Actionable Knowledge Research Articles

AI-Enhanced Data Visualization: Transforming Complex Data into Actionable Insights

Purpose: The purpose of this study is to explore how artificial intelligence (AI) becomes a part of data visualization. Thus, data from complex datasets are transformed into dynamic, interactive, and personalized visual experiences that will help in deeper insights and actionable knowledge. The research is supposed to design a holistic system and rules for using AI to make data visualization more effective and super interactive for the users. Methodology: The methodology involves the in-depth examination of artificial intelligence-based data visualization tools and platforms by using case studies. The study analyses the impact of AI technologies such as machine learning, natural language processing, and augmented and virtual reality on the scalability, interactivity, and personalization of data visualizations. The sentence also talks about the analysis of the moral factors that are part of the process of introducing AI in data visualization. Findings: The findings indicate that AI greatly improves the process and the quality of data visualization, thus, it makes possible the management of big, complicated, multi-dimensional datasets in a more efficient and precise way. The AI-driven tools give the users the opportunity to see the actions that are happening in real-time, predict the results, and personalize the tools according to their individual needs, thereby increasing the decision-making processes. Furthermore, ethical issues like data privacy, bias, and transparency must be well managed. This research has the distinctive feature of providing a theoretical framework that emphasizes the importance of AI in the development of data visualization technologies. Unique contribution to theory, policy and practice: In practice, it gives the rules for the implementation of AI tools to achieve more effective and user-focused visualizations. The policy focuses on the necessity of ethical standards in AI deployments, which means the data visualization practices should be transparent, accountable, and bias-free, thus creating trust and reliability in the AI applications.

Utilizing Social Media and Crowdsourcing for Crisis Management and Communication: proposing an Integrative Framework

Utilizing social media and crowdsourcing (SMCS) in crisis management is crucial for improving communication and citizen engagement. However, practitioners working in crisis management organizations often face challenges when translating the outcomes of scientific research into actionable knowledge. To aid disaster management organizations, a comprehensive set of resources including practical tools, guidelines, and use examples are necessary. This will help response organizations to integrate the different components of SMCS coherently and consistently in their organizations and to promote disaster resilience for different users. An integrative Framework, developed by the authors as part of the EU-funded Horizon 2020 project, LINKS – strengthening links between technologies and society for European disaster resilience, serves such resources. This paper presents how this Framework came into being and describes its main components. It then provides a case study from the Netherlands, focusing on the scenario of industrial, chemical hazards, to illustrate how the Framework was actually used.

Digital Transformation and its Impact on Safety Culture During Organizational Change

In today's era of rapid technological advancements, organizations are increasingly embracing digital transformation as a pivotal strategy to enhance their competitiveness and operational efficiency. This paradigm shift towards digitalization entails the integration of advanced digital technologies into the fabric of organizational processes and systems. However, this transformative journey often unfolds in tandem with significant organizational change, reshaping not only operational workflows but also the very culture that underpins the workplace dynamics. This research article delves into the complex interplay between digital transformation initiatives and the overarching safety culture within organizations undergoing profound organizational change processes. Recognizing that safety culture constitutes a cornerstone of organizational well-being and performance, this study seeks to elucidate the multifaceted implications of digitalization on safety practices, attitudes, and behaviors in the workplace. Through a meticulous examination of the challenges, opportunities, and strategic imperatives inherent in the convergence of digital transformation and safety culture, this research endeavors to offer nuanced insights that can inform organizational decision-making and practice. By unpacking the intricacies of this nexus, the study aims to equip stakeholders with actionable knowledge and best practices conducive to nurturing a positive safety culture amidst the backdrop of digital transformation endeavors. In essence, this research article serves as a beacon illuminating the path towards a harmonious integration of digital technologies and safety imperatives within the organizational milieu. By fostering a deeper understanding of the dynamics at play and delineating pragmatic strategies for navigating this terrain, the study endeavors to empower organizations to embark on their digital transformation journeys while safeguarding the well-being and resilience of their workforce.

