Though there are different interpretations in the scholarly literature of what a social learning is: whether it is an individual, organisational, or collective process. For example, Freeman (2007), in his study on policy change in the public health sector, conceptualised collective learning of public officials as a process of epistemological bricolage. In his interpretation, the new policy ideas are the result of this bricolage process, when the “acquired second-hand” ideas are transformed into “something new”. The literature on (democratic) governance points opens another perspective to the policy change, emphasising the importance of public engagement in the policy-making process. Following this school of thought the new policy is the result of a deliberative act that involves different participants. In other words, the ideas about policy are not borrowed, but are born in social deliberation. Combining the insights gained from both literatures – social learning and governance – the policy change is interpreted, as a result of a broad social interaction process, which is also the social learning for all participants.The paper will focus on further development of the conceptualisation of policy change through social deliberation and social learning and will attempt to define the involved micro mechanisms. The exploratory case study of policy change that was preceded by a broad public debate will help to describe and establish the mechanisms. Specifically, the paper will focus on the decision of the Dutch government to cease the exploration of natural gas from the Groningen gas field. The radical change in national policy regarding gas exploration is seen as a result of a broader public debate, which was an act of social deliberation and social learning at the same time.
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This paper revisits how and why new multinational knowledge-based strategies and multi-level governmental policies influence the upgrading process of regions in developing economies. Automotive multinationals traditionally exploited local asset conditions, but it is shown that they have also been contributing to knowledge-generation systems via investments in R&D centres and cooperation with regional knowledge producers. We discern three elements of the upgrading process of regions—upgrading of domestic firms, subsidiary evolution and establishment of strategic relations with local knowledge institutes—to analyse two case studies: Ostrava (Czech Republic) and Shanghai (China). The cases show that all types of upgrading—product, process, chain and functional—have taken place in the last years, and that follow sourcing may have a positive impact on regional upgrading. These observations provide lessons for governments in developing economies which aim to strengthen innovation-based regional development.
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This chapter presents Critical Policy Discourse Analysis (CPDA) which merges critical discourse analysis (CDA) with critical policy studies (CPS). CPDA engages with a discursive analysis of a policy problem, generally drawing on critical discourse analysis for its methodology, in this case Text Oriented Discourse Analysis (TODA). The research addresses the problem of complexity reduction in the process of policy-making and illustrates this with an analysis of the UN Agenda “Transforming the World, the 2030 Agenda for Sustainable Development”, which introduces the sustainable development goals (SDGs). It presents the reader with a detailed example of how to perform a TODA research. It indeed reveals mechanisms of policy reduction such as decontextualization, singularization, a limited spatio-temporal frame reduced to the timespan of the UN. It discusses the potential consequences of this for the effectivity of the SDGs and presents alternative theories and voices that do capture the complexity of real life events. The final section suggests further developments in CPDA and advocates bringing complexity to the fore.
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A welcome policy can be embedded in a municipal authority organisation in a number of different ways. Each has its own strengths and weaknesses. To be effective, the local policy makers must be clear on how they hope to make use of the welcome policy and how this will benefit or suffer from different organisational structures. No one ‘ideal’ structure will ‘fit’ all municipal situations in Europe. However, to be aware of the strengths and weaknesses of the organisational structure that most closely resembles the local situation can increase the chances of successful policy implementation.
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Shared Vision Planning (SVP) is a collaborative approach to water (resource) management that combines three practices: (1) traditional water resources planning; (2) structured participation of stakeholders; (3) (collaborative) computer modeling and simulation. The authors argue that there are ample opportunities for learning and innovation in SVP when we look at it as a form of Policy Analysis (PA) in a multi-actor context. SVP faces three classic PA dilemmas: (1) the role of experts and scientific knowledge in policymaking; (2) The design and management of participatory and interactive planning processes; and (3) the (ab)use of computer models and simulations in (multi actor) policymaking. In dealing with these dilemmas, SVP can benefit from looking at the richness of PA methodology, such as for stakeholder analysis and process management. And it can innovate by incorporating some of the rapid developments now taking place in the field of (serious) gaming and simulation (S&G) for policy analysis. In return, the principles, methods, and case studies of SVP can significantly enhance how we perform PA for multi-actor water (resource) management.
