Search results

This study aims to investigate the influence of the Confucius Institute (CI) on outward foreign direct investment (OFDI) by China and its potential interaction with cultural difference and institutional quality in host countries.

In the empirical study, the gravity model is adopted as the benchmark to investigate the effects of CI on China's OFDI using the ordinary least squares or Poisson Pseudo Maximum Likelihood estimators. Panel data on China's OFDI from 2004 to 2015 are used. Cultural difference and institutional quality are included explicitly as control variables to examine the effects of CI on China's OFDI.

CI has a significant positive effect on China’s OFDI, and this effect depends on the cultural difference and institutional quality of the host country. The impact of CI on China’s OFDI is more prominent in host countries with a smaller cultural difference or lower institutional quality.

CI is a comprehensive platform for foreign cultural exchange and signifies the rebirth of Confucianism in China. The present study shows that CI can stimulate the growth of China’s OFDI, with implications for other Asian countries influenced by Confucianism. Based on the results of the study, strategies for “Going Global” and encouraging economic growth based on cultural exchange and the recognition of host country heterogeneities are proposed.

The purpose of this paper is to investigate the effect of titanium nitride (TiN) on microstructure and composition of 96.5Sn3Ag0.5Cu (SAC305) lead-free solder joints under a large temperature gradient.

In this paper, SAC305 lead-free composite solder containing 0.05 Wt.% TiN was prepared by powder metallurgy method. A temperature gradient generator was designed and the corresponding samples were also prepared. The microstructural evolution, internal structure and elemental content of SAC305 and SAC305/TiN solder joints before and after thermal loading were comparatively studied.

The experimental results show that the addition of the TiN reinforcing phase can effectively inhibit the diffusion and migration of copper atoms and, therefore, affect the distribution of newly formed Cu-Sn IMC in solder joints under the condition of thermal migration (TM). Compared with the SAC305 solder joint, the interconnection interface and internal structure of the composite solder joint after 600 h of TM are also relatively complete.

The TiN reinforcing phase is proven effective to mitigate the TM behavior in solder joints under thermal stressing. Specifically, based on the observation and analysis results of microstructure and internal structure of composite solder joint, the TiN particle can change the temperature gradient distribution of the solder joint, so as to suppress the diffusion and migration of Sn and Cu atoms. In addition, the results of Micro-CT and compositional analysis also indicate that the addition of TiN reinforcement is very helpful to maintain the structural integrity and the compositional stability of the solder joint. Different from other ceramic reinforcements, TiN has good thermo- and electro-conductivity and the thermal-electrical performance of composite solder will not be significantly affected by this reinforcement, which is also the main advantage of selecting TiN as the reinforcing phase to prepare composite solder. This study can not only provide preliminary experimental support for the preparation of high reliability lead-free composite solder but also provide a theoretical basis for the subsequent study (such as electro-thermo distribution in solder joints), which has important application significance.

Motivated by empirical features that characterize cryptocurrency volatility data, the authors develop a forecasting strategy that can account for both model uncertainty and heteroskedasticity of unknown form. The theoretical investigation establishes the asymptotic optimality of the proposed heteroskedastic model averaging heterogeneous autoregressive (H-MAHAR) estimator under mild conditions. The authors additionally examine the convergence rate of the estimated weights of the proposed H-MAHAR estimator. This analysis sheds new light on the asymptotic properties of the least squares model averaging estimator under alternative complicated data generating processes (DGPs). To examine the performance of the H-MAHAR estimator, the authors conduct an out-of-sample forecasting application involving 22 different cryptocurrency assets. The results emphasize the importance of accounting for both model uncertainty and heteroskedasticity in practice.

Based on the error analysis, the authors proposed a new kind of high accuracy boundary element method (BEM) (HABEM), and for the large-scale problems, the fast algorithm, such as adaptive cross approximation (ACA) with generalized minimal residual (GMRES) is introduced to develop the high performance BEM (HPBEM). It is found that for slender beams, the stress analysis using iterative solver GMRES will difficult to converge. For the analysis of slender beams and thin structures, to enhance the efficiency of GMRES solver becomes a key problem in the development of the HPBEM. The purpose of this paper is study on the preconditioning method to solve this convergence problem, and it is started from the 2D BE analysis of slender beams.

