Leading the Charge: A Guide to Management, Entrepreneurship and Technology in the Dynamic Business Landscape Edition 1
Human resource management involves a strategic and cohesive method to efficiently oversee personnel within a company or organization, aimed at enhancing their performance to contribute to the organization's competitive edge. Human Resources are crucial in any organisation, irrespective of sector. This study examines the impact of technology on Human Resources practices within the Micro, Small, and Medium Enterprises (MSMEs) sector. With the advent of digitalization, MSMEs are increasingly integrating technological solutions into their HR functions to streamline processes, enhance productivity, and improve employee engagement. The study highlights the transformative impact of technology on HR practices within MSMEs.
Human Resources (HR) is very important in any organisation irrespective of sector. The term HR is used because it recognises people as a crucial asset, akin to equipment or supplies, essential for businesses to fulfil their objectives. Among all the resources at their disposal, employees are typically regarded as the most invaluable. Technology is significantly shaping various aspects of modern life, and it has increased the use of tools for HR management. From recruitment to talent management, compliance, payroll, and performance management, basic HR functions are undergoing transformation thanks to technology. Furthermore, emerging technologies are expanding HR's role, focusing more on employee engagement and productivity. This study examines the impact of technology on Human Resources (HR) practices within the Micro, Small, and Medium Enterprises (MSMEs) sector. With the advent of digitalization, MSMEs are increasingly integrating technological solutions into their HR functions to streamline processes, enhance productivity, and improve employee engagement. A descriptive study is conducted on only the secondary data. This paper explores the various ways in which technology, such as HRIS (Human Resource Information Systems), AI (Artificial Intelligence), and data analytics, is reshaping recruitment, training, learning and development, performance management, and employee relations within MSMEs. Additionally, it investigates the challenges and opportunities associated with the adoption of technology in HR practices for MSMEs, considering factors such as cost, skill gaps, and organizational culture. The study highlights the transformative impact of technology on HR practices within MSMEs in Bengaluru.
Copyright (c) 2025 Author(s). The licensee is the publisher (BP International).
Operational Threats and Mitigation Strategies for Auto Component Manufacturers in the Digital Age
Purpose: The purpose of this paper is to have a deep understanding of threats during various operational phases. This paper provides an idea of various activities at different stages, where the identification of threats can be primary information before they occur during manufacturing operations. A proper action plan can be prepared and executed to handle various threats during operation and to achieve the goal of a successful manufacturer. Methodology: A study has been performed to identify the common threats in manufacturing operations. During the study, data was collected through various questionnaires and respondents were from automotive industries with experience from 5 to 20 years contributing in different phases of operation. Findings: During interaction with industrial leaders, it was found that 65% of participants expressed their concern related to the availability of technically skilled manpower and looking at technological enhancement like Industry 4.0, digitalisation etc to be considered as one of the major threats. During the survey, it was also a strong voice from 62% of participants that expectations from end users are changing very frequently which has been a major threat to placing ourselves in a competitive market. 50% of respondents from auto component manufacturers affirmed that the product life cycle of automotive manufacturing industries is getting reduced year by year which is a major threat considering huge investments for particular products and setups which lead to additional financial burdens. 70 % of industrial leaders have expressed that managing rising product costs while staying in the market is a major threat. Raw material costs, operational costs and overhead costs lead to an increase in product costs when OEM (Original equipment manufacturer) expects to reduce the cost of the product from automotive suppliers. Industrial leaders who comprise 60% of the participants expressed that the operational expenses and required resources allocated for operation are probably insufficient, with additional allocation. Provided operational budget may not be enough but an additional allocation of funds can be managed. A budget is defined as the required full financial estimation of the cost which is generally estimated well ahead of than operational schedule. It has been highlighted that the total operation cost to produce a quality product sometimes crosses the budgeted cost. Practical Implications: In this research, threat analysis as a tool can be useful during the initial stage. Threat identification and analysis of the impacts are a very important activity. By planning judiciously, the threats can be handled and minimise the intensity of impact on operational activities. Originality/Value: The important value of threat measures is the probable loss due to threats at the operational phase. Threats can result in to increase in cost, timeline, infrastructure and failure of the operations.
Examining Differences in Work-life Balance of Early Career and Seasoned Academicians
This research paper investigates the dynamics of work-life balance and stress management within the faculty community of universities in Dehradun, with a specific focus on age-related factors. The study will categorize faculty members into Early Career Academicians and Seasoned Academicians groups to discern variations in their experiences and coping mechanisms. The primary aim is to analyze how the challenges and coping mechanisms vary between the younger and older age groups within the academic community. The research adopts a descriptive study design, employing a mixed-methods approach to gather comprehensive insights. Quantitative surveys have been distributed among several universities of Dehradun to collect demographic information, work-related data, and stress levels. Qualitative surveys have been conducted as semi-structured interviews to delve deeper into the subjective experiences, exploring the impact of age on work-related stress and coping mechanisms. The findings of the study revealed the phenomenon of stress among faculty members in academia, with a specific focus on understanding why Early Career Academicians may experience higher stress levels compared to their established counterparts. Examining various factors, including career establishment, job insecurity, teaching challenges, financial pressures, organizational adaptation, and work-life balance struggles. The implications of elevated stress levels on individual well-being, job satisfaction, and overall efficiency, this research seeks to contribute to a nuanced understanding of stress dynamics in academic settings. The findings may inform targeted interventions, support mechanisms, and institutional policies aimed at alleviating stress among younger faculty members and fostering a healthier work environment within academia.
