K
Kin Keung Lai
Researcher at Shenzhen University
Publications - 587
Citations - 15177
Kin Keung Lai is an academic researcher from Shenzhen University. The author has contributed to research in topics: Supply chain & Artificial neural network. The author has an hindex of 60, co-authored 547 publications receiving 13120 citations. Previous affiliations of Kin Keung Lai include City University of Hong Kong & North China Electric Power University.
Papers
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Journal ArticleDOI
Hierarchical economic information filtering model concerning vendor selection
TL;DR: A new hierarchical economic information filtering model for vendor selection, consisting of three phases in which leading enterprises select their vendors, which contributes to increasing information search efficiency, and reduces information search time and cost is proposed.
Book ChapterDOI
A Class of Expected Linear Bi-level Programming with Random Fuzzy Coefficients
TL;DR: In this paper, a class of linear bi-level programming with random fuzzy coefficients, which has no mathematical meaning because of the uncertain factors is considered, and some theorems are proposed to obtain the equivalent model.
Journal ArticleDOI
Research on Distribution Optimization of Emergency Perishable Materials Considering Periodic Changes in Freshness
TL;DR: In this paper , a piecewise function is constructed to describe the impact of freshness on the quality and quantity of emergency perishable materials at different time stages, and an approximate algorithm is designed to solve the model, with the time complexity and the upper and lower bounds of the approximate ratio analyzed.
Journal ArticleDOI
Evolution of the Complex Partnerships between Banks and B2B e-Trading Platforms: A Theoretical Interpretation from the Chinese Market
TL;DR: Results show that, at the initial stage of growth of the platforms’ abilities to rate online borrowers, the leadership and the absolute benefit of the banks will suffer a “double decline,” which explains why the leading banks in China “divorced” the B2B platforms during 2011 to 2013.
Proceedings ArticleDOI
The Compensation Model for Default-Risk of Corporate Bonds in China under Kalman Filter
Kaihao Liang,Kin Keung Lai +1 more
TL;DR: Algorithm of the Kalman Filter is applied in modeling of jump-risk compensation and the parameter method of maximum likelihood estimation is used to obtain the default probability and default intensity.