The Study of Typology of Competitive Actions in Digital Environment: An Empirical Investigation of Mobile Instant Messaging

The highly competitive and increasingly transparent characteristics of the digital environment have led inter-firm rivalry more frequently. Competitive actions and competitor’s responses together determine firms’ value creation. The key to obtain competitive advantages is to stop or delay competitor’s response. Therefore, our research question is which type of actions is the most effective in digital environment. Grounded in the framework of explorative/exploitative in the organizational learning literature, we organize competitive actions from two dimensions: resources based (strategic versus tactical) and innovation based (innovative versus efficient). This paper studies the competitive actions in mobile instant messaging industry and use structured content analysis to capture firms’ competitive actions. Finally, 113 matched competitive actions and responses were collected. Then, we compare the effects of different types of competitive actions from three aspects, that is the number of responses, response time and response quality. The results show that innovative-strategic action is the most effective action in digital environment. Our action-level study of MIM (mobile instant messaging) promotes better understanding of how firms interact with each other in digital environment. Moreover, the new typology of competitive action helps us identify competitive actions in digital environment more precisely and help managers to better understand industry dynamics thus developing appropriate strategies to compete in the industry

Estimates of daily ground-level NO2 concentrations in China based on big data and machine learning approaches

Nitrogen dioxide (NO2) is one of the most important atmospheric pollutants. However, current ground-level NO2 concentration data are lack of either high-resolution coverage or full coverage national wide, due to the poor quality of source data and the computing power of the models. To our knowledge, this study is the first to estimate the ground-level NO2 concentration in China with national coverage as well as relatively high spatiotemporal resolution (0.25 degree; daily intervals) over the newest past 6 years (2013-2018). We advanced a Random Forest model integrated K-means (RF-K) for the estimates with multi-source parameters. Besides meteorological parameters, satellite retrievals parameters, we also, for the first time, introduce socio-economic parameters to assess the impact by human activities. The results show that: (1) the RF-K model we developed shows better prediction performance than other models, with cross-validation R2 = 0.64 (MAPE = 34.78%). (2) The annual average concentration of NO2 in China showed a weak increasing trend . While in the economic zones such as Beijing-Tianjin-Hebei region, Yangtze River Delta, and Pearl River Delta, the NO2 concentration there even decreased or remained unchanged, especially in spring. Our dataset has verified that pollutant controlling targets have been achieved in these areas. With mapping daily nationwide ground-level NO2 concentrations, this study provides timely data with high quality for air quality management for China. We provide a universal model framework to quickly generate a timely national atmospheric pollutants concentration map with a high spatial-temporal resolution, based on improved machine learning methods

Analysis on the Influence of Fault Protection Coal Pillar Size on Rockburst

Compared with other types of rockburst, fault rockburst releases the most energy and brings the hugest damage to the stope. Reasonable fault protection coal pillar can effectively prevent and control the occurrence of fault rockburst. Reasonable fault protection coal pillar (FPCP) can prevent and control the occurrence of fault rockburst effectively. Based on the engineering background of No. 7 mining area in a coal mine, this paper analyzes the reasonable coal pillar size on both sides of normal fault. Combined with the geological conditions in site, through the mechanical analysis of coal pillar stability, it is calculated that the critical FPCP size is 27.9 m for the working face in the upper wall and 39.0 m for the working face in the footwall. Through numerical simulation analysis, it is found that with the critical size of FPCP, the stress concentration coefficient in front of the upper wall working faces and footwall working faces is about 1.59. When the size of FPCP is smaller than the critical one, the difference of stress concentration coefficient between the two working faces (upper wall working face and footwall working face) is large, and the difference becomes larger and larger with the decrease of coal pillar size. When the size of FPCP is larger than the critical one, the difference of stress concentration coefficient between the two working faces (upper wall working face and footwall working face) is small, and the stress concentration coefficient of the two faces tends to be equal with the increase of coal pillar size. The rationality of coal pillar size is verified by field application, which provides a basis for the selection of FPCP in subsequent mining under similar conditions

Realizing Superior Electrochemical Performance of Asymmetric Capacitors through Tailoring Electrode Architectures

ZnCo2O4 as an electrode material for supercapacitors has been extensively investigated owing to its unique structural characteristics and high capacitance. However, the conductivity still cannot reach the level of the industrialization. In order to solve this problem, it is an efficient strategy to develop composed electrode materials. Here, we prepare ZnCo2O4-based electrode materials through a facile hydrothermal route. The ZnCo2O4/CoMoO4 sample possesses a specific capacitance of 903 C at 1 A g(-1). An assembled asymmetric capacitor presents an energy density of 135.6 Wh kg(-1) at 2704.1 W kg(-1) and capacity of 95.1% after 8000 cycles