Eternal E-Waste Lifecycle Management: A Classified Review
With the threats to human health and the environment posed by the exponential growth in electronic devices, e-waste management has become a crucial global concern. The amount of electronic trash is growing, and traditional linear methods of consumption and disposal have not been able to keep up, endangering public health, and the environment, and depleting resources. In response, the idea of "eternal e-waste management" presents a paradigm change in the direction of circularity, stressing the ongoing repurposing, recycling, and reusing of resources in order to reduce waste production and increase resource efficiency. The extended producer responsibility (EPR) concept, which holds manufacturers responsible for the whole lifecycle of their products—from design and production to end-of-life disposal—lays the foundation of this strategy. EPR programs lessen the environmental effect of electronic products by encouraging sustainable patterns of production and consumption and by providing incentives for eco-design practices and material recovery. Furthermore, in order to make the collection, disassembly, and recycling of electronic trash easier, everlasting e-waste management depends on infrastructural development and technical innovation. By allowing the extraction of valuable materials from e-waste streams, advanced recycling methods including mechanical shredding, chemical treatment, and metallurgical procedures minimize environmental damage and the demand for virgin resources. Governments adopt rules, incentives, and awareness programs to encourage responsible e-waste disposal and recycling practices. Policy interventions are vital in fostering everlasting e-waste management. In order to handle transboundary e-waste flows and unify regulatory regimes across jurisdictions, international cooperation and coordination are also crucial. To sum up, everlasting e-waste management provides a comprehensive and long-term solution to the expanding problem of electronic trash. Embracing circularity, encouraging technological innovation, and putting supportive regulations in place can help societies move forward toward a more resource-efficient and sustainable future while lessening the negative effects of e-waste on the environment and human health.
The Role of Ecolabeling in Green Marketing: A Consumer Perspective
Aims: In this study the in-depth knowledge about how consumers perceive and are aware of the eco-labels in green marketing and how well these labels are effective in nature [1]. Eco-labels can bring out a positive perception in people towards the environment. In this study, a descriptive analysis is conducted by understanding the effectiveness of ecolabelling and we also come across how the dynamics towards eco-labelling has made a difference in the FMCG or fast-moving consumer goods. We also understand how consumer buying behaviour changes towards eco-labelled products. Non-probability sampling and survey were done using a questionnaire. The research took place in Bangalore and the duration to complete this research paper was around 30 days. A mixed methodology is used. Through this study, we understand people’s choices and their perception towards the eco-labels and their awareness about the eco-labels and if given a choice would their preference still be the same or changed. The results obtained, eco-labels play a vital role in green marketing by serving as a trusted guide for environmentally conscious consumers. Through providing transparent information about the sustainability of products, eco-labels empower consumers to make informed choices aligned with their values [2]. Overall, eco-labels represent a valuable tool in promoting sustainability and influencing consumer behaviour towards more environmentally friendly purchasing decisions.
A Review of a Classified Gas Leak Detection Alarm System Based on Arduino Uno
Gasoline is used in homes, offices, and storage containers that meet certain standards, but there are times when it spills and becomes dangerous due to liquid petroleum. An alarm device vibrates a buzzer alarm to do this. The amount of liquid petroleum gasoline present is audibly indicated by the buzzer. Smoke, ISO-butane, liquefied petroleum gasoline, and aromatic propane can all be detected by these flame detectors. The detector's sensitivity and reaction time combination is one of its advantages. The gasoline detector with liquefied petroleum switches to active low (logically 0-0) output when it detects a gasoline leak from the house or place of business. This project makes use of the Arduino universal network object, which detects fuel leaks and avoids weak communications. Liquid-crystal display and buzzer devices are.
The Mediating Role of Team Members’ Empowerment in the Link Between Leadership Stages and Organizational Outcomes
Background: Leaders are expected to be versatile in their work, needing to adapt their leadership style, attitude, and skills to contribute to the team’s growth and development. At different stages of team development, leadership approaches need to evolve to guide the team to the next stage. Aim: This study aims to analyze the mediating role of team members’ empowerment in the relationship between effective team leadership stages and organizational outcomes. Methodology: The data for this correlational research (empirical) study was collected through a structured questionnaire, that includes questions framed to measure effective team leadership concerning the stages of team development, i.e. LAS - General Leadership attitude and Skills, DCL - Directive and Confident Leader, MEM - Involving Members in leadership and participating as an Expert and ITL - Inter Team Leadership. The sample of 115 was drawn from the executive level leaders across the organizations through LinkedIn platform using a snowball sampling technique during the period of September 2023 to November 2023. The hypothesized relationships were then analyzed using the structural equation model IBM SPSS and AMOS software. Findings: Results revealed that there is a relationship between effective team leadership stages and organizational outcomes and also found that there is a significant mediation role of EPM - team members’ empowerment on the relationship between effective team leadership stages and organizational outcomes.
