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This paper aims to investigate the relationship between corporate environmental, social and governance (ESG) ratings and leverage manipulation and the moderating effects of internal and external supervision.

The authors draw on a sample of Chinese non-financial A-share-listed firms from 2013 to 2020 to explore the effect of ESG ratings on leverage manipulation. Robustness and endogeneity tests confirm the validity of the regression results.

ESG ratings inhibit leverage manipulation by improving social reputation, information transparency and financing constraints. This effect is weakened by internal supervision, captured by the ratio of institutional investor ownership, and strengthened by external supervision, captured by the level of marketization. The effect is stronger in non-state-owned firms and firms in non-polluting industries. The governance dimension of ESG exhibits the strongest effect, with comprehensive environmental governance ratings and social governance ratings also suppressing leverage manipulation.

Firms should strive to cultivate environmental awareness, fulfil their social responsibilities and enhance internal governance, which may help to strengthen the firm’s sustainability orientation, mitigate opportunistic behaviours and ultimately contribute to high-quality firm development. The top managers of firms should exercise self-restraint and take the initiative to reduce leverage manipulation by establishing an appropriate governance structure and sustainable business operation system that incorporate environmental and social governance in addition to general governance.

Policymakers and regulators should formulate unified guidelines with comprehensive criteria to improve the scope and quality of ESG information disclosure and provide specific guidance on ESG practice for firms. Investors should incorporate ESG ratings into their investment decision framework to lower their portfolio risk.

This study contributes to the literature in four ways. Firstly, to the best of the authors’ knowledge, it is among the first to show that high ESG ratings may mitigate firms’ opportunistic behaviours. Secondly, it identifies the governance factor of leverage manipulation from the perspective of firms’ subjective sustainability orientation. Thirdly, it demonstrates that the relationship between ESG ratings and leverage manipulation varies with the level of internal and external supervision. Finally, it highlights the importance of governance in guaranteeing the other two dimensions’ roles by decomposing overall ESG.

This study aims to revisit the relationship between Shariah-compliant firms and earnings management. Specifically, the authors examine whether Shariah-certified firms have lower earnings management than non-Shariah-certified firms and how often a firm must hold its certification to observe considerably reduced earnings management. This study also explores how senior management ethnic dualism affects the association of Shariah certification and earnings management.

The authors analyze the hypothesized association between Shariah certification and earnings management using a panel regression model and several robustness tests, including the Heckman selection model. The sample consists of 547 nonfinancial firms listed on the Bursa Malaysia stock exchange, with 5,478 firm-year observations over the 2001–2016 sample period.

Shariah certification is found to mitigate earnings management, particularly for firms that consistently retain their Shariah status. The longer firms retain their Shariah certification continually, the lower the earnings management. Additionally, the results indicate that the negative impact of Shariah certification on earnings management is driven by ethnic duality when a specific ethnic group dominates the top management.

Firms’ commitment to religious-based screening and continuation of certification plays a significant role in improving earnings quality. Firms are committed to abiding by the Shariah code of conduct instead of using the Shariah status for reputation purposes to attract investors.

For investors, the continuous compliance status is a crucial indicator of a firm’s commitment to comply with Shariah principles and to mitigate earnings management. Regarding policy implications, Shariah-compliance guidelines can constrain earnings manipulation, especially among firms lacking ethnic diversity.

The study shows that Shariah certification must be maintained consecutively to reduce earnings management. Shariah certification’s governance function is crucial in ethnically homogeneous firms, primarily when one ethnic group dominates the senior management.

The purpose of this paper is to analyze the interaction between internal factors of corporate governance, especially the relationship between equity checks and balances and corporate social responsibility (CSR), and further analyze the mediating of green innovation performance and the moderating role of environmental uncertainty.

This study adopts a sample of Chinese A-share listed companies on the Shanghai and Shenzhen stock exchanges from 2012 to 2020 constructed a regulated mediation effect model, empirically tests the impact of equity checks and balances on CSR and the mediation and mediator roles of green innovation performance and environmental uncertainty.

