Zilker S, Marx E, Stierle M, Matzner M (2022)
Publication Type: Conference contribution, Conference Contribution
Publication year: 2022
Conference Proceedings Title: Proceedings of the 55th Hawaii International Conference on System Sciences
Event location: Maui, Hawaii
URI: http://hdl.handle.net/10125/79571
Open Access Link: https://scholarspace.manoa.hawaii.edu/bitstream/10125/79571/0190.pdf
With the ongoing trend of servitization nurtured through digital technologies, the analysis of services as a starting point for improvement is gaining more and more importance. Service analytics has been defined as a concept to analyze the data generated during service execution to create value for providers and customers. To create more useful insights from the data, there is a continuous need for more advanced solutions for service analytics. One promising technology is process mining which has its origins in business process management. Our work provides insights into how process mining is currently used to analyze service processes and how it could be used along the service process. We find that process mining is increasingly applied for the analysis of the providers' internal operations, but more emphasis should be put on analyzing the customer interaction and experience.
APA:
Zilker, S., Marx, E., Stierle, M., & Matzner, M. (2022). Process Mining for Advanced Service Analytics – From Process Efficiency to Customer Encounter and Experience. In Proceedings of the 55th Hawaii International Conference on System Sciences. Maui, Hawaii.
MLA:
Zilker, Sandra, et al. "Process Mining for Advanced Service Analytics – From Process Efficiency to Customer Encounter and Experience." Proceedings of the Hawaii International Conference on System Sciences, Maui, Hawaii 2022.
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