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The effect of board intellectual capital on non-profit organizational performance in non-western, less developed economies has been an important yet under-researched area. Given that the institutional and business relationships of a board account for the majority of board intellectual capital, the purpose of this paper is to fill the previously mentioned research gap by addressing how the interactions of the two relationships of board directors influence Chinese philanthropic foundation performance.

Following Creswell's (2014) explanatory sequential mixed-methodology, a qualitative study (Study 1) was first conducted to pre-test the assumptions, and then a quantitative study (Study 2) was carried out based on a secondary database of 1,405 Chinese philanthropic foundations to further examine the hypotheses. Several regression models were built for analyzing the results.

Study 1 confirmed that Chinese philanthropic foundations gained greater revenues and hosted more public welfare activities by leveraging the reinforcing or complementary effects of board directors' intellectual capital to improve organizational performance. Study 2 further examined the hypotheses that the interactions of intellectual capital increased the total revenue and public welfare expenditure of the foundations; however, significant positive relationships were only identified in foundations at the local level, and no significant associations were found in those at the national level.

The research indicates that the intellectual capital of board directors may influence the performance of their philanthropic foundations. Thus, Chinese philanthropic foundations should be more aware of the importance of this influence when determining which candidates will join the board.

The study makes significant contributions to the existing knowledge of the development of non-governmental organizations; it incorporates the resource dependence theory and agency theory into understanding how the intricate interactions between the institutional and business relationships of board directors affect foundation performance and how the jurisdiction affiliations act as a boundary condition for such relationships in a non-western setting such as China.

This purpose of this study was to develop a 3D printer based on powder particle. The best degreasing and sintering process of a blank body was investigated to obtain a metal product with high precision and high surface finish. This process will greatly reduce the difficulty and cost of forming a complex metal product with high application value.

Stainless steel powder and polymer materials were mixed using a rubber mixing machine. The powders were granulated to prepare a mixed material. A powder feed 3D printer was used at low temperature (about 200°C) to print and degrease the body. A series of sintering experiments were performed to study the different sintering temperatures, and the physical and mechanical properties of the sample sintered under various conditions were compared to determine the best degreasing and sintering process.

The reaction at 1,370°C was the optimal route for the metal billet degreasing. The resulting metal products had fine structure and stable performance compared with the products with traditional powder metallurgy composition.

Most 3D printed metal powder materials rely on imports, which are expensive and increase the manufacturing cost. These drawbacks limit the application and development of metal 3D printing technology to a certain extent. The successful study of this molding method greatly reduces the difficulty and cost of forming complex metal products with high application value. This report will provide valuable guidance for sintering process and forming methods.

This study aims to analyze the relationship between the nonpathological traits of narcissism and decisions under conditions of uncertainty and risk in light of the prospect (PT) and fuzzy-trace theories (FTT).

This paper conducted an empirical-theoretical study with 210 Brazilian academics from the business area (accountants and managers), using a self-reported questionnaire to collect data. This paper analyzed the data through descriptive statistical techniques, correlation, test of hypotheses and logistic regression.

The results point to a lower disposition of respondents to narcissistic traits, although the characteristics of self-sufficiency, authority, exploitation and superiority have been demonstrated. Most participants chose the sure gain in positive scenarios and risk in light of possibility of losses. However, those with high levels of narcissism showed higher propensity to make risky decisions, both in positive and negative scenarios.

The empirical results about risky decision-making behavior of individuals with narcissist traits spur further investigation on the impacts of attitudes and behaviors in organizations as they are affected by psychosocial factors. These attitudes and behaviors, reflected in administrative and financial reports, influence future decisions of investors.

The interaction between the areas of business administration and psychology in regard to the effects of the narcissist personality trait and the FTT is both original and valuable for the business area. The simplest scenario based on the FTT theory can help eliminate issues around the interpretation and complexities of calculations regarding decision-making scenarios in PT format.

The purpose of this study is to extend a sensitivity-based reliability technique for the processors deployed in industrial drive (ID).

The processor provides flexible operation, re-configurability, and adaptable compatibility in industrial motor drive system. A sensitivity-based model allows a robust tool for validating the system design. Sensitivity is the probability of a partial failure rate for a distributed variable; sensitivity and failure rates are also complementary. Conversely, traditional power electronic components reliability estimating standards have overlooked it, and it is essential to update them to account for the sensitivity parameter. A new sensitivity-based reliability prediction methodology for a typical 32-bit microprocessor operating at 30ºC deployed in ID is presented to fill this gap. The proposed techniques are compared with the estimated processor reliability values obtained from various reliability standards using the validated advanced logistics development tool. The main contribution of this work is to provide a sensitivity extended reliability method over the conventional method directing toward improving reliability, availability, and maintainability in the design of ID.

The analysis shows that the sensitivity of the processor’s circuit increases due to increases in complexity of the system by reducing the overall mean time between failure upon comparing among conventional reliability standards.

The significance of this paper lies in the overall, sensitivity-based reliability technique for processors in comparison to the traditional reliability complexity in IDs.

