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The Ministry of Industry and Information Technology (MIIT) universities are important bases for science and technology research and play a critical role in China’s National Innovation System. Based on the Web of Science (WoS), this article analyzes the statistics of paper published by MIIT universities and universities from across China including MIIT universities. The results are as follows: (1) Both the MIIT universities and universities nationwide in China have increased their international academic publications, and MIIT have shown a greater increase for the past decade. (2) In terms of U-I-G interaction, for UG relations, the Tug value of MIIT universities has remained stable, while that of universities in China has become declined. For UI relations, the Tui value of both MIIT universities and universities in China has shown steady growth. For UIG relations, MIIT universities have a greater synergistic effect of Triple Helix relationship than universities in China. (3) For more details in seven MIIT universities, universities elected into “Project 985”, including HIT, BUAA, BIT and NPU, have published more papers, and been more synergistic with government and industry (UIG relations) than other three universities, including NUAA, NUST and HEU. Based on the empirical results, we discuss our findings, and make certain suggestions regarding policy incentives, reasonable administrative system and U-I-G interaction mode, which is significant not only for Chinese universities but also for universities in other developing countries. [ABSTRACT FROM AUTHOR]

This paper aims to optimize a desirable fare structure for the public transit service along a bus-subway corridor with the consideration of those factors related to equity in trip, including travel distance and comfort level. The travel distance factor is represented by the distance-based fare strategy, which is an existing differential strategy. The comfort level one is considered in the area-based fare strategy which is a new differential strategy defined in this paper. Both factors are referred to by the combined fare strategy which is composed of distance-based and area-based fare strategies. The flat fare strategy is applied to determine a reference level of social welfare and obtain the general passenger flow along transit lines, which is used to divide areas or zones along the corridor. This problem is formulated as a bi-level program, of which the upper level maximizes the social welfare and the lower level capturing traveler choice behavior is a variable-demand stochastic user equilibrium assignment model. A genetic algorithm is applied to solve the bi-level program while the method of successive averages is adopted to solve the lower-level model. A series of numerical experiments are carried out to illustrate the performance of the models and solution methods. Numerical results indicate that all three differential fare strategies play a better role in enhancing the social welfare than the flat fare strategy and that the fare structure under the combined fare strategy generates the highest social welfare and the largest resulting passenger demand, which implies that the more equity factors a differential fare strategy involves the more desirable fare structure the strategy has. [ABSTRACT FROM AUTHOR]

Although studies have increasingly linked air pollution to specific health outcomes, less well understood is how public perceptions of air quality respond to changing pollutant levels. The growing availability of air pollution measurements and the proliferation of social media provide an opportunity to gauge public discussion of air quality conditions. In this paper, we consider particulate matter (PM) measurements from four Chinese megacities (Beijing, Shanghai, Guangzhou, and Chengdu) together with 112 million posts on Weibo (a popular Chinese microblogging system) from corresponding days in 2011–2013 to identify terms whose frequency was most correlated with PM levels. These correlations are used to construct an Air Discussion Index (ADI) for estimating daily PM based on the content of Weibo posts. In Beijing, the Chinese city with the most PM as measured by U.S. Embassy monitor stations, we found a strong correlation (R = 0.88) between the ADI and measured PM. In other Chinese cities with lower pollution levels, the correlation was weaker. Nonetheless, our results show that social media may be a useful proxy measurement for pollution, particularly when traditional measurement stations are unavailable, censored or misreported. [ABSTRACT FROM AUTHOR]

The tradition of keeping written records of gift received during household ceremonies in many countries offers researchers an underutilized means of data collection for social network analysis. This paper first summarizes unique features of the gift record data that circumvent five prevailing sampling and measurement issues in the literature, and we discuss their advantages over existing studies at both the individual level and the dyadic link level using previous data sources. We then document our research project in rural China that implements a multiple wave census-type household survey and a long-term gift record collection. The pattern of gift-giving in major household social events and its recent escalation is analyzed. There are significantly positive correlations between gift network centrality and various forms of informal insurance. Finally, economic inequality and competitive marriage market are among the main demographic and socioeconomic determinants of the observed gift network structure. [ABSTRACT FROM AUTHOR]

