This page has only limited features, please log in for full access.

Dr. Yigang Wei
School of Economics and Management, Beihang University, Beijing, China

Basic Info


Research Keywords & Expertise

0 Innovation
0 Renewable Energy
0 Sustainable Development
0 ecological efficiency
0 Carbon market

Fingerprints

Sustainable Development
Innovation

Honors and Awards

The user has no records in this section


Career Timeline

The user has no records in this section.


Short Biography

The user biography is not available.
Following
Followers
Co Authors
The list of users this user is following is empty.
Following: 0 users

Feed

Journal article
Published: 28 June 2021 in International Journal of Disaster Risk Reduction
Reads 0
Downloads 0

The cycle of traditional disaster loss assessment methods is too long because the assessment results need to be passed among multiple issues. Such a long cycle causes relevant departments to be unable to make emergency decisions in a timely manner. This paper builds a dynamic and real-time model for disaster loss assessment based on social media data. This model presents a method for mining quantitative human loss information from social media data and a truth discovery algorithm for handling social media data conflicts. An experiment using the actual data of the Jiuzhaigou earthquake is conducted to verify the model. The results confirm that the method proposed in this study can accelerate the process of reporting traditional human loss information between multiple levels and departments and assess human loss in a real-time and dynamic manner. The findings are important for providing timely assistance to official agencies and the public.

ACS Style

Siqing Shan; Feng Zhao; Yigang Wei. Real-time assessment of human loss in disasters based on social media mining and the truth discovery algorithm. International Journal of Disaster Risk Reduction 2021, 62, 102418 .

AMA Style

Siqing Shan, Feng Zhao, Yigang Wei. Real-time assessment of human loss in disasters based on social media mining and the truth discovery algorithm. International Journal of Disaster Risk Reduction. 2021; 62 ():102418.

Chicago/Turabian Style

Siqing Shan; Feng Zhao; Yigang Wei. 2021. "Real-time assessment of human loss in disasters based on social media mining and the truth discovery algorithm." International Journal of Disaster Risk Reduction 62, no. : 102418.

Research article
Published: 20 May 2021 in Environmental Science and Pollution Research
Reads 0
Downloads 0

The world has been challenged by achieving the plausible goal of sustainable development. This study aims to evaluate the ecological footprint and ecological carrying capacity and their driving factors of Shandong province in China from 1994 to 2017. Back propagation neural network method is adopted to predict the ecological footprint from 2018 to 2030. The findings are as follows: (1) The growth of ecological footprint has caused the ecological deficit in Shandong. (2) With regards to population, the increase of total population and the urbanization rate will incur the expansion of ecological footprint. (3) In terms of affluence, the elasticity coefficients of GDP per capita, the production value of industrial sectors, and the proportion of output value of the secondary industry in GDP are 0.068, 0.064, and 0.130 respectively. (4) In terms of technology, the elasticity coefficients of internal expenditure on R&D in GDP and patent number are 0.096 and 0.047 respectively, indicating that technological progress can promote ecological footprint in a short term. (6) The results of the prediction show that the ecological footprint of Shandong from 2018 to 2030 in the policy-regulation scenario is far less than that of the business-as-usual scenario. The policy recommendations are suggested to tackle the sustainable development challenges.

ACS Style

Yan Li; Zhicheng Wang; Yigang Wei. Pathways to progress sustainability: an accurate ecological footprint analysis and prediction for Shandong in China based on integration of STIRPAT model, PLS, and BPNN. Environmental Science and Pollution Research 2021, 1 -24.

AMA Style

Yan Li, Zhicheng Wang, Yigang Wei. Pathways to progress sustainability: an accurate ecological footprint analysis and prediction for Shandong in China based on integration of STIRPAT model, PLS, and BPNN. Environmental Science and Pollution Research. 2021; ():1-24.

Chicago/Turabian Style

Yan Li; Zhicheng Wang; Yigang Wei. 2021. "Pathways to progress sustainability: an accurate ecological footprint analysis and prediction for Shandong in China based on integration of STIRPAT model, PLS, and BPNN." Environmental Science and Pollution Research , no. : 1-24.

Journal article
Published: 19 May 2021 in International Journal of Environmental Research and Public Health
Reads 0
Downloads 0

PM2.5 not only harms physical health but also has negative impacts on the public’s wellbeing and cognitive and behavioral patterns. However, traditional air quality assessments may fail to provide comprehensive, real-time monitoring of air quality because of the sparse distribution of air quality monitoring stations. Overcoming some key limitations of traditional surface monitoring data, Web-based social media platforms, such as Twitter, Weibo, and Facebook, provide a promising tool and novel perspective for environmental monitoring, prediction, and evaluation. This study aims to investigate the relationship between PM2.5 levels and people’s emotional intensity by observing social media postings. This study defines the “emotional intensity” indicator, which is measured by the number of negative posts on Weibo, based on Weibo data related to haze from 2016 and 2017. This study estimates sentiment polarity using a recurrent neural networks model based on LSTM (Long Short-Term Memory) and verifies the correlation between high PM2.5 levels and negative posts on Weibo using a Pearson correlation coefficient and multiple linear regression model. This study makes the following observations: (1) Taking the two-year data as an example, this study recorded the significant influence of PM2.5 levels on netizens’ posting behavior. (2) Air quality, meteorological factors, the seasons, and other factors have a strong influence on netizens’ emotional intensity. (3) From a quantitative viewpoint, the level of PM2.5 varies by 1 unit, and the number of negative Weibo posts fluctuates by 1.0168 units. Thus, it can be concluded that netizens’ emotional intensity is significantly positively affected by levels of PM2.5. The high correlation between PM2.5 levels and emotional intensity and the sensitivity of social media data shows that social media data can be used to provide a new perspective on the assessment of air quality.

