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                <text>Customer Perspective through Artificial Intelligence: Forecasting Green Products Sustainable Development</text>
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                <text>The idea of planned behavior was developed in 1980 as a philosophy of deliberate action to interpret human behavior. The primary element of this theory is an individuals purpose, which is impacted by the attitude of expecting that the behavior will result in the desired result. This theory has helped in determining certain characteristics of an individual that includes smoking, drinking, services, and so on. The theory states that the behaviors are achieved through motivation and control. These characteristics developed are completely voluntary which can sometimes help in the betterment and improvement in any field. The name of the theory itself gives us a clarity that it is a well-planned formation of behaviors different from his or her normative and preconceived beliefs and norms.  2024 Sachi Nandan Mohanty, Preethi Nanjundan and Tejaswini Kar.</text>
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                <text>Artificial Intelligence in Forecasting: Tools and Techniques, pp. 113-124.</text>
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                <text>ISBN: 978-104005150-4; 978-103250615-9</text>
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                <text>Jacob J., School of Business and Management, CHRIST (Deemed to be University), Karnataka, Bengaluru, India; Saji J., School of Business and Management, CHRIST (Deemed to be University), Karnataka, Bengaluru, India; Antony A.C., Christ College, Vadgaon Sheri, Off Pune Nagar Road, Maharashtra, Pune, India</text>
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                <text>Customer preferences to select a restaurant through smart phone applications: An exploratory study</text>
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                <text>Customer acceptance and preference; Restaurant promotion; Use of smart phone applications</text>
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                <text>The increasing number of Smart Phone Applications (SPA) user and fast growing restaurant industry proves the great potential of using SPA as business marