Computing of the contribution rate of scientific and technological progress to economic growth in Chinese regions

According to the new economic growth theory, a new method of computing the contribution rate of scientific and technological (S&T) progress to economic growth based on the Cobb–Douglas production function and the Solow residual value method is proposed in this paper. This method includes three steps: Firstly, according to their levels of S&T progress, fuzzy soft clustering of thirty one Chinese regions is performed to obtain the membership degree of these places to the categories. Secondly, to calculate the contribution rates that different categories of levels of S&T progress contribute to economic growth. Thirdly, to multiply the obtained contribution rate of each category by the membership degree of the place belonging to this category, from which the contribution rate of S&T progress to economic growth in each place is obtained. Finally, this method is used to calculate the contribution rates of S&T progress to economic growth in thirty one Chinese regions during the period from 1998 to 2007. Last but not least, some reasonable suggestions and conclusions are proposed by analyzing the computing results.     

Comparative study on economic contribution rate of education of China and foreign countries based on soft computing method

Economic contribution rate of education (ECRE) is the key factor of education economics. This article selected China, South Korea, United States and other countries for a total of 15 samples, and put the data of the same period under the framework of soft computing, to simulate the production chain of “education–potential human capital–actual human capital–economic growth”. The basic idea is: Firstly, 15 countries are softly categorized according to the level of science and technology (S&T) progress. Secondly, potential human capital and actual human capital establish the internal correlation (fuzzy mapping) in the same classification, and we conceptualize actual human capital as one production factor, joined with the other two production factors, fixed asset and land, to set up the fuzzy mapping to economic growth., and then calculate economic contribution rate of education of China and foreign by two fuzzy mapping of them. Thirdly, this paper analyzes the present state and differences in the development of education between China and foreign according to different ECRE, and offers proposals for promoting the education in China.     

How Should the Chinese Government Invest R&D Funds: Enterprises or Institutions?

With the rapid increase of the government R&D investment in China, the efficient optimization of the R&D investment areas of the Chinese government significantly influences regional innovation productivity and economic growth in the long run. By expanding the R&D-based growth model and using empirical analysis, this paper discusses the optimal combination for the government to coordinate its R&D expenditure as productive public investment in various sectors, under the condition of promoting long-term economic growth, is discussed by considering the aspects of capability for independent innovation, the development capability for basic knowledge, and the absorption capability for the technique. Results are as follows. (1) The level of production efficiency of enterprises, such as the capability for independent innovation, the development capability for basic knowledge, and absorption capability, influences the inclination of the government to invest in enterprises and institutions. When an enterprise has a high production efficiency level, technological level A, and knowledge storage B, increased investment from institutions to the enterprise can significantly promote regional economy growth. Otherwise, the government should increase R&D investment in institutions. (2) The government R&D investment in institutions can indirectly promote economic growth through the promotion of human capital and the understanding and absorption capacity of external knowledge, independent innovation capability, and basic knowledge development capability of enterprises. This paper may help the government to create appropriate policies with higher efficiency in R&D investment, and promote technical progress and economic growth in China.     

AI and Global Science and Technology Assessment

Strength in science & technology (S&T) is the foundation of a nation's economic power, so an effective, automated means of continually assessing this strength is critical to understanding a country's economic status. Six essays on global S&T assessment present various research frameworks, computational methods, issues, and results relative to knowledge mapping, scientometrics, information visualization, digital libraries, and multilingual knowledge management.     

中国经济增长要素分析：1978～2012

改革开放三十年来,物质资本要素是中国经济主要的增长动力,并且重要性逐渐上升;人力资本增长动力在1982年左右达到峰值,此后不断下降;劳动力增长动力在1988年达到峰值,此后也不断下降;全要素生产率呈倒“w”型增长轨迹,三次TFP的快速增长都与中国几次重要的经济制度变迁有着重要联系。在1978年～2012年间,经济体制改革、对外开放、基础设施建设、研发对TFP的解释存在变动,不同时期对TFP的解释力度不同。本文预测2013年～2020年,物质资本、人力资本、TFP增长动力将有所下降,经济潜在增长率将会下降到6％～8％之间。在未来十年,中国潜在经济增长速度将会下滑。     