(1) Equity checks and balances among shareholders have a significant positive impact on CSR. (2) Equity checks and balances have a positive impact on green innovation performance, green innovation performance has a positive impact on CSR and green innovation performance plays a partial mediation effect between equity checks and balances and CSR. (3) Additionally, environmental uncertainty not only moderates the relationship between Green Innovation Performance and CSR but also moderates the direct effect between equity balance and CSR, which verifies the existence of a moderated mediation effect.

The study only considers listed companies on the Shanghai and Shenzhen stock markets as the research sample and does not include unlisted and gem enterprises.

The present research can offer some managerial implications about implementing equity checks and balances among shareholders, actively fulfilling CSR and developing new products.

This study complements previous studies on the role of green innovation in corporate governance by exploring the impact of green innovation on equity checks and balances and CSR. And this study explores the dynamic moderating of environmental uncertainty within enterprises and provides another explanation for the mixed results of equity checks and balances, green innovation performance and CSR.

By demonstrating the influence of the ownership structure of A-shares listed companies on CSR, this paper provides a new and comprehensive theoretical framework to examine the interaction between equity checks and balances, green innovation performance, environmental uncertainty and CSR. The results can be used as a reference for corporate governance, improving innovation performance and fulfilling CSR.

The advancement of digital maturity at a business level has proven to be challenging, with limited time, resources and skills in extracting and mapping business processes. In order to advance digitalization, the mapping of all business activities is essential. To close this gap, this research is aimed at enabling the operational level extraction and classification of business activities using a graphical methodology. This objective is accomplished through the development of a digital tool that leverages Software Development Life Cycle (SDLC) principles.

This research is focused on facilitating rapid extraction of business activities with the adoption of a graphical methodology. Business activities are captured through a digital tool in a structured, interlinked and hierarchical manner.

Notably, this work is novel as it introduces a new graphical tool to replace traditional tools in the domain of Business Process Mapping (BPM). This graphical tool is distinguished by a unique feature; that is a self-configuring database with the flexibility to capture all process options, providing innovative solutions to the challenges faced in digitalizing business processes.

This work is original in that a new graphical interface is developed to replace traditional tools in the space of BP data gathering. The unique challenge of an auto configuring database with flexibility to capture all process options is presented.

The economic and administrative conditions of countries normatively have an effect on the economy and level of market development. Moreover, it is of great importance for a healthy economy whether the public institutions and organizations are transparent and functioning in accordance with their purpose. The aim of this study is to show whether there is a relationship between transparency and market efficiency.

Correlation analysis has been conducted between prediction accuracy rates, which are obtained by seven different machine learning algorithms and Corruption Perception Index (CPI) levels.

It has been statistically shown that the indices of countries with low corruption levels are harder to predict, which, in turn, can be interpreted as having higher weak-form market efficiency. According to that, an intermediate negative correlation has been found between CPI scores and predictability levels of stock indices. Considering the findings, it can be interpreted that the markets of countries with relatively more transparent and well-functioning public sector have more weak-form market efficiency.

The study can be extended with cutting-edge machine learning and deep learning techniques in future studies. There are very few studies which try to explain factors related to market efficiency. Thus, the authors claim that there is still room for further research in order to determine the factors related to market efficiency, implying that current literature is still far from explaining the causation behind the inefficiencies.

According to findings, the markets of countries with relatively more transparent and well-functioning public sector have more weak-form market efficiency. Based on these findings, in practice, it can be said that more successful predictions can be made using machine learning algorithms in countries with relatively lower CPI scores.

In literature, the factors related to market efficiency are still far from explaining the causation behind the inefficiencies. Thus, it has been investigated whether transparent and well-functioning public institutions and organizations have any relation with market efficiency.

This paper aims to study using a mobile manipulator with a collaborative robotic arm component to manipulate objects beyond the robot’s maximum payload.

This paper proposes a single-short probabilistic roadmap-based method to plan and optimize manipulation motion with environment support. The method uses an expanded object mesh model to examine contact and randomly explores object motion while keeping contact and securing affordable grasping force. It generates robotic motion trajectories after obtaining object motion using an optimization-based algorithm. With the proposed method’s help, the authors plan contact-rich manipulation without particularly analyzing an object’s contact modes and their transitions. The planner and optimizer determine them automatically.

