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Despite its devastating nature, the COVID-19 pandemic has also catalyzed a substantial surge in the adoption and integration of technological tools within economies, exerting a profound influence on the dissemination of information among participants in stock markets. Consequently, this present study delves into the ramifications of post-pandemic dynamics on stock market behavior. It also examines the relationship between investors' sentiments, underlying behavioral drivers and their collective impact on global stock markets.

Drawing upon data spanning from 2012 to 2023 and encompassing major world indices classified by Morgan Stanley Capital International’s (MSCI) market and regional taxonomy, this study employs a threshold regression model. This model effectively distinguishes the thresholds within these influential factors. To evaluate the statistical significance of variances across these thresholds, a Wald coefficient analysis was applied.

The empirical results highlighted the substantive role that investors' sentiments and behavioral determinants play in shaping the predictability of returns on a global scale. However, their influence on developed economies and the continents of America appears comparatively lower compared with the Asia–Pacific markets. Similarly, the regions characterized by a more pronounced influence of behavioral factors seem to reduce their reliance on these factors in the post-pandemic landscape and vice versa. Interestingly, the post COVID-19 technological advancements also appear to exert a lesser impact on developed nations.

This study pioneers the investigation of these contextual dissimilarities, thereby charting new avenues for subsequent research studies. These insights shed valuable light on the contextualized nexus between technology, societal dynamics, behavioral biases and their collective impact on stock markets. Furthermore, the study's revelations offer a unique vantage point for addressing market inefficiencies by pinpointing the pivotal factors driving such behavioral patterns.

This study aims to investigate the impact of earnings predictability and truthfulness on nonprofessional investors’ investment willingness.

Earnings predictability is captured by quarterly earnings autocorrelation, and earnings truthfulness is indicated by real earnings management (REM). The average of investment attractiveness and willingness measures investment willingness. The authors use experiments to isolate the impact of quarterly earnings autocorrelation and REM on investors’ investment behaviors.

From the 2 × 2 design, the authors observe that investors weight more on earnings predictability than earnings truthfulness.

The generalization of the findings may be constrained for the following reasons. First, the authors use only one proxy, REM, to measure earnings truthfulness. In addition, the authors provide the participants, Amazon Mechanical Turk, with earnings predictability. Results may no longer hold if each participant has different understanding and analysis of earnings predictability.

In periods of unprecedented and severe financial uncertainty (i.e. the COVID-19 pandemic), investors rely more on earnings predictability than on earnings truthfulness. The study assists managers to strategically emphasize the predictability of earnings to attract investors, especially when firms face financial challenges or uncertainty.

This study contributes to understanding investor behavior and the critical role of earnings predictability and truthfulness in shaping investment decisions.

This paper contributes to the literature of earnings properties in financial reporting, particularly by shedding light on the nuanced interplay between earnings predictability and earnings truthfulness. The research also demonstrates that elevated earnings autocorrelation indirectly stimulates investment willingness by enhancing the investors’ perception of earnings persistence of targeted firms.

This study aims to investigate the impact of digital leadership (capabilities, experience, predictability and vision) and green organizational culture on firms' digital transformation and financial performance. Additionally, the research aims to evaluate the mediating role of digital transformation in the relationship between digital leadership and firms' financial performance.

A purposive sampling technique was employed to identify and select individuals with relevant expertise and experiences in the field of digital transformation. A total of 164 responses were collected, and the questionnaire was designed based on a five-point Likert-type scale. The data were analyzed using SmartPLS 4 (Statistical Software for Structural Equation Modeling).

The findings indicate that digital leadership capabilities, experience, predictability and vision do not directly impact firms' performance. However, there is an indirect influence on firms' performance through digital transformation. While both digital transformation and green organizational culture (GOC) positively influence firms' financial performance, GOC, leader predictability and leader vision positively influence digital transformation. The results confirm that digital transformation mediates the relationship between capabilities, experience, predictability and vision and firms' financial performance.

The study highlights that strategic capabilities can enhance value-added processes during digital transformation, contributing to sustainability in the digital era. Overall, this research significantly advances both theoretical understanding and practical applications in the context of digital leadership and its impact on firms. Limited digital transformation stages among Malaysian firms impact the research, with some entities cautious about data disclosure and having limited cooperation with researchers. Gathering data from diverse sources would have strengthened the findings and methodological rigor of this multilevel study. Despite these limitations, the research offers fresh insights into the role of GOC, different facets of digital leadership and their influence on digital transformation and financial performance. This enhances existing knowledge and challenges assumptions of the transformational leadership theory (TLT) framework.

