To increase inter-region connectivity, the Indonesian government initiated infrastructure projects such as toll roads, airport, highways, as well as agriculture ones throughout the countries. One of the big projects in road infrastructure was the Cikampek–Palimanan (Cipali) toll road in West Java with a budget of more than USD1 billion which started to operate in July 2015. This paper is aimed to evaluate the impact of the toll road on accessibilities, trades, and investments in the region it traverses. To carry out the analysis, we used qualitative approach, difference-in-difference approach, and ANOVA, utilizing three kinds of data. The first data is collected from a survey of 331 small-medium enterprises (SMEs) in the logistics and the hotel and restaurant industries. The second one is bank loan data sourced from Bank Indonesia, while the third one is investment data from Investment Coordinating Board of Indonesia (BKPM).
After two years of its operation, Cipali toll road has increased accessibility, mobility, trade, and investment in the region it traverses. The travel time was reduced by 39%, while the cargo volume of the local businesses increased by 30% to 40%. These led to an improvement of wholesale trade volume in almost all regencies. However, SMEs in the hotel and restaurant industry along the traditional northern coastal highway in Subang, Indramayu, and Brebes experienced a decline due to the traffic shifting. Meanwhile, investments from national companies especially those of labor-intensive manufacturing industries flowed significantly especially to Subang and Majalengka, which reflected a “sorting effect”. However, investments from local and foreign businesses did not increase significantly yet after 2.5 years of toll operation.
To reap the benefit from the presence of Cipali toll road, the local governments should improve the ease of doing business to attract investments that boost employment in return. In addition, given a better accessibility from Greater Jakarta and a large number of potential visitors passing through the toll road, local businesses in the trade sector would benefit if they could promote the local attractions such as in tourism activities supported by the local government. The latter strategy should also be implemented by the local governments and local businesses in the northern coastal traditional route to minimize the negative impact of the toll road due to the traffic shifting. This strategy should be strengthened through increasing connectivity from the toll exits to local business areas and through increasing the ease of doing business.

This study investigates non-academic employees’ perceptions of their line managers’ leadership styles at a private university in Malaysia and how these perceptions influence their intention to remain employed. Employing a qualitative approach and the path-goal theory as a theoretical framework, data were collected through purposive sampling from 10 non-academic employees and analyzed thematically using NVivo 12 software. The findings reveal that a supportive and participative leadership style fosters an informal leadership dynamic between line managers and subordinates. Informal leadership behaviors encompass affective qualities and effective communication that enable the development of close relationships outside the workplace, facilitating increased employee engagement and motivation levels. Consequently, this approach notably improves employee retention. This study offers a comprehensive understanding of informal leadership styles contributing to enhanced human resource management at the private university while providing an inclusive perspective on employees’ perceptions and their intention to remain employed. Finally, we propose a model of employees’ perception of leadership styles as the main driver that better serves their intention to stay in organizations.

This study aims to investigate the impact of dance training on the mental health of college students. Utilizing experimental research methods, we established an experimental group and a control group to compare changes in mental health dimensions—including anxiety, depression, self-esteem, and social skills—between the two groups before and after 12 weeks of dance training. The findings indicate that dance training significantly reduces levels of anxiety and depression, while also improving self-esteem and social skills, thereby enhancing social adaptability. These results provide empirical support for the use of dance as an intervention for mental health and offer new insights for mental health education in colleges and universities.

The purpose of this study is to investigate the relationship between the use of business intelligence applications in accounting, particularly in invoice handling, and the resultant disruption and technical challenges. Traditionally a manual process, accounting has fundamentally changed with the incorporation of BI technology that automates processes and allows for sophisticated data analysis. This study addresses the lack of understanding about the strategic implications and nuances of implementation. Data was collected from 467 accounting stakeholder surveys and analyzed quantitatively using correlational analysis. Multiple regression was utilized to investigate the effect of BI adoption, technical sophistication on operational and organizational performance enhancements. The results show a weak association between the use of BI tools and operational enhancements, indicating that the time for processing invoices has decreased. Challenges due to information privacy and bias were significant and negative on both operational and organizational performance. This study suggests that a successful implementation of a BI technology requires an integrated plan that focuses on strategic management, organizational learning, and sound policies This paper informs practitioners of how accounting is being transformed in the digital age, motivating accountants and policy makers to better understand accounting as it evolves with technology and for businesses to invest in concomitant advances.

The main purpose of this paper was to examine the impact of generative artificial intelligence (AI) on employee well-being and work dynamics. Using qualitative methodology, three semi-structured interviews were conducted to investigate the implications of generative AI on employee outcomes such as efficiency, job satisfaction, ethical considerations, and work-life balance. The findings highlighted the potential benefits and risks associated with generative AI implementation in the workplace. The study contributed to the literature by adopting a qualitative approach, allowing in-depth exploration of individual experiences with generative AI in the workplace. The study discussed the implications for employers, employees, and society.

This study explores the intricate relationship between emotional cues present in food delivery app reviews, normative ratings, and reader engagement. Utilizing lexicon-based unsupervised machine learning, our aim is to identify eight distinct emotional states within user reviews sourced from the Google Play Store. Our primary goal is to understand how reviewer star ratings impact reader engagement, particularly through thumbs-up reactions. By analyzing the influence of emotional expressions in user-generated content on review scores and subsequent reader engagement, we seek to provide insights into their complex interplay. Our methodology employs advanced machine learning techniques to uncover subtle emotional nuances within user-generated content, offering novel insights into their relationship. The findings reveal an inverse correlation between review length and positive sentiment, emphasizing the importance of concise feedback. Additionally, the study highlights the differential impact of emotional tones on review scores and reader engagement metrics. Surprisingly, user-assigned ratings negatively affect reader engagement, suggesting potential disparities between perceived quality and reader preferences. In summary, this study pioneers the use of advanced machine learning techniques to unravel the complex relationship between emotional cues in customer evaluations, normative ratings, and subsequent reader engagement within the food delivery app context.