Knowledge-city index construction: An intellectual capital perspective

Knowledge cities are the most capable of producing sustainable economic growth. Cities, where relationships between people are more extensive, provide the most natural environment in which to look for evidence of the knowledge spillovers so emphasized by the endogenous growth theory. The intellectual capital approach considers the ability to transform knowledge and intangible resources into sustainable long-term wealth. The approach does not only contemplate sustainability and social wellbeing, but also intangible factors such as human development, economic structure, trade, image and innovation. This paper proposes a novel methodology to measure intangible capital as the growth capacity of knowledge cities based on intellectual capital using a composite index of seven intangible factors, disaggregated into 19 dimensions with 73 different indicators. Using this methodology, we rank 158 European cities for which information is available. The results show clear differences between northern and southern European cities. The top positions in the ranking are occupied by cities with a favorable balance in human capital; the most important growth factors in the most developed cities being research, development and innovation and image components, whilst these together with the human components are the most important growth factors in the poorest cities.     

Evaluating the criteria for human resource for science and technology (HRST) based on an integrated fuzzy AHP and fuzzy DEMATEL approach

This study intends to use a combination of fuzzy Analytic Hierarchy Process (AHP) and fuzzy Decision-making Trial and Evaluation Laboratory (DEMATEL) method in human resource for science and technology (HRST). Specifically, this study first uses AHP to evaluate the weighting for each criterion and then use DEMATEL method to establish contextual relationships among those criteria. We find out Infrastructure might be more critical since it is a cause and will directly influence human resource for science and technology performance. For human resource for science and technology (HRST), improving Infrastructure might be a better choice for the long period of time. Moreover, Education, R&D Expenses and Immediate output are more important second-tier criteria than Value, Cooperation, Labor Market, Human Capital and Intermediate output. Therefore, the improvement should be started with Infrastructure, particularly on identification of the Education, R&D Expenses and Immediate output.     

Fuzzy R&D portfolio selection of interdependent projects

Global competition of markets has forced firms to invest in targeted R&D projects so that resources can be focused on successful outcomes. A number of options are encountered to select the most appropriate projects in an R&D project portfolio selection problem. The selection is complicated by many factors, such as uncertainty, interdependences between projects, risk and long lead time, that are difficult to measure. Our main concern is how to deal with the uncertainty and interdependences in project portfolio selection when evaluating or estimating future cash flows. This paper presents a fuzzy multi-objective programming approach to facilitate decision making in the selection of R&D projects. Here, we present a fuzzy tri-objective R&D portfolio selection problem which maximizes the outcome and minimizes the cost and risk involved in the problem under the constraints on resources, budget, interdependences, outcome, projects occurring only once, and discuss how our methodology can be used to make decision support tools for optimal R&D project selection in a corporate environment. A case study is provided to illustrate the proposed method where the solution is done by genetic algorithm (GA) as well as by multiple objective genetic algorithm (MOGA).     

An Optimal Balanced Economic Growth and Abatement Pathway for China Under the Carbon Emissions Budget

Arguments over equity during abatement goal setting is the principal obstacle to climate mitigation cooperation, while allocating global emissions to each country as deduced from the climate objective according to certain equitable principles offers an effective alternative to ending this dispute. Such an alternative also endows each country with the freedom to determine and develop its own pathway under its emissions budget while ensuring that global climate targets are met. Within this context, this paper integrated economic growth theory with the optimal control model and simulated the optimal abatement pathway as well as the economic growth trajectory for China within the allocated emissions budget. The study found that research and development (R&D) investment is an effective way of improving energy efficiency. Our simulation showed that the R&D intensity of the gross domestic product (GDP) would see a slight decline for the inceptive period, followed by an aggressive rise to a relatively high level before decreasing again. Under the 450 ppm carbon concentration target, the R&D investment intensity would have to increase significantly beginning from 2014 because of the more stringent demands as compared to other less rigorous targets such as 500 ppm. The economy would continue to grow, although growth would occur less rapidly under rigorous targets: relative to 2007 levels, the GDP would grow by 11-fold and 15-fold under the 450 and 500 ppm scenarios, respectively. Before enforcement of an effective R&D investment, the carbon emissions would increase rapidly, while after enforcement, the speed of carbon emissions would slow down.     

IT assets, organization capital and market power: Contributions to business value

How much IT capital contributes to the economic value of firms is a relevant but complex issue, since the contribution may come from different sources that are difficult to separate. In this paper, we model the determinants of the economic value of multi-asset firms with market power when the adjustment costs of investing in IT capital turn into organization capital, increasing the future cash flow of the firm. The resulting valuation equation, new in the literature, has four simultaneous sources of economic value: (i) purchase costs of the assets, (ii) adjustment costs, (iii) organization capital, and (iv) rents from market power. The model is tested with a unique data base from Spanish banks in a time period when these banks invested heavily in IT capital. We find that 54% of the economic value of the representative bank corresponds to the purchase cost of material and immaterial assets, including IT capital. The remaining 46% corresponds to the contributions of: adjustment costs (17%), organization capital (7%) and rents from market power (22%).     

