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According to the management obfuscation hypothesis, managers have incentives to influence the audit reports’ communicative value. This study aims to examine the relationship between corporate earnings management and the readability of Chinese-text audit reports and the impact of key audit matter (KAM) disclosure requirements on this relationship.

This research adopts Taiwanese firms from 2010 to 2019 to investigate the association between earnings management and readability of Chinese-text audit reports within the framework of the KAM disclosure requirements implemented in 2016.

The findings show that auditors tend to issue less readable audit reports to firms undertaking earnings management, particularly after introducing KAM disclosures. Additional analyses indicate that such adverse impacts of client earnings management on audit report readability have become more pronounced for firms audited by a newly pointed or long-tenure lead audit partner, with high business risk, poor monitoring of governance mechanisms or a large amount of nonaudit services. These results suggest that auditor partners may compromise auditor independence and use flexible narratives in audit reports as a form of moral insurance.

As auditors may manage audit report readability to reduce audit liability, authorities must formulate policies concerning audit report disclosure to strengthen its communicative value and simplify language usage. Additionally, authorities should strengthen quality control standards concerning auditor independence to reduce auditor pressure from clients’ economic importance.

This study provides valuable insights into auditors' responses to corporate earnings management behavior, particularly regarding the interplay between earnings management, audit report quality and regulatory changes, thus expanding our understanding of the dynamics within the auditing profession.

The manoeuvring of everyday spaces to nudge the population towards a physically active lifestyle or active living has been the hallmark of the policy modes of instrumental thinking for combating physical inactivity, particularly in urban spaces across the world. Thus, the active promotion of fitness activities by the postcolonial state signifies the centrality of the body in disciplining docile and inactive individuals to produce fit and active citizens. Such a population-based approach has often raised concerns about social and spatial justice and expressions of identity, liberty, and surveillance, even as everyday spaces in cities continue to exhibit elements of colonial governmentality. In the midst of this, the body continues to be central to the ways in which such a population makes sense of being physically active and ‘being healthy’ in their everyday lives. By employing a multi-sited ethnography conducted over a period of 10 months in different public parks in Delhi, the present chapter aims to understand the ways in which fitness activities are performed, produced, and practised in the city. While public parks themselves are a product of colonial urban governmentalities in Delhi, this chapter argues that active bodies engaged in everyday sports in the parks also emerge as the critical site for the bodily inscription of global standards of physical activity. Driven by Western fitness regimes, individuals tend to understand themselves as entrepreneurial selves that can bring to life this imagination of the body ideal even while being engaged in various fitness and leisure activities aimed at being ‘healthy’.

This study aims to better understand the influence of various post-treatments on the microstructure and mechanical properties of additively manufactured parts for critical applications.

In this study, Laser Powder Bed Fusion (LPBF) fabricated Inconel 718 (IN718) samples were subjected to various heat treatments, namely homogenization, solution heat treatment and double aging, to investigate their influence on the microstructure, mechanical properties and fracture mechanism at an elevated temperature of 650 °C. Homogenization treatment was performed at 1080 °C for durations ranging from 1–8 h. The solution treatment temperature varied from 980 °C to 1140 °C for 1 h, followed by double aging treatment.

At 650 °C, the as-built sample showed the minimum strength but demonstrated the maximum elongation to failure compared to the heat-treated samples. The strength of the IN718 superalloy increased by 20.26% to 34.81%, while ductility significantly reduced by 65.26% to 72.89% after various heat treatments compared to the as-built state. This change is attributed to the enhancement in grain boundary strength resulting from the pinning effect of the intergranular δ-phase.

The study observed that the variations in the fracture mechanism of LPBF fabricated IN718 depend on the duration and temperature of heat treatment. This research provides a thorough overview of the high-temperature mechanical properties of LPBF fabricated IN718 subjected to different homogenization times and solution treatment temperatures, correlating these effects to the corresponding changes in microstructure.

