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The present research responds to researchers’ calls for more research of consumer animosity on potential boundary conditions (e.g. product categories) and marketing strategies that may mitigate such negative impacts on marketers’ product and/or brand performance, with a special focus on the soft service sector. This paper aims to address the unique characteristics of service internationalization, i.e. cultural embeddedness, hybridized country origins and high consumption visibility, by proposing a social identity signaling model to explain consumer animosity effects in the soft service sector.

Two surveys (Pretest with 240 participants and Study 1 with 351 participants) and one experiment (Study 2 with 731 participants) were conducted to empirically test our hypotheses in the Japanese-Chinese relationship context.

The stronger the national/cultural symbolism and social expressiveness, the stronger the consumer avoidance for the service category. Then the consumer culture positioning strategy that can mitigate an offending country’s cultural symbolism can reduce consumer avoidance.

This research introduces two factors that could affect the negative social identity signaling capacity of service categories in the animosity context: the national/cultural symbolism reflecting an offending country and the social expressiveness communicating social identity. In line with the social identity signaling perspective, the present research specifically uses consumer avoidance as the dependent variable to capture the notion that consumers avoid consuming services because they wish to avoid being associated with an offending country that may threaten their in-group social identities.

The purpose of this paper is to argue that Bernoulli's “utility function solution to the St Petersburg paradox” was wrong and to find a new method to solve the paradox.

This goal is attained through two ways: using Bernoulli's and Kramer's utility function to construct new paradoxes; and designing and implementing a new St Petersburg game which does not carry the effect of diminishing marginal utility.

In this paper, the author finds that Bernoulli's “utility function solution to the St Petersburg paradox” was wrong, and also finds a new model to solve the paradox, which is also a brand‐new model of estimates under uncertainty.

Bernoulli put forward the diminishing marginal utility of currency and thus accordingly provided the utility function solution to solve the paradox. This paper indicates that the Bernoulli's utility function solution does not work. Thus, further research needs to be taken in several aspects: is the diminishing marginal utility of currency tenable? Does the marginal utility of currency decrease monotonically? Are concave utility functions represented by negative index functions which are widely used in theoretical study reasonable?

The paper proposes a brand‐new possible research idea and direction for economic theoretical researches based on uncertainty.

This paper proved the untenability of the utility function solution to solve the St Petersburg paradox for the first time and proposed the pioneering “risk adjustment model” of estimates under uncertainty.

This article has been withdrawn as it was published elsewhere and accidentally duplicated. The original article can be seen here: 10.1108/00483480710716759. When citing the article, please cite: Bih-Shiaw Jaw, Ya-Hui Ling, Christina Yu-Ping Wang, Wen-Ching Chang, (2007), “The impact of culture on Chinese employeesʼ work values”, Personnel Review, Vol. 36 Iss: 1, pp. 128 - 144.

This paper is a study of the current trends and conditions of electronic resources for Chinese studies, based on a recent survey on the Internet of 29 Chinese libraries in North America and eight Chinese libraries in China, Taiwan and Hong Kong. The survey discussed current electronic resources for Chinese studies, with a union list of major Chinese language databases currently used in libraries in Asia and the US. Current views on the use and development of electronic resources for Chinese studies were summarised.

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.

The purpose of this paper is to explore Taiwan’s regional energy efficiency trend and complement the work of the total-factor energy efficiency (TFEE) index proposed by Hu and Wang (2006). It further extends panel data stochastic frontier analysis (SFA) modeling for estimating disaggregate energy efficiency.

This paper applies the panel data stochastic production frontier to estimate the TFEE scores for 20 administrative regions in Taiwan over the period 2004-2015. The SFA models include five inputs (employed population, amount of productive electricity power consumed, amount of electricity consumed for household and non-household electric lighting, amount of gasoline sales, and amount of diesel sales) and one output (total real income in the base year of 2011).

This research concludes with three main findings: the inefficient administrative regions of Taiwan include mostly large industrial parks and the petrochemical industry cluster; the top five administrative regions with inefficient diesel use are mostly metropolitan areas that the concern of air pollution caused by diesel system arouses the awareness to use less diesel fuel; and the average TFEE score on household and non-household electric lighting is higher than the usage efficiency of productive electricity power, gasoline, and diesel, but there is still room for efficiency improvement.

Most administrative regions in Taiwan are not efficient in almost all kinds of energy use. The results show that the efficiencies of using productive electricity power, gasoline, and diesel need to be improved a lot more.

