Crowdsourcing has risen as a prominent way to outsource work to people reachable online. A critical predictor for the success of crowdsourcing campaigns on the market depends on the crowdsourcer’s ...ability to signal credibility towards the potential workers. Therefore, this study investigates which indicators of trustworthiness on crowdsourcers' profiles (gamification-based, transparency, and experience) and level of monetary compensation predict crowdsourcee participation and consequent crowdsourcing campaign success. This study analyzes data of 101 crowdsourcing tasks from a popular Chinese crowdsourcing platform “Xiao Yu’er”. We employ the methods of Structural Equation Modelling and fuzzy set Qualitative Comparative Analysis to find out that gamification-based indicators of trustworthiness were positively associated with task popularity and further successfulness of the crowdsourcing task. Furthermore, in addition to profile credibility based on gamification-based indicators being sufficient, combinations of money with transparency and money with experience can substitute lack of other indicators as way to signal sufficient credibility.
This paper examines the results of a global Korn Ferry survey that assessed pay transparency-related market practices. Despite increased attention and pressure from internal and external ...stakeholders, organizations are still in the early stages of implementing pay transparency strategies. Organizations plan to overhaul their reward communication strategies, with manager training and employee education as the primary focus areas. Managers play a critical role as the first line of communication with employees on their team, and organizations recognize that a significant upskilling effort will be needed to enable them to communicate effectively about pay decisions and avoid unintended consequences. The authors provide considerations for organizations moving toward more transparent pay practices, including clarifying a pay transparency strategy, assessing their current practices, improving compensation programs, aligning their leaders and developing effective rewards communications strategies.
•CSR transparency consists of communication regimes reflected by social processes.•Employees are conducive for the formation of CSR transparency.•Employee autonomy may prompt more radical and genuine ...behavior of CSR transparency.•Employees can act as gatekeepers in the disclosure of information.•Employees function as advocates for civil society – from a bottom-up position.
Corporate Social Responsibility (CSR) transparency has predominantly been treated as an organizational outcome in previous literature. Drawing on rich qualitative data, we find that CSR transparency can emerge through sensemaking processes where employees are instrumental in exercising moral judgements, engaging with stakeholders, and creating shared narratives. The study contributes to our understanding of CSR transparency by showing that the phenomenon is reflected by social processes and should not be narrowly conceptualized as an outcome of information disclosure at the corporate level. The study also provides fine-grained details about the cognitive and organizational mechanisms at play in the shaping of CSR transparency. Specifically, we introduce a bottom-up model which explains how reserved and non-reserved approaches of CSR transparency are developed.
In this work, we report numerical research concerning a planar electromagnetically induced transparency (EIT) terahertz metamaterial capable of exhibiting refractive index sensing with high ...sensitivity. The unit cell of the proposed EIT metamaterial is consisted by metal cut wires with staggered H-shaped arrangement, and can display a sharply narrow transmission transparency peak at 2.653 THz with high quality-factor (Q-factor) valued 48.3. Through analysis of the extracted surface current distributions on metallic structures, it is confirmed that the EIT-like resonance results from the destructive interference of the electric quadrupole excited by the strong radiation of electric dipole. Furthermore, the EIT-like effect shows highly sensitive response to the refractive index of the covered layer. When it covered by 3μm-thickness analyte layer, the EIT metamaterial can yield a sensitivity of 0.2695 THz/refractive index unit (RIU) and a figure of merit (FOM) of 5.39. Meanwhile, it is also found that the sensitivity S is inversely proportional to the dielectric constant of the substrate material, and effective sensing capability maintains when the coverage thickness within 15μm. The proposed EIT metamaterial design provides great potential application for refractive index sensing performance.