Damage to reinforced concrete (RC) structural elements is inevitable. Such damage can be the result of several factors, including aggressive environmental conditions, overloading, inadequate design, poor work execution, fire, storm, earthquakes etc. Therefore, repairing and strengthening is one way to improve damaged structures, so that they can be reutilized. In this research, the use of an ultra high-performance fibre-reinforced concrete (UHPFRC) layer is proposed as a strengthening material to rehabilitate damaged-RC beams. Different strengthening schemes pertaining to the structural performance of the retrofitted RC beams due to the flexural load were investigated.

A total of 13 normal RC beams were prepared. All the beams were subjected to a four-point flexural test. One beam was selected as the control beam and tested to failure, whereas the remaining beams were tested under a load of up to 50% of the ultimate load capacity of the control beam. The damaged beams were then strengthened using a UHPFRC layer with two different schemes; strip-shape and U-shape schemes, before all the beams were tested to failure.

Based on the test results, the control beam and all strengthened beams failed in the flexural mode. Compared to the control beam, the damaged-RC beams strengthened using the strip-shape scheme provided an increase in the ultimate load capacity ranging from 14.50% to 43.48% (or an increase of 1.1450 to 1.4348 times), whereas for the U-shape scheme beams ranged from 48.70% to 149.37% (or an increase of 1.4870–2.4937 times). The U-shape scheme was more effective in rehabilitating the damaged-RC beams. The UHPFRC mixtures are workable, as well easy to place and cast into the formworks. Furthermore, the damaged-RC beams strengthened using strip-shape scheme and U-shape scheme generated ductility factors of greater than 4 and 3, respectively. According to Eurocode8, these values are suitable for seismically active regions. Therefore, the strengthened damaged-RC beams under this study can quite feasibly be used in such regions.

Observations of crack patterns were not accompanied by measurements of crack widths due to the unavailability of a microcrack meter in the laboratory. The cost of the strengthening system application were not evaluated in this study, so the users should consider wisely related to the application of this method on the constructions.

Rehabilitation of the damaged-RC beams exhibited an adequate structural performance, where all strengthened RC beams fail in the flexural mode, as well as having increment in the failure load capacity and ductility. So, the used strengthening system in this study can be applied for the building construction in the seismic regions.

Aside from equipment, application of this strengthening system need also the labours.

The use of sand blasting on the surfaces of the damaged-RC beams, as well as the application of UHPFRC layers of different thicknesses and shapes to strengthen the damaged-RC beams, provides a novel innovation in the strengthening of damaged-RC beams, which can be applicable to either bridge or building constructions.

This study aims to enhance the effectiveness of knowledge markets and overall knowledge management (KM) practices within organisations. By addressing the challenge of internal knowledge stickiness, it seeks to demonstrate how machine learning and AI approaches, specifically a text-based AI method for personality assessment and regression trees for behavioural analysis, can automate and personalise knowledge market incentivisation mechanisms.

The research employs a novel approach by integrating machine learning methodologies to overcome the limitations of traditional statistical methods. A natural language processing (NLP)-based AI tool is used to assess employees’ personalities, and regression tree analysis is applied to predict and categorise behavioural patterns in knowledge-sharing contexts. This approach is designed to capture the complex interplay between individual personality traits and environmental factors, which traditional methods often fail to adequately address.

Cognitive style was confirmed as a key predictor of knowledge-sharing, with extrinsic motivators outweighing intrinsic ones in market-based platforms. These findings underscore the significance of diverse combinations of environmental and individual factors in promoting knowledge sharing, offering key insights that can inform the automatic design of personalised interventions for community managers of such platforms.

This research stands out as it is the first to empirically explore the interaction between the individual and the environment in shaping actual knowledge-sharing behaviours, using advanced methodologies. The increased automation in the process extends the practical contribution of this study, enabling a more efficient, automated assessment process, and thus making critical theoretical and practical advancements in understanding and enhancing knowledge-sharing behaviours.

This study aims to investigate the moderating role of natural language processing natural language processing (NLP) on the relationship between AI-empowered AIS (data gathering, data analysis, risk assessment, detection, prevention and Investigation) and auditing and fraud detection.

