We construct a unique data set that includes all reported institutional block trades on the London Stock Exchange and analyze the market reaction to buy and sell trades. We find that the type of investors behind the trade and the combination of the trade's size and the trader's resulting level of ownership are the major determinants of the information effects and the asymmetry between price impacts of buy and sell trades. In particular, large trades undertaken by fund managers, the most active investors in our sample, have strong information content, while, for the remaining trades, we report limited support for the information and the price impact asymmetry hypotheses. These results hold even after accounting for trade complexity and volatility effects in the regressions.

This study explores the Environmental, Social, and Governance (ESG) disclosure practices of 31 information technology firms listed on Borsa Istanbul (BIST), with a particular emphasis on transparency and accountability. Building on legitimacy, stakeholder, and signalling theories, the study develops a composite ESG disclosure index based on 18 binary indicators covering strategy, environmental performance, social impact, stakeholder engagement, and governance structures. Each indicator is equally weighted and combined into environmental, social, and governance sub-indices, which are then aggregated into a firm-level ESG disclosure score using a single min–max normalisation scheme. K-means clustering, validated through the elbow method and silhouette coefficient, is applied to identify groups of firms with similar ESG disclosure profiles. The empirical results show substantial heterogeneity in disclosure intensity across Turkish IT firms. A small group of companies exhibits proactive and comprehensive ESG communication, whereas many firms disclose only limited and fragmented information. Governance- and reporting-related indicators (C6 and C7) are particularly influential, underscoring the importance of standardised ESG reporting and board-level oversight in strengthening transparency. The study contributes to the emerging ESG disclosure literature by providing a methodologically consistent framework for assessing ESG transparency in the IT sector and offering practical insights for regulators, investors, and corporate decision-makers aiming to improve the reliability of ESG reporting in Turkey.

The aim of this study was to develop a model that classifies companies into high or low categories based on their return on equity (RoE), the most important indicator of financial performance, using sustainability and governance-related committee reports and reports shared with the public. As a sample, the RoE, sustainability, and governance variables of all 427 companies traded on the Istanbul Stock Exchange in 2024 were used. Using a 70:30 stratified split between the training and test sets, three tree-based models (XGBoost, LightGBM, and Random Forest) were used to perform a binary classification task. The findings show that tree-based models perform only slightly better than the naive majority class rule, and therefore, have limited overall classification power. A noteworthy finding from the study is that SHAP-based explainability analysis shows that the Corporate Governance Report (IMNG), the Integrated Report (IREP) and the existence of a Sustainability Committee (ICOM) rank higher in terms of SHAP-based global importance in the High RoE classification model, although their average contributions are small and, in the case of IMNG, predominantly negative for the probability of belonging to the High RoE class. Methodologically, the article moves away from traditional econometric methods based on ESG scores, instead combining a predictive classification structure with TreeSHAP-based explanations. These findings indicate a need for reporting practices that offer deeper content, clearer evidence of governance quality, and stronger data integrity to better support investors’ decision-making processes through sustainability and governance.

This study models the auditor–client relationship as a strategic game shaped by two-sided information asymmetry and examines how this structure influences key audit outcomes, namely audit delay and audit fees, in Türkiye. Using a game-theoretic framework complemented by empirical analysis, the study analyzes independent audit reports dated 31 December 2024 for 201 Borsa Istanbul firms audited by Big Four auditors. Two ordinary least squares models are estimated: one for audit delay and one for the logarithm of audit fees. The findings indicate that firm size and effort-related cost proxies play a central role in explaining audit fees, reflecting scale-related audit complexity. Financial risk, while not significantly associated with audit fees, is found to be negatively related to audit delay, suggesting that riskier firms may accelerate the reporting process through stronger monitoring, earlier planning, or tighter regulatory scrutiny. Audit opinion, by contrast, does not exhibit a statistically meaningful association with reporting delay, likely due to limited variation within the sample. Overall, the results partially support the risk–effort–cost mechanism proposed by the game-theoretic framework and highlight how institutional features of the Turkish audit market shape the relationship between risk and reporting timeliness. The study contributes to the literature by framing the audit process as a strategic decision environment and by providing updated evidence from an emerging market context.

Background/Objectives: The comparative evaluation of health system performance is becoming increasingly critical for policy makers in the context of rising health expenditures, demographic ageing, and the deepening of health inequalities between countries. In the existing literature, a substantial proportion of studies addressing health performance either examine causal relationships based on single health outcomes or rely on a single multi criteria decision making (MCDM) method based on equal or subjective weighting. This situation may lead to limitations in terms of method sensitivity and the reliability of the resulting rankings. This study addresses an important gap in the literature by directly tackling method sensitivity through the integrated use of objective weighting and multiple ranking methods. The aim of this study is to evaluate the health system performance of OECD countries within an integrated MCDM framework based on objective weighting. Methods: The analysis covers 27 OECD countries and is based on key indicators representing health performance, such as life expectancy, avoidable mortality, infant mortality rate, and maternal mortality rate. Criterion weights are determined objectively using the CRITIC method, and country performance rankings are obtained using the MAIRCA and MARCOS methods. Results: The findings indicate that there are substantial differences in health system performance among OECD countries. The high level of consistency between the results obtained from different ranking methods supports the methodological robustness of the findings. Conclusions: In this respect, the study contributes to the literature on health system performance evaluation at both methodological and applied levels and provides policy makers with a more reliable framework for comparative analysis.

Effective management of Environmental, Social, and Governance (ESG) practices within the framework of transparency and accountability in businesses is crucial for enhancing their compliance capacity in the face of regulatory pressures and contributing to the early detection of environmental and social risks. This study aims to evaluate the ESG disclosure-based performance of businesses operating in the textile, clothing, and leather sectors in Turkey by examining their ESG indicators from a transparency and accountability perspective. The CRITIC (Criteria Importance Through Intercriteria Correlation) method was used to determine the relative importance levels of the indicators, while the MABAC (Multi-Attributive Border Approximation Area Comparison) and COPRAS (Complex Proportional Assessment) methods were used to rank the performance of businesses within the framework of these indicators. Finally, clustering analysis was used to classify businesses with similar characteristics. The findings show that corporate governance principles are the most important indicator, and that Kordsa Teknik Tekstil A.Ş. and Söktaş Tekstil Sanayi ve Ticaret A.Ş. exhibit a significant and positive difference in terms of transparency and accountability in their ESG practices compared to other businesses. The combined use of CRITIC, MABAC, COPRAS, and cluster analysis offers an innovative, robust decision-making approach and holistic methodological integration for assessing ESG disclosure-based performance in the context of transparency and accountability for businesses.