Predicting and analyzing behaviors of investors is of great value to financial institutions. This paper uses survey data from about 9,000 individual investors across China to explore the predictability of decision behaviors by studying demographic characteristics that are relatively easy to obtain. After applying Pearson’s chi-squared test, Spearman rank correlation test, and several data mining methods, we verified that demographic characteristics are closely linked to decision behaviors, and it would be an economical and feasible solution for financial organizations to build initial behavioral prediction models especially when investors’ behavioral data are insufficient. [ABSTRACT FROM AUTHOR]

We investigate the interdisciplinarity of mathematics based on an analysis of projects sponsored by the NSFC (National Natural Science Foundation of China). The motivation of this study lies in obtaining an efficient method to quantify the research interdisciplinarities, revealing the research interdisciplinarity patterns of mathematics discipline, giving insights for mathematics scholars to improve their research, and providing empirical supports for policy making. Our data set includes 6147 NSFC-sponsored projects implemented by 3225 mathematics professors in 177 Chinese universities with established mathematics departments. We propose the weighted-mean DIRD (diversity of individual research disciplines) to quantify interdisciplinarity. In addition, we introduce the matrix computation method, discover several properties of such a matrix, and make the computation cost significantly lower than the bitwise computation method. Finally, we develop an automatic DIRD computing system. The results indicate that mathematics professors at top normal universities in China exhibit strong interdisciplinarity; mathematics professors are most likely to conduct interdisciplinary research involving information science (research department), computer science (research area), computer application technology (research field), and power system bifurcation and chaos (research direction). [ABSTRACT FROM AUTHOR]

In this study, university-industry collaborations in China and the USA are analyzed in terms of co-authored publications indexed in the Web of Science (WoS). Results show a wide gap between China and the USA: Chinese universities are much less active in collaborations with industry in terms of either publication productivity or collaboration intensity. In selecting local and foreign industrial partners, however, more variation exists among Chinese universities than among US universities. The US system is domestically oriented more than that of China. In the USA, the intensity of university-industry collaboration is determined by research quality, whereas in China this is not the case. In both China and the USA, distance is not critical for the establishment of domestic university-industry collaboration. A high correlation is found between productivity indicators including total publications and university-industry co-authored publications. However, the productivity indicators are less correlated with the intensity of university-industry collaboration. Large research universities with strong ties to domestic industry play critical roles in both national publication systems. [ABSTRACT FROM AUTHOR]

Tourist congestion at hot spots has been a major management concern for UNESCO World Heritage Sites and other iconic protected areas. A growing number of heritage sites employ technologies, such as cameras and electronic ticket-checking systems, to monitor user levels, but data collected by these monitoring technologies are often under-utilized. In this study, we illustrated how to integrate data from hot spots by camera-captured monitoring and entrance counts to manage use levels at a World Heritage Site in Southeastern China. 6,930 photos of a congestion hotspot (scenic outlook on a trail) were collected within the park at a 10-minute interval over 105 days from January to November 2017. The entrance counts were used to predict daily average and maximum use level at the hotspots. Results showed that the average use level at the congestion hotspot did not exceed the use limit mandated by the park administration agency. However, from 9:20 am to 12:00 pm, the use level at hotspots exceeded visitor preferred use level. Visitor use level was significantly higher at the hotspot during a major Chinese “Golden Week”. The daily entrance counts significantly predicted the average and maximum use level at the hotspot. Based on our findings, park managers can achieve the management goals by permitting the corresponding number of visitors passing the entrances. The gap manifested the complexities in visitor capacity management at high-use World Heritage Sites and other protected areas and calls for innovative monitoring and management strategies. [ABSTRACT FROM AUTHOR]