Modeling and Validation of Key Performance Indicators for Business: An Entropy-Based Approach
A company management system based on key performance indicators (KPIs) allows optimizing the company’s ecosystem by helping managers effectively manage available resources in key functions based on information about the company’s economic and operational activities. The article focuses on developing KPIs in a company and understanding the necessary criteria to be taken into account to improve the efficiency of the new system implementation at the micro and macro levels. This will help not only to achieve short-term goals but also in the strategic aspect will allow us to remain at the appropriate level of competitiveness, adapt to changes, and develop despite external challenges. The article actualizes that the effectiveness of KPIs directly depends on how well the indicators are structured, and how correctly they are interpreted and updated. In this study, we propose utilizing information theory tools to develop complexity-informed decision-making systems through precursor indicators. Specifically, classical information, approximation, fuzzy, permutation, and distribution entropies was examined. To test the effectiveness of these indicators, stock returns of the four most and least developed and globalized companies were analyzed. The findings reveal that the determinism or chaotic behavior of these companies is variable, as indicated by entropy metrics calculated using a sliding window algorithm. The performance of companies fluctuates with market conditions, showing increased efficiency and demand, reflected by rising trends and minimal entropy during certain periods, and maximum entropy during periods of disturbance. Empirical results demonstrate that approximation-based entropies are particularly resilient across varying market conditions and effectively distinguish between developed and chaotic companies.
Global Strategies for Climate-Neutral Business: Green Public Relations and Digital Solutions
Aims: The study aims to systematically investigate and substantiate the integration of green PR, digital transformation, and ESG principles into a complex strategy for achieving climate neutrality by global business. It seeks to explore the synergies and potential leverage points among these three domains to outline a holistic approach that corporations can adopt to mitigate their environmental impact in the digital era. Study Design: The research utilizes a qualitative approach, incorporating an extensive review of existing data, case studies, and statistical analysis to explore green strategies, ESG targets and green PR within digital solutions in order to satisfy corporate sustainability and climate neutrality. Methodology: The methodology includes a detailed literature review to gather insights on digital transformation, green PR, and ESG strategies in business; analysis of examples of corporations implementing sustainability strategies; and analysis of open data related to corporate expenditures on green transitions, the effectiveness of digital solutions for sustainability, and surveys of environmental awareness provided by reputable global agencies. Results: The study identifies the main challenges faced by corporations in achieving climate neutrality. It highlights the effectiveness of digital solutions in managing climate sustainability and the critical role of green PR in fostering environmental responsibility and engaging stakeholders. The research also presents data indicating a significant consumer demand for environmentally friendly products and corporate practices. Conclusion: The authors conclude that digital transformation and green PR are complementary strategies that create synergies in the pursuit of sustainable development. They emphasize the importance of integrating these strategies with ESG principles to develop effective corporate sustainability strategies. The study provides recommendations for leveraging digital innovations to enhance ESG initiatives, aiming to achieve climate neutrality.
ELYSIUMGATE: Non-Fungible Tokens (NFTS) for Event Perfection
In recent years, blockchain technology has witnessed significant attention and adoption across various industries due to its potential to revolutionize traditional systems. Non-Fungible Tokens (NFTs), a unique form of digital asset authenticated and stored on a blockchain, have emerged as a novel application within this domain. This paper proposes ELYSIUMGATE, a conceptual framework that harnesses NFTs to enhance the organization and execution of events. By leveraging blockchain’s immutability, transparency, and decentralized nature, ELYSIUMGATE aims to address key challenges associated with event management, including ticketing, authentication, and engagement. This research explores the technical architecture of ELYSIUMGATE, its potential benefits, and implications for event organizers, participants, and stakeholders. Additionally, it discusses potential risks and limitations associated with implementing NFTs in event management. Through a comprehensive analysis, this paper demonstrates how ELYSIUMGATE can contribute to achieving event perfection by ensuring trust, security, and efficiency in event organization and execution.
Banking Brilliance Unveiling Trends through Bibliometric and Thematic Lens
This study aims to conduct a bibliometric and thematic examination of banking efficiency and performance. Using co-citation analysis, scientific mapping, bibliographic coupling, performance evaluation, and bibliographic coupling, the study looks at articles published between 2009 and 2023. The study used thematic clustering, performance analysis, and bibliometric analysis to review 1548 publications from the Scopus database. This study examined several things, including theme mapping, authorship and nation collaborations, the most influential papers, co-occurrence of keywords, co-citations, prolific authors, essential institutions, nations, and the scientific production of publications. The study employed VoS viewer as a tool for performance analysis and thematic clustering. Regarding documents published, 2023 was the most productive year, with 190 articles. The most impactful nations and universities are the United States of America and “Islamic Azad University (Iran)”. The “Journal of Banking and Finance” was the most productive. The authors also identified six research theme clusters about the effectiveness and performance of banks. It gives academics direction and information on the current status of study on the various factors impacting the body of literature on the effectiveness and performance of banks. It also outlines possible directions for further research in this area. For the first time, a thorough performance analysis and scientific mapping of banking efficiency and performance that takes into account all pertinent banking efficiency and performance factors are presented in one study.
