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Societal challenges such as migration, poverty, and climate change can be considered ‘wicked problems’ for which no optimal solution exists. To address such problems, public administrations increasingly aim for data-driven policy making. Data-driven policy making aims to make optimal use of sensor data, and collaborate with citizens to co-create po...
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... by Janssen and Helbig [2], we distinguish three phases: predictive and problem definition, design and experimentation, and evaluation and implementation. Table 3 elaborates innovations and impact per phase of the Policy Lab approach, and identifies challenges. The first phase of policy making -predictive and problem definition, (real-time) sensor data is used, comprising physical sensor data such as roadside traffic data, and virtual data such as social media data. ...Similar publications
The purpose of this Guide is to provide guidelines for researchers on how to develop and organise co-creation. This Guide includes instructions for the participating researchers and for the facilitators. The Guide describes the main aspects of co-creation that must be considered when similar processes are organised. Co-creation is considered in thi...
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... On the other hand, citizens can judge whether the policies and the responsible party serve them well based on indicators [14]. Data-driven policymaking, emphasizes the use of data analytics, big data, and open data across the three successive stages of policymaking: agenda setting, policy implementation, and policy evaluation [15]. Data-driven policies can boost transparency, legitimacy, and efficiency. ...
... Data-driven policymaking builds on the concept of evidencebased policymaking, which considers three types of evidence: "systematic ('scientific') research, program management experience ('practice'), and political judgement" [15, p. 1]. Consequently, it also faces several challenges of evidence-based policymaking extended by data-related issues, such as: -a shift in culture and process of policymaking [19], -social inclusion, involvement, and co-creation by citizens and stakeholders [15], -the growing number of necessary data sources and involved stakeholders with increasing policy complexity [20,21], -lacking skills of policymakers to draw conclusions from data [5]. ...
This paper identifies and validates the challenges hindering the integration of circular economy into evidence-based policy making, and proposes an outlook for enhancing the effective use of circular economy monitors. It highlights the limitations of current circular economy monitoring systems, which often fail to transform circular economy information into actionable knowledge for policy makers. Using the echelon Design Science Research approach, which divides projects into manageable ‘echelons’ to tackle complex socio-technical problems, this study focuses on the problem analysis echelon. Through 13 semi-structured interviews with intended users and an extensive literature review, the study identifies and validates five challenges to embedding circular economy in policy-making. These challenges are the delayed benefits of circular economy actions, fragmented policy coordination, the lack of a policy agenda for higher R strategies, the complexity of circular economy implementation, and the gap between theoretical frameworks and practical policy needs. This analysis is grounded in the theory of effective use as our Kernel Theory. To address the ineffective use of circular economy monitors, the study proposes an outlook of design requirements and design principles. This paper contributes to the literature on policy monitoring frameworks and circular economy policymaking by delineating a validated problem space that future researchers can use to improve the effective use of circular economy monitors in policymaking.
... According to contemporary research on the topic, big data may be utilized in various ways to enhance public sector results (Dritsakis et al., 2018;Lee, 2020;Suominen & Hajikhani, 2021). These include enhancing government efficiency (Maciejewski, 2017), effectiveness (Concilio et al., 2019), and openness (van Veenstra & Kotterink, 2017), making policy decisions with more knowledge (Blum, 2018), and delivering better services based on improved insight into citizens' needs and wants (Shah et al., 2021). As noted by academicians, big data utilization has enormous promise in public policy sectors, including health care , the economy (Anejionu et al., 2019), the environment (Miljand, 2020), and transportation (Zannat & Choudhury, 2019). ...
