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Introduction: The Great Financial Crisis of 2008 highlighted the importance of financial cycle fluctuations. While the regulatory response was to mandate higher bank capital requirements during the financial cycle upswing, academic research focussed on identifying the best performing early warning indicators to forecast financial cycle fluctuations that have proven to be often unrelated to business cycle changes. To safeguard the global financial system against the financial cycle fluctuations, Basel Committee of Banking Supervisors, based on first strands of empirical evidence, proposed the credit-to-GDP gap as the headline indicator tied to the countercyclical capital buffer. However, later research on this indicator identified certain concerns, among them subpar performance for economies with short available data series.

Aim of the Study: To this end this study aims to analyse various financial cycle indicators from a unique perspective of their potential viability under limited historical data availability.

Methods: For this purpose, a meta-study of existing research is carried out as well as an empirical study to compare performance of certain indicators for the sample of six countries in the Central, Eastern and South-Eastern European region, where long data series are not available.

Main Findings: It was found that certain approaches, among them calculation of raw credit growth rate and application of Hamilton filter, can supplement or possibly even outperform the Basel credit-to-GDP gap indicator under limited data availability.

Conclusion: Author concludes that for limited time series Basel credit-to-GDP gap can be potentially outperformed by other indicators and further research in this currently under-studied field is warranted.

Originality of the Paper: By using various financial cycle indicators that already proven their early warning prediction powers from previous research, this study focusses on their potential viability under limited historical data availability. Respective findings might be appreciated for supplementing policy-makers’ toolkits as complementary indicators in cases where there is no available long time series for financial cycle estimation, for example, such as countries that entered market economies relatively late.

The purpose of this paper is to bridge the gap between the pros and cons of a questionable finance-growth nexus.

Over 20 fundamental characteristics that have influenced the debate over the last decades have been examined. The empirical evidence is based on 196 outcomes from 20 studies. The author assesses the degree of heterogeneity and identify causes of the observed differentiation.

The findings also show evidence of publication bias. Overall, a genuine effect exists between financial development and economic growth. A finance-growth nexus might not be appealing in our era because of: endogeneity-based estimations, publication bias, and effects of financial activity. A historical justification has also been discussed.

Encouraging the publication of results with findings that are not consistent with the mainstream positive finance-growth nexus should provide new scholarly insights into the relationship. Depending on the specific context of sampled countries, the role of policy has also been to encourage financial development through measures that may expose countries to negative external shocks like financial crises. Policy makers that have been viewing the challenges of development exclusively from this point of view for the rewards of growth may not be getting the financial dynamics correctly.

Very few meta-analysis studies have focused on the finance-growth nexus.

The use of meta-analysis in information systems (IS) research has increased. Because this research domain has matured and an increasing number of empirical studies have become available, meta-analysis is now perceived as a useful approach to synthesize an increasing body of empirical research. The present paper gives an overview of meta-analytical techniques, the evolution of meta-analysis in IS, the focus of these studies and method choices made by authors.

This overview is based on 100 meta-analysis studies published in IS journals. These meta-analytical studies synthesize data from 6,262 empirical studies, and the meta-analyses were published between 1989 and 2020. The studies were coded with regard to 16 major method choices that IS researchers made when conducting meta-analyses.

This overview describes the key areas of meta-analysis (e.g. strategy and firm performance) and the journals that publish the meta-analysis. This overview also identifies method issues where meta-analyses have improved in recent years as well as issues that require some attention. Scholars receive guidance about good practices in terms of 16 major method choices related to (1) problem formulation, (2) literature search, (3) coding information, (4) analyzing and integrating effect sizes and (5) interpreting results and reporting findings.

Addressing the identified method issues helps authors of future meta-analyses to increase the transparency of reporting and the likelihood of getting published. The substantive findings of a meta-analysis also often depend on researchers' method choices. Similar overviews exist for other disciplines, such as marketing and management.

The purpose of this paper is to study a little researched relation: the relation from economic growth in a less developed country to the development aid it receives. Does economic growth influence donor aid allocation decisions?