The authors conducted experiments and analyses using simulations and real-world executions to examine the method’s performance. The method successfully found manipulation motion that met contact, force and kinematic constraints. It allowed a mobile manipulator to move heavy objects while leveraging supporting forces from environmental obstacles.

This paper presents an automatic approach for solving contact-rich heavy object manipulation problems. Unlike previous methods, the new approach does not need to explicitly analyze contact states and build contact transition graphs, thus providing a new view for robotic grasp-less manipulation, nonprehensile manipulation, manipulation with contact, etc.

This examine the impact of environmental, social and governance (ESG) performance on financial reporting quality (FRQ) before and during COVID-19 in the Egyptian market.

This study uses quarterly data from 2017 to 2021 to draw conclusions, with a sample consisting of 486 firm-year observations for 27 Egyptian companies listed on the Standard and Poor’s/Egyptian Stock Exchange ESG index. This study uses both firms’ ESG scores and the Beneish Model, an earnings detection model, as proxies for FRQ. COVID-19 effects on ESG performance and FRQ were examined by using Pearson’s correlation coefficient and two-stage least squares.

COVID-19 has a significant impact on the link between ESG and FRQ. This implies that corporations with high ESG performance are less likely to manipulate earnings (having a low M-score) and thus provide high FRQ during the COVID-19 pandemic. Moreover, there is a significant positive relationship between firm size, leverage and M-Score, indicating that large firms typically present a high FRQ.

The sample size and data availability are the main research limitations. Additionally, this study only considers the effects of firms’ ESG performance on FRQ during the COVID-19 pandemic. Thus, future research should consider other factors associated with investors’ corporate social responsibility (CSR).

This research has practical implications for market regulators seeking to establish a legislative framework and enhance guidance to mandate managers to provide ESG data and CSR reports appropriate for Egypt and other developing economies in times of crisis.

Promoting the adoption of ESG practices in business, particularly during crises, has the potential to effectively provide high-quality and reliable financial reporting required for investment.

This study aspires to address notable deficiencies in the pertinent literature concerning the relationship between ESG performance and FRQ during COVID-19. To the best of the authors’ knowledge, little is known about how ESG performance changes in response to pandemics in emerging markets. To address this gap, this study examines the effects of COVID-19 on the relationship between ESG performance and FRQ in Egyptian-listed firms from 2017 to 2021.

This paper investigates whether China's R&D tax deduction policy triggers firms to manipulate their R&D expenditures upward.

This paper employs the ratio of actual tax savings as a proxy for the benefits of the R&D tax deduction policy based on manually collected and systematically cross-checked data. The relationship between tax benefits and abnormal R&D spending is estimated in a sample of Chinese A-share listed companies for the period 2007–2018.

The findings suggest that tax deductions lead to positive abnormal R&D spending and that this deviation in R&D spending may be attributed to firms' upward R&D manipulation for tax avoidance. The results also indicate that this behavior is more significant for the period after the policy revision, in non-HNTEs (high and new technology enterprises), and in firms with a high ratio of R&D expenses.

It is difficult to establish a sophisticated and unified model to identify the specific strategy of upward R&D manipulation that firms use to obtain tax benefits.

Managers should take into account upward R&D manipulation when designing governance mechanisms. Policymakers in developing countries may further pursue preferential tax policies that cover every stage of innovation activities gradually; the local provincial governments need to leverage their proximity and flexibility advantages to develop a tax collection and administration system.

This study contributes to the understanding of the complex effect of R&D tax incentives and helps more fully illuminate firms' upward R&D manipulation behavior from the perspective of tax planning strategies, which are underexplored in previous research.

This paper attempts to investigate the effect of corruption on the real and accrual earnings management of target firms in the process of mergers and acquisitions.

The sample includes target firms from the European area that participate in mergers or acquisitions announced during 2010–2020. The preliminary empirical part estimates the level of earnings management during the period two years before the deal's announcement to identify whether the sample follows the manipulation behavior that the literature suggests for target firms. The primary empirical analysis focuses on the impact of corruption on real and accrual-based earnings management proxies, employing regression models and two alternative proxies for corruption. The existing literature points out that the combination of low levels of corruption and an integrated legal system reduces earnings manipulation.

