Responsible AI (RAI) governance is increasingly understood not as a static checklist of principles, but as a dynamic process embedded in institutional, organisational, and sociotechnical contexts. While several ethical frameworks exist, translating high-level principles into situated organisational practices remains challenging. Empirical studies examining how public sector organisations operationalise RAI remain fragmented, limiting cumulative insights. To address this gap, we conduct a realist synthesis review of 21 empirical studies. Our analysis shows that similar interventions in different contexts activate distinct mechanisms and produce divergent outcomes with varying degrees of alignment to RAI principles. From these variations, we identify three cross-cutting dynamics explaining outcomes: organisational embeddedness, power- expertise tensions, and trust-transparency relationships. Together, we term it the situated dynamics of RAI governance. This approach moves beyond asking whether interventions “work” to explain why similar interventions succeed in some contexts and fail in others.

Sustainable urban transport is a complex challenge requiring innovation in technologies, culture, and policies. However, the relatively weak conceptualisation of agency in the transitions literature limits the usefulness of this approach for the governance of urban transport. The objective of this chapter is to contribute to the conceptualisation of agency in the multilevel perspective of sustainability transitions. We propose that two types of actors exercise agency to foster innovation: technology constituencies, which promote the adoption of specific technologies by citizens, businesses, or governments, and instrument constituencies, which promote the adoption of specific policy instruments. We posit that the two constitute distinct, albeit possibly overlapping, actors and that their relationships help better understand and explain how innovations evolve. We discuss the implications of this distinction for the governance of urban transport and argue that the presence of instrument and technology constituencies, and their relationships, should be examined more closely in future research.

Transnational municipal networks (TMNs) such as C40 or ICLEI have been posited to foster city-to-city learning in accelerating climate change mitigation and, thereby, facilitating the transition to net-zero greenhouse gas emissions. However, the existing literature on the role of climate networks has hardly examined the relationship between membership and climate change mitigation outcomes and impact, without which it is premature to be optimistic about TMNs role in the net-zero transition. In this article, we address this gap through a mixed methods analysis in the case of the C40 cities initiative. We combine a staggered difference-in-differences regression to shed light on the relationship between membership in the C40 initiative and carbon dioxide (CO₂) emissions during 2002–18 in over 700 OECD cities with a qualitative cross-case analysis of Bogotá, Colombia and Copenhagen, Denmark to unpack how and when the C40 initiative influences climate action at the city level. Results show that there is no statistically significant relationship between C40 membership and CO₂ emissions, indicating that cities in the C40 initiative may not have reduced CO₂ emissions more than other OECD cities, after controlling for socioeconomic characteristics, weather, country characteristics, city fixed effects, time fixed effects, and city-specific annual time trends. Furthermore, the complementary qualitative analysis showed the C40 network's direct intervention is limited to increasing or maintaining the ambition of cities; the network was found to have limited influence on city-level policy planning and implementation. There is a need to further study and address local policy implementation for realizing net-zero in relation to TMN membership.

Despite the recognition that policy evaluations are inherently normative as they are shaped by political and social values, justice is rarely addressed systematically in policy evaluation practice or research. By overlooking structural inequities and failing to scrutinize power dynamics, this omission risks hindering accountability, legitimizing injustice, and inhibiting policy learning. To help bridge this gap, we build on the policy success heuristic, which is a multidimensional approach for assessing programmatic, process, and political outcomes of public policy. Drawing on the philosophical literature on justice, we link three prominent categories—distributive, procedural, and recognition justice—with the dimensions of policy success. Based on this linkage, we propose a reflective framework that uniquely integrates justice principles into each dimension of the policy success heuristic. The framework can be applied ex-ante or ex-post to assess whether a policy is, or is likely to be, not only successful but also just, contributing to navigating the is/ought distinction at the heart of policy evaluation.

Innovation in public policy is a rapidly expanding field, highlighting its critical role in addressing complex societal challenges. This bibliometric review (n = 17,264) synthesizes over 50 years of scholarship, systematically identifying key gaps, including conceptual fragmentation, limited theoretical engagement, methodological conservatism, and geographic and sectoral imbalance, and underutilization of the comparative perspective. These challenges constrain the field’s ability to address pressing global issues such as climate change adaptation, digital transformation, economic inequality, and the energy transition. This study proposes a comprehensive research agenda to bridge these gaps and move the field from niches toward more inclusive, integrative, and rigorous mainstream scholarship.

