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Realist evaluation and experimental designs are both well-established approaches to evaluation. Over the past 10 years, realist trials—evaluations purposefully combining realist evaluation and experimental designs—have emerged. Informed by a comprehensive review of published realist trials, this article examines to what extent and how realist trials align with quality standards for realist evaluations and randomized controlled trials and to what extent and how the realist and trial aspects...

Evaluators are interested in capturing how things causally influence one another. They are also interested in capturing how stakeholders think things causally i...

This article assesses the application of the problem driven iterative adaptation (PDIA) approach to public financial management reform in six African countries. It draws on primary data collected using a mix of interviews, overt participation observations and a short survey. PDIA responds to shortcomings in orthodox approaches to reform and technical assistance in developing countries. It stresses local solutions to local problems, achieved through experimentation and adaptation. The...

Responses to sustainability challenges are not delivering results at the scale and speed called for by science, international agreements, and concerned citizens. Yet there is a tendency to underestimate the large-scale impacts of small-scale, local, and contextualized actions, and particularly the role of individuals in scaling transformations. Here, we explore a fractal approach to scaling sustainability transformations based on “universal values.” Universal values are proposed as intrinsic...

The idea that technologies can change moral beliefs and practices is an old one. But how, exactly, does this happen? This paper builds on an emerging field of inquiry by developing a synoptic taxonomy of the mechanisms of techno-moral change. It argues that technology affects moral beliefs and practices in three main domains: decisional (how we make morally loaded decisions), relational (how we relate to others) and perceptual (how we perceive situations). It argues that across these three...

Participatory action research (PAR) is an approach to research that prioritizes the value of experiential knowledge for tackling problems caused by unequal and harmful social systems, and for envisioning and implementing alternatives. PAR involves the participation and leadership of those people experiencing issues, who take action to produce emancipatory social change, through conducting systematic research to generate new knowledge. This Primer sets out key considerations for the design of...

Achieving impact through research for development programmes (R4D) requires engagement with diverse stakeholders across the research, development and policy divides. Understanding how such programmes support the emergence of outcomes, therefore, requires a focus on the relational aspects of engagement and collaboration. Increasingly, evaluation of large research collaborations is employing social network analysis (SNA), making use of its relational view of causation. In this paper, we use...

Large publicly funded programmes of research continue to receive increased investment as interventions aiming to produce impact for the world’s poorest and most marginalized populations. At this intersection of research and development, research is expected to contribute to complex processes of societal change. Embracing a co-produced view of impact as emerging along uncertain causal pathways often without predefined outcomes calls for innovation in the use of complexity-aware approaches to...

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...

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...