The study opens the door to further research into distinct leadership components and their effects in a similar context. By highlighting the positive influence of capabilities, experience, predictability and vision on digital transformation, it expands the theoretical and empirical scope in the realm of digital leadership. These findings encourage critical examination, refinement and evolution of TLT, providing insights for leaders and managers as they navigate digitalization, financial performance and digital leadership within organizations. In an era of digital transformation, leaders play a central role in building a psychologically safe environment and nurturing digitally skilled teams capable of managing technological changes. Leaders should possess the digital capabilities, experience, vision and predictability necessary to drive digital transformation, mitigate potential threats and adapt to the dynamic digital landscape.

These findings support government initiatives to accelerate digitalization and Industry 4.0 implementation. Collaboration between the government and private organizations is essential to create policies and practices that facilitate broad participation in digital transformation programs. Policymakers must adopt a proactive approach to address issues related to Internet accessibility, trade barriers, financing access and resource reallocation. These policies aim to ensure a high-quality and affordable digital infrastructure, cultivate trust in digital technologies and equip organizational leaders with the necessary digital skills.

This research provides valuable insights for practitioners to enhance firms' digital transformation. As a practical contribution, this study’s findings can inform how firms can better manage their key digital leadership resources and GOC to foster digital transformation and improve their financial performance.

Using the next-day and next-week returns of stocks in the Korean market, we examine the association of option volume ratios – i.e. the option-to-stock (O/S) ratio, which is the total volume of put options and call options scaled by total underlying equity volume, and the put-call (P/C) ratio, which is the put volume scaled by total put and call volume – with future returns. We find that O/S ratios are positively related to future returns, but P/C ratios have no significant association with returns. We calculate individual, institutional, and foreign investors’ option ratios to determine which ratios are significantly related to future returns and find that, for all investors, higher O/S ratios predict higher future returns. The predictability of P/C depends on the investors: institutional and individual investors’ P/C ratios are not related to returns, but foreign P/C predicts negative next-day returns. For net-buying O/S ratios, institutional net-buying put-to-stock ratios consistently predict negative future returns. Institutions’ buying and selling put ratios also predict returns. In short, institutional put-to-share ratios predict future returns when we use various option ratios, but individual option ratios do not.

This study examines the association between internal corporate governance mechanisms (i.e. board of directors and audit committee) and the information value of bank earnings. The authors comparatively assess this association across different bank types, Islamic versus conventional banks. The authors also investigate the mediating effect of Shariah governance.

The authors utilize a unique and an international sample of 723 bank-year observations representing 100 listed banks from 16 countries during the period 2007–2015. The authors investigate the characteristics of the board of directors and audit committee (i.e. size and independence) and employ three core analyses for earnings informativeness (i.e. earnings persistence, cash flow predictability and reliability of loan loss provisions). Additional analyses address Shariah supervisory boards’ (SSBs’) size, financial expertise and multiple outside directorships. The authors use the random-effect Generalised Least Squares (GLS) estimation technique and provide several robustness checks and sensitivities.

The authors find that, on average, having large and independent boards (and audit committees) increases the informativeness of reported earnings for banks. Conditional on bank type, our results report strong evidence for differential effects across the two alternative banking systems. In Islamic banks, large and independent board of directors (and audit committees) is positively associated with all measures of information value. There is insignificant evidence for conventional banks. However, SSBs show no significant effect on the reported earnings’ informativeness.

This is the first study, to the best of our knowledge, that empirically and comparatively assesses the information value of reported earnings in association with effective internal governance while recognizing the institutional characteristics of different bank types. The authors offer new insights to policymakers, investors and other stakeholders located within countries operating on a dual banking system. The results could help regulators to improve their rules/guidance related to double-layer governance and financial reporting quality.

This study aims to endeavour to decode artificial intelligence (AI)-based tokens' complex dynamics and predictability using a comprehensive multivariate framework that integrates technical and macroeconomic indicators.

In this study we used advance machine learning techniques, such as gradient boosting regression (GBR), random forest (RF) and notably long short-term memory (LSTM) networks, this research provides a nuanced understanding of the factors driving the performance of AI tokens. The study’s comparative analysis highlights the superior predictive capabilities of LSTM models, as evidenced by their performance across various AI digital tokens such as AGIX-singularity-NET, Cortex and numeraire NMR.

This study finding shows that through an intricate exploration of feature importance and the impact of speculative behaviour, the research elucidates the long-term patterns and resilience of AI-based tokens against economic shifts. The SHapley Additive exPlanations (SHAP) analysis results show that technical and some macroeconomic factors play a dominant role in price production. It also examines the potential of these models for strategic investment and hedging, underscoring their relevance in an increasingly digital economy.