ACS Style

Siqing Shan; Xijie Ju; Yigang Wei; Zijin Wang. Effects of PM2.5 on People’s Emotion: A Case Study of Weibo (Chinese Twitter) in Beijing. International Journal of Environmental Research and Public Health 2021, 18, 5422 .

AMA Style

Siqing Shan, Xijie Ju, Yigang Wei, Zijin Wang. Effects of PM2.5 on People’s Emotion: A Case Study of Weibo (Chinese Twitter) in Beijing. International Journal of Environmental Research and Public Health. 2021; 18 (10):5422.

Chicago/Turabian Style

Siqing Shan; Xijie Ju; Yigang Wei; Zijin Wang. 2021. "Effects of PM2.5 on People’s Emotion: A Case Study of Weibo (Chinese Twitter) in Beijing." International Journal of Environmental Research and Public Health 18, no. 10: 5422.

Journal article
Published: 16 January 2021 in Journal of Rural Studies
Reads 0
Downloads 0

Rural nonfarm sector (RNFS) development is an important part of China's national “Rural Revitalization Strategy”. RNFS is also a prerequisite for prosperity in the rural economy, which is properly measured by rural resident income (RRI). Thus, China's rural economic policy should be based on the perspicuity of RNFS′ spatial agglomeration situation and the clarity of its development trend. Previous studies on RRI, however, have paid limited attention on RNFS's spatial pattern and its effects on RRI especially after the ownership reform of township and village enterprises. The present study aims to estimate the effect of RNFS on RRI by assessing the RNFS development level in different provinces and investigating their spatial characteristics from 2000 to 2013. The main conclusions are as follows: (1) the overall development of RNFS in China is rapid, but the spatial differences are expanding, the agglomeration degree is relatively low, and the composition of industrial types is higher in the eastern region than in the middle and western regions; 2) regression results show that the RNFS has a significant positive effect on RRI. On the contrary, RRI's dependence on RNFS in the middle and western regions is higher than that in the eastern region. Government departments should foster RNFS on the basis of local conditions. Guided by the long-term objective of rural revitalization, the proportion of nonagricultural employment in rural areas should be constantly increased to improve RRI.

ACS Style

Wei Han; Yigang Wei; Jianming Cai; Yunjiang Yu; Furong Chen. Rural nonfarm sector and rural residents’ income research in China. An empirical study on the township and village enterprises after ownership reform (2000-2013). Journal of Rural Studies 2021, 82, 161 -175.

AMA Style

Wei Han, Yigang Wei, Jianming Cai, Yunjiang Yu, Furong Chen. Rural nonfarm sector and rural residents’ income research in China. An empirical study on the township and village enterprises after ownership reform (2000-2013). Journal of Rural Studies. 2021; 82 ():161-175.

Chicago/Turabian Style

Wei Han; Yigang Wei; Jianming Cai; Yunjiang Yu; Furong Chen. 2021. "Rural nonfarm sector and rural residents’ income research in China. An empirical study on the township and village enterprises after ownership reform (2000-2013)." Journal of Rural Studies 82, no. : 161-175.

Journal article
Published: 14 January 2021 in International Journal of Environmental Research and Public Health
Reads 0
Downloads 0

Against the backdrop of globalization and trade facilitation, the products consumed by a country are more and more relying on the importation of those products from other countries. Therefore, the pollutant emissions of products associated are transferred from consuming countries to exporting countries, which significantly changes the spatial distribution of global pollutant emissions. The objective of this research is to analyse the embodied nitrogen oxide (NOx) emissions in the trading process between China and the European Union (EU) and to further trace the interindustry and intercountry transfer paths. This study constructs a multiregional input–output (MRIO) model based on the latest EORA global supply chain database. The MRIO model quantitatively analyses the total NOx emissions from the production and consumption ends of China and the EU from 1995 to 2014. Important findings are derived from the empirical results as follows. (1) In 2014, China’s production end emissions were 1824.38 kilotons higher than those of the consumption end. By contrast, the situation in the EU was the opposite, i.e., production end emissions were 1711.97 kilotons lower than those of the consumption end. (2) In the trade between China and the EU, the EU is a net importer of embodied NOx, and China is a net exporter of embodied NOx. In 2014, 2.55% of China’s domestic NOx emissions were transferred to the EU in China-EU trade, accounting for 2.75% of China’s domestic consumption demand. (3) In 2014, Electricity, Gas and Water (397.75 kilotons), Transport (343.55 kilotons), Petroleum, Chemical and non-metallic Products (95.9 kilotons), Metal Products (49.88 kilotons), Textiles and Apparel (26.19 kilotons), are among the industries with the most embodied NOx emissions from China’s net exports during its two-way trade with the EU. 4) In the bilateral trade between the EU and China, many countries are in the state of embodied NOx net import. The top three net importers in 2014 were Germany (169.24 kilotons), Britain (128.11 kilotons), France (103.21 kilotons).

