中国非公有制经济发展的新机遇

《国务院关于鼓励支持和引导个体私营等非公有制经济发展的若干意见》发布后,万众瞩目。该意见共分放宽非公有制经济市场准入、加大对非公有制经济的财税金融支持、完善对非公有制经济的社会服务、维护非公有制企业和职工的合法权益、引导非公有制企业提高自身素质、改进政府对非公有制企业的监管、加强对发展非公有制经济的指导和政策协调等7个部分,计36条,从政策层面详细阐述了促进非公有制经济发展的意义和举措。积极发展“非公”经济,事关社会主义现代化建设全局与中华民族的全面复兴。国务院《意见》的出台,无论在理论和实践层面都给我们带来了新的课题甚至争论。为此,本刊特组织众多理论家、企业家和政府官员一道,对“36条”具体内容进行详细解读,对我国非公经济的发展建言献策。     

“新国九条”并非“速效救市丸”

五月中旬，国务院发布《关于进一步促进资本市场健康发展的若干意见》，业界人士称之为“新国九条”。诸多专家站台解读，一言以蔽之日，“新国九条”“为资本市场的发展再度明确了方向”，许多股民的脸上也露出长久难见的笑容，“给点阳光就灿烂”。     

政策

首届全国制造业与物流业联动发展大会在上海召开 由国家发展和改革委员会主办的首届全国制造业与物流业联动发展大会于9月24日在上海召开。 国家发展和改革委员会副主任、全国现代物流工作部际联席会议召集人欧新黔出席会议并讲话。她在讲话中传达了曾培炎副总理在9月21日国务院召开的全国服务业工作会议上的讲话精神及大会做出的各项工作部署，并强调，促进物流业发展是党中央、国务院提出的转变经济增长方式、     

吴敬琏柳传志为落实“非公经济36条”把脉

在具有划时代意义的“非公经济36条”问世5周年之际，日前国务院召开常务会议研究部署进一步落实鼓励和引导民间投资健康发展的政策措施。实事求是地说，5年来“非公36条”落实得并不理想。经济学家吴敬琏坦言，“此次提出的政策并没有太新的内容。”“我们应该全面地检查一下，对于人代会上提出的政策，我们落实的情况如何，不能总在原地打转转。”“政策落实得不理想，归根到底是体制的阻碍。     

网游整顿劈出第四斧

新闻出版总署音像电子和网络出版管理司副司长寇晓伟6月3日表示．“国务院将于近期专门下达文件规范网络游戏的管理，网络游戏目前多头管理的局面将结束。”但他并没有做过多的透露该文件的细节内容．他让大家“等着看吧”。在回答新闻出版署对网游出版管理的政策是否会改变时．他明确表示新闻出版署既定的政策不会改变。     

深化改革，中关村再鼓科技创新风帆

2011，一开年，我们又听到了中关村国家自主创新示范区的前进脚步声。国务院原则同意中关村“1＋6”的鼓励科技创新和产业化的系列先行先试改革政策，这些政策将于今年年初正式实施。     

破解不前房控迷局——王珏林：将房地产调控进行到底——当前房地产形势研讨会侧记

自“国十条”出台以来，楼市成交量不断下探，而7、8月却连续两个月上涨。尤其是北京、上海、广州、深圳等城市价量齐升，让观望买房的人坐卧不安。网络媒体上多方观点、多种声音交织在一起，让人们对房地产的发展走向越发迷茫。国家住房和城乡建设部政策研究中心副主任王珏林就积极响应国务院和北京市政府近期出台的房地产宏观调控政策，促进房地产及相关行业的健康发展阐述自己的观点。     

海淀创新之帆乘势启航——海淀全力推进国家自主创新示范区核心区建设

海淀园将按照国务院批复精神，贯彻落实科学发展观。充分发挥核心区创新资源优势，带动中关村国家自主创新示范区整体发展。     

海淀区重点项目引进扶持办法

第一章总则第一条为深入学习实践科学发展观，落实国务院《关于同意支持中关村科技园区建设国家自主创新示范区的批复》（国函[2009]28号），贯彻执行市政府《关于同意加快建设中关村国家自主创新示范区核心区的批复》（京政函[2009]24号），根据区委、区政府《关于进一步促进高新技术产业发展的决定》（京海发[2009]10号），     

