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Investigating and analyzing the causality amid tourism, environment, economy, energy consumption, and carbon emissions using TodaYamamoto approach for Himachal Pradesh, India
Himachal Pradesh is a preferred tourist destination with a Compound Annual Growth Rate (CAGR) of 10.76% between 201112 and 202021. The increasing trend of CAGR has boosted the tourism economy in the state while impacting the local environment. The negative impacts have recently increased due to changes in climatic patterns and increased tourism influx during the post-pandemic period. In this context, the present study analyzed the impact of tourism on the environment, economy, and energy consumption using the Environmental Kuznets Curve (EKC) hypothesis. The novelty of this study is to the existing literature on sustainable tourism development through investigating the interrelationship between tourism, environment, economy, energy consumption, and carbon emissions by employing the TodaYamamoto (TY) technique. This study will be a pioneering scientific investigation with quantitative results in the western Himalayan states of India, encompassing Jammu & Kashmir, Uttarakhand, and Himachal Pradesh. The annual data for each variable, such as per capita carbon emission (CEP), per capita Gross State Domestic Product (GSDP), per capita GSDP square, per capita energy consumption (ECP), and per capita tourism receipts (TRP), was collected from 2010 to 2021. This study exhibited an inverted-U EKC in the state, signifying the initial stage of economic development and extensive exploitation of natural resources for tourism. The TY results indicated an inter-causal relationship and feedback association among the variables in the study area. Thus, increased TRP would lead to an upsurge in energy consumption affecting the environmental quality due to increased carbon emissions. Such environmental degradation in the state would negatively impact the tourism sector in the long run. The research findings would guide planners and policymakers in promoting sustainable tourism. The Author(s), under exclusive licence to Springer Nature B.V. 2023. -
Investigating Educators Behavioural Intentions Towards Smart Tools in Education
This study explores pre-service and in-service teachers behavioral intention to adopt smart tools by examining their perceptions of usefulness, ease of use, enjoyment, and contextual readiness. Using a quantitative survey design, data was collected from 42 participants across the Delhi-NCR region through purposive sampling. A composite score of 15 Likert-scale items was used to measure behavioural intention, followed by quartile-based analysis, independent samples t-tests (for gender), and one-way ANOVA (for age groups). While results revealed no statistically significant differences across gender and age, the quartile distribution indicated a varied spectrum of intention, with participants broadly categorised into low, moderate, and high-intention groups. The study highlights the need for teacher training programs to go beyond technical instruction. It advocates for a more nuanced, context-aware approach to technology readiness in teacher education that bridges the gap between vision and practice in the evolving ecosystem of Education 5.0. 2026 by IGI Global Scientific Publishing. All rights reserved. -
Investigating Factors for an Inclusive Workforce for Women in the Logistics and Supply Chain Industry
This study seeks to identify and analyze the major factors that contribute to an inclusive workforce for women in the area of logistics and supply chain. It further addresses the need for gender diversity and inclusivity in a traditionally male-dominated field by adopting a human-centric approach. This study employs a combination of Fuzzy Delphi Method (FDM) and Fuzzy Best Worst Method (FBWM) for methodically identifying and prioritizing factors that influence inclusiveness for women in the logistics and supply chain industry. FDM gathers experts' opinions and achieves a consensus on the identified relevant factors. Subsequently, FBWM is used to analyze the factors, providing a clear priority ranking based on their relative significance. The analysis identified potential factors that are crucial for fostering an inclusive workforce in the logistics and supply chain industry for women. The factors were classified into three main categories: employee growth and culture, inclusive business ecosystems, and accessibility and diversity factors. Based on the global weights, the top three ranked factors are: gender-inclusive supply chain practices, skill development workshops, and supporting women-owned businesses. This study is original in terms of gender inclusiveness in the logistics and supply chain industry. The innovative combination of multiple methods stipulates a robust methodology for identifying and analyzing the factors that impact inclusiveness, offering a novel contribution to the literature and practical applications in this field. 2025 The Author(s). Corporate Social Responsibility and Environmental Management published by ERP Environment and John Wiley & Sons Ltd. -
Investigating Factors in Quality of Work-life in Indian Garment Industry at Bangalore