Developing an action-oriented performance framework for sustainability measurement in the new product development

PurposeThe integration of sustainability, performance measurement and new product development (NPD) is key for aligning environmental and social objectives with business strategies. While previous research has initiated proposals for integrating sustainability into NPD or incorporating sustainability into corporate measurement systems, there is a notable deficiency in studies that comprehensively integrate these three perspectives. In this sense, this study proposes a performance framework (PF) to integrate sustainability performance indicators (PIs) into the measurement system considering the company’s NPD phases.Design/methodology/approachThe PF was developed through a literature review and action research (AR). This resulting PF was positively evaluated by the practitioners in the company.FindingsFirst, the review enabled the synthesis of an initial conceptual PF with 188 sustainability PIs and a five-step procedure. Then, the empirical results of the AR led to a new PF that presents the systematisation of the PIs database and a practice-based seven-stage approach.Research limitations/implicationsThis action-oriented research limits the extent to which this study’s findings can be generalised. Future research should apply the PF in different research designs to produce managerially relevant knowledge.Practical implicationsThis PF may provide managers with actionable knowledge that best supports the measurement system integration with sustainability PIs considering the NPD phases.Originality/valueIntegrating sustainability, performance measurement and the NPD has been recognised as critical for supporting decision-making concerning the impact of processes and products. Compared with previous frameworks, the proposed PF extends the existing literature by introducing a systematised PIs database and a novel procedure for integrating sustainability measurement throughout the NDP.

Beyond Mobile Payments: Exploring the Evolution and Future of Fintech (BY IJISRT)

In today's digital age, FinTech’s have become universal, transforming the way individuals conduct financial transactions. However, with the convenience of Fintech also come challenges that users encounter. This book chapter investigates into the changing landscape of Fintech challenges, drawing insights from a comprehensive survey conducted among various respondents The survey finds three primary obstacles faced by users during Fintech: network issues, time consumption, and privacy concerns. Notably, a significant proportion of respondents reported encountering network-related problems, highlighting the critical role of stable connectivity in facilitating seamless transactions. Moreover, the chapter explores into the foiling experienced by users due to the time-and privacy nature of the payment process, shedding light on the need for streamlined and efficient payment mechanisms. Building upon the survey findings, the chapter offers valuable insights into potential strategies and solutions to address these challenges. By elucidating practical approaches and technological innovations aimed at enhancing Fintech systems' efficiency and security, the chapter equips readers with actionable knowledge to navigate the digital payment landscape effectively. This study's findings add to academic discussion and have practical implications for policymakers, industry practitioners, and educators.

Discovery of Actionable Patterns Through Scalable Vertical Data Split Method with Meta Actions and Information Granules

Action Rules are rule based systems that extract actionable patterns which are hidden in big volumes of data. Users need recommendations on actions they can undertake to increase their profit or accomplish their goals, this recommendations are provided by Actionable patterns. In the technological world of big data, massive amounts of data are collected by organizations, including in major domains like financial, medical, social media and Internet of Things(IoT). To analyze and store such a massive amount of data, distributed computing frameworks like Hadoop and Spark are introduced to store the big data in a distributed fashion which manage and analyze them in parallel. The traditional Action Rules extraction models, which analyze the data in a nondistributed fashion, do not perform well when dealing larger datasets. Serious complications of discovering Action Rules with such distributed environments are - data distribution among computing nodes and calculation of major parameters including : support, confidence, utility, and coverage, that represent the whole data. Information granules form basic entities in the world of Granular Computing(GrC), which represents meaningful smaller units derived from a larger complex information system. In this research, we focus on the data distribution phase of the distributed Actionable Pattern Mining problem. To handle the data distribution task by splitting the big data in both horizontal and vertical fashions - we propose partition threshold rho. In this work, we concentrate on using information granules to implement a vertical data splitting strategy with Meta Actions. Hence our results discover valuable Actionable Knowledge with application in Business and Education domains.

Progress with the Learning Health System 2.0: a rapid review of Learning Health Systems’ responses to pandemics and climate change

