Please use this identifier to cite or link to this item: http://hdl.handle.net/10125/50081

Towards a Technician Marketplace using Capacity-Based Pricing

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dc.contributor.author Wolff, Clemens
dc.contributor.author Vössing, Michael
dc.contributor.author Schmitz, Björn
dc.contributor.author Fromm, Hansjörg
dc.date.accessioned 2017-12-28T00:50:29Z
dc.date.available 2017-12-28T00:50:29Z
dc.date.issued 2018-01-03
dc.identifier.isbn 978-0-9981331-1-9
dc.identifier.uri http://hdl.handle.net/10125/50081
dc.description.abstract Today, industrial maintenance is organized as an on-call business: Upon a customer’ s service request, the maintenance provider schedules a service technician to perform the demanded service at a suitable time. In this work, we address two drawbacks of this scheduling approach: First, the provider typically prioritizes service demand based on a subjective perception of urgency. Second, the pricing of technician services is inefficient, since services are priced on a time and material basis without accounting for additional service quality (e.g. shorter response time). We propose the implementation of a technician marketplace that allows customers to book technician capacity for fixed time slots. The price per time slot depends on the remaining capacity and therefore incentivizes customers to claim slots that match their objective task urgency. The approach is evaluated using a simulation study. Results show the capabilities of capacity-based pricing mechanisms to prioritize service demand according to customers’ opportunity costs.
dc.format.extent 10 pages
dc.language.iso eng
dc.relation.ispartof Proceedings of the 51st Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Service Analytics
dc.subject industrial maintenance, service pricing, technician dispatching, willingness-to-pay
dc.title Towards a Technician Marketplace using Capacity-Based Pricing
dc.type Conference Paper
dc.type.dcmi Text
dc.identifier.doi 10.24251/HICSS.2018.194
Appears in Collections: Service Analytics


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