Quantitative methodology was adapted through a questionnaire. In total, 221 individuals represented the population of the study, and SPSS was used to screen primary data. The study indicated the acceptance of the hypothesis that “Artificial Intelligence in AIS has a statistically significant influence on auditing and fraud detection,” showing a strong correlation between auditing and fraud detection. The study concluded that NLP moderates the relationship between AI in AIS and auditing and fraud detection.

The study’s implications lie in its contribution to the development of theoretical models that explore the complementary attributes of AI and NLP in detecting financial fraud.

A cross-sectional design is a limitation.

NLP is a useful tool for developing more efficient methods for detecting fraudulent activities and audit risks.

The study’s originality stems from its focus on the use of AI-empowered AIS, a relatively new technology that has the potential to significantly impact auditing and fraud detection processes within the accounting field.

The e-services market is expected to reach nearly $500bn globally by 2028. As this marketplace grows, customer-to-customer interactions (CCIs) occurring through virtual channels will likely increase. Consequently, the purpose of this research is to examine how the context in which CCI’s occur (i.e. virtual vs in-person) and the frequency of their occurrence affects customer identification, leading to increased customer engagement and more favorable purchase behaviors.

Two studies were conducted to test the proposed models and hypotheses. The sample for Study 1 is comprised of college students taking in-person or online classes (n = 290). In Study 2, members of an online brand community (n = 125) were surveyed. Hypotheses were tested using structural equation modeling (SEM).

Overall, results support a mediation effect such that CCI context (virtual vs in-person) affects customer engagement and purchase behaviors via customer identification. Specifically, Study 1 finds that customer engagement behaviors (CEBs) are greater for in-person CCIs due to the frequency of interactions and heightened identification between customers. Study 2 further examines the CCI frequency-identification link and finds that customer-firm identification is the only form of identification that affects CEBs and purchase behaviors.

Limited customer engagement research has examined the effects of CCIs on CEBs, and research has rarely compared in-person to virtual CCI contexts. This paper addresses these shortcomings by testing the effects of in-person and virtual CCIs on CCI frequency, identification and CEBs. This research fills another important gap in the literature by considering the unique effects of specific dimensions of customer identification on CEBs and purchase behaviors.

This paper aims to investigate the impact of the revised Code of Corporate Governance 2017 (CCG-2017) clauses pertaining to board independence, mandatory inclusion of female directors, audit committee (AC) chair independence and directors’ expertise on earnings manipulation.

Using an unbalanced panel of 323 listed companies from 2015 to 2019, this study uses panel data regression models with a robust methodology called difference-in-differences to tackle the potential endogeneity.

This study’s findings show that, as compared to the pre-CCG-2017 period, board- and AC-related variables increased significantly in the post-CCG-2017 period. Furthermore, financial experts on the board and board independence have a negative effect on discretionary accruals (DAs), whereas female directors and DAs are positively related, as is real activity manipulation. The AC-related variables, such as AC independence, expertise in AC, and AC chair independence, are significantly different from the preperiod to the postperiod, whereas their relationship is not according to the hypotheses of the study. Moreover, these results are robust to additional analysis of the alternative proxies for female directorship and the endogeneity problem.

The findings of this study have implications for regulators and practitioners who are concerned with the functions of the board of directors (BOD). The findings of this research study show that earnings management (EM) may be reduced by independent and expert directors. However, board gender diversity is not reducing the EM. Therefore, the decision to appoint female directors to the board should be based on their business and professional attributes rather than simply filling quotas or blindly adhering to regulations. Moreover, the findings of this research may assist the regulator in encouraging listed firms to enhance board governance via independence, diversity and competency, which are useful for effective monitoring.

This study fills a gap in the literature by providing the first evidence of country-specific regulation (CCG-2017), concerning the BOD and AC-related clauses on EM in Pakistan, which is missing in the relevant literature general and in Pakistan in particular.