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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.

Despite the evident and dramatic increase in smartphone usage worldwide, some consumers continue to use traditional mobile phones. The purpose of this paper is to investigate the behavioral intentions of these laggard and non-smartphone users.

This current study examines the effects of consumer demographics, psychographics, and smartphone characteristics on the intentions of non-smartphone consumers to switch or resist the use of smartphones. Data were collected using a convenience sample of non-smartphone users in Taiwan. The proposed model is tested using the consistent partial least squares (PLSc) path modeling technique.

PLSc results indicate that consumer psychographics and smartphone characteristics play more important roles than consumer demographics. Specifically, price consciousness, nostalgia, and perceived ease of use are good predictors of intention to switch, whereas perceived usefulness and ease of use are strong predictors of the intention to resist smartphone adoption.

The results of this study have implications for mobile phone vendors and mobile manufacturers who target non-smartphone users or laggard adopters.

This study is among the few that focus on non-smartphone users’ perceptions of smartphones. Hence, this empirical study could contribute to the development and testing of theories related to the smartphone adoption process.

Based on generic reviews of research on school leadership, this study aims to conceptualize an emerging leadership competence model for further prioritizing school leadership training needs by decision-making trial and evaluation laboratory (DEMATEL)-based analytic network process (ANP). Targeting at a specific group of junior high school principals in Taiwan, the synthesized prioritization of core competences and competence indicators computed by DEMATEL-based ANP can be used as a blueprint for systematically developing school principal preparation programs elsewhere based on contextually specific needs and concerns.

For the purpose of detecting the priority of competences extracted from a plethora of literature in relation to school leaders’ skills, abilities and knowledge, a hybrid MCDM model, known as DEMATEL-based ANP, is used to snapshot critical leadership competences for tailoring the intended junior high school principal preparation program.

Results of global weight computations by DEMATEL-based ANP show that the overall prioritization of the five dimensions in ranking order are “Redesigning the organization,” “Related leadership practices,” “Setting Directions,” “Personal Characteristics” and “Developing People.” Factor-level analysis indicated that “Legality,” “Consensus Building,” “Shared Vision,” “Strategic Management,” “Authoritarianism,” “Modeling Behavior” and “High Performance Emphasis” were prioritized factors to be included in developing the intended school principal preparation program.

Contextually based findings yielded from DEMATEL-based ANP would only be applicable to the target context under investigation. Generalizing the findings to junior high school principals elsewhere might not be appropriate. Methods introduced in this study are extensible to further studies aiming at shaping leadership trainings in other school settings to achieve maximum impact based on contextually specific needs. Limitations associated with sophisticated mathematical computations involved in performing high-leverage MCDM models would shed light on the importance of interdisciplinary collaborations between scholars, practitioners and methodologists.

To efficiently deliver training for junior high school principals, the prioritization of core competences and competence indicators solicited by DEMATEL-based ANP can be used as a scenario-based reference for planning the intended school principal preparation program planning, as well as a mechanism for selecting and evaluating potential and incumbent school principals with desired leadership competences.

This study has used DELATEL-based ANP as a decision-making tool to disclose a plethora of competences extracted from different threads in the literature into a prioritized competence framework that differs from past one-size-fit-all approach to design and plan school principal preparation programs.

This paper aims to establish a prediction model of stable transmission time of spiral bevel gear during a loss-of-lubrication event in helicopter transmission system.

To observe the temperature change of spiral bevel gear during working condition, a test rig of spiral bevel gear was developed according to the requirements of experiments and carried out verification experiments.

The prediction is verified by the test of detecting the temperature of oil pool. The main damage form of helicopter spiral bevel gears under starved lubrication is tooth surface burn. The stable running time under oil-free lubrication is mainly determined by the degree of tooth surface burn control.

The experimental data of the spiral bevel gear oil-free lubrication process are basically consistent with the simulation prediction results. The results lay a foundation for the working life design of spiral bevel gear in helicopter transmission system under starved lubrication.

