Can innovation really bring economic growth?:The role of social filter in China

This study explores the relationship between R&D investment and economic growth in China, using a newly collected panel data set. Specifically, we investigate how social filters are connected to R&D output. Instead of linking R&D investment directly to economic performance, we adopt a two-step strategy which identifies the impact R&D investment on R&D output, and then study the causal links between R&D output and economic development. Our results suggest that the relationship between R&D input, R&D output and economic growth diverges by different region and sectors. Most of positive associations stem from non-peripheral regions and non-state owned sectors. Social filters are also more effective under these circumstances. These results reveal the complexity of relationships between R&D efforts and economic performance and point to the important role of social filters in innovation and growth

Queen Bees:How is female managers' happiness determined?

This paper aims to study the determinants of subjective happiness among working females with a focus on female managers. Drawn on a large social survey data set (N=10470) in China, this paper constructs gender development index at sub-national levels to study how institutional settings are related to female managers’ happiness. We find that female managers report higher levels of happiness than non-managerial employees. However, the promoting effect is contingent on individual characteristics and social-economic settings. The full sample regression suggests that female managers behaving in a masculine way generally report a high level of happiness. Meanwhile, female managers who refuse to support gender equality report low happiness levels. Sub-sample analysis reveals that these causalities are conditioned on regional culture. Masculine behavior and gender role orientation significantly predict subjective happiness only in gender-egalitarian regions. This study is one of the first to consider both internal (individual traits) and external (social-economic environment) factors when investigating how female managers’ happiness is impacted. Also, this study challenges the traditional wisdom on the relationship between female managers’ job satisfaction and work-home conflict. This study extends the literature by investigating the impacts of female managers’ masculine behavior on their happiness. This study is useful for promoting female managers' leadership effectiveness and happiness

Reducing the Resource Acquisition Costs for Returnee Entrepreneurs: Role of Chinese National Science Parks

Purpose: The purpose of this paper is to empirically explore the mechanisms through which Chinese National Science Parks' (NSPs) services facilitate returnee entrepreneurs' (REs) acquisition of resources for their new ventures. Resource acquisition is crucial for new ventures, but it inevitably leads to significant costs increase. Although the NSPs offer various services to REs to reduce these costs, they still struggle to find the right mix of services. Design/methodology/approach: From the transaction cost's perspective, an exploratory multiple-case study was conducted with data collected from six NSPs in China. Findings: The results reveal that four types of NSP services (mentoring and training, social event, promotion of REs and accreditation of resource holders (RHs)) have both individual and joint effects on reducing REs' resource acquisition costs. Specifically, the “accreditation of RHs” service directly helps REs reduce search costs. The combination of “accreditation of RHs”, “promotion of REs” and “social event” services help REs and RHs to establish guanxi. Further, guanxi, working along with the “mentoring and training” service, helps REs to reduce contracting, monitoring and enforcement costs. Originality/value: This study is among the first to explore the matching mechanisms between science parks’ services and entrepreneurs' cost reduction. This helps reconcile the inconsistent findings on science parks' effect by explaining why some NSPs are able to provide strong support to REs while others are less successful. In addition, the findings are useful for NSPs to develop the right mix of tailored services for REs. Finally, REs will find this study useful to evaluate which NSP is a more suitable location for their new ventures

Toward Global Soil Moisture Monitoring With Sentinel-1: Harnessing Assets and Overcoming Obstacles

The final authenticated publication is available at https://doi.org/10.1109/TGRS.2018.2858004.Soil moisture is a key environmental variable, important to, e.g., farmers, meteorologists, and disaster management units. Here, we present a method to retrieve surface soil moisture (SSM) from the Sentinel-1 (S-1) satellites, which carry C-band Synthetic Aperture Radar (CSAR) sensors that provide the richest freely available SAR data source so far, unprecedented in accuracy and coverage. Our SSM retrieval method, adapting well-established change detection algorithms, builds the first globally deployable soil moisture observation data set with 1-km resolution. This paper provides an algorithm formulation to be operated in data cube architectures and high-performance computing environments. It includes the novel dynamic Gaussian upscaling method for spatial upscaling of SAR imagery, harnessing its field-scale information and successfully mitigating effects from the SAR's high signal complexity. Also, a new regression-based approach for estimating the radar slope is defined, coping with Sentinel-1's inhomogeneity in spatial coverage. We employ the S-1 SSM algorithm on a 3-year S-1 data cube over Italy, obtaining a consistent set of model parameters and product masks, unperturbed by coverage discontinuities. An evaluation of therefrom generated S-1 SSM data, involving a 1-km soil water balance model over Umbria, yields high agreement over plains and agricultural areas, with low agreement over forests and strong topography. While positive biases during the growing season are detected, the excellent capability to capture small-scale soil moisture changes as from rainfall or irrigation is evident. The S-1 SSM is currently in preparation toward operational product dissemination in the Copernicus Global Land Service.5205392

GFM Product User Manual

This Product User Manual (PUM) is the reference document for all end-users and stakeholders of the new Global Food Monitoring (GFM) product of the Copernicus Emergency Management Service (CEMS). The PUM provides all of the basic information to enable the proper and effective use of the GFM product and associated data output layers. This manual includes a description of the functions and capabilities of the GFM product, its applications and alternative modes of operation, and step-by-step guidance on the procedures for accessing and using the GFM product