ACS Style

Yan Li; Yigang Wei; Xueqing Wang; Hanxiao Xu. Substantial Nitrogen Oxide Pollution Is Embodied in the Bilateral Trade between China and the European Union. International Journal of Environmental Research and Public Health 2021, 18, 675 .

AMA Style

Yan Li, Yigang Wei, Xueqing Wang, Hanxiao Xu. Substantial Nitrogen Oxide Pollution Is Embodied in the Bilateral Trade between China and the European Union. International Journal of Environmental Research and Public Health. 2021; 18 (2):675.

Chicago/Turabian Style

Yan Li; Yigang Wei; Xueqing Wang; Hanxiao Xu. 2021. "Substantial Nitrogen Oxide Pollution Is Embodied in the Bilateral Trade between China and the European Union." International Journal of Environmental Research and Public Health 18, no. 2: 675.

Original contribution
Published: 01 December 2020 in EcoHealth
Reads 0
Downloads 0

Biodiversity loss is on the list of the most challenging issues the world sustainability faces. This study aims to examine the global illegal ivory trades, identify key hub countries and map the key smuggling routes in the worldwide illegal ivory trading network. A social network analysis (SNA) and a set of network indicators are used to investigate CITES’s (Convention on International Trade in Endangered Species of Wild Fauna and Flora) ivory trading data from 1975 to 2017. Several important conclusions are derived: (1) The social network of global ivory trading is closely connected, with an average path length of 2.643 and an average clustering coefficient of 0.463. An average of 45,410.384 kg of ivory products was trafficked from each of the 182 countries to an average of another 8.17 countries. The dynamic networks of global ivory trading show the pattern of high connectivity and high aggregation. (2) The USA, the UK, Zimbabwe, South Africa, China, Japan, Sudan, Belgium and Hong Kong are the most important hubs in the worldwide ivory trade according to degrees and centralities in the SNA. (3) According to trading weight density, three significant ivory trafficking routes are illustrated: 1. African countries (Sudan, Zimbabwe, South Africa, Central African Republic, the Republic of Congo, Somalia and Uganda) to Hong Kong; 2. Belgium to Hong Kong and Japan; 3. Mutual transactions between Japan and Hong Kong. The analytical framework in this study can also be useful for studying other illegal trading activities, like other animal trades, with respect to biodiversity conversation, and could serve as a reference for other network-based sustainability challenges, such as human migration, biological invasion, and waste smuggling and dumping.

ACS Style

Wenyang Huang; Huiwen Wang; Yigang Wei. Mapping the Illegal International Ivory Trading Network to Identify Key Hubs and Smuggling Routes. EcoHealth 2020, 17, 523 -539.

AMA Style

Wenyang Huang, Huiwen Wang, Yigang Wei. Mapping the Illegal International Ivory Trading Network to Identify Key Hubs and Smuggling Routes. EcoHealth. 2020; 17 (4):523-539.

Chicago/Turabian Style

Wenyang Huang; Huiwen Wang; Yigang Wei. 2020. "Mapping the Illegal International Ivory Trading Network to Identify Key Hubs and Smuggling Routes." EcoHealth 17, no. 4: 523-539.

Journal article
Published: 19 September 2020 in International Journal of Environmental Research and Public Health
Reads 0
Downloads 0

Detecting the period of a disease is of great importance to building information management capacity in disease control and prevention. This paper aims to optimize the disease surveillance process by further identifying the infectious or recovered period of flu cases through social media. Specifically, this paper explores the potential of using public sentiment to detect flu periods at word level. At text level, we constructed a deep learning method to classify the flu period and improve the classification result with sentiment polarity. Three important findings are revealed. Firstly, bloggers in different periods express significantly different sentiments. Blogger sentiments in the recovered period are more positive than in the infectious period when measured by the interclass distance. Secondly, the optimized disease detection process can substantially improve the classification accuracy of flu periods from 0.876 to 0.926. Thirdly, our experimental results confirm that sentiment classification plays a crucial role in accuracy improvement. Precise identification of disease periods enhances the channels for the disease surveillance processes. Therefore, a disease outbreak can be predicted credibly when a larger population is monitored. The research method proposed in our work also provides decision making reference for proactive and effective epidemic control and prevention in real time.

ACS Style

Siqing Shan; Qi Yan; Yigang Wei. Infectious or Recovered? Optimizing the Infectious Disease Detection Process for Epidemic Control and Prevention Based on Social Media. International Journal of Environmental Research and Public Health 2020, 17, 6853 .

