Authors - Anubrata Dhar Chaudhuri, Raj Chakraborty Abstract - The hospitality sector faces increasing pressure to integrate sustainability into operations while maintaining high productivity. Green Human Re-source Management (GHRM) practices have proven to enhance employee engagement and promote eco-friendly organizational citizenship behavior. How-ever, traditional GHRM frameworks lack the digital, real-time analytics needed to respond dynamically to workforce changes and sustainability goals. This research work proposes the AI-GHRM Integration Model (AGIM), a novel conceptual framework that extends the classical Stimulus-Organism-Response (SOR) paradigm into a dynamic feedback loop powered by artificial intelligence (AI). AGIM consists of a multi-layered architecture incorporating AI-based predictive analytics for attrition and engagement forecasting, NLP-driven sentiment analysis of employee well-being, IoT-enabled automation of sustainability compliance, and privacy-preserving security mechanisms. This paper outlines the AGIM conceptual model, compares its dimensions with traditional GHRM, and presents a hypothesis matrix linking AI-powered interventions to employee and sustainability outcomes. A mixed-method research methodology is discussed, blending qualitative case studies with quantitative analytics. Use case scenarios illustrate AGIM’s implementation phases in a hotel setting. The discussion highlights theoretical contributions (extending SOR with AI feed-back) and practical implications for business information systems in “smart secure systems”. Future work includes empirical validation and expansion to other service industries.
Authors - Nerisa Thornsr, Sa-Aat Niwitpong, Suparat Niwitpong Abstract - The delta-Rayleigh distribution comprises a mixture of zero and non-negative values following the Rayleigh distribution. Percentiles are practical tools for describing skewed data and are widely used in several fields. The purpose of this study is to construct confidence intervals for different percentiles of the delta-Rayleigh distributions using generalized confidence interval (GCI), normal approximation (NA), method of variance estimates recovery (MOVER), percentile bootstrap confidence interval (PBCI), and Bayesian methods. Monte Carlo simulations were conducted to evaluate the performance of these methods using coverage probabilities and average widths. The results indicate that the GCI method outperformed others. For a real-world data application, we utilized a dataset on CO concentration to assess the performance of the presented methods.
Authors - Surya Anugrah, Sabo Hermawan, Christian Wiradendi Wolor, Eka Septariana Puspa, Windy Permata Suyono, Dwi Handarini Abstract - Indonesia’s bold leap toward digital tax reform culminated in the 2025 launch of its Core Tax Administration System (CTAS) a centralized platform aimed at streamlining taxpayer services, boosting compliance, and modernizing revenue administration. This study critically evaluates the early- stage implementation of CTAS using a dual-theoretical lens: the Technology Acceptance Model (TAM) and Institutional Theory. Drawing on government documents, user surveys, and media analysis, findings reveal a paradox while users widely acknowledge CTAS’s potential to simplify tax filing, technical glitches, complex interfaces, and poor system responsiveness undermine its usability and acceptance. Moreover, institutional misalignments such as inadequate training, low digital literacy, and resistance to change pose structural barriers to reform success. By integrating behavioral insights with systemic analysis, this research highlights the multilevel challenges of digital transformation in public finance. The paper concludes with actionable lessons for emerging economies navigating the tension between technological innovation and institutional readiness in the digital era.
Authors - Krishna Saurabh Soni, Pranshi Talati, Jash Mandani, Dweepna Garg, Parth Goel Abstract - Recruitment has become a lot more complicated with a surge in the number of applicants for each job. Traditional resume screening methods are time-consuming and subjective—and that leads to inefficiencies and biases in candidate selection. What we need is a more efficient, fair and accurate way to evaluate resumes. That’s where a new resume screening system comes in. By using Retrieval-Augmented Generation (RAG) with the Gemini API, we can improve the accuracy, efficiency and fairness of resume evaluation. That system pulls out the most relevant information from resumes, compares a candidate’s skills to the job description and gives you a selection probability score-complete with reasoning. We combined Natural Language Processing (NLP), machine learning and a resume dataset from Kaggle to refine the evaluation process. The experiments show the model can identify missing skills, match candidate qualifications to job requirements and give job seekers valuable insights. Integrating RAG into the hiring process can make a real difference to recruitment outcomes-and reduce bias and manual workload.
Authors - Naina Kokate, Supriya Gorde, Rashmi Kale, Sayali Mulik, Kashmira Naik, Kartik Mundwadkar, Atharva Navale, Piyush Nakade Abstract - The rapid increase in portable electronic device usage has intensified the demand for sustainable and self-sufficient energy solutions. KineCharge addresses this need by innovatively harvesting kinetic energy generated during cycling and converting it into usable electrical power. The system uses a DC motor directly connected to a bicycle wheel, which produces electricity as the wheel rotates. This generated electrical energy is regulated through a diode to ensure proper current flow and is managed via a battery charging module. The harvested energy can be stored in a rechargeable battery for later use or accessed immediately through a USB output to charge smartphones and other portable devices. This design offers an environmentally friendly and costeffective alternative to traditional power sources, particularly benefiting cyclists, outdoor enthusiasts, and individuals in remote or off-grid locations. KineCharge promotes clean energy utilization while providing a practical means to keep devices powered during travel. By leveraging mechanical energy from cycling, it reduces reliance on conventional electrical grids and supports the adoption of sustainable energy practices. Additionally, the project serves as an educational tool that demonstrates principles of energy conversion and renewable power generation. Designed for easy installation on most bicycles, KineCharge offers a portable and green energy solution adaptable to a variety of users. It exemplifies innovative thinking in renewable energy and contributes to fostering energy independence and environmental sustainability in everyday life.