BackgroundPandemics and climate change each challenge health systems through increasing numbers and new types of patients. To adapt to these challenges, leading health systems have embraced a Learning Health System (LHS) approach, aiming to increase the efficiency with which data is translated into actionable knowledge. This rapid review sought to determine how these health systems have used LHS frameworks to both address the challenges posed by the COVID-19 pandemic and climate change, and to prepare for future disturbances, and thus transition towards the LHS2.0.MethodsThree databases (Embase, Scopus, and PubMed) were searched for peer-reviewed literature published in English in the five years to March 2023. Publications were included if they described a real-world LHS’s response to one or more of the following: the COVID-19 pandemic, future pandemics, current climate events, future climate change events. Data were extracted and thematically analyzed using the five dimensions of the Institute of Medicine/Zurynski-Braithwaite’s LHS framework: Science and Informatics, Patient-Clinician Partnerships, Continuous Learning Culture, Incentives, and Structure and Governance.ResultsThe search yielded 182 unique publications, four of which reported on LHSs and climate change. Backward citation tracking yielded 13 additional pandemic-related publications. None of the climate change-related papers met the inclusion criteria. Thirty-two publications were included after full-text review. Most were case studies (n = 12, 38%), narrative descriptions (n = 9, 28%) or empirical studies (n = 9, 28%). Science and Informatics (n = 31, 97%), Continuous Learning Culture (n = 26, 81%), Structure and Governance (n = 23, 72%) were the most frequently discussed LHS dimensions. Incentives (n = 21, 66%) and Patient-Clinician Partnerships (n = 18, 56%) received less attention. Twenty-nine papers (91%) discussed benefits or opportunities created by pandemics to furthering the development of an LHS, compared to 22 papers (69%) that discussed challenges.ConclusionsAn LHS 2.0 approach appears well-suited to responding to the rapidly changing and uncertain conditions of a pandemic, and, by extension, to preparing health systems for the effects of climate change. LHSs that embrace a continuous learning culture can inform patient care, public policy, and public messaging, and those that wisely use IT systems for decision-making can more readily enact surveillance systems for future pandemics and climate change-related events.Trial registrationPROSPERO pre-registration: CRD42023408896.

Turning ‘managed retreat’ research into practice ready tools: needed guidelines to reach stakeholders

Abstract The study of “managed retreat” as a response to climate change impacts has emerged in recent years as an important field of inquiry that is in need of substantial further research and improved understanding—particularly in the United States (Dundon and Abkowitz, 2021; Plastrik and Cleveland, 2019; Hino, et al., 2017; Dachary-Bernard, et al., 2019). However, the critical participant stakeholders in managed retreat discussions—often city/county planning officials and community members in vulnerable areas—often do not have adequate access to meaningful planning information or other tools to support decision making. With some notable exceptions, important research in this field that could assist communities is often relegated to academic journals that are not often visited by city or county planners faced with the very decisions this research could inform. Although the realities of research careers often require a focus on publication in prestigious academic journals, more attention is now needed to get actionable research knowledge in the hands of the practitioner. The need to develop user-friendly tools that direct research information into the hands of stakeholders most likely to benefit from such work is even more urgent than ever: climate change presents current, continuing, and substantial challenges for humanity in nearly every sector of the economy. Many extreme weather events have already increased (in frequency and/or severity) because of our changing climate, including flooding, heavy precipitation, extreme heat, and other climate-induced events (U.S. EPA, n.d.).

Newborn screening for Duchenne muscular dystrophy: the perspectives of stakeholders

The rapidly evolving clinical landscape of Duchenne muscular dystrophy (DMD) is driving innovative approaches for early diagnosis through genomic newborn bloodspot screening (NBS). However, the potential impact of these programs on families and healthcare systems remains unexplored. This study assessed the perceived benefits, harms, barriers, and enablers for DMD NBS amongst primary caregivers of children with DMD and healthcare professionals (HCPs). This Australian multi-centre cross-sectional study used a mixed-methods convergent methodology. Participants completed a codeveloped questionnaire and their perceptions on the utility, model of care, and processes of DMD NBS were thematically analysed. Participants included 50 caregivers and 26 HCPs (68.5% and 53.1% response rate respectively). Most caregivers (40/50, 80%) perceived net benefits of DMD NBS and highlighted an early diagnosis as actionable knowledge, even with the current paucity of disease modifying therapies. This knowledge was valued to enable access to multidisciplinary supportive care (29/50, 58%), clinical trials (27/50, 54%), psychological support (28/50, 56%), inform reproductive planning (27/50, 54%), and facilitate financial planning based on the future needs of their child (27/50, 54%). Whilst HCPs acknowledged these opportunities, only 16/26 (61.5%) believed there were definite net benefits, with notable concerns over the psychological harms of diagnostic knowledge without a recourse to disease modifying therapeutic intervention early in life. Caregivers and HCPs perceived a range of potential benefits of DMD NBS. Health system readiness will be founded on developing an integrated model of care that not only supports the psychosocial and information needs of families receiving a newborn diagnosis of DMD, but also provides care and clinical surveillance for individuals for whom a diagnosis may remain uncertain. Medical Research Futures fund (GNT2017165, MRF2015965).