This paper introduces a script designed to automate the conversion of textual content into visually engaging videos with synchronized audio narration. The script accepts a plain text file as input and generates a video where each word is animated, allowing for dynamic presentation of textual information. Key features include customizable text attributes such as font size, color, and animation speed, along with dynamic background color transitions for enhanced visual appeal. Utilizing libraries such as `argparse`, `numpy`, `Pillow`, `gtts`, `moviepy`, and `pydub`, the script efficiently processes the input text, computes word durations, and generates corresponding video frames. It seamlessly integrates synthesized audio narration generated from the input text, ensuring coherence between visual and auditory elements in the resulting video. Empirical evaluation and case studies demonstrate the effectiveness and versatility of the script across domains such as e-learning, content marketing, and entertainment. It offers a streamlined approach to converting textual content into multimedia formats, with potential applications in educational tutorials, promotional material, and social media content creation. This paper provides a comprehensive overview of the script's implementation, customization options, and usage instructions. Additionally, it discusses potential applications and compares the script with existing methods in the field of automated video generation from textual input. Overall, the script serves as a valuable tool for content creators seeking to enhance the presentation and accessibility of textual information through dynamic multimedia content generation.
Aqua Kit: A Kit for Efficient Freshwater Fish Farming – A Comprehensive Sensor-Based Approach
Fish farming and aquaculture have been practiced for hundreds of years, and Asia’s country has shared approximately 55% of global production. In recent years, the authorization body has noticed a significant drop in fish farming in fresh water, like ponds, and lakes, and also several unclarities among people on how to take care of fish in artificial aquatic resources. The main causes of that include inadequate optimization a poor understanding of and culture surrounding fisheries a weak approach to fishing a shortage of personnel and a dearth of reliable databases pertaining to aquatic and fisheries resources, weak approach to fisheries, inadequate manpower, water pollution, poor optimization, and not adequate good fisheries knowledge and culture. The integration of Internet of Things (IoT) technology has revolutionized the realm of freshwater fish farming by providing a sophisticated and real-time monitoring system. This paper proposes an innovative approach to enhancing the aquaculture industry through the utilization of various sensors and IoT devices. By continuously monitoring water quality parameters and the well-being of aquatic life, this approach aims to optimize the farming process, mitigate risks, and ensure a sustainable environment for freshwater fish. The proposed solution may cover all of the above aspects to build a healthy fisheries culture and easily connect aqua research and development to continue monitoring to the ground level, it will also help to maintain a proper database to build better aquaculture, maintain the sustainability of nature and aquaculture. The system will be a smart machine learning (deep learning) and Internet of Things (IoT) based system that can detect oxygen, temperature, Ph level, ammonia, water overflow, fish disease, and many more and store the data as (big data) also manage to have user-friendly communication with as well as higher authorities.
Autism Spectrum Disorder Prediction Using Machine Learning
Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition characterized by challenges in social interaction, communication, and restricted repetitive behaviors. Early diagnosis and intervention significantly improve outcomes for individuals with ASD. In this paper, we propose a machine learning approach using an Artificial Neural Network (ANN) classifier to predict ASD based on a set of relevant features extracted from clinical assessments and behavioral observations. The ANN model is trained on a large dataset of individuals with and without ASD, incorporating features such as demographic information, medical history, and behavioral characteristics. Moreover, its web-based deployment ensures broader accessibility, facilitating early interventions and support. These advanced models can identify subtle patterns that may not be detectable through traditional clinical assessments alone.
EduTrust: A Blockchain-Powered Bridge for Seamless Academic Verification between Institutions and Employers
In a paradigm shift for academic record management, our groundbreaking system introduces a blockchain-based result verification system for university students, offering unparalleled transparency, security, and efficiency. Deployed on the Blockchain, this innovative solution not only simplifies result management but addresses a pressing industry concern- the challenging process and excessive costs associated with employers verifying student academic trajectories. By leveraging the decentralized and tamper-proof nature of blockchain technology, the system enables employers to authenticate academic records seamlessly and securely, eliminating the need for costly third-party agencies.
SIAS: Sensory Impairment Assistive Software
SIAS – Sensory Impairment Assistive Software, presents an innovative application of YOLO (You Only Look Once), and CNN (Convolutional Neural Network). Through Python-based deep learning techniques, the system leverages YOLO’s speed and accuracy to identify objects within a live camera feed, providing vocal announcements to the user. Furthermore, it offers a few additional features, which include gesture-to-speech conversion to facilitate communication between the physically challenged, Text-to-speech conversion, and Image Processing. This proposes an innovative communication system framework for deaf, dumb and blind people within a single compact device.
