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Barriers to Smart Home Technologies in India
Smart home technologies (SHT) are critical for effectively managing homes in a digital society. However, SHTs face challenges related to their limited use in developing country contexts. This study investigates the factors that act as barriers to SHT adoption among individuals in Bengaluru, India. The roles of perceived risk, performance and after-sale service, and demographics in using smart home technologies (SHT). This study used the data from the primary survey of 133 respondents. The collected data were analyzed using regression analysis. The results supported five of the proposed hypotheses, namely, perceived performance risk, perceived financial risk, perceived psychological risk, and technological uncertainty, which influence the Behavioral intention to adopt SHT. However, service intangibility is influenced by performance risk. Income and age influence the psychological risk and adoption of SHT. The study identifies the barriers to SHT adoption. The supportive environment for SHT needs to be strengthened to reduce the associated risks. IFIP International Federation for Information Processing 2024. -
Barriers to Green Supply Chain Management in the Construction IndustryA Systematic Review
The construction industry is project-based and requires the cooperation of several stakeholders, mainly architects, contractors, and suppliers, to ensure that materials, finance and information move through the construction supply chain with minimal hurdles. The fragmented nature of the industry creates obstacles to integrating green practices into the supply chain to reduce the industrys negative environmental effects. This study aims to review the literature on barriers to adopting green supply chain management practices in the construction industry, pinpoint research gaps and suggest directions for further research in the domain. The articles for the literature review were retrieved from the Scopus database from 2014 to 2024. The search was refined using PRISMA guidelines. 18 relevant empirical studies were reviewed for this purpose. The findings reveal that the major impediments were high costs of implementing green practices across different phases, namely, the design procurement, construction, operation and demolition phases, inadequate knowledge and awareness of green procurement, design and construction, insufficient technical expertise, lack of government incentives for adopting green practices, lack of availability of green building materials and technologies, lack of top management commitment and inadequate policies and regulations on green construction. Extant literature indicates that past studies have examined the most significant barriers in developed and developing countries, mostly using quantitative surveys. It is suggested that future researchers conduct an in-depth analysis of the barriers in different contexts by gathering qualitative data from the construction industry stakeholders. This would support the creation of policies and strategies by practitioners and policymakers to address the issues of incorporating environmental concerns into the building supply chain. It will, therefore, encourage the sector to strive for environmental sustainability. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
Barriers to corporate social responsibility implementation in the medium size manufacturing sector: an interpretive structure modelling approach
Purpose: Corporate social responsibility (CSR) practices are gaining momentum globally but their implementation becomes problematic due to the presence of barriers. So, this study aims to identify the barriers to CSR implementation among manufacturing enterprises, develop their classification and establish relationships among the barriers. Design/methodology/approach: An exhaustive list of barriers was identified from the literature, and following surveys and expert opinions, 19 critical barriers were extracted. Interpretive structure modelling was used to understand the hierarchal and contextual relationships among barriers of CSR implementation. Findings: The results show that are no autonomous variables present in the study. The proposed conceptual framework presents the hierarchy and interlinkage of barriers to CSR implementation in manufacturing enterprises. The results also indicate that rigidity in culture and corruption in the system and within the governance system of the country are the two most influential barriers that impede CSR implementation in manufacturing enterprises. Originality/value: The interactions among CSR barriers provide policymakers, industrial practitioners and managers with a framework to recognise and evaluate mutual relationships and interlinking among barriers. CSR training and undertaking CSR in collaboration can help medium enterprises overcome these barriers and prepare strategies to mitigate their impact. 2021, Emerald Publishing Limited. -
Barriers to career advancement of women chefs leading to their poor visibility in hotel industry: A study with special reference to Bengaluru /