Big data analytics (BDA) enhances knowledge and decision-making. Despite its importance, the connection between technical progress and political change is neglected in the administrative process. Most studies focus on e-government, e-governance, and how technology can improve existing operations of the bureaucracy. However, this article aims to explore the potential of BDA for public policy systems and provide a linkage for the transformation toward digital and smart governance using preferred reported items for systematic review and meta-analysis (PRISMA) approach to reveal the relevant documents and narrative review approach to interpret the application of BDA at each step of the public policy system. In addition, this study identifies several common public policy-related big data sources and techniques that could be used at the various stages of the public policy process. This study argues that BDA has the potential to be used for policy formulation in the four main phases—planning, design, service delivery, and evaluation. Most studies confirm its potential in the policy process for taxation, health, education, transportation, law, economy, and social system. This study reveals that it is also suitable for public policy execution stages, such as public supervision, public regulation, service delivery, and policy feedback. Previous studies have indicated that the application of BDA can transform traditional or manual governance systems into digital and smart governance. We contend that the policy cycle should be seen as a dynamic and iterative process characterized by continuous evolution. Though each step of transformation has its unique challenges in handling BDA and maintaining the Information and Communication Technology (ICT) infrastructure, it can ensure an accurate, prompt, and context-oriented public policy system. These insights provide a novel outlook on effectively managing the interplay between innovation and traditional approaches in the realm of public policy development.
... These policies may focus on financial product development, interest rate structures, and lending criteria. Community-driven policies align the bank's operations with the genuine demands of the community, making financial services more accessible, relevant, and impactful (Choi et al., 2014;Chague et al., 2015;Svirydzenka, 2016;Veenstra & Kotterink, 2017;Palmieri et al., 2018;Whitehouse et al., 2018). ...
Local community representation plays a pivotal role in shaping the governance structures and decision-making processes of rural and community banks (RCBs) in developing countries. This systematic review aims to comprehensively assess the impact of community representation on RCBs within the context of developing nations, shedding light on the dynamics that influence the effectiveness of local voices in governing these essential financial institutions. Employing a rigorous methodology encompassing database searches, inclusion criteria, and quality assessment, this review synthesizes a diverse range of empirical studies, theoretical frameworks, and case examples. The conceptual framework explores the diverse forms of community representation within RCBs and examines the theoretical foundations underpinning their influence in developing country settings. Drawing on an extensive body of literature, this review investigates how community representation affects governance structures, focusing on the roles, powers, and structural changes that emerge within RCBs in the context of resource-constrained economies. Through an exploration of future research directions and identified gaps, the review offers insights into emerging trends and the pressing need for further investigations in this critical area, aiming to contribute to the sustainable development goals of these nations. The findings of this systematic review provide valuable insights into the interplay between local community representation and RCB governance in developing countries, offering practical recommendations for policymakers, practitioners, and scholars working to enhance the role of community voices in the decision-making processes of essential financial institutions that serve as lifelines in these economies. By synthesizing existing knowledge and highlighting areas for improvement, this review informs discussions on promoting financial inclusion and economic development in the developing world.
... Today more than ever, it is evident that data can play a role when designing, implementing and evaluating public policies (Verstraete et al., 2021;Aragona & De Rosa, 2019;van Veenstra & Kotterink, 2017). While their importance is highlighted in evidence-based approaches (Brunswicker et al., 2019), public policy literature identifies barriers to data understanding, interpretation, and operationalisation (Oliver et al., 2014;. ...
... From a broad organisational perspective, data-informed decision-making (Chaffey & Wood, 2005) -implying awareness of the current situation and performance (van Veenstra & Kotterink, 2017;Veale et al., 2018) -can play a role in public sector innovation, contributing to developing multi-level and cross-silos actions associating PA's needs to available approaches, technologies, and trends. Data serves as a valuable resource, supporting evidence-based policymaking and driving reflection and learning through action (Concilio & Pucci, 2021, p. 15). ...
... Currently, there is a significant focus on exploring novel interdisciplinary methodologies to harness the potential of data-driven and data-aware policymaking. These endeavours are currently under investigation and experimentation and aim to deliver timely and reliable information (van Veenstra & Kotterink, 2017). In line with this stream of research, the study reports on developing and validating a narrative model to translate data into policy-relevant information. ...
Today more than ever, it is evident the role that data can play when designing policies. Not only can understandable data orient better strategies, but they can also enable reflexive practices within Public Administrations, giving directions for knowledge management and smarter governance. However, multiple gaps concur to affect data understanding and interpretation, hindering their subsequent translation into policy-valuable information. To tackle challenges related to data interpretation and usage, the article (i) illustrates a narrative approach for building profiles of cities as narrative feedback from sets of data and (ii) investigates their potential as a (self-)evaluation and a decision-making support device. The feedback structure relies on the conceptual model built for the DIGISER Project, which investigated multidimensional digital transition processes across European cities. Dynamic feedback retrieves data from the project dataset, translating them into discursive form. The effectiveness of the approach and its device is validated through a qualitative enquiry on a textual excerpt provided to three different departments of one of the cities that participated in the survey. The study corroborates that designing narrative feedback as semantic interpretations can trigger understanding, (self-)reflection and support policy change, informing policy formulation and facilitating cross-silo interactions across administrative units engaged in digital transformation processes.
