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FACTORS AFFECTING ORGANIC FARMING CULTIVATION AND THEIR ROLE IN ACHIEVING SUSTAINABLE DEVELOPMENT GOALS (SDG)
Objectives: The paper aims to explore the factors which influence the organic farming cultivation in India and how they lead towards attainment of SDG. Theoretical Framework: This paper has adopted Theory of Planned Behavior to identify the factors which influence the organic farming and define their relationship with SDG. Method: The paper attempts to explore the factors which influence the organic farming intention among the farmers. It further explores the relationship between intention for organic farming and adoption of organic farming. The data was captured through detailed questionnaire which was captured through 347 respondents. The data analysis was performed with the help of SPSS 29 and AMOS 29 The mediating role of motivation was also explored using process Macro 4.2. Results & Discussions: The findings revealed that environment and cost influence the organic farming intention while attitude and perception had no effect on organic farming intention. Adoption of organic farming shared a positive relationship with organic farming intention The Cultivation of organic products lead to attainment of following goals No Poverty (SDG 1), zero Hunger (SDG2), Good Health and Well Being (SDG3) and Responsible Consumption and Production (SDG 12). Research Implications: The study reveals that there is a need to raise the awareness level among the farmers regarding the role of organic farming, its environmental impacts and health benefits associated with it. The findings underscore the importance of implementing additional training and awareness programs targeted at novice and less-experienced farmers. Such initiatives aim to familiarize them with diverse aspects of marketing, economics, and social factors associated with organic farming. 2025, Editora Alumni In. All rights reserved. -
From physical to digital: what drives generation Z for mobile commerce adoption?
Purpose: This study aims to identify factors affecting generation Z as the early adopters of mobile commerce (m-commerce). The research seeks to explore their behavioral intention to adopt m-commerce in India with consideration of gender differences while providing empirical validation for the theory of planned behavior (TPB). Design/methodology/approach: In this study, a modified TPB model has been used to explain generation Zs intention to adopt m-commerce. The proposed model was tested using a survey method with a sample of 245 students from a private university in Northern India. Subgroup analysis was performed to find gender differences in the process of adopting m-commerce. Findings: All three independent constructs have a positive influence on the behavioral intention of generation Z to adopt m-commerce. Further, the male subgroup has a lower beta value for attitude and higher beta value for subjective norm in comparison to the female subgroup. For perceived behavioral control, no significant difference in beta value across gender could be established. Practical implications: A better understanding of generation Z behavioral intentions will be of great use to telecom companies, marketers and electronic commerce companies to formulate strategies to expedite the use of m-commerce. As gender plays an important role in attitude and subjective norms, companies are advised to target their communication tactics in accordance to gender. Originality/value: To the best of the authors knowledge, this study is one of the first to test TPB and generation Z association in the context of m-commerce adoption in India. Data regarding the difference between the two genders has also shed light on the uniqueness of the context. 2021, Emerald Publishing Limited. -
Investigation of Spectroscopic Parameters and Trap Parameters of Eu3+-Activated Y2SiO5 Phosphors for Display and Dosimetry Applications
Using the solid-state reaction technique, varied Y2SiO5 phosphors activated by europium (Eu3+) ions at varied concentrations were made at calcination temperatures of 1000 C and 1250 C during sintering in an air environment. The XRD technique identified the monoclinic structure, and the FTIR technique was used to analyze the generated phosphors. Photoluminescence emission and excitation patterns were measured using varying concentrations of Eu3+ ions. The optimal strength was observed at a 2.0 mol% concentration. Emission peaks were detected at 582 nm and 589 nm for the 5D0?7F1 transition and at 601 nm, 613 nm, and 632 nm for the 5D0?7F2 transition under 263 nm excitation. Because Eu3+ is naturally bright, these emission peaks show how ions change from one excited state to another. This makes them useful for making phosphors that emit red light for use in optoelectronics and flexible displays. Based on the computed (1931 CIE) chromaticity coordinates for the photoluminescence emission spectra, it was determined that the produced phosphor may be used in light-emitting diodes. The TL glow curve was examined for various doping ion concentrations and durations of UV exposure levels, revealing a broad peak at 183 C. Using computerized glow curve deconvolution (CGCD), we calculated the kinetic parameters. 2024 by the authors. -
Does Google Trend Affect Cryptocurrency? An Application of Panel Data Approach