海淀区促进高新技术产业发展专项资金管理办法

第一章总则第一条为深入学习实践科学发展观，落实国务院《关于同意支持中关村科技园区建设国家自主创新示范区的批复》（国函[2009]28号），贯彻执行市政府《关于同意加快建设中关村国家自主创新示范区核心区的批复》（京政函[2009]24号），根据区委、区政府《关于进一步促进高新技术产业发展的决定》（京海发[2009]10号），     

Contributions of Econometrics to Public Policy Analysis in the Information Age

In this paper we model U.S. economic growth over the next 25 years. Despite the anticipated aging of the population, moderate population growth will provide growing supplies of labor well into the 21st century. Improvements in labor quality due to education and experience will also continue for some time, but will eventually disappear. Productivity growth for the U.S. economy will be below long-term historical averages, but labor-using technical change will be a stimulus for growth of labor demand. Year-to-year changes in economic activity will be primarily the consequence of capital accumulation. However, the driving forces of economic growth over the long term will be demography and technology. This is a revised version of the keynote speech that I delivered on 16 January 2009 at the 6th International Conference of Socionetwork Strategies, at Kansai University, Japan.     

Impact of Online Customer Reviews on Sales Outcomes: An Empirical Study Based on Prospect Theory

This study examines the influence of the valence of online customer reviews on sales outcomes based on prospect theory. Numerous studies have revealed the importance of customer reviews in online marketing. However, only few studies have explored the impact of online customer reviews on sales outcomes in the dynamic process. Prior studies in behavioral economics literature have indicated that people differently value gains and losses and that losses have more emotional impact than an equivalent amount of gains. This study verifies whether prospect theory applies to the relation between online customer reviews and sales outcomes. Relevant data were collected from Amazon.co.jp, and three statistical models were employed to investigate the relation between the two factors. Major findings confirm that negative customer reviews considerably impact online sales than positive reviews. Furthermore, the findings indicate that the marginal effects of positive and negative reviews decrease with the increase in their volume. The results of this study will enable marketers to compare the relative sales effects of different types of customer reviews and improve the effectiveness of customer service management.     

Facebook e-Portfolios for Career Education Focused on Japanese Employment Practice: A Case Study

The authors propose the effectiveness of Facebook functions in the promotion of career education. In recent years, career education in Japanese universities has differed slightly from that in other countries. Japanese students are trained to be competitive in the job-hunting process; they need to obtain the technical skills and knowledge necessary to pass a company entrance examination or a university oral interview. This practice is in stark contrast with the intrinsic meaning of vocational/career education, which is the process by which students acquire the abilities and independence required by a certain industry. This meaning is manifested in the purpose of the career education program of Hokkai-Gakuen University’s Faculty of Business Administration. The program’s purpose is to foster independence in its students rather than the acquisition of skills for the job-hunting process. The professional independence of every student is important to their career development after graduating from the university. On the other hand, it is known that e-portfolios generally encourage students to record and assess their activities. To promote the activities that students tackle in the program, we introduced an e-portfolio using Facebook. This study shows the characteristics and achievements of our e-portfolio.     

Prediction Model for Bollywood Movie Success: A Comparative Analysis of Performance of Supervised Machine Learning Algorithms

The main purpose of this paper is to do a comparative analysis of prediction models using various machine learning techniques. The models will be used to predict whether a movie will be a hit or flop before it is actually released. The techniques used for comparisons are decision tree, random forest (RF), support vector machine, logistics regression, adaptive tree boosting, and artificial neural network algorithms. The major predictors used in the models are the ratings of the lead actor, IMDb ranking of a movie, music rank of the movie, and total number of screens planned for the release of a movie. The results of most models indicated a reasonable accuracy, ranging from 80 to 90%. However, models based on two techniques, RF and logistic regression, achieved an accuracy of 92%. From the results, the most important predictors of a movie’s success are music rating, followed by its IMDb rating and total screens used for release.

     

Graph-Based Entropy for Detecting Explanatory Signs of Changes in Market

Graph-based entropy, an index of the diversity of events in their distribution to parts of a co-occurrence graph, is proposed for detecting signs of structural changes in the data that are informative in explaining latent dynamics of consumers’ behavior. For obtaining graph-based entropy, connected sub-graphs are first obtained from the graph of co-occurrences of items in the data. Then, the distribution of items occurring in events in the data to these sub-graphs is reflected on the value of graph-based entropy. For the data on the position of sale, a change in this value is regarded as a sign of the appearance, the separation, the disappearance, or the uniting of consumers’ interests. These phenomena are regarded as the signs of dynamic changes in consumers’ behavior that may be the effects of external events and information. Experiments show that graph-based entropy outperforms baseline methods that can be used for change detection, in explaining substantial changes and their signs in consumers’ preference of items in supermarket stores.     