Authors - Surya Anugrah, Rochma Sudiati, Eka Septariana Puspa, Windy Permata Suyono, Sabo Hermawan, Septi Nurmalita Abstract - Carbon tax policies have been widely adopted as instruments for climate change mitigation; however, their implementation in developing countries continues to face significant structural and political challenges. This study aims to analyze the influence of per capita carbon emissions and tax revenue on carbon tax rates in ten developing countries during the period 2021-2023. Utilizing a panel data regression approach with fixed effects models, this research examines the causal relationship between environmental and fiscal factors and the determination of carbon tax rates. The estimation results reveal that per capita carbon emissions have a negative and statistically significant effect on carbon tax rates, with a coefficient of -6.09 (p0.05), suggesting that fiscal considerations are not yet a primary determinant in the design of carbon tax policies in developing economies. The policy implications of this study highlight the need for more progressive and integrated carbon tax reforms aligned with sustainable development agendas, particularly in support of Sustainable Development Goal (SDG) 13. This study contributes novel empirical evidence to the green fiscal literature in developing countries and offers strategic recommendations for policymakers to optimize the role of carbon taxation in global emissions reduction efforts.
Authors - Navya H, Ananthavalli Thangam Abstract - Education is an important tool in empowering people with the required knowledge and influencing their perspective and attitude for transforming the society. This assumes more importance in the context of the goal of lifelong learning. Achieving goals require behaviour change at multiple levels. This study is an attempt to assess the impact of education on the perspectives of people in promoting eco-friendly behaviour. Quality education is invariably connected with certain goals such as reducing poverty and promoting gender equality. As we drive towards the targets of SDGs, a closer look at the intricate relation of education with the goals of zero hunger, gender equality and poverty reduction points towards the urgency in using education not merely as a goal in itself but a catalyst for attaining the desired goals. Equipped with the necessary skills, education provides opportunities for employment. Coupled with the awareness of sustainable development, the goals of economic advancement can be attained with less damage to the environment. Inclusive education with provision of equal opportunities for women leads to gender equality and participation of women in progress. A cross-sectional survey was taken to assess the perspective of the role of education as a catalyst to promote the SDGs. The results strongly indicated the need to provide quality education with the right strategy and policy interventions. There are economic and social challenges to overcome. The role of institutions is to be emphasized. Concerted efforts by academicians, corporates and the government can strengthen the pillars of economy, environment and equity.
Authors - Tran Phuong Duy, Nguyen Gia Tuan Anh Abstract - This study aims to evaluate the trend of stock price fluctuations in the Vietnamese banking industry in the period of 2019-2023 by integrating real-world data with quantitative models and modern machine learning techniques. Data is collected from reputable sources such as HOSE, Vietstock and CafeF, including financial indicators (EPS, ROE, P/E, ROA), macroeconomic factors (operating interest rates, exchange rates, foreign cash flows) and market sentiment index (Vietnam VIX). The applied analytical models include linear regression, logistic regression, GARCH, VAR, VaR and Random Forest. The research results show that the VIX index has a clear impact on bank stock prices, and the proposed system is capable of supporting investors in determining the appropriate trading time, classifying stocks according to risk and expected return. The article not only provides a quantitative perspective but also provides an effective visualization tool, contributing to improving the quality of investment decisions in the Vietnamese stock market.
Authors - Usha Sadhani, Melita Simoes, A M Kadakol Abstract - In today’s dynamic work environment, employee attrition is a crucial challenge for organizations that are impacted by demographic and job-related factors. This study examines the role of gender in attrition across different job roles and encompasses a multi-method approach taking into consideration 1,470 employees. The analysis found that there is no significant influence of gender in the attrition rates. Job satisfaction and tenure of an employee within an organization emanated as stronger predictors of attrition than gender, aligning with the established theories that highlighted the preference of job-related factors over demographic characteristics that helps in the retention of an employee. The logistic regression model showed a statistically significant result but was not very effective at predicting who leaves, highlighting the complexity of attrition and the role of factors not included in the study. Overall, the findings suggest that gender alone is insufficient to explain attrition patterns, highlighting the importance of contextual factors such as job role and employee satisfaction. This research contributes to the ongoing dialogue on diversity and retention by demonstrating that effective talent management should consider the nuanced interactions between job characteristics and individual experiences rather than relying on broad demographic generalizations.
Authors - Priyanka S. Dhore, Michael Savariapitchai, Rohini Chavhan Abstract - Repeatedly, being burnt out, constitutes a severe health issue, affecting employee welfare, and negatively impacting the long-term sustainability of health organizations. It revolves around different types of management styles that don't burn an employee out, but instead create an environment conducive to work, given health institutions. Exploring the work of four different dimensions of leadership: transformational, ethical, health-promoting, and resilient; would be towards reducing burning out and improving employee well-being, as well as creating a positive organizational culture. The study adopted a quantitative approach wherein close-ended survey questionnaires were used to collect data from a sample of 101 healthcare employees. Results revealed that empathic, supportive, and team-focused behavior of leaders has considerable impact on the burnout and job satisfaction levels of workers. In addition, interventions such transformational and health-promoting leadership have been found to have a positive influence on organizational health, supportive policies, and retention of employees, among others. Workplace leadership praise the productivity and balance. Leadership helps to focus Tasks. It encourages the distribution of workloads. It sets up mental health projects and it backs employee welfare. Healthcare leadership requires listening to concerns raised by employees, creating a work-life balance, and enforcing fair policies to prevent burnout. There is evidence in favor of having an enlightened discussion for healthcare leaders that improves the environment balancing conditions between burnout-prevention and better performance of the organization.
