Cooperatives are special because the members not only own the cooperative, but also patronize it. CEO’s decision has an impact on the overall members’ interests. Understanding how CEOs differ from members regarding their evaluations on cooperative performance and what causes the differences, is valuable for CEOs to best serve the members. This paper evaluates the difference between CEO and member evaluation regarding their cooperatives, and further examines the role of governance in predicting the evaluations and differences in evaluations, based on a set of first-hand data containing Chinese agricultural cooperatives (240 CEOs and 543 members). Cooperative performance is measured by three indicators: member profitability, social influence in the local community, and overall performance. The results show that members have higher scores than CEOs regarding member profitability and overall performance, while CEOs have a higher evaluation regarding social influence. “This is an Accepted Manuscript of an article published by Taylor & Francis in 'The Social Science Journal' on 27 Jan. 2020 available online: https://www.tandfonline.com/doi/abs/10.1016/j.soscij.2019.01.006. LinkedIn: https://www.linkedin.com/in/xiao-peng-20466772/
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Explainable Artificial Intelligence (XAI) aims to provide insights into the inner workings and the outputs of AI systems. Recently, there’s been growing recognition that explainability is inherently human-centric, tied to how people perceive explanations. Despite this, there is no consensus in the research community on whether user evaluation is crucial in XAI, and if so, what exactly needs to be evaluated and how. This systematic literature review addresses this gap by providing a detailed overview of the current state of affairs in human-centered XAI evaluation. We reviewed 73 papers across various domains where XAI was evaluated with users. These studies assessed what makes an explanation “good” from a user’s perspective, i.e., what makes an explanation meaningful to a user of an AI system. We identified 30 components of meaningful explanations that were evaluated in the reviewed papers and categorized them into a taxonomy of human-centered XAI evaluation, based on: (a) the contextualized quality of the explanation, (b) the contribution of the explanation to human-AI interaction, and (c) the contribution of the explanation to human- AI performance. Our analysis also revealed a lack of standardization in the methodologies applied in XAI user studies, with only 19 of the 73 papers applying an evaluation framework used by at least one other study in the sample. These inconsistencies hinder cross-study comparisons and broader insights. Our findings contribute to understanding what makes explanations meaningful to users and how to measure this, guiding the XAI community toward a more unified approach in human-centered explainability.
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During the COVID-19 pandemic, the bidirectional relationship between policy and data reliability has been a challenge for researchers of the local municipal health services. Policy decisions on population specific test locations and selective registration of negative test results led to population differences in data quality. This hampered the calculation of reliable population specific infection rates needed to develop proper data driven public health policy. https://doi.org/10.1007/s12508-023-00377-y
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Coastal nourishments, where sand from offshore is placed near or at the beach, are nowadays a key coastal protection method for narrow beaches and hinterlands worldwide. Recent sea level rise projections and the increasing involvement of multiple stakeholders in adaptation strategies have resulted in a desire for nourishment solutions that fit a larger geographical scale (O 10 km) and a longer time horizon (O decades). Dutch frontrunner pilot experiments such as the Sandmotor and Ameland inlet nourishment, as well as the Hondsbossche Dunes coastal reinforcement project have all been implemented from this perspective, with the specific aim to encompass solutions that fit in a renewed climate-resilient coastal protection strategy. By capitalizing on recent large-scale nourishments, the proposed Coastal landSCAPE project C-SCAPE will employ and advance the newly developed Dynamic Adaptive Policy Pathways (DAPP) approach to construct a sustainable long-term nourishment strategy in the face of an uncertain future, linking climate and landscape scales to benefits for nature and society. Novel long-term sandy solutions will be examined using this pathways method, identifying tipping points that may exist if distinct strategies are being continued. Crucial elements for the construction of adaptive pathways are 1) a clear view on the long-term feasibility of different nourishment alternatives, and 2) solid, science-based quantification methods for integral evaluation of the social, economic, morphological and ecological outcomes of various pathways. As currently both elements are lacking, we propose to erect a Living Lab for Climate Adaptation within the C-SCAPE project. In this Living Lab, specific attention is paid to the socio-economic implications of the nourished landscape, as we examine how morphological and ecological development of the large-scale nourishment strategies and their design choices (e.g. concentrated vs alongshore uniform, subaqueous vs subaerial, geomorphological features like artificial lagoons) translate to social acceptance.
The Netherlands has approximately 220,000 industrial accidents per year (with 60 people who die). That is why every employer is obliged to organize company emergency response (BHV), including emergency response training. Despite this, only one-third of all companies map out their occupational risks via a Risk Inventory & Evaluation (RI&E) and the share of employees with an occupational accident remains high. That is why there is continuous innovation to optimize emergency response training, for example by means of Virtual Reality (VR). VR is not new, but it has evolved and become more affordable. VR offers the possibility to develop safe realistic emergency response simulations where the student has the feeling that they are really there. Despite the increase in VR-BHV training, little research has been done on the effect of VR in ER training and results are contradictory. In addition, there are new technological developments that make it possible to measure viewing behavior in VR using Eye-Tracking. During an emergency response training, Eye-Tracking can be used to measure how an instruction is followed, whether students are distracted and observe important elements (danger and solutions) during the simulation. However, emergency response training with VR and Eye-Tracking (interactions) does not exist. In this project, a prototype is being developed in which Eye-Tracking is incorporated into a VR-BHV training that was developed in 2021, in which emergency situations such as an office fire are simulated (the BHVR application). The prototype will be tested by means of an experiment in order to partly answer the question to what extent and in what way Eye-Tracking in VR offers added value for (RI&E) emergency response training. This project is therefore in line with the mission-driven innovation policy 'The Safety Professional' and helps SMEs that often lack resources and knowledge for research into the effectiveness of innovative technologies in education/training. The project will include a prototype, a production report and research article, and is open to new participants when writing a larger application about the application and effect of VR and Eye-Tracking in emergency response training.
There is increasing interest for the use of Virtual Reality (VR) in the field of sustainable transportation and urban development. Even though much has been said about the opportunities of using VR technology to enhance design and involve stakeholders in the process, implementations of VR technology are still limited. To bridge this gap, the urban intelligence team of NHTV Breda University of Applied Sciences developed CycleSPEX, a Virtual Reality (VR) simulator for cycling. CycleSpex enables researchers, planners and policy makers to shape a variety of scenarios around knowledge- and design questions and test their impact on users experiences and behaviour, in this case (potential) cyclists. The impact of infrastructure enhancements as well as changes in the surrounding built environment can be tested, analysed an evaluated. The main advantage for planners and policy makers is that the VR environment enables them to test scenarios ex-ante in a safe and controlled setting.“The key to a smart, healthy and safe urban environment lies in engaging mobility. Healthy cities are often characterized by high quality facilities for the active modes. But what contributes to a pleasant cycling experience? CycleSPEX helps us to understand the relations between cyclists on the move and (designed) urban environments”
