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Relationships between financial transparency, trust, and performance: an examination of donors’ perceptions
To better understand donors’ decisions within the nonprofit context, it is important to empirically attend to their perceptions of nonprofits. Drawing upon extant literature, a parsimonious conceptual model of donor perceptions is developed. Hypotheses derived from the model are empirically tested by means of structural equation modelling using 2017 survey data from 400 usable responses. The study finds positive associations between (1) perceptions of financial transparency and perceived performance, (2) perceived financial transparency and donor trust, and (3) donor trust and perceived performance. Different explanatory mechanisms are suggested to account for these findings. (1) could be explained by an ‘informational’ mechanism, whereas (2) and (3) could be explained by a ‘performative’ mechanism. The focus on donor perceptions has important implications for regulators when considering the assessment of nonprofit disclosure practices. The findings would also be valuable to nonprofits in developing strategies aimed at legitimising their operations by improving perceptions of their performance and trust in their ‘organisational brand’. By examining subjective perceptions of transparency and performance, this paper extends the nonprofit literature on donors’ perceptions, and adds a fresh perspective to the growing body of work on nonprofit transparency.
Towards next-gen smart manufacturing systems: the explainability revolution
The paper shares the author’s perspectives on the role of explainable-AI in the evolving landscape of AI-driven smart manufacturing decisions. First, critical perspectives on the reasons for the slow adoption of explainable-AI in manufacturing are shared, leading to a discussion on its role and relevance in inspiring scientific understanding and discoveries towards achieving complete autonomy. Finally, to standardize explainability quantification, a new Transparency–Cohesion–Comprehensibility (TCC) evaluation framework is proposed and demonstrated.
Network analysis of cross-income-level collaboration on multiple myeloma in sub-Saharan Africa
Cross-income-level collaboration (CILC) is crucial for developing global health approaches that benefit low- and middle-income countries (LMICs). Multiple myeloma (MM) is a representative example of a complex, understudied disease in sub-Saharan Africa (SSA). Based on publications, we developed a network analysis tool to assess scientific collaborations. Here, we present findings from a systematic analysis of publications retrieved from PubMed between January 2002 and June 2022. We evaluated individual institutional contributions and collaboration patterns using undirected weighted networks. Our findings reveal that intra-income-level collaborations dominate MM research in SSA, with high-income countries (HICs) primarily engaging with a few local institutions, mainly in South Africa and Nigeria. Increasing CILC is essential to advance research in this area. Our analysis tool provides insights into the collaboration strength, highlights gaps in the field and identifies leading institutions, ultimately aiming to support the development of more effective international collaboration and research strategies.
Modelling volumetric growth of emerging urban areas around new transit stations
Cities in developing countries are fast transforming from area-based expansion, representing spatial growth, to volumetric expansion, representing a higher skyline. Existing urban growth prediction models predict only spatial or two-dimensional growth. This paper demonstrates a volumetric urban growth model, incorporating the vertical expansion of urban areas. Two separate models were calibrated for spatial and built-up height growth, using historical growth patterns of transit-triggered new town development in India. The models were applied to upcoming transit station areas in India to predict the volumetric urban expansion for the next twenty years.
Building collaborative infrastructures for an interdisciplinary higher education master’s program
This paper examines the practices and importance of building a collaborative infrastructure in interdisciplinary education, using the context of the master’s program developed by the Interdisciplinary Consortium for Applied Research in Ecology and Evolution (ICARE) as a case study. The study focuses on two levels of collaborative infrastructure: The project organization and project practice of the ICARE program and the specific use of CoNavigator, a physical tool for interdisciplinary teaching, learning, and collaboration. The analysis explores the educational aspects of the ICARE program and investigates how the training teams (each consisting of a master’s student, supervisors, and mentors) within the project organized themselves and developed their collaboration methods. By examining the challenges faced by ICARE and the implications for its Trainees and stakeholders, this paper emphasizes the significance of prioritizing and developing robust and explicit collaborative infrastructures both at the program and institutional level, as the challenges identified in ICARE mirror those at higher institutional levels, where interdisciplinary activities are not sustained unless they are fully embedded in the visible and physical structures. The findings provide valuable insights for future interdisciplinary study programs and underscore the necessity of proactive infrastructure planning and implementation to support successful interdisciplinary teaching and learning practices.
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