This paper aims to provide an analytic technique for determining the convection heat transfer and temperature of oil jet lubricated spur gears.

A multiphase flow model is developed to calculate the convection heat transfer coefficients on different gear faces during different contact conditions. The frictional heat is calculated and a method to distribute between the two gears is developed. A finite element model is established to calculate the temperatures in both meshing and cooling processes.

The convection heat transfer coefficients on different surfaces are obtained successfully. Area-related formulae are developed to calculate the heat distribution coefficients. The gear temperature reaches a maximum at the beginning of meshing, then reduces and gets minimum at pitch point, after that it increases again. The gear temperature descends rapidly to steady temperature during the short time of jet cooling process. The tendency of computational results coincides well with the experimental results.

The research presented here could be used in the design phase of the jet lubricated spur gears. The precise temperature is obtained to assess the thermal capacity of gears, from which the gear parameters and oil supply conditions could be adjusted and designed.

The finite element method has been increasingly applied in stress, thermal and dynamic analysis of gear transmissions. Preparing the models with different design and modification parameters for the finite element analysis is a time-consuming and highly skilled burden.

To simplify the preprocessing work of the analysis, a parametric finite element modeling method for spur and helical gears including profile and lead modification is developed. The information about the nodes and elements is obtained and exported into the finite element software to generate the finite element model of the gear automatically.

By using the three-dimensional finite element tooth contact analysis method, the effects of tooth modifications on the transmission error and contact stress of spur and helical gears are presented.

The results demonstrate that the proposed method is useful for verifying the modification parameters of spur and helical gears in the case of deformations and misalignments.

Modeling and analysis of dimensional variation propagation is a crucial support technology for variation reduction, product/process design evaluation and recognition of variation source. However, owing to the multi-deviation (i.e. part deviations and fixture deviations) and multi-interaction (i.e. part-to-part interaction, part-to-fixture interaction and station-to-station interaction) in assembly processes, it is difficult for designers to describe or understand the variation propagation (or accumulation) mechanism clearly. The purpose of this paper is to propose a variation propagation modeling and analysis (VPMA) method based on multiple constraints aiming at a single station.

Initially, part-to-part constraints (PPCs) and part-to-fixture constraints (PFCs) are applied for the multi-interaction of assembly, and multiple constraints graph (MCG) model is proposed for expressing PPCs, PFCs, parts, as well as the variation propagation relation among them. Then, locating points (LPs) are adopted for representing the deviations in constraints, and formulas for calculating the deviations of LPs are derived. On that basis, a linearized relation between LPs’ deviations and part’s locating deviations is derived. Finally, a wing box is presented to validate the proposed method, and the results indicate the methodology’s feasibility.

MCG is an effective tool for dimensional VPMA, which is shown as an example of this paper.

Functions of geometric constraints in dimensional variation propagation are revealed, and MCG is proposed to formulize dimensional variation propagation.

The purpose of this research is to develop a Social Information System research model that uses the core constructs intrinsic motivation, extrinsic motivation, and amotivation to explain social networking adoption among tweens, teens and young adults.

In developing the research model, we triangulated theories to examine the different orientations of motivation. The data collection process included a stratified sample size of 270 respondents. Following data collection we analyzed the results using structural equation modeling in the Partial Least Square software package.

The constructs amotivation, intrinsic and extrinsic motivations were all statistically significant in explaining continuance intention to use social networking services (SNS).

Researchers and practitioners have intimated that although there has been a rise in the number of persons accessing and becoming members of SNS, several subscribers who join subsequently leave after a minimal period. The practical implication of this study lies in providing a preliminary understanding of what determines or inhibits continuance intention of SNS membership.

Despite efforts, research in IS and technology acceptance literature regarding SNS diffusion is limited in scope. The theoretical implication of this study lies in the model that has been developed and validated to provide a more effective tool for the scholarly evaluation of SNS adoption. Existing adoption models are insufficient to explain voluntary technology usage of this nature.

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.