... These policies may focus on financial product development, interest rate structures, and lending criteria. Community-driven policies align the bank's operations with the genuine demands of the community, making financial services more accessible, relevant, and impactful (Choi et al., 2014;Chague et al., 2015;Svirydzenka, 2016;Veenstra & Kotterink, 2017;Palmieri et al., 2018;Whitehouse et al., 2018). ...
Local community representation plays a pivotal role in shaping the governance structures and decision-making processes of rural and community banks (RCBs) in developing countries. This systematic review aims to comprehensively assess the impact of community representation on RCBs within the context of developing nations, shedding light on the dynamics that influence the effectiveness of local voices in governing these essential financial institutions. Employing a rigorous methodology encompassing database searches, inclusion criteria, and quality assessment, this review synthesizes a diverse range of empirical studies, theoretical frameworks, and case examples. The conceptual framework explores the diverse forms of community representation within RCBs and examines the theoretical foundations underpinning their influence in developing country settings. Drawing on an extensive body of literature, this review investigates how community representation affects governance structures, focusing on the roles, powers, and structural changes that emerge within RCBs in the context of resource-constrained economies. Through an exploration of future research directions and identified gaps, the review offers insights into emerging trends and the pressing need for further investigations in this critical area, aiming to contribute to the sustainable development goals of these nations. The findings of this systematic review provide valuable insights into the interplay between local community representation and RCB governance in developing countries, offering practical recommendations for policymakers, practitioners, and scholars working to enhance the role of community voices in the decision-making processes of essential financial institutions that serve as lifelines in these economies. By synthesizing existing knowledge and highlighting areas for improvement, this review informs discussions on promoting financial inclusion and economic development in the developing world.
... Until very recently, despite a significant body of literature on epidemiological models (survey papers (Shankar et al. 2021) and books (Martcheva 2015)), policy informatics to control the effects of such epidemics and to mitigate the effects of policy interventions is relatively nascent ( Puron-Cid et al. 2016, Veenstra and Kotterink 2017, Wan 2022. The recent work on the automatic control of epidemics and optimization has focused on the use of either greedy algorithms (Minutoli et al. 2020) or reinforcement learning frameworks such as Deep Q-learning variants ( Khadilkar et al. 2020, Ohi et al. 2020, Colas et al. 2021, Bampa et al. 2022. ...
To mitigate the impact of the pandemic, several measures include lockdowns, rapid vaccination programs, school closures, and economic stimulus. These interventions can have positive or unintended negative consequences. Current research to model and determine an optimal intervention automatically through round-tripping is limited by the simulation objectives, scale (a few thousand individuals), model types that are not suited for intervention studies, and the number of intervention strategies they can explore (discrete vs continuous). We address these challenges using a Deep Deterministic Policy Gradient (DDPG) based policy optimization framework on a large-scale (100,000 individual) epidemiological agent-based simulation where we perform multi-objective optimization. We determine the optimal policy for lockdown and vaccination in a minimalist age-stratified multi-vaccine scenario with a basic simulation for economic activity. With no lockdown and vaccination (mid-age and elderly), results show optimal economy (individuals below the poverty line) with balanced health objectives (infection, and hospitalization). An in-depth simulation is needed to further validate our results and open-source our framework.
... Within a wider scope, McAuliffe et al. (2022) reviewed the use of data in debates on and governance of migration. The authors concluded that the world has well and truly entered a data-driven age with a movement from evidence-based policy to data-driven policy (van Veenstra & Kotterink, 2017). "However, in moving in this direction we risk becoming more and more distant from the underlying meaning of data variables, thereby increasing the risk of ineffective data-driven policy that misunderstands and misinterprets social phenomena such as migration" (McAuliffe et al., 2022, p. 4). ...