AMA Style

Siqing Shan, Qi Yan, Yigang Wei. Infectious or Recovered? Optimizing the Infectious Disease Detection Process for Epidemic Control and Prevention Based on Social Media. International Journal of Environmental Research and Public Health. 2020; 17 (18):6853.

Chicago/Turabian Style

Siqing Shan; Qi Yan; Yigang Wei. 2020. "Infectious or Recovered? Optimizing the Infectious Disease Detection Process for Epidemic Control and Prevention Based on Social Media." International Journal of Environmental Research and Public Health 17, no. 18: 6853.

Research article
Published: 09 June 2020 in Systems Research and Behavioral Science
Reads 0
Downloads 0

Industrial Internet is an important component of Industry 4.0. It aims to help manufacturers achieve intelligent management and decision making. In information era, manufacturing is becoming increasingly sophisticated and intelligent. Traditional manufacturers are exploring approaches to improve their competitiveness. Industrial Internet appears to be the solution for them to achieve their goals. However, they lack the guidelines to implement Industrial Internet. As such, this paper reviews Industry 4.0 and Industrial Internet and presents a case study about how Sany Heavy Industry applying systems thinking in implementing Industrial Internet and transforming itself into intelligent manufacturing. The growth path of intelligent manufacturing in Sany Heavy Industry is outlined. The directions for future development of intelligent manufacturing are discussed.

ACS Style

Siqing Shan; Xin Wen; Yigang Wei; Zijin Wang; Yong Chen. Intelligent manufacturing in industry 4.0: A case study of Sany heavy industry. Systems Research and Behavioral Science 2020, 37, 679 -690.

AMA Style

Siqing Shan, Xin Wen, Yigang Wei, Zijin Wang, Yong Chen. Intelligent manufacturing in industry 4.0: A case study of Sany heavy industry. Systems Research and Behavioral Science. 2020; 37 (4):679-690.

Chicago/Turabian Style

Siqing Shan; Xin Wen; Yigang Wei; Zijin Wang; Yong Chen. 2020. "Intelligent manufacturing in industry 4.0: A case study of Sany heavy industry." Systems Research and Behavioral Science 37, no. 4: 679-690.

Journal article
Published: 07 June 2020 in Energies
Reads 0
Downloads 0

China has set out an ambitious target of emission abatement; that is, a 60–65% reduction in CO2 emission intensity by 2030 compared with the 2005 baseline level and emission peak realisation. This paper aimed to forecast whether China can fulfil the reduction target of CO2 emission intensity and peak by 2030 based on the historical time series data from 1990 to 2018. Four different forecasting techniques were used to improve the accuracy of the forecasting results: the autoregressive integrated moving average (ARIMA) model and three grey system-based models, including the traditional grey model (1,1), the discrete grey model (DGM) and the rolling DGM. The behaviours of these techniques were compared and validated in the forecasting comparisons. The forecasting performance of the four forecasting models was good considering the minimum mean absolute percentage error (MAPE), demonstrating MAPE values lower than 2%. ARIMA showed the best forecasting performance over the historical period with a MAPE value of 0.60%. The forecasting results of ARIMA indicate that China would not achieve sufficient reductions despite its projected emission peak of 96.3 hundred million tons by 2021. That is, the CO2 emission intensity of China will be reduced by 57.65% in 2030 compared with the 2005 levels. This reduction is lower than the government goal of 60–65%. This paper presents pragmatic recommendations for effective emission intensity reduction to ensure the achievements of the claimed policy goals.

ACS Style

Yan Li; Yigang Wei; Zhang Dong. Will China Achieve Its Ambitious Goal?—Forecasting the CO2 Emission Intensity of China towards 2030. Energies 2020, 13, 2924 .

AMA Style

Yan Li, Yigang Wei, Zhang Dong. Will China Achieve Its Ambitious Goal?—Forecasting the CO2 Emission Intensity of China towards 2030. Energies. 2020; 13 (11):2924.

Chicago/Turabian Style

Yan Li; Yigang Wei; Zhang Dong. 2020. "Will China Achieve Its Ambitious Goal?—Forecasting the CO2 Emission Intensity of China towards 2030." Energies 13, no. 11: 2924.

Journal article
Published: 23 May 2020 in Socio-Economic Planning Sciences
Reads 0
Downloads 0

Urban river pollution has brought about serious challenges to residents in terms of bodily health and emotional well-being. Based on a social media platform, Chinese Twitter (Weibo), this paper proposes a research framework to investigate the emotional responses of people according to four dimensions: trends, seasons, space and dynamics (TSSD). This study presents several important findings. First, negative responses were much more common than positive ones across all seasons, 22.8% and 9.2%, respectively, which means that river pollution adversely affects residents' well-being in general. Second, negative responses are likely related to local garbage piles, landslides, heavy rains, traffic jams, and demolition, while positive reactions are likely related to beautiful weather or spending time with family members. Third, summer and winter are more likely to induce negative emotions than spring and autumn, with the negative index of summer or winter approaching 80%. This study confirmed that social media data are of great value in measuring the behaviors and emotional responses of humans to their surrounding environment.

