Volume 13 | Issue 5 |

 Abstract

In the internet shopping scenario, buyer behaviour is affected by a plethora of factors, including buyer trust, privacy concerns and perceived risk. Online retail (e-retail) is quite evidently growing at a fast pace, and the degree of online purchase is humongous. However due to complex market scenario intense competition and ever-changing consumer dynamics, sustainability is sceptical. Hence e-tailers are extremely focused on the loyalty aspect of buyers. Thus, it is pivotal for marketers to identify those factors that foster e-retail patronage behaviour amongst online buyers, specifically generation Z. Demographically more than 50% of India's population is below the age of 25. Therefore, the study is focused on individuals belonging to that age group. The objective of this research is to explore those factors of an e-retail stores that are pivotal in developing a sense of loyalty among Generation Z consumers. This study explores the patronage behaviour of Generation Z consumers by focusing on three key variables: e-store atmospherics, e-service quality, and e-merchandise, in relation to their patronage intentions. Data was gathered through a structured questionnaire. The findings identified additional significant factors influencing patronage behaviour. The outcome revealed that e-merchandise showed a negative association with e-patronage intentions, whereas both e-service quality and e-store atmospherics were found to have a positive impact on Generation Z's online patronage behaviour.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Patronage Behaviour, Generation Z, E-retailers, e-store attributes, e-service, e-merchandize.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The primary responsibility of the State is to ensure the fair and impartial administration of justice, making it accessible to all citizens, irrespective of socio-economic status. In India, this responsibility is upheld through judicial independence, but procedural delays and jurisdictional limitations hinder timely access to justice. One key aspect of the judicial system, writ jurisdiction under Article 32 of the Indian Constitution, plays a crucial role in protecting citizens' fundamental rights, particularly against violations by the State. However, the current framework of writ jurisdiction faces significant barriers in terms of accessibility, particularly for marginalized communities. This research examines the challenges faced by Indian citizens due to the absence of writ jurisdiction at lower judicial levels, and the urgent need for the implementation of Article 32(3), which empowers Parliament to authorize other courts, such as High Courts, to issue writs. While Article 32 allows citizens to directly approach the Supreme Court for the enforcement of fundamental rights, its practical effectiveness is limited by factors such as legal illiteracy, financial constraints, and bureaucratic delays. These barriers disproportionately affect vulnerable populations, leaving them without effective legal recourse. The study critically analyzes the systemic issues in accessing justice, especially in rural and economically disadvantaged areas, and highlights how the lack of writ jurisdiction at lower levels exacerbates these challenges. The research proposes the expansion of writ jurisdiction under Article 32(3) as a solution to improve access to justice.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Access to Justice, Article. 32(3), Judicial Independence, Jurisdiction, Delay

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The study on customer satisfaction and service quality at Shri Bhakti Medical Agencies Pvt. Ltd. focuses on understanding how well the company meets the needs and expectations of its customers. Using surveys and feedback collection methods, the research identifies key factors influencing customer satisfaction, including timely delivery, product quality, communication, and customer support. The findings show that while the company has a strong foundation in delivering reliable products, there is room to enhance service efficiency and responsiveness. Based on the analysis, recommendations are made to further strengthen customer relationships and drive future growth. Through a structured survey approach, the study assesses the organization's performance across critical service quality dimensions. The analysis reveals a strong correlation between service responsiveness, reliability, and overall customer satisfaction. Areas for improvement, particularly in proactive communication and personalized services, are identified. Strategic recommendations are proposed to enhance service delivery, optimize customer experience, and ensure sustainable growth. The study emphasizes the need for customer-centric policies and training initiatives to improve service standards, aiming to foster stronger, long-term customer relationships.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Customer satisfaction, service quality, timely delivery, product reliability, communication, customer support, responsiveness, personalized service, customer experience, sustainable growth.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The study investigates the causes and impacts of job stress in construction workers, one of the most challenging industries because of unsafe working conditions, long working hours, illness, and intra-organizational conflict. The study used a mixed-method, Structural Equation Modeling (SEM) for examining relations between major stressors--risky work environment, overtime, health issues, and workplace conflicts--and Logistic Regression to categorize workers according to levels of stress. Information from 205 employees, comprising laborers, supervisors, and engineers, showed that workplace conflicts had the most significant positive effect on stress, and overtime, which was found to have a negative correlation, implying that paid overtime might reduce stress since it is voluntary and well-compensated which gives financial relief. Married and older employees were discovered to experience lower levels of stress. The results highlight the importance of managing workplace conflicts and improving employee well-being in the construction sector.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Job stress, Structural equation modelling, Logistic regression, Construction, Mixed method approach, workplace conflicts.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Introductions over the past few decades have experienced major changes in the way drug delivery is done, as nanotechnology plays a key role. The ability to manipulate nanoscalas (1-100 nm) materials has enabled the potential for targeting, regulation, and longer drug release. Systemic toxicity, fast metabolism and reduced solubility are some of the drawbacks of traditional drug taxes. The drugs are encapsulated, protected before they get worse, and can be delivered precisely to the intended location thanks to the airlines made possible by nanotechnology. The current developments in nanotechnology-based drug taxes and their impact on future healthcare are the focus of this article.

