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This study attempts to answer the question: “how are the two drivers, accountability focus and organizational learning, independently and interactively associated with public agencies’ proactive policy orientation?” The first driver is the multiple accountabilities that public agencies pursue: (1) bureaucratic, (2) legal, (3) professional and (4) political. The second driver is the organizational learning activities of public agencies: (1) socialization, (2) externalization, (3) combination and (4) internalization.

For data, 800 respondents from the public agencies in South Korea were surveyed.

The analysis provided several findings: (1) the discretionary accountabilities (professional and political) have a greater positive influence on the proactive policy orientation; (2) the conventional accountabilities (legal and bureaucratic) tend to have negative impacts on the proactive policy orientation and (3) among the four types of accountability, legal accountability can be more significantly complemented by organizational learning activities, which can enable both visionary and realistic administration in a balanced manner.

This study provides a unique insight on how organizational proactivity can be ensured through the interactions of organizational accountabilities and organizational learning.

The promotion of autonomous vehicles introduces privacy and security risks, underscoring the pressing need for responsible innovation implementation. To more effectively address the societal risks posed by autonomous vehicles, considering collaborative engagement of key stakeholders is essential. This study aims to provide insights into the governance of potential privacy and security issues in the innovation of autonomous driving technology by analyzing the micro-level decision-making processes of various stakeholders.

For this study, the authors use a nuanced approach, integrating key stakeholder theory, perceived value theory and prospect theory. The study constructs a model based on evolutionary game for the privacy and security governance mechanism of autonomous vehicles, involving enterprises, governments and consumers.

The governance of privacy and security in autonomous driving technology is influenced by key stakeholders’ decision-making behaviors and pivotal factors such as perceived value factors. The study finds that the governmental is influenced to a lesser extent by the decisions of other stakeholders, and factors such as risk preference coefficient, which contribute to perceived value, have a more significant influence than appearance factors like participation costs.

This study lacks an investigation into the risk sensitivity of various stakeholders in different scenarios.

The study delineates the roles and behaviors of key stakeholders and contributes valuable insights toward addressing pertinent risk concerns within the governance of autonomous vehicles. Through the study, the practical application of Responsible Innovation theory has been enriched, addressing the shortcomings in the analysis of micro-level processes within the framework of evolutionary game.

Policy is key for effective displacement governance in times of crises and in response and recovery. Therefore, this study assessed if Australian climate, disaster and emergency management policies provide effective mechanisms for governing displacement crises and areas where current approaches could be improved.

This study assessed 18 national and state-level disaster, emergency and climate change management frameworks to determine if best practice displacement governance themes were reflected in policy documents. Deductive thematic analysis was undertaken using Braun and Clarke’s six-phase method.

Issues of displacement are reflected in policies analysed in this study. However, current policy frameworks need to be equipped to comprehensively address the housing requirements of displaced people or provide long-term initiatives. Approaches are focused on crisis management rather than pre-emptively planning for displacement response and recovery. Therefore, Australia has not exercised national responsibility for displaced people appropriately.

Disaster displacement is an under-researched area of Australian scholarship and disaster management policy and practice. Therefore, this paper has practical implications in so far as it draws attention to the issue of displacement in Australia. A limitation of this paper is that it only analysed policy frameworks specific to disasters. While broader engagement was outside the scope of this study, this limitation provides opportunities for further research from disciplinary perspectives of public housing and homelessness to examine displacement policy challenges in these fields. Furthermore, this study is limited to a theoretical inquiry into this topic through a desktop review of policy documents. While this is a necessary first step, empirical studies are required to determine accurate displacement rates, drivers and people’s experience of being displaced.

This research aims to inform policy by presenting recommendations for policy interventions for disaster displacement governance. Therefore, this research has practical implications as policy and disaster risk reduction (DRR) professionals can draw from the findings of this research when planning and initiating disaster response for displaced persons.

This research draws attention to an area of disaster management practice and policy that has not been adequately accounted for. Highlighting gaps in current policy can assist in developing targeted strategies and solutions for internally displaced people, which protect their rights and meet their needs.