According to our knowledge, the absence of AI research frameworks for forecasting and modelling current aria-leading AI tokens is apparent. Due to a lack of study on understanding the relationship between the AI token market and other factors, forecasting is outstandingly demanding. This study provides a robust predictive framework to accurately identify the changing trends of AI tokens within a multivariate context and fill the gaps in existing research. We can investigate detailed predictive analytics with the help of modern AI algorithms and correct model interpretation to elaborate on the behaviour patterns of developing decentralised digital AI-based token prices.

The purpose of this paper is to examine the supervening loss of inter-organisational trust in long-term commercial contracts. The underlying research question is whether contract law – the legal institution regulating economic exchanges – should intervene and enable a party to a long-term commercial contract to extricate itself from a situation where a relationship of trust has broken down irretrievably.

This paper uses doctrinal methodology and theoretical conceptualisation to answer the underlying research question. The legal instrument chosen for analysis purposes is the UNIDROIT Principles of International Commercial Contracts. This paper also draws on extant literature on inter-organisational trust (including conceptual and empirical studies) to support the arguments and propositions. Furthermore, this study proceeds to assess the substantive justifiability of the proposed remedial measure using four normative values: legal certainty and predictability, protection of the performance interest, economic efficiency and the preservation of the relation.

The central argument put forward in this paper is the reformulation of draft Article 6.3.1 proposed by the UNIDROIT Working Group on Long-Term Contracts, which confers a novel right to terminate for a compelling reason. This paper presents a multidimensional model of inter-organisational trust that would serve as the conceptual framework for the proposed reformulation of the provision and establishes a coherent juridical basis for the legal solution that would accord with the Principles of International Commercial Contracts’ general remedial scheme. As for the normative assessment, this paper demonstrates that the proposed remedial measure would significantly promote efficient outcomes and positively serve the norms of legal certainty, protection of the performance interest and the preservation of the relation.

This paper addresses the lacuna in current legal scholarship in relation to the adverse socio-economic effects following trust violation and deterioration in inter-organisational relationships. Additionally, the propositions and findings should contribute to the workings of the UNIDROIT in adopting new rules and principles that would serve the special requirements of cross-border trade.

Offsite construction (OC) is an efficient method to reduce waste in the construction industry from a circular economy perspective. Yet, its uptake is subdued by the ambiguities around its supply chain. Hence, the purpose of this study is twofold: to identify the OC project delivery models, the limitations in their procurement approach to facilitate the resilience of the supply chain and interventions to promote supply chain resilience (SCR) and to identify the gaps in the existing procurement process and propose further research areas that implement strategies to improve SCR.

The study was conducted as a systematic literature review. In total, 41 peer-reviewed research papers published between 2013 and 2023 were shortlisted through the preferred reporting items for systematic reviews and meta-analysis guidelines. A descriptive analysis was conducted, followed by a thematic analysis.

The descriptive analysis reveals that the emphasis on digitising OC has shifted to transforming the business model, procurement and supply chain with a human-centric view. In thematic analysis, the predictability of the SC partners and the probabilities of evaluating the prospects are revealed as arbitrary characteristics in the current procurement strategies. Rewarding collaborative relationships among SC partners and incorporating provisions to postpone the module delivery are some interventions to promote flexibility. Drafting comprehensive and effective contracts that address transparency issues and facilitating the need for continuous development of capabilities through procurement are among the further research avenues proposed.

This study is a precursor demonstrating the potential of the procurement process to implement the decrees of SCR for better goal congruence of the OC supply chain.

We propose a risk factor for idiosyncratic entropy and explore the relationship between this factor and expected stock returns.

We estimate a cross-sectional model of expected entropy that uses several common risk factors to predict idiosyncratic entropy.

We find a negative relationship between expected idiosyncratic entropy and returns. Specifically, the Carhart alpha of a low expected entropy portfolio exceeds the alpha of a high expected entropy portfolio by −2.37% per month. We also find a negative and significant price of expected idiosyncratic entropy risk using the Fama-MacBeth cross-sectional regressions. Interestingly, expected entropy helps us explain the idiosyncratic volatility puzzle that stocks with high idiosyncratic volatility earn low expected returns.

We propose a risk factor of idiosyncratic entropy and explore the relationship between this factor and expected stock returns. Interestingly, expected entropy helps us explain the idiosyncratic volatility puzzle that stocks with high idiosyncratic volatility earn low expected returns.