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This paper uses discourse theory to obtain a broader understanding of how research impact of sustainable tourism research develops in the environmental policy domain. Discourse theory shifts emphasis from the substance of science versus policy to the use of science in policy processes and explains the political dimensions of policymaking. We first review a well-documented science-policy gap in sustainable tourism research on climate change to develop an alternative conceptualisation of research impact. Then, using a case study approach, we investigate this framework by evaluating the impact of a PhD thesis about aviation’s global CO 2 emissions on the Dutch aviation policy process. The case study shows research impact is entwined with various other elements, and embedded in a specific governance context. Research influenced contrasting science-policy interactions and contributed to conflicting policy actions and reactions. The impact of research in this case was manifested through the formation and interplay of multiple knowledge objects that were both embraced and marginalised. In settings like this, research is used to legitimise pre-existing policy positions rather than to develop new policies. We discuss the implications of narrow conceptions of research impact. The paper highlights the need for advanced policy analysis in sustainable tourism research.
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Aim: To evaluate healthcare professionals' performance and treatment fidelity in the Cardiac Care Bridge (CCB) nurse-coordinated transitional care intervention in older cardiac patients to understand and interpret the study results. Design: A mixed-methods process evaluation based on the Medical Research Council Process Evaluation framework. Methods: Quantitative data on intervention key elements were collected from 153 logbooks of all intervention patients. Qualitative data were collected using semi-structured interviews with 19 CCB professionals (cardiac nurses, community nurses and primary care physical therapists), from June 2017 until October 2018. Qualitative data-analysis is based on thematic analysis and integrated with quantitative key element outcomes. The analysis was blinded to trial outcomes. Fidelity was defined as the level of intervention adherence. Results: The overall intervention fidelity was 67%, ranging from severely low fidelity in the consultation of in-hospital geriatric teams (17%) to maximum fidelity in the comprehensive geriatric assessment (100%). Main themes of influence in the intervention performance that emerged from the interviews are interdisciplinary collaboration, organizational preconditions, confidence in the programme, time management and patient characteristics. In addition to practical issues, the patient's frailty status and limited motivation were barriers to the intervention. Conclusion: Although involved healthcare professionals expressed their confidence in the intervention, the fidelity rate was suboptimal. This could have influenced the non-significant effect of the CCB intervention on the primary composite outcome of readmission and mortality 6 months after randomization. Feasibility of intervention key elements should be reconsidered in relation to experienced barriers and the population. Impact: In addition to insight in effectiveness, insight in intervention fidelity and performance is necessary to understand the mechanism of impact. This study demonstrates that the suboptimal fidelity was subject to a complex interplay of organizational, professionals' and patients' issues. The results support intervention redesign and inform future development of transitional care interventions in older cardiac patients.
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Energy policies are vital tools used by countries to regulate economic and social development as well as guarantee national security. To address the problems of fragmented policy objectives, conflicting tools, and overlapping initiatives, the internal logic and evolutionary trends of energy policies must be explored using the policy content. This study uses 38,277 energy policies as a database and summarizes the four energy policy objectives: clean, low-carbon, safe, and efficient. Using the TextCNN model to classify and deconstruct policies, the LDA + Word2vec theme conceptualization and similarity calculations were compared with the EISMD evolution framework to determine the energy policy theme evolution path. Results indicate that the density of energy policies has increased. Policies have become more comprehensive, barriers between objectives have gradually been broken, and low-carbon objectives have been strengthened. The evolution types are more diversified, evolution paths are more complicated, and the evolution types are often related to technology, industry, and market maturity. Traditional energy themes evolve through inheritance and merger; emerging technology and industry themes evolve through innovation, inheritance, and splitting. Moreover, this study provides a replicable analytical framework for the study of policy evolution in other sectors and evidence for optimizing energy policy design
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Over the past forty years, the use of process models in practice has grown extensively. Until twenty years ago, remarkably little was known about the factors that contribute to the human understandability of process models in practice. Since then, research has, indeed, been conducted on this important topic, by e.g. creating guidelines. Unfortunately, the suggested modelling guidelines often fail to achieve the desired effects, because they are not tied to actual experimental findings. The need arises for knowledge on what kind of visualisation of process models is perceived as understandable, in order to improve the understanding of different stakeholders. Therefore the objective of this study is to answer the question: How can process models be visually enhanced so that they facilitate a common understanding by different stakeholders? Consequently, five subresearch questions (SRQ) will be discussed, covering three studies. By combining social psychology and process models we can work towards a more human-centred and empirical-based solution to enhance the understanding of process models by the different stakeholders with visualisation.
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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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