The Indian manufacturing sector has a long way to go in enhancing work-life standards for employees. Low standards of work-life hamper the productivity of an organization. Most employees of garment manufacturing units in Bengaluru are from outer rural areas. They come in search of employment in garment units. Though there are labour acts and labour laws, most of the manufacturing units provide poor job environments for employees. This leads to fluctuations in the performance of employees and would have detrimental effects on their health and performance, resulting in attrition. Quality of work life is the solution. This paper aims at unravelling factors leading to recognition of work-life standards so those garment units can work in that dimension to solve their productivity issues and also improve the happiness of their employees. A descriptive approach was made to attain objectives with survey-based data collection. The collected data were subjected to exploratory factor analysis and multiple regression analysis. The study found welfare and safety lead to a quality of work-life in garment units. More cross-sectoral studies are suggested to understand the blend of factors defining the quality of work life and arrive at a generalized model nation-wide. This generalization in the long term should be a key decision-making point for safety and welfare policy development in the world. 2022 The authors. -
Investigating Funding Inequities, Resource Allocation, and Institutional Biases Impacting Marginalized K- 12 Students
Investigating funding inequities in K- 12 education reveals how resource allocation and institutional biases disproportionately affect marginalized students. Many schools serving low- income and minority populations often receive significantly fewer financial resources than their wealthier counterparts. This stark disparity not only imcts the quality of education but also limits access to essential programs and support services. Additionally, institutional biases, both implicit and explicit, can further exacerbate these inequities, influencing decisions related to student discipline, curricular offerings, and support services. It is crucial to analyze how these systemic issues perpetuate cycles of disadvantage, affecting student achievement and overall well- being. Efforts focused on reforming funding formulas, enhancing community engagement, and promoting equitable practices within schools must be foundational to ensuring all students have the opportunity to thrive academically.. 2026 by IGI Global Scientific Publishing. All rights reserved. -
Investigating key biological traits of Malva parviflora influencing its competitive invasion in wheat crops
Plant invasion is a major concern for ecologists and agriculturists. Early detection of potential invaders (weeds) would save energy and resources that would otherwise be used to tackle them after they had spread. A study was initiated at the ICAR-Indian Agricultural Research Institute, New Delhi, on the basis of the early detection and rapid response (EDRR) strategy. For this study, we choose the little mallow (Malva parviflora L.), a newly introduced Malvaceae family weed in the agricultural fields of Delhi and adjoining regions of India. The above-ground allometric parameters ofM. parviflora populations in the main field and the field boundary were compared. The findings revealed that the EDRR approaches established by this study provided useful information to corroborate the weed species' invasion. The canopy diameter, plant height, and the number of leaves M. parviflora differed between the field boundaries (25.72cm, 24.40cm, 58.97, respectively) and main field (12.79cm, 49.08cm, 18.85, respectively) populations in all three locations, except the canopy diameter was comparable in location 2. Furthermore, neighborhood analysis showed that the M. parviflora had greater acclimatization with a variety of neighbors (38 plant species), i.e., legumes, noxious weeds, and seasonal dominant weeds. Malva parviflora has become a dominant weed along the field boundary. However, it has the potential to spread to the main field and become a serious weed in winter crops in the future. The EDRR methodologies developed in this study can be used to assess the invasion of new weeds in a variety of habitats. Plant Science and Biodiversity Centre, Slovak Academy of Sciences (SAS), Institute of Zoology, Slovak Academy of Sciences (SAS), Institute of Molecular Biology, Slovak Academy of Sciences (SAS) 2025. -
Investigating Key Contributors to Hospital Appointment No-Shows Using Explainable AI
The healthcare sector has suffered from wastage of resources and poor service delivery due to the significant impact of appointment no-shows. To address this issue, this paper uses explainable artificial intelligence (XAI) to identify major predictors of no-show behaviours among patients. Six machine learning models were developed and evaluated on this task using Area Under the Precision-Recall Curve (AUC-PR) and F1-score as metrics. Our experiment demonstrates that Support Vector Classifier and Multilayer Perceptron perform the best, with both scoring the same AUC-PR of 0.56, but different F1-scores of 0.91 and 0.92, respectively. We analysed the interpretability of the models using Local Interpretable Model-agnostic Explanation (LIME) and SHapley Additive exPlanations (SHAP). The outcome of the analyses demonstrates that predictors such as the patients' history of missed appointments, the waiting time from scheduling time to the appointments, patients' age, and existing medical conditions such as diabetes and hypertension are essential flags for no-show behaviours. Following the insights gained from the analyses, this paper recommends interventions for addressing the issue of medical appointment no-shows. 2024 IEEE. -
Investigating MnSe@Y2O3 nanocomposite as an electrode for asymmetric hybrid supercapacitor
