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The crux of this paper is to unveil efficient features and practical tools that can predict credit default.

Annual data of non-financial listed companies were taken from 2000 to 2020, along with 71 financial ratios. The dataset was bifurcated into three panels with three default assumptions. Logistic regression (LR) and k-nearest neighbor (KNN) binary classification algorithms were used to estimate credit default in this research.

The study’s findings revealed that features used in Model 3 (Case 3) were the efficient and best features comparatively. Results also showcased that KNN exposed higher accuracy than LR, which proves the supremacy of KNN on LR.

Using only two classifiers limits this research for a comprehensive comparison of results; this research was based on only financial data, which exhibits a sizeable room for including non-financial parameters in default estimation. Both limitations may be a direction for future research in this domain.

This study introduces efficient features and tools for credit default prediction using financial data, demonstrating KNN’s superior accuracy over LR and suggesting future research directions.

This study aims to examine the impact of extensible business reporting language (XBRL) technology and its functionality on various aspects of financial reporting and its overall quality.

To conduct this study, data was collected from a variety of professionals, including accountants, auditors, tax advisors and others. A structured research instrument was developed, and the collected data were analysed using structural equation modelling and mediation analysis techniques.

The study’s results showed that XBRL technology and its functionality have a noteworthy impact on different aspects of financial reporting. Moreover, the various aspects of financial reporting positively affect the overall quality of financial reporting.

This study solely relied on the opinions of various professionals regarding the current issue under investigation and did not empirically assess the reporting practices of companies by examining their XBRL-based reports. Additionally, it concentrated solely on financial reporting aspects and did not account for non-financial aspects. The main theoretical contributions of this paper to technology in financial reporting, XBRL and accounting literature are that it sheds light on the influence of the use of technologies in the business reporting process and their influence on various aspects of business reporting, which has only received confined focus from earlier studies so far.

This study’s findings could provide valuable insights to the managerial teams of organizations seeking to digitize their business reporting practices, specifically in areas such as regulatory compliance, integrated reporting and timely dissemination of reports in a sustainable way. Furthermore, it could help these teams reap the benefits of technology for various regulatory compliance matters.

This study could assist business organizations and regulatory authorities in adopting and implementing technology such as XBRL for accounting and business reporting. Furthermore, the study’s findings can aid in enhancing financial reporting practices by considering emerging aspects such as ESG and sustainability aspects.

This paper aims to examine whether the cooperation between female chief financial officers (CFO) and the proportion of female directors would impact investment efficiency. The investigation is grounded in the increasing number of female top managers globally and the notion that female tends to cooperate more with other female than with male.

This study uses publicly listed firms in Bursa Malaysia from 2016 to 2020, which yielded a sample of 2,022 firm-year observations. The authors used multivariate ordinary least square regression to test the relationship, and to correct for the selection bias, the Heckman selection and PSM test were used.

The authors find a positive relationship between female CFOs and investment efficiency. A higher proportion of female directors accentuates this result. The findings support the homophily argument that similar characteristics (gender) promote cooperation. This shows that cooperation between female CFOs and directors improves investment efficiency. The results suggest that the improvement in investment efficiency could relate to higher managerial discretion for female CFOs and their ability to collaborate with female directors. These results are robust to a series of additional endogeneity tests. The findings have important implications for policymakers and firms to encourage more appointments of females in top management positions.

By highlighting the cooperation between female CFOs and female directors, this study contributes to the understanding that cooperation among females improves investment efficiency.

This paper aims to develop a conceptual framework informed by a literature review. This framework aims to deepen and broaden the understanding of the relationship between corporate governance mechanisms and non-financial reporting (NFR) through qualitative research approaches.

A review of corporate governance and NFR literature and existing research frameworks leads to the development of a conceptual framework to encourage future qualitative accounting research on the corporate governance mechanisms for NFR.

Few studies consider the complex interrelationships between NFR and corporate governance mechanisms. Quantitative studies using secondary data sources dominate accounting research on the topic. Of the small number of qualitative studies, many are theoretical and offer little new knowledge about the effectiveness of corporate governance mechanisms in practice. The research framework, developed from a literature review and consideration of multiple qualitative approaches, proposes numerous avenues for future research.

This paper is based on a scoping review of the literature using peer-reviewed journal papers. Other researchers may have identified additional literature for inclusion, including grey literature.