The conventional sparse approximate inverse (SAI) based on adjacent nodes is modified to that based on adjacent nodes along the boundary line. In addition, the authors proposed a dual node variable merging (DNVM) preprocessing for slender thin-plate beams. As benchmark problems, the pure bending of thin-plate beam and the local stress analysis (LSA) of real thin-plate cantilever beam are applied to verify the effect of these two preconditioning method.

For the LSA of real thin-plate cantilever beams, as GMRES (m) without preconditioning applied, it is difficult to converge provided the length to height ratio greater than 50. Even with the preconditioner SAI or DNVM, it is also difficult to obtain the converged results. For the slender real beams, the iteration of GMRES (m) with SAI or DNVM stopped at wrong deformation state, and the computation failed. By changing zero initial solution to the analytical displacement solution of conventional beam theory, GMRES (m) with SAI or DNVM will not be stopped at wrong deformation state, but the stress error is still difficult to converge. However, by GMRES (m) combined with both SAI and DNVM preconditioning, the computation efficiency enhanced significantly.

This paper presents two preconditioners: DNVM and a modified SAI based on adjacent nodes along the boundary line of slender thin-plate beam. In the LSA, by using GMRES (m) combined with both DNVM and SAI, the computation efficiency enhanced significantly. It provides a reference for the further development of the 3D HPBEM in the LSA of real beam, plate and shell structures.

The authors propose to estimate a varying coefficient panel data model with different smoothing variables and fixed effects using a two-step approach. The pilot step estimates the varying coefficients by a series method. We then use the pilot estimates to perform a one-step backfitting through local linear kernel smoothing, which is shown to be oracle efficient in the sense of being asymptotically equivalent to the estimate knowing the other components of the varying coefficients. In both steps, the authors remove the fixed effects through properly constructed weights. The authors obtain the asymptotic properties of both the pilot and efficient estimators. The Monte Carlo simulations show that the proposed estimator performs well. The authors illustrate their applicability by estimating a varying coefficient production frontier using a panel data, without assuming distributions of the efficiency and error terms.

The effects of social learning and network externalities in the diffusion of a new product imply that there should be local spillovers from existing owners to new adopters in a closely related community. Using the data from a unique household survey in rural China, this paper aims to examine the importance of local spillovers in the diffusion of two major durable goods, washing machine and refrigerator.

Based on a 1999 rural household survey of durable goods consumption conducted by the National Bureau of Statistics (NBS) of China, the authors examine the likelihood of rural households adopting a washing machine and a refrigerator during 1998-1999, respectively.

The estimation results indicate that a household is more likely to buy its first durable good in villages where a large share of households already own one. Further evidence suggests that these patterns are unlikely to be explained by unobserved local characteristics. When examined in more detail, the extent of local spillovers appears to be positively related to the household education level.

First, the study reveals the importance of local spillovers in the diffusion of these two durables. Specifically, 64 percent of washing machine adoptions during 1998-1999 are due to these spillovers. For refrigerator adoptions, the proportion is 55 percent. Second, to the authors' best knowledge, the authors are among the first to test and provide evidence on the interaction between education level and local spillovers based on the learning hypothesis.

Past research shows that users of smart home devices (SHDs) have privacy concerns. These concerns have been validated from technical research that shows SHDs introduce a lot of privacy risks. However, there is limited research in addressing these concerns and risks. This paper aims to bridge this gap by informing the design of data-related privacy controls for SHDs.

In this paper, the authors follow a user-centered design approach to design data-related privacy controls from design requirements backed by literature. The authors test the design for usability and perceived information control using psychometrically validated scales. For this purpose, two variations of the prototype (MyCam1 with a listing of data-related privacy controls and MyCam2 with three privacy presets) were created and tested them in a between-subjects experimental setting. Study participants (n = 207) were recruited via Mechanical Turk and asked to use the prototype app. An online survey was distributed to the participants to measure some usability and privacy-related constructs.