Social Media Impact on Mental Health Using Data Analytics: A Classified Review
This study examines the complex relationship between social media use and mental health using a comprehensive methodology, highlighting both positive and negative effects. Social media has become a major source of dependency for many people who are struggling with mental health concerns. The phrase "social media" describes a broad category of digital platforms that allow users to engage with each other in a virtual community and exchange, co-create, or share various types of digital content, including messages, images, videos, and information. Examples of these platforms include Facebook, Instagram, Snapchat, LinkedIn, and Twitter. Studies have demonstrated that the rates of social media use by individuals with a variety of mental diseases, including psychotic disorders, depression, and other severe mental health issues, are comparable to those of the general population. Social media's pervasiveness has led to an explosion of studies examining its effects on mental health. This study applies data analytics to a thorough analysis of the body of literature, classifying the various conclusions using a hierarchical method. The study examines the possible advantages and disadvantages of social media use, investigating its connections to a range of mental health issues, such as social comparison, anxiety, and depression. The paper clarifies how data analytics may be used to comprehend the intricate link between social media and mental health by examining user behavior, linguistic trends, and content engagement. The study also highlights future prospects and constraints, emphasizing the necessity for longitudinal research and the ethical issues related to data collecting and processing in this field. With its insights into the complex effects of social media on mental health and its potential to stimulate more study and intervention techniques, this categorized review is an invaluable tool for academics, policymakers, and mental health practitioners.
A system that can monitor calories is needed as individuals all over the world are becoming increasingly interested in maintaining a healthy weight, eating more nutritious food, and avoiding junk food. The nutrition from our daily meals can be beneficial in keeping our health. Dietitians and patients can measure and control daily food consumption with the use of the Food Calorie and Nutrition measurement system. The knowledge and information about an individual's fitness are found on the responsive website that is part of the proposed system. In order to create the website and give it a distinct look, we also used data from gym workout books. The fundamental knowledge of fitness, such as how to stay healthy by exercising and consuming foods high in calories, proteins, and carbs, among other ingredients. Includes user logins for administrators and users as well. A chatbot with artificial intelligence regarding human nutrition is the online artificial dietician. Like an actual dietitian, it serves as a diet consultant. Dietitians are knowledgeable about food's nutritional content. Based on a person's schedule, body type, height, and weight, a dietician provides advice. All of this data is also requested and processed by the system from the user. It enquires about the user's age, height, weight, and number of hours worked. The system stores and processes this data and then calculates the nutrient value needed to fill up user needs.
Study of an Innovative Approach to IoT Based Human Activity Recognition
Recognizing human activities is vital for numerous contemporary applications rooted in the Internet of Things (IoT) framework, spanning from the creation of intelligent video surveillance setups to the advancement of robotic assistants for the elderly. Recently, there has been significant exploration into machine learning algorithms to enhance the recognition of human activities. Despite these research endeavors, there remains a notable dearth of studies focusing on efficiently recognizing complex human activities, particularly those involving transitions, and no research has been conducted to assess the impact of noise in training data on algorithm performance. This paper addresses these gaps by presenting an innovative activity recognition system centered on a neural classifier with memory capabilities, designed to optimize the classification of both transitional and non-transitional human activities. Utilizing unobtrusive IoT devices such as accelerometers and gyroscopes integrated into widely-used smartphones, the system effectively identifies human activities [1,2]. The key feature of the proposed system lies in leveraging a neural network augmented with short-term memory to retain information about preceding activities' characteristics. Experimental validation demonstrates the reliability and accuracy of the proposed system compared to state-of-the-art classifiers, highlighting its robustness in handling noisy data. Human Activity Recognition (HAR) is essential for various modern applications within the Internet of Things (IoT) framework, from developing intelligent video surveillance systems to enhancing robotic assistants for the elderly. Despite significant advancements in machine learning algorithms for HAR, there is a notable lack of research on effectively recognizing complex human activities, particularly those involving transitions, and assessing the impact of noise in training data on algorithm performance. This paper addresses these gaps by presenting an innovative activity recognition system centered on a neural classifier with memory capabilities. Designed to optimize the classification of both transitional and non-transitional human activities, the system employs unobtrusive IoT devices such as accelerometers and gyroscopes integrated into widely used smartphones [1,3]. A key feature of the proposed system is the utilization of a neural network augmented with short-term memory to retain information about preceding activities' characteristics. Experimental validation demonstrates the system's reliability and accuracy compared to state-of-the-art classifiers, emphasizing its robustness in handling noisy data.
License Plate Recognition and Extraction of Details from Database
A sort of technology known as number plate recognition (LPR), primarily software, allows computer systems to automatically read a car's number plate number from digital photos. License Plate Recognition systems use the concept of optical character recognition to read the characters on vehicle license plates. Registration plate detection devices rely on optical character processing to comprehend the written information on the automobile's registration tag. Stated differently, LPR produces the characters that are engraved on an automobile's registration plate after receiving an image of the vehicle as input. It displays the vehicle's details and reads the characters. It can make use of already-installed closed-circuit television, and traffic enforcement cameras. It is used by enforcement agencies across the globe to enforce the law, including Figuring out whether an automobile is licensed or registered. On top of that, this is the case utilized by highway agencies and other pay-per-use roadways for electronic toll collecting and traffic flow cataloging. The main motive is to interpret and show registration plate individuals so that cars may be recognized and categorized.