Mapping Rice Seasonality in the Mekong Delta with Multi-Year Envisat ASAR WSM Data

Rice is the most important food crop in Asia, and the timely mapping and monitoring of paddy rice fields subsequently emerged as an important task in the context of food security and modelling of greenhouse gas emissions. Rice growth has a distinct influence on Synthetic Aperture Radar (SAR) backscatter images, and time-series analysis of C-band images has been successfully employed to map rice fields. The poor data availability on regional scales is a major drawback of this method. We devised an approach to classify paddy rice with the use of all available Envisat ASAR WSM (Advanced Synthetic Aperture Radar Wide Swath Mode) data for our study area, the Mekong Delta in Vietnam. We used regression-based incidence angle normalization and temporal averaging to combine acquisitions from multiple tracks and years. A crop phenology-based classifier has been applied to this time series to detect single-, double- and triple-cropped rice areas (one to three harvests per year), as well as dates and lengths of growing seasons. Our classification has an overall accuracy of 85.3% and a kappa coefficient of 0.74 compared to a reference dataset and correlates highly with official rice area statistics at the provincial level (R² of 0.98). SAR-based time-series analysis allows accurate mapping and monitoring of rice areas even under adverse atmospheric conditions

Understanding consumers’ social media engagement behaviour:An examination of the moderation effect of social media context

Social media has become a norm for retailers seeking to engage actively with consumers. There is growing evidence that some consumers choose not to engage with social media marketing content and that the depth of consumer engagement varies across different social media. However, there is a lack of empirical research on contextual factors that may contribute to such differences. Moreover, the variation of social media engagement behaviours, namely, consumption, contribution, and creation is underexplored. Hence, we seek to understand the various levels of engagement behaviours that are influenced by key social media contextual factors, namely media richness and content trustworthiness. We analyse 721 survey responses using PLS-SEM. Results reveal significant effects of media context on engagement behaviours. This research contributes to the growing body of literature on social media engagement, in particular, understanding the impact of social media contextual factors on various engagement behaviours

A Comparison of Terrain Indices toward Their Ability in Assisting Surface Water Mapping from Sentinel-1 Data

The Sentinel-1 mission provides frequent coverage of global land areas and is hence able to monitor surface water dynamics at a fine spatial resolution better than any other Synthetic Aperture Radar (SAR) mission before. However, SAR data acquired by Sentinel-1 also suffer from terrain effects when being used for mapping surface water, just as other SAR data do. Terrain indices derived from Digital Elevation Models (DEMs) are easy but effective approaches to reduce this kind of interference, considering the close relationship between surface water movement and topography. This study compares two popular terrain indices, namely the Multi-resolution Valley Bottom Flatness (MrVBF) and the Height Above Nearest Drainage (HAND), toward their performance on assisting surface water mapping using Sentinel-1 SAR data. Four study sites with different terrain characteristics were selected to cover a very wide range of topographic conditions. For two of these sites that are floodplain dominated, both normal and flooded scenarios were examined. MrVBF and HAND values for the whole study areas, as well as statistics of these values within water areas were compared. The sensitivity of applying different thresholds for MrVBF and HAND to mask out terrain effect was investigated by adopting quantity disagreement and allocation disagreement as the accuracy indicators. It was found that both indices help improve water mapping, reducing the total disagreement by as much as 1.6%. The HAND index performs slightly better in most of the study cases, with less sensitivity to thresholding. MrVBF classifies low-lying areas with more details, which sometimes makes it more effective in eliminating false water bodies in rugged terrain. It is therefore recommended to use HAND for large scale or global scale water mapping. However, for water detection in complex terrain areas, MrVBF also performs very well

Deriving exclusion maps from C-band SAR time-series in support of floodwater mapping

Synthetic Aperture Radar (SAR) intensity is used as an input to many flood-mapping algorithms. The appearance of floodwater tends to cause a substantial decrease of backscatter intensity over scarcely vegetated terrain. However, limitations exist in areas where the SAR backscatter is not sufficiently sensitive to surface changes, e.g. shadow areas due to topography or obstacles on the ground, densely forested areas, sand, etc. Thus, we argue that it is of paramount importance to complement any SAR-based flood extent map with an exclusion map (EX-map) indicating all areas where the presence of water cannot be derived from SAR intensity observations. In this study, we introduce a methodology for generating an EX-map based on the analysis of time-series of SAR backscatter data. In particular, the identification of the EX-map is based on the combined use of three temporal indicators based on backscatter statistics, i.e. temporal median, minimum and standard deviation. As a test case, EX-maps were derived from Sentinel-1 data acquired during the 2014–2019 time period from six representative study sites. Reference maps were generated using a global land cover map, Digital Elevation Model (DEM)-derived shadow/layover masks, global urban footprint (GUF) data and a Sand Exclusion Layer (SEL). The cross-comparison revealed that the EX-map was consistent with reference maps obtained from other data sources.FFG - Österr. Forschungsförderungs- gesellschaft mbH11717Luxembourg National Research Fund (FNR