An incentive mechanism for partner selection from a collaborative network with private information. (April 2021)
- Record Type:
- Journal Article
- Title:
- An incentive mechanism for partner selection from a collaborative network with private information. (April 2021)
- Main Title:
- An incentive mechanism for partner selection from a collaborative network with private information
- Authors:
- Wang, Cheng
Wu, Runhua
Deng, Lili - Abstract:
- Highlights: Partner selection problem with private information is studied. An incentive mechanism is designed to reveal the private information. A systematic solution is provided to select the optimal partners. The number of candidates in each period affects the utility significantly. Abstract: Partner selection is critical to the success of a Virtual Enterprise. This paper studies the partner selection problem under the virtual organization breeding environment where candidates have private information about their cost to undertake the tasks. A systematic solution is provided to reveal the true value of the private information and then select the optimal partners. This solution mainly comprises two steps: (1) For each possible cost combination, a multi-objective integer nonlinear programming model and an algorithm are designed to obtain the optimal partners. Then, a social choice correspondence, which indicates the optimal partners for any cost combination, is formulated. (2) An incentive mechanism is constructed to implement the social choice correspondence and ensure that candidates will announce their values of cost truthfully. Furthermore, a numerical study is provided to illustrate the effectiveness of the solution and to investigate the relationship between the construction of the collaborative network and the utility to partners. We find that the number of candidates in each period affects the utility of partners as well as the expected surplus of the leading companyHighlights: Partner selection problem with private information is studied. An incentive mechanism is designed to reveal the private information. A systematic solution is provided to select the optimal partners. The number of candidates in each period affects the utility significantly. Abstract: Partner selection is critical to the success of a Virtual Enterprise. This paper studies the partner selection problem under the virtual organization breeding environment where candidates have private information about their cost to undertake the tasks. A systematic solution is provided to reveal the true value of the private information and then select the optimal partners. This solution mainly comprises two steps: (1) For each possible cost combination, a multi-objective integer nonlinear programming model and an algorithm are designed to obtain the optimal partners. Then, a social choice correspondence, which indicates the optimal partners for any cost combination, is formulated. (2) An incentive mechanism is constructed to implement the social choice correspondence and ensure that candidates will announce their values of cost truthfully. Furthermore, a numerical study is provided to illustrate the effectiveness of the solution and to investigate the relationship between the construction of the collaborative network and the utility to partners. We find that the number of candidates in each period affects the utility of partners as well as the expected surplus of the leading company significantly. … (more)
- Is Part Of:
- Computers & industrial engineering. Volume 154(2021)
- Journal:
- Computers & industrial engineering
- Issue:
- Volume 154(2021)
- Issue Display:
- Volume 154, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 154
- Issue:
- 2021
- Issue Sort Value:
- 2021-0154-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-04
- Subjects:
- Partner selection -- Collaborative network -- Social choice correspondence -- Incentive mechanism design
Engineering -- Data processing -- Periodicals
Industrial engineering -- Periodicals
620.00285 - Journal URLs:
- http://www.sciencedirect.com/science/journal/03608352 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.cie.2020.107053 ↗
- Languages:
- English
- ISSNs:
- 0360-8352
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3394.713000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 22463.xml