ACS Style

Siqing Shan; Jing Peng; Yigang Wei. Environmental Sustainability assessment 2.0: The value of social media data for determining the emotional responses of people to river pollution—A case study of Weibo (Chinese Twitter). Socio-Economic Planning Sciences 2020, 75, 100868 .

AMA Style

Siqing Shan, Jing Peng, Yigang Wei. Environmental Sustainability assessment 2.0: The value of social media data for determining the emotional responses of people to river pollution—A case study of Weibo (Chinese Twitter). Socio-Economic Planning Sciences. 2020; 75 ():100868.

Chicago/Turabian Style

Siqing Shan; Jing Peng; Yigang Wei. 2020. "Environmental Sustainability assessment 2.0: The value of social media data for determining the emotional responses of people to river pollution—A case study of Weibo (Chinese Twitter)." Socio-Economic Planning Sciences 75, no. : 100868.

Article
Published: 16 April 2020 in Environment, Development and Sustainability
Reads 0
Downloads 0

With the rapid and widespread urbanization, a large number of people pour into cities, which bring a series of urban diseases and directly threaten the sustainable development of the destination city. It is particularly important to reasonably measure the population carrying capacity to promote the sustainable development of cities. Therefore, based on Shanghai’s municipal data from 1985 to 2017, this paper used the probability-satisfaction method to predict the urban population carrying capacity of Shanghai in 2020. Several important findings are derived: First, there is a general pattern that the urban population carrying capacity increases as the probability-satisfaction level decreases; second, the sensitive degrees of the population carrying capacity of different constraining factors vary. The sensitive degrees of the city’s GDP, fiscal revenues and paved road areas are lower than those of other constraining factors; third, currently the number of medical practitioners, the paved road areas and the volume of waste emission are the three most important constraining factors in Shanghai. Fourth, results of the multifactor analysis reveal that when the probability-satisfaction level is equal to the ideal level, the overall population carrying capacity of Shanghai is between 17.55 million and 23.52 million; when the probability-satisfaction level research the acceptable level, the overall population carrying capacity of Shanghai is between 20.35 million and 30.12 million people. Therefore, by 2020, the Shanghai government needs to formulate well-considering population management plan according to actual resources conditions in order to achieve balanced and sustainable urban development.

ACS Style

Yingying Zhang; Yigang Wei; Jian Zhang. Overpopulation and urban sustainable development—population carrying capacity in Shanghai based on probability-satisfaction evaluation method. Environment, Development and Sustainability 2020, 23, 3318 -3337.

AMA Style

Yingying Zhang, Yigang Wei, Jian Zhang. Overpopulation and urban sustainable development—population carrying capacity in Shanghai based on probability-satisfaction evaluation method. Environment, Development and Sustainability. 2020; 23 (3):3318-3337.

Chicago/Turabian Style

Yingying Zhang; Yigang Wei; Jian Zhang. 2020. "Overpopulation and urban sustainable development—population carrying capacity in Shanghai based on probability-satisfaction evaluation method." Environment, Development and Sustainability 23, no. 3: 3318-3337.

Journal article
Published: 20 March 2020 in Structural Change and Economic Dynamics
Reads 0
Downloads 0

China has promised to reduce 60–65% of its 2005 carbon emission per GDP unit in 2030. This study aims to decompose China's emission reduction task to regional and provincial levels according to efficiency, equity, and synthesizing principles, respectively, during 1996–2015. Results show the following: (1) Through the cluster analysis of eight indexes including shadow price, China's provinces can be divided into three sub-regions; (2) In regional level, Sub-region 2 should take the largest carbon reduction proportion, accounting for about 60%; Sub-region 3 and Sub-region 1 should take 30% and 10% respectively;(3) On provincial level, the provinces that account for more than 5% of carbon dioxide emission reduction task of China are Shandong (9.33%), Shanxi (8.83%), Hebei (7.56%), Jiangsu (6.90%), Sichuan (6.40%), Guangdong (5.23%), and Inner Mongolia (5.20%);(4) Considering the emission reduction costs, it is best to decompose tasks according to the equity principle in the provincial level.

ACS Style

Yan Li; Yigang Wei; Xiaoling Zhang; Yuan Tao. Regional and provincial CO2 emission reduction task decomposition of China's 2030 carbon emission peak based on the efficiency, equity and synthesizing principles. Structural Change and Economic Dynamics 2020, 53, 237 -256.

AMA Style

Yan Li, Yigang Wei, Xiaoling Zhang, Yuan Tao. Regional and provincial CO2 emission reduction task decomposition of China's 2030 carbon emission peak based on the efficiency, equity and synthesizing principles. Structural Change and Economic Dynamics. 2020; 53 ():237-256.

Chicago/Turabian Style

Yan Li; Yigang Wei; Xiaoling Zhang; Yuan Tao. 2020. "Regional and provincial CO2 emission reduction task decomposition of China's 2030 carbon emission peak based on the efficiency, equity and synthesizing principles." Structural Change and Economic Dynamics 53, no. : 237-256.

