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Decoding the alchemy of employee retention: A case of the manufacturing sector of the National Capital Region, India
The ability of a company to retain its staff is referred to as employee retention. It may also be referred to as a decrease in employee attrition or employee turnover rate. Employee retention is one such mechanism which ensures that the human capital stays with the organisation for a longer duration. The study focusses on identifying the drivers of employee retention in the manufacturing industry with respect to certain factors such as mentoring, career development, work environment, job autonomy, and compensation. This research has used the descriptive research design with some elements of exploratory research design. The sample size for the study was 122. Primary data has been collected with the help of a prevalidated questionnaire with multiple-choice closed-ended questions on a five-point Likert scale. The collected data was analysed using Excel and SPSS with statistical tools like T-test, ANOVA, multiple linear regression, etc. A direct positive relation has been found between mentoring, work environment and compensation, and the employees' intention to stay. 2024, IGI Global. -
AI Based Technologies for Digital and Banking Fraud During Covid-19
The only viral thing today is the Covid 19 virus, which has severely disrupted all the economic activity around globe because of which all the businesses are experiencing irrespective of its domain or country of origin. One such major paradigm shift is contactless business, which has increased digital transaction. This in turn has given hackers and fraudsters a lot of space to perform digital scams line phishing, spurious links, malware downloads etc. These frauds have become undesirable part of increased digital transactions, which needs immediate attention and eradication from the system with instant results. In this pandemic situation where, social distancing is key to restrict the spread of the virus, digital payments are the safest and most appropriate payment method, and it needs to be safe and secure for both the parties. Artificial intelligence can be a saviour in this situation, which can help combat the digital frauds. The present study will focus on the different kinds of frauds which customers and facing, and most possible ways Artificial intelligence can be incorporated to identify and eliminate such kind of frauds to make digital payments more secure. Findings of the study suggest that inclusion of AI did bring a change in the business environment. AI used for entertainment has become an essential part in business. Transfiguration from process to platform focused business. The primary requirement of AI is to study the customer experience and how to give a better response for improving the satisfaction. But recently AIs are used not only for customer support, but its been observed that businesses have taken it as marketing strategy to increase demand and sales. 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Energy-efficient smart cities with green internet of things
With governments of different countries having a vision of smart cities, the technology adoption and implementation are at its peak and the current increase in the usage of advanced technology for a smart city has led to an increase in the carbon imprint across the globe, which needs immediate attention for the environment sustainability. Although the Internet of things (IoT)-enabled devices have changed our world by bringing an ease to our lifestyle, it has to be kept under consideration that they also have adverse effects on the environment. Over the past few years, enabling energy conservation via Internet of Things in the growth of smart cities has received a great deal of attention from researchers and industry experts and has paved the way for an emerging field called the green IoT. There are different dimensions of IoT, in which an effective energy consumption is needed to encourage a sustainable environment. This conceptual paper focuses on the key concept of green IoT and sustainability, knowledge of Smart cities' readiness to Green IoT (G-IoT)-enabled sustainable practices, and identifying the Green IoT sustainability practices for smart cities. The Author(s), under exclusive license to Springer Nature Switzerland AG 2021. All rights reserved. -
Artificial Intelligence and Internet of Things readiness: Inclination for hotels to support a sustainable environment
The idea of Smart Cities has been one of the key driving factors for the urban transformation to a low carbon climate, sustainable economy and mobility in recent years because of the alarming situation of global warming. One of the industries with swift growth is hotel sector and hence is one of the key contributors to carbon emission and leaves environment footprints. The new emerging concept of sustainable tourism is envisaged as an important part of the Smart Cities paradigm. Improving sustainability by saving energy is becoming a primary task toady for many hotels. A great opportunity is provided by Artificial Intelligence (AI) and Internet of Things (IoT) to assimilate different systems on a platform by encouraging and assisting hotel guests to operate through single device and optimizing hotel operations. Current research focuses to identify the strategic positions of a hotel in terms of sustainability, AI and IoT technology. Components that will be considered by Hotels for the strategic intention of adopting AI and IoT for environmental sustainability. Different development and modification needed to be taken if management wants high sustainability readiness and/or IoT readiness. This conceptual paper constructs on the comprehensive study and systematic review of different area where the hotels can feasibly implement AI and IoT for improving sustainably. 2021 Elsevier Inc. All rights reserved. -
