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This paper aims to investigate the impact of the implementation of the critical audit matters (CAMs) disclosure requirement and the subsequent relationship between CAM disclosures and audit report lag, as well as audit fees in the USA.

This study used difference-in-differences analyses to investigate the impact that the implementation of the requirement for auditors to report CAMs on their audit report has on the audit process. It also used levels regression models to examine the relationship that CAM disclosures have with audit report lag and audit fees.

This study found that the implementation of the CAM disclosure requirement in the USA reduced audit report lag while not significantly affecting audit fees. This suggests that the CAM disclosure requirement may increase the cooperation between auditors and managers and improve the efficiency of the audit process.

This study’s results are informative for assessing the economic impact of requiring CAM disclosures, which should be of importance to regulators, auditors and accounting researchers.

This study used different approaches to investigate two aspects of the CAM disclosure requirement – the effect of the implementation of the disclosure requirement and the subsequent effects related to CAM reporting outcomes. Unlike many previous studies investigating CAM disclosures, which relied on experiments and questionnaires, this study used actual CAM disclosure data in the USA to investigate the impact on audit report lag and audit fees.

This study aims to differentiate crime-related characteristics (such as the number of cases filed against current convictions and criminal history) based on the criminal thinking prevailing among convicts. However, because of the low reliability of subscales and poor structural validity of indigenous and translated versions of international instruments, a new instrument criminal attitude measure (CAM) was extracted to measure criminal thinking patterns among convicts incarcerated in central prisons of Punjab.

A cross-sectional research design was used. Data was collected from 1,949 male convicts (extracting mutually exclusive data from 649 respondents for EFA and 1,300 respondents for confirmatory factor analysis [CFA]). Both data samples were collected from convicts incarcerated in the nine (all) central jails of Punjab, Pakistan.

The results of this study showed poor model fit for both the indigenous criminal thinking scale and the translated version of criminogenic cognition scale. CAM was extracted through principal component analysis and proposed as a 15-item questionnaire with five factors extracted through varimax rotation. Those five factors are power orientation, mollification, entitlement, mistrust toward authorities and short-term orientation. The results of CFA for CAM confirmed the proposed five-factor structure for the construct. Findings based on MANOVA further found that CAM differentiates between the thinking patterns of recidivists, convicts with multiple charges filed against them in current convictions and convicts with a familial criminal record. The findings of this study showed that CAM is a practical, valid and reliable instrument for measuring criminal thinking among convicts.

In this study, using the survey method was inevitable because of the restrictions imposed by the granted permission. However, this time duration was extended because of the courtesy of the Superintendent and Deputy Superintendent of each jail. This study is focused on a male sample only, and the findings cannot be generalized to females. The phenomena proposed (based on large data sets) in this study can further be elaborated using qualitative research designs and methods (using a small sample with an in-depth study). So, it is also suggested to test this new instrument on a comparative study between prisoners and non-prisoners to explore whether scale can differentiate between these two groups.

A short-scale and easy-to-administer instrument was developed for assessing major criminogenic needs among convicts for prison management, i.e. assigning barracks, allocating treatment and also detecting changes in attitude after imprisonment.

To the best of the authors’ knowledge, this study is the first study to explore and validate the construct of criminal attitudes among convicts using both the EFA and CFA. A small and valid instrument facilitates the measurement of criminogenic needs among prisoners. Data was collected from all central jails in Punjab. This study explored comparatively less researched crime characteristics in a relatively large sample.

This paper aims to evaluate the effect of consumption of a high-fat diet (HFD) rich with total saturated fats on adiposity and serum levels of vascular cell adhesion molecule (sVCAM-1), a biomarker of endothelial inflammation/dysfunction. Another aim is to evaluate whether supplementation of a phytosomal formulation of curcumin would reduce adiposity measures and sVCAM-1 levels in HFD rats.

The study was conducted on 17 male rats which were allocated to one of three feeding regimen groups: normal diet (ND); HFD, or HFD with dietary phytosomal curcumin (HFD-C). Anthropometric measures were recorded weekly up to 20 weeks of feeding intervention, at the end of which, sVCAM-1 levels were also compared with one-way ANOVA and Tukey post-hoc analysis.