Although novel policies will be especially important for addressing grand societal challenges, how the digital transition influences the ability of governments to adopt new policies remains unclear. In this study, the relationship between digitization and policy innovation is explored in order to understand how the two might be related. Specifically, media narratives are studied in the case of the ongoing rollout of smart metering in India to assess whether and how this instance of digital governance has been discussed in the news. To do so, 370 articles in the largest English language daily newspaper in India have been analyzed using topic modelling and sentiment analysis. Findings highlight the polysemic nature of smart metering and its ability to support highly (re-)configurable and targeted policy designs, as well as some resistance to this policy innovation thus far. Implications of the findings are discussed for theory and research on digital governance and policy innovation.

This editorial marks the relaunch of the Policy Innovation section of this journal, responding to the urgent need for innovative public policy amid global challenges such as climate change, economic inequality, and technological disruption. It reflects on the journal’s pivotal contributions to the subject and underscores the importance of comparative analysis in driving policy innovation. The section invites submissions that push theoretical and methodological boundaries, expand research into underexplored geographies and domains, and tackle the implications of policy innovation for equity, fairness, and justice. By broadening the scope of policy innovation, the journal aims to inspire cutting-edge, rigorous, and actionable research.

Understanding what conditions promote or hinder energy affordability in energy transitions is crucial for coal and carbon-intensive regions (CCIRs) dealing with the trade-off between phasing out fossil fuels and deepening social inequalities. While previous studies have included household and national-level conditions, this paper addresses the research gap covering regional-level conditions by drawing from regional energy governance, energy justice, and sociotechnical transition frameworks. A mixed-method approach consisting of a fuzzy-set qualitative comparative analysis and case-study analysis is applied to 14 CCIRs in Europe, Asia, and North America. Results show that energy affordability in CCIRs is influenced by combinations of regional and (inter)national conditions. Whereas the existing literature and transition policies do not differentiate between the CCI sector's transition type, this paper highlights that conditions underlying energy (un)affordability differ when the CCI sector is phased out or has the option to transition. Based on the findings, this study calls for a multi-level governance approach to alleviating and preventing energy unaffordability and recommends that policy mixes like the EU Just Transition Fund consider the different types of CCIR transitions.

Policy innovation is considered important for addressing major challenges such as climate change and the sustainable energy transition. Although policy learning is likely to play a key role in enabling policy innovation, the link between them remains unclear despite much research on both topics. To address this gap, we move beyond a binary treatment of policy innovation and differentiate policy problem innovation from policy instrument innovation and policy process innovation. Subsequently, we synthesise the literature on policy learning with the research on the multiple streams framework (MSF), a well-known lens for explaining policy innovation. Like earlier policy learning studies, we distinguish several types of learning by posing the key questions of learning, but in the context of each stream of the MSF: who learns (actors), what (beliefs), how (modes), and to what effect (ripening). This new conceptualisation clarifies the relationship of each type of policy learning to the varieties of policy innovation. Further, it indicates that policy learning is likely to result in policy innovation if and only if it influences the coupling among the three streams during a window of opportunity – through policy entrepreneurship – and not otherwise. We conclude with the implications of this study for future research on policy innovation, policy learning, and the MSF.

Although causal evidence synthesis is critical for the policy sciences—whether it be analysis for policy or analysis of policy—its repeatable, systematic, and transparent execution remains challenging due to the growing volume, variety, and velocity of policy-relevant evidence generation as well as the complex web of relationships within which policies are usually situated. To address these shortcomings, we develop a novel, semi-automated approach to synthesizing causal evidence from policy-relevant documents. Specifically, we propose the use of natural language processing (NLP) for the extraction of causal evidence and subsequent homogenization of the text; causal mapping for the collation, visualization, and summarization of complex interdependencies within the policy system; and graph analytics for further investigation of the structure and dynamics of the causal map. We illustrate this approach by applying it to a collection of 28 articles on the emissions trading scheme (ETS), a policy instrument of increasing importance for climate change mitigation. In all, we find 300 variables and 284 cause-effect pairs in our input dataset (consisting of 4524 sentences), which are reduced to 70 unique variables and 119 cause-effect pairs after homogenization. We create a causal map depicting these relationships and analyze it to demonstrate the perspectives and policy-relevant insights that can be obtained. We compare these with select manually conducted, previous meta-reviews of the policy instrument, and find them to be not only broadly consistent but also complementary. We conclude that, despite remaining limitations, this approach can help synthesize causal evidence for policy analysis, policy making, and policy research.