The convergence of new EO data flows, new methodological developments and cloud computing infrastructure calls for a paradigm shift in operational agriculture monitoring. The Copernicus Sentinel-2 ...mission providing a systematic 5-day revisit cycle and free data access opens a completely new avenue for near real-time crop specific monitoring at parcel level over large countries. This research investigated the feasibility to propose methods and to develop an open source system able to generate, at national scale, cloud-free composites, dynamic cropland masks, crop type maps and vegetation status indicators suitable for most cropping systems. The so-called Sen2-Agri system automatically ingests and processes Sentinel-2 and Landsat 8 time series in a seamless way to derive these four products, thanks to streamlined processes based on machine learning algorithms and quality controlled in situ data. It embeds a set of key principles proposed to address the new challenges arising from countrywide 10 m resolution agriculture monitoring. The full-scale demonstration of this system for three entire countries (Ukraine, Mali, South Africa) and five local sites distributed across the world was a major challenge met successfully despite the availability of only one Sentinel-2 satellite in orbit. In situ data were collected for calibration and validation in a timely manner allowing the production of the four Sen2-Agri products over all the demonstration sites. The independent validation of the monthly cropland masks provided for most sites overall accuracy values higher than 90%, and already higher than 80% as early as the mid-season. The crop type maps depicting the 5 main crops for the considered study sites were also successfully validated: overall accuracy values higher than 80% and F1 Scores of the different crop type classes were most often higher than 0.65. These respective results pave the way for countrywide crop specific monitoring system at parcel level bridging the gap between parcel visits and national scale assessment. These full-scale demonstration results clearly highlight the operational agriculture monitoring capacity of the Sen2-Agri system to exploit in near real-time the observation acquired by the Sentinel-2 mission over very large areas. Scaling this open source system on cloud computing infrastructure becomes instrumental to support market transparency while building national monitoring capacity as requested by the AMIS and GEOGLAM G-20 initiatives.
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•First ever national crop mapping at 10 m for Mali, Ukraine and South-Africa•Near real time agriculture monitoring at parcel level made operational nationwide•Demonstration across the world of multi-sensor EO exploitation for crop monitoring•Sentinel-2 time series mapping crop type at 10 m resolution along the growing season•Sen2-Agri: an innovative system to monitor crops in any country around the globe
This article reviews recent advances in missing data research using graphical models to represent multivariate dependencies. We first examine the limitations of traditional frameworks from three ...different perspectives: transparency, estimability, and testability. We then show how procedures based on graphical models can overcome these limitations and provide meaningful performance guarantees even when data are missing not at random (MNAR). In particular, we identify conditions that guarantee consistent estimation in broad categories of missing data problems, and derive procedures for implementing this estimation. Finally, we derive testable implications for missing data models in both missing at random and MNAR categories.
We assess evidence from theoretical-modelling, empirical and experimental studies on how interactions between instruments of climate policy affect overall emissions reduction. Such interactions take ...the form of negative, zero or positive synergistic effects. The considered instruments comprise performance and technical standards, carbon pricing, adoption subsidies, innovation support, and information provision. Based on the findings, we formulate climate-policy packages that avoid negative and employ positive synergies, and compare their strengths and weaknesses on other criteria. We note that the international context of climate policy has been neglected in assessments of policy mixes, and argue that transparency and harmonization of national policies may be key to a politically feasible path to meet global emission targets. This suggests limiting the complexity of climate-policy packages.
Key policy insights
Combining technical standards or targets, such as renewable-energy quota, or adoption subsidies with a carbon market can produce negative synergy, up to the point of adding no emissions reduction beyond the cap. For maximum emissions reduction, renewable energy policy should be combined with carbon taxation and target expensive reduction options not triggered by the tax.
Evidence regarding synergy of information provision with pricing is mixed, indicating a tendency for complementary roles (zero synergy). Positive synergy is documented only for cases where information provision improves effectiveness of price instruments, e.g. by stimulating social imitation of low-carbon choices.
We conclude that the most promising packages are combining innovation support and information provision with either a carbon tax and adoption subsidy, or with a carbon market. We further argue that the latter could have stronger potential to harmonize international policy, which would allow to strengthen mitigation policy over time.
Imaging spectrometry of non-oceanic aquatic ecosystems has been in development since the late 1980s when the first airborne hyperspectral sensors were deployed over lakes. Most water quality ...management applications were, however, developed using multispectral mid-spatial resolution satellites or coarse spatial resolution ocean colour satellites till now. This situation is about to change with a suite of upcoming imaging spectrometers being deployed from experimental satellites or from the International Space Station. We review the science of developing applications for inland and coastal aquatic ecosystems that often are a mixture of optically shallow and optically deep waters, with gradients of clear to turbid and oligotrophic to hypertrophic productive waters and with varying bottom visibility with and without macrophytes, macro-algae, benthic micro-algae or corals. As the spaceborne, airborne and in situ optical sensors become increasingly available and appropriate for aquatic ecosystem detection, monitoring and assessment, the science-based applications will need to be further developed to an operational level. The Earth Observation-derived information products will range from more accurate estimates of turbidity and transparency measures, chlorophyll, suspended matter and coloured dissolved organic matter concentration, to more sophisticated products such as particle size distributions, phytoplankton functional types or distinguishing sources of suspended and coloured dissolved matter, estimating water depth and mapping types of heterogeneous substrates. We provide an overview of past science, current state of the art and future directions so that early career scientists as well as aquatic ecosystem managers and associated industry groups may be prepared for the imminent deluge of imaging spectrometry data.
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