Integrating Trust and Economic Theories with Knowledge Science for Dependable Service Automation
This paper examines the necessity to integrate Economic Theories and Trust Theories with Knowledge Science for trustworthy service automation in modern day society’s technology-driven environment. Current demands for open user-centric distributed service systems far outweigh the capabilities of existing systems in application areas such as health care, e-business, and consumer-centric power and water distribution systems. The basis of service transactions, whether in traditional market place or on-line system, is trust and lack of trust will have diminishing effect on the economic value. It is essential to identify user perspectives and relate their social psychology to meaningful trust determinants in the system to be automated. Since the systems are typically large, distributed, and deal with many heterogeneous collection of sensory devices and actuators that are specific to each service domain, it is necessary that the experts of the application domain and system developers share their knowledge and wisdom in the creation of the system. Sharing knowledge requires trust, and using the acquired knowledge requires creativity, born out of tacit knowledge, to go beyond risks. Motivated by this triangular web of Economics, Trust, and Knowledge that impacts on consumer-centric service automation, this paper explores their interesting connections, explains the different kinds of trust to be distilled from it, and identifies the design stages where the appropriate trust determinants are to be fostered in order to achieve a dependable service automation system.
KeywordsService Automation Economic Theory Trust Theory Knowledge Science
Unable to display preview. Download preview PDF.
- 1.Ackoff, R.L.: From Data to Wisdom. Journal of Applies Systems Analysis 16, 3–9 (1989)Google Scholar
- 5.Cross, R., Baird, L.: Technology is Not Enough: Improving Performance by Building Organizational Memory. Sloan Management Review 41(3), 69–78 (2000)Google Scholar
- 7.Friedman, B., Khan, P.H., Howe, D.C.: Trust Online. Communications of the ACM 43(12) (2000)Google Scholar
- 8.Fritz, M., Hausen, T., Schefer, G., Canavari, M.: Trust and Electronic Commerce in the Agrifood Sector: a trust model and experimental experience. Presented at the XIth International Congress of the EAAE (European Association of Agricultural Economists), The Future of Rural Europe in the Global Agri-Food System, Copenhagen, Copenhagen, Denmark, August 24-27 (2005)Google Scholar
- 15.Levin, T., Irvine, C., Benzel, T., Nguyen, T., Clark, P., Bhaskara, G.: Trusted Emergency Management. Technical Report (NPS-CS-09-001), Naval Postgraduate School, Monterey, California, USA (2009)Google Scholar
- 20.Myers, A., Liskov, B.: A Decentralized Model for Information Flow Control. In: Proceedings of the 16th ACM Symposium on Operating System Principles, Saint Malo, France (October 1977)Google Scholar
- 21.Pavlou, P.A.: Consumer Acceptance of Electronic Commerce: Integrating Trust and Risk with the Technology Acceptance Model. International Journal of Electronic Commerce 7(3), 101–134 (2003)Google Scholar
- 23.Sillence, E., Briggs, P., Fishwick, L., Harris, P.: Trust and Mistrust of Online Health Sites. In: ACM SIGCHI Conference on Human Factors in Computing Systems, Vienna (2004)Google Scholar
- 24.TCIPG. Trustworthy Cyber Infrastructure For The Power Grid, http://tcipg.org/