The authors’ apply two different methodologies. First, a quantitative and systematic review is presented of the literature of 30 empirical studies of aid allocation where a growth coefficient is estimated. Second, a primary study is presented of the data using a panel of 147 countries for the period 1967‐2004.

The growth‐aid relation should be negative if humanitarian motives dominate aid allocation decisions. The result from both the meta‐analysis and the primary data analysis suggests a very small effect between lagged growth and aid allocations, with a dominating positive sign. This result appears to be driven partly by the large development banks.

No attempt has previously been made to summarize the literature on growth as a motive for giving aid. This paper offers the first attempt to do so, by presenting a meta‐analysis of the empirical literature, as well as analysis of the primary data.

A meta-study covering the past decade maps the development of Norwegian municipal planning, climate adaptation and institutional vulnerability towards climate change. This paper aims to explore the implementation of climate adaptive changes in Norwegian legal planning and building framework into municipal practice and policy instruments from 2007 to 2016. The study is planned to answer the question: what drivers ensure increased municipal efforts in their climate adaptive planning and building practice?

The paper presents empirical findings from two qualitative research projects, each with nine interviews of municipal key personnel within three municipalities’ planning and building services and an ongoing qualitative, expert interview-based study (eight individual/group interviews).

Risk reduction and climate resilience are still unsatisfactorily attended in many Norwegian municipalities. There is a gap between political and administrative levels in communicating bilateral expectations and needs for incorporation of climate adaptive measures. Policy instruments maintaining climate adaptation are in demand by different building process actors. Yet, extreme weather events seem to be the main drivers for actual implementation of climate change aspects into municipal policy instruments. Networking, both within and between municipalities, is an important strategy for learning climate adaptation.

Both globally and in Norway, the focus on climate change impacts is steadily increasing. Municipal risk and vulnerability analyses are statutory, as is the incorporation of the results into local plans at appropriate levels.

The originality of this paper is the meta-perspective over the past decade, the qualitative approach and the use of environmental psychology theories.

In this paper, the authors report the findings of an experiment on the effectiveness of gamification on work performance in a real industrial workplace setting with monotonous, repetitive work.

The authors conducted an experiment with a simple gamification application that the authors added to a given information system and compared the work performance of an experimental group (n = 16) with a control group (n = 15) over a period of one month.

The results of the authors’ experiment show that gamification of the workplace leads to a measurable improvement of work performance, creates prevailingly positive emotions and increases the motivation of the workers.

The authors’ findings provide reasons for conducting future research on the contiguity of gamification and the Hawthorne effect or similar phenomena. In this regard, it also seems necessary to take a closer look at who is really affected by a gamified environment and what the boundaries of the gamified environment are.

The authors demonstrate that gamification is a useful tool for process improvement. Furthermore, our results are helpful for a more successful implementation of gamification.

Gamification has proven to be effective in a large number of application contexts, such as education, health and crowdsourcing. Despite the generally positive evaluation of its effectiveness, gamification is still thought to work differently in different contexts. Therefore, there is a gap in the literature on this topic with respect to real industrial workplaces. To the best of the authors’ knowledge, the authors are among the first to have conducted a gamification experiment in a real industrial context.

This paper aims to report an analysis of the graphical representations of 14 corporate real estate (CRE) models. It does this to establish the systematic, metatheoretical requirements for modelling CRE alignment which to date have been disguised in a multitude of models.

This meta study of CRE alignment models used a qualitative hermeneutic method to inductively develop understanding of the models’ constituent parts. Several iterations of graphical and textual analysis were required to do this. Further deductive analysis sought to understand the individual models relative to this new understanding.

The analysis showed that a total of 12 components have been used to model CRE alignment. These are divided into four Building Blocks: understanding corporate strategy; understanding real estate performance; making real estate strategy; and implementing real estate strategy. While every model’s representation contained the four Building Blocks, few models contained all 12 components, though all contained at least seven. Completeness of representation in this study should not be inferred as equating to effectiveness as an alignment process. Various feedback mechanisms were also evident between the components.