Articles
Published: 10 February 2020 in Enterprise Information Systems
Reads 0
Downloads 0

User-Generated Content (UGC) is becoming a powerful data source to support emergency management. Managers usually face two difficulties in practical emergency management. First, the requirement topics for emergency management are changing over time. Second, the value of the same microblog is changing over different emergency phases. The contributions of this study lie in the following aspects. First, this paper develops a multiphase dynamic assessment model. Second, an idea for the dynamic evaluation of UGC is proposed. Third, this paper presents an effective quantification method to assess the dynamic value of social media data.

ACS Style

Siqing Shan; Xiaohui Liu; Yigang Wei; Lida Xu; Baishang Zhang; Lei Yu. A new emergency management dynamic value assessment model based on social media data: a multiphase decision-making perspective. Enterprise Information Systems 2020, 14, 680 -709.

AMA Style

Siqing Shan, Xiaohui Liu, Yigang Wei, Lida Xu, Baishang Zhang, Lei Yu. A new emergency management dynamic value assessment model based on social media data: a multiphase decision-making perspective. Enterprise Information Systems. 2020; 14 (5):680-709.

Chicago/Turabian Style

Siqing Shan; Xiaohui Liu; Yigang Wei; Lida Xu; Baishang Zhang; Lei Yu. 2020. "A new emergency management dynamic value assessment model based on social media data: a multiphase decision-making perspective." Enterprise Information Systems 14, no. 5: 680-709.

Journal article
Published: 20 December 2019 in International Journal of Strategic Property Management
Reads 0
Downloads 0

Based on the monthly data of 35 cities during the period 2006−2017, this study adopts a recursive forward looking method to detect the presence of housing bubbles and investigate their potential cyclical patterns in China’s large and medium sized cities. Empirical results show that the number of cities reporting housing bubbles has been increasing since 2013, before it declined in 2017. Regarding regional disparities of housing bubbles, 1st-tier and 1.5-tier cities have higher probability than 2nd-tier cities for housing bubbles. In general, eastern region cities have more housing bubbles than central and western region cities, which may indicate the problem of shrinking cities China is facing nowadays. Bubble signals for market correction in major cities and municipalities seemed alarming in particular for the period 2013−2016, however it is difficult to conclude if the market adjustment in 2017 indicates a cyclical pattern.

ACS Style

Jing Li; Yigang Wei; Yat Hung Chiang. BUBBLES OR CYCLES? HOUSING PRICE DYNAMICS IN CHINA’S MAJOR CITIES. International Journal of Strategic Property Management 2019, 24, 90 -101.

AMA Style

Jing Li, Yigang Wei, Yat Hung Chiang. BUBBLES OR CYCLES? HOUSING PRICE DYNAMICS IN CHINA’S MAJOR CITIES. International Journal of Strategic Property Management. 2019; 24 (2):90-101.

Chicago/Turabian Style

Jing Li; Yigang Wei; Yat Hung Chiang. 2019. "BUBBLES OR CYCLES? HOUSING PRICE DYNAMICS IN CHINA’S MAJOR CITIES." International Journal of Strategic Property Management 24, no. 2: 90-101.

Research article
Published: 19 June 2019 in Sustainable Development
Reads 0
Downloads 0

Globally, cities are generally facing challenges of sustainable development, and this is particularly true in megacities. To reveal the relationship between economy and ecology, green gross domestic product (GDP) represents the ideology and requirements of sustainable development. In this study, emergy analysis theory is introduced to the green GDP accounting system and to a sustainable development evaluation framework using Wuhan City from 1994 to 2015 as a case study. The results show that (a) the green GDP increases as traditional GDP grows year by year, indicating the improvement of the sustainability development of Wuhan. (b) In terms of green GDP contributing factors, the proportion of nonrenewable energy in traditional GDP decreased from 11.91% to 5.31%, reflecting remarkable progresses in the promotion of saving energy. (c) In terms of the sustainability dynamic assessment, result greater than one for the Emergy Sustainability Index implies the economic system of Wuhan following a trajectory of sustainable development, but the downward trend of the Environment Index of Sustainable Development in recent years indicates that Wuhan needs to improve its socioeconomic performance. Based on the emergy analysis, this study provides a theoretical framework for investigating and assessing the temporal characteristics of green GDP accounting, urban sustainability assessment, and inhibiting factors in the progress of sustainability. Empirical findings provide theoretical support and policy recommendations for the promotion of urban sustainable development.

ACS Style

Yigang Wei; Yan Li; Xinjing Liu; Meiyu Wu. Sustainable development and green gross domestic product assessments in megacities based on the emergy analysis method—A case study of Wuhan. Sustainable Development 2019, 28, 294 -307.

AMA Style

Yigang Wei, Yan Li, Xinjing Liu, Meiyu Wu. Sustainable development and green gross domestic product assessments in megacities based on the emergy analysis method—A case study of Wuhan. Sustainable Development. 2019; 28 (1):294-307.

Chicago/Turabian Style

Yigang Wei; Yan Li; Xinjing Liu; Meiyu Wu. 2019. "Sustainable development and green gross domestic product assessments in megacities based on the emergy analysis method—A case study of Wuhan." Sustainable Development 28, no. 1: 294-307.

