UTS site search

Dr Jun Zhang

Biography

Personal webpage:

http://zhangjun.weebly.com

Associate Professor, Economics Discipline Group
Core Member, Centre for Policy and Market Design
PhD Econ.
 
Phone
+61 2 9514 3203
Can supervise: Yes

Journal articles

Chen, C., Zhang, J. & Guo, R.S. 2016, 'The D-Day, V-Day, and bleak days of a disruptive technology: A new model for ex-ante evaluation of the timing of technology disruption', European Journal of Operational Research, vol. 251, no. 2, pp. 562-574.
View/Download from: Publisher's site
© 2016 Elsevier B.V. All rights reserved. The recent failure of major PC and smartphone makers in launching new generations of high-tech products in time shows that analyzing and capturing the timing of technology disruption is an important yet less explored research area. This paper conducts theoretical and empirical analyses for ex-ante quantitative evaluation of the timing of technology disruption. We conceptualize the ease and network factors as key determinants of performance improvement for a disruptive technology. A dynamic consumer model is developed to identify two critical times, termed D-Day and V-Day, of technology disruption. We also show that, if the network factor dominates the performance improvement process, there may exist some "bleak days" during which a firm would discontinue a "promising" technology that will eventually disrupt. Empirical tests are conducted with data of hard disk drives, semiconductor technologies, and CPU performance for mobile devices to verify key model assumptions and to show how to estimate the ease and network factors. We also perform a numerical experiment to demonstrate how to forecast the timing of technology disruption. A decision tree and a systematic framework are also developed to operationalize key model parameters and analytical results from a decision-support perspective. This paper contributes to the literature by presenting a novel analytical tool and new insights for high-tech companies to forecast and manage the timing of technology disruption.
Zhang, J. & Zhou, J. 2016, 'Information Disclosure in Contests: A Bayesian Persuasion Approach', Economic Journal.
View/Download from: Publisher's site
© 2015 Royal Economic Society. We examine optimal information disclosure through Bayesian persuasion in a two-player contest. One contestant's valuation is commonly known and the other's is his private information. The contest organiser can precommit to a signal to influence the uninformed contestant's belief about the informed contestant. We show that to search for the optimal signal when the informed contestant's valuation follows a binary distribution, it is without loss of generality to compare no disclosure with full disclosure; otherwise, such a restriction causes loss of generality. We propose a simple method to compute the optimal signal, which yields explicit solutions in some situations.
Cadsby, C.B., Du, N., Wang, R. & Zhang, J. 2016, 'Goodwill Can Hurt: A theoretical and experimental investigation of return policies in auctions', Games and Economic Behavior, vol. 99, pp. 224-238.
View/Download from: Publisher's site
© 2016 Elsevier Inc.Will generous return policies in auctions benefit bidders? We investigate this issue using second-price common-value auctions. Theoretically, we find that the symmetric bidding equilibrium is unique unless returns are free, and when returns are free there exist multiple equilibria with different implications for sellers. Moreover, more generous return policies mitigate the winner's curse, but also push the bids higher, thus hurting bidders by eroding their surplus. In the experiment, bids increase and bidders' earnings decrease with more generous return policies as predicted. With free returns, many bidders bid above the highest possible value, subsequently returning the item regardless of value. Though consistent with equilibrium behavior, this is not optimal for sellers.
Fu, Q., Lu, J. & Zhang, J. 2016, 'Disclosure policy in Tullock contests with asymmetric stochastic entry', Canadian Journal of Economics, vol. 49, no. 1, pp. 52-75.
View/Download from: Publisher's site
© 2016 Canadian Economics AssociationWe examine how disclosure policy can be optimally designed to incentivize contestants when their participation is exogenously stochastic. In a generalized Tullock contest setting with two players who are asymmetric in both their values and entry probabilities, we fully characterize the necessary and sufficient conditions under which no disclosure dominates full disclosure. We find that the comparison depends solely on a balance effect exercised by entry probabilities on the expected total effort. The optimal disclosure policy must better balance the competition. These conditions continue to hold when the precision r of Tullock contests is endogenously chosen by the designer.
Chen, C., Zhang, J. & Delaurentis, T. 2014, 'Managing Global Supply Chain Quality and Risk: Analytical Model and Case Study', International Journal of Production Economics, vol. 152, pp. 188-199.
View/Download from: Publisher's site
Zhang, J. & Chen, C. 2013, 'Green Product Design with Product-Line Strategies under Technology Efficient Frontiers: Analytical Results and Empirical Tests', IEEE Transactions on Engineering Management, vol. 60, no. 2, pp. 340-352.
Zhang, J. & Wang, R. 2013, 'Optimal mechanism design with resale via bargaining', Journal of Economic Theory, vol. 148, no. 5, pp. 2096-2123.
View/Download from: Publisher's site
In this paper, we examine the optimal mechanism design of selling an indivisible object to one regular buyer and one publicly known buyer, where inter-buyer resale cannot be prohibited. The resale market is modeled as a stochastic ultimatum bargaining game between the two buyers. We fully characterize an optimal mechanism under general conditions. Surprisingly, in this optimal mechanism, the seller never allocates the object to the regular buyer regardless of his bargaining power in the resale market. The seller sells only to the publicly known buyer, and reveals no additional information to the resale market. The possibility of resale causes the seller to sometimes hold back the object, which under our setup is never optimal if resale is prohibited. We find that the seller's revenue is increasing in the publicly known buyer's bargaining power in the resale market. When the publicly known buyer has full bargaining power, Myerson's optimal revenue is achieved; when the publicly known buyer has no bargaining power, a conditionally efficient mechanism prevails. © 2013 Elsevier Inc.
Zhang, J. 2013, 'Revenue maximizing with return policy when buyers have uncertain valuations', International Journal of Industrial Organization, vol. 31, no. 5, pp. 452-461.
View/Download from: Publisher's site
Zhang, J. & Wang, R. 2009, 'The Role of Information Revelation in Elimination Contests', The Economic Journal, vol. 119, no. 536, pp. 613-641.
View/Download from: Publisher's site
Zhang, J. & Chen, C. 2009, 'The Inconvenient Truth about Improving Vehicle Fuel Efficiency: A Multi-Attributes Analysis of the Technology Efficient Frontier of the US Automobile Industry', Transportation Research Part D: Transport and Environment, vol. 14, pp. 22-31.