This paper aims to propose a two-period model, including an original manufacturer, a retailer and a third-party remanufacturer, in which the products manufactured by the original manufacturer are patent-protected and the remanufacturing degree of remanufactured products influences the purchasing decisions of consumers.

This paper analyzes the decisions of the original manufacturer, the retailer and the third-party remanufacturer of two periods, using Stackelberg game and obtains the equilibrium solutions of the three parties.

The study finds that consumers’ focus degree to the remanufacturing degree has a negative correlation with the equilibrium unit patent-licensing fee, the retail price of remanufactured products, the remanufacturing degree of remanufactured products and the wholesale price of new products in the first period, but has a positive correlation with the retail price of new products in the second period.

(1) Consumers’ focus degree to the remanufacturing degree has a negative correlation with the equilibrium unit patent-licensing fee, the retail price of remanufactured products, the remanufacturing degree of remanufactured products and the wholesale price of new products in the first period, but has a positive correlation with the retail price of new products in the second period. (2) The remanufacturing action efficiency of the third-party remanufacturer has a positive correlation with the equilibrium unit patent-licensing fee, the retail price of remanufactured products, the remanufacturing degree of remanufactured products and the wholesale and retail prices of new products in the second period.

The purpose of this paper is to evaluate the forecasting performance of grey prediction models on educational attainment vis-à-vis that of exponential smoothing combined with multiple linear regression employed by the National Center for Education Statistics (NCES).

An out-of-sample forecasting experiment was carried out to compare the forecasting performances on educational attainments among GM(1,1), GM(1,1) rolling, FGM(1,1) derived from the grey system theory and exponential smoothing prediction combined with multivariate regression. The predictive power of each model was measured based on MAD, MAPE, RMSE and simple F-test of equal variance.

The forecasting efficiency evaluated by MAD, MAPE, RMSE and simple F-test of equal variance revealed that the GM(1,1) rolling model displays promise for use in forecasting educational attainment.

Since the possible inadequacy of MAD, MAPE, RMSE and F-type test of equal variance was documented in the literature, further large-scale forecasting comparison studies may be done to test the prediction powers of grey prediction and its competing out-of-sample forecasts by other alternative measures of accuracy.

The findings of this study would be useful for NCES and professional forecasters who are expected to provide government authorities and education policy makers with accurate information for planning future policy directions and optimizing decision-making.

As a continuing effort to evaluate the forecasting efficiency of grey prediction models, the present study provided accumulated evidence for the predictive power of grey prediction on short-term forecasts of educational statistics.

The aim of this paper is to demonstrate the application of optimal globalization grey relational analysis (GGRA) as a workable decision-making tool to prioritize emotional intelligence (EI) training needs of specific groups of academic leaders.

The study involved administrating the emotional skills assessment process to 50 academic leaders in the USA and 50 in Taiwan. Optimal GGRA was utilized to prioritize EI training needs of the two distinct groups of academic leaders.

Results of the optimal GGRA suggest that context-specific EI interventions focusing on enhancing weak areas of emotional competency are made possible through optimal globalization grey analysis.

Optimal GGRA is introduced as a valid decision-making technique for planning effective EI interventions. The results have implications for designing training courses targeting on enhancing weak areas of emotional competency.

The utility of optimal GGRA as a decision-making tool to prioritizing training needs for the two cultural groups of academic leaders in the study aims at going beyond the narrow psychometric perspectives of measurements on leadership potentials and reaching out to practical approaches to leadership development and training.

The purpose of this paper is to propose a unified optimization design method and apply it to handle the brake squeal instability involving various uncertainties in a unified framework.

Fuzzy random variables are taken as equivalent variables of conventional uncertain variables, and a unified response analysis method is first derived based on level-cut technique, Taylor expansion and central difference scheme. Next, a unified reliability analysis method is developed by integrating the unified response analysis and fuzzy possibility theory. Finally, based on the unified reliability analysis method, a unified reliability-based optimization model is established, which is capable of optimizing uncertain responses in a unified way for different uncertainty cases.

The proposed method is extended to perform squeal instability analysis and optimization involving various uncertainties. Numerical examples under eight uncertainty cases are provided and the results demonstrate the effectiveness of the proposed method.

Most of the existing methods of uncertainty analysis and optimization are merely effective in tackling one uncertainty case. The proposed method is able to handle the uncertain problems involving various types of uncertainties in a unified way.