Cryptocurrency has emerged globally as the most profitable investment asset of the decade. The media exposure and reportage on cryptocurrency are frequent, and it seems that prices of cryptocurrencies could only rise higher. In today's digital world, any individual's first go-to information-seeking platform is the Google search engine. Thus, it is imperative to understand how Google's search trend affects an investable asset and its market as a whole. Researchers have explored varied sentiment measurement proxies such as news coverage, Facebook and Twitter posts, and, most importantly, Google searches. Numerous research studies show increasing interest in Google search volume and its predictive ability to understand investment returns and economic outcomes. In a behavioural finance context, the present research uses Pearson's correlation and panel regression to examine the association of cryptocurrency returns (Bitcoin, Ethereum, and Ripple) and their varied characteristics with the Google search intensity. The study's findings reveal that investors searching for information on Cryptocurrency online drive the price increase in cryptocurrency and push the trading volume up and increase the volatility of the cryptocurrency returns. Furthermore, investor sentiment has a statistically significant impact on cryptocurrencies' trading volume and weekly volatility in periods of high or greedy investor sentiment. The findings imply that the 'price pressure hypothesis' given by Barber and Odean (2008) as a stock market research finding is also present in the cryptocurrency market. 2023 SCMS Group of Educational Institutions. All rights reserved. -
Cryptocurrency Market Anomaly: The Day-of-the-Week-Effect
Cryptocurrency has emerged as a fad amongst investors, academicians and policy-makers as a financial asset, making it important to empirically test the price behaviour of this emerging market. This paper is designed to investigate the presence of a well-known day-of-the-week effect in the young and emerging cryptocurrency market returns from August 2015 to March 2019. Using varied statistical techniques, this anomaly is examined for six cryptocurrencies (Bitcoin, Ethereum, Ripple, Litecoin, Stellar and Tether). The study applies both parametric and non-parametric statistical tests, i.e.,Bar Graph, Heat map, Students t-test, Analysis of Variance (ANOVA),regression analysis with dummy variables and the Kruskal Wallis Test. The studys findings show that no sample cryptocurrency returns exhibit the day-of-the-week effect phenomenon.The statistically insignificant result of the day-of-the-week effect in thecryptocurrency returns showcases the evidence of market efficiency in the cryptocurrency market. Indian Institute of Finance. -
Two-dimensional Ti3C2Tx MXenes as a catalyst support for the synthesis of 1,4-disubstituted-1,2,3-triazoles via azide-nitroalkene oxidative cycloaddition
Two-dimensional transition metal carbides/nitrides: MXenes have become a prime choice for researchers to exploit their outstanding properties for various applications in different fields majorly including energy, health and environment. Interestingly, there are no reports of utilizing 2D materials especially MXenes as a catalyst support for organic transformations. In the present study, we have utilized 2D Ti3C2Tx MXenes as a catalyst support for the synthesis of 1,4-disubstituted-1,2,3-triazoles via azide-nitroalkene cycloaddition for the first time. Reusability of Ti3C2Tx MXene catalyst up to five cycles without the loss of catalytic activity with appreciable yields of the product is the noteworthy feature of the present protocol. The synthesized 1,2,3-triazole derivatives possessing long alkyl chain upto fourteen carbon atoms on terminal nitrogen in triazole ring could become a good precursors to give a liquid crystalline properties beyond its biological properties. Nontoxic catalyst, catalyst reusability, broad substrate scope, and good yield are some of the salient features of the present protocol. 2023 Elsevier B.V. -
Optimized Multi-Scale Attention Convolutional Neural Network for Micro-Grid Energy Management System Employing in Internet of Things
The combination of micro-grid energy management systems (EMSs) with the Internet of Things (IoT) offers a promising way to improve energy use and distribution. However, challenges such as device compatibility and the difficulty of managing energy efficiently make it hard to implement these systems effectively. This study offers a significant advancement in energy management by using IoT for microgrid systems. An Optimized Multi-scale Attention Convolutional Neural Network for microgrid EMS employing IoT (OMACNN-MGEMS-IoT) is proposed in this study, which enables efficient monitoring and control of energy resources. The proposed model's input data are gathered from the MQTT dataset. This research employs a Regularized Bias-aware Ensemble Kalman Filter (RBAEKF) for pre-processing input data, ensuring the removal of outliers and updating missing values. The MACNN is then used for effective fault detection within the microgrid. To enhance its performance, the Sheep Flock Optimization Algorithm (SFOA) is introduced to optimize the MACNN parameters, ensuring accurate fault detection. Implemented on the MATLAB platform, the performance of the OMACNN-MGEMS-IoT method is assessed through various performance metrics, demonstrating significant improvements. Notably, the proposed method achieves higher cost reductions of 25%, 22%, and 26% compared to existing approaches such as the IoT platform for energy management in multi-micro grid systems (IoT-PEM-MMS), a micro-grid system infrastructure implementing IoT for efficient energy management in buildings (MSII-IoT-EEM) and a hybrid deep learning-based online energy management scheme for industrial microgrids (HDL-OEM-IM). The findings highlight the impact of the proposed OMACNN-MGEMS-IoT method in enhancing energy efficiency and cost-effectiveness in microgrid systems. 2025 John Wiley & Sons Ltd. -
