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The purpose of this study is to investigate the association between nonaudit services (NAS) and out-of-period adjustments (OOPAs). Over the years, the number of OOPAs has risen while the number of restatements has decreased. This could indicate an improvement in financial reporting quality. It could also indicate the use of a type of stealth restatement for opportunistic purposes. These less prominent restatements are more likely to go undetected and could perpetuate opportunistic disclosure and mitigate the likelihood of unfavorable market reactions.

The authors use a two-stage multivariate regression analysis to examine the relationship between NAS and the reporting of an OOPA. The authors use prior research on NAS to guide the model development. The authors perform several robustness checks including different types of NAS and different characteristics of OOPAs.

The results indicate that NAS has a significantly negative association with the existence of OOPAs. The core findings suggest that NAS does not impair auditor independence. Rather, greater amounts of NAS may contribute to knowledge spillover, which leads to higher financial reporting and audit quality. The results are robust to several additional tests.

The results raise interesting implications for regulators, executives, auditors, investors and future research. The authors provide insight into the relationship between NAS and auditor independence.

To the best of the authors’ knowledge, prior research has not considered the effect of NAS on OOPAs. The authors contribute to the literature by providing evidence that OOPAs, a form of stealth restatements, is an important consideration in audit quality research.

While a substantial amount of research has been conducted in western societies exploring public attitudes toward police (ATP) among immigrants in recent decades, the question of how recently arrived immigrants view the police in Asian societies has been largely overlooked. This study aims to explore Southeast Asian immigrants' ATP in Taiwan and how assimilation, discrimination, affirmation, procedural justice, bifocal lenses and contact experiences – viewed simultaneously – impact their perceptions.

Using a combination of convenience and snowball sampling methods, a total of 579 completed survey responses were collected in Taiwan with a response rate of 89%. Structural Equation Modeling (SEM) was used to examine key factors that impact immigrants' attitudes toward the Taiwanese police.

The findings suggest that procedural justice and assimilation are two robust and direct predictors of immigrants' attitudes toward Taiwanese police. Immigrants from Southeast Asian countries who perceive that they have been treated fairly by Taiwan police tended to report more positive ATP. Likewise, higher levels of assimilation boosted confidence in the police. In addition, both nationality and marital status had a significant impact on perceptions of the police.

This pioneering study examines immigrants' ATP among four groups of Southeast Asians in Taiwan —namely, immigrants from Indonesia, Vietnam, Thailand and the Philippines. The use of SEM strengthens the robustness of the findings derived from this study.

This article seeks to offer an answer. It explores the criteria on which commercial property market participants can develop strategies in hugely challenging circumstances. For this purpose, a survey-based approach was developed with work conducted with property-market professional in the United Kingdom (UK), France, Germany and Sweden to produce a criteria-based tool supporting adaption to changing market circumstances.

The data have been analyzed using statistical analysis. The data's statistical analysis included Cronbach's alpha's application to evaluate the respondents' replies' reliability. A entral tendency test was used to identify the means of relevance of the criteria. The Mann–Whitney U test was used to determine potential material differences between the UK and other countries with Bonferroni corrections applied to minimize type-I errors.

Thirty characteristics have been identified that impact the dynamics of the commercial property market. Their relevance to the commercial property market was determined using a survey. The literature analysis showed that the researchers paid more attention to quantitative criteria and their comparison. The survey showed that the relevance of criteria to the commercial property market dynamics is unequal. However, the survey results showed that it is most important to pay attention to emotional criteria to adapt to uncertainty changing conditions. The problem of the environment has been on the agenda for the last four decades. Therefore, the fact that the results of the study showed that the environmental criteria are the least significant is unexpected.

The study involved economically developed countries of Europe. Extending the study's geographical scope would be valuable in revealing whether the same differences exist in other geographical areas (such as Australia or the USA).

The practical implication of the analysis may be to facilitate the decision-making process of either selecting a country for commercial property investment or selecting the most sensitive and relevant criteria for the decision-making.

Criteria for commercial property market performance which promote successful property investment have been developed. Moreover, the criteria affecting the commercial property market have been weighted by their relevance to the market and their sequence of relevance has been established. And finally, the developed criteria have been placed into five groups that could serve as a foundation for a macro-level assessment of commercial property market dynamics.

Corporate social responsibility (CSR) was mandated and institutionalised in India through the Companies Act (2013), a decade ago. It is critical to understand the priorities of the models used by the companies to effectuate their CSR policy. This paper aims to understand the skewing of interest towards Education and Health interventions. The paper then proposes a framework to cross-level and effectuate CSR programme implementation.

The qualitative study conducted in-depth interviews of the stakeholders from the CSR environment. The findings are used to derive a model to effectuate CSR in India.

The findings may be divided into two sub-themes – (a) observations from the field study and (b) integrated solution ecosystem (ISE) framework. The qualitative study and the insights form the first component. The proposed framework which can enhance the efficiency of CSR practices may be found in the second sub-theme.

Operationalisation of the proposed model, if adopted would require integrated efforts from multiple functional departments which could lead to an extended timeframe for implementation. This may eventually lead to a need to revise the model in the making. The research could also include perspectives from governmental stakeholders which is missing here.

The emerging model can present an opportunity for corporates and policymakers to revisit the CSR structure and frameworks. It can also be used to evaluate and audit the CSR practices of companies.