Social Capital,Resilience and Accessibility in Urban Systems: a Study on Sweden

Spatial systems appear to exhibit often a complex pattern of socio-economic development, in terms of (un)employment, income, mobility, ethnic composition, and urbanisation rates. Their evolution is co-determined by such factors as: market proximity, labour and housing market developments, public amenities, use of and access to transport systems, socio-economic composition of the population, etc. In addition, a sine qua non for sustaining urban economic growth is the local or regional presence of individual and collective cognitive assets that favour knowledge acquisition and transfer, education, innovation, and creativity. In this context, social capital and spatial accessibility are critical factors. The present paper aims to provide an operational framework for mapping out and understanding the mechanisms which drive spatial systems from the perspective of the resilience of urban areas, in the light of their social capital in combination with accessibility. Particular attention is therefore given to the essential role of social capital and transport accessibility in shaping both the economic development of cities and the spatial pattern in the evolution of cities, in terms of, inter alia, education, age, ethnic composition, (un)employment, and socio-economic poverty. For our quantitative analysis of the Swedish urban system, a quantile regression model is introduced and applied in order to study which urban-economic factors in Sweden determine the different levels of social capital, which are seen here as the fundamental component of the resilience capacity of urban areas.     

The role of R&D and corporate governance in Korea: IT firms versus non-IT firms

Recent economic development in Korea was mostly driven by companies in the IT sector. Also, it is widely argued that R&D investment has a positive impact on firm value, especially for IT firms. In this paper, we analyze how R&D investment has contributed to the growth of Korea’s economy by examining the effect of R&D investment on firms’ market value, measured as Tobin’s Q, and investigate whether this effect is different between firms in the IT sector and firms in the non-IT sector. We also account for the effect of another major change experienced by Korean firms: changes in corporate governance structure. We find that for firms in the IT industry, higher R&D investment coupled with high foreign ownership results in higher firm valuation.     

An intelligent adaptive system for the optimal variable selections of R&D and quality supply chains

The cost of research & development (R&D) and quality management are always regarded as two major parts of total cost. The variable performance of R&D and quality design is an important index that will reflect the effectiveness of the cost reduction. This research has attempted to simultaneously vary all of the variables to achieve the global optimum for the optimal variable selections of R&D and quality design. Genetic algorithm (GA) can treat all of the variables for the global search. In this study, fuzzy refinement with orthogonal arrays was effective in improving the performance of the GA, and also showed the benefits of a good chromosome structure on the behavior of GA. It is also proposed the postponement design with temporal concept, to select the effective variables for the cost reduction of R&D and quality management design. The experimental results showed that tempo-postponement design will increase the flexibility and quick response for supply chain management. Hence, this approach can act as a useful guideline for researchers working on the optimization of the key variable selections for R&D and quality model design.     

广东省水稻生物质能的估算

利用MODIS传感器的MOD17A3数据,通过处理获取了广东省的NPP(植被净初级生产力)分布图;同时,根据Landsat获取的广东省土地利用类型图,提取出广东省水稻的空间分布图。将两者叠加并进行相关运算和分析,得到全省水稻生物量的分布图及其统计数据。同时,进行野外测量并参考已有的研究成果,取稻草和稻秆产量与水稻产量的重量比为0.623,获得水稻总的农作物残余。除去还田、造纸及用做牲畜饲料的那部分,仍有三成左右的可用生物量。研究表明:珠江三角洲经济发展迅猛的城市,水稻生物质能的占有量较少;而在一些边远山区,水稻生物质能占的比重明显偏大。本文通过定量化的研究,为以后广东省水稻生物质能的开发提供了有价值的参考信息。     

Robust Monte Carlo Method for R&D Real Options Valuation

This paper is devoted to developing a robust numerical analysis of least squares Monte Carlo (LSM) in valuing R&D investment opportunities. As it is well known, R&D projects are characterized by sequential investments and therefore they can be considered as compound options involving a set of interacting American-type options. The basic Monte Carlo simulation takes a long time and it is computationally intensive and inefficient. In this context, LSM method is a powerful and flexible tool for capital budgeting decisions and for valuing R&D investments. In particular way, numerical tests are performed to examine the optimal choice of basis function and polynomial degree in terms of reduction of the execution time, accuracy and improvement in the simulation.     