AI in e-learning
This current research chapter focuses on the different areas of e-learning where AI can be implemented to make e-learning a better experience. E-learning is a 24/7 platform where learners can gain knowledge at the convenience of their home and timeframe. AI can help such learners with different adaptive technologies in clarifying the doubt, identifying the problem area of the learner and providing them a customized learning solution. Adaptive learning suggested that the learning pace is different for different learners. It must be made sure that the educational supplies and amenities provided must fit the requirement of each learner; else, it will lose its essence. There are different AI features to enhance the learning experience of e-learning. The providers must keep this in mind that the acquired information about learners must be wisely used while implementing the AI technology to e-learning mode so that the blended model can provide an enriching experience to the end-user. Cognitive learning can be a key to constructive, collaborative and contextualized execution of AI-enabled learning processes. Maximization of AI effectiveness as a tool of e-learning can be brought only when it is implemented to overall program pedagogy and is monitored for continuous improvement. The Institution of Engineering and Technology 2021. -
Computational Model for Hybrid Job Scheduling in Grid Computing
Grid computing the job scheduling is the major issue that needs to be addressed prior to the development of a grid system or architecture. Scheduling is the users job to apropos resources in the grid environment. Grid computing has got a very wide domain in its application and thus induces various research opportunities that are generally spread over many areas of distributed computing and computer science. The cardinal point of scheduling is being attaining apex attainable performance and to satisfy the application requirements with computing resources at exposure. This paper posits techniques of using different scheduling techniques for increasing the efficacy of the grid system. This hybrid scheduler could enable the grid system to reduce the execution time. This paper also proposes an architecture which could be implemented ensuring the optimal results in the grid environment. This adaptive scheduler would possibly combine the pros of two scheduling strategies to produce a hybrid scheduling strategy which could cater the ever changing workload encountered by the gird system. The main objective of the proposed system is to reduce to overall job execution time and processor utilization time. 2020, Springer Nature Switzerland AG. -
Neurodiversity at the Workplace: The new paradigm of talent acquisition and retention
The importance of neurodiversity in the workplace has gained popularity in recent years. Companies can access a pool of distinctive skills and viewpoints that can stimulate innovation, creativity, and productivity by embracing neurodiversity in the workplace. This chapter examines the idea of neurodiversity in relation to hiring and retaining talent, emphasizing the advantages for both companies and workers. It covers methods for establishing welcoming environments at work that support neurodiverse workers and help them reach their full potential. It also looks at how corporate culture, HR regulations, and leadership all contribute to creating a welcoming workplace for individuals who are neurodiverse. Companies can promote diversity, equity, and inclusion at the workplace in addition to attracting and retaining neurodiverse employees (NDEs). A conceptual framework has been proposed to demonstrate the influence of various factors like awareness, perceived benefits, accommodation, organizational policy, stigma, and unconscious bias on retention of NDEs. 2024, IGI Global. -
The role of big data in predicting consumer behavior
Consumer behavior prediction is a significant task, and it is a prerequisite for marketing activities. Regardless of the product type/market type, predicting consumer behavior plays a vital role in determining the target market. The activities involved in identifying a target market include the tasks of analyzing the offerings, conducting market research, identifying market segments to create consumer profiles, and assessing the competition. In order to complete all four tasks mentioned above, it needs to have comprehensive and precise data/dataset in hand. It also means that the data/fact is the primary source of predicting consumer behavior. In today's digital world, sources of source (data) are multifold. During the process of data collection, if the repository is accepting data from such sources, then all five "V" (Volume, Velocity, Variety, Veracity, and Value) of data should be considered. The role of big data in predicting consumer behavior is inevitable. Machine learning models shall be deployed to analyze data from big data. In this chapter, benchmark datasets, and machine learning, are used to demonstrate the usage of artificial intelligence in analyzing, forecasting, and predicting consumer behavior. Before concluding the chapter, the performance of algorithms is evaluated and compared to find the most suitable models for predicting consumer behavior. Benchmark datasets are used in this chapter to represent the role of big data in predicting consumer behavior. 2023 Nova Science Publishers, Inc. All rights reserved. -