Fostering Employee Relations through Communication Practices: Creating a Culture of Trust, Sharing and Transparency
Aims: The purpose of this study is to ascertain how the Dhanturi Group of Hotels Pvt Ltd's employee relationships are affected by good communication skills. Study Design: A descriptive study was conducted among randomly selected respondents. Place and Duration of Study: The research took place within Dhanturi Group of Hotels Pvt Ltd. Methodology: The study included 125 individuals, aged between 20 and 35, 80 of whom were men and 45 of whom were women. investigated how communication behaviors affect employee relationships using a descriptive research methodology. Surveys, interviews, and focus groups were conducted with a representative sample of 125 workers from a variety of departments to gauge opinions about communication methods and levels of trust. While the goal of qualitative analysis was to find important themes in employee experiences, survey data analysis attempted to identify trends. Results: There are statistically significant positive associations between employee relationships and sharing, transparency, and trust, according to an analysis of correlations among key factors related to positive employee relationships through effective communication. The Pearson correlation coefficients for these relationships ranged from 0.117 to 0.294. An R-value of 0.860, which suggests that these communication behaviors account for 74% of the variance in employee relationships, and an Adjusted R Square value of 0.733, which indicates a good model fit, validated the strong positive relationship between the independent variables (sharing, transparency, and trust) and the dependent variable (employee relationships). Conclusion: The study emphasizes how crucial it is to promote openness, confidence, and a sharing culture in communication methods in order to improve healthy employee connections. Transparency was found to be the strongest predictor, followed by trust, and sharing, and these findings provide insightful information for organizations looking to create focused strategies to foster a collaborative and supportive work environment. These findings also suggest possible areas for future research into interaction effects and contextual factors.
An Empirical Study on Millennial’s Behavior towards Perception of Investment Avenues with Reference to the Kutch Region of the Gujarat
The finance sector is a vital component of the economy, serving as a stimulant for economic growth, resource allocation, and risk management. It contributes to the creation of capital by mobilizing savings and directing them towards investments. In this investment decision, the investors play a crucial role in the economic development. This study’s primary goal is to examine the effects of gender, occupation, income level, and annual savings on the investment decision. The author also aims to find out the impact of investment objectives on the investment decisions of millennials. Millennials represent a large and influential portion of the population. Their decisions make a huge difference in the economy and it is essential to find the factors that affect the millennial’s investment behaviour. The study fills a deliberate gap by identifying the influence of demographics on the financial choices of millennials. In this study, the researcher has studied the investment behaviour of the 102 working millennials in the Kutch region of Gujarat. The study focuses on millennials' objectives while choosing the investment avenues, and factors influencing investment decisions. The analysis and data interpretation was done by SPSS. The research emphasizes that something is lacking in the study and found the absence of a strong correlation between annual savings and monthly income. The gender is significantly associated with gold & silver and Real estate. As the same demographic factor occupation is also significantly associated with the traditional avenues.
Indonesian Politics Articles Hoax Determination on Social Media
Currently, a lot of news about politics can cause misinterpretation because the news is not necessarily true or a hoax. Hoax is fake news spread to gain trust so that people feel confident the content is true. Another impact of hoaxes can be detrimental to people's emotions and finances. In Indonesia, especially DKI Jakarta, the spread of hoaxes ahead of the general election, between September 2023 and February 2024, is very high. To filter articles on social media, it is necessary to classify political news whether it falls into the hoax or non-hoax category. The hoax classification process uses a preprocessing stage which consists of tokenization and winnowing. Followed by the process of weighting words and Jaccard similarities until the classification process using the N-Gram method can provide accuracy in determining hoax or non-hoax news on social media. The aim of this research is to build a system model that can find political news information. The system will systematically determine news into a predetermined hoax or non-hoax label or category. Using a sample of 200 articles obtained from online social media. The article used is in the form of text without images included. Articles are taken from online social media because a lot of information is spread through social media. The research will be made into two categories or labels, namely hoax and non-hoax. The evaluation results in this research use a confusion matrix, where the precision obtained is 0.90, the recall is 0.78 and the accuracy obtained is 85%. Using the Vector Space Model method and Jaccard stemming, and similarity can make it easier to classify large numbers of articles.
A Survey on Investigating Machine Learning Approaches for Real-time Yoga Pose Rectification
Yoga is an ancient technique, which is based on a science, which focuses on the harmony between mind and body. This practice is highly recommended by doctors for curing different health ailments, yet many struggle with proper execution of asana which may put the user at risk of injury. Hence, it brings the need to perform the asanas accurately. This paper delves into the various methods used to solve the difficulty of grasping yoga poses by precisely identifying and guiding practitioners in real-time and addresses these challenges by leveraging computer vision and machine learning (ML). The methodologies explored also include deep learning (DL), and hybrid models. Specifically, neural networks like CNNs and key point detection techniques, such as those implemented with OpenCV, OpenPose, and Mediapipe, significantly improve the accuracy of pose estimation. The integration of these technologies allows for real-time feedback, aiding practitioners in maintaining correct poses and reducing injury risks. Moreover, with a virtual yoga guide, users can practice yoga anytime also eliminating the hassle and expense of commuting to yoga centers and gyms. It helps the user maintain accurate yoga poses and avoid injuries which can hamper the body in the long term, making it easier to practice yoga at home. This makes wellness practices like yoga accessible and vision to have a huge contribution to a healthier society.