Research article
Published: 11 April 2019 in PLoS ONE
Reads 0
Downloads 0

The changing population age structure has a significant influence on the economy, society, and numerous other aspects of a country. This paper has innovatively applied the method of compositional data forecasting for the prediction of population age changes of the young (aged 0-14), the middle-aged (aged 15-64), and the elderly (aged older than 65) in China, India, and Vietnam by 2030 based on data from 1960 to 2016. To select the best-suited forecasting model, an array of data transformation approaches and forecasting models have been extensively employed, and a large number of comparisons have been made between the aforementioned methods. The best-suited model for each country is identified considering the root mean squared error and mean absolute percent error values from the compositional data. As noted in this study, first and foremost, it is predicted that by the year 2030, China will witness the disappearance of population dividend and get mired in an aging problem far more severe than that of India or Vietnam. Second, Vietnam's trend of change in population age structure resembles that of China, but the country will sustain its good health as a whole. Finally, the working population of India demonstrates a strong rising trend, indicating that the age structure of the Indian population still remains relatively "young". Meanwhile, the continuous rise in the proportion of elderly population and the gradual leveling off growth of the young population have nevertheless become serious problems in the world. The present paper attempts to offer crucial insights into the Asian population size, labor market and urbanization, and, moreover, provides suggestions for a sustainable global demographic development.

ACS Style

Yigang Wei; Zhichao Wang; Huiwen Wang; Yan Li; Zhenyu Jiang. Predicting population age structures of China, India, and Vietnam by 2030 based on compositional data. PLoS ONE 2019, 14, e0212772 .

AMA Style

Yigang Wei, Zhichao Wang, Huiwen Wang, Yan Li, Zhenyu Jiang. Predicting population age structures of China, India, and Vietnam by 2030 based on compositional data. PLoS ONE. 2019; 14 (4):e0212772.

Chicago/Turabian Style

Yigang Wei; Zhichao Wang; Huiwen Wang; Yan Li; Zhenyu Jiang. 2019. "Predicting population age structures of China, India, and Vietnam by 2030 based on compositional data." PLoS ONE 14, no. 4: e0212772.

Journal article
Published: 02 March 2019 in Safety Science
Reads 0
Downloads 0

In the era of big data, could popularized social media platforms assist with urban damage monitoring and assessment and aid disaster rescue? Before, during, and after such disasters, citizens might disseminate disaster-related text and data through social media platforms. Therefore, social media is both a powerful and promising tool for disaster response management, including enhancing situation awareness, promoting emergency information flow, predicting disasters and coordinating rescue efforts. This study develops a framework for real-time urban disaster damage monitoring and assessment. Social media texts sent during and after the Tianjin explosion and Typhoon Nepartak (i.e., a manmade and natural large-scale disaster, respectively) disasters are collected and constitute the database. The real-time monitoring of physical damage and sentiment provides the main categories of damage and damage scale information. In this study, a physical assessment provides a detailed quantity of the losses according to the different types of damage sustained over time. One pronounced innovation is the study’s comprehensive perspective, which facilitates a thorough analysis of both the emotional and physical damage in real-time scenarios. In addition, a quantity evaluation of physical damage is performed. The findings suggest that social media can be used for rapid damage evaluations as the real-time and huge information flow contains the aforementioned damage categories, damage scale and damage quantity messages. The social media database damage assessment model presented in this study can enhance disaster situation awareness and rescue operations.

ACS Style

Siqing Shan; Feng Zhao; Yigang Wei; Mengni Liu. Disaster management 2.0: A real-time disaster damage assessment model based on mobile social media data—A case study of Weibo (Chinese Twitter). Safety Science 2019, 115, 393 -413.

AMA Style

Siqing Shan, Feng Zhao, Yigang Wei, Mengni Liu. Disaster management 2.0: A real-time disaster damage assessment model based on mobile social media data—A case study of Weibo (Chinese Twitter). Safety Science. 2019; 115 ():393-413.

Chicago/Turabian Style

Siqing Shan; Feng Zhao; Yigang Wei; Mengni Liu. 2019. "Disaster management 2.0: A real-time disaster damage assessment model based on mobile social media data—A case study of Weibo (Chinese Twitter)." Safety Science 115, no. : 393-413.

Journal article
Published: 31 January 2019 in Sustainability
Reads 0
Downloads 0

“Land finance” refers to the key fiscal strategy in which local governments in China generate revenue through land grant premiums and land tax revenues. A burgeoning body of literature has focused on the driving factors of China’s land finance from different aspects including fiscal decentralization, revenue decentralization, competition among local governments, land marketization, infrastructure development, and economic development. However, little research has provided a comprehensive perspective integrating social, economic and institutional aspects to investigate the driving forces of these unique and profound issues in China. This study aims to investigate the driving factors and working mechanism of land finance. A theoretical and empirical model was proposed using soft budget constraint theory and least squares structural equation modeling (PLS-SEM). The panel data of 35 Chinese major cities were assessed between 2006 and 2015. The empirical results contend the following: (1) the land transfer and fiscal systems provide the key impetus for land financing because the land transfer system forms a stable modality, and the fiscal system is an important incentive for land financing; (2) the effects of the economic development and political system are insignificant; and (3) the political and land systems significantly influence economic development. Our contributions focus on two aspects. Firstly, a comprehensive framework of factors germane to land finance is constructed. Secondly, a new research methodology for land use study is proposed. To the best of our knowledge, the current study is the first to employ the PLS-SEM method to delineate and verify the influence paths between multiple driving factors and land finance in different cities. Hence, research reliability can be improved.