Developing an research and development (R&D) process improvement system to simulate the performance of R&D activities

Because of a shorter R&D cycle time and the increasing complexity of technology development, efficient decision support systems for R&D activities are necessary to facilitate R&D processes. In particular, small and medium enterprises (SMEs) require efficiency of R&D projects due to a lack of R&D budgets and resources. Therefore, this paper aims to develop a system which can assess current levels of R&D processes of companies and improve problematic processes. To this end, the proposed system applies a standard R&D process to evaluate the R&D level of companies, including four types of database and three modules: performance level analysis, comparison analysis, and performance simulation analysis. First, the module of performance level analysis aims to draw strong and weak R&D processes of companies, using three factors: importance, performance goal and current performance on each process. The second module provides the function of comparison analysis that compares the performance level of a company with that of others. Finally, the performance simulation analysis investigates influences of critical processes on R&D outcomes and predicts how much the processes can enhance technical, economic and process outcomes. In particular, a case study is presented to illustrate the application of the proposed system to an IT company. This system can help managers enhance their R&D performance by presenting necessary improvements on critical processes.     

White knight in dark days? Supply chain finance firms,blockchain, and the COVID-19 pandemic

We investigate the impact of the announcement of the COVID-19 pandemic on the market value and trading volume of supply chain finance (SCF) firms. Using an event study, we observe a significant valuation loss and higher trading volume of SCF firms. However, blockchain-enabled SCF firms are protected from such valuation loss and volatility in trading. We find that higher research and development (R&D) and capital expenditures by firms prevent the loss. Moreover, the firm value of blockchain-enabled SCF firms is impacted by their membership in a blockchain consortium and progress in blockchain implementation. Investors’ confidence in blockchain reduces the market uncertainty.     

铁路物流节点规划模糊聚类分析

现代物流作为先进的组织方式和管理技术,已经成为经济发展重要的推动力量。针对目前缺乏对铁路物流节点综合发展规划研究的现状,文中运用模糊聚类分析方法进行研究。首先,建立影响因素指标体系,并通过递阶层次分析结构模型表现出来;然后,按模糊聚类分析的步骤建立数学模型,包括一级指标评价、无量纲化处理、建立模糊关系、模糊聚类等;最后,通过规划实例来说明指标体系和数学模型的具体应用。文中的研究内容,对于科学规划分层分类的铁路物流节点,实现不同运输方式物流节点之间的合理分工与协调布局具有重要意义。     

Using Boosting for Financial Analysis and Performance Prediction: Application to S&;P 500 Companies,Latin American ADRs and Banks

This paper demonstrates how the boosting approach can support the financial analysis functions in two ways: (1) As a predictive tool to forecast corporate performance, and rank accounting and corporate variables according to their impact on performance, and (2) As an interpretative tool to generate alternating decision trees that capture the non-linear relationship among accounting and corporate governance variables that determine performance. We compare our results using Adaboost with logistic regression, bagging, and random forests. We conduct 10-fold cross-validation experiments on one sample each of S&P 500 companies, American Depository Receipts (ADRs) of Latin American companies and Latin American banks. Adaboost results indicate that large companies perform better than small companies, especially when these companies have a limited long-term assets to sales ratio. Performance improves for large LAADR companies when the country of residence is characterized by a weak rule of law. In the case of S&P 500 companies, performance increases when the compensation for top officers is mostly variable.     

SLIGA Based underwater weapon safety and arming system

 The Naval Surface Warfare Center, Indian Head Division (NSWCIHD) is applying microelectromechanical system (MEMS) technology to underwater weapon Safety and Arming (S&A) system development. MEMS technology provides an opportunity to develop a miniaturized S&A system that is more sophisticated with improved safety and reliability at a lower cost compared to current systems. An S&A system prevents premature initiation of the weapon while reliably ensuring initiation at the appropriate time. An S&A system uses multiple sensors and devices. In comparison with other weapon S&A systems, a critical aspect of underwater weapon S&A systems is the mechanical interlock system utilizing actuators and mechanical sensors. This paper describes the design, development and fabrication of S&A SLIGA device prototypes and of a SLIGA based S&A system. NSWCIHD worked with members of the HI-MEMS Alliance during design, development and fabrication. Advancements achieved by the HI-MEMS Alliance and SLIGA S&A design issues are discussed. Received: 25 August 1997/Accepted: 10 September 1997