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

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

Deriving Exclusion Maps from C-Band Sar Time-Series: An Additional Information Layer for Sar-Based Flood Extent Mapping

Change detection has been widely used in many flood-mapping algorithms using pairs of Synthetic Aperture Radar (SAR) intensity images as floodwater often leads to a substantial decrease of backscatter. However, limitations still exist in many areas, such as shadow, layover, urban areas and densely vegetated areas, where the SAR backscatter is not sufficiently impacted by floodwater-related surface changes. This study focuses on these so-called exclusion areas, i.e. areas where SAR does not allow detecting water based on change detection. Our approach considers both pixel-based time series analyses and object-based spatial analyses using 20m Sentinel-1 Interferometric Wide Swath data, including 922 Sentinel-1 tiles covering the River Severn basin (UK) and the Lake Maggiore area (Italy). The results show that our exclusion map presents a good agreement (∼63%) with reference data derived from different data sources and indicate that it may complement SAR-derived flood extent maps. Allowing to accurately identify potential misclassifications in flood extent mapping, our exclusion map provides valuable information for flood management and, in particular, flood forecasting and prediction.3954006Luxembourg National Research Fund (FNR