The HFD group had the greatest values for raw anthropometric data, and there was a group difference in anthropometric measures, however there was no significant difference between HFD and HFD-C for any measure. The gain at 20 weeks from initial values did reveal significant differences in weight and abdominal circumference between HFD and HFD-C groups. There were significant group differences in sVCAM-1 levels, with only HFD-C displaying significant lower levels than HFD group.

This is the first study that shows the capacity of a phytosomal formulation of curcumin in reducing adiposity and sVCAM-1 levels during daily intake of saturated fats above the recommended level. The results are promising in that this formulation can protect against endothelial inflammation/dysfunction, and can be used as complimentary therapy to suppress dyslipidemia/obesity-related cardiovascular complications.

Customer lifetime value (CLV) is one of the key indicators to measure the success or health of an organization. How can an organization assess the organization's customers' lifetime value (LTV) and offer relevant strategies to retain prospective and profitable customers? This study offers an integrated view of different methods for calculating CLVs for both loyalty members and non-membership customers.

This study outlines eleven methods for calculating CLV considering (1) the deterministic aspect of NPV (Net present value) models in both finite and infinite timespans, (2) the geometric pattern and (3) the probabilistic aspect of parameter estimates through simulation modeling along with (4) the migration models for including “the probability that customers will return in the future” as a key input for CLV calculation.

The CLV models are validated in the context of complementary and alternative medicine (CAM)in the healthcare industry. The results show that understanding CLV can help the organization develop strategies to retain valuable customers while maintaining profit margins.

The integrated CLV models provide an overview of the mathematical estimation of LTVs depending on the nature of the customers and the business circumstances and can be applied to other business settings.

Advancements in responsive manufacturing have been supporting companies over the last few decades. However, manufacturers now operate in a context of continuous uncertainty. This research paper explores a mechanism where companies can “elastically” provision and deprovision their production capacity, to enable them in coping with repeated disruptions. Such a mechanism is facilitated by the imitability and substitutability of production resources.

An inductive study was conducted using Gioia methodology for this theory generation research. Respondents from 20 UK manufacturing companies across multiple industrial sectors reflected on their experience during COVID-19. Resource-based view and resource dependence theory were employed to analyse the manufacturers' use of internal and external production resources.

The study identifies elastic responses at four operational levels: production-line, factory, company and supply chain. Elastic responses that imposed variable-costs were particularly well-suited for coping with unforeseen disruptions. Further, the imitability and substitutability of manufacturers helped others produce alternate goods during the crisis.

While uniqueness of production capability helps manufacturers sustain competitive advantage against competitors during stable operations, imitability and substitutability are beneficial during a crisis. Successful manufacturing companies need to combine these two approaches to respond effectively to repeated disruptions in a context of ongoing uncertainties. The theoretical contribution is in characterising responsive manufacturing in terms of resource heterogeneity and resource homogeneity, with elastic resourcing as the underlying mechanism.

The purpose of the research is to investigate whether corporate social responsibility awareness (pCSR), environmental concerns (EC) and consumer environmental knowledge (CK) will have an impact on sustainable purchase intention (SPI). Furthermore, this paper also contributes to surveying the mediating impact of consumer attitudes (CAs) between intention and the three factors mentioned above.

SmartPLS (version 4.0) structural equation modeling (SEM) and quantitative methods were used to analyze 457 responses from consumers. The survey sample consisted of individuals between the ages of 18 and 34, with a male-to-female ratio of 70 to 30. The study aims to examine and put into practice new directions for manufacturing firms in the fields of fashion, food and consumer products. At the same time, provide more convincing evidence about the use of these fields in the research.

The study showed a favorable link between pCSR, EC, CK and SPI through the proposed hypotheses. The research additionally showed that CAs mediate between the aforementioned variables.

The important and distinctive results of this study encourage both consumers and enterprises to make changes in their perceptions of society. Consumers should gradually change their daily lifestyle by consuming more sustainable products. As a result, this outcome will provide the impetus for manufacturing businesses to alter their operational procedures in order to support the shift from the production of products to more friendly processes, with the help of all levels of management within the business.

This study aims to examine how new regulation changes for the auditor’s report, so-called key audit matters (KAMs), influence tax avoidance.

This study uses data from firms listed on the Omani capital market over the period 2012–2019 and analyzes these data using pooled panel data regression with a robust standard error. It uses two common proxies for tax avoidance and two measures for the KAMs disclosure requirement.