Asian Journal of Managerial Science, Vol.7, Issue 2, pp.34-36, ISSN No: 2249-6300. -
Barriers hindering digital transformation in SMEs
The chapter aims to find interdependencies between barriers that hinder adoption of digital transformation technologies in small and medium firms. Barriers were identified using an extensive literature review and finalized after consulting an expert panel. Next, a pairwise questionnaire was developed, and responses from essential stakeholders working with small and medium firms were collected. Data were analyzed using the DEMATEL technique. Salient challenges for implementing digital transformation technologies were identified, and the cause-and-effect relationship between the barriers was established. Lack of proper digital vision and strategy was identified as the most critical barrier that hinders adoption of digital transformation technologies in small and medium firms. Digital technologies help to improve the efficiency of the firms and improve resource utilization by facilitating timely and accurate decision making. Hence, overcoming the identified challenges in transformation will improve the operations of the production system and organizational process. 2024, IGI Global. All rights reserved. -
Bardic Destinies: A Comparative Study of European Poetic and Indian Kavya-Itihasa Tradition
This volume critically explores the cultural significance and fate of the literary in the European and the Indian traditions as it traces the history of the reception of works that have had a deep hold on the lives and sensibilities of people across time and cultures. The book grapples with three major concepts in the humanitiesthe literary, the philosophical/theological and the historical. It looks at Homers reception by Plato; Virgils reception by Christianity; the many responses that The Mahabharata has received over centuries and across cultures in India; and the reception of Kumaravyasas Kumaravyasabharata, among other works, and analyses the understanding of truth, time and history that influence the reading of these works in different times and cultural contexts. Part of the Critical Humanities across Cultures series, this book will be useful for scholars and researchers of philosophy, literature, history, comparative literature, cultural studies and post-colonial studies. 2024 Krishna Kanchith R. -
Bard-Taylor ferroconvection with time-dependent sinusoidal boundary temperatures
The combined effect of centrifugal acceleration and time-varying boundary temperatures on the onset of convective instability of a rotating magnetic fluid layer is investigated by means of the regular perturbation method. A perturbation expansion in terms of the amplitude of applied temperature field is implemented to effectively deal with the effects of temperature modulation. The criterion for the threshold is established based on the condition of stationary instability manifesting prior to oscillatory convection. The modulated critical Rayleigh number is computed in terms of Prandtl number, magnetic parameters, Taylor number and the frequency of thermal modulation. It is shown that subcritical motion exists only for symmetric excitation and the destabilizing effect of magnetic mechanism is perceived only for asymmetric and bottom wall excitations. It is also delineated that, for bottom wall modulation, rotation tends to stabilize the system at low frequencies and the opposite is true for moderate and large frequencies. Furthermore, it is established that, notwithstanding the type of thermal excitation, the modulation mechanism attenuates the influences of both magnetic stresses and rotation for moderate and large frequencies. Published under licence by IOP Publishing Ltd. -
Barbell-shaped giant radio galaxy with ? 100 kpc kink in the jet
We present for the first time a study of peculiar giant radio galaxy (GRG) J223301+131502 using deep multi-frequency radio observations from GMRT (323, 612, and 1300 MHz) and LOFAR (144 MHz) along with optical spectroscopic observations with the WHT 4.2m optical telescope. Our observations have firmly established its redshift of 0.09956 and unveiled its exceptional jet structure extending more than ? 200 kpc leading to a peculiar kink structure of ? 100 kpc. We measure the overall size of this GRG to be ? 1.83 Mpc; it exhibits lobes without any prominent hotspots and closely resembles a barbell. Our deep low-frequency radio maps clearly reveal the steep-spectrum diffuse emission from the lobes of the GRG. The magnetic field strength of ? 5 ?G and spectral ages between about 110 to 200 mega years for the radio lobes were estimated using radio data from LOFAR 144 MHz observations and GMRT 323 and 612 MHz observations. We discuss the possible causes leading to the formation of the observed kink feature for the GRG, which include precession of the jet axis, development of instabilities and magnetic reconnection. Despite its enormous size, the Barbell GRG is found to be residing in a low-mass (M200 ? 1014 M) galaxy cluster. This GRG with two-sided large-scale jets with a kink and diffuse outer lobes residing in a cluster environment, provides an opportunity to explore the structure and growth of GRGs in different environments. 2022 EDP Sciences. All rights reserved. -