MIrreM is a Coordination and Support Action commissioned to produce a handbook on the improvement of measuring irregular migration as well as a handbook on regularisation – two hitherto loosely connected policy domains. The project consortium unites a wide range of partners from research and civil society and involves external stakeholders in a collaborative manner – each from discrete professional fields with specific expertise. The implementation of project purposes occurs in independent but nested work packages and tasks – among the analysis of political handling of irregular migration issues, the inventory and advancement of data in irregular migration and the characteristics of migrants in an irregular situation, and the design of policy options that offer a way out of an irregular situation. Obviously, the MIrreM mission is exciting and supporting policy changes in the highly contested field of irregular migration governance.
Considering the diversity of involved actors and the heterogeneity of pursued purposes, this paper formulates a common conceptual framework that serves the goal of providing an orientation to reach a shared understanding of the project mission and a common conceptual alignment. At the same time, the paper aims to sensitize for the ambiguities and the complexity the project partners have to cope with in the implementation of the project’s mission. The paper identifies five key themes, relevant both for the internal communication within the consortium and for external communication with stakeholders:
• A first theme concerns the diversity of purposes, tasks and expertise. An effective way to prevent disintegration is to consciously build an epistemic entanglement between the two issues – partners with expertise on regularisation consider which numbers and statistics are required for this task while partners with expertise on estimates and measurement consider which numbers and statistics are available or can be provided.
• A second theme concerns a shared basic understanding of the importance and implications of statistical thinking in our times. The concept of statistical thinking critically reflects the pervasive importance of quantification that shape public perception and political decision making and strengthen a tendency towards a governance by numbers. Awareness of the social and political implications of statistical thinking sensitizes for the risks and chances related to aspired changes in the measuring and governance of irregular migration.
• A third theme concerns the nature of different drivers for change in public policies. MIrreM strives for changes that display distinct features. The improvement of measuring is a first-order change – a variation that occurs within a given system that remains unchanged – while regularisation as a more contested issue display features of a second-order change – a variation whose occurrence changes the system itself - that involves discontinuity and constitute a new direction. As a coordination and support action, MIrreM has to be aware of the complexity and multi-centric nature of political decision making that rarely comply with expectations of rational procedures. In particular in the case of complex issues like irregular migration, changes occur in a situation of urgency as result of non-linear and non-predictable decision making influenced by a situational availability of possible responses. MIrreM aims to develop and make available possibilities for the improvement of measuring irregular migration and implementation of regularisation.
• A fourth theme concerns the systematic development of policy options. The approach of Critique Guided Designing provides orientation for the development of policy options in highly contested policy fields. Critique Guided Designing entails the development of first-best policy design and systematically collects and reviews reservation in order to re-design a policy option that is technically feasible, politically acceptable and ethically preferable. Consequently, Critique Guided Designing enable as second-best options the identification of incremental steps towards the realization of technically feasible, politically acceptable and ethically preferable policy designs.
• A fifth theme concerns stakeholder engagement. MIrreM aims to produce the handbooks with stakeholders in a collaborative manner. Findings from stakeholder research indicate that the identification of and communication with stakeholders is an intricate issue and imply also risks. Considering that MIrreM operates in a contested policy field, the paper proposes to complement the classic criteria of stakeholder identification – power, urgency, legitimacy – with expertise and alignment. Stakeholder engagement should be organized with a task-specific orientation that focus in a first stage on the collaborative development of tasks with well-aligned stakeholders and in a second stage on the inclusion of a broader range of stakeholders in critique-guided assessment events.
Finally, the concluding chapter provides a brief summary of the paper, identifying the availability of more and more sophisticated policy options for change in the highly contested policy field of irregular migration governance as the main asset of MIrreM.
... We also offer one contribution to policy. With nation states typically having national strategies and visions for SDG compliance in place, the need for national oversight of progress and spend is an important source of data that could help drive better policy [49]. We suggest targeting this through regulating that data on SDG integration should be provided as open data from all organizations in the public sector. ...
