关键词：
Manufacturing intelligence;High-quality growth;Energy efficient;Total factor productivity;Green total factor productivity
摘要：
Manufacturing intelligence is an important starting point to achieve high-quality economic growth. Based on the non-radial and non-angular DEA-SBM model, combined with the Malmquist index method, this paper calculates the total factor productivity and green total factor productivity of 286 prefecture-level cities in China, which are used as the indicators of high-quality economic growth. At the same time, the proxy variables of manufacturing intelligence are further constructed, and the impact of intelligent manufacturing on high-quality and energy-efficient economic growth is empirically analyzed. It is found that intelligent manufacturing significantly promotes China’s high-quality and energy-efficient economic growth. Productivity is further decomposed into specific indicators such as technical efficiency, technological progress, pure technical efficiency, pure technical progress, scale efficiency and scale technology, and the mechanism of intelligent manufacturing is analyzed from multiple angles. The research finds that manufacturing intelligence improves the total factor productivity through technological progress effect. Green total factor productivity has been improved through the improvement of technical efficiency effect, but the development of intelligence has brought new challenges to China's labor market. In order to further develop the potential of intelligence, it is necessary to further improve the enterprises’ scale efficiency, while increasing the research and development of energy technology.
作者机构：
[Xu, Huimin] Wuhan Polytech Univ, Sch Econ, Wuhan 430048, Peoples R China.;[Xu, Huimin; Hu, Shougeng] China Univ Geosci, Sch Publ Adm, Wuhan 430074, Peoples R China.;[Li, Xi] Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & Re, Wuhan 430079, Peoples R China.
通讯机构：
[Huimin Xu] S;School of Economics, Wuhan Polytechnic University, Wuhan 430048, China<&wdkj&>School of Public Administration, China University of Geosciences, Wuhan 430074, China<&wdkj&>Author to whom correspondence should be addressed.
关键词：
Yangtze River Economic Belt;urban development;urban area;night-time light;VIIRS
摘要：
Research on urban development patterns and urban sprawl in the Yangtze River Economic Belt (YREB) has received wide attention. However, existing research has always made use of statistical data, which are not often available. Considering the high availability of satellite data, this study attempts to combine two satellite-acquired indexes, including urban area and night-time light, to evaluate the urban development of the YREB during 2012–2019. The methods included using growth index, rank-size law, and the Markov transition matrix, as well as constructing urban night-time light density and unbalanced index of night-time light, derived from the Gini Index. Some important patterns were revealed. Firstly, the three reaches (Upper Reaches, Middle Reaches, and Lower Reaches) in the YREB have all shown rapid growth in urban area and night-time light, and they all have increased in urban density. Secondly, from the perspective of regional disparity, the Upper Reaches have the highest growth rate of the urban area, while the Middle Reaches have the highest growth rate of night-time light; and the Upper Reaches have more urban sprawl, while the Middle Reaches have shown more compact growth. Thirdly, higher urban density is related to more balanced development across cities. Our study suggests new knowledge can be obtained by combining the two indexes for understanding urban development in the YREB.
摘要：
With the cyclical development of emerging technologies, in reality, the evolution dynamics of their innovation networks will inevitably show obvious time attributes. Numerous network analyses of real complex systems usually focus on static networks; however, it is difficult to describe that most real networks undergo topological evolutions over time. Temporal networks, which incorporate time attributes into traditional static network models, can more accurately depict the temporal features of network evolution. Here, we introduced the time attribute of the life cycle of emerging technology into the evolution dynamics of its innovation network, constructed an emerging technology temporal innovation network from a temporal network perspective, and established its evolution model in combination with the life cycle and key attributes of emerging technology. Based on this model, we took 5G technology as an example to conduct network evolution simulation, verified the rationality of the above model building, and analyzed the cyclical evolution dynamics of this network in various topological structures. The results show that the life cycle of emerging technology, as well as multiple knowledge attributes based on the key attributes of emerging technology, are important factors that affect network evolution by acting on node behaviors. Within this study, we provide a more realistic framework to describe the internal mechanism of the cyclical evolution of emerging technology innovation network, which can extend the research on innovation network evolution from the single topological dynamics to the topological–temporal dynamics containing time attributes and enrich the research dimensions of innovation network evolution from the perspective of temporal evolution.
摘要：
This research analyses the relative efficacy of gold price, financial market, and stock exchange hedging against sectoral and industry-level global stock market returns. Incorporating Gold into equity-based asset allocation techniques and assessing the stock market and financial sector during the COVID-19 epidemic is one way to diversify your portfolio and reduce risk. After orthogonalizing raw returns concerning a robust collection of relevant universal variables, we conduct our analysis inside a bivariate GARCH(p, q) framework. To further assess ideal portfolio proportions and the efficacy of hedging methods, we expand the volatility spillovers study by calculating the optimal weights for a minimal risk portfolio and determining the hedge ratio. In high-volatility environments, our results show which financial market and stock exchange sectors and industries investors should prioritize to minimize the risk and maximize reward. Use of country-specific macroeconomic variables indices to supplement the worldwide index, (3) separate analysis for the COVID-19 first wave due to the existing argument that the pandemic raises unexpected market events and our early data showing co-movement among the three unpredictability metrics during the pandemic. These findings have important implications for portfolio entrepreneurs and business investors looking to buy international equities.
摘要：
eBay’s feedback rating system is currently widely used. In this study, we examine if eBay’s feedback rating types (+, 0, −) are consistent with the sentiments reflected in the textual comments posted by buyers. Using the datasets collected from eBay, we test the hypotheses associated with the research questions at three levels: individual, group, and total. Overall, the types of feedback ratings are consistent with the sentiments embedded in the textual comments. However, there are some issues with eBay’s current feedback rating system: (1) at the individual level, the correlation coefficient between the ratings and the comments’ sentiments is low at 0.4311 (<0.5). While the three types of ratings are symmetric, like (−1, 0, +1), buyers’ textual comments have asymmetric distributions of sentiments among these three types. The three simple feedback ratings (+, 0, −) are not fully aligned with the sentiments revealed in the textual comments posted by buyers. We propose expanding the current three ratings into five ratings such as (−2, −1, 0, +1, +2), which might help remedy the issue. We contribute to the literature by tapping into this less-studied area vital to improving the online marketplace’s efficiency.
