Google Scholar 

  28. Kok, J.N., Boers, E.J., Kosters, W.A., Van der Putten, P., Poel, M.: Artificial intelligence: definition, trends, techniques, and cases. Artif. Intell. 1, 270–299 (2009)

    Google Scholar 

  29. Kuss, P., Leenes, R.: The ghost in the machine-emotionally intelligent conversational agents and the failure to regulate ‘deception by design’. SCRIPTed 17, 320 (2020)

    Article  Google Scholar 

  30. Liu, S., Helfenstein, S., Wahlstedt, A.: Social psychology of persuasion applied to human agent interaction. Hum. Technol. Interdisc. J. Hum. ICT Environ. (2008)

    Google Scholar 

  31. Looije, R., Neerincx, M.A., Cnossen, F.: Persuasive robotic assistant for health self-management of older adults: design and evaluation of social behaviors. Int. J. Hum.-Comput. Stud. 68(6), 386–397 (2010)

    Article  Google Scholar 

  32. Lugrin, B.: Introduction to Socially Interactive Agents, 1 edn, p. 1–20. Association for Computing Machinery, New York (2021). https://doi.org/10.1145/3477322.3477324

  33. MacInnis, D.J.: A framework for conceptual contributions in marketing. J. Mark. 75(4), 136–154 (2011)

    Article  Google Scholar 

  34. Moulik, S.: DIL-A Conversational Agent for Heart Failure Patients. Ph.D. thesis, The Claremont Graduate University (2019)

    Google Scholar 

  35. Mower, E., Black, M.P., Flores, E., Williams, M., Narayanan, S.: Rachel: design of an emotionally targeted interactive agent for children with autism. In: 2011 IEEE International Conference on Multimedia and Expo, pp. 1–6. IEEE (2011)

    Google Scholar 

  36. Norman, W.T.: Toward an adequate taxonomy of personality attributes: replicated factor structure in peer nomination personality ratings. J. Abnorm. Soc. Psychol. 66(6), 574 (1963)

    Article  Google Scholar 

  37. Nwana, H.S.: Software agents: an overview. Knowl. Eng. Rev. 11(3), 205–244 (1996)

    Article  Google Scholar 

  38. Palmatier, R.W., Houston, M.B., Hulland, J.: Review articles: Purpose, process, and structure (2018)

    Google Scholar 

  39. Pinkie, A., Kaoru, S.: 3d real-time conversational virtual agents system: do facial expressions and camera angles persuade human? In: The 2023 International Conference on Artificial Life and Robotics (2023)

    Google Scholar 

  40. Rajaguru, R.: Motion picture-induced visual, vocal and celebrity effects on tourism motivation: stimulus organism response model. Asia Pac. J. Tour. Res. 19(4), 375–388 (2014)

    Article  Google Scholar 

  41. Rheu, M., Shin, J.Y., Peng, W., Huh-Yoo, J.: Systematic review: trust-building factors and implications for conversational agent design. Int. J. Hum.-Comput. Interact. 37(1), 81–96 (2021)

    Article  Google Scholar 

  42. Rogers, S., Fiechter, C.N., Langley, P.: An adaptive interactive agent for route advice. In: Proceedings of the third annual conference on Autonomous Agents, pp. 198–205 (1999)

    Google Scholar 

  43. Schulman, D., Bickmore, T.: Persuading users through counseling dialogue with a conversational agent. In: Proceedings of the 4th International Conference on Persuasive Technology, pp. 1–8 (2009)

    Google Scholar 

  44. Sumi, K.: Learning story marketing through practical experience of story creation system. In: Aylett, R., Lim, M.Y., Louchart, S., Petta, P., Riedl, M. (eds.) ICIDS 2010. LNCS, vol. 6432, pp. 98–110. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-16638-9_13

    Chapter  Google Scholar 

  45. Sumi, K., Nagata, M.: Evaluating a virtual agent as persuasive technology. In: Csapó, J., Magyar, A. (eds.) Psychology of Persuasion (2010)

    Google Scholar 

  46. Xie, G.X., Boush, D.M., Liu, R.R.: Tactical deception in covert selling: a persuasion knowledge perspective. J. Mark. Commun. 21(3), 224–240 (2015)

    Article  Google Scholar 

  47. Zulkifli, A.N., Noor, N.M., Bakar, J.A.A., Mat, R.C., Ahmad, M.: A conceptual model of interactive persuasive learning system for elderly to encourage computer-based learning process. In: 2013 International Conference on Informatics and Creative Multimedia, pp. 7–12. IEEE (2013)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Pinkie Anggia .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Anggia, P., Sumi, K. (2023). Persuasion-Building Fundamental Premises and Implications for Conversational Agents: A Conceptual Model in Captology. In: Meschtscherjakov, A., Midden, C., Ham, J. (eds) Persuasive Technology. PERSUASIVE 2023. Lecture Notes in Computer Science, vol 13832. Springer, Cham. https://doi.org/10.1007/978-3-031-30933-5_18

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-30933-5_18

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-30932-8

  • Online ISBN: 978-3-031-30933-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics