The integration of data analytics into forensic accounting has revolutionized the detection and prevention of financial fraud. This paper conducts a comprehensive analysis of recent advancements in this field, highlighting the application of machine learning, data mining, and big data techniques in identifying fraudulent activities. By reviewing the latest research and examining case studies, we demonstrate the enhanced accuracy and efficiency these technologies offer over traditional methods. The findings suggest that financial institutions should adopt these advanced tools to mitigate fraud risks and improve overall financial security. The paper also explores future research directions, emphasizing the need for developing hybrid models and real-time detection systems to further enhance fraud detection capabilities.

Abstract The main aim of this study is to explore the mediating effect of innovation in the relationship between human resource management (HRM) practices and organizational performance. HRM practices are observed through selective hiring, training, participative decision-making, and rewarding. Innovation is conceptualized over behavioral, product, process, and market innovation. The study relies upon the principles of social exchange theory and resource-based theory. Data were collected from 408 managers in an emerging economy context. The proposed conceptual model is evaluated with structural equation modeling using Lisrel 8.8 and SPSS 22. Study findings suggest that innovation influences the relationship between selective hiring, training, and participative decision-making and organizational performance. However, no mediating effect of innovation was found in a relationship between rewarding and organizational business performances. Since human resources and innovation are among the leading sources for building competitive advantage for companies, the study findings contribute to HRM and innovation.

Enterprise resource planning (ERP) systems have become the most important tool for integrating businesses and achieving the “once only” principle in data entry, which contributes to resource efficiency, the enhancement of numerous organizational processes and capabilities, and, ultimately, improved business performance. In this study, we examine the ERP system’s quality as the company’s dynamic capability, contributing to business performance according to the dynamic capability perspective. Thus, we incorporate theoretical mechanisms into the model of the ERP system’s dimensions as a function of financial and non-financial organizational performance. We hypothesized that companies with a better ERP system, with all three dimensions, information, system, and services, will achieve better non-financial and financial performance. The model was tested using primary data collected using a survey method in the environment of a developing country, where the digital transformation of companies is still at a lower level. Structural equation modeling was employed for data analysis, and the results suggest a positive relationship between ERP system quality and both types of organizational business performance. The results indicate that not all dimensions have the same effect. The quality of information and service is particularly important for business performance until the system’s technical characteristics have no significant effect.

As we look at our daily lives and the world around us, it is becoming more and more difficult to learn new things and our new knowledge is suffering because of the fast and intense way of life we lead. The development of technology has greatly influenced this way of life. In recent years, we have witnessed the rapid growth and development of technology and seen how technology affects many aspects of our lives. Therefore, the aim of this paper is to contribute to the under-standing of the concept of e-learning in organizations and the influence of organizational support on the intention to use e-learning systems and how the use of e-learning improves individual work performance. The paper used structural equation modelling technique to test the hypotheses at the level of employees in different sectors. The results showed that the most significant predictor of individual job performance was intention to use e-learning, followed by knowledge sharing. In addition, the results showed that knowledge sharing and personal innovative-ness were significant predictors of perceived usefulness.

this paper draws on Uses and Gratification theory and aims to explore the role and impact of different types of social media use at the workplace on employee innovative behavior and individual job performance. Structural equation modeling was used in the estimation of the model linking social media use, employee innovative behavior, and job performance. The findings suggest that only the cognitive use of social media in the workplace has a positive impact on employee innovative behavior and indirectly on job performance. In contrast, social use has a significant negative effect on job performance.