New and existing companies are looking for ways to thrive in a competitive environment with innovative business models while respecting society and avoiding actions that harm the planet. Trends such as circular economy, fair trade, lowsumerism, and sharing economy are some of the many emerging entrepreneurial approaches that address this issue, but there is still a gap between what theory argues and the levels of environmental and social sustainability realized when theory is put into practice. In fact, most research on the topic of sustainable business models is still exploratory and does not fully acknowledge these emerging approaches, whose definitions, boundaries, and defining characteristics are still somewhat vague. This study seeks to contribute to the understanding of the inner entrepreneurial dynamics of innovative sustainable business models. In particular, we focus on the fashion business, a resource-intensive industry in which opportunities to reduce environmental impacts and to innovate business models abound. The aim of our research is to investigate innovative business models in the fashion industry that have sustainability as their defining characteristic, especially in terms of value proposition. In order to do that, we combine a systematic review of the literature with empirical research comprised of six interviews with specialists in sustainability, business model innovation, and the fashion industry, along with eight case studies on innovative fashion startups we define as 'born sustainable.' As a result, we propose a synthesizing framework that discloses trends and drivers of innovative and sustainable business models in the fashion industry. We also highlight opportunities and challenges for researchers and entrepreneurs interested in this topic.

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Foot and mouth disease (FMD) is a highly infectious disease that affects cloven-hoofed livestock and wildlife. FMD has been a problem for decades, which has led to various measures to control, eradicate and prevent FMD by National Veterinary Services worldwide. Currently, the identification of areas that are at risk of FMD virus incursion and spread is a priority for FMD target surveillance after FMD is eradicated from a given country or region. In our study, a knowledge-driven spatial model was built to identify risk areas for FMD occurrence and to evaluate FMD surveillance performance in Rio Grande do Sul state, Brazil. For this purpose, multi-criteria decision analysis was used as a tool to seek multiple and conflicting criteria to determine a preferred course of action. Thirteen South American experts analyzed 18 variables associated with FMD introduction and dissemination pathways in Rio Grande do Sul. As a result, FMD higher risk areas were identified at international borders and in the central region of the state. The final model was expressed as a raster surface. The predictive ability of the model assessed by comparing, for each cell of the raster surface, the computed model risk scores with a binary variable representing the presence or absence of an FMD outbreak in that cell during the period 1985 to 2015. Current FMD surveillance performance was assessed, and recommendations were made to improve surveillance activities in critical areas.

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