Impact of the Pandemic on Entrepreneurial Ecosystems
Entrepreneurship is crucial for the global economy, as it helps ideas develop from the drawing board to an executable stage. An excellent economic state of a country is the outcome of a well-designed system where the stakeholders interact with each other towards innovation and social development. This study is an empirical investigation into the COVID pandemic and its effects on the Indian entrepreneurial eco-system. Primary data was collected from 155 entrepreneurs of India, who were independent and first movers of entrepreneurs in their family during COVID times. Poor planning, exhausting resources, a slowdown in productivity, lower employment, and employee retention were the after-effects of the pandemic. It was found that the pandemic negatively affected the entrepreneurial ecosystem and its stakeholders. However, constant support by the government and well-designed policy measures would help assist existing businesses affected due to COVID-19 and encourage the entrepreneurial future in India. Copyright 2022, IGI Global. -
Security analysis in multi-tenant cloud computing healthcare system
Cloud Computing is an innovation in the field of Information Technology and in healthcare system because of the deployment models which services as profitability for the tenants. Cloud Computing is cost-effective, flexible and a delivery platform which provides business and services over internet. Multi-tenancy with its hardware sharing and high degree of configurability is utilized in cloud computing health care system even though many health care organizations are unwilling to adapt due to infrastructure and security shortcoming. In order to store the sensitive health care data cloud service providers should include promising security features where both the trusted and untrusted parties should be addressed in it. This paper addresses the security requirements and security issues in multi-tenant healthcare system, a frame is proposed for analyzing the security issues based on the available requirements and possible counter measures been suggested. The security concerns are analyzed by trust, confidentiality, integrity, audit and compliances and furthermore insight for the security is provided in multi cloud with possible security recommended for healthcare system. IAEME Publication. -
Teacher-Trainess Attitude Towards ICT
Journal of Education and Practice, Vol-4 (19), pp. 18-21. ISSN-2222-1735 -
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. -
From a recession to the COVID-19 pandemic: Inflation-unemployment comparison between the UK and India
The recession in India and the UK peaked in 2017 due to the implications of new policy initiatives. The outbreak of the COVID-19 pandemic at the beginning of 2020 intensified the crisis, causing a drastic decline in aggregate demand and output. India and the UK have resorted to monetary and fiscal stimulus packages to face the economic crisis. This study investigated the inflation-unemployment dynamics during the recession and COVID-19 times in India and the UK. Using a generalized additive model (GAM), the results of this study revealed that the recession had given way to stagflation in India. In contrast, in the UK, it has led to a more severe recession in the short-run. During the downturn, policy initiatives aggravate the recession and eventually turn to stagflation in India due to inflation caused by the weak supply side. However, in the UK, the policy initiatives during this downturn pushed the economy into a deeper recession due to reduced demand. The outbreak of the COVID-19 pandemic has had a similar recessionary impact on both economies. A time horizon based recovery plan is suggested to help the economies recover from stagflation and even deeper recession. This framework could enable policymakers to choose the right path of recovery within the shortest possible time. 2021 by the author. Licensee MDPI, Basel, Switzerland. -
Nudges and choice architecture in public policy: A bibliometric analysis
In recent years, nudges and choice architecture have gained significant attention amongst researchers, particularly in the domain of public policymaking. This study contributes to the existing literature on the application of nudges and choice architecture in public policy through a bibliometric analysis. A total of 419 documents from the Web of Science database from 2010 to 2021 were analysed, identifying the most prolific authors, foundational works, and sources, along with primary research themes. The study identifies keywords and themes that shape the current research trends and visualizes the intellectual structure of empirical works. The findings show an increasing focus on this subject area over the past decade, with a growing interest in themes such as dietary habits, healthcare, effectiveness of behavioral interventions, and sustainable choices. The application of nudges and choice architecture in policies related to health, food consumption, and diet management has also become increasingly prevalent as evidenced by the exponential growth in publications on these topics. 2023 Elsevier Inc. -
