Search results

South Korean multinational enterprises (MNEs) have developed rapidly since the late 1950s. This chapter investigates South Korean MNEs’ talent management, more specifically international recruitment and selection policies and practices in their Chinese operations.

Using the snowball method through Chinese and Korean networks we recruited ten Korean MNEs to participate in this research. We conducted semi-structured interviews with key individuals within the organisations.

It reveals that South Korean MNEs tend to adopt the polycentric approach or a mixed approach of being polycentric and ethnocentric to international staffing, with the number of expatriates reducing gradually over time. South Korean MNEs adopt ‘one-way selection’ in recruiting and selecting expatriates and localise recruitment procedures and selection criteria for host-country nationals.

South Korean MNEs have paid inadequate attention to: firstly, expatriates’ career development; and secondly, personal and family issues emerging from expatriation and repatriation. This study highlights these issues.

Panel data provide the possibilities of estimating individual treatment effects for multiple individuals. Two issues are considered: (1) differences in the estimated individual treatment effects are due to heterogeneity or a chance mechanism? (2) what is the best way to estimate the average treatment effects? Testing and aggregation methods are suggested. Monte Carlo simulations are also conducted to shed light on these two issues. An empirical analysis on the involvement of underground organization in China’s Peer-to-Peer (P2P) activities through the “anti-gang” campaign is also provided.

This paper provides a selective survey of the panel macroeconometric techniques that focus on controlling the impact of “unobserved heterogeneity” across individuals and over time to obtain valid inference for “structures” that are common across individuals and over time. We consider issues of (i) estimating vector autoregressive models; (ii) testing of unit root or cointegration; (iii) statistical inference for dynamic simultaneous equations models; (iv) policy evaluation; and (v) aggregation and prediction.

To reduce the influence of temperature on MEMS gyroscope, this paper aims to propose a temperature drift compensation method based on variational modal decomposition (VMD), time-frequency peak filter (TFPF), mind evolutionary algorithm (MEA) and BP neural network.

First, VMD decomposes gyro’s temperature drift sequence to obtain multiple intrinsic mode functions (IMF) with different center frequencies and then Sample entropy calculates, according to the complexity of the signals, they are divided into three categories, namely, noise signals, mixed signals and temperature drift signals. Then, TFPF denoises the mixed-signal, the noise signal is directly removed and the denoised sub-sequence is reconstructed, which is used as training data to train the MEA optimized BP to obtain a temperature drift compensation model. Finally, the gyro’s temperature characteristic sequence is processed by the trained model.

The experimental result proved the superiority of this method, the bias stability value of the compensation signal is 1.279 × 10^–3°/h and the angular velocity random walk value is 2.132 × 10^–5°/h/vHz, which is improved compared to the 3.361°/h and 1.673 × 10^–2°/h/vHz of the original output signal of the gyro.

This study proposes a multi-dimensional processing method, which treats different noises separately, effectively protects the low-frequency characteristics and provides a high-precision training set for drift modeling. TFPF can be optimized by SEVMD parallel processing in reducing noise and retaining static characteristics, MEA algorithm can search for better threshold and connection weight of BP network and improve the model’s compensation effect.

This study aims to demonstrate the numerical application of differential quadrature (DQ) methods and show the experimental application of free vibration analysis of fiber-metal laminated composite (FML) plates with various boundary conditions.

The FMLs are hybrid structures consisting of fiber-reinforced polymer matrix composites such as carbon, glass, aramid and different metal sheets, and are currently widely used in the automobile, aircraft and aerospace industries. Thus, free vibration analysis of these hybrid materials is necessary for the design process. The governing equations of motion are derived based on the classical plate theory. The DQ, generalized DQ (GDQ) and harmonic DQ (HDQ) differential quadrature methods have been used to solve the governing equations of an FML composite plate numerically. The accuracy and convergence of the numerical model have been verified by comparing the results available in the published literature with the results obtained from these methods. Moreover, an experimental procedure has been performed in order to compare the results against those of the numerical methods.

It is noteworthy that a high degree of similarity and accuracy was observed between the numerical results obtained by the DQ methods and the experimental results. Thus, the present study validates the applicability of the DQ methods for designing the FML composite plates.

In this study, the advantages of the DQ methods have been demonstrated differently from previous studies on the vibration analysis of the FML plates.