With high-speed urbanization and strict requirements on energy conservation and environmental protection, eco-city has become the priority of urban development in China. Governments of all levels promote various eco-city planning schemes within a short term, but most schemes are characterized by randomness and subjectivity. To solve the lack of scientific pre-implementation evaluation for eco-city planning and improve eco-city construction quality, a systematic analysis is conducted in this study from three dimensions, namely, eco-city planning scheme, operating mechanism, and guarantee measures. A 3D evaluation model for eco-city planning is constructed through index selection. Schemes are ranked comprehensively with the distance measure method, and projection analysis is performed with the four-grid evaluation screen. Finally, the 3D evaluation model is applied to evaluate eco-city planning for Shenzhen, Chongqing, and Weifang. Results show that the model can be used to evaluate eco-city planning schemes effectively and comprehensively and offers targeted optimization suggestions in accordance with the evaluation results. Construction of the 3D evaluation model of eco-city planning based on the distance measure to determine the reasonability of eco-city planning reduces the institutional and social costs of eco-city planning practices.

This paper aims to examine the factors affecting the implementation of affordable housing policies in two Chinese municipal governments. Since 2010, the Chinese government has enforced an ambitious plan to adopt affordable housing provisions accompanying a series of urbanization programs. Furthermore, the policy implementation at the local level has led to various outcomes but has been scarcely investigated. The views of policy implementation from local officials are crucial in the context of intergovernmental relations. Therefore, it is important to examine the views of local public officials on the development status and challenges in the context of Chinese intergovernmental relations.

This paper verifies which factors exert significant impacts on the willingness of local officials to adapt affordable housing policies by using the logistic regression model and marginal effect estimation. With original data from the fieldwork surveys of city administrators, the measures incorporated local characteristics as well as the intergovernmental support from the central government in two selected megacities, Guangzhou and Shenzhen.

There are significant differences in local investment between the selected cities. Intergovernmental support from the central government, city development strategies, implementation perceptions of local governments and land supply, all significantly impact the selection of an affordable housing program and its overall implementation.

To the best of the authors’ understanding, this study would be one of the first to empirically explore the view of municipal public officials on affordable housing policy in China. This paper provides an empirical analysis from municipal public officials on the local implementation of affordable housing policies in China. As the outcome of housing policies actually depends on the implementation willingness of public officials and the overall performance of local governments, this explorative study would benefit the future development of China’s affordable housing policy.

The purpose of this paper is to draw conclusions about China's agricultural integration (CAI) by looking back its processes stage by stage, discussing the problems related to CAI, in order to learn salutary lessons for the future of agricultural development, for the increase in rural income, and especially for the promotion of CAI.

The paper comprises three stages: analyzing the process of CAI from the household responsibility system, to agricultural industrialization, until the stage of CAI led by farmers' co‐operatives; discussing the related practice together with literature; and historically proving that there is no better way to promote CAI than letting it be led by farmers' co‐operatives.

The paper finds that, the development of China's agricultural economic organizations is owing to CAI, and can be studied stage by stage; the process of CAI proves that it needs to be promoted as a new style led by farmers' co‐operative in order to increase rural income; literature review also gives eloquent proof of the above viewpoint; agricultural integration led by farmers' co‐operative should be taken as a better way to upgrade CAI and to increase rural income, for it can decrease the benefit disputes that usually happened in the former type of agricultural industrialization.

The obvious value of the paper is to show, by a historical review, a way to promote CAI and to increase farmers' income. A literature review finds these countermeasures comprehensively, historically, and theoretically. The information about CAI will be beneficial for people who are interested in the topic.

Study conditions of empirical publications on time series modeling and forecasting of electricity prices vary widely, making it difficult to generalize results. The key purpose of the present study is to offer a comparison of different model types and modeling conditions regarding their forecasting performance.

The authors analyze the forecasting performance of AR (autoregressive), MA (moving average), ARMA (autoregressive moving average) and GARCH (generalized autoregressive moving average) models with and without the explanatory variables, that is, power consumption and power generation from wind and solar. Additionally, the authors vary the detailed model specifications (choice of lag-terms) and transformations (using differenced time series or log-prices) of data and, thereby, obtain individual results from various perspectives. All analyses are conducted on rolling calibrating and testing time horizons between 2010 and 2014 on the German/Austrian electricity spot market.

The main result is that the best forecasts are generated by ARMAX models after spike preprocessing and differencing the data.

The present study extends the existing literature on electricity price forecasting by conducting a comprehensive analysis of the forecasting performance of different time series models under varying market conditions. The results of this study, in general, support the decision-making of electricity spot price modelers or forecasting tools regarding the choice of data transformation, segmentation and the specific model selection.

Empirical publications on the time series modeling and forecasting of electricity prices vary widely regarding the conditions, and the findings make it difficult to generalize results. Against this background, it is surprising that there is a lack of statistics-based literature reviews on the forecasting performance when comparing different models. The purpose of the present study is to fill this gap.

The authors conduct a comprehensive literature analysis from 2000 to 2015, covering 86 empirical studies on the time series modeling and forecasting of electricity spot prices. Various statistics are presented to characterize the empirical literature on electricity spot price modeling, and the forecasting performance of several model types and modifications is analyzed. The key issue of this study is to offer a comparison between different model types and modeling conditions regarding their forecasting performance, which is referred to as a quasi-meta-analysis, i.e. the analysis of analyses to achieve more general findings independent of the circumstances of single studies.

The authors find evidence that generalized autoregressive conditional heteroscedasticity models outperform their autoregressive–moving-average counterparts and that the consideration of explanatory variables improves forecasts.

To the best knowledge of the authors, this paper is the first to apply the methodology of meta-analyses in a literature review of the empirical forecasting literature on electricity spot markets.