The ISE posits a bunch of actionable themes which can deliver an impactful transition from the existing approach to CSR to a more far reaching one. While the ground rules are revisited, the approach also allows a critical departure from a corporate-driven model of engagement with the community. The modifications or corrections in this model would also mean a more inclusive layering of developmental interventions. The diversity which could potentially be brought in to designing interventions can be another key impact.

This paper presents insights for some of the pivotal stakeholders of CSR in countries like India. It presents a possible model of effective and optimal utilisation of CSR spending.

This study is the first to investigate the causal relationship between Bitcoin and equity price returns by sectors. Previous studies have focused on aggregated indices such as S&P500, Nasdaq and Dow Jones, but this study uses mixed frequency and disaggregated data at the sectoral level. This allows the authors to examine the nature, direction and strength of causality between Bitcoin and equity prices in different sectors in more detail.

This paper utilizes an Unrestricted Asymmetric Mixed Data Sampling (U-AMIDAS) model to investigate the effect of high-frequency Bitcoin returns on a low-frequency series equity returns. This study also examines causality running from equity to Bitcoin returns by sector. The sample period covers United States (US) data from 3 Jan 2011 to 14 April 2023 across nine sectors: materials, energy, financial, industrial, technology, consumer staples, utilities, health and consumer discretionary.

The study found that there is no causality running from Bitcoin to equity returns in any sector except for the technology sector. In the tech sector, lagged Bitcoin returns Granger cause changes in future equity prices asymmetrically. This means that falling Bitcoin prices significantly influence the tech sector during market pullbacks, but the opposite cannot be said during market rallies. The findings are consistent with those of other studies that have established that during market pullbacks, individual asset prices have a tendency to decline together, whereas during market rallies, they have a tendency to rise independently. In contrast, this study finds evidence of causality running from all sectors of the equity market to Bitcoin.

The findings have significant implications for investors and fund managers, emphasizing the need to consider the asymmetric causality between Bitcoin and the tech sector. Investors should avoid excessive exposure to both Bitcoin and tech stocks in their portfolio, as this may lead to significant drawdowns during market corrections. Diversification across different asset classes and sectors may be a more prudent strategy to mitigate such risks.

The study's findings underscore the need for investors to pay close attention to the frequency and disaggregation of data by sector in order to fully understand the true extent of the relationship between Bitcoin and the equity market.

Replication is a primary self-correction device in science. In this paper, we have two aims: to examine how and when the results of replications are used in management and organization research and to use the results of this examination to offer guidelines for improving the self-correction process.

Study 1 analyzes co-citation patterns for 135 original-replication pairs to assess the direct impact of replications, specifically examining how often and when a replication study is co-cited with its original. In Study 2, a similar design is employed to measure the indirect impact of replications by assessing how often and when a meta-analysis that includes a replication of the original study is co-cited with the original study.

Study 1 reveals, among other things, that a huge majority (92%) of sources that cite the original study fail to co-cite a replication study, thus calling into question the impact of replications in our field. Study 2 shows that the indirect impact of replications through meta-analyses is likewise minimal. However, our analyses also show that replications published in the same journal that carried the original study and authored by teams including the authors of the original study are more likely to be co-cited, and that articles in higher-ranking journals are more likely to co-cite replications.

We use our results to formulate recommendations that would streamline the self-correction process in management research at the author-, reviewer- and journal-level. Our recommendations would create incentives to make replication attempts more common, while also increasing the likelihood that these attempts are targeted at the most relevant original studies.

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 investigates the fitting techniques for notch fatigue curves, seeking a more reliable method to predict the lifespan of welded structures.

Building on the fatigue test results of butt and cruciform joints, this research delves into the selection of fitting methods for the notch fatigue curve of welded joints. Both empirical formula and finite element methods (FEMs) were employed to assess the notch stress concentration factor at the toe and root of the two types of welded joints. Considering the mean stress correction and weld misalignment coefficients, the notch fatigue life curves were established using both direct and indirect methods.

An engineering example was employed to discern the differences between the direct and indirect approaches. The findings highlight the enhanced reliability of the indirect method for fitting the fatigue life curve.

While the notch stress approach is extensively adopted due to its accurate prediction of component fatigue life, most scholars have overlooked the importance of its curve fitting methods. Existing literature scantily addresses the establishment of these curves. This paper offers a focused examination of fatigue curve fitting techniques, delivering valuable perspectives on method selection.

The purpose of the study is to compare methodologies for mapping a historic building, with image capture by smartphones and drones, using photogrammetric techniques for three-dimensional (3D) modeling of the structure. Processes and products are also analyzed, as well as possibilities for storing and visualizing data for structuring a cadastre of historical and artistic heritage are studied.

For mapping with smartphones, the overlapping of photographs was guaranteed, with data acquisition using three different cameras, on the same date as the aerial survey. The models were made from different combinations of camera use. For storage, a conceptual model based on ISO 19.152:2012 is proposed, which was implemented in the MongoDB, resulting in a database for storage. The visualization was carried out on the Cesium ion platform.

The results indicate that the terrestrial 3D reconstruction using smartphones is an efficient alternative to the historical and artistic cadastre, presenting texture quality superior to the aerial survey in a shorter production time. When dealing with the conceptual model, the LADM (Land Administration Domain Model) standardization guarantees interoperability and facilitates data exchange. In addition, it proved to be flexible for the creation of thematic profiles, supporting their effective storage. The insertion of data in the visualization platform was simple and effective, and it even generated sharing links for visualization of the models.

The study analyses a low-cost method with the use of easily accessible devices, with a combination of methodologies and applied techniques. The data storage and visualization method is also simple and flexible, suitable for application in the cadastre of historical heritage.