This chapter explores the use of “responsive” or “interactive” urban media technologies as a tool or “building block” in the (re)design of urban public spaces. This is especially relevant as in the last two decades, urban development and digital technologies have brought out new types of urban typologies and practices often referred to as “networked urbanism.” These typologies and practices bring out specific challenges with regard to their functioning as public space. We argue that responsive technologies could reinforce qualities of public space in this condition of “networked urbanism”; however, their implementation demands new strategies and above all new forms of cooperation between disciplines such as architecture, urban design, and urban interaction design. To aid such an approach, this chapter introduces a heuristic of five mechanisms of responsive media. These are meant to function as a shared vocabulary aiding designers of various backgrounds to collaborate in an interdisciplinary design process for public spaces in a broader development of networked urbanism.
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This chapter discusses the sharing economy in the Netherlands, focussing on shared mobility and gig work platforms. The Netherlands has been known as one of the pioneers in the sharing economy. Local initiatives emerged at the beginning of the 2010s. International players such as Uber, UberPop, and Airbnb followed soon after. Initially, the sharing economy was greeted with a sense of optimism, as it was thought to contribute to social cohesion and sustainability. Over the last few years, the debate has shifted to the question of how public values can be safeguarded or stimulated. In this regard, shared mobility is hoped to contribute to more sustainable transport. In the gig economy, scholars and labour representatives fear a further flexibilisation of labour; others see opportunities for economic growth.
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Objective: To construct the underlying value structure of shared decision making (SDM) models. Method: We included previously identified SDM models (n = 40) and 15 additional ones. Using a thematic analysis, we coded the data using Schwartz’s value theory to define values in SDM and to investigate value relations. Results: We identified and defined eight values and developed three themes based on their relations: shared control, a safe and supportive environment, and decisions tailored to patients. We constructed a value structure based on the value relations and themes: the interplay of healthcare professionals’ (HCPs) and patients’ skills [Achievement], support for a patient [Benevolence], and a good relationship between HCP and patient [Security] all facilitate patients’ autonomy [Self-Direction]. These values enable a more balanced relationship between HCP and patient and tailored decision making [Universalism]. Conclusion: SDM can be realized by an interplay of values. The values Benevolence and Security deserve more explicit attention, and may especially increase vulnerable patients’ Self-Direction. Practice implications: This value structure enables a comparison of values underlying SDM with those of specific populations, facilitating the incorporation of patients’ values into treatment decision making. It may also inform the development of SDM measures, interventions, education programs, and HCPs when practicing.
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