In this research work, manganese selenide (MnSe) and yttrium oxide (Y2O3) nanoparticles have been synthesized by facile melt diffusion and hydrothermal technique which are then composited by ultrasonication. The composite MnSe@Y2O3 has been analyzed as a supercapacitor electrode. The growth structure of the composite was scrutinized systematically by powder X-ray diffraction (PXRD), scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX), high resolution transmission electron microscopy (HRTEM), and selected area diffraction pattern (SAED). The Trasatti and Dunn's plots have been also plotted to calculate the capacitive and diffusive contribution. The device is fabricated with PVA-KOH gel electrolyte. Also, the fabricated device MnSe@Y2O3||AC has exhibited a specific capacity of 48.39 C/g at 1 A/g through the potential window of 01.7 V. The wide potential window is evidence for high energy density. This also provides elevated energy density of 19 Wh/kg, at high power density of 1445 W/kg, and has shown brilliant cyclic stability of 70.16 % even after 5000 charge/discharge cycles. 2024 Elsevier B.V. -
Investigating Personalized Learning Paths to Address Educational Disparities Using Advanced Artificial Intelligence Systems
This innovative study reimagines the role of Natural Language Processing (NLP) in individualized education by highlighting the critical need to incorporate cultural subtleties. While natural language processing (NLP) offers great potential for improving classroom instruction, current research frequently fails to account for the complex issues caused by cultural variation. This research fills a significant need by providing a novel framework for the detection and incorporation of cultural subtleties into individualized learning programs. Further research into common biases is driving the development of natural language processing models with greater cultural sensitivity and awareness, such as gender bias in Named Entity Recognition (NER) and sentiment bias in cultural preferences. In order to correct past biases and promote gender neutrality in educational content, the research makes use of an adaptive NER algorithm and a diverse training dataset. Similarly, to guarantee nuanced and fair sentiment evaluations, the study suggests regularly evaluating and retraining sentiment algorithms with datasets that represent multiple cultures. A Cultural Relevance Score of 0.9, Adaptive Content Embedding vectors [0.3, 0.6, -0.2.], and an impressive Cosine Similarity of 0.85 are some of the evaluation measures that highlight the effectiveness of the research. These measurements show encouraging gains, which confirms that the research might help make schools more welcoming and sensitive to different cultures. The research has the potential to revolutionize individualized education by making it more accessible and engagingfor students from all backgrounds. 2024 IEEE. -
Investigating Risk Factors for Enhanced Portfolio Performance: An AI Approach for Indian Midcap Market Analysis
This research investigates the potential of machine learning (ML) for constructing portfolios that outperform human-based management, specifically focusing on the Indian midcap market. The study compares AI-based portfolio compositions, optimised using various risk measures, to the holdings of top midcap mutual funds. In this research, the top five midcap mutual funds sectoral distributions, portfolio compositions, and AI-generated portfolios are examined. According to the research, there is significant performance potential in the AI-generated portfolio, particularly when taking shorter investment horizons into account. Portfolios that maximise the Sharpe ratio produced the best returns throughout the course of the test period for four out of the six sectors, according to the research statistics. Additionally, in order to shed light on the effectiveness and possible advantages of our strategy, our study compares the suggested technique to existing investing strategies that concentrate on particular corporations as well as well-established market benchmarks. The research shows that, particularly when taking shorter investment horizons into account, the AI-generated portfolio has great performance potential. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Investigating Salt-Finger Convection Under Time-Dependent Gravity Modulation in Micropolar Liquids
This paper investigates how gravity modulation affects salt-finger convection in a micropolar liquid layer confined between two parallel, infinitely long plates separated by a thin gap. The system is heated and has solute added from above. The study uses linear stability analysis to examine when and how salt-finger convection, driven by the salt-finger process, begins. To analyze this, the partial differential equations governing the system are solved numerically using normal mode analysis. The Venezian approach is applied to find the critical Rayleigh number and the solutal Rayleigh number, which are key to understanding the onset of convection. Also, the paper explores how different micropolar fluid parameterssuch as the coupling parameter, micropolar heat conduction parameter, couple stress parameter, and inertia parameteraffect the system when gravity modulation is present. It is found that gravity modulation can either stabilize or destabilize convection, depending on its frequency. At very high frequencies (approaching infinity), the effect of gravity modulation becomes minimal, having little impact on the convection process. The paper also examines the relationship between the critical Rayleigh number and the solutal Rayleigh number, which are related to heat and solute concentration, respectively. 2024 Wiley Periodicals LLC. -
Investigating Salt-Finger Convection Under Time-Dependent Gravity Modulation in Micropolar Liquids
