Evaluating Strategies to Restore Trust in Decision Support Systems in Cross-Company Cooperation
Advancing automation in many technical areas (mobility, production, medicine, etc.) is accompanied by new challenges for the interaction between humans and technical systems. Trust in automation is a key element for the use of technology and for compliance with its recommendations. This also applies to decision support systems (DSS) in the production domain. These can make the increasing complexity of production processes and networks manageable but can lead to serious financial losses in case of error as well. The present study addresses the restoring of trust in those DSS after a failure. In an exploratory two-stage approach, interviews were used to identify user requirements for trust restoring measures, followed by a questionnaire study including a business simulation game to quantify those measures in an exemplary manner. Preliminary results suggest that trust can only be restored to a very limited extent by specific intervention measures, but that systems must laboriously rebuild trust by long-term error-free functioning.
KeywordsRepairing trust in automation Decision Support Systems Failure management Cyber-physical production systems Human factors
This research was funded by the German Research Foundation (DFG) within the Cluster of Excellence „Integrative Production Technology for High-Wage Countries” (EXC 128) and the Integrated Cluster Domain “Self-Optimizing Production Networks”  (ICD D1). The authors thank all participants for sharing opinions on a novel technology. Furthermore, thanks go to Christin Gatzka, Felix Glawe, Susanne Gohr, Nils Plettenberg, Lisanne Simons, and Jacqueline Bialas for their research support.
- 1.Gorry, G.A., Morton, M.S.S.: A framework for management information systems. Sloan Manag. Rev. 13, 50–70 (1971)Google Scholar
- 2.Burstein, F., Holsapple, C.: Handbook on Decision Support Systems 1. Springer, Heidelberg (2008)Google Scholar
- 4.Brauner, P., Calero Valdez, A., Philipsen, R., Ziefle, M.: Defective still deflective – how correctness of decision support systems influences user’s performance in production environments. In: HCI in Business, Government, and Organizations: Information Systems, pp. 16–27. Springer, Cham (2016)CrossRefGoogle Scholar
- 8.Brauner, P., Calero Valdez, A., Philipsen, R., Ziefle, M.: How correct and defect decision support systems influence trust, compliance, and performance in supply chain and quality management. LNCS, pp. 333–348 (2017)Google Scholar
- 14.Johnson, J.D., Sanchez, J., Fisk, A.D., Rogers, W.A.: Type of automation failure: the effects on trust and reliance in automation. In: Proceedings of the Human Factors and Ergonomics Society Annual Meeting, vol. 48, no. 18, pp. 2163–2167. SAGE Publications Sage CA, Los Angeles (2014)CrossRefGoogle Scholar
- 19.Buchholz, V., Kulms, P., Kopp, S.: It’s (Not) Your Fault! Blame and Trust Repair in Human-Agent Cooperation. Kognitive Systeme 1 (2017)Google Scholar
- 20.Philipsen, R., Brauner, P., Stiller, S., Ziefle, M., Schmitt, R.: The role of human factors in production networks and quality management. In: International Conference on HCI in Business, pp. 80–91. Springer, Cham (2014)Google Scholar
- 22.Karrer, K., Glaser, C., Clemens, C., Bruder, C.: Technikaffinität erfassen – der Fragebogen TA-EG. Mensch Mittelpunkt techn. Syst. 8, 196–201 (2009)Google Scholar
- 23.Beierlein, C., Kemper, C., Kovaleva, A.J., Rammstedt, B.: Interpersonales Vertrauen (KUSIV3). In: Zusammenstellung sozialwissenschaftlicher Items und Skalen (2014)Google Scholar
- 25.Wagenmakers, E., Marsman, M., Jamil, T., Ly, A., Verhagen, J., Love, J., Selker, R., Gronau, Q.F., Šmíra, M., Epskamp, S., Matzke, D., Rouder, J., Morey, R.: Bayesian inference for psychology. part I: theoretical advantages and practical ramifications. Psychon. Bull. Rev. 25(1), 35–57 (2018). https://doi.org/10.3758/s13423-017-1343-3CrossRefGoogle Scholar