The temporal dimension of acceptance is under-researched in technology acceptance research. Yet, people’s perceptions on technology use may change over time when gaining user experiences. Our 6-month home study deploying an interactive robot provides insight into the long-term use of use interactive technology in a domestic environment. We present a phased framework for the acceptance of interactive technology in domestic environments. Based on 97 interviews obtained from 21 participants living in different household types, the results provide an initial validation of our phased framework for long-term acceptance showing that acceptance phases are linked to certain user experiences which evolve over time when people gain experience with the technology. Involving end users in the early stages of development helps researchers understand the cultural and social contexts of acceptance and enables developers to apply this gained knowledge into their future designs.
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Technology in general, and assistive technology in particular, is considered to be a promising opportunity to address the challenges of an aging population. Nevertheless, in health care, technology is not as widely used as could be expected. In this chapter, an overview is given of theories and models that help to understand this phenomenon. First, the design of (assistive) technologies will be addressed and the importance of human-centered design in the development of new assistive devices will be discussed. Also theories and models are addressed about technology acceptance in general. Specific attention will be given to technology acceptance in healthcare professionals, and the implementation of technology within healthcare organizations. The chapter will be based on the state of the art of scientific literature and will be illustrated with examples from our research in daily practice considering the different perspectives of involved stakeholders.
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Change has become continuous, and innovation is a primary approach for hospitality, i.e., hotel companies, to become or remain economically viable and sustainable. An increasing number of management researchers are paying more attention to workplace rather than technological innovation. This study investigates workplace innovation in the Dutch hotel industry, in three- and four-star hotels in the Netherlands, by comparing them to other industries. Two samples were questioned using the Workplace Innovation survey created by the Dutch Network of Social Innovation (NSI). The first was conducted in the hospitality industry, and these data were compared with data collected in a sample of other industries. Results suggest that greater strategic orientation on workplace innovation and talent development has a positive influence on four factors of organizational performance. Greater internal rates of change, the ability to self-organize, and investment in knowledge also had positive influences on three of the factors—growth in revenue, sustainability, and absenteeism. Results also suggest that the hospitality industry has lower workplace innovation than other industries. However, no recent research has assessed to what degree the hospitality industry fosters workplace innovation, especially in the Netherlands. Next to that, only few studies have examined management in the Dutch hotel industry, how workplace innovation is used there, and whether it improves practices.
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Youth care is under increasing pressure, with rising demand, longer waiting lists, and growing staff shortages. In the Netherlands, one in seven children and adolescents is currently receiving youth care. At the same time, professionals face high workloads, burnout risks, and significant administrative burdens. This combination threatens both the accessibility and quality of care, leading to escalating problems for young people and families. Artificial intelligence (AI) offers promising opportunities to relieve these pressures by supporting professionals in their daily work. However, many AI initiatives in youth care fail to move beyond pilot stages, due to barriers such as lack of user acceptance, ethical concerns, limited professional ownership, and insufficient integration into daily practice. Empirical research on how AI can be responsibly and sustainably embedded in youth care is still scarce. This PD project aims to develop practice-based insights and strategies that strengthen the acceptance and long-term adoption of AI in youth care, in ways that support professional practice and contribute to appropriate care. The focus lies not on the technology itself, but on how professionals can work with AI within complex, high-pressure contexts. The research follows a cyclical, participatory approach, combining three complementary implementation frameworks: the Implementation Guide (Kaptein), the CFIR model (Damschroder), and the NASSS-CAT framework (Greenhalgh). Three case studies serve as core learning environments: (1) a speech-to-text AI tool to support clinical documentation, (2) Microsoft Copilot 365 for organization-wide adoption in support teams, and (3) an AI chatbot for parents in high-conflict divorces. Throughout the project, professionals, clients, ethical experts, and organizational stakeholders collaborate to explore the practical, ethical, and organizational conditions under which AI can responsibly strengthen youth care services.