Banking System and Financial Inclusion Process in India: Issues and Perspectives
PSNA Journal of Business and System, Vol-3 (1), pp. 74-83. ISSN-2319-2909 -
Banking Dynamics and Economic Growth in India: Unveiling the Interplay of Key Performance Indicators
Purpose: This study aimed to analyze the influence of bank performance on economic growth. We proposed a framework of banking variables to gain a holistic picture. Design/Methodology/Approach: To identify the causal relationship, we ran cointegration tests and vector autoregression (VAR). In addition, we used the impulse response function test. This helped in analyzing the response of GDP growth to banking shocks. Findings: We identified that banking variables like domestic credit (DC), return on equity, and capital adequacy ratio can stimulate economic growth. Long-term and short-term influence of banking performance on economic growth. Improved performance of banks can translate to economic growth. Our results also indicated that well-capitalized banking, high return on equity, and increased credit access were critical drivers of GDP growth. Practical Implications: This research offered important insights into the role of banking performance in influencing economic growth. We recommended that policymakers implement measures to improve capital adequacy, enhance profitability, and increase credit flow for sustained economic success and development. Originality/Value: This study added to existing research by examining how banking performance influenced economic growth in a developing context. Unlike prior studies that focused mainly on advanced economies, our analysis centered on India, offering evidence from an emerging financial system and providing context-specific insights. 2025, Associated Management Consultants Pvt. Ltd. All rights reserved. -
Banana peels as a cost effective substrate for fungal chitosan synthesis: optimisation and characterisation
Massive accumulation of unprocessed banana peels enthralls sustainable issues as they are eventually dumped as landfills leading to emission of obnoxious gasses. To avoid these persisting challenges the present study shims lights on chitosan production from the characterised fungal strain using banana peel hydrolysate as an effective medium. Substantial amount of carbohydrate in banana peels serves as a potential solution for fungal chitosan production in a view to attain a circular bioeconomy and repurposed for synthesis of beneficial products in a cost effective manner. Presence of fermentable sugars in banana peels qualifies them as a feasible substrate which could be exploited for scaling up of fungal chitosan synthesis. Screened isolate was subjected to statistical optimisation using formulated medium to elucidate the influential factors that had significant effect on chitosan production. The harvested chitosan biomass was characterised through standardised techniques and evaluated for further studies. Statistical optimisation reveals that ammonium nitrate (5 g/L), pH (6) and incubation time (144 hrs) were the three PBD variables that had a greater influence on fungal chitosan yield. The validated developed model exhibited maximum yield of 200 mg/L, a 4.4 fold increase than unoptimised medium (45 mg/L). These findings emphasise the fermentative synthesis of chitosan through valorisation of banana peel prop up a complementary approach in concomitant with preserving renewable resources and bioproduct formation. 2023 Informa UK Limited, trading as Taylor & Francis Group. -
Banana peels as a cost effective substrate for fungal chitosan synthesis: optimisation and characterisation
Massive accumulation of unprocessed banana peels enthralls sustainable issues as they are eventually dumped as landfills leading to emission of obnoxious gasses. To avoid these persisting challenges the present study shims lights on chitosan production from the characterised fungal strain using banana peel hydrolysate as an effective medium. Substantial amount of carbohydrate in banana peels serves as a potential solution for fungal chitosan production in a view to attain a circular bioeconomy and repurposed for synthesis of beneficial products in a cost effective manner. Presence of fermentable sugars in banana peels qualifies them as a feasible substrate which could be exploited for scaling up of fungal chitosan synthesis. Screened isolate was subjected to statistical optimisation using formulated medium to elucidate the influential factors that had significant effect on chitosan production. The harvested chitosan biomass was characterised through standardised techniques and evaluated for further studies. Statistical optimisation reveals that ammonium nitrate (5 g/L), pH (6) and incubation time (144 hrs) were the three PBD variables that had a greater influence on fungal chitosan yield. The validated developed model exhibited maximum yield of 200 mg/L, a 4.4 fold increase than unoptimised medium (45 mg/L). These findings emphasise the fermentative synthesis of chitosan through valorisation of banana peel prop up a complementary approach in concomitant with preserving renewable resources and bioproduct formation. 2023 Informa UK Limited, trading as Taylor & Francis Group. -