ACS Style

Xinhua Zhu; Yigang Wei; Yani Lai; Yan Li; Sujuan Zhong; Chun Dai. Empirical Analysis of the Driving Factors of China’s ‘Land Finance’ Mechanism Using Soft Budget Constraint Theory and the PLS-SEM Model. Sustainability 2019, 11, 742 .

AMA Style

Xinhua Zhu, Yigang Wei, Yani Lai, Yan Li, Sujuan Zhong, Chun Dai. Empirical Analysis of the Driving Factors of China’s ‘Land Finance’ Mechanism Using Soft Budget Constraint Theory and the PLS-SEM Model. Sustainability. 2019; 11 (3):742.

Chicago/Turabian Style

Xinhua Zhu; Yigang Wei; Yani Lai; Yan Li; Sujuan Zhong; Chun Dai. 2019. "Empirical Analysis of the Driving Factors of China’s ‘Land Finance’ Mechanism Using Soft Budget Constraint Theory and the PLS-SEM Model." Sustainability 11, no. 3: 742.

Journal article
Published: 01 January 2019 in International Journal of Hospitality Management
Reads 0
Downloads 0

High employee turnover has been a concern of the hotel practitioners and academics. Previous research more focused on reducing employee turnover by improving economic incentives. However, psychological incentives are getting more concerned now. This study aims to analyze the psychological mechanism affecting the attitudinal and behavioral loyalty of employees in hotel sector. This study uses organizational commitment theory and regards the hotel employee as an internal customer to construct and verify a conceptual framework. Several important findings are observed. First, affective, normative, and continuance commitment have apparent and varying effects on the attitudinal and behavioral loyalty of employees. Second, the attitudinal loyalty of employees significantly promotes behavioral loyalty. Third, employee trust and satisfaction in hotel sector are vital antecedents of the three dimensions of organizational commitment. These findings have important implications for managing hotel employee turnover and improving the psychological achievements of employees to consequently enhance attitudinal and behavioral loyalty.

ACS Style

Tang Yao; Qi Qiu; Yigang Wei. Retaining hotel employees as internal customers: Effect of organizational commitment on attitudinal and behavioral loyalty of employees. International Journal of Hospitality Management 2019, 76, 1 -8.

AMA Style

Tang Yao, Qi Qiu, Yigang Wei. Retaining hotel employees as internal customers: Effect of organizational commitment on attitudinal and behavioral loyalty of employees. International Journal of Hospitality Management. 2019; 76 ():1-8.

Chicago/Turabian Style

Tang Yao; Qi Qiu; Yigang Wei. 2019. "Retaining hotel employees as internal customers: Effect of organizational commitment on attitudinal and behavioral loyalty of employees." International Journal of Hospitality Management 76, no. : 1-8.

Journal article
Published: 08 December 2018 in Journal of Cleaner Production
Reads 0
Downloads 0

In China, carbon emission mitigation is a considerable challenge due to the massive quantity of CO2 emissions, which has been relentlessly growing for a long time. In this study, the Driving-Pressure-State-Impact-Response (DPSIR) method is used to identify the influential factors of China’s carbon emissions. This empirical research, which is based on provincial panel data and the structural equation model through the partial least squares approach, reveals the path relationships between carbon emissions and their influential factors. The estimation comprehensively covers 35 indicators during the period of 1996 to 2015. Empirical results show that the driving factor, pressure, state and response on the national level significantly impact carbon emissions. From a regional perspective, driving factor has significant impact in the northeast, northwest, southwest and south of China, and pressure factor exerts effect in the northeast, north, east, northwest, southwest and central south of China. The state factor plays a role in the southwest, central and south. As for response factor, the northeast, east, northwest and southwest are affected regions. This study provides a comprehensive and accurate indicator estimation framework for carbon emission. The identified influential factors can guide Chinese governments at all levels in scientifically formulating policies to effectively reduce carbon emission.

ACS Style

Yigang Wei; Xinhua Zhu; Yan Li; Tang Yao; Yuan Tao. Influential factors of national and regional CO2 emission in China based on combined model of DPSIR and PLS-SEM. Journal of Cleaner Production 2018, 212, 698 -712.

AMA Style

Yigang Wei, Xinhua Zhu, Yan Li, Tang Yao, Yuan Tao. Influential factors of national and regional CO2 emission in China based on combined model of DPSIR and PLS-SEM. Journal of Cleaner Production. 2018; 212 ():698-712.

Chicago/Turabian Style

Yigang Wei; Xinhua Zhu; Yan Li; Tang Yao; Yuan Tao. 2018. "Influential factors of national and regional CO2 emission in China based on combined model of DPSIR and PLS-SEM." Journal of Cleaner Production 212, no. : 698-712.