Mahidol University International College

About: Mahidol University International College is a based out in . It is known for research contribution in the topics: Tourism & Corporate governance. The organization has 240 authors who have published 485 publications receiving 6095 citations.

Internationalization Factors of Thai Multinationals and Thailand's Bilateral Trade Policy

Abstract: This article investigates the impact of Thailand's recent bilateral free-trade agreements (FTAs) on the internationalization of Thai multinational enterprises (MNEs). The results highlight the relative importance of internal and external factors in the internationalization of developing country MNEs. The empirical evidence indicated that Thai MNEs judged bilateral FTAs as a critical facilitator of internationalization success. The FTAs facilitated firms' exports to a certain degree and marginally expedited firms' international purchasing activities. The influence of FTAs on firms' foreign investment was not discernible.

Perfect switching of the spin polarization in a ferromagnetic gapless graphene/superconducting gapped graphene junction

Abstract: With the fabrication of gapped graphene, interest in the tunneling spectroscopy in graphene-based FG/SG junctions in which one side consists of a gapless ferro-magnetic graphene (FG) and the other side, of a gapped superconducting graphene (SG) has arisen. The carriers in the gapless (gapped) graphene are 2D relativistic particles having an energy spectrum given by E = ℏ 2 v F 2 k 2 + ( mv F 2 ) 2 (where mv F 2 is the gap and v F is the Fermi velocity). The spin currents in this FG/SG junction are obtained within the framework of the extended Blonder–Tinkham–Klapwijk (BTK) formalism. The effects of the superconducting energy gap in SG, of the gap mv F 2 which opened in the superconducting graphene, of the exchange field in FG, of the spin-dependent specular Andreev reflection, of the effective Fermi energy ( E FF ) of FG and of the bias voltage across the junction ( V ) are simulated. It is seen that by adjusting E FF or V , the spin polarization (defined as SP(%) = 100% × ( G ↑ − G ↓ )/( G ↑ + G ↓ )) can be switched from a pure spin up (SP = +100%) state to pure spin down (SP = −100%) state.

Drowsiness Detection using Facial Emotions and Eye Aspect Ratios

Abstract: Drowsy drivers are a major cause of many road accidents around the world. Facial emotions are known to be one of the visual cues for detecting drowsiness. In this paper, we propose a machine learning approach to drowsiness detection based on using a combination of facial emotion features extracted by using deep convolutional neural networks (CNN) and eye-aspect-ratio (EAR) features. The combined feature vectors are then used for training a classifier. From our experiments, we obtain a classification accuracy of 81.7% when we use the combined features with a support vector machines (SVM) classifier.

Using demographic identification to estimate the effects of board size on corporate performance

Abstract: Motivated by agency theory, we investigate the effect of board size on corporate outcomes. To address endogeneity, we exploit the variations in the director-age populations across the states in the US. We argue that firms with access to a larger pool of potential directors tend to have larger boards. Consistent with this notion, our empirical results show that firms located where the size of the director-age population is larger have significantly larger board size. Because the director-age population represents broad demographic trends outside of any firm’s control, it is unlikely related to firm outcomes or policies and should be exogenous. Using the director-age population as our instrument, we estimate the effects of board size on firm value and profitability. Our approach is less vulnerable to endogeneity and is more likely to show a causal effect.