Banana bract derived cellulose coatings for enhancing shelf life of cherry tomatoes: Insights in to a sustainable post harvest technology
The increasing substantial generation of food waste poses a critical challenge for global waste management. A potential solution involves extracting commercially valuable products, such as biopolymers, from food waste. Cellulose biopolymer emerges as a promising candidate in this context. The current research investigates the potential of employing banana bracts (Musa acuminata) as a low-cost substrate for the extraction of cellulose biopolymer. Cellulose extraction from various residues of banana processing waste has been previously researched. However, there is a limited amount of the literature on cellulose extraction from the bracts that are left over after processing. The initial extraction phase involves an ethanol-toluene treatment to remove the laxatives, followed by an alkali treatment using KOH and bleaching using a mixture of acetic acid and sodium chlorite solution to derive white cellulose fibres. The extraction of cellulose from banana bracts yielded 36.98 0.0094% (w/w%). Examination of functional groups utilizing Fourier transform infrared provided characteristic peaks of cellulosic material. X-ray diffraction, thermogravimetric analysis, differential scanning calorimetry, and scanning electron microscopy were used to comprehend further the molecular architecture, thermal stability, and purity of the extracted cellulose. The cellulose mixture of varying concentrations (0.5, 0.75, and 1.0% [w/v%]) was coated on cherry tomatoes to investigate their shelf-life extension property. The cherry tomatoes (Solanum lycopersicum var. cerasiforme) coated with 0.75% (w/w%) cellulose solution retained firm structure and fresh appearance after 8days, in contrast with the decayed control group. The current investigation focuses on novel insights into the potential of banana bracts as a valuable resource in the pursuit of sustainable and cost-effective cellulose extraction, for both waste management and enhancing the preservation of perishable food items. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025. -
Ban or boon: Consumer attitude towards plastic bags ban
In Tamil Nadu, the state government has imposed a ban on plastic bags two years ago. This has created a major impact of the day to day life of common people. Though it has positive effect on the environment, the common public had different perception as a consumer. This paper aimed at studying the consumer attitude towards the ban on plastic bags. A descriptive research design adopted to address the various dimension of consumer perception towards the ban on plastic ban. A sample size of 400 respondents was selected on the basis of systematic random sampling technique to collect data through structured questionnaire. For conducting the survey, consumers of retail shops in urban and rural places were chosen as target respondents. The collected data were analyzed with the help of statistical tools such as ANOVA, t-Test, Correlation, Linear Regression and Structural equation modelling and the interpretation reported. The result revealed that only 34 percentage of respondent were aware the environmental impact of plastic bags. About 71 percentage of consumers reported that they have faced difficulties in their day to day life due to plastic ban. 2021 American Institute of Physics Inc.. All rights reserved. -
Bamboo Trade Dynamics: A Hybrid ARIMALSTM Forecasting Approach for Indias ExportImport Trends (20172025/26)
Bamboo plays a dual role in Indias economy, serving as both an ecological safeguard and a driver of rural livelihoods. This paper examines bamboo exportimport flows between 2017 and 2025/26 using official trade statistics. A hybrid ARIMALSTM forecasting model is implemented to capture both linear and nonlinear patterns. Results demonstrate rising exports, stable imports, and higher predictive accuracy compared to ARIMA alone, confirming bamboos growing role in sustainable trade. The Author(s), under exclusive license to Springer Nature Switzerland AG 2026. -
Balconing An Intersection of Morbidity and Language
[No abstract available] -
Balancing work and life inacademia: unraveling theemployee engagement mystery