This paper investigates how gravity modulation affects salt-finger convection in a micropolar liquid layer confined between two parallel, infinitely long plates separated by a thin gap. The system is heated and has solute added from above. The study uses linear stability analysis to examine when and how salt-finger convection, driven by the salt-finger process, begins. To analyze this, the partial differential equations governing the system are solved numerically using normal mode analysis. The Venezian approach is applied to find the critical Rayleigh number and the solutal Rayleigh number, which are key to understanding the onset of convection. Also, the paper explores how different micropolar fluid parameterssuch as the coupling parameter, micropolar heat conduction parameter, couple stress parameter, and inertia parameteraffect the system when gravity modulation is present. It is found that gravity modulation can either stabilize or destabilize convection, depending on its frequency. At very high frequencies (approaching infinity), the effect of gravity modulation becomes minimal, having little impact on the convection process. The paper also examines the relationship between the critical Rayleigh number and the solutal Rayleigh number, which are related to heat and solute concentration, respectively. 2024 Wiley Periodicals LLC. -
Investigating stock market efficiency in India
International Journal of Computer Application & Management, Vol. 3, Issue 3,pp.45-48 ISSN No. 2231-109 -
Investigating sustainable development for the COVID-19 vaccine supply chain: a structural equation modelling approach
Purpose: Immunization is one of the most cost-effective ways to save lives while promoting good health and happiness. The coronavirus disease 2019 (COVID-19) pandemic has served as a stark reminder of vaccines' ability to prevent transmission, save lives, and have a healthier, safer and more prosperous future. This research investigates the sustainable development (SD) of the COVID-19 vaccine supply chain (VSC). Design/methodology/approach: This study investigates the relationship between internal process, organizational growth, and its three pillars of SD environmental sustainability, economic sustainability and social sustainability. Survey-based research is carried out in the hospitals providing COVID-19 vaccines. Nine hypotheses are proposed for the study, and all the hypotheses got accepted. The survey was sent to 428 respondents and received 291 responses from health professionals with a response rate of 68%. For the study, the healthcare professionals working in both private and public hospitals across India were selected. Findings: The structural equation modelling (SEM) approach is used to test the hypothesis. All nine hypotheses are supported. This study examines a link between internal processes and organizational learning and the three sustainability pillars (environmental sustainability, economic sustainability and social sustainability). Practical implications: This study will help the management and the policymakers to think and adopt SD in the COVID-19 VSC. This paper also implies that robust immunization systems will be required in the future to ensure that people worldwide are protected from COVID-19 and other diseases. Originality/value: This paper shows the relationship between organizational learning and internal process with environmental sustainability, economic sustainability and social sustainability for the COVID-19. Studies on VSC of COVID-19 are not evident in any previous literature. 2022, Subhodeep Mukherjee, Manish Mohan Baral, Venkataiah Chittipaka, Surya Kant Pal and Ramji Nagariya. -
Investigating system vulnerabilities in digital environments
[No abstract available] -
Investigating the contrast diurnal relationship of land surface temperatures with various surface parameters represent vegetation, soil, water, and urbanization over Ahmedabad city in India
Many climatic problems have arisen due to congested and inefficient planning, reduced vegetation cover, and increased pollution from factories and vehicles. One such primary concern is increased land surface temperature (LST) contributes to the urban heat island (UHI) occurrence. This research aims to understand better the UHI effect in the region neighbouring the Indian city of Ahmedabad. MODIS sensor data (onboard Aqua and Terra platforms) and Landsat data were used for the study. The research was done for the summer, monsoon, and winter seasons in the research region, using data from thirteen years between 2003 and 2015. The current study looked at LSTs' spatial and temporal differences to assess the SUHI effect over Ahmedabad city. The association between diurnal LST and various surface variables such as vegetation, built-up, soil, water, and so on has also been examined. A variety of land surfaces influences the diurnal variations of LSTs. The diurnal associations of LST with vegetation, urbanization, soil, and water factors have been studied. The overall study of LST' relationship with all of the various parameters reveals a very significant dynamic relationship. 2022 The Author(s) -
Investigating the Determinants of Financial Well-Being: A SEM Approach
Studies reveal that the financial well-being of employees has a direct bearing on their productivity and overall well-being. The wellness initiatives organized by the information technology (IT) companies operating in India have also started focusing on the contributing aspects of financial well-being. In this context, the article explores the determinants of financial well-being of IT professionals in India. The article utilizes confirmatory factor analysis (CFA) for the analysis. The study employs a survey questionnaire covering financial literacy, financial behavior, and financial fragility. It also attempts to recognize the influence of gender and job roles (technical or managerial) in ascertaining financial well-being. The sample data used in the study include 237 professionals employed in the IT sector. The study uses partial least squared structured equation modelling (PLS-SEM) to understand the connection between the determining factors. The results indicate that financial well-being is positively influenced by financial literacy and financial behavior while financial fragility has a substantial negative impact. The financial literacy and financial fragility are significantly different between technical and managerial roles. Gender appears to have a sizeable impact on the financial behavior and financial fragility levelswomen employees performed better in both the factors. Interestingly, financial literacy levels of the two genders are not significantly different. The results show that there is a need to focus on literacy, behavior, and fragility in financial wellness programs organized by the IT industry. Further, the study recommends offering tailored financial wellness training modules created based on the job levels and gender instead of following one program, fits all standardized approach. 