Unveiling the Crucial Role of Statistics in Big Data Analytics

This paper focuses on the role of statistics in big data analytics to build analytical accuracies and precise decision-making insights. Statistics and data mining techniques that are useful for big data analytics include: significance testing, classification, regression/prediction, cluster analysis, association rule learning, hypothesis testing, anomaly detection, and visualization. Statistical analysis provides a scientific justification to move from data to knowledge and turn it into actionable insights, emphasizing their role in data preprocessing, pattern recognition, and predictive modeling. The study navigates through prominent statistical methods such as regression analysis, hypothesis testing, and machine learning algorithms, illustrating their efficacy in extracting actionable knowledge from vast and complex datasets. Moreover, it sheds light on the symbiotic relationship between statistics and technological advancements, showcasing their collaborative potential in driving innovation within the Big Data domain. By synthesizing current research and practical applications, this paper aims to underscore the indispensable nature of statistical methodologies in harnessing the power of Big Data for informed decision-making. In the era of Big Data, where information proliferates at an unprecedented scale, the role of statistics has become increasingly vital in extracting meaningful insights from the vast and complex datasets that characterize this landscape. This paper seeks to unravel the intricate interplay between statistics and Big Data analytics, elucidating the significance of statistical methodologies in navigating the challenges posed by the sheer volume, velocity, and variety of data

LinChemIn: Route Arithmetic─Operations on Digital Synthetic Routes.

Computational tools are revolutionizing our understanding and prediction of chemical reactivity by combining traditional data analysis techniques with new predictive models. These tools extract additional value from the reaction data corpus, but to effectively convert this value into actionable knowledge, domain specialists need to interact easily with the computer-generated output. In this application note, we demonstrate the capabilities of the open-source Python toolkit LinChemIn, which simplifies the manipulation of reaction networks and provides advanced functionality for working with synthetic routes. LinChemIn ensures chemical consistency when merging, editing, mining, and analyzing reaction networks. Its flexible input interface can process routes from various sources, including predictive models and expert input. The toolkit also efficiently extracts individual routes from the combined synthetic tree, identifying alternative paths and reaction combinations. By reducing the operational barrier to accessing and analyzing synthetic routes from multiple sources, LinChemIn facilitates a constructive interplay between artificial intelligence and human expertise.

Editorial: Producing actionable knowledge about marginalized populations and communities: a challenge to editors and journals

Editorial: Producing actionable knowledge about marginalized populations and communities: a challenge to editors and journals

Middle-range theorising supporting and supported by action research: focusing on practitioner preparedness

Increased demand for actionable knowledge in operations- and supply chain management has fuelled the interest in collaborative, action-oriented research design as well as modes of theorising that generate adaptable and actionable frameworks. Whilst action research (AR) design as well as middle-range theories (MRT) offer guiding principles herein, they are researcher centric in nature. It is taken for granted that practitioners that enter such an endeavour have a certain level of knowledge or experience prior to the initial stages of formalising the research problem. Practitioners in non-academic, operations management-intensive industries or craftsmanship-based industries, such as construction or carpeting (often in the SME range) are often neither prepared nor equipped with the principles necessary to convey their managerial challenges into collaborative research design. This risk limiting or even hindering altogether such participation. This paper elaborates on combining the logic of AR and MRT. By conceptualising a preparatory phase for initiating practitioner engagement, complementing the conventional AR cycle, a four-step approach is presented: (1) Identifying a joint interest; (2) Teaching – Awakening interest in the topic through MRT frameworks; (3) Accepting buy-in to the AR cycle and determining the problem; and (4) Proposing MRT frameworks for analysis and entering the traditional AR cycle.

Public health surveillance and the data, information, knowledge, intelligence and wisdom paradigm.

This article points out deficiencies in present-day definitions of public health surveillance, which include data collection, analysis, interpretation and dissemination, but not public health action. Controlling a public health problem of concern requires a public health response that goes beyond information dissemination. It is undesirable to have public health divided into data generation processes (public health surveillance) and data use processes (public health response), managed by two separate groups (surveillance experts and policy-makers). It is time to rethink the need to modernize the definition of public health surveillance, inspired by the authors' enhanced Data, Information, Knowledge, Intelligence and Wisdom model. Our recommendations include expanding the scope of public health surveillance beyond information dissemination to comprise actionable knowledge (intelligence); mandating surveillance experts to assist policy-makers in making evidence-informed decisions; encouraging surveillance experts to become policy-makers; and incorporating public health literacy training - from data to knowledge to wisdom - into the curricula for all public health professionals. Work on modernizing the scope and definition of public health surveillance will be a good starting point.