A Study on Benefits Associated with Brand in the Purchase of Mysore Silk Saree
Introduction: A Mysore Silk Saree is a very unique and enjoyable purchase for customers since it embodies a weaving of both material and intangible advantages. These sarees are of high quality and are expertly woven with finest silk, which ensures both durability and opulent aesthetics. Customer relationship management is crucial for the business of Mysore silk sarees because it focuses on maintaining a strong market presence while prioritizing customer satisfaction and accordingly the customer is turning into a key factor for the little and huge organizations. Aims and objectives: This research paper aims to study the complex relationship between consumer preferences, brand influence, and the traditional realm of buying Mysore silk sarees. It covers the relationship with business partners, regulators and investors and society in large. The aim of the study is also investigate customer behaviors and opinions towards buying Mysore Silk Sarees. It examines the branding components and how it affects the consumers decisions. It studies the complex relationship of consumer preferences, brand influence, and the traditional realm of buying Mysore silk sarees and understanding the customer needs, that includes design, color, pattern, quality, trust, celebrity endorsement, brand name, tradition. Place and Duration of Study: The study was conducted in Bangalore city, with also include people who might be the visitors to the city. Duration of the study was 2 months from May and June 2023. Study Design: The research design used is Descriptive design. In this study design, features, behaviors, or occurrences are carefully observed and described without the usage of manipulative factors. It seeks to give readers a precise and thorough overview of the topic under study. This design gives a better understanding to the researchers into current patterns, linkages, and trends, so that it will give them a scope of further research opportunities. Data has been gathered by using both statistical methods and theme classification for qualitative inputs. When navigating the world of Mysore silk saree procurement, this analytical phase sought to identify trends, patterns, and recurring themes relating to the perceived advantages associated with brands. Results: The research results provide brands, producers, and marketers with concrete ideas on how to incorporate the observed advantages into their branding strategy and strengthen consumer loyalty and trust. Mysore silk creates a brand image in the customer’s mindsets and maintains a long-term relationship with their customers. Conclusion: Purchasing a Mysore Silk Saree is an act of supporting regional craftspeople, conserving history, and boosting local economies. Additionally, these sarees became symbols of distinction, denoting not just individual pride but also a group ties to a past that still permeates modern life.
Driving Financial Inclusion in Bharat's Amrit Kaal: The Role of Digital Payment Platforms and Embedded Finance
The 21st century is the century of technological advancement, in the context of the modern world people prefer everything under one roof. They don’t want to go to different places to get different products and services. There is a time when people prefer to stand in a queue to deposit money in a bank; those days are gone as technology advances to the next level. Digital wallets almost replaced cash transactions and India is in the phase of becoming a cashless economy. Embedded finance is financial services offered by non-financial companies such as bill payment, recharge, and money transfers etc., Here the companies which provide such services do not necessarily mean to be in the finance industry. Some of the best examples of embedded finance include PhonePe, Google Pay, Paytm, Amazon Pay etc., This study focused on the effectiveness and expansion of embedded finance in India using trend and comparative analysis and provided an analysis of how digitization changed every aspect of the Indian economy. The study completely depends on secondary data gathered from various websites, journals and research articles. The study concludes that the growth of embedded finance has added strength to the Indian economy by enhancing the availability of financial services at the fingertips.
Social Media and Emotional Intelligence: A Modern-Day Interplay among College Students
Aim: To study the influence of social media on the Emotional Intelligence of college students. Methodology: A convenient sampling method was used with 150 postgraduate college students from selected colleges in Bangalore, of which 78 were male and 72 were female. A survey instrument was developed to study the influence of social media on Emotional Intelligence, focusing on the self-management construct of the Emotional Competence Inventory (ECI). The instrument contained 22 variables across the 6 dimensions of the self-management construct and was administered online through Google Forms. The instrument achieved a reliability score of 0.9. Sixty-six hypotheses were formulated for one-sample t-tests, independent sample t-tests, and MANOVA. Results: The one-sample t-test results highlighted that the sample mean values of all the variables were higher than the test value and significant (maximum mean difference of 1.352 at P=0.000). The independent sample t-test showed no significant difference in perceptions between male and female respondents. Similarly, no significant difference was found in the perception of respondents regarding the influence of social media on emotional intelligence based on the duration of social media use. Conclusion: The usage of social media has a positive influence on the self-awareness and self-management of college students. Instagram, WhatsApp, and YouTube were the most used social media platforms. The top reasons for usage included knowledge and skill development, personal and professional networking, and entertainment. Further studies are necessary to explore the influence of social media on social awareness and social skills constructs of ECI. The influence can also be studied more deeply using other established instruments of emotional intelligence.
