Browsing by Author "Lin, Hang-Rung"

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A systematic approach for identifying level-1 error covariance structures in latent growth modeling
(2017-05-01)
Ding, Cherng G.
;
Jane, Ten-Der
;
Wu, Chiu-Hui
;
Lin, Hang-Rung
;
Shen, Chih-Kang
It has been pointed out in the literature that misspecification of the level-1 error covariance structure in latent growth modeling (LGM) has detrimental impacts on the inferences about growth parameters. Since correct covariance structure is difficult to specify by theory, the identification needs to rely on a specification search, which, however, is not systematically addressed in the literature. In this study, we first discuss characteristics of various covariance structures and their nested relations, based on which we then propose a systematic approach to facilitate identifying a plausible covariance structure. A test for stationarity of an error process and the sequential chi-square difference test are conducted in the approach. Preliminary simulation results indicate that the approach performs well when sample size is large enough. The approach is illustrated with empirical data. We recommend that the approach be used in LGM empirical studies to improve the quality of the specification of the error covariance structure.
Lessons from the global financial crisis for the semiconductor industry
(2015-10-01)
Wu, Chiu-Hui
;
Ding, Cherng G.
;
Jane, Ten-Der
;
Lin, Hang-Rung
;
Wu, Cheng-Ying
During the global financial crisis in 2008, governments around the world have used a variety of policies to support threatened industries and to stabilize financial systems. In the present study, we empirically compare the patterns of the dynamic change in the financial performance of the semiconductor industry before and after government intervention by using the piecewise linear trajectory model for Japan, South Korea and Taiwan, three major economies for the industry. The empirical results indicate that during the global financial crisis, the performance of the semiconductor industry can benefit from government support, in spite of the fact that the improvement was somewhat delayed after intervention. Moreover, the change pattern of the performance depends on the performance factor and the economy. Based on the results obtained as well as literature support, we summarize the economic and industrial policies that might have demonstrated usefulness for the industry and discuss some implications. (C) 2015 Elsevier Inc. All rights reserved.
Using LGM analysis to identify hidden contributors to risk in the operation of a nuclear power plant
(2015-06-01)
Ding, Cherng G.
;
Lin, Hang-Rung
;
Wu, Chiu-Hui
;
Jane, Ten-Der
;
經營管理研究所
In this study, an approach is proposed to identify hidden contributors to risk in the operation of a nuclear power plant. Hypotheses linking safety performance to its influential factors are developed based on theory and literature. The failure to support the relational hypotheses with longitudinal safety performance data from a plant signifies hidden contributors to risk in the operation of the plant, which can be specifically identified by looking into the empirical results inconsistent with theoretical expectations. To demonstrate the use of the approach, we develop five hypotheses and analyze the longitudinal failure data for 28 years collected from 342 pumps in a large nuclear power plant by using latent growth modeling (LGM). The average trajectory of pump failures for the entire plant is inverted-U-shaped. Four hidden risk contributors in the operation of the sample plant have been identified. We suggest that, in addition to the adequacy of training and safety management systems, crew resource management be used to enhance nuclear safety for the sample plant. We recommend that the proposed approach be used for any other nuclear power plant to help identify hidden risk contributors and in other similar situations. (C) 2015 Elsevier Ltd. All rights reserved.