Displacement is a growing climate change issue. This research aims to help address this problem by drawing attention to areas where Australian disaster management approaches fail to account for displaced populations. Therefore, this research has practical implications for addressing future issues of disaster injustice that may arise if displacement continues, unacknowledged in disaster management.

This paper aims to investigate the literacy corpus regarding the potential of big data to improve public decision-making processes and direct these processes toward the creation of public value. This paper presents a map of current knowledge in a sample of selected articles and explores the intersecting points between data from the private sector and the public dimension in relation to benefits for society.

A bibliometric analysis was performed to provide a retrospective review of published content in the past decade in the field of big data for the public interest. This paper describes citation patterns, key topics and publication trends.

The findings indicate a propensity in the current literature to deal with the issue of data value creation in the private dimension (data as input to improve business performance or customer relations). Research on data for the public good has so far been underestimated. Evidence shows that big data value creation is closely associated with a collective process in which multiple levels of interaction and data sharing develop between both private and public actors in data ecosystems that pose new challenges for accountability and legitimation processes.

The bibliometric method focuses on academic papers. This paper does not include conference proceedings, books or book chapters. Consequently, a part of the existing literature was excluded from the investigation and further empirical research is required to validate some of the proposed theoretical assumptions.

Although this paper presents the main contents of previous studies, it highlights the need to systematize data-driven private practices for public purposes. This paper offers insights to better understand these processes from a public management perspective.

The purpose of this study is to propose an innovative and efficient process in urban policy-making that combines a divergent and creative method with a convergent and strategic one. At the same time, the purpose is also to propose a useful innovation to enforce the usability of both methods. On the one hand, mission-oriented policies run the risk of being overly focused on the present and of not being able to develop preparedness in organization. On the other hand, scenario development has the reverse problem it often does not point out how to use scenario narratives to inform and devise short-term strategic actions.

The paper proposes an innovative methodological approach, the mission-oriented scenarios, which hybridizes Mazzucato's mission-oriented public policy framework with Jim Dator's Manoa school four futures method. The proposed methodological innovation emerges from a urban foresight academic-led project carried out in the context of the Metropolitan City of Turin, Italy, where a first application of the mission-oriented scenarios was tested on six different focal issues (from reindustrialization to cultural policies) and the scenario narratives were used as sources for the grounding of 12 missions and 48 strategic actions towards 2030.

Mission-oriented scenarios can contribute to the generation of more sustainable and inclusive urban public policies. This methodological proposal is based on an original mix of knowledge exchange procedures borrowed from methodological approaches with different backgrounds: the mission-oriented and the archetypal scenarios. Their conjunction could support the formulation of ambitious yet pragmatic policies, giving a plurality of actors the opportunity to act and establish fruitful and lasting partnerships.

The paper reconstructs one of the first urban foresight projects carried out in a major Italian city by two prestigious universities and exposes a methodological innovation resulting from reflection on the strengths and weaknesses of the project, which opens the door to the development of a new scenario technique.

The purpose of the study detailed here was to engage with Directors of Centres for Doctoral Training (CDTs) during the first year of their new Centres to form a snapshot view of the nature and type of training that was being incorporated and how this might affect the wider institution – in this case the university. Using an organisational learning lens, this paper empirically examines the work-in-progress of the responsible innovation (RI) training in CDTs to assess how new RI understandings are being created, retained and transferred within the CDTs, questioning whether this process represents a programme of “institutionalisation”.

During the past decade, RI has become increasingly embedded within the EU and UK research context, appearing with greater frequency in funding calls and policy spaces. As part of this embedding, in its 2018 funding call for CDTs, the Engineering and Physical Sciences Research Council (EPSRC) required RI training to be included in the programme for all doctoral students.

The paper concludes that, at present, institutionalisation is highly variegated, with the greater organisational change required to truly embed RI mindsets.

The paper provides original, empirical research evidence of RI institutionalisation in UK CDTs, and, using a “learning organisation” lens, examines areas of value to both RI and learning organisation theory.

The purpose of this paper is three-fold. Firstly, through selected case studies, to provide an overview of how non-traditional data from digital public services were used as a source of knowledge for policymaking. Secondly, to argue for a design for policy approach to support the successful integration of non-traditional data into policymaking practice, thus supporting data-driven innovation for policymaking. Thirdly, to encourage a vision of the relation between data-driven innovation and public policy that considers policymaking outside the authoritative instrumental logic perspective.