As part of the cultural landscape, administrative toponyms do not only reflect natural and sociocultural phenomena, but also help with related management and naming work. Historically, county-level administrative districts have been stable and basic administrative regions in China, playing a role in the country’s management. We explore the spatio-temporal evolutionary characteristics of the county-level administrative toponyms cultural landscape in China’s eastern plains areas. A Geographical Information System (GIS) analysis, Geo-Informatic Tupu, Kernel Density Estimation, and correlation coefficients were conducted. We constructed a GIS database of county-level administrative toponyms from the Sui dynasty onward using the Northeast China, North China, and Yangtze Plains as examples. We then summarized the spatio-temporal evolutionary characteristics of the county-level administrative toponyms cultural landscape in China’s eastern plains areas. The results indicate that (1) the number of toponyms has roughly increased over time; (2) toponym densities on the three plains are higher than the national average in the corresponding timeframe since the Sui; and (3) county-level administrative toponyms related to mountains and hydrological features accounted for more than 30% of the total in 2010. However, the percentage of county-level administrative toponyms related to natural factors on the three plains has decreased since the Sui. To explore the factors influencing this spatio-temporal evolution, we analyzed the correlations between the toponyms and natural factors and human/social factors. The correlation degree between toponym density and population density is the highest, and that between toponym density and Digital Elevation Model (DEM) the lowest. Temperature changes were important in toponym changes, and population changes have influenced toponym changes over the last 400 years in China. [ABSTRACT FROM AUTHOR]

Lane change violations are a major cause of traffic conflicts and accidents at urban intersections and one of many road-safety issues in China. This study aims to explore the socio-psychological factors underlying drivers’ motivation for lane change violation behavior at urban intersections and examines how these factors predict this violation behavior. A self-reported questionnaire is designed by applying the construct of the theory of planned behavior (TPB) to collect data. Five hundred-six valid responses are received from the questionnaire survey conducted on the Internet in China. The data are then analyzed using structural equation modeling (SEM). The results of the analysis show that behavioral intention is the strongest predictor of self-reported lane change violation behavior at urban intersections. Perceived behavioral control has both direct and indirect effects on self-reported lane change violation behavior. Furthermore, attitude, subjective norms and perceived behavioral control are found to have significant correlations with drivers’ intention of lane change violations at urban intersections. The results of this study could provide a reference for designing more effective interventions to modify drivers’ lane change violation behavior at urban intersections. [ABSTRACT FROM AUTHOR]

China's rapid urbanization and high traffic accident frequency have received many researchers’ attention. It is important to reveal how urban infrastructures and other risk factors affects the traffic accident frequency. A growing amount of research has examined the local risk factors impact on traffic accident frequency at certain time. Some studies considered these spatial influences but overlooked the temporal correlation/heterogeneity of traffic accidents and related risk factors. This study explores risk factors’ influence on urban traffic accidents frequency while considering both the spatial and temporal correlation/heterogeneity of traffic accidents. The study area is split into 100 equally sized rectangle traffic analysis zones (TAZs), and the urban traffic accident frequency and attributes in each TAZ are extracted. The linear regression model, spatial lag model (SLM), spatial error model (SEM) and time-fixed effects error model (T-FEEM) are established and compared respectively. The proposed methodologies are illustrated using ten-month traffic accident data from the urban area of Guiyang City, China. The results reveal that the time-fixed effects error model, which considers both spatial and temporal correlation/heterogeneity of traffic accidents, is superior to other models. More traffic accidents will happen in those TAZs that have more hospitals or schools. Moreover, hospitals have a greater influence on traffic accidents than schools. Because of the location in the margin of the city, those TAZs that have passenger stations have more traffic accidents. This study provides policy makers with more detailed characterization about the impact of related risk factors on traffic accident frequencies, and it is suggested that not only the spatial correlation/heterogeneity but also the temporal correlation/heterogeneity should be taken into account in guiding traffic accident control of urban area. [ABSTRACT FROM AUTHOR]

The worldwide rise of shared bicycle use has changed the way people travel. Here we analyze shared bicycle use from the perspective of the theory of planned behavior, and propose a model to investigate factors influencing shared bicycle usage in China. A total of 211 shared bicycle users selected from 28 provinces throughout China completed a self-reported survey. Structural equation modelling (SEM) was used to delineate the pathway from shared bicycle usage. The SEM model demonstrated that: (1) shared bicycle use intention was significantly associated with four variables, namely travel attitude(β = 0.491, t = 24.569), social norms(β = 0.149, t = 6.771), travel habits(β = 0.146, t = 7.226) and perceived behavioral control (β = 0.190, t = 11.110); (2) shared bicycle use behavior was significantly affected by shared bicycle use intention(β = 0.406, t = 15.936), and also by travel habits(β = 0.320, t = 11.921); (3) shared bicycle use behavior was also affected by demographic variables (gender, age) and situational factors (distance). The conclusions of this study provide useful data for operators of bicycle services and government policy makers. [ABSTRACT FROM AUTHOR]

