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FROM BUSINESS STRATEGY AND SOCIAL CAPITAL PERSPECTIVE TO TRAVEL AGENCIES’ COMPETITIVE ADVANTAGE
Chih-Hsing Liu,Jeou-Shyan Horng,Sheng-Fang Chou,Yung-Chuan Huang,Bernard Gan,Wei-Long Lee 글로벌지식마케팅경영학회 2018 Global Marketing Conference Vol.2018 No.07
Many firms see organizational learning systems as critical to facilitating competitive advantage. However, until now, few tourism studies have empirically investigated and identified how the different characteristics of highly competitive organizations, such as travel agencies, influence competitive advantage in a dynamic environment. This study uses a mediation-moderation analysis for such an empirical examination. A total of 288 travel agencies from Taiwan were analysed. The authors found that travel agencies’ shared goals may influence competitive advantage through characteristics of dynamic capability development, differential strategy implication and social capital accumulation. Greater levels of organizational learning may positively strengthen the relationships between (a) shared goals and dynamic capability, (b) shared goals and social capital, and (c) social capital and competitive advantage. Implications of these findings for managerial and theoretical frameworks are also discussed.
An Improvement on Robust H<SUB>∞</SUB> Control for Uncertain Continuous-Time Descriptor Systems
Hung-Jen Lee,Shih-Wei Kau,Yung-Sheng Liu,Chun-Hsiung Fang,Jian-Liung Chen,Ming-Hung Tsai,Li Lee 대한전기학회 2006 International Journal of Control, Automation, and Vol.4 No.3
This paper proposes a new approach to solve robust H∞ control problems for uncertain continuous-time descriptor systems. Necessary and sufficient conditions for robust H∞ control analysis and design are derived and expressed in terms of a set of LMIs. In the proposed approach, the uncertainties are allowed to appear in all system matrices. Furthermore, a couple of assumptions that are required in earlier design methods are not needed anymore in the present one. The derived conditions also include several interesting results existing in the literature as special cases.
Tsai Li-Jen,Chung Chi-Hsiang,Lin Chien-Jung,Su Sheng-Chiang,Kuo Feng-Chih,Liu Jhih-Syuan,Chen Kuan-Chan,Ho Li-Ju,Kuo Chih-Chun,Chang Chun-Yung,Lin Ming-Hsun,Chu Nain-Feng,Lee Chien-Hsing,Hsieh Chang-H 한국한의학연구원 2022 Integrative Medicine Research Vol.11 No.2
Background: Diabetic patients are at high risk of developing cancer. Traditional Chinese medicine (TCM) has become increasingly popular as an adjuvant treatment for patients with chronic diseases, and some studies have identified its beneficial effect in diabetic patients with cancer. The purpoes of this study was to outline the potential of TCM to attenuate hospitalization and mortality rates in diabetic patients with carcinoma in situ (CIS). Methods: A total of 6,987 diabetic subjects with CIS under TCM therapy were selected from the National Health Insurance Research Database of Taiwan, along with 38,800 of 1:1 sex-, age-, and index year-matched controls without TCM therapy. Cox proportional hazard analysis was conducted to compare hospitalization and mortality rates during an average of 15 years of follow-up. Results: A total of 3,999/1,393 enrolled-subjects (28.62%/9.97%) had hospitalization/mortality, including 1,777/661 in the TCM group (25.43%/9.46%) and 2,222/732 in the control group (31.80%/10.48%). Cox proportional hazard regression analysis showed a lower rate of hospitalization and mortality for subjects in the TCM group (adjusted HR=0.536; 95% CI=0.367–0.780, P<0.001; adjusted HR=0.783; 95% CI=0.574– 0.974, P = 0.022). Kaplan-Meier analysis showed that the cumulative risk of hospitalization and mortality in the case and control groups was significantly different (log rank, P<0.001 and P = 0.011, respectively). Conclusions: Diabetic patients with CIS under TCM therapy were associated with lower hospitalization and mortality rates compared to those without TCM therapy. Thus, TCM application may reduce the burden of national medical resources.
Grey Neural Network-Based Forecasting System for Vision-Guided Robot Trajectory Tracking
Shih-Hung Yang,Chung-Hsien Chou,Chen-Fang Chung,Wen-Pang Pai,Tse-Han Liu,Yung-Sheng Chang,Jung-Che Li,Huan-Chan Ting,Yon-Ping Chen 제어로봇시스템학회 2011 제어로봇시스템학회 국제학술대회 논문집 Vol.2011 No.10
This paper presents a grey neural network-based forecasting system (GNNFS) in solving the prediction problem. GNNFS adopts a grey model to predict the signal and a neural network (NN) to forecast the prediction error of the grey model. A sequential batch learning (SBL) is developed to adjust the weights of the NN. The proposed GNNFS is applied to a binocular robot, called an Eye-Robot, for human-robot interaction which involved predicting the trajectory of a participant’s hand and tracking the hand. By applying the SBL, the GNNFS can gradually learn to predict the trajectory of the hand and track it well. The experimental results show that the GNNFS can carry out the SBL in real-time for vision-guided robot trajectory tracking.