This study finds a sharp decrease in the effective tax rate following the introduction of KAMs disclosure and the issuance of more KAMs in audit reports. This result is supported by several robustness checks. In an additional analysis, the authors observe interesting results, indicating that real earnings management mediates this association, while the audit committee plays a moderating role. The authors do not find a moderating effect of Big4 on this association, but find discrepancies within the Big4 firms in relation to this moderating effect.

The results of this study indicate that although the introduction of the KAMs disclosure requirement may have positive consequences, it may also lead to unintended negative consequences. This conclusion has not been comprehensively reported in literature.

This study aimed to use enrollment information including demographic, family background and financial status, which can be gathered before the first semester starts, to construct early prediction models (EPMs) and extract crucial factors associated with first-year student dropout probability.

The real-world samples comprised the enrolled records of 2,412 first-year students of a private university (UNI) in Taiwan. This work utilized decision trees (DT), multilayer perceptron (MLP) and logistic regression (LR) algorithms for constructing EPMs; under-sampling, random oversampling and synthetic minority over sampling technique (SMOTE) methods for solving data imbalance problems; accuracy, precision, recall, F1-score, receiver operator characteristic (ROC) curve and area under ROC curve (AUC) for evaluating constructed EPMs.

DT outperformed MLP and LR with accuracy (97.59%), precision (98%), recall (97%), F1_score (97%), and ROC-AUC (98%). The top-ranking factors comprised “student loan,” “dad occupations,” “mom educational level,” “department,” “mom occupations,” “admission type,” “school fee waiver” and “main sources of living.”

This work only used enrollment information to identify dropout students and crucial factors associated with dropout probability as soon as students enter universities. The extracted rules could be utilized to enhance student retention.

Although first-year student dropouts have gained non-stop attention from researchers in educational practices and theories worldwide, diverse previous studies utilized while-and/or post-semester factors, and/or questionnaires for predicting. These methods failed to offer universities early warning systems (EWS) and/or assist them in providing in-time assistance to dropouts, who face economic difficulties. This work provided universities with an EWS and extracted rules for early dropout prevention and intervention.

The study investigates the antecedents and consequences of digital ad avoidance in the e-commerce industry. This study aims to investigate how digital ad avoidance relates to internet usage over time, using a two-wave longitudinal research design. This study also explores how real-world advertising clutter (clutter and non-clutter) affects these relationships.

The data were collected from 192 online consumers in Türkiye, and a two-wave longitudinal research design and structural equation modeling were conducted to test the hypotheses of the conceptual model.

The results indicated that perceived goal impediment and prior negative experience had positive effects on affective avoidance in both ad-clutter and non-clutter periods. Further, affective avoidance had a significant positive effect on both cognitive and behavioral avoidance in either period. In addition, ad clutter moderated the effects of cognitive and behavioral avoidance on online purchase intention.

This research provides new evidence of the crucial role perceived goal impediment, prior negative experience and perceived control each play in driving digital ad avoidance. This paper contributes to the body of knowledge in the field by exploring how advertising clutter (both cluttered and non-cluttered settings) moderates these relationships through a two-wave longitudinal study.

This analysis examines the relationship between corruption and firm productivity in Vietnam.

The authors apply the system generalized method of moments estimation approach on a panel dataset constructed from comprehensive enterprise surveys covering all the sectors over the 2011–2020 period.

The results confirm a non-linear relationship between corruption and firm productivity. Where corruption is severe, leaving corruption alone tends to benefit firm productivity because efforts to control corruption are likely to cause greater delays. In less corrupt provinces, corruption appears to harm firm productivity while efforts to control corruption provide significant productivity gains. This U-shaped relationship is confirmed for small firms and those in the private sector sub-samples. Intriguingly, this study reveals that the U-shaped relationship does not apply to micro, medium, large firms, state-owned firms and foreign-invested firms because corruption is found to have no significant impact on productivity among these sub-samples. Changes in regulations after 2014 toward promoting a transparent business environment are shown to foster the positive impact of lowering corruption on firm productivity.

This study suggests that lowering corruption is beneficial for firm productivity at the micro level. However, where corruption is severe, monitoring corruption alone is likely to cause adverse effects on productivity due to increased bureaucratic delays. Institutional reforms might play an important role in leveraging the effects of lowering corruption on productivity in highly corrupt areas.

This paper sheds new light on the relationship between corruption and firm productivity in the broad existing literature and especially in the limited number of studies for Vietnam.