Wang, Chun and Dargahi, Farnaz (2012) Service customization under capacity constraints: an auction-based model. Journal of Intelligent Manufacturing . ISSN 0956-5515
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Official URL: http://dx.doi.org/10.1007/s10845-012-0689-7
Abstract
In mass customization, companies strive to enhance customer value by providing products and services that are approximate to customers’ needs. A company’s strategy of allocating its limited capacity to meeting diverse customer requirements directly impact customer perceived value in terms of available options, cost, and schedule. Proposed in this paper is an auction-based mass customization model for solving the problem of service customization under capacity constraints (SCCC). The proposed model integrates customers’ customization decision making with the allocation of company’s capacity through multilateral negotiation between the company and its customers. The negotiation is conducted through a combinatorial iterative auction designed to maximize the overall customer value given limited capacity. The auction is incentive-compatible in the sense that customers will follow the prescribed myopic best-response bidding strategy. Experimental results indicate that customization solutions computed by the proposed model are very close to the optimal one. Revenue performance is also adequate when there is sufficient competition in the market.
| Divisions: | Concordia University > Gina Cody School of Engineering and Computer Science > Concordia Institute for Information Systems Engineering |
|---|---|
| Item Type: | Article |
| Refereed: | Yes |
| Authors: | Wang, Chun and Dargahi, Farnaz |
| Journal or Publication: | Journal of Intelligent Manufacturing |
| Date: | 2012 |
| Digital Object Identifier (DOI): | 10.1007/s10845-012-0689-7 |
| Keywords: | Mass customization, capacity allocation, service customization, combinatorial iterative auction, multilateral negotiation, design by customers |
| ID Code: | 976811 |
| Deposited By: | Danielle Dennie |
| Deposited On: | 28 Jan 2013 16:55 |
| Last Modified: | 18 Jan 2018 17:43 |
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