Findings show that the presented prototype designs were usable and met the privacy control needs of users. The prototype design with privacy presets (MyCam2) was found to be significantly more usable than the list of privacy controls (MyCam1).

The findings of this paper are original and build on the paper presented at the International Symposium on Human Aspects of Information Security and Assurance (HAISA 2022). This paper contributes improved and usable designs of privacy controls for smart home applications.

Large supermarkets, chain stores and enterprises with large-scale warehousing put forward higher standards and requirements for the automation and informatization of warehouses. As one of the fast-growing commercial supermarkets in China, the traditional warehouse management mode has restricted the rapid development of Yonghui Superstores to a certain extent. The purpose of this paper is to find out how the existing warehouse mode can be changed and to solve the existing problems of warehouse management of Yonghui Superstores.

This research puts forward construction of warehouse center, which is based on radio frequency identification (RFID) and sensor technology, then designs the model for receiving, storage, operations management, distribution and outbound to solve the existing problems of warehouse management of Yonghui Superstores.

What technologies should be adopted to meet storage requirements? How to monitor the storage environment in real time and improve the operation and management level of the warehouse? This study found that building a warehouse center based on RFID and sensor technology was a good solution.

The Yonghui Superstores warehouse center model lacks corresponding simulation experiments, and the investment and income are difficult to estimate quantitatively.

This paper has designed and discussed the warehouse center model based on RFID and sensor technology, which provides a few references for the actual investment and construction of a warehouse center. In addition, the warehouse center model has strong generalized applicability and could be widely used in various enterprises.

The warehouse center could improve the warehouse management level of Yonghui Superstores and change the traditional warehouse management mode. To some extent, it improves the enterprise flexibility of the market, which will be of great significance to improve business efficiency and enhance brand image and competitiveness.

This study takes Yonghui Superstores as a case to analyze the problems of warehousing management in detail and then designs a warehouse center based on RFID and sensor technology. The study discusses the location and distribution, software and hardware selection, benefits evaluation, significances and return on investment, which makes the warehouse center model versatile, technically feasible and economically applicable.

The purpose of this paper is to examine the impacts of farmland renting-in on planted grain acreage.

A survey data of five counties were analyzed with the two-stage ordinary least squares model.

Households renting-in land trended to plant more maize, and the more land was rented by a household the more maize was planted, while wheat acreage showed non-response to farmland renting-in.

Overall, the analysis suggests that policy makers should be prepared for different changing trends of grain crop acreage across the nation as farmland transfer continues. Future research should pay attention to the effect of farmland transfer on agricultural productivity and rural household income growth.

As the Chinese Government is promoting larger-scale and more mechanized farms as a way of protecting grain security, it is important to understand whether farmland renting-in will reduce planted grain acreage. This study provides empirical evidence showing the answer to that question may differ across different regions and depend on the particular grain crop in question.

Introduction: When people need to take decisions, being economic decisions or otherwise, their decisions tend to rely on information the brain has already processed, and this includes the resources that the person has already invested. This is called sunk cost bias in the behavioural economics literature. On the other hand, mental practices could lead to the mental accounting bias, where people allocate a different value to a fixed amount of money, depending on circumstances.

Purpose: In this chapter, both biases mental accounting and sunk cost are investigated for the tourism industry in Turkey.

Methodology: The topic is researched through scenario-based questions and the Chi-square Automatic Interaction Detector (CHAID) method is applied.

Findings: As a result, it could be reported that people, regardless of gender, fall into sunk cost and mental accounting biases in decisions relating to their vacations. Mental accounting biases can be primarily explained using the scenario questions posed rather than gender, education, and income while sunk cost bias is explained by status, ‘being s university student’ and ‘income level’.

Practical implications: Rapid price changes in the tourism industry can disturb consumers who are mental accounting and sunk cost biased. So, they can change their holiday preferences or be dissatisfied with it and give negative feedback.