This paper investigates the effects of the German national minimum wage introduction and its subsequent up-rating on job finding rates of unemployed welfare recipients. While the literature is inconclusive on the sign of overall employment effects of the minimum wage, the range of estimates suggests that if effects are negative, they are likely to be rather small. However, such overall effects may mask negative effects on employment prospects of unemployed welfare recipients, who tend to be only loosely attached to the labour market. For the analysis, this paper uses a sample of unemployed welfare recipients based on high-quality administrative data and employs a difference-in-differences strategy by exploiting regional variation in the bite of the minimum wage in order to estimate the effects of the minimum wage. While theoretically ambiguous, estimates show that minimum wages had a beneficial and rather homogeneous impact on job finding rates of unemployed welfare recipients. Sensitivity analyses highlight the robustness of these findings.

Evaluation teams have been critical to the success of Clinical and Translational Science Award (CTSA) programs funded by the National Center for Advancing Translational Sciences (NCATS). Given the limited resources often available to evaluation teams and the growing emphasis on impact evaluation and continuous quality improvement (CQI), CTSA programs may need to develop innovative strategies to build capacity for effectively implementing CQI and impact evaluation, while still tracking commonly reported metrics. To address this challenge, the Boston University (BU) Clinical and Translational Science Institute (CTSI) partnered with the BU Hariri’s Software and Application Innovation Lab (SAIL) to develop a web-based digital tool, known as TrackImpact, that streamlines data collection, saving significant time and resources, and increasing evaluation team capacity for other activities. Time and cost saving analyses are used to demonstrate how we increased evaluation team capacity by using this innovative digital tool.

The Duke Research Equity and Diversity Initiative (READI) was established in 2021 to engage Durham and surrounding communities in clinical research and build capacity to promote equitable access to research participation. Within READI, a voucher program was launched with the goals of increasing diverse participation in clinical research, improving community-partnered research, and enhancing community engagement. The vouchers leveraged a stand-alone, community-centered, outpatient research clinic, the Duke Research at Pickett (R@P) facility, which was originally opened to support COVID-19 trials. A formative evaluation of the voucher program was conducted with 3 voucher-awarded teams, READI personnel, and R@P staff. Data included 18 semi-structured interviews (n = 14) over two timepoints (Spring 2023, 2024). A rapid response analysis approach was used. Data indicate that READI voucher-awarded services were useful for voucher teams, with value for supporting community-engaged efforts, making research participation accessible, creating a community-centered and streamlined service facility, and personnel development benefits. Communication and flexibility of support services facilitated program implementation. Challenges occurred in service utilization logistics and incorporating community engagement into research support services. Ultimately, we find that a research support program with embedded community engagement support is feasible; this type of support can be integral in normalizing community-engaged research.

While community engagement (CE) has been increasing in the mental and behavioral health fields, evaluation of CE remains a challenge. Currently, there are no published evaluation tools that assess frequency of engagement, and many CE measures are not based on established engagement theories. Based on the International Association for Public Participation’s CE continuum, the CE team of the Mental and Behavioral Health Institute (MBHI) at a large pediatric hospital developed a system of measurement to describe frequency of engagement across eight initiatives. This tool, the Frequency of Active Community Engagement (FACE) measure, was administered to the leaders of each of the participating MBHI teams. FACE summarized CE frequencies for three target populations (youth, caregivers, and community members) for each team. Follow-up team meetings provided additional descriptive information for the development of CE goals. In this special communication, we describe this data collection approach, CE results, as well as future directions and potential uses for FACE as an evaluation tool.

Clinical and Translational Science Award (CTSA) hubs are charged with supporting high-quality, community-engaged clinical research; improving the effectiveness and efficiency of research; and facilitating dissemination and implementation of findings into practice, leading to improved clinical outcomes and public health. Traditional academic outcomes, such as publications, subsequent grant funding, and innovative research methods, have often been cited as evidence of hubs’ impacts. This article describes one CTSA’s approach to extending beyond traditional research outcomes to operationalizing and measuring impacts on health, health care, and public support of research. The approach replaces logic models with key driver diagrams, shifts responsibility for performance indicators to individual programs, consolidates and standardizes impact measures across programs, and adapts existing measures, such as the Translational Science Benefits Model. Measurement challenges include the extended time from supporting a study to its impact, reliance on investigators and partners to provide information, gaining access to organization-wide data, limited validated tools for this purpose, and the limits to documenting breadth of impact. Early lessons learned include the need to embrace various and often imperfect methods and measures, strategically engage partners for mutual benefit, support programs to adopt a continuous improvement mindset, and collaborate with leadership to prioritize and support change.