Research on the economic burden of air pollution has focused primarily on its macroeconomic impact. However, as some studies have found that air pollution can lead to avoidance behavior–for example, reducing the time spent outdoors–we hypothesize that it can also influence consumer spending activity. We combine high frequency data on ozone and fine particulate pollution with daily consumer spending in brick-and-mortar retail in 129 postal codes in Spain during 2014 to estimate the association between the two. Using a linear fixed effects model, we find that a 1-standard deviation increase in ozone concentration (20.97 μg/m3) is associated with 3.9 percent decrease in consumer spending (95% CI: -0.066, -0.012; p<0.01). The association of fine particulate matter with consumer spending is, however, not statistically significant (β: 0.005; 95% CI: -0.009, 0.018; p>0.10). Further, we do not observe a sufficiently strong bounce-back in consumer spending in the day–or even the week–following higher ozone concentration. Also, we find that the relationship between ozone concentration and consumer spending is heterogeneous, with those aged below 25 and those aged 45 or above exhibiting stronger negative association. This research informs policymakers about a plausibly unaccounted cost of ambient air pollution, even at concentrations lower than the WHO air quality guideline for short-term exposure.

Introduction: The target of universal access to affordable, reliable, and modern energy services—key for individual, social, and economic well-being—is unlikely to be achieved by 2030 based on the current trend. Public policy will likely need to play a key role in accelerating progress in this regard. Although perspectives from the field of policy studies can support this effort, to what extent they have been employed in the literature on energy access remains unclear. Methods: This study analyzed nearly 7,500 publications on energy access through a combination of bibliometric review and computational text analysis of their titles and abstracts to examine whether and how they have engaged with public policy perspectives, specifically, policy process research, policy design studies, and the literature on policy evaluation. Results: We discovered 27 themes in the literature on energy access, but public policy was not among them. Subsequently, we identified 23 themes in a new analysis of the 1,751 publications in our original dataset, mentioning “policy” in their title or abstract. However, few of them engaged with public policy, and even those that did comprised a rather small share of the literature. Finally, we extracted phrases pertaining to public policy in this reduced dataset, but found limited mention of terms related to the policy process, policy design, or policy evaluation. Discussion: While to some extent this might reflect the multidisciplinary nature of the research on energy access, a manual review of the abstracts of select publications corroborated this finding. Also, it shed light on how the literature has engaged with public policy and helped identify opportunities for broadening and deepening policy relevant research on energy access. We conclude that, despite their relevance to energy access, public policy perspectives have infrequently and unevenly informed existing research on the topic, and call on scholars in both communities to address this gap in the future.

Electricity access is an important issue and building capacity for it requires drawing relevant lessons from past policies. In this study, we evaluate the effect of the Jyotigram Yojana, or the lighted village scheme, a supply-side policy intervention during 2003–08 to increase rural electricity access in Gujarat, India. We hypothesize that policy implementation is associated with increased electricity consumption. To test this hypothesis, we exploit variation in the timing of policy implementation at the village level, and use a generalized difference-in-differences strategy for identification. Further, we use night-time luminosity measured through remote sensing as a proxy for electricity consumption, and control for weather, village fixed effect, year fixed effect, and village or administrative block specific time trend. We find that while the overall effect of the policy on night-time luminosity was not statistically significant, the effects were likely heterogeneous, with the night-time luminosity increasing in some districts after policy implementation and decreasing in others. We conclude that the policy might have had a re-distributive effect on electricity access or consumption and recommend adopting a more holistic approach – incorporating both supply-side and demand-side measures – to increase electricity access.

As policy innovation is essential for upscaling responsible innovation, understanding its relationship to value change(s) occurring or sought in sociotechnical systems is imperative. In this study, we ask: what are the different types of values in the policy process? And, how does value change influence policy innovation? We propose a disaggregation of values and value change based on a four-stream variant of the multiple streams framework (MSF), a conceptual lens increasingly used for explaining policy innovation in sociotechnical transitions. Specifically, we posit that the values that ‘govern’ problem framing, policy design, political decision making, and technological diffusion can evolve relatively independently, potentially leading to value conflict. We apply this framework to the ongoing case of the market-based economic dispatch of electricity (MBED) policy in the Indian energy transition using content analysis. We find that the MBED scheme—with its emphasis on efficiency (problem), economic principles (policy), low-cost dispatch (technology), and centralization (politics)—attempts value change in each stream. Each instance of value change is, however, widely contested, with the ensuing value conflicts resulting in significant opposition to this policy innovation. We conclude that a disaggregation of values based on the MSF can facilitate an analysis of value change and value conflict in sociotechnical transitions and lay the foundation for systematically studying the relationships among technological change, value change, and policy change.

