STRATEGIC EXERCISE OF REAL OPTIONS：INVESTMENT DECISIONS IN TECHNOLOGICAL SYSTEMS

Viewing investment projects in new technologies as real options, this paper studies the effects ofendogenous competition and asymmetric information on the strategic exercise of real options. We firstdevelop a multi-period, game-theoretic model and show how competition leads to early exercise andaggressive investment behaviors and how competition erodes option values. We then relax the typicalfull-information assumption found in the literature and allow information asymmetry to exist acrossfirms. Our model shows, in contrast to the literature that payoff is independent of the ordering ofexercise, that the sequential exercise of real options may generate both informational and payoffexternalities. We also find some surpising but interesting results such as having more information isnot necessarily better.     

FROM MANUFACTURING SCHEDULING TO SUPPLY CHAIN COORDINATION：THE CONTROL OF COMPLEXITY AND UNCERTAINTY

With time-based competition and rapid technology advancements, effective manufacturingscheduling and supply chain coordination are critical to quickly respond to changing marketconditions. These problems, however, are difficult in view of inherent complexity and variousuncertainties involved. Based on a series of results by the authors, decomposition and coordination byusing Lagrangian relaxation is identified in this paper as an effective way to control complexity anduncertainty.A manufacturing scheduling problem is first formulated within the job shop context withuncertain order arrivals, processing times, due dates, and part priorities as a separable optimizationproblem. A solution methodology that combines Lagrangian relaxation, stochastic dynamicprogramming, and heuristics is developed. Method improvements to effectively solve large problemsare also highlighted. To extend manufacturing scheduling within a factory to coordinate autonomicmembers across chains of suppliers, a decentralized supply chai     

ORGANIZATIONAL LEARNING AND VENDOR SUPPORT QUALITY BY THE USAGE OF APPLICATION SOFTWARE PACKAGES： A STUDY OF ASIAN ENTREPRENEURS

In this paper we study how organizational learning impacts organizational behavior, and howvendor support quality enhances product adoption and usage behavior.These constructs were verifiedusing Application Software Packages(ASP)-a prewritten, precoded, commercially available set ofprograms that eliminates the need for individuals or organizations to write their own softwareprograms for certain functions. The relationship between ASP usage, usage outcomes and useprocesses were also investigated. Two hundred and ninety-five Chinese, Indian, and Malayentrepreneurships were studied. It was found that usage outcome strongly determines usage, while useprocess has only an indirect relationship (via outcome) on usage. The impact of organizational learningand vendor service quality on usage, usage outcome, and use process were robust. Theoretical andpractical implications of the research are discussed.     

Technical Notes ：STUDIES ON THE VALUE OF SECONDARY MARKET TO THE SUPPLY CHAIN

This paper investigates the impact of a secondary market, where retailers can buy and sell excessinventories, on the supply chain. We develop a two-period model with a single manufacturer and tworetailers. At the beginning of the first period the retailers order and receive products from themanufacturer, but at the beginning of the second period, they can trade surplus products betweenthemselves in the secondary market. We investigate the impact of the correlated dependence ofretailers' demand on both the quantity effect and the allocation effect under the secondary market.Lastly,we study potential strategies for the manufacturer to increase sales with the existence of thesecondary market.     

LOGISTICS SCHEDULING： ANALYSIS OFTWO-STAGE PROBLEMS

This paper studies the coordination effects between stages for scheduling problems where decision-making is a two-stage process. Two stages are considered as one system. The system can be a supply chain that links two stages, one stage representing a manufacturer; and the other, a distributor It also can represent a single manufacturer, while each stage represents a different department responsible for a part of operations. A problem that jointly considers both stages in order to achieve ideal overall system performance is defined as a system problem. In practice, at times, it might not be feasible for the two stages to make coordinated decisions due to (i) the lack of channels that allow decision makers at the two stages to cooperate, and/or (ii) the optimal solution to the system problem is too difficult (or costly) to achieve.Two practical approaches are applied to solve a variant of two-stage logistic scheduling problems. The Forward Approach is defined as a solution procedure by which the first sta     

产品数据管理系统实施方法学

提出了产品数据管理系统的实施概念 ,并从系统工程角度提出了产品数据管理实施的策略 ,给出了的产品数据管理系统的实施步骤和技术路线 .探讨了产品数据管理的实施方法 ,并将该方法成功地应用于实际的产品数据管理系统的实施过程中 .     

系统方法论研究的现状分析与展望

对目前系统方法论的研究进行分类：硬系统方法论、软系统方法论和批评性系统方法论，分析了不同系统方法的哲学思想、方法步骤及其局限性，探讨了未来系统方法论发展的形式。     

ISAR target recognition based on non-negative sparse coding

Aiming at technical difficulties in feature extraction for the inverse synthetic aperture radar (ISAR) target recognition, this paper imports the concept of visual perception and presents a novel method, which is based on the combination of non-negative sparse coding (NNSC) and linear discrimination optimization, to recognize targets in ISAR images. This method implements NNSC on the matrix constituted by the intensities of pixels in ISAR images for training, to obtain non-negative sparse bases which characterize sparse distribution of strong scattering centers. Then this paper chooses sparse bases via optimization criteria and calculates the corresponding non-negative sparse codes of both training and test images as the feature vectors, which are input into k neighbors classifier to realize recognition finally. The feasibility and robustness of the proposed method are proved by comparing with the template matching, principle component analysis (PCA) and non-negative matrix factorization (NMF) via simulations.     

Improved adaptive pruning algorithm for least squares support vector regression

As the solutions of the least squares support vector regression machine(LS-SVRM) are not sparse,it leads to slow prediction speed and limits its applications.The defects of the existing adaptive pruning algorithm for LS-SVRM are that the training speed is slow,and the generalization performance is not satisfactory,especially for large scale problems.Hence an improved algorithm is proposed.In order to accelerate the training speed,the pruned data point and fast leave-one-out error are employed to validate the temporary model obtained after decremental learning.The novel objective function in the termination condition which involves the whole constraints generated by all training data points and three pruning strategies are employed to improve the generalization performance.The effectiveness of the proposed algorithm is tested on six benchmark datasets.The sparse LS-SVRM model has a faster training speed and better generalization performance.     

Novel reference range selection method in InlSAR imaging

Aiming at the reference range selection for different antennas in interferometric inverse synthetic aperture radar (InISAR) systems, this paper proposes a respective focusing (RF) method. The reference ranges for echoes of different antennas are selected respectively for RF, which is different from the traditional uniform focusing (UF) with the same reference range applied to all the antennas. First, a comparison between UF and RF for InISAR signal model considering the ranging error is given. Compared with RF, UF has an advantage in overcoming the ranging error differences between different antennas. Then the influence of ranging error upon the interferometric imaging with RF is investigated particularly, and it is found that the ranging error differences between different antennas are far smaller than the wavelength, which is advantageous to imaging. By comparing the capabilities of interferometric imaging between RF and UF, it is concluded that RF is a better choice in conquering problems such as image mismatching and phase ambiguity even with ranging errors. Simulations demonstrate the validity of the proposed method.