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This study aims to deeply analyze the contribution of work motivation and work environment conditions in improving employee satisfaction and performance. The methodology applied is a Systematic Literature Review (SLR) following the guidelines of Wahono (2015) and Kitchenham (cited in Fauzi et al., 2018). Data were collected through literature exploration in Google Scholar, Garuda Ristekdikti, and university journal websites with a publication limit between 2020 and 2025. Through a selection process, a number of relevant articles were successfully collected for narrative analysis. The results of the study revealed that work motivation has a positive and significant influence on employee performance, both directly and indirectly through job satisfaction as a mediator. A supportive work environment also plays a crucial role in increasing employee enthusiasm, productivity, and job satisfaction. Overall, the synergy between high work motivation and a conducive work environment can create maximum performance and strengthen employee loyalty to the organization. The results of this study provide importance for human resource managers to pay more attention to motivation and work conditions as an approach to improving performance and efficiency in organizations.

In the current era of digital transformation, organizations are increasingly turning to Artificial Intelligence (AI) to enhance the precision and agility of managerial decisions. This study investigates how AI adoption within management accounting systems influences decision-making efficiency and managerial performance. Using survey data collected from managers and accountants in medium-to-large firms across Central Java, the research applies Partial Least Squares Structural Equation Modeling (PLS-SEM) to examine the hypothesized relationships. The results reveal that AI adoption significantly improves decision-making efficiency, which in turn enhances managerial performance. Furthermore, leadership support strengthens the relationship between AI adoption and decision-making efficiency, indicating that human and organizational factors remain critical for realizing technological benefits. The findings contribute to management accounting literature by elucidating the mechanism through which AI technologies create managerial value specifically, by accelerating analytical processes and improving the quality of managerial judgments. Practically, the study suggests that firms should focus on leadership involvement, data governance, and employee training to ensure that AI systems complement, rather than replace, human judgment. Overall, this study highlights that successful AI adoption in management accounting is not merely a technical transition but a strategic and cultural evolution toward evidence-based decision-making.

This study aims to determine whether there is an influence on the Impact of the Digital Era (X1), Organizational Culture (X2), and Employee Involvement (X3) on Employee Work Efficiency (Y) at PT Indogadai Prima Tangerang City Branch. The research used in this study is quantitative, with a non-probability sampling technique. The sample consisted of 100 respondents representing different job positions, ranging from area managers, store heads, cashiers, to sales clerks. Data were collected through a structured questionnaire using a Likert scale. Furthermore, the data analysis applied descriptive statistics, validity and reliability tests, classical assumption tests, multiple linear regression, t-tests, and the coefficient of determination using SPSS version 25. The results of this study indicate that the Impact of the Digital Era has a positive but not significant effect on Employee Work Efficiency, Organizational Culture has a significant effect on Employee Work Efficiency, while Employee Involvement does not significantly influence Employee Work Efficiency. Among the independent variables, Organizational Culture is the most influential factor in determining employee efficiency. The findings highlight the importance of strengthening organizational culture to enhance efficiency while ensuring that digital transformation is implemented with strategies that reduce resistance and increase adaptability. This research contributes theoretically to the study of human resource management in the digital transformation era and provides practical recommendations for companies in developing policies to optimize employee efficiency.

Recent developments in information and communication technology such as artificial intelligence (AI) provide new opportunities to increase the efficiency and accuracy of performance assessment. The impact of the COVID-19 pandemic and the shift to a remote work model has created a need for technology solutions to unify and transmit the performance of employees working from multiple locations. The use of technology in performance management evaluations may raise concerns regarding data security and privacy, inconvenience or resistance to employees or stakeholders. Not all employees or managers have the same level of skill and understanding of the technology being implemented and it requires a high initial investment in maintenance and upgrades. This article provides an understanding of how technology can be applied in management performance evaluation and its benefits in increasing efficiency, objectivity and accuracy in employee assessment as well as providing recommendations for innovation and changes in the use of technology in management performance evaluation. The methodology used is a qualitative method by collecting data from various information sources. Some of the positive impacts of implementing technology in performance evaluation management are increased efficiency and productivity, real-time feedback, increased objectivity and fairness, more accurate and measurable performance monitoring. The technologies that can be used are Go Talent, Feedback and Recognition Systems, Analytics Technology, Application-Based Performance Evaluation Systems, Use of AI for Objective Evaluation and Chabots for Feedback.