A transition to sustainable energy will require not only technological diffusion and behavioral change, but also policy innovation. While research on energy transitions has generated an extensive literature, the extent to which it has used the policy innovation perspective – entailing policy entrepreneurship or invention, policy diffusion, and policy success – remains unclear. This study analyzes over 8000 publications on energy transitions through a bibliometric review and computational text analysis to create an overview of the scholarship, map conceptual engagement with public policy, and identify the use of the policy innovation lens in the literature. We find that: (i) though the importance of public policy is frequently highlighted in the research, the public policy itself is analyzed only occasionally; (ii) studies focusing on public policy have primarily engaged with the concepts of policy mixes, policy change, and policy process; and (iii) the notions of policy entrepreneurship or invention, policy diffusion, and policy success are hardly employed to understand the sources, speed, spread, or successes of energy transitions. We conclude that the value of the policy innovation lens for energy transitions research remains untapped and propose avenues for scholars to harness this potential.

Although cities have risen to prominence as climate actors, emissions’ data scarcity has been the primary challenge to evaluating their performance. Here we develop a scalable, replicable machine learning approach for evaluating the mitigation performance for nearly all local administrative areas in Europe from 2001-2018. By combining publicly available, spatially explicit environmental and socio-economic data with self-reported emissions data from European cities, we predict annual carbon dioxide emissions to explore trends in city-scale mitigation performance. We find that European cities participating in transnational climate initiatives have likely decreased emissions since 2001, with slightly more than half likely to have achieved their 2020 emissions reduction target. Cities who report emissions data are more likely to have achieved greater reductions than those who fail to report any data. Despite its limitations, our model provides a replicable, scalable starting point for understanding city-level climate emissions mitigation performance.

This chapter examines whether and how the difference in the location of evaluators influences the choice of approaches, tools, and procedural issues in policy evaluation. It illustrates the differences in these dimensions of evaluation through a discussion of external and internal evaluation in the case of the Asian Development Bank and multilateral development aid. External evaluators may have a broader perspective and independence, but internal evaluators may have higher-information processing capacity and access to specialized information and records, which external evaluators may not. Impact evaluation is primarily concerned with causal attribution of changes in outcomes to the program or policy. While internal evaluators might be more interested in specific cases, external evaluators often use such techniques to generalize across cases.

While the emergence of big data creates several opportunities for governance and public policy, new capabilities, processes, standards, strategies, and technologies will be essential for deriving value from big data while addressing issues and mitigating risks posed by it. Arguably, above all, these will require the integration of big data analytics in public policy pedagogy. In this chapter, we examine whether public policy education has kept pace with the growth of big data research in the field, with a specific focus on the Asian context. We start by identifying prominent themes in research on big data in governance and public policy. We supplement that with an analysis of academia’s response by examining the prevalence of big data teaching in public policy programs. Based on our analysis, we highlight the current geographic and institutional dominance in research and teaching on the topic, and conclude with key lessons for the design, content, and delivery of pedagogy on big data in public policy.

While the emergence of big data raises concerns regarding governance and public policy, it also creates opportunities for diversifying the toolkit for analysis for the policy sciences as a whole, i.e., research concerning policy analysis as well as policy studies. Further, it opens avenues for practice, which together with research requires adaptation in teaching curricula if policy education were to remain relevant. However, it is not clear to what extent this opportunity is being realized in public policy research and teaching. In this study, we examine the prevalence of big data analytics in public policy research and pedagogy using bibliometric analysis and topic modeling for the former, and content analysis of course titles and descriptions for the latter. We find that despite significant scope for application of various big data techniques, the use of these analytic techniques in public policy has been largely limited to select institutions in a few countries. Further, data science has received limited attention in policy pedagogy, once again with significant geographic variation in its prevalence. We conclude that, to stay relevant, the policy sciences need to pay more attention to the integration of big data techniques in policy research, pedagogy, and thereby practice.

Although the diffusion of policy innovations can promote sustainability, how this process can be accelerated remains unclear. I address this gap by conceptualizing policy transfer and policy diffusion using the multiple streams framework (MSF) and developing hypotheses to connect them. I apply this theorization to explain the limited spread of the energy conservation building code (ECBC) in India by combining a process trace of policy adoption in the embedded case of Andhra Pradesh with a dyadic event history analysis of state-level diffusion during 2012-18. The data for this study are collated from official statistics, elite interviews, news reports, policy documents, and secondary literature. The qualitative analysis shows that policy transfer to Andhra Pradesh occurred when external influence and prior adoption elsewhere were used by a policy entrepreneur to exploit a window of opportunity and couple problem, policy, and politics in the state; the dyadic analysis demonstrates that policy diffusion was influenced by the interaction among the structural characteristics of the problem, policy, and politics streams. I conclude with the implications for research on policy diffusion and the MSF as well as the relevance of the findings for promoting policy innovation for a sustainable energy transition.