Big data have contributed to deepen our understanding in regards to many human systems, particularly human mobility patterns and the structure and functioning of transportation systems. Resonating the recent call for ‘open big data,’ big data from various sources on a range of scales have become increasingly accessible to the public. However, open big data relevant to travelers within public transit tools remain scarce, hindering any further in-depth study on human mobility patterns. Here, we explore ticketing-website derived data that are publically available but have been largely neglected. We demonstrate the power, potential and limitations of this open big data, using the Chinese high-speed rail (HSR) system as an example. Using an application programming interface, we automatically collected the data on the remaining tickets (RTD) for scheduled trains at the last second before departure in order to retrieve information on unused transit capacity, occupancy rate of trains, and passenger flux at stations. We show that this information is highly useful in characterizing the spatiotemporal patterns of traveling behaviors on the Chinese HSR, such as weekend traveling behavior, imbalanced commuting behavior, and station functionality. Our work facilitates the understanding of human traveling patterns along the Chinese HSR, and the functionality of the largest HSR system in the world. We expect our work to attract attention regarding this unique open big data source for the study of analogous transportation systems. [ABSTRACT FROM AUTHOR]

Social networks play an important role in our daily lives. However, social ties are rather elusive to quantify, especially for large groups of subjects over prolonged periods of time. In this work, we first propose a methodology for extracting social ties from long spatio-temporal data streams, where the subjects are 17,795 undergraduates from a university of China and the data streams are the 9,147,106 time-stamped RFID check-in records left behind by them during one academic year. By several metrics mentioned below, we then analyze the structure of the social network. Our results center around three main observations. First, we characterize the global structure of the network, and we confirm the small-world phenomenon on a global scale. Second, we find that the network shows clear community structure. And we observe that younger students at lower levels tend to form large communities, while students at higher levels mostly form smaller communities. Third, we characterize the assortativity patterns by studying the basic demographic and network properties of users. We observe clear degree assortativity on a global scale. Furthermore, we find a strong effect of grade and school on tie formation preference, but we do not find any strong region homophily. Our research may help us to elucidate the structural characteristics and the preference of the formation of social ties in college students’ social network. [ABSTRACT FROM AUTHOR]

Housing is among the most pressing issues in urban China and has received considerable scholarly attention. Researchers have primarily concentrated on identifying the factors that influence residential property prices and how such mechanisms function. However, few studies have examined the potential factors that influence housing prices from a big data perspective. In this article, we use a big data perspective to determine the willingness of buyers to pay for various factors. The opinions and geographical preferences of individuals for places can be represented by visit frequencies given different motivations. Check-in data from the social media platform Sina Visitor System is used in this article. Here, we use kernel density estimation (KDE) to analyse the spatial patterns of check-in spots (or places of interest, POIs) and employ the Getis-Ord method to identify the hot spots for different types of POIs in Shenzhen, China. New indexes are then proposed based on the hot-spot results as measured by check-in data to analyse the effects of these locations on housing prices. This modelling is performed using the hedonic price method (HPM) and the geographically weighted regression (GWR) method. The results show that the degree of clustering of POIs has a significant influence on housing values. Meanwhile, the GWR method has a better interpretive capacity than does the HPM because of the former method’s ability to capture spatial heterogeneity. This article integrates big social media data to expand the scope (new study content) and depth (study scale) of housing price research to an unprecedented degree. [ABSTRACT FROM AUTHOR]