Since the implementation of the New Cooperative Medical Scheme (NCMS) in 2003, this program has experienced rapid growth. Even so, little is known about the association between NCMS expansion and labor force supply among rural residents in China. The purpose of this paper is to examine the effects of the NCMS on labor force supply for rural Chinese populations.

Using data from the China Health and Nutrition Survey (CHNS), a difference-in-differences (DD) approach is employed to estimate the impact of NCMS expansion on labor supply outcomes, including hours of worked in agriculture, off-farm labor force participation, not working, and weeks off due to illness. A number of falsification tests are conducted to identify whether the assumption of common trends of DD analyses is satisfied. The robustness of results is checked through additional estimation, including panel fixed effects and instrumental variable approach.

Results show that the NCMS expansion has a positive effect on the hours of worked in agriculture and off-farm labor force participation, and reduces the likelihood of not working and weeks off due to illness. The effect on hours of agricultural production is larger for male adults, those aged 50 or more, and individuals in low-income families. This study demonstrates the importance of potential health improvements from public health insurance in promoting rural residents’ labor productivity.

Studies concerning the effects of public health insurance on labor supply in developing countries remain limited. The findings of this study provide important insights into how public health insurance programs, like the NCMS, may affect patterns of labor supply among rural residents, and can help policymakers improve health policies aimed to reduce the number of uninsured farmers while maintaining high levels of labor supply, productivity, and health status among the most vulnerable of populations.

Structural performance of additively manufactured parts is deposition path-dependent because of the induced material anisotropy. Hence, this paper aims to contribute a novel idea of concurrently performing the deposition path planning and the structural topology optimization for additively manufactured parts.

The concurrent process is performed under a unified level set framework that: the deposition paths are calculated by extracting the iso-value level set contours, and the induced anisotropic material properties are accounted for by the level set topology optimization algorithm. In addition, the fixed-geometry deposition path optimization problem is studied. It is challenging because updating the zero-value level set contour cannot effectively achieve the global orientation control. To fix this problem, a level set-based multi-step method is proposed, and it is proved to be effective.

The proposed concurrent design method has been successfully applied to designing additively manufactured parts. The majority of the planned deposition paths well match the principle stress direction, which, to the largest extent, enhances the structural performance. For the fixed geometry problems, fast and smooth convergences have been observed.

The concurrent deposition path planning and structural topology optimization method is, for the first time, developed and effectively implemented. The fixed-geometry deposition path optimization problem is solved through a novel level set-based multi-step method.

This paper aims on the trajectory tracking of the developed six wheel-legged robot with heavy load conditions under uncertain physical interaction. The accuracy of trajectory tracking and stable operation with heavy load are the main challenges of parallel mechanism for wheel-legged robots, especially in complex road conditions. To guarantee the tracking performance in an uncertain environment, the disturbances, including the internal friction, external environment interaction, should be considered in the practical robot system.

In this paper, a fuzzy approximation-based model predictive tracking scheme (FMPC) for reliable tracking control is developed to the six wheel-legged robot, in which the fuzzy logic approximation is applied to estimate the uncertain physical interaction and external dynamics of the robot system. Meanwhile, the advanced parallel mechanism of the electric six wheel-legged robot (BIT-NAZA) is presented.

Co-simulation and comparative experimental results using the BIT-NAZA robot derived from the developed hybrid control scheme indicate that the methodology can achieve satisfactory tracking performance in terms of accuracy and stability.

This research can provide theoretical and engineering guidance for lateral stability of intelligent robots under unknown disturbances and uncertain nonlinearities and facilitate the control performance of the mobile robots in a practical system.

This study examines the relationship between food experience, emotion, place attachment, and tourists' revisit behavioral intention. A survey questionnaire is conducted on-site in Lukang and distributed to 408 tourists. The dimensions of food experience are established through factor analysis, and a hypothesized model of the relationships between the constructs is tested using structural equation modeling (SEM). The results indicate that tourists' food experiences included local flavor, media recommendation, local learning, life transfer, and interpersonal sharing. In addition, food experience has a significant impact on emotion and place attachment, and emotion has a substantial effect on place attachment. Finally, place attachment significantly impacts tourists' revisit behavioral intention. The study makes a significant theoretical contribution by identifying food experience, emotion, and place attachment as the salient predictors of heritage tourists' revisit intention. Furthermore, the study suggests that food experiences enhance effective bonding at tourism destinations.