Advertisement

Analysis of Trust in Automation Survey Instruments Using Semantic Network Analysis

  • Heejin Jeong
  • Jangwoon Park
  • Jaehyun Park
  • Thanh Pham
  • Byung Cheol Lee
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 781)

Abstract

This study analyzed existing survey instruments to provide an integrated list of keywords/constructs to measure the various perceptions of trust building in automation. While the trust between users and automated functions or systems has been an area of substantial research interest to understand the interactions between human and automation, research efforts to measure the trust to date have led to inconclusive and mixed outcomes. Of the existing scales for measuring trust in automation, inadequate development of constructs and the lack of reliability and validity have been identified as major causes for such outcomes. To develop a scale in a more objective and systematic approach, 86 keywords from existing 9 survey instruments were identified. The keyword network was developed based on the semantic textural similarity, and the network centrality analysis provided total 14 keywords with high centrality and degree matrics. The results can suggest some potential solutions about the lack of consistency and the wide array of constructs without adequate analytic justification in prior survey instruments. The outcomes will be utilized to develop a new integrated scale that can be generally applicable to a wide variety of automation adoption or, with slight modifications, in most trust in automation applications.

Keywords

Trust in automation Natural language processing Network analysis Semantic textural similarity 

References

  1. 1.
    Sheridan, T.B.: Task allocation and supervisory control. In: Handbook of Human-Computer Interaction. 8 (1988)CrossRefGoogle Scholar
  2. 2.
    Onnasch, L., Wickens, C.D., Li, H., Manzey, D.: Human performance consequences of stages and levels of automation: an integrated meta-analysis. Hum. Factors 56, 476–488 (2014)CrossRefGoogle Scholar
  3. 3.
    Jeong, H., Park, J., Park, J., Lee, B.C.: Inconsistent work performance in automation, can we measure trust in automation. Int. Robot. Autom. J. 3, 00075 (2017)Google Scholar
  4. 4.
    Lee, J.D., Moray, N.: Trust, self-confidence, and operators’ adaptation to automation. Int. J. Hum.-Comput. Stud. 40, 153–184 (1994)CrossRefGoogle Scholar
  5. 5.
    Lee, J.D., See, K.A.: Trust in automation: designing for appropriate reliance. Hum. Factors J. Hum. Factors Ergon. Soc. 46, 50–80 (2004)CrossRefGoogle Scholar
  6. 6.
    Chien, S.-Y., Lewis, M., Hergeth, S., Semnani-Azad, Z., Sycara, K.: Cross-country validation of a cultural scale in measuring trust in automation. Proc. Hum. Factors Ergon. Soc. Annu. Meet. 59, 686–690 (2015)CrossRefGoogle Scholar
  7. 7.
    Singh, I.L., Molloy, R., Parasuraman, R.: Automation-induced “complacency”: development of the complacency-potential rating scale. Int. J. Aviat. Psychol. 3, 111–122 (1993)CrossRefGoogle Scholar
  8. 8.
    Muir, B.M., Moray, N.: Trust in automation. Part II. Experimental studies of trust and human intervention in a process control simulation. Ergonomics 39, 429–460 (1996)CrossRefGoogle Scholar
  9. 9.
    Larzelere, R.E., Huston, T.L.: The dyadic trust scale: toward understanding interpersonal trust in close relationships. J. Marriage Fam. 595–604 (1980)CrossRefGoogle Scholar
  10. 10.
    Rempel, J.K., Holmes, J.G., Zanna, M.P.: Trust in close relationships. J. Pers. Soc. Psychol. 49, 95 (1985)CrossRefGoogle Scholar
  11. 11.
    Doney, P.M., Cannon, J.P.: Trust in buyer-seller relationships. J. Mark. 61, 35–51 (1997)CrossRefGoogle Scholar
  12. 12.
    Ganesan, S.: Determinants of long-term orientation in buyer-seller relationships. J. Mark. 1–19 (1994)CrossRefGoogle Scholar
  13. 13.
    Lewis, J.D., Weigert, A.: Trust as a social reality. Soc. Forces 63, 967–985 (1985)CrossRefGoogle Scholar
  14. 14.
    Mayer, R.C., Davis, J.H., Schoorman, F.D.: An integrative model of organizational trust. Acad. Manag. Rev. 20, 709–734 (1995)CrossRefGoogle Scholar
  15. 15.
    Friedman, B., Khan Jr., P.H., Howe, D.C.: Trust online. Commun. ACM 43, 34–40 (2000)CrossRefGoogle Scholar
  16. 16.
    Jian, J.-Y., Bisantz, A.M., Drury, C.G.: Foundations for an empirically determined scale of trust in automated systems. Int. J. Cogn. Ergon. 4, 53–71 (2000)CrossRefGoogle Scholar
  17. 17.
    Madsen, M., Gregor, S.: Measuring human-computer trust. In: 11th Australasian Conference on Information Systems, pp. 6–8. Citeseer (2000)Google Scholar
  18. 18.
    Chien, S.-Y., Semnani-Azad, Z., Lewis, M., Sycara, K.: Towards the development of an inter-cultural scale to measure trust in automation. In: International Conference on Cross-Cultural Design, pp. 35–46. Springer (2014)Google Scholar
  19. 19.
    Merritt, S.M., Ilgen, D.R.: Not all trust is created equal: dispositional and history-based trust in human-automation interactions. Hum. Factors 50, 194–210 (2008)CrossRefGoogle Scholar
  20. 20.
    Lee, I., Choi, B., Kim, J., Hong, S.-J.: Culture-technology fit: effects of cultural characteristics on the post-adoption beliefs of mobile Internet users. Int. J. Electron. Commer. 11, 11–51 (2007)CrossRefGoogle Scholar
  21. 21.
    Hwang, Y., Lee, K.C.: Investigating the moderating role of uncertainty avoidance cultural values on multidimensional online trust. Inf. Manage. 49, 171–176 (2012)CrossRefGoogle Scholar
  22. 22.
    Mcknight, D.H., Carter, M., Thatcher, J.B., Clay, P.F.: Trust in a specific technology: an investigation of its components and measures. ACM Trans. Manag. Inf. Syst. TMIS 2, 12 (2011)Google Scholar
  23. 23.
    Han, L., Kashyap, A.L., Finin, T., Mayfield, J., Weese, J.: UMBC_EBIQUITY-CORE: semantic textual similarity systems. In: * SEM@ NAACL-HLT, pp. 44–52 (2013)Google Scholar
  24. 24.
    Miller, G.A.: WordNet: a lexical database for English. Commun. ACM 38, 39–41 (1995)CrossRefGoogle Scholar
  25. 25.
    Opsahl, T., Agneessens, F., Skvoretz, J.: Node centrality in weighted networks: generalizing degree and shortest paths. Soc. Netw. 32, 245–251 (2010)CrossRefGoogle Scholar
  26. 26.
    Freeman, L.C.: A set of measures of centrality based on betweenness. Sociometry, 35–41 (1977)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  • Heejin Jeong
    • 1
  • Jangwoon Park
    • 2
  • Jaehyun Park
    • 3
  • Thanh Pham
    • 4
  • Byung Cheol Lee
    • 2
  1. 1.Department of Industrial and Operations EngineeringUniversity of MichiganAnn ArborUSA
  2. 2.Department of EngineeringTexas A&M University – Corpus ChristiCorpus ChristiUSA
  3. 3.Department of Industrial and Management EngineeringIncheon National University (INU)IncheonRepublic of Korea
  4. 4.Department of Computing ScienceTexas A&M University – Corpus ChristiCorpus ChristiUSA

Personalised recommendations