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The United Kingdom Research and Innovation (UKRI) Global Challenges Research Fund (GCRF) aimed to address global challenges to achieve the United Nations (UN) Sustainable Development Goals through 12 interdisciplinary research hubs. This research documents key lessons learned around working with Theory of Change (ToC) to guide Monitoring, Evaluation and Learning (MEL) within these complex research for development hubs. Interviews and document reviews were conducted in ten of the research...

Research for development (R4D) funding is increasingly expected to demonstrate value for money (VfM). However, the dominance of positivist approaches to evaluating VfM, such as cost-benefit analysis, do not fully account for the complexity of R4D funds and risk undermining efforts to contribute to transformational development. This paper posits an alternative approach to evaluating VfM, using the UK’s Global Challenges Research Fund and the Newton Fund as case studies. Based on a...

The complexity of issues addressed by research for development (R4D) requires collaborations between partners from a range of disciplines and cultural contexts. Power asymmetries within such partnerships may obstruct the fair distribution of resources, responsibilities and benefits across all partners. This paper presents a cross-case analysis of five R4D partnership evaluations, their methods and how they unearthed and addressed power asymmetries. It contributes to the field of R4D...

Research for development (R4D) aims to make a tangible difference to development challenges, but these effects typically take years to emerge. Evaluation (especially impact evaluation) often takes place before there is evidence of development impact. In this paper, we focus on opportunities for assessing the potential for impact at earlier stages in the research and innovation process. We argue that such a focus can help research programme managers and evaluators learn about the...

When funders aren’t accountable for impact, it ruins the party for everyone.

Considering Systems Thinking (ST) as a cognitive skill can create greater acceptability of and openness to the discipline from practitioners and researchers outside operations research and management science. Rather than associating ST with frameworks and methodologies, ST as a cognitive skill can help popularize and democratize the discipline. This paper highlights how the conceptual lens of Holistic Flexibility can help practitioners deploy ST as a cognitive skill without the application...

Scholarly attention in innovation in the public sector is growing rapidly, provoking analytical complexity. We developed a systematic literature review about Public Sector Innovation (PSI), analysing 169 articles published between 2001 and 2021, using PRISMA. We present a comprehensive approach to PSI testing and empirically develop an analytical framework based on the most common combinations of the studied dimensions. Additionally, we propose three main research avenues for the future of...

“Hacking by the prompt”—writing simple yet creative conversational instructions in ChatGPT's message window—revealed many valuable additions to the evaluator's toolbox for all stages of the evaluation process. This includes the production of terms of reference and proposals for the dissemination of final reports. ChatGPT does not come with an instruction book, so evaluators must experiment creatively to understand its potential. The surprising performance of ChatGPT leads to the question:...

Innovation teams must navigate inherent tensions between different learning activities to produce high levels of performance. Yet, we know little about how teams combine these activities—notably reflexive, experimental, vicarious, and contextual learning—most effectively over time. In this article, we integrate research on teamwork episodes with insights from music theory to develop a new theoretical perspective on team dynamics, which explains how team activities can produce harmony,...

Digital transformation has become a buzzword that is permeating multiple fields, including public administration and management. However, it is unclear what is transformational and how incremental and transformational change processes are linked. Using the PRISMA method, we conduct a systematic literature review to structure this growing body of evidence. We identified 164 studies on digitally-induced change and provide evidence for their drivers, implementation processes, and outcomes. We...

Large language models (LLMs) are a type of generative artificial intelligence (AI) designed to produce text-based content. LLMs use deep learning techniques and massively large data sets to understand, summarize, generate, and predict new text. LLMs caught the public eye in early 2023 when ChatGPT (the first consumer facing LLM) was released. LLM technologies are driven by recent advances in deep-learning AI techniques, where language models are trained on extremely large text data from the...

Motivation This paper explores adaptive approaches to development programmes that aim at improving service provision in underperforming sectors in fragile and conflict affected states (FCAS). It does this through a case study of the Integrated Maji Infrastructure and Governance Initiative for eastern Democratic Republic of the Congo's (IMAGINE) public-private partnership model for water provision. Purpose The processes and decisions that culminated in IMAGINE's model emphasize the need...

In the past three decades nonviolent social protest has become the most reliable path to democracy. However, not all nonviolent mobilization campaigns succeed. To examine why some nonviolent campaigns are more successful than others, we analyze the use of a particular type of activist campaign tactic, the "dilemma action." The dilemma action is a nonviolent civil-disobedience tactic that provokes a "response dilemma" for the target. Collecting original data on dilemma actions during...

While many knowledge workers may fear that the rise of artificial intelligence (AI) will threaten their jobs, this article argues that small evaluation businesses should embrace AI tools to increase their value in the marketplace and remain relevant. In this article, consultants from a research, evaluation, and strategy firm, Intention 2 Impact, Inc., make a case for using AI tools to disrupt business as usual in evaluation from theoretical and practical perspectives. Theoretically, AI may...

Improved seed has the potential to boost crop yields and improve livelihoods for millions of small farmers in Malawi. Yet many small farmers are not using it. The reasons are numerous, but one of the most important is the prevalence of fake seed in the marketplace. Improved seed is more expensive to produce and sells for a much higher price than normal seed and grain, providing an incentive for unscrupulous traders to cheat farmers, using various tricks such as filling improved seed packets...

Diverse approaches to promoting disability inclusive employment aim to transform workplaces into truly inclusive environments, usually with intervention strategies targeting two main groups: employers and jobseekers with disabilities. However, they do not always consider other relevant stakeholders or address the relationships and interactions between diverse actors in the wider social ecosystem. These approaches often neglect deeper ‘vexing’ difficulties which block progress towards...

Political economy analysis (PEA) has been advanced as critical to understanding the political dimensions of policy change processes. However, political economy (PE) is not a theory on its own but draws on several concepts. Nannini et al, in concert with other scholars, emphasise that politics is characterised by conflict, contestation and negotiation over interests, ideas and power as various agents attempt to influence their context. This commentary reflects how Nannini et al wrestled with...

Systems approaches are currently being advocated and implemented to address complex challenges in Public Health. These approaches work by bringing multi-sectoral stakeholders together to develop a collective understanding of the system, and then to identify places where they can leverage change across the system. Systems approaches are unpredictable, where cause-and-effect cannot always be disentangled, and unintended consequences – positive and negative – frequently arise. Evaluating such...

Introduction:The Most Significant Change (MSC) technique is a complex-aware monitoring and evaluation tool, widely recognized for various adaptive management purposes. The documentation of practical examples using the MSC technique for an ongoing monitoring purpose is limited. We aim to fill the current gap by documenting and sharing the experience and lessons learned of The Challenge Initiative (TCI), which is scaling up evidence-based family planning (FP) and adolescent and youth sexual...