Background: Data from the Chinese police service suggest substantial reductions in road traffic injuries since 2002, but critics have questioned the accuracy of those data, especially considering conflicting data reported by the health department. Methods: To address the gap between police and health department data and to determine which may be more accurate, we conducted a simulation study based on the modified Smeed equation, which delineates a non-linear relation between road traffic mortality and the level of motorization in a country or region. Our goal was to simulate trends in road traffic mortality in China and compare performances in road traffic safety management between China and 13 other countries. Results: Chinese police data indicate a peak in road traffic mortalities in 2002 and a significant and a gradual decrease in population-based road traffic mortality since 2002. Health department data show the road traffic mortality peaked in 2012. In addition, police data suggest China’s road traffic mortality peaked at a much lower motorization level (0.061 motor vehicles per person) in 2002, followed by a reduction in mortality to a level comparable to that of developed countries. Simulation results based on health department data suggest high road traffic mortality, with a mortality peak in 2012 at a moderate motorization level (0.174 motor vehicles per person). Comparisons to the other 13 countries suggest the health data from China may be more valid than the police data. Conclusion: Our simulation data indicate China is still at a stage of high road traffic mortality, as suggested by health data, rather than a stage of low road traffic mortality, as suggested by police data. More efforts are needed to integrate safety into road design, improve road traffic management, improve data quality, and alter unsafe behaviors of pedestrians, drivers and passengers in China. [ABSTRACT FROM AUTHOR]

We investigate the economic hubs and authorities of the world trade network (WTN) from to , an era of rapid economic globalization. Using a well-defined weighted hyperlink-induced topic search (HITS) algorithm, we can calculate the values of the weighted HITS hub and authority for each country in a conjugate way. In the context of the WTN, authority values are large for countries with significant imports from large hub countries, and hub values are large for countries with significant exports to high-authority countries. The United States was the largest economic authority in the WTN from to . The authority value of the United States has declined since , and China has now become the largest hub in the WTN. At the same time, China's authority value has grown as China is transforming itself from the “factory of the world” to the “market of the world.” European countries show a tendency to trade mostly within the European Union, which has decreased Europe's hub and authority values. Japan's authority value has increased slowly, while its hub value has declined. These changes are consistent with Japan's transition from being an export-driven economy in its high economic growth era in the latter half of the twentieth century to being a more mature, economically balanced nation. [ABSTRACT FROM AUTHOR]

Background: Although China ratified the WHO Framework Convention on Tobacco Control [FCTC] in 2005, the partial ban on tobacco advertising does not cover the internet. Weibo is one of the most important social media channels in China, using a format similar to its global counterpart, Twitter. The Weibo homepage is a platform to present products, brands and corporate culture. There is great potential for the tobacco industry to exploit Weibo to promote products. Methods: Seven tobacco industry Weibo accounts that each had more than 5000 fans were selected to examine the content of Weibos established by tobacco companies or their advertising agents. Results: Of the 12073 posts found on the seven accounts, 92.3% (11143) could be classified into six main themes: traditional culture, popular culture, social and business affairs, advertisement, public relations and tobacco culture. Posts under the theme of popular culture accounted for about half of total posts (49%), followed by ‘advertisement’ and ‘tobacco culture’ (both at 12%), ‘traditional culture’ and ‘public relations’ (both at 11%), and finally ‘social and business affairs’ (5%). 33% of posts included the words ‘cigarette’ or ‘smoking’ and 53% of posts included the tobacco brand name, indicating that tobacco companies carefully construct the topic and content of posts. Conclusions: Weibo is an important new online marketing tool for the Chinese tobacco industry. Tobacco industry use of Weibo to promote brands and normalize smoking subverts China's ratification of the WHO FCTC. Policy to control tobacco promotion needs reforming to address this widespread circumvention of China's tobacco advertising ban. [ABSTRACT FROM AUTHOR]

So far, many studies on educational games have been carried out in America and Europe. Very few related empirical studies, however, have been conducted in China. This study, combining both quantitative with qualitative research methods, possibly compensated for this regret. The study compared data collected from two randomly selected classes (out of 13 classes) under computer game-based instruction (CGBI) and non-computer game-based instruction (NCGBI), respectively, in a senior high school located in Nanjing, Capital of Jiangsu Province, in China. The participants were 103 students, composed of 52 boys and 51 girls (aged 17-18 years old). The following conclusion was reached: (1) participants under CGBI obtained significantly greater learning achievement than those under NCGBI; (2) participants were significantly more motivated by CGBI compared with NCGBI; (3) there were no significant differences in learning achievement between boys and girls; although (4) boys were significantly more motivated by CGBI than girls. Both disadvantages and advantages were discussed, together with directions for future research. [ABSTRACT FROM AUTHOR]