Purpose: The purpose of this paper is to explore the impact of Artificial Intelligence on the performance of Indian Banks in terms of financial metrics. The study focused specifically on the NIFTY Bank Index. The paper also advocates that a greater transparency in disclosing AI related information in a Bank’s annual report is required even if it is voluntary. Design/Methodology/Approach: The paper uses a mixed method approach where quantitative and qualitative analysis is combined. A dynamic panel data model is used to understand the impact of AI of Return on Equity (RoE) of 12 Indian Banks in the NIFTY Bank Index over a five-year period. In addition to that, Content analysis of annual reports of banks was conducted to examine AI related disclosure and transparency. Findings: The paper highlights that the integration of Artificial Intelligence (AI) significantly influences the financial performance of sample banks of India. Return on Equity the specific parameter positively influenced with adoption of AI. The profitability of banks is positively impacted by reduced errors and improved operational efficiency. The content analysis of annual reports of the banks indicates different approach for AI disclosure where some banks give detailed information and some are not transparent about AI initiatives. The findings suggest that a higher level of transparency could enhance confidence of all stakeholders. Theoretical Implications: The positive relation between adoption of AI and financial performance, specifically ROE, gives a foundation for academic research to explore the dynamics of emerging technology and financial systems. The study can be extended to explore the impact on other performance indicators in different sectors. Practical Implications: The findings of this study emphasize the importance of transparent AI related disclosures. A detailed reporting about integration of AI helps in enhanced stakeholders’ confidence in case of banking industry. The regulatory framework of banks may also consider making mandatory AI disclosure practices to ensure due accountability to maximize the benefits of AI in banking.
This paper reviews the emerging potential of mid-tier transit, articulating how a complex set of established and new factors could contribute both to better transit outcomes and the associated urban regeneration around station precincts. The analysis is based on two structured literature reviews, supported by insights from the authors’ original research. The first provides an overview of the established and new rationale for mid-tier technologies such as the established Light Rail Transit (LRT) and Bus Rapid Transit (BRT) as well as the new Trackless Tram Systems (TTS). The established role for mid-tier transit is now being given extra reasons for it to be a major focus of urban infrastructure especially due to the need for net zero cities. The second review, is a detailed consideration of established and new factors that can potentially improve patronage on mid-tier transit. The established factors of urban precinct design like stop amenities and improved accessibility and density around stations, are combined with new smart technology systems like advanced intelligent transport systems and real-time transport information for travellers, as well as new transport technologies such as micro-mobility and Mobility on Demand. Also explored are new processes with funding and development models that properly leverage land value capture, public private partnerships, and other entrepreneurial development approaches that are still largely not mainstreamed. All were found to potentially work, especially if done together, to help cities move into greater mid-tier transit.
This research paper aims to explore the issue of university dropouts in Greece, which has become a growing concern in recent years due to its impact on individuals, educational institutions, and society as a whole. One of the main contributing factors to students discontinuing their higher education in Greece is the choice of the wrong faculty. Financial challenges, unrelated to tuition fees, also significantly affect students’ ability to pursue their studies. Family background plays a crucial role, with students from families with higher educational attainment exhibiting greater persistence. The study found that gender, age, and academic performance can influence students’ perceptions of dropout factors, which can change as they progress through their educational journey. To address these challenges, the research proposes a multifaceted approach, including early intervention programs, expanded financial support, improved mental health and counseling services, flexible learning options, and strong academic advising.
The rapid advancement of financial technology (Fintech) has revolutionized the way financial transactions are conducted, with E-payment services becoming increasingly integral to daily commerce. This paper examines consumer perceptions and attitudes towards E-payment services offered by Fintech companies, identifying key factors that influence their acceptance and usage. Employing a quantitative approach, the research integrates quantitative data from surveys and applied SEM (Structural Equation Modelling) through AMOS. Out of 450, 420 respondents have given their views on perceptual preferences and attitudes with the help of SPSS. KMO and Bartlett’s Test are executed to understand and to check the factors for implementing factor analysis further through extractions. Anticipated findings are expected to reveal a spectrum of consumer attitudes shaped by factors such as trust, security, convenience, and technological familiarity. It contributes to the existing literature by providing updated insights into consumer behaviour in the Fintech sector and suggesting actionable strategies for service providers to enhance user engagement and satisfaction. It holds the potential to inform both theoretical frameworks in technology acceptance and practical marketing strategies for Fintech companies aiming to optimize E-payment services for diverse consumer bases.
The study aims to investigate and analyse the social media, precisely the Instagram activity of several hotels in the city of Yogyakarta, Indonesia. Having been the second most popular destination besides Bali, it is mainly dominated by domestic tourism. Although several governmental institutions exist, the study focuses on the hotel’s activity only. The main purpose was to find, that after the classification of the posts, whether there is a more positive effect of one as opposed to the other type of posts. In addition, it was also important to see if with the time advancing positive effect of likes and comments appear and the relation of hashtags, likes and comments. Data was collected between 1st of January 2023. and 15th of July 2024. The first step was to collect posts done by the suppliers and then the posts were classified. Also, the number of hashtags used were collected. Second step was to collect the response from the demand side by gathering their likes and comments. Data then was analysed with SPSS 24 and JASP program. Results show that while there is no significance on increasing likes and comments with the months advancing, but in terms of the type of the posts there is. Promotional posts with other suppliers tend to bring a lot more comments and likes than self-promotional posts. This study’s main purpose to analyse through social media posts to enhance online networking by local suppliers promoting each other’s products.
The policy to accelerate the design of the Detailed Spatial Plan regulation document (RDTR) is a strategic step to enhance ease of doing business and promote sustainable development in Indonesia. Targeting 2036 RDTR sites nationwide, the initiative relies on various policy interventions and technical approaches. However, as of 8 January 2024, only 399 RDTRs (19.59%) were enacted after four years of implementation. This underperformance suggests the need to examine factors influencing the process, including issues at each stage of the RDTR design business process. While often overlooked due to its perceived irrelevance to the core substance of planning, analyzing the process is crucial to addressing operational and procedural challenges. This research identifies critical issues arising from the preparation to the enactment stage of RDTR regulations and proposes necessary policy changes. Using an explanatory approach, the study employs methods such as Analytic Hierarchy Process (AHP), post-review analysis, stakeholder analysis, business process evaluation, and scenario planning. Results show several impediments, including challenges related to commitment, technical and substantive issues, managerial coordination, policy frameworks, ICT support, and data availability. These findings serve as inputs for the development of business process improvement scenarios and reengineering schemes based on Business Process Management principles.
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