Digital transformation is increasingly prioritized within the public sector to assure sustained relevance. At the same time, sustainable development goals (SDGs) are increasingly addressed in the strategies and missions of public sector actors. Previous research highlights that sustainability requires integration into internal procedures and governance structures (e.g., accounting) to avoid running the risk of merely being ceremonial and green washing. With digital transformation deemed critical for the public sector, we would hence expect to see an integration of SDGs in digital initiatives. This study answers the research question of how SDGs are integrated into digital transformation initiatives. We answer the question through purposive sampling of digital initiatives within a large, Swedish municipality, where each initiative is categorized on the notion of which SDGs they are related to. The findings show that there is a decoupling of sustainability in digital transformation initiatives, that risks leading to directly detrimental effects for both the digital transformation of the public sector as well as for sustainability. This is discussed through integration with previous literature with the intent of identifying future avenues for research and recommendations for practice.KeywordsDigital transformationSustainable development goalsSDGResponsible information systemsDigital government
... The proliferation of innovation labs is a testament to a realised need for experimentation with new technology applications. Smaller successes enable organisations to mature and build capabilities before undertaking a large-scale AI-driven challenge (Desouza et al., 2020;van Veenstra & Kotterink, 2017). ...
... Co-creation of AI solutions with stakeholders provides varied viewpoints and helps develop a clear definition of the problem (Fatima et al., 2021). Citizen collaboration enhances positive perceptions of AI decisions and higher adoption (Criado & Gil-Garcia, 2019;Gesk & Leyer, 2022;Lopes et al., 2019;van Veenstra & Kotterink, 2017). Collaborating with employees on service design alleviates concerns of AI replacing jobs and enhances internal use and adoption (A. ...
Artificial Intelligence (AI) implementation in public administration is gaining momentum heralded by the hope of smart public services that are personalised, lean, and efficient. However, the use of AI in public administration is riddled with ethical tensions of fairness, transparency, privacy, and human rights. We call these AI tensions. The current literature lacks a contextual and processual understanding of AI adoption and diffusion in public administration to be able to explore such tensions. Previous studies have outlined risks, benefits, and challenges with the use of AI in public administration. However, a large gap remains in understanding AI tensions as they relate to public value creation. Through a systematic literature review grounded in public value management and the resource-based view of the firms, we identify technology-organisational-environmental (TOE) contextual variables and absorptive capacity as factors influencing AI adoption as discussed in the literature. To our knowledge, this is the first paper that outlines distinct AI tensions from an AI implementation and diffusion perspective within public administration. We develop a future research agenda for the full AI innovation lifecycle of adoption, implementation, and diffusion.
... 1. data driven, which groups papers whose main focus is on the direct role that data can have in leading policy decisions (Lansky et al., 2007;van Veenstra & Kotterink, 2017); 2. knowledge dissemination, which groups papers whose focus is explicitly on the processes and strategies through which knowledge is diffused (Kingston, 2012); 3. policy advice, which groups publications that are focused on the science-policy interface, how the scientific and policy communities work together to reach decisions and how policymakers obtain the information they need (Engels, 2005); 4. evidence-based, which groups all papers that analyse the role of evidence in decisionmaking processes for any step in the policy cycle (Claes et al., 2015;Clark, 2012). ...
The use of knowledge and evidence in policymaking is a recurrent topic of research due to
its scientific and policy relevance. The existing and expansive body of literature has been
scrutinised in various ways to grasp the dimensions of knowledge utilisation in policymaking,
although most of this research has a monosectoral focus and is based on very general
criteria of analysis that do not completely account for the complexity of policy making.
This paper overcomes this limitation by enlightening the epistemological divide in the
field between an objectivist and a subjectivist perspective and by distinguishing two different
focuses in this literature: a focus on knowledge for policy making and a focus on
knowledge in policy making. Based on this analytical distinction, the paper presents an
original and unprecedented systematic, intersectoral metareview by considering the thirtyyear
period between 1990 and 2020 (approximately 1,400 were selected for fine-grained
analysis). This metareview offers a broader and more detailed map with a clear idea of the
distribution of interest in the topic among the different policy fields, a better classification
of the theoretical/empirical content and research goals that scholars adopt and a novel and,
above all, more fine-grained perspective on the types of conditions that favour or disfavour
a significant role of knowledge in policymaking. Ultimately, and above all, this metareview
identifies three highly relevant components of policy making that can facilitate or constrain
the use of knowledge in policymaking more than others: values/ideology/beliefs, actors’
relationships, and policy capacities.