Purpose: This study aims to further the understanding of employees engagement by explaining their organizational commitment through their perception of the availability of work-life benefits in the organization. This study also investigates the mediating role of job satisfaction in this context. Design/methodology/approach: The model was tested on the primary data collected in two phases from 270 teaching professionals in higher education institutes in Northern India. Barren and Kennys algorithm and hierarchical regression analysis were used to test the hypotheses. Findings: The results reveal that employees perception of work-life benefits strongly influences their organizational commitment. Also, the results support that employees job satisfaction mediates the above-mentioned relationship. Research limitations/implications: Self-reported data could be considered as a key limitation of this study and for more accurate results supervisors (line managers) perspective could also be included in future studies. Also, in addition to perceived work-life benefits, supervisors support could also have an impact on employees commitment, thus its inclusion in the model could draw a clearer picture. Originality/value: This research has two key contributions: first, it adds to the limited literature examining the employees engagement issues in the academic sector. Second, this research is one of, if not the first, to investigate perceived work-life benefits among third-level teaching staff in India to explain employees commitment to their organizations. 2024, Emerald Publishing Limited. -
Balancing the Cart: Evaluating Imbalance-Aware Machine-Learning Pipelines for Predicting E-Commerce Purchases
We present a comprehensive investigation into predicting purchase conversions in e-commerce sessions, addressing the challenges of severe class imbalance and complex user behavior signals. Using a real-world dataset of 12,330 user sessions described by 24 features (interaction counts, durations, bounce/exit rates, page values, temporal and device metadata), we first conduct exploratory analysis to reveal seasonal peaks in conversion and strong correlations between page value metrics and purchase likelihood. To mitigate the low positive-class rate (10.8%), we embed SMOTE oversampling within our training pipelines, ensuring balanced learning for all classifiers. We then perform a head-to-head comparison of twelve algorithmsranging from linear and generative methods (Logistic Regression, LDA, Gaussian NB), instance-based learners (KNN, SVM), bagging ensembles (Random Forest, Extra Trees, AdaBoost), gradient boosters (XGBoost, LightGBM, CatBoost), to a feed-forward neural network (MLP). Evaluation on a stratified 80/20 holdout set uses overall accuracy plus precision, recall, and F1-score for the purchase class, alongside ROC AUC. Our results demonstrate that ensemble tree methods dramatically outperform simpler models: LightGBM achieves the highest F1 (0.694) and ROC AUC (0.924), with Extra Trees closely following (F1 0.678, AUC 0.926). Simpler classifiers, despite SMOTE, lag markedly in recall and F1, underscoring the importance of powerful nonlinear learners. These findings establish a new benchmark for imbalance-aware conversion prediction and recommend SMOTE-augmented gradient boosting and randomized tree ensembles as the methods of choice for future research and practical deployments. 2025 IEEE. -
Balancing patient privacy and predictive accuracy through data anonymization in healthcare
Data anonymization in healthcare is essential for protecting sensitive patient information while enabling secure usage for research, analytics, and AI-driven clinical decision-making. In this study, the MIMIC-III - Deep Reinforcement Learning dataset was used, which contains comprehensive electronic health records (EHRs) of ICU patients. Data preprocessing was performed using Min-Max Normalization to scale numerical features and ensure consistency. Anonymization techniques such as pseudonymization, generalization, suppression, data masking, and statistical methods like k-anonymity, l-diversity, and t-closeness were applied to safeguard patient privacy. The anonymized dataset was then utilized for predictive modelling using AI techniques including Random Forest and LSTM. Results demonstrated that privacy was maintained with 0% PII leakage, while predictive accuracy remained high, achieving accuracy of 94.6%, precision of 93.8%, recall of 92.5%, and F1-score of 93.1%. This study highlights that effective data anonymization ensures compliance with HIPAA and GDPR while retaining the utility of healthcare data for advanced analytics and AI applications. 2026 Techno-Press -
Balancing module in evolutionary optimization and Deep Reinforcement Learning for multi-path selection in Software Defined Networks
Software Defined Network (SDN) has been used in many organizations due to its efficiency in transmission. Machine learning techniques have been applied in SDN to improve its efficiency in resource scheduling. The existing models in SDN have limitations of overfitting, local optima trap and lower efficiency in path selection. This study applied Balancing Module (BM)-Spider Monkey Optimization (SMO)-Crow Search Algorithm (CSA) for multi path selection in SDN to improve its efficiency. The balancing module applies Gaussian distribution to balance between exploration and exploitation in the multi-path selection process. The Balancing module helps to escape local optima trap and increases the convergence rate. Deep Reinforcement learning is applied for resource scheduling in SDN. The Deep reinforcement learning technique uses the reward function to improve the learning performance, and the BM-SMO-CSA technique has 30 J energy consumption, where the existing models: DRL has 40 J energy consumption, and Graph-ACO has 62 J energy consumption. 2022