2023 KJ Somaiya Institute of Management. -
Investigating the Dynamic Interlinkages between Exchange Rates and the NSE NIFTY Index
This study aims at examining the short-run and long-run dynamic linkages among exchange rates and stock market index in India through a structured cointegration and Granger causality tests. Daily exchange rates of USD, EUR, CNY, JPY, and GBP to INR along with the daily movement of NSE NIFTY for a period spanning 13 years from 6 September 2005 to 31 December 2018 were used for the analysis. The results reveal that there is no evidence for a stable long-run relationship between NSE NIFTY and the exchange rates under study. However, the VAR-based Granger causality test shows that USD, JPY, and CNY have short-run causal relationship with NSE NIFTY. The NSE NIFTY also seemed to have an influence on USD expressed in terms of Indian rupee. The impulse response analysis further supports the results of the Granger causality test and provides information on the time required for the NSE NIFTY index to recover from a shock caused by the fluctuation in exchange rates. 2021 by the authors. -
Investigating the dynamics, synchronization and control of chaos within a transformed fractional SamardzijaGreller framework
In this article, in response to the limitations of existing ecological models, we address the critical need for a more comprehensive understanding of predatorprey dynamics by presenting a modified fractional SamardzijaGreller model that incorporates intra- and inter-species competitions within two predator populations. Our model stands out for being more realistic because it considers the natural competition that occurs among and between two predator species when they share a common prey We derived the local stability conditions at equilibrium points using RouthHurwitz conditions for the modified model. With the help of a suitably chosen Lyapunov function, we also obtained the global stability condition for our fractional model. The existence of chaos has been confirmed through Lyapunov exponents and bifurcation in the new system for two distinct sets of initial conditions for different fractional orders. Employing the active control method, we establish conditions for synchronization between these two fractional systems and introduce control functions for chaos management in the modified model. Numerical simulations, utilizing the generalized AdamsBashforthMoulton method, support the theoretical findings across a spectrum of fractional orders ranging from 0 to 1. We demonstrated the adaptability of the active control method for different fractional orders. A fractional order of ? equal to 1 for synchronization shows rapid convergence, but a drop to ? equal to 0.80 causes a substantial slowdown that takes almost six times more number of iterations to complete. Thus, we shed light on how the fractional order of the system plays a pivotal role in determining the speed of synchronization, with lower orders leading to a noticeable delay and higher fractional orders favoring faster synchronization. Our thorough investigation contributes to the understanding of complex ecological systems and offers practical insights into fractional chaos control mechanisms within the context of predatorprey models. 2024 Elsevier Ltd -
Investigating the Electrochemical Behavior of Flowerlike-Co-Pi-Decorated Ti3C2TxMXene for Cathodic CO2Utilization: A Sustainable Approach
The rising CO2 concentration in the atmosphere has sparked the need for research communities and industries to shift toward embracing technologies prioritizing CO2 conversion and utilization. This research presents the fabrication of flowerlike cobalt-inorganic phosphate-decorated Ti3C2Tx MXene-modified carbon fiber paper (Co-Pi/Ti3C2Tx/CFP) electrode for electrochemical CO2 fixation via benzyl chloride transformation to produce industrially and pharmaceutically important phenylacetic acid (PAA). The multilayered Ti3C2Tx, having a large specific surface area, functions as the nucleation centers for the deposition of Co-Pi and enhances its physical, chemical, and electron transmission attributes. The Co-Pi anchored to Ti3C2Tx in turn modifies the interlayer properties of MXene, prevents restacking of the layered MXene structure, provides additional electrocatalytic sites, and escalates the electrocatalytic efficiency. Cyclic voltammetry and potentiostatic electrolysis studies revealed a higher current response, lower reduction potential, and increased productivity at the Co-Pi/Ti3C2Tx/CFP electrode for benzyl chloride transformation with CO2 coupling, yielding the desired carboxylic acid. Under optimal conditions, potentiostatic electrolysis at ?1.6 V for 8 h yielded up to 62% PAA, following a diffusion-controlled two-electron reduction mechanism. Furthermore, the electrodes showed good repeatability, reproducibility of electrochemical responses, and excellent stability over 60 days. 2025 American Chemical Society