A qualitative small-N case study analysis based on desk research data was developed to provide an overview of how data-centric public services could become a source of knowledge for policymaking. The analysis was based on an original theoretical-conceptual framework that merges the policy cycle model and the policy capacity framework.

This paper identifies three potential areas of contribution of a design for policy approach in a scenario of data-driven innovation for policymaking practice: the development of sensemaking and prefiguring activities to shape a shared rationale behind intra-/inter-organisational data sharing and data collaboratives; the realisation of collaborative experimentations for enhancing the systemic policy analytical capacity of a governing body, e.g. by integrating non-traditional data into new and trusted indicators for policy evaluation; and service design as approach for data-centric public services that connects policy decisions to the socio-technical context in which data are collected.

The small-N sample (four cases) selected is not representative of a broader population but isolates exemplary initiatives. Moreover, the analysis was based on secondary sources, limiting the assessment quality of the real use of non-traditional data for policymaking. This level of empirical understanding is considered sufficient for an explorative analysis that supports the original perspective proposed here. Future research will need to collect primary data about the potential and dynamics of how data from data-centric public services can inform policymaking and substantiate the proposed areas of a design for policy contribution with practical experimentations and cases.

This paper proposes a convergence, yet largely underexplored, between the two emerging perspectives on innovation in policymaking: data for policy and design for policy. This convergence helps to address the designing of data-driven innovations for policymaking, while considering pragmatic indications of socially acceptable practices in this space for practitioners.

Organizational citizenship behaviour (OCB) holds importance for employees and employers. Although it is culturally relativistic, its definition is West-dominated. Conceptual investigations in non-Western cultures yield different dimensions of OCB. Existing OCB models lack contemporariness and reciprocity. Their perspective may be biased towards management. Practice based on such theory gives poor outcomes. To address these gaps, the authors reconceptualized OCB in the Indian context from an employee perspective.

The authors conducted a qualitative study to build an employee-centric, inductive OCB model. The authors briefed respondents about the meaning of OCB and sought descriptions of instances of OCB performed or witnessed by them. The authors collected 478 descriptions from 49 private sector employees in India. The thematic analysis developed ten themes, each an OCB component, organized into four super-themes, denoting interpersonal, individual, organizational and community orientations.

Five OCB components are new emic additions by the model: Building social relationships, emotionally mature behaviour, learning and knowledge creation, housekeeping and event management, and higher order citizenship. Organizational governance participation is absent from the model. Housekeeping and relationship building are the most appearing OCBs, while voice is the least. Findings are discussed in relation to temporal and cultural background, respondent characteristics and perspective.

Organizations can better support employee OCBs by acknowledging OCBs unique to India, investigating low proportions of voice and civic virtue in the Indian model and informing people policies with this new knowledge.

This is the first attempt to build an inductive model of OCB in India from the employee perspective, making significant contributions to organizational theory and practice.

The literature on economic forecasting, is showing an increase in criticism, of the inaccuracy of forecasts, with major implications for economic, and fiscal policymaking. Forecasts are subject to the systemic uncertainty of human systems, considerable event-driven uncertainty, and show biases towards optimistic growth paths. The purpose of this study is to consider approaches to improve economic foresight.

This study describes the practice of economic foresight as evolving in two separate, non-overlapping branches, short-term economic forecasting, and long-term scenario analysis of development, the latter found in studies of climate change and sustainability. The unique case of Ireland is considered, a country that has experienced both steep growth and deep troughs, with uncertainty that has confounded forecasting. The challenges facing forecasts are discussed, with brief review of the drivers of growth, and of long-term economic scenarios in the global literature.

Economic forecasting seeks to manage uncertainty by improving the accuracy of quantitative point forecasts, and related models. Yet, systematic forecast failures remain, and the economy defies prediction, even in the near-term. In contrast, long-term scenario analysis eschews forecasts in favour of a set of plausible or possible alternative scenarios. Using alternative scenarios is a response to the irreducible uncertainty of complex systems, with sophisticated approaches employed to integrate qualitative and quantitative insights.