The usage of micromobility devices is growing to promote sustainable transportation, prompting manufacturers and regulators to enable its safe integration into urban environments. This has created the need for a tool to evaluate such devices. This paper presents the development of a versatile dynamometer design for verification and validation of micromobility devices by emulating real-world conditions while capturing vehicle and battery performance in real-time. A custom Graphical User Interface (GUI) is used to control and configure the system, as well as enabling the user to analyze and save incoming data. Six devices were chosen from distinct categories to collect data and demonstrate the capabilities and modularity of the dynamometer. The results reflect the ability of the dynamometer to be used for standardized testing of various micromobility devices.

The NIH’s Clinical and Translational Science Award (CTSA) program has placed greater emphasis on Continuous Quality Improvement (CQI) in recent years. Our institution’s CTSA-supported Institute for Clinical and Translational Research (ICTR) implemented a novel CQI process in response. This manuscript shares lessons learned from our implementation, reflecting a paradigm shift from managing an “evaluation program” to creating a process whose central goal is CQI. Our objective is to share these reflections to support other CTSA hubs’ efforts to successfully implement CQI programs. Key elements of our implementation included (1) establishing a shared understanding about CQI’s purpose; (2) leveraging a centralized management approach while addressing barriers to implementation; and (3) creating structures that foster collaboration. The CQI framework we chose, FACE (Focus, Analyze, Change, Evaluate), enabled us not only to improve the activities of ICTR modules but also, over time, to refine the CQI process itself. Through regular convenings of module leaders, the ICTR has sought to cultivate a culture of CQI as a dynamic, participatory process that supports mutual learning and collective problem-solving.

Virtual reality (VR) based product evaluation is a growing area of research, but has not yet been studied in the context of design education. In this study, participants evaluated four pairs of product design student models in physical and VR form using a custom VR application. The models included a variety of product types and a variety of prototyping materials. Participants rated the physical and VR models using a rubric adapted from a study of design student prototyping. Significant differences were found in VR versus physical ratings of some model evaluation categories, but only for certain products. The majority of participants preferred the physical model evaluation over the VR evaluation. Our findings suggest that VR product evaluation may be suitable for use in design education contexts, especially when budget or time for physical prototyping is limited.

Creativity is a fundamental aspect of design that can bring us novel and useful products. However, measuring creativity in design can always be challenging as there is a lack of standardized quantification methods and the inherent limitations of mathematical modelling. Previous approaches often rely on human experts to assess design creativity. Still, humans can be subjective and biased in their evaluation procedures. Recent advancements in AI have inspired us to integrate LLMs as evaluators in engineering design. In this study, we utilize LLMs to assess the novelty and usefulness of design ideas. We developed an evaluation procedure and tested it using design samples. Experimental results demonstrate that the proposed method enhances creativity evaluation capabilities across various LLMs and improves the alignment between LLM and human expert assessments.

Most innovation performance measurement approaches focus on ex-post outcome data, leaving decision-makers without timely guidance during the early phases of new product development (NPD). This gap is particularly critical in high-risk, high-regulation industries such as Urban Air Mobility (UAM), where long development cycles, regulatory hurdles, and uncertain user adoption demand real-time, in-process innovation metrics. In this paper, we propose a Desirability-Feasibility-Viability (DFV) framework that links key innovation phases (Discovery, Development, and Commercialization) to leading indicators that track innovation progress before market entry. Using UAM as an illustrative case study, we demonstrate how our framework enables stakeholders to navigate uncertainty, optimize resource allocation, and make data-driven innovation decisions.

Design method validation is fundamental to ensure that design methods achieve their objectives in the intended situations and are accepted in practice. Although various method validation approaches have been developed, there is still a lack of practical guidance for planning validation studies based on project characteristics. To address this, an intensity map of the validation effort is presented as the core of a scenario-based planning approach. It categorizes projects according to the novelty of the method and the state of research on the problem or the research area, enabling the required validation studies, their sequence and validation criteria to be identified. Thereby, researchers can plan validation studies and estimate the required effort situation-based, allowing for a better alignment with their individual project characteristics before starting studies.

This novel contributions reveal how environmental regulations drive engineering design costs, focusing on the emblematic case of packaging. Using a regulatory database and simulation-based modeling, we evaluate functional expansion as a key driver of cost escalation, identifying its volume effect (rising costs from added environmental functions) and scope effect (increased interdependencies among ecosystem actors). The findings offer a simulated cost envelope to support engineering design teams in their forecasts, but also underscore the hurdles of sustainably managing these regulatory-driven costs in the packaging product system, by benchmarking cost trajectories against sustainability metrics, such as carbon pricing.

This paper explores the multifaceted concept of design theories value, challenging traditional views of science and philosophy and proposing a novel framework for evaluation. Through critical analysis, considering design theories like C-K theory, PSI, GDT, and CDP, and insight from the history of science, we establish the need for a new value model of design theories that includes design-related and other general properties such as generativity, robustness, and impact on practice. We adapt a recently developed system value model (SVM) to consider the diverse perspectives of design theory stakeholders. Our framework is tested on the PSI theory, demonstrating its applicability. This paper redefines how we perceive and measure the value of design theories, offering insights that could influence future research and practice in design science.