The integration of performance management and risk management in the public sector: an empirical case

Performance management and risk management in the public sector have undergone significant improvements; however, few empirical studies have conceptualised the integration of performance management and risk management. This study aimed to understand why it fails in practice and turns into disintegration. To do this, we analyse the role of different actors involved in the integration between performance management and risk management. We have conducted our analysis at the organisational level in a regional context, adopting two different research methods, documentary analysis and collections of interviews. This paper contributes to the theoretical debate with interesting new insights about organisational practices in the public sector. In this research, we adopted the disintegration framework, broadly used as a research methodology in the ontological and social paradigm as reported (Täubig in Totale Institution Asyl, Juventa Verlag, Munich, 2009) for analysing the integration and disintegration between performance management and risk management. This approach presumes the collective engagement of researchers and practitioners, which can help bring to the surface the knowledge embedded in practice and transform it into actionable knowledge to produce practice changes. This study contributes to the public accounting literature by providing empirical evidence about organisational practices in the public sector. It offers a practical and general understanding of performance management and risk management practices functioning in public government. It shows the fundamental role played by key actors when performance management and risk management practices are implemented. This empirical research also has practical implications, creating the basis for the implementation of an integrated system of performance management and risk management in regional governments.

Linking absorptive capacity and project performance in environmental uncertainty: A perspective on implementation arrangements

AbstractThis study utilizes the concept of absorptive capacity as a unique way to view implementations arrangements in resource‐scarce public sector organizations. It introduces absorptive capacity as a policy implementation capacity and explains the relationship between potential and Realized Absorptive Capacity and project performance, primarily, in the higher education, primary and secondary health and social welfare departments in the Government of the Punjab, Pakistan. The main research question ascertains the effect of absorptive capacity on project performance and how environmental uncertainty intervenes in the relationship between different aspects of absorptive capacity (potential absorptive capacity, PACAP and realized absorptive capacity, RACAP) and project performance. In order to do so five hypotheses are developed. In order to explore the assumptions, the relationships among variables are ascertained based on 167 responses from ongoing public sector projects/schemes (2020) using bivariate correlations, and linear and multiple linear regression analyses. The results of this study support findings suggested by prior research, confirming a positive influence of absorptive capacity on project performance in terms of knowledge acquisition and assimilation. The same is true for a direct relationship of public sector projects. The public sector projects have used the existing experience and knowledge resources to further enhance their capabilities and exploited knowledge. Further, the actionable knowledge has been transformed into performance goals of the projects. The unstable external environment, unable to predict future environmental conditions and changing project requirements did not seem to affect the existing transferability and utilization of knowledge for achieving social sector projects' performance.

Seasonal dynamics of fallow and cropping lands in the broadacre cropping region of Australia

Fallowing is an important strategy for enhancing soil health, water harvesting and crop yields, thus improving sustainability and reducing production risks in dryland farming systems in Australia. However, accurate data regarding the location, frequency, extent, and duration of fallow land is not readily available at high spatio-temporal resolutions before and during a cropping season. As a result, continental maps depicting seasonal dynamics of fallow and cropping lands and their responses to climate change and human activities remain missing. This study set out to develop an automated approach to discriminate fallow areas from cropping areas within Australian broadacre cropping region. This was done by applying a mathematical algorithm of turning point detection technique to a curve fitted vegetation index time series from 2016 to 2022, derived from high spatial (10 m) and temporal (5-days) resolution Sentinel-2 data. Specifically, we aimed to derive: (i) 5-day revisit fallow/cropping map layers; (ii) key attributes of the fallow and cropping periods (e.g., start, end, duration); (iii) cropping intensity and area. The proposed approach yielded a high and significant overall accuracy, surpassing 92% with substantial balanced accuracy (>0.9) against >3000 fields for individual winter and summer seasons across Australia. In addition, this study's temporal and geographical outputs, encompassing seasonal attributes, cropping intensity and cropping areas, robustly enhanced the understanding of seasonal cropping dynamics and historical shifts in dryland farming practices. Findings derived from this analysis aligned well with extreme climatic events and changes in crop activities adopted in response to such events. Future research will aim to extract key seasonal dynamics attributes influenced by cropping practices, enhancing the conversion of high-resolution earth observation data into actionable industry knowledge.