Ensembled convolutional neural network for multi-class skin cancer detection
A skin cancer diagnosis is critically important in medical image processing. The role of dermoscopy and dermatologists is inevitable in skin cancer diagnosis. But, considering the time constraints on diagnosing patients on time, even medical experts need computer-assisted methods to automate the diagnosis process with a higher accuracy rate and with good performance. Such computer-assisted methods with induced artificial intelligence (AI) algorithms are gaining significance. The challenging task of medical image processing is finding benign/malignant pigmented skin lesions after the input image of patients. To identify this difference, AI-based classification algorithms shall be deployed. During the implementation of such algorithms, several performance aspects are evaluated. Once the best such algorithm is identified and evaluated for its performance attributes, it shall be deployed to assist dermatologists. This book chapter explains such a novel multiclass skin cancer classification algorithm. The proposed algorithm uses the best of the attributes and parameters of a deep convolutional neural network (CNN) to give the best-ever enactment among similar existing algorithms. The result achievement of the developed deep CNN based multi-class skin cancer classification algorithm (DCNN-MSCCA) is demonstrated using the HAM10000 dataset. To establish the significance of the developed algorithm, the performance parameters of the DCNN-MSCCA are compared with a few existing significant algorithms. The maximum accuracy of DCNN-MSCCA in predicting the exact multi-class skin cancer is 95.1%. This book chapter explains the implementation details of DCNN-MSCCA using python and libraries supporting CNN. 2024 River Publishers. -
Inplane Lateral Load Behaviour of Masonry Walls
Masonry is one of the commonly used construction technology both in urban and rural areas. In this paper the in-plane behaviour of masonry walls is analytically studied considering existing closed form equations. Previous studies have proven that the lateral load behaviour mainly depends on the aspect ratios (h/L) as well as the axial loads. From this analysis the governing failure is determined and the lateral load versus lateral deflection curve is plotted for various percentages of axial loads. This graph gives the ductility of the wall. This concept is further applied to a simple masonry structure and the push over curve is plotted. 2020, Springer Nature Switzerland AG. -
A Review on Influence of Cutting Fluid on Improving the Machinability of Inconel 718
Nickel-based superalloys are widely used in the production and manufacturing sectors that require processes or applications that endure or operate at very high superheating temperatures. With the properties of high tensile strength, high melting point, and lightweight structural arrangement of molecules within the alloy material composition makes it more suitable for industrial utilization in aerospace industries and marine applications. This review paper discusses the use of various coolant lubricants that improves the machinability of Inconel 718 based on parameters such as surface roughness and tool wear under the influence of cutting speed, feed rate, and depth of cut. The machine used for analysis is CNC milling machine which will be used for experimentation using ceramic inserts as end milling tool. Various cooling techniques such as hybrid cooling, flood emulsion cooling, minimum quantity lubrication, and cryogenic cooling are being summarized in this paper from various experimentations and conclusions of other authors. On the basis of review, the hybrid cooling technique is found to be better than other cooling techniques because of its ability to obtain long tool life and smoother surface finish on the workpiece. With the use of these reviewed data, further research for finding a more compatible and effective cooling lubricant has to be done by experimentation in order to obtain an improved machining process for Inconel 718 material. 2020, Springer Nature Singapore Pte Ltd. -
Key challenges in developing and executing higher education learners' learning outcomes
This chapter examines higher education institutions' complex obstacles in developing and implementing effective learning outcomes. It emphasizes the need for outcomes that include subject-specific and general skills, meet students' diverse requirements, align with market demands, and incorporate emerging technologies. To facilitate student success in the 21st century, institutions must address these. It examines multidisciplinary programs, technology integration, faculty training, and student participation in outcome formation. It proposes enhancing outcomes through emerging technologies, social and emotional learning, global citizenship education, and entrepreneurship education, emphasizing student-centred approaches. Effective learning outcomes are essential for fostering student success in a constantly changing environment. Case studies from India, the United Kingdom, and the United States provide insights, emphasizing India and lessons from the US and UK experiences. 2024, IGI Global. All rights reserved. -