Emerging Technologies Transforming the HR Landscape
The field of Human Resources has seen considerable changes due to the rapid growth of technology, which has transformed traditional HR methods and processes. In the framework of developing technologies like as chatbots, blockchain, augmented reality, virtual reality, robotic process automation, natural language processing, and artificial intelligence, this study examines the changing landscape of HR management. The first section of the article traces the development of HR technology. After that, it looks at how HR technology is now being adopted and highlights how upcoming technologies have the ability to completely change a range of HR operations. The article investigates the effects of emerging technologies on important HR tasks like hiring and talent acquisition, employee training and development, performance management and feedback, and employee engagement and experience through detailed scrutiny. While recognizing the potential that emerging technologies offer, the study also addresses the difficulties in implementing them. There is a need for more studies on the ethical implications of AI and the impact of various AI technologies for long-term sustainability could be the area of focus. Future directions for HR technology are covered in this study, along with its effects on the workplace. The significance of ongoing learning and adaptability for HR professionals is emphasized. It ends by highlighting how new technologies have the ability to completely change the HR environment and how businesses must embrace innovation in order to be competitive in the rapidly changing digital economy.
The Role of Microfinance in Driving Economic Growth and Financial Inclusion in India
Finance is the foundation of the economic development of a country. Financial activities contribute to the growth of a country’s economy. India has transformed the entire financial sector with the introduction of inclusive finance, digitization and other regulations and has become an excellent financial service provider. However, it is still difficult to popularize rural finance practices. Microfinance is crucial in addressing the financial requirements in backwoods communities. It is also instrumental in the emergence of Self-Help Groups (SHGs), small business owners and new entrepreneurs. Microfinance integrates the financial services system by identifying its target customers and preparing financial products according to the exigency of the unorganized sector. Presently, microfinance has grown by 21% in FY2023 (FY2023) compared to FY2022 (FY2022). This study focuses on the play of microfinance in providing adequate finance to various sectors of the unorganized sector in India and facilitating economic growth.
Revolutionizing Retail Operations: AI and ML Implementation
Aim: This paper highlights the transformative influence of the integration of artificial intelligence (AI) and machine learning (ML) technologies on the retail landscape in India, focusing on their role in enhancing customer experiences, driving sales, and reshaping retail operations and raising awareness about the ethical considerations associated with the integration, for sustainable growth and customer trust. Methodology: Systematic review research is conducted to analyse and collect data from scholarly research databases and industry analysis. Selected research papers and reports were scrutinized, and the analysis considered their research design analysis, methodologies utilized, and data sources, to provide a comprehensive overview of the use of AI and ML in retail commerce. Findings: The transformative capacity of Artificial Intelligence (AI) and Machine Learning (ML) within the retail sector is discussed in the findings. AI and ML technologies have a strong and deep ability to enrich user experiences through personalized recommendations, optimize inventory management, streamline supply chains, implement efficient pricing strategies, and enhance consumer service. The study discusses the limitations and scope for ethical considerations during the integration of AI and ML within the retail landscape. Conclusion: This study emphasizes the importance of AI and ML in shaping the future scope of the retail landscape. By discussing the disruptive potential, and ethical implications of AI and ML technology integration, it provides invaluable insights to retailers, policymakers, and industry stakeholders, urging them towards continued exploration and investment in the retail ecosystem.
Strategies for Cultivating Healthy Workplaces in the IT Industry: A Comprehensive Examination of HR Dynamics
Background: In modern society, the IT sector plays a pivotal role in driving innovation, connectivity, and efficiency across various industries. In the fast-paced landscape of the Information Technology (IT) industry, the pursuit of strategies to foster healthy workplaces is a critical imperative. Aims: This research aims to examine the impact of workplace stress on employee productivity and mental well-being in the Information Technology (IT) industry, specifically focusing on companies in Mysuru city. It also seeks to propose and evaluate strategies for creating a healthy workplace environment within this sector. Research Methodology: The study adopts a descriptive research approach, conducting a comprehensive literature review to understand existing theories and practices related to building healthy workplaces in the IT industry. Simple random sampling is employed to select 150 IT employees from 6 major IT companies in Mysuru city. Data is collected using a structured questionnaire and analyzed using descriptive statistics, ANOVA, and a 5-point Likert scale to unravel patterns, trends, and variations in workplace dynamics. Additionally, company-wise analysis is conducted to assess the impact of various workplace strategies. Results: The findings indicate that workload intensity remains consistent across age groups, and there are no significant gender-based disparities in various workplace stressors. However, flexible work arrangements and mental health programs exhibit significant variations among companies, highlighting the need for tailored wellness initiatives. Age-neutral and gender-inclusive strategies are recommended to foster a healthier work environment. Conclusion: This research underscores the importance of addressing workplace stress in the IT industry and emphasizes the need for customized wellness initiatives tailored to the unique dynamics of each organization. Moving forward, future research could explore the effectiveness of specific interventions to provide actionable guidelines for enhancing employee well-being and productivity in the evolving IT industry.