The effectiveness of smart home technology in home care situations depends on the acceptance and use of the technology by both users and end-users. In the Netherlands many projects have started to introduce smart home technology and telecare in the homes of elderly people, but only some have been successful. In this paper, features for success and failure in the deployment of new (ICT) technology in home care are used to revise the technology acceptance model (TAM) into a model that explains the use of smart home and telecare technology by older adults. In the revised model we make the variable 'usefulness' more specific, by describing the benefits of the technology that are expected to positively affect technology usage. Additionally, we state that several moderator variables - that are expected to influence this effect - should be added to the model in order to explain why people eventually do (not) use smart home technology, despite the benefits and the intention to use. We categorize these variables, that represent the problems found in previous studies, in 'accessibility', 'facilitating conditions' and 'personal variables'.
Individuals with mild intellectual disabilities or borderline intellectual functioning are at increased risk to develop a substance use disorder—however, effective treatment programs adapted to this target group are scarce. This study evaluated the effectiveness of Take it Personal!+ in individuals with mild intellectual disabilities or borderline intellectual functioning and substance use disorder. Take it Personal!+ is a personalized treatment based on motivational interviewing and cognitive-behavioral therapy supported by an mHealth application. Data were collected in a nonconcurrent multiple baseline single-case experimental design across individuals with four phases (i.e., baseline, treatment, posttreatment, and follow-up). Twelve participants were randomly allocated to baseline lengths varying between 7 and 11 days. Substance use quantity was assessed during baseline, treatment, and posttreatment with a daily survey using a mobile application. Visual analysis was supported with statistical analysis of the daily surveys by calculating three effect size measures in 10 participants (two participants were excluded from this analysis due to a compliance rate below 50%). Secondary, substance use severity was assessed with standardized questionnaires at baseline, posttreatment, and follow-up and analyzed by calculating the Reliable Change Index. Based on visual analysis of the daily surveys, 10 out of 12 participants showed a decrease in mean substance use quantity from baseline to treatment and, if posttreatment data were available, to posttreatment. Statistical analysis showed an effect of Take it Personal!+ in terms of a decrease in daily substance use in 8 of 10 participants from baseline to treatment and if posttreatment data were available, also to posttreatment. In addition, data of the standardized questionnaires showed a decrease in substance use severity in 8 of 12 participants. These results support the effectiveness of Take it Personal!+ in decreasing substance use in individuals with mild intellectual disabilities or borderline intellectual functioning.
Digital transformation has been recognized for its potential to contribute to sustainability goals. It requires companies to develop their Data Analytic Capability (DAC), defined as their ability to collect, manage and analyze data effectively. Despite the governmental efforts to promote digitalization, there seems to be a knowledge gap on how to proceed, with 37% of Dutch SMEs reporting a lack of knowledge, and 33% reporting a lack of support in developing DAC. Participants in the interviews that we organized preparing this proposal indicated a need for guidance on how to develop DAC within their organization given their unique context (e.g. age and experience of the workforce, presence of legacy systems, high daily workload, lack of knowledge of digitalization). While a lot of attention has been given to the technological aspects of DAC, the people, process, and organizational culture aspects are as important, requiring a comprehensive approach and thus a bundling of knowledge from different expertise. Therefore, the objective of this KIEM proposal is to identify organizational enablers and inhibitors of DAC through a series of interviews and case studies, and use these to formulate a preliminary roadmap to DAC. From a structure perspective, the objective of the KIEM proposal will be to explore and solidify the partnership between Breda University of Applied Sciences (BUas), Avans University of Applied Sciences (Avans), Logistics Community Brabant (LCB), van Berkel Logistics BV, Smink Group BV, and iValueImprovement BV. This partnership will be used to develop the preliminary roadmap and pre-test it using action methodology. The action research protocol and preliminary roadmap thereby developed in this KIEM project will form the basis for a subsequent RAAK proposal.
Digital transformation has been recognized for its potential to contribute to sustainability goals. It requires companies to develop their Data Analytic Capability (DAC), defined as their ability to manage and analyze data effectively. Despite the governmental efforts to promote digitalization, there seems to be a knowledge gap on how to proceed, with 37% of Dutch SMEs reporting a lack of knowledge, and 33% reporting a lack of support in developing DAC. While extensive attention has been given to the technological aspects of DAC, the people, process, and organizational culture aspects are as important, requiring a comprehensive approach and thus a bundling of knowledge from different expertise. Therefore, the objective of this KIEM proposal is to identify organizational enablers and inhibitors of DAC through a series of interviews and case studies, and use these to formulate a preliminary roadmap to DAC.
By transitioning from a fossil-based economy to a circular and bio-based economy, the industry has an opportunity to reduce its overall CO2 emission. Necessary conditions for effective and significant reductions of CO2-emissions are that effective processing routes are developed that make the available carbon in the renewable sources accessible at an acceptable price and in process chains that produce valuable products that may replace fossil based products. To match the growing industrial carbon demand with sufficient carbon sources, all available circular, and renewable feedstock sources must be considered. A major challenge for greening chemistry is to find suitable sustainable carbon that is not fossil (petroleum, natural gas, coal), but also does not compete with the food or feed demand. Therefore, in this proposal, we omit the use of first generation substrates such as sugary crops (sugar beets), or starch-containing biomasses (maize, cereals).