The analysis provides the most complete map of the modelling requirements for CRE alignment. It differs from previous theoretical work on alignment by synthesising a metatheory of alignment representation. By providing a more coherent theory by which to model CRE alignment the metatheory provides a consistent basis on which to investigate and theorise aspects of CRE alignment.

The purpose of this paper is to describe and compare various theoretical models of decision making such as classical rational decision making, left‐brain/right‐brain dominance decision making, utilization of tacit knowledge in decision making, utilization of intuition in decision making, utilization of emotional intelligence in decision making, a systems approach to decision making, and spirit‐based decision making.

Studies on different modalities of decision making are reviewed, discussed, and compared.

The traditional assumption of the optimality of rational decision making may be improved by including other dimensions of decision making. It is posited that organizations that encourage and support multi‐dimensional decision making, which utilizes the rational, intuitional, emotional and spiritual aspects of the whole person, develop better management–employee relations, more creative problem solving, and better market place performance.

Development and testing of instruments that measure multi‐dimensional decision making would extend the scope of this study.

This paper compares different styles of decision making to assist the manager in making optimal decisions. By expanding on the traditional rational decision making model to include other dimensions of decision‐making, managers are able to capture additional information in framing their decisions.

Meta-synthesis of the research evidence adds value to the process of literature reviewing, providing useful knowledge for researchers, practitioners and policymakers. The aim of the chapter is to explain what meta-synthesis involves and how it illuminates our understanding of concepts. Previous papers on meta-synthesis (by the author) have reviewed research strategies in information behaviour research and methods for meta-synthesis, discussed application of meta-synthesis to research on information behaviour of women, and proposed methods suitable for integrating information literacy research. Meta-synthesis methods have been applied to many areas of social science research. The literature review examines how to reduce the risks involved in suitable for integrating qualitative research or qualitative and quantitative research; outlines the main approaches used in meta-synthesis before explaining the processes used in a meta-synthesis of research on information behaviour of women, reflects on the meta-synthesis methods used, and which might have been used, and shows what meta-synthesis achieves. Meta-synthesis should be used more in information behaviour research, but it is a rigorous process, requiring time and effort to get useful results. On the other hand, meta-synthesis provides more new knowledge, and a deeper understanding of our ideas, than a conventional literature review.

Upon the realization of the need for guideline in cross-organizational data integration, in an exploratory manner, this study developed a public data governance framework, specifically, the governance for integrated public data (GIPD) framework and identified the influential factors of its successful implementation. This framework was then subjected to an analysis of a real data integration case in the South Korean public sector to test its efficacy.

To develop the GIPD framework, the authors conducted an extensive meta study, focus group interviews and the analytic hierarchy process involving field experts. Further, the authors performed topic modeling on documents from Korean research and development data integration projects, and compared the extracted factors to those of the GIPD to illustrate the latter's usefulness in a real case.

Legislation, policy goals and strategies, operation organization, decision-making council, financial support size and objective, system development and operation, data integration, data generation, system/data standardization and master data management were derived as the 10 important factors in implementing the GIPD framework. The illustrative case of Korea revealed that decision-making council, financial support size and objective, legislation, data generation and data integration were insufficient.

Although this study reveals important findings, it has a few limitations. First, the potential factors for data governance might vary depending on the attribute of the “interviewee” (such as their career or experience period) and the goal and area of GIPD framework building. Second, the inherent limitation of topic modeling in determining topics from groups of extracted keywords means that topics may be interpreted in various ways, depending on the perspective of the expert.

This study is highly significant in that it provides a starting point for discussions on the issue of data integration among public institutions. Therefore, although this study examined public data governance based on R&D data, it will contribute to providing a sufficient guideline for any type of inter-institutional data governance framework, what to discuss and how to discuss between institutions.

The findings are expected to provide a roadmap to formulate practical guidelines on inter-institutional data cooperation and a diagnostic matrix to improve the existing data governance system, especially in the public sector, from the existing practice of empirical analysis using a mixed methodology approach.