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 Keywords

Drug delivery systems, Nanocarriers, Targeted drug delivery, Nanoparticles, Liposomes, Bioavailability Enhancement, Smart Drug delivery, Future trends in nanomedicine

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The Smart Rainwater Harvesting System makes use of modern technology for capturing and collecting rainwater. The system leads to better and longer-term water management by incorporating IoT-based tools and interrogating domain-tested approaches. The system is operated by an Arduino Uno, which serves as the central processing unit of the system. The control unit connects to different functional sensors; ultrasonic sensors determine the level of the water in the tank, pH sensors determine if the water is safe, and rain sensors enable the system to be activated automatically when it is raining. The optimization of operations requires a minimum amount of manual work to be done. The system implements actuators and servo motors which automatically turn open and close valves. The components responsive to the sensors regulate the different actions wherein water can either be collected, filtered, stored, or sent to where it is required. The sensors transmit all the information to the cloud in a real-time-stream, enabling users to monitor the system with a mobile app from any place. Users can check the devices whether they are at home, at work, or on a trip, and they will be able to make the necessary modifications from their mobile devices. The simulations on Tinkercad provided adequate hope concerning the outcomes and as such, prototypes were built and tested. Testing proved that the system could autonomously collect water, check its quality, and manage its distribution in an efficient self-regulating manner. The system relies on solar power to further enhance sustainability. This feature eliminates dependence on the electric grid, making it very useful for remote locations with limited or no access to electricity. The SRHS has been tailored to be low-cost, with simple structural modifications, and considered 'green technology'. Whether deployed within residential units, commercial structures, or agricultural land, the invention provides an innovative solution aimed at mitigating the worrisome problem of water deficit on a global scale.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

IOT

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This study aims to explore the factors influencing employees investment decisions, With the growing importance of financial independence and investment planning, understanding the role of financial literacy, risk tolerance, and demographic factors in shaping investment behavior is crucial. A structured questionnaire was administered to 201 employees using simple random sampling. Both primary and secondary data were collected and analyzed using non-parametric tools (Kruskal-wallis H test, Mann-whitney and correlation). The findings reveal that financial literacy and risk tolerance significantly impact employees investment decisions, while demographic factors such as age, income, education, and marital status also play a critical role. The study concludes that higher financial literacy and risk-taking ability lead to more confident and diversified investment behaviors.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Financial literacy, Risk tolerance, Demographic factors, Non-parametric tools, Investment decision.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Geographic Information Systems (GIS) have transformed with the integration of data science, enabling advanced spatial analysis, predictive modeling, and decision-support across fields like urban planning, environmental science, and public health. This review explores how machine learning (ML), spatial statistics, and big data are revolutionizing GIS, covering foundational techniques such as supervised/unsupervised learning for geospatial pattern recognition (e.g., land cover classification using CNNs), spatial regression models (e.g., geographically weighted regression) for localized predictions, and graph-based analytics for network-constrained problems like traffic flow optimization. Real-world applications include precision agriculture through crop yield prediction using satellite imagery and IoT sensor fusion, disaster response with real-time flood mapping via social media geodata and hydrological models, and smart cities using ML-driven urban sprawl simulation and infrastructure planning. The paper also critically examines challenges like data heterogeneity, computational scalability, and ethical concerns (e.g., location privacy), and highlights emerging trends such as AI-powered GIS automation and the potential of quantum computing for spatial data, proposing future research directions.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Geographic Information Systems (GIS), Data Science, Spatial Machine Learning, Big Geospatial Data, Remote Sensing, Spatial Optimization, Urban Informatics, Environmental Modeling, Geoprivacy, AI-Driven GIS

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This project presents an integrated system combining computer vision, deep learning, and IoT-based V2V (Vehicle-to-Vehicle) communication to improve road safety and enable smarter transportation solutions. The system is developed in three main stages. First, a real-time lane detection module is implemented using Python and OpenCV. It employs image processing techniques such as color thresholding, edge detection, and Hough Transform to accurately identify lane boundaries from a live camera feed, enhancing driver assistance and road alignment. Second, object detection is performed using the YOLOv3 deep learning model, which identifies surrounding vehicles, pedestrians, and other road objects from real-time video frames. YOLO's high-speed and accurate detection capability makes it suitable for safety-critical environments. The model processes input frames, applies non-maximum suppression to eliminate duplicate detections, and marks detected objects with bounding boxes and labels. Third, the V2V communication system is developed using the ESP32 microcontroller and IoT platform Blynk. This system monitors temperature and collision status using a DHT11 sensor and digital input pin. When critical conditions such as engine overheating or accidents are detected, alerts are displayed on an LCD and transmitted to a mobile application via Wi-Fi, enabling remote awareness. All three components work together to provide a robust and real-time vehicle monitoring and safety system. This approach not only aids in lane discipline and object awareness but also ensures timely communication in emergencies. The integration of vision-based detection, AI models, and IoT connectivity forms a foundation for future autonomous and connected vehicle technologies.

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 Keywords

Vehicle Trajectory Prediction, Long Short-Term Memory (LSTM), Vehicle-to-Vehicle Communication (V2V), Deep Learning, Time Series Forecasting, Intelligent Transportation Systems (ITS), Autonomous Vehicles, Neural Networks, Real-time Prediction, Safety and Collision Avoidance.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This project focuses on developing an innovative solution to combat cryptographic ransomware using AI-driven Honeypots, BiLSTM (Bidirectional Long Short-Term Memory) model, and Format Preserving Encryption (FPE). The system autonomously detects and defends against ransomware attacks by analyzing behavior patterns, protecting critical data, and continuously adapting to new attack techniques.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Ransomware, Cryptographic ransomware, AI-Driven Honeypots, BiLSTM (Bidirectional Long Short-term Memory), Format Preserving Encryption (FPE), Behavior patterns.

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Creative Commons Attribution 4.0 and The Open Definition