More qualitative research into NFR and corporate governance mechanisms may help to guide practitioners seeking to incorporate sustainability into their governance practices.

The critical relationship between NRF and corporate governance is under-explored in research yet has significant consequences for organisations pursuing sustainability.

The authors develop a conceptual framework for qualitative accounting research on NFR and corporate governance, addressing key outstanding questions in this area and considering different theoretical perspectives when approaching this critical topic. Although there is scope for further research in general in this promising area, including quantitative reviews and discursive studies, qualitative research would be of particular value. The authors also outline multiple directions for nurturing academic debate.

This study aims to propose a longitudinal analysis of motivations for Integrated Reporting (IR) adoption, internal changes, the benefits of IR implementation and compliance challenges.

The authors analyse a longitudinal case study of an Italian-listed company (Eni) participating in the IR-Pilot Programme (PP) and covering 10 years of IR adoption. The analysis was based on a mixed-method approach that included semi-structured interviews, content analysis of annual reports and triangulation with other data sources. Results are discussed regarding institutional theory, legitimacy theory and diffusion of innovation theory.

The study suggests that motivations for adopting IR change over time and participation in the IR-PP helps Eni acquire a comprehensive and substantial integrated view of value creation over time, makes integrated culture a key factor for strategic business sustainability and confirms the readiness of early adopters to comply with the non-financial Directive (NFD).

This study, among the few longitudinal case studies, provides organisations, regulators and academics with insights into the motivations driving the successful adoption and implementation of IR and the NFD. The results may help companies consider one of the tools currently deemed to bring sustainability into action and participation in pilot groups.

This study aims to explore the association between chief executive officer (CEO) tenure and the quality of information disclosed through integrated reporting quality (IRQ), which combines financial and non-financial data. The authors also investigate how formal (e.g. board independence and gender diversity) and informal (e.g. corporate culture) governance mechanisms influence this association. By analysing these factors, the authors expect to provide valuable insights on the impact of CEO tenure and governance structures on the comprehensive nature of integrated reporting.

This study uses a sample of the top 200 Australian Securities Exchange (ASX)-listed companies from 2015 to 2019. IRQ is measured through levels of compliance with the integrated reporting (IR) framework proposed by the International Integrated Reporting Council (IIRC). The hypotheses are tested using multiple regression analyses.

The authors find that CEO tenure is negatively associated with IRQ. Furthermore, CEO tenure has a more positive influence on IRQ in the early CEO tenure years than later ones. The authors' study finds that the association between CEO tenure and IRQ is insignificant when firms have a high level of monitoring, as measured by board independence and gender diversity. The authors also document that competitive corporate culture moderates the negative association between CEO tenure and IRQ.

The authors' study highlights the significant impact of internal formal and informal governance mechanisms on disclosure practices in Australia's voluntary IR environment. By shedding light on these factors, the authors' research enhances understanding of Australian companies' IR practices and offers valuable insights for scholars, policymakers and practitioners in the field.

The goal of this work is to evaluate how digital transformation disclosure in corporate news and press releases affects stock prices. We examine American and Chinese companies from the energy and industry sectors for two periods: pre-COVID-19 and during the COVID-19 pandemic.

To estimate the effects of disclosure of information related to digital transformation, we applied the bag-of-words (BOW) method. As the benchmark dictionary, we used Kindermann et al. (2021), with the addition of original dictionaries created via Latent Dirichlet allocation (LDA) analysis. We also employed panel regression analysis and random forest.

For USA energy sector, all aspects of digital transformation were insignificant in pre-COVID-19 period, while sustainability topics became significant during the pandemic. As for the Chinese energy sector, digital strategy implementation was significant in pre-pandemic period, while digital technologies adoption and business model innovation became relevant in COVID-19 period. The results show the greater significance of digital transformation aspects for industrials sectors compared to the energy sector. The result of random forest analysis proves the efficiency of the authors’ dictionary which could be applied in practice. The developed methodology can be considered relevant.

The research contributes to the existing literature in theoretical, empirical and methodological ways. It applies signaling and information asymmetry theories to the financial markets, digital transformation being used as an instrument. The methodological contribution of this article can be described in several ways. Firstly, our data collection process differs from that in previous papers, as the data are gathered “from investor’s point of view”, i.e. we use all public information published by the company. Secondly, in addition to the use of existing dictionaries based on Kindermann et al. (2021), with our own modifications, we apply the original methodology based on LDA analysis. The empirical contribution of this research is the following. Unlike past works, we do not focus on particular technologies (Hong et al., 2023) connected with digital transformation, but try to cover all multi-dimensional aspects of the transformational process and aim to discover the most significant one.

