Cost estimation of a service family based on modularity

Choon Khai Tay and Song Lin Chen

International Journal of Production Research, 2016, vol. 54, issue 10, 3059-3079

Abstract: Companies are competing to offer high varieties of customised services on top of customised products to increase revenues and customer satisfaction. By adopting product family design methodologies, new concepts such as service families and service platforms are adopted in the service sectors. Despite that, increasing diversity in service offerings induces complexity and difficulty in service cost estimation. This research presents a service family cost estimation methodology that is based on service modularity and activity based costing (ABC). A service family is identified by selecting a set of similar services. Subsequently, activities of each service are identified with an activity diagram. The service family is then decomposed into functional and physical elements, where service modules are identified. Service activities are then mapped into relevant service modules using k -mean clustering algorithms, and activities of each service module are segregated into common and specific services using un-weighted pair group method with arithmetic mean. Finally, modified two-stage ABC methodology is applied to estimate the costs for a service family. To demonstrate the applicability of the proposed methodology, a case study is carried out to estimate the cost for a family of aircraft engines.

Date: 2016
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2016.1156781 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tprsxx:v:54:y:2016:i:10:p:3059-3079

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TPRS20

DOI: 10.1080/00207543.2016.1156781

Access Statistics for this article

International Journal of Production Research is currently edited by Professor A. Dolgui

More articles in International Journal of Production Research from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().