To support economic and fiscal policymaking, it is necessary support advancement in approaches to economic foresight, to improve handling of uncertainty and related risk.

While European Union Regulation (EC) 1466/97 mandates pursuit of improved accuracy, in short-term economic forecasts, there is now a case for implementing advanced foresight approaches, for improved analysis, and more robust decision-making.

Building economic resilience and adaptability, as part of a sustainable future, requires both long-term strategic planning, and short-term policy. A 21st century policymaking process can be better supported by analysis of alternative scenarios.

To the best of the authors’ knowledge, the article is original in considering the application of scenario foresight approaches, in economic forecasting. The study has value in improving the baseline forecast methods, that are fundamental to contemporary economics, and in bringing the field of economics into the heart of foresight.

Foresight J's journey started in 1999, and in 2022, it marked the conclusion of its 24 years of publication. This paper aims to provide an overall overview of important research trends published in Foresight J between 1999 and 2022 by conducting a quantitative analysis of the journal’s literature. The overarching goal is to provide valuable insights into the dynamics of scholarly communication, aiding researchers, institutions and policymakers in assessing the significance and influence of academic work, guiding future research directions and academic evaluation.

The two bibliometrics methodologies that make up the methodology of this article are scientific mapping and performance analysis. Authors have explained the development and composition of the Foresight J using these methods. The SCOPUS database is being used in current research to analyse several dimensions, such as the evolution of publications by year, the most cited papers, core authors and researchers, leading countries and prolific institutions. Moreover, the conceptual structure, scope, burst detection and co-occurrence analysis of the journal are mapped using network visualization software such as VOSviewer, CiteSpace and RStudio.

With a strong track record of output over the years, Foresight J has continued to develop in terms of publications. It is determined that “Saritas” is the author with the greatest overall impact. However, according to SCOPUS bibliometric data, “Blackman” and “Richardson” are the authors with the greatest relevance in terms of the quantity of articles. In addition, it becomes apparent that the USA, Australia and the UK are very productive nations in terms of publications. The most popular fields of the journal have always been forecasting, foresight, scenario planning, strategic planning, decision-making, technology and sustainable development. These are also the author keywords that appear the most frequently. In contrast, new study themes in the Foresight J include digital technologies, innovation, sustainability, blockchain, artificial intelligence and sustainability.

Several noteworthy research implications are provided by the bibliometric study of Foresight J. “Saritas” is the author with the most overall impact, indicating that the precise contributions and influence of this researcher in the fields of forecasting, foresight and related fields. Given that “Blackman” and “Richardson” are well-known writers, it is also critical to examine the scope and complexity of their contributions to potentially identify recurring themes or patterns in their writing. The geographic productivity results, which show that the USA, Australia and the UK are the top three countries for Foresight J publications, may encourage more research into regional differences, patterns of collaboration and the worldwide distribution of research endeavours in the context of forecasting and foresight. Popular fields including scenario planning, forecasting, foresight and sustainable development are consistent, indicating persistent research interests. Examining the causes of these subjects’ ongoing relevance can reveal information about the consistency and development of scholarly interests over time.

Foresight J’s bibliometric analysis has real-world applications for many stakeholders. It helps editors and publishers make strategic decisions about outreach and content by providing insights regarding the journal’s influence. Assessing organizational and author productivity helps institutions allocate resources more effectively. Policymakers acquire an instrument to evaluate research patterns and distribute funds efficiently. In general, bibliometric study of a journal helps decisionmakers in academic publishing make well-informed choices that maximize the potential of options for authors, editors, institutions and policymakers.

The societal ramifications of bibliometrically analysing Foresight J from 1999 and 2022 are substantial. This analysis highlights, over the past 24 years, research trends, technological developments and societal priorities have changed by methodically looking through the journal’s articles. Gaining knowledge about the academic environment covered by the journal can help raise public awareness of important topics and promote critical thinking. In addition, the analysis can support evidence-based decision-making by alerting decision makers to the influential research that was published in Foresight J. This could have an impact on the course of policies pertaining to innovation, technology and societal development.

This study presents a first comprehensive article that provides a general overview of the main trends and patterns of the research over the Foresight J’s history since its inception. Also, the paper will help the scientific community to know the value and impact of Foresight J.