“Critical Making in Collaboration with Nature”, discusses the outcomes of the Making Sustainability Work project from Fall 2020. With support of CoECI Zaaigelden scheme, the Critical Making learning community put together a group of makers from research, education and industry to explore the implications of designing with natural materials and biological processes, such as biopolymers, fungal composites and bacteria dye. By following a selection of modules from the Fabricademy global training program, participants explored hands-on techniques to create their own design materials and colours from renewable and biodegradable resources and documented their journeys. The shared experience was reflected upon in a series of interviews and essays touching on the following questions: • In what way do unruly natural materials challenge ways of doing and teaching design? • How do grown materials fit into or challenge makers’ goals of sustainability?• What is needed to bring biological processes into communities of practice in the field of design, art and making?• How and when does criticality emerge in the making process? • How do processes of thinking and doing intersect and what is the role of social interactions and collaboration?
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Current many changes are taking place in the elderly care: care is changing from supply-oriented to demand driven, problems have to be more serious than previously to get a placement in a nursing home, furthermore the demand for heavier care will increase due to ageing. The aim of this study is to acquire a clear insight in the decision-making process with regard to placement in a nursing home facility.
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In case of a major cyber incident, organizations usually rely on external providers of Cyber Incident Response (CIR) services. CIR consultants operate in a dynamic and constantly changing environment in which they must actively engage in information management and problem solving while adapting to complex circumstances. In this challenging environment CIR consultants need to make critical decisions about what to advise clients that are impacted by a major cyber incident. Despite its relevance, CIR decision making is an understudied topic. The objective of this preliminary investigation is therefore to understand what decision-making strategies experienced CIR consultants use during challenging incidents and to offer suggestions for training and decision-aiding. A general understanding of operational decision making under pressure, uncertainty, and high stakes was established by reviewing the body of knowledge known as Naturalistic Decision Making (NDM). The general conclusion of NDM research is that experts usually make adequate decisions based on (fast) recognition of the situation and applying the most obvious (default) response pattern that has worked in similar situations in the past. In exceptional situations, however, this way of recognition-primed decision-making results in suboptimal decisions as experts are likely to miss conflicting cues once the situation is quickly recognized under pressure. Understanding the default response pattern and the rare occasions in which this response pattern could be ineffective is therefore key for improving and aiding cyber incident response decision making. Therefore, we interviewed six experienced CIR consultants and used the critical decision method (CDM) to learn how they made decisions under challenging conditions. The main conclusion is that the default response pattern for CIR consultants during cyber breaches is to reduce uncertainty as much as possible by gathering and investigating data and thus delay decision making about eradication until the investigation is completed. According to the respondents, this strategy usually works well and provides the most assurance that the threat actor can be completely removed from the network. However, the majority of respondents could recall at least one case in which this strategy (in hindsight) resulted in unnecessary theft of data or damage. Interestingly, this finding is strikingly different from other operational decision-making domains such as the military, police and fire service in which there is a general tendency to act rapidly instead of searching for more information. The main advice is that training and decision aiding of (novice) cyber incident responders should be aimed at the following: (a) make cyber incident responders aware of how recognition-primed decision making works; (b) discuss the default response strategy that typically works well in several scenarios; (c) explain the exception and how the exception can be recognized; (d) provide alternative response strategies that work better in exceptional situations.
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The decision-making process in boardrooms has a significant impact on organizational performance. In the last two decades, scientific research on the decision-making process in boardrooms has increased. This resulted in a substantial body of knowledge about boardroom factors and their relation to organizational performance. However, the effectiveness of the decision-making process in boardrooms is still mainly a black box. Amongst other things, scientific findings seem to contradict each other, which could mean additional insights are still missing. This research aims to contribute to a better understanding of this black box.