Nurturing the Rudiments and Use Cases of Ongoing Natural Language Generation for a Future Profitable Business More Profitable
Decoding the world of artificial intelligence and its usage in the current intelligence landscape enhance bottom-up growth in building resilient global business. The areas of artificial intelligence (AI) concerned with human-to-machine and machine-to-human interaction. The Next Wave in AI-driven speech is Natural Language Generation (NLG). Natural Language Generation (NLG) is the use of artificial intelligence (AI) programming to produce written or spoken narrative from a dataset. NLG is related to computational linguistics, natural language processing (NLP) and natural language understanding (NLU). NLG research often focuses on building computer programs that provide data points with context. Sophisticated NLG software has the ability to mine large quantities of numerical data, identify patterns and share that information in a way that is easy for humans to understand. The speed of NLG software is especially useful for producing news and other time-sensitive stories on the internet. At its best, NLG output can be published verbatim as web content. The goal of Natural language generation (NLG) is to use AI to produce written or spoken narrative from a dataset. Therefore, this study aims to study how NLG enables machines and humans to communicate seamlessly, simulating human to human conversations and using NLG how organizations are building new customer experiences, monetizing information assets, introducing new offerings and streamlining operational costs. Therefore, the coverage of this chapter will answer to the industrialists and new start-ups. What can NLG do for business? and what are the future applications of NLG? 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Upskilling and Curating the Potentials of IoT Enabled Smart Cities: Use Cases and Implementation Strategies
The reason for opting the Internet of Things in the smart city system was to manage assets, resources and services efficiently and improve the operations across the city. This will be achieved by the inception of cognitive technologies, including the Internet of things (IOT). The IoT enabled Smart cities enables the utilities for improving transportation and accessibility, improve social services, promote sustainability, and give its citizens a voice. However, the barriers to smart cities are siloed, piecemeal implementations, growing expectations, uninformed citizens and shrinking budgets and little or no investment capital. Smart streetlights, lighting adapts to the activity on the street. Parking sensors provide real time information on an app where to find vacant parking spaces. Garbage sensors and automated waste collection are recent eras of smart cities. Overall it improves the operational efficiency and provides better quality of service. Thus, India thought of IoT enabled Smart cities which include housing, schools, offices and retail. In this paper, we examine significant aspects of an IoT infrastructure for smart cities, outlining the innovations implemented in the cities of India as use cases and Implementation Strategies. Exceptional attention is devoted to the potential applications of smart cities. 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
EXPERIENTIAL TOURISM: Nature-based Tourism Trends in India
The rise of experiential tourism in recent years is seemingly gaining momentum. Tourism providers are marketing immersive travel experiences by engaging visitors with the destinations history, residents, and environment. Experience tourism entails immersing oneself in the essence of the destination in its truest sense. Authenticity involving emotions and values is of great importance for tourism marketing. Experiential travel rejects the idea of the traditional visitor experiences and gets back to the roots of travel. Over the last decade, nature-based tourism has become a widespread phenomenon and contributes more than US$120 billion to global GDP. The recent pandemic has additionally stimulated the demand for spending time and nature. Thus, experiential nature-based tourism could play an important role in the sustainable recovery of global tourism. This chapter discusses Indias critical experiential tourism trends through the marketing perspective and provides innovative marketing solutions for nature-based experiential tourism planning and development. Extensive and comprehensive literature has been used in this study to identify and critically reflect on vital nature-based experiences worldwide and the recent trends in the market. 2023 Taylor and Francis. -
Contemplating hair: Many shades of hair oppression in India
What is it like to be a woman with wavy/curly hair in a country like India? Although hair stories are different for different women, one common hair story for all Indian women with wavy/curly hair is moments of insecurity regarding the normalcy and beauty appeal of their hair. Aside from the discrimination faced due to the texture of hair, Indian women also face restrictions and suffocations in terms of creative self-expression of hair. This chapter presents an overview of the hair culture in India from a historical perspective along with religious narratives. The nature of hair discrimination of women in India is discussed and the chapter also shed light on institutionalised illogical restrictions. The author's personal hair stories will serve as an example to underline the complexity of hair discrimination in India. 2024, IGI Global. All rights reserved. -