Consumer response towards personalised pricing strategies in online marketing
E-tailers are now capable of customising prices for an individual buyer or a group of buyers who exhibit similar behavioural traits and perceived ability to pay. Tailoring prices based on personal information may evoke unanticipated reactions as it could infringe users privacy and hurt fair price perceptions. To investigate the potential impact of positive and negative online personalised pricing situations, this study conducted a controlled experiment to observe the changes in consumer behaviour in a personalised pricing context. Seven hundred and twenty responses were collected from thriving online-active communities in India and Malaysia, both countries with high growth of e-commerce activities. Consumers reaction towards fair price, customer loyalty, privacy concern, purchase satisfaction; and the influence of these constructs on post purchase behaviours such as repurchase intentions, revenge intentions and strategic purchase intentions were analysed using PLS SEM modelling. Results indicate online consumers in both countries have high privacy concerns, and as it increased, their repurchase intentions decreased correspondingly. Strategic purchase intentions and revenge intentions increased regardless of positive and negative purchase situations, while purchase satisfaction mediates fair price perceptions and repurchase intentions. Copyright 2021 Inderscience Enterprises Ltd. -
An approach to develop content based video modules /
Researchers World Journal Of Arts Science And Commerce, Vol.7, Issue 1, pp.101-104, ISSN: 2231-4172. -
Exploring the effect of Covid-19 on herding in Asian financial markets
We examine herding behavior before, during, and after the Covid-19 pandemic in eight prominent Asian stock markets. Daily stock returns for the period Jan- 2018 to July- 2022 in the markets were investigated using the models prescribed by Chang et al., (2000) and Chiang and Zheng (2010). The empirical results provide strong support to earlier studies by providing robust evidence of herding in Vietnam, Indonesia, India, South Korea, and Singapore when the market is bullish and Indonesia and Vietnam also exhibit herding when the market is bearish. Herding tendency is dominant for Vietnam, India, and Indonesia during the pandemic with the post-pandemic time being more potent for China and Vietnam. Notably, an anti-herding tendency is found in China, Hong Kong, and Singapore. As a policy measure, efficient information dissemination, deterrence of insider trading, and regulation of mispricing can be undertaken. 2022 -
An Empirical Analysis of Factors and Variables Influencing Internet Banking among Bangalore Customers
International Journal of Research in Computer Application & Management, Vol. 2, Issue 10, pp. 143-148, ISSN No. 2231-1009 -
N-rGO/NiCo2O4 nanocomposite for high performance supercapacitor applications
Spinel structured transition metals oxide GO/NiCo2O4 nanocomposites and nitrogen doped N-rGO/NiCo2O4 nanocomposites were developed. Powder X-ray diffraction investigations confirmed the structure. The bonding vibrations of the produced nanocomposites were confirmed using infrared and Raman spectroscopy. EDX analysis was used to determine the composition and element weights of the nanocomposites. The electrochemical properties of the nanomaterials were measured using 1M KOH electrolyte. At 5mVs?1 scan rates, cyclic voltammetry revealed a specific capacitance (Csp) of 1078.2 Fg?1 for N-rGO/NiCo2O4. The bare and nanocomposites of NiCo2O4, GO/NiCo2O4, and N-rGO/NiCo2O4 specific capacitance, charge-discharge capability, and cyclic stability were investigated. Energy density and power density of the N-rGO/NiCo2O4 nanocomposite were estimated to be 20.4 Wh kg?1 and 1300W kg?1, respectively. N-rGO//N-rGO/NiCo2O4 asymmetric supercapacitor device with Ed of 14.9 Wh kg?1 and Pd of 3500W kg?1 was fabricated. 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
Effects of nitrogen, sulphur, and temperature treatments on the spectral, structural, and electrochemical characteristics of graphene oxide for energy storage applications
The structural and surface modifications have been studied on the hydrothermally Nitrogen (N) and Sulphur (S) doped and thermally reduced at 350 C nitrogen-doped, nitrogen-sulfur-doped graphene oxides. Raman spectra confirmed the reduction of graphene oxides by shifts in position and intensity variations of the D and G bands. EDX and mapping images revealed the carbon-oxygen ratio as well as the doping of nitrogen and sulphur into two-dimensional graphene oxide. The electrochemical properties of undoped and doped graphene oxides were investigated using a three-electrode system using a 1 M KOH electrolyte. It shows how doping, and reduction improve current conduction in graphene oxides. The specific capacitance of N,S-rGO after being synthesized and reduced at 350C was 930 Fg?1 and 1059 Fg?1, respectively, according to cyclic voltammetry results. The N-rGO specific capacitance was found to be similar, with 850 Fg?1 and 891 Fg?1, respectively, for the as prepared and reduced at 350C. The charge-discharge analysis, cycle stability, and impedances for the applied frequency ranges of undoped and doped graphene oxides for energy storage applications have all been estimated and discussed. 2023