Unveiling Pathways to Enhance Social Learning Processes in Water Struggles

To advance actionable knowledge production in the context of water struggles, this article identifies ways to strengthen transformative learning processes within riverine social movements. The complex challenges associated with water struggles point to an increasing need to explore ways in which these processes can be shaped and to promote changes in the worldviews that inform how water and riverine environments are perceived and structured. This study draws on the grassroots movement for the social-ecological regeneration of the Taquara Stream in Porto Alegre, Brazil. Research on this case has shown that the actions conducted by this movement fostered learning processes through the creation of innovative forms of involvement that brought together multiple actors. A panel of experts conducted an in-depth analysis of the learning practices observed in this case. This article discusses five aspects of the learning process, which have been identified by the experts, that are essential to expanding the transformative potential of water-related social movements: (1) building relationships of trust between actors, (2) building links with and between key actors in the process, (3) creating dialogue spaces that promote the co-creation of actionable knowledge, (4) engaging actors spontaneously, proactively, and co-responsibly in the process, and (5) bringing participatory research into local processes.

Effective Management of Construction Project Team: Identifying Leadership Qualities and Responsibilities

Leadership within construction project teams is a critical aspect of effective project management, yet a comprehensive understanding of essential leadership qualities and responsibilities remains elusive in academic discourse. This research addresses this gap by identifying key leadership characteristics crucial for the efficient management of construction teams. The study objectives include exploring essential leadership characteristics and filling the gap in the leadership literature specific to the construction industry. This study employed a qualitative data collection and analysis approach involving in-depth interviews with nine seasoned professionals from diverse construction-related roles and organizations. The findings reveal that emotional intelligence and relationship building are paramount for creating a collaborative and innovative work environment. Empowerment and inclusivity foster team initiative and diversity, although caution is warranted to mitigate potential negative impacts on role stress and unethical behavior. Recognition and appreciation of team contributions contribute to morale and motivation, while continuous learning encourages adaptability and growth. Precise goal setting and efficient communication are foundational for focused and responsive team dynamics, while delegation and trust-building strategies promote collaboration and cohesion. Finally, prioritizing employee well-being ensures a positive and healthy work environment conducive to sustained engagement. The study contributes valuable insights into leadership characteristics vital for constructing teams' optimal functioning and management. The multifaceted nature of construction project management is highlighted, emphasizing the need for leaders to possess a diverse skill set to navigate the complexities of team dynamics in the construction industry. The findings provide actionable knowledge for practitioners and scholars, fostering a more holistic comprehension of effective ......

Participation and co‐production in climate adaptation: Scope and limits identified from a meta‐method review of research with European coastal communities

AbstractAs climate change impacts increase, there are growing calls for strengthening relationships between researchers and other stakeholders to advance adaptation efforts. Participation and co‐production are widely held to be key to such relationships, both intended to open substantive engagement in science and research to non‐experts. Gains commonly attributed to participation and co‐production include improved understanding of user needs and contexts, enhanced trust, creating actionable knowledge for adaptation planning and decision‐making, and other new outcomes and practices supporting adaptation progress. At the same time, scrutiny of existing efforts to use participation and co‐production reveals limits and gaps in understanding the conditions and processes required to undertake them in meaningful, appropriate, and effective ways. This review assesses such limitations and gaps across the growing volume of research focused on adapting coastal and island communities within Europe. We systematically reviewed 60 peer‐reviewed papers, drawing on a novel meta‐method review approach to synthesize patterns in participation and co‐production implementations, types of outcomes, and the latter's associations with study research designs. We identify a propensity toward using more simplistic definitions of community, more conventional, extractive research methods in working with study communities, and emphasizing knowledge generation over other outcomes. These issues are all limits on participation and co‐production effectiveness, and we make recommendations to reduce them. We also recommend further recourse to systematic review methods to aid the development of participation and co‐production knowledge for adaptation.This article is categorized under: Assessing Impacts of Climate Change > Evaluating Future Impacts of Climate Change Perceptions, Behavior, and Communication of Climate Change > Perceptions of Climate Change Climate and Development > Social Justice and the Politics of Development