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Background Clients facing decision-making for long-term care are in need of support and accessible information. Construction of preferences, including context and calculations, for clients in long-term care is challenging because of the variability in supply and demand. This study considers clients in four different sectors of long-term care: the nursing and care of the elderly, mental health care, care of people with disabilities, and social care. The aim is to understand the construction of preferences in real-life situations. Method Client choices were investigated by qualitative descriptive research. Data were collected from 16 in-depth interviews and 79 client records. Interviews were conducted with clients and relatives or informal caregivers from different care sectors. The original client records were explored, containing texts, letters, and comments of clients and caregivers. All data were analyzed using thematic analysis. Results Four cases showed how preferences were constructed during the decision-making process. Clients discussed a wide range of challenging aspects that have an impact on the construction of preferences, e.g. previous experiences, current treatment or family situation. This study describes two main characteristics of the construction of preferences: context and calculation. Conclusion Clients face diverse challenges during the decision-making process on long-term care and their construction of preferences is variable. A well-designed tool to support the elicitation of preferences seems beneficial.
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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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By combining different disciplines such as entrepreneurship, psychology, and business administration, this paper provides insights into the decision-making process involved in the succession of agricultural family businesses. It offers an overview of how choices and decisions are influenced among all actors involved in the process, including the incumbent, successor, non-succeeding family members, and both informal and formal advisors. This overview creates practical insights to support a more successful business succession process. Decision-making in business succession is influenced by several factors such as business systems and culture, as well as mutual relationships, personality traits, behavioral patterns, and habits of those involved. Communication and trust, between both succeeding and incumbent family members, are important aspects that can lead to a successful process. When family relationships are strong, there is a better chance that the social-emotional aspects of business succession do not become a bottleneck. Financial, tax and legal issues can often be resolved if the social-emotional foundation is solid.
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Purpose: This study assesses the perceived quality of the outcomes in decision-making phases by using the conversational ai approach. Design/Method: The research adopts an experimental design to explore the impact of conversational artificial intelligence (AI) in the separate phases of a decision-making making process. This investigation is conducted through a team-level “Shark Tank” game, which serves as a dynamic platform. Findings: The data indicated a discernible pattern across all five steps of the decision-making process. The integration of AI, particularly Conversational AI, consistently improves the perceived quality of decisions, with varying degrees of impact at various stages. Originality/Value: This study contributes by particularly focusing on the conversational AI approach, to discern its efficacy in enhancing decision making processes. It is critical in contributing to the rapidly growing field of AI in decision making, providing a deeper understanding of AI's role in improving decision making quality.
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Daniel Birnbaum, rector van de Städelschule in Frankfurt, curator vanPortikus en veelgevraagd samensteller van biënnales over de hele wereld, is artistiek leider van de centrale presentatie van de 53e Biënnalevan Venetië, getiteld Making Worlds . Henk Slager reisde naar Frankfurtom met Birnbaum te spreken over de achtergronden van de belangrijkstetentoonstelling van deze zomer.
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Introduction: Different models of frameworks for dietetic care are used in Europe. There is a substantial need for a consistent framework to compare research results and to cooperate on an international level. Therefore, one of the goals of the EU-funded project IMPECD was the development of a unified framework Dietetic Care Process (DCP) in order to foster a shared understanding of process-driven dietetic counselling. Materials and Methods:: Based on a literature review and in-depth analysis of different frameworks an iterative and incremental development process of finding solutions for decision-making within the consortium consisting of dietetic experts from 5 European HEI was passed. The developed DCP model was integrated in an online training course including 9 clinical cases (MOOC) to train students. The draft versions and the concluding final version DCP model were evaluated and re-evaluated by teachers and 25 students at two Intensive Study Programmes. Results:: The DCP model consists of five distinct, interrelated steps which the consortium agreed on: Dietetic Assessment, Dietetic Diagnosis, Planning Dietetic Intervention, Implementing Dietetic Intervention, Dietetic Outcome Evaluation. A standardized scheme was developed to define the process steps: dedication, central statement, aim and principles, and operationalization. Discussion:: Existing different process models were analyzed to create a new and consistent concept of a unified framework DCP. The variety within the European countries represented by the consortium proved to be both a challenge in decision-making and an opportunity to integrate multinational perspectives and intensify the scientific discourse. The development of a standardized scheme with precise definitions is a prerequisite for planning study designs in health services research. Besides, clarification is essential for establishing process-guided work in practice. The evaluated MOOC is now implemented in study programmes used by 5 European HEI in order to keep approaches and process-driven action comparable. The MOOC promotes the exchange of ideas between future professionals on an international level.
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