Sustainability experiments in the agri-food system : uncovering the factors of new governance and collaboration success

In recent years, research, society and industry recognize the need to transform the agri-food system towards sustainability. Within this process, sustainability experiments play a crucial role in transforming the structure, culture and practices. In literature, much attention is given to new business models, even if the transformation of conventional firms toward sustainability may offer opportunities to accelerate the transformation. Further acceleration could be achieved through collaboration of multiple actors across the agri-food system, but this calls for a systems approach. Therefore, we developed and applied a new sustainability experiment systems approach (SESA) consisting of an analytical framework that allows a reflective evaluation and cross-case analysis of multi-actor governance networks based on business and learning evaluation criteria. We performed a cross-case analysis of four agri-food sustainability experiments in Flanders to test and validate SESA. Hereby, the key factors of the success of collaboration and its performance were identified at the beginning of a sustainability experiment. Some of the key factors identified were risk sharing and the drivers to participate. We are convinced that these results may be used as an analytical tool for researchers, a tool to support and design new initiatives for policymakers, and a reflective tool for participating actors

Are life-extending treatments for terminal illnesses a special case? Exploring choices and societal viewpoints

Criteria used by the National Institute for Health and Care Excellence (NICE) to assess life-extending, end-of-life (EoL) treatments imply that health gains from such treatments are valued more than other health gains. Despite claims that the policy is supported by societal values, evidence from preference elicitation studies is mixed and in-depth research has shown there are different societal viewpoints. Few studies elicit preferences for policies directly or combine different approaches to understand preferences.Survey questions were designed to investigate support for NICE EoL guidance at national and regional levels. These ‘Decision Rule’ and ‘Treatment Choice’ questions were administered to an online sample of 1496 UK respondents in May 2014. The same respondents answered questions designed to elicit their agreement with three viewpoints (previously identified and described) in relation to provision of EoL treatments for terminally ill patients. We report the findings of these choice questions and examine how they relate to each other and respondents' viewpoints.The Decision Rule questions described three policies: DA – a standard ‘value for money’ test, applied to all health technologies; DB – giving special consideration to all treatments for terminal illnesses; and DC – giving special consideration to specific categories of treatments for terminal illnesses e.g. life extension (as in NICE EoL guidance) or those that improve quality-of-life (QoL). Three Treatment Choices were presented: TA – improving QoL for patients with a non-terminal illness; TB – extending life for EoL patients; and TC – improving QoL at the EoL.DC received most support (45%) with most respondents giving special consideration to EoL only when treatments improved QoL. The most commonly preferred treatment choices were TA (51%) and TC (43%). Overall, this study challenges claims about public support for NICE's EoL guidance and the focus on life extension at EoL and substantiates existing evidence of plurality in societal values

Social Spending Generosity and Income Inequality: A Dynamic Panel Approach

This paper explores whether more generous social spending polices in fact lead to less income inequality, or if redistributive outcomes are offset by behavioral disincentive effects. To account for the inherent endogeneity of social policies with regard to inequality levels, I apply the System GMM estimator and use the presumably random incidence of certain diseases as instruments for social spending levels. The regression results suggest that more social spending effectively reduces inequality levels. The result is robust with respect to the instrument count and different data restrictions. Looking at the structure of benefits, particularly unemployment benefits and public pensions are responsible for the inequality reducing impact. More targeted benefits, however, do not significantly reduce income inequality. Rather, their positive effect on pre-government income inequality hints at substantial disinctive effects.Social Benefits, Redistribution, Income Inequality, System GMM

Evaluating telemedicine: A focus on patient pathways

Evaluations of telemedicine have sought to assess various measures of effectiveness (e.g., diagnostic accuracy), efficiency (e.g., cost), and engagement (e.g., patient satisfaction) to determine its success. Few studies, however, have looked at evaluating the organizational impact of telemedicine, which involves technology and process changes that affect the way that it is used and accepted by patients and clinicians alike. This study reviews and discusses the conceptual issues in telemedicine research and proposes a fresh approach for evaluating telemedicine. First, we advance a patient pathway perspective, as most of the existing studies view telemedicine as a support to a singular rather than multiple aspects of a health care process. Second, to conceptualize patient pathways and understand how telemedicine impacts upon them, we propose simulation as a tool to enhance understanding of the traditional and telemedicine patient pathway

Facet-Based Browsing in Video Retrieval: A Simulation-Based Evaluation

In this paper we introduce a novel interactive video retrieval approach which uses sub-needs of an information need for querying and organising the search process. The underlying assumption of this approach is that the search effectiveness will be enhanced when employed for interactive video retrieval. We explore the performance bounds of a faceted system by using the simulated user evaluation methodology on TRECVID data sets and also on the logs of a prior user experiment with the system. We discuss the simulated evaluation strategies employed in our evaluation and the effect on the use of both textual and visual features. The facets are simulated by the use of clustering the video shots using textual and visual features. The experimental results of our study demonstrate that the faceted browser can potentially improve the search effectiveness

Bayesian Synthesis: Combining subjective analyses, with an application to ozone data

Bayesian model averaging enables one to combine the disparate predictions of a number of models in a coherent fashion, leading to superior predictive performance. The improvement in performance arises from averaging models that make different predictions. In this work, we tap into perhaps the biggest driver of different predictions---different analysts---in order to gain the full benefits of model averaging. In a standard implementation of our method, several data analysts work independently on portions of a data set, eliciting separate models which are eventually updated and combined through a specific weighting method. We call this modeling procedure Bayesian Synthesis. The methodology helps to alleviate concerns about the sizable gap between the foundational underpinnings of the Bayesian paradigm and the practice of Bayesian statistics. In experimental work we show that human modeling has predictive performance superior to that of many automatic modeling techniques, including AIC, BIC, Smoothing Splines, CART, Bagged CART, Bayes CART, BMA and LARS, and only slightly inferior to that of BART. We also show that Bayesian Synthesis further improves predictive performance. Additionally, we examine the predictive performance of a simple average across analysts, which we dub Convex Synthesis, and find that it also produces an improvement.Comment: Published in at http://dx.doi.org/10.1214/10-AOAS444 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org