16,637 research outputs found

    Competing Claims on Natural Resources: What Role for Science?

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    Competing claims on natural resources become increasingly acute, with the poor being most vulnerable to adverse outcomes of such competition. A major challenge for science and policy is to progress from facilitating univocal use to guiding stakeholders in dealing with potentially conflicting uses of natural resources. The development of novel, more equitable, management options that reduce rural poverty is key to achieving sustainable use of natural resources and the resolution of conflicts over them. Here, we describe an interdisciplinary and interactive approach for: (i) the understanding of competing claims and stakeholder objectives; (ii) the identification of alternative resource use options, and (iii) the scientific support to negotiation processes between stakeholders. Central to the outlined approach is a shifted perspective on the role of scientific knowledge in society. Understanding scientific knowledge as entering societal arenas and as fundamentally negotiated, the role of the scientist becomes a more modest one, a contributor to ongoing negotiation processes among stakeholders. Scientists can, therefore, not merely describe and explain resource-use dynamics and competing claims, but in doing so, they should actively contribute to negotiation processes between stakeholders operating at different scales (local, national, regional, and global). Together with stakeholders, they explore alternatives that can contribute to more sustainable and equitable use of natural resources and, where possible, design new technical options and institutional arrangements

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

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    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

    Bringing tasks back in: an organizational theory of resource complementarity and partner selection

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    To progress beyond the idea that the value of inter-firm collaboration is largely determined by the complementarity of the resources held by partners, we build a theoretical framework that explains under which conditions a set of resources or capabilities can be considered as complementary and resulting in superior value creation. Specifically, we argue that the tasks that an inter-firm collaboration has to perform determine complementarities, and that complementarities arise from similar and dissimilar resources alike. We capture this relationship in the concept of task resource complementarity. Further, we examine factors that impact on the relevance of this construct as a predictor of partner selection. Finally, we discuss which implications arise for a theory of the firm when tasks are explicitly incorporated into the conceptualization of resource complementarity

    Knowledge integration in One Health policy formulation, implementation and evaluation

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    The One Health concept covers the interrelationship between human, animal and environmental health and requires multistakeholder collaboration across many cultural, disciplinary, institutional and sectoral boundaries. Yet, the implementation of the One Health approach appears hampered by shortcomings in the global framework for health governance. Knowledge integration approaches, at all stages of policy development, could help to address these shortcomings. The identification of key objectives, the resolving of trade-offs and the creation of a common vision and a common direction can be supported by multicriteria analyses. Evidence-based decision-making and transformation of observations into narratives detailing how situations emerge and might unfold in the future can be achieved by systems thinking. Finally, transdisciplinary approaches can be used both to improve the effectiveness of existing systems and to develop novel networks for collective action. To strengthen One Health governance, we propose that knowledge integration becomes a key feature of all stages in the development of related policies. We suggest several ways in which such integration could be promoted

    Rethinking soft OR interventions: models as boundary objects

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    In this paper I draw on research on the role of objects in problem solving collaboration to make a case for the conceptualisation of models as potential boundary objects. Such conceptualisation highlights the possibility that the models used in Soft OR interventions perform three roles with specific effects: transfer to develop a shared language, translation to develop shared meanings, and transformation to develop common interests. If these roles are carried out effectively, models enable those involved to traverse the syntactic, semantic and pragmatic boundaries encountered when tackling a problem situation of mutual concern, and help create new knowledge that has consequences for action. I illustrate these roles and associated effects via two empirical case vignettes drawn from an ongoing action research programme studying the impact of Soft OR interventions. Building on the insights generated by the case vignettes, I develop an analytical framework that articulates the dynamics of knowledge creation within Soft OR interventions. The framework can shed new light on a core aspect of Soft OR practice, especially with regards to the impact of models on the possibilities for action they can afford to those involved. I conclude with a discussion of the prescriptive value of the framework for research into the evaluation of Soft OR interventions, and its implications for the conduct of Soft OR practice

    Towards Convergence: How to Do Transdisciplinary Environmental Health Disparities Research.

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    Increasingly, funders (i.e., national, public funders, such as the National Institutes of Health and National Science Foundation in the U.S.) and scholars agree that single disciplines are ill equipped to study the pressing social, health, and environmental problems we face alone, particularly environmental exposures, increasing health disparities, and climate change. To better understand these pressing social problems, funders and scholars have advocated for transdisciplinary approaches in order to harness the analytical power of diverse and multiple disciplines to tackle these problems and improve our understanding. However, few studies look into how to conduct such research. To this end, this article provides a review of transdisciplinary science, particularly as it relates to environmental research and public health. To further the field, this article provides in-depth information on how to conduct transdisciplinary research. Using the case of a transdisciplinary, community-based, participatory action, environmental health disparities study in California's Central Valley provides an in-depth look at how to do transdisciplinary research. Working with researchers from the fields of social sciences, public health, biological engineering, and land, air, and water resources, this study aims to answer community residents' questions related to the health disparities they face due to environmental exposure. Through this case study, I articulate not only the logistics of how to conduct transdisciplinary research but also the logics. The implications for transdisciplinary methodologies in health disparity research are further discussed, particularly in the context of team science and convergence science

    Collaborative planning in non-hierarchical networks - an intelligent negotiation-based framework

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    In today’s competing business market, companies are constantly challenged to dynamically adapt to customer expectations by diminishing the time response that goes from the beginning of the business opportunity to the satisfaction of the customer need. Simultaneously, there is increased recognition of the advantages that companies obtain in focusing on their core business and seeking other competencies through partnerships with other partners by forming collaborative networks. These new collaborative organizational structures require a new set of methods and tools to support the management of manufacturing processes across the entire supply chain. The present paper addresses the collaborative production planning problem in networks of non-hierarchical, decentralized, and independent companies. By proposing a collaborative planning intelligent framework composed of a web-based set of methods, tools, and technologies, the present study intends to provide network stakeholders with the necessary means to responsively and efficiently address each one of the market business opportunities. Through this new holistic framework, the managers of the networked companies can address the challenges posed during collaborative network formation and supply chain production planning.The research leading to these results received funding from the European Union’s Seventh Framework Program (FP7/2007-2013) under grant agreement No. 260169. This work was also financed by national funds through the Portuguese funding agency, FCT—Fundação para a Ciência e a Tecnologia, within project LA/P/0063/2020
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