Ethiopia has enacted laws on transparency and disclosure of information in state-owned enterprises (SOEs). However, these laws are not strict enough, with the transparency and disclosure practices disappointing in the country. Thus, this study aims to investigate the legal framework governing transparency and disclosure in SOEs.

This study uses doctrinal, qualitative and comparative approaches. Domestic legal texts are appraised based on the organization for economic co-operation and development Guideline on Corporate Governance of State-owned Enterprises, the World Bank Toolkit on Corporate Governance of State-owned Enterprises and best national practices. This approach has been further corroborated by qualitative analysis of the basic principles of transparency and disclosure.

The finding reveals that the laws on transparency and disclosure do not comply with global practices and are inadequate to ensure transparency and discourse in SOEs. They fail to establish appropriate disclosure frameworks and practices at the SOE and state-ownership entity levels. They also indiscriminately subject enterprises to multiple auditing functions and conflicting responsibilities.

To the author’s knowledge, this study is the first legal literature on transparency and disclosure in Ethiopian SOEs. This study assists the state as owner in reforming the laws and uplifting SOEs from their current unpleasant condition. It can also become a reference for future research.

This paper aims to introduce a new perspective on long-term stock return predictability by focusing on the relative (individual and hybrid) informative power of a wide range of accounting (firm-related), technical and macroeconomic factors while considering the past performance of the stocks using machine learning algorithms.

The sample includes a panel data set of 94 non-financial firms listed in Egyptian Exchange 100 index from 2014: Q1 to 2019: Q4. Relativity has been investigated by comparing relevant factors’ individual and combined informative power and differentiating between losers and winners based on historical stock returns. To predict the quarterly stock returns, Gaussian process regression (GPR) has been used. The robustness of the results is examined through the out-of-sample test. This study also uses linear regression (LR) as a benchmark model.

The past performance and the presence of other predictors influence the informative power of relevant factors and hence their predictive ability. The out-of-sample results show a trade-off between GPR and LR with proven superiority to GPR in limited experiments. The individual informative power outperforms the hybrid power, in which macroeconomic indicators outperform the remaining sets of indicators for losers, while winners show mixed results in terms of various performance evaluation metrics. Prediction accuracy is generally higher for losers than for winners.

This study provides interesting insight into the dynamic nature of the predictor variables in terms of stock return predictability. Hence, this study also deepens the understanding of asset pricing in a way that directly contributes to practitioners’ portfolio diversification strategies.

In concern of the chaos of factors in the literature and its accompanying misleading conclusions, this study takes another look at the approach that studies stock return predictability. To the best of the authors’ knowledge, this is the first study in the Egyptian context that re-examines the predictive power of the previously discovered factors from a different perspective that highlights their relative nature.

The objective of this study is to examine developments in the discursive practice of non-financial reporting in the public healthcare sector. In doing so, the authors investigate how the main reform foci of productivity and quality are represented, with a specific focus on the patient.

Drawing on critical discourse analysis (CDA), the authors conduct a longitudinal study (2007–2018) of healthcare reporting foci across the five administrative regions responsible for public hospitals in Denmark. The study analyses sixty annual reports and draws on contemporary reform documents over this period. CDA enables a micro-textual analysis, combined with macro-insights and discussions on social practice.

The findings show complex webs of presentation strategies, but in particular two changes occur during the period. First, the patient is centred throughout but the framing changes from productivity and waiting lists to quality and dialogue. Second, in the first years, the regions present themselves as actively highlighting financial and quality concerns, which changes to a passive and indirect form of presentation steered by indicators and patient legislation enforced by central government. This enhances passivity and distance in healthcare regional non-financial reporting where the regions seek to conform to such demands. Simultaneously, however, the authors find a tendency to highlight very different local initiatives, which shows an attempt to go beyond a pure automatic mode of reporting found in earlier studies.

Responding to the literature on both healthcare and financial reporting, this study identifies novel links between micro-level texts and macro-level social practices, enabling insights into the potentially intertwined impacts of public-sector reporting. The authors offer insights into the complexity of the construction of non-financial reporting in the public sector, which has a wider impact and different intentions than private-sector reporting.