The findings provide strong evidence for systematic downwards accounting manipulation practices, whereas the findings for real earnings management are not significant. The findings of the main empirical part show that corruption is positively associated with accrual-based manipulation and negatively related to real earnings management. In essence, in economies with a high level of transparency, managers adopt the manipulation of operating activities as a less detectable practice of earnings management instead of engaging in accounting procedures.

This study contributes to the literature highlighting the diversification of these firms' manipulation strategies according to the national level's corruption status.

Artificial intelligence (AI) offers many benefits to improve predictive marketing practice. It raises ethical concerns regarding customer prioritization, market share concentration and consumer manipulation. This paper explores these ethical concerns from a contemporary perspective, drawing on the experiences and perspectives of AI and predictive marketing professionals. This study aims to contribute to the field by providing a modern perspective on the ethical concerns of AI usage in predictive marketing, drawing on the experiences and perspectives of professionals in the area.

The study conducted semistructured interviews for 6 weeks with 14 participants experienced in AI-enabled systems for marketing, using purposive and snowball sampling techniques. Thematic analysis was used to explore themes emerging from the data.

Results reveal that using AI in marketing could lead to unintended consequences, such as perpetuating existing biases, violating customer privacy, limiting competition and manipulating consumer behavior.

The authors identify seven unique themes and benchmark them with Ashok’s model to provide a structured lens for interpreting the results. The framework presented by this research is unique and can be used to support ethical research spanning social, technological and economic aspects within the predictive marketing domain.

La Inteligencia Artificial (IA) ofrece muchos beneficios para mejorar la práctica del marketing predictivo. Sin embargo, plantea preocupaciones éticas relacionadas con la priorización de clientes, la concentración de cuota de mercado y la manipulación del consumidor. Este artículo explora estas preocupaciones éticas desde una perspectiva contemporánea, basándose en las experiencias y perspectivas de profesionales en IA y marketing predictivo. El estudio tiene como objetivo contribuir a la literatura de este ámbito al proporcionar una perspectiva moderna sobre las preocupaciones éticas del uso de la IA en el marketing predictivo, basándose en las experiencias y perspectivas de profesionales en el área.

Para realizar el estudio se realizaron entrevistas semiestructuradas durante seis semanas con 14 participantes con experiencia en sistemas habilitados para IA en marketing, utilizando técnicas de muestreo intencional y de bola de nieve. Se utilizó un análisis temático para explorar los temas que surgieron de los datos.

Los resultados revelan que el uso de la IA en marketing podría tener consecuencias no deseadas, como perpetuar sesgos existentes, violar la privacidad del cliente, limitar la competencia y manipular el comportamiento del consumidor.

El estudio identifica siete temas y los comparan con el modelo de Ashok para proporcionar una perspectiva estructurada para interpretar los resultados. El marco presentado por esta investigación es único y puede utilizarse para respaldar investigaciones éticas que abarquen aspectos sociales, tecnológicos y económicos dentro del ámbito del marketing predictivo.

人工智能（AI）为改进预测营销实践带来了诸多益处。然而, 这也引发了与客户优先级、市场份额集中和消费者操纵等伦理问题相关的观点。本文从当代角度深入探讨了这些伦理观点, 充分借鉴了人工智能和预测营销领域专业人士的经验和观点。旨在通过现代视角提供关于在预测营销中应用人工智能时所涉及的伦理观点, 为该领域做出有益贡献。

本研究采用了目的性和雪球抽样技术, 与14位在人工智能营销系统领域具有丰富经验的参与者进行为期六周的半结构化访谈。研究采用主题分析方法, 旨在深入挖掘数据中显现的主要主题。

研究结果表明, 在营销领域使用人工智能可能引发一系列意外后果, 包括但不限于加强现有偏见、侵犯客户隐私、限制竞争以及操纵消费者行为。

本研究通过明确定义七个独特的主题, 并采用阿肖克模型进行基准比较, 为读者提供了一个结构化的视角, 以解释研究结果。所提出的框架具有独特之处, 可有效支持在跨足社会、技术和经济领域的预测营销中展开的伦理研究。