Title: A Bayesian model of design imperfections in online feedback systems and their relative impacts
Authors: Ming Zhou, Menglin Cao
Addresses: Department of Organization and Management, Lucas Graduate School of Business, San Jose State University, One Washington Square, BT 659, San Jose 95192, CA, USA. ' Marketing Database Decision Strategy Manager, Wells Fargo Bank, 45 Fremont St., 2nd Floor, San Francisco 94105, CA, USA
Abstract: Recent studies have proposed an overwhelming number of solutions to design imperfections of online feedback systems. However, in what sequence the imperfections should be perfected is yet to be operationalised. In this study, we focused upon the relative damages of design imperfections in order to understand the urgency to deal with each imperfection and develop an operational sequence. The effectiveness of online feedback systems was defined using a Bayesian model. The relative damages were then consistently evaluated using the effectiveness criteria. We concluded that identity changing deserved the highest priority on an auction manager|s to do list.
Keywords: online feedback systems; Bayesian models; rank ordering; feedback imperfections; feedback system design; decision making; design imperfections; identity changing; auction management.
DOI: 10.1504/IJMOR.2011.040878
International Journal of Mathematics in Operational Research, 2011 Vol.3 No.4, pp.451 - 471
Published online: 12 Feb 2015 *
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