Nanohybridization of Ni-Co-S Nanosheets with ZnCo2O4 Nanowires as Supercapacitor Electrodes with Long Cycling Stabilities

Hybrid structured electrode materials for supercapacitors have attracted enormous interest. However, the rational design of electrode materials with high conductivity and energy density is still a challenge for energy storage devices. Herein, ZnCo2O4@Ni-Co-S composites are prepared through a simple electrochemical process. Due to the high structural stability, the products show excellent specific capacitance. Furthermore, the device delivers an energy density of 53.1 Wh kg(-1) at a power density of 3375 W kg(-1) and demonstrates excellent cycle stability

Enhanced electrochemical performances of ZnCo2O4@CoMoO(4 )core-shell structures with long cycling stabilities

Developing electrode materials with high specific capacitance and excellent stability for energy storage is necessary to solve energy shortage issues. In this work, we prepareZnCo(2)O(4)@CoMoO4 core - shell structures on nickel foam by a simple hydrothermal approach. The as-synthesized products show excellent electrochemical performances. It reveals that the secondary growth of CoMoO4 nanosheets induces many active sites and facilitates rapid ion and electron transmission. In addition, the as-assembled device delivers high energy density, indicating that the as-obtained samples are excellent candidates for future energy storage applications

Fabricating 2D Host −Guest Kagomé Packing for C₂‑Symmetric Aromatic Carboxylic Acids with Different Spatial Configuration: Different Ways, Same Destination

The self-assembly of two kinds of C2-symmetric aromatic carboxylic acids named 4,4′,4″,4‴-(1,4-phenylenebis(azanetriyl))tetrabenzoic acid (H4PTA) and 5′,5″-bis(4-carboxyphenyl)-[1,1′:3′,1″:3″,1‴-quaterphenyl]-4,4‴-dicarboxylic acid (H4QDA) and the coadsorption with coronene (COR) molecules at different solution concentrations were investigated at the heptanoic acid (HA)/highly oriented pyrolytic graphite (HOPG) interface by scanning tunneling microscopy (STM). H4PTA molecules with nonplanar conformation self-assembled into a highly ordered rhombus structure at variational concentrations and subsequently could be regulated into a Kagomé network by the coadsorption of COR molecules. H4QDA molecules with planar conformation self-assembled into two various nanostructures (rhombus structure and Kagomé network) coexisting on the HOPG surface at different concentrations. The Kagomé architecture of H4QDA could act as a rigid host template to trap the COR molecules. Meanwhile, COR exhibited preferential adsorption in the porous template: COR only entered the hexagonal cavities at low concentrations and filled in all hexagonal and triangular cavities at high concentrations. Density functional theory (DFT) calculations and molecular dynamics (MD) simulations showed that the host–guest co-assembled structures were more thermodynamically and kinetically stable. The formation of different self-assembly and co-assembly processes of two molecules could be attributed to the dissimilar molecular conformation. Our work is of significance to further explore the formation mechanism of two-dimensional (2D) porous arrangements and provides an ideal way to regulate the adsorption of porous templates

Estimates of daily ground-level NO2 concentrations in China based on Random Forest model integrated K-means

Nitrogen dioxide (NO2) is one of the most important atmospheric pollutants and the precursors of acid rain, tropospheric ozone, and atmospheric aerosols. However, due to the poor quality of source data and the computing power of the models, current ground-level NO2 concentration data lack either high-resolution coverage or full nation-wide coverage. This study estimates the ground-level NO2 concentration in China with national coverage at relatively high spatiotemporal resolution (0.25°; daily intervals) over the newest past 6 years (2013–2018). We developed an advanced model, named Random Forest model integrated K-means (RF-K), for the estimates with multi-source parameters. Besides meteorological parameters, satellite retrievals parameters, and anthropogenic emission inventories parameters, we also innovatively introduce socioeconomic parameters to assess the impact of human activities. Our results show that: (1) the RF-K model developed by us shows better prediction performance than others. (2) the annual average NO2 concentration of China showed a weak declining trend (-0.013±0.217 μgm−3yr−1) from 2013 to 2018, indicating that pollutant controlling targets had been achieved in China overall. By mapping daily nationwide ground-level NO2 concentrations, this study provides high-quality timely, and detailed data for air quality management and epidemiological analyses for China. The RF-K model can be used easily for other pollutants (e.g. SO2 and O3) considering that their ground-level concentrations can be estimated depending on the similar emitting sources and influence factors, and our model's input data sources also cover information on other pollutants