BLOCKS: Efficient and Stable Online Visualization of Dynamic Network Evolution

It is computationally and cognitively expensive to observe the evolution of community structure on dynamic networks in real-time, not only because the data sets tend to be complex, but also because the visual interfaces are often complicated. We introduce BLOCKS, a simple but efficient framework to abstract and visualize the evolution of community structure on dynamic networks. Instead of indicating detailed changes of nodes and links temporally, BLOCKS regards communities as visual entities and focuses on representing their behaviors and relation changes on a time series. Experiments detected a stable performance of BLOCKS compared with previous methods while detecting the community structure of networks. We also present a case study that shows an effective learning process of network evolution with BLOCKS.     

An Approach to Security for Unstructured Big Data

Security of Big Data is a huge concern. In a broad sense, Big Data contains two types of data: structured and unstructured. Providing security to unstructured data is more difficult than providing security to structured data. In this paper, we have developed an approach to provide adequate security to unstructured data by considering types of data and their sensitivity levels. We have reviewed the different analytics methods of Big Data to build nodes of different types of data. Each type of data has been classified to provide adequate security and enhance the overhead of the security system. To provide security to a data node, and a security suite has been designed by incorporating different security algorithms. Those security algorithms collectively form a security suite which has been interfaced with the data node. Information on data sensitivity has been collected through a survey. We have shown through several experiments on multiple computer systems with varied configurations that data classification with respect to sensitivity levels enhances the performance of the system. The experimental results show how and in what amount the designed security suite reduces overhead and increases security simultaneously.     

The Future of Socionetwork Strategies

In the first stage of creating technological improvements for a democratic society, the leaders of the Society of Socionetwork Strategies have conducted statistical research on the effect of information and communication technology on the global economy. In the second stage, younger professors, based on their Positive Studies, have leapt into a multi-agent simulation of Grid Computing. In the third stage, a terra-bite scale of social data-collecting and the mining of large-scale data in our real world will be next. The next generation of scientists will share knowledge and intellectual inquiry in the fields of statistics, mathematics, and the social sciences with the help of computers connecting such scholars from all over the world.     

Simulation Analysis of a Dynamic Reallocation-based Routing Functionality for SAGE Application

A large amount of scientific data is generated through computation and analysis. Also, today’s scientific research necessitates an aggregation of diverse expertise from experts with different backgrounds. Therefore, visualizing and sharing these data among scientists in an intuitive and easy manner is of more importance in scientific collaborative research than ever. We have focused on SAGE, a middleware that realizes a large-scale remote visualization leveraging network streaming technique as a promising building block technology. However, no advanced network control function for efficient use of the network is equipped with SAGE although SAGE relies on a network streaming techniques. Our previous research integrated a functionality that detected network failures avoided such failure by rerouting network flows of SAGE into the functionality. Nonetheless, a network congestion avoidance functionality to adapt a collection of network flows generated by SAGE to the underlying network has not been developed yet. In this paper we explore the feasibility of a reallocation-based dynamic routing functionality for SAGE, with which all network flows on the network are rearranged. For feasibility research, we perform simulation experiments to observe the behavior of the functionality. The evaluation confirms that our proposed functionality works correctly and brings better throughput for each flow.     

The Effects of Proposals for Basic Pension Reform on the Income Distribution of the Elderly in Japan

The aging of the population in Japan is a serious problem, and the reform of the public pension scheme is a major political issue. Although the 2004 pension reform was enforced to ensure a sustainable pension system in such an aging society, people remain quite apprehensive about the pension system. Consequently, various sectors have created new proposals for pension reform to overcome these problems, and it has become a recent policy debate. The objective of this article is to prepare projections for the income distribution of households containing elderly people using the Japanese microsimulation model, INAHSIM (Integrated Analytical Model for Household Simulation), and to evaluate the effect of the proposals on the living standards of the elderly. According to the simulation results, the problem of very low pension amounts for the elderly does not appear to be growing. However, changes in co-resident families of the elderly, such as the increase in the number of people living alone, may cause a decline in their standard of living. The author points out the problems of the previously proposed reform plans and proposes an alternative reform plan based on the perspective used in this paper.