Individuals Attitude Concerning Memes: A Study Reference to Active Social Media Users
Todays digital world, memes are more popular among the youngsters to express ones emotion. Nowadays, almost everyone is largely relying on social media to send memes and emojis in order to share the information in a humorous way. Lots of research article are reviewed about the social media memes, internet memes and this paper summarizes the usage of social media and following the trending pattern in communicating or sharing information through the social media platform. This study is aimed to study about the individuals attitude towards memes and its effect among the social media users. Through survey, total of 193 samples were collected by using questionnaire and statistical tools like Reliability test, Chi square and Correlation analysis have been used to interpret the collected data. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Navigating the landscape of green marketing trends and identifying greenwashing red flags
Through this chapter, the authors intend to provide information to the fashion and retail industry about the latest trends and their drawbacks, further increasing the awareness of environmentally conscious consumers. The objective of the study is first to examine the prevalent green marketing strategies adopted by fashion and retail businesses. Further, it also evaluates the actual reality and effectiveness behind the strategies used by brands to understand if they are creating an illusion of sustainability or are genuinely committed through case studies of various retail brands. Lastly it investigates consumer attitudes and perceptions of green marketing in fashion and retail. This research employs an approach to explore driving factors for green marketing in the fashion and retail industry. Utilizing secondary data, a comprehensive review of existing literature on sustainable practices, consumer behaviour, and industry trends was done. 2024, IGI Global. All rights reserved. -
Evaluation of Consumer Experiences by Extended AIDUA Framework in the World of the Metaverse the Future of Next-Gen Hospitality
The hospitality industry is continuously exploring novel ways to enhance consumer experiences, and the advent of the metaverse presents exciting prospects for transforming guest interactions. The metaverse can provide an immersive, 3D social experience of a virtual world by using technologies like virtual reality and augmented reality, which helps bridge the gap between the real and virtual worlds. This study explores consumer experiences in the metaverse in the hospitality context. Using the extended AIDUA (artificial intelligence device usage acceptance) model, the research aims to comprehensively analyze customers willingness to accept the metaverse in the dynamic digital landscape. The objective of this study is to investigate how the metaverse revolutionizes consumer experiences in the hospitality sector, specifically in the context of room and amenity booking, in-house events, and virtual tours. In this study, a three-step cognitive appraisal process with utilitarian motivation and the attitude of the customers that determines customers willingness and objection to utilizing AI devices is evaluated through secondary data. The metaverse empowers guests to optimize in-house event participation, seamlessly navigate their stay through taking a virtual walkthrough to explore a higher-end suite, and touring the city virtually. Practical implications for industry practitioners and researchers seeking to exploit the potential of the metaverse to create an immersive and unforgettable consumer experience in the ever-evolving landscape of hospitality are explored in this chapter. 2024 selection and editorial matter, Park Thaichon, Pushan Kumar Dutta, Pethuru Raj Chelliah and Sachin Gupta; individual chapters, the contributors. -
Exploring vector and raster data formats for geospatial visualization with python
The chapter uses Python to explore vector and raster data formats within geospatial visualization. It highlights their pivotal role across diverse environmental science, urban planning, and natural resource management domains. A nuanced comprehension of these formats is deemed essential for proficient geospatial visualization in Python, as they facilitate the storage and manipulation of spatial data. Vector data formats accurately represent points, lines, and polygons within a coordinate system. In contrast, raster data formats are tailored to depict continuous surfaces or grids of data. An array of libraries and tools are outlined for exploring and visualizing these geospatial data formats in Python, each serving distinct functionalities ranging from data manipulation to visualization. The chapter systematically introduces the concept of geospatial visualization, elucidates the disparities and application scenarios of vector and raster data formats, and subsequently elucidates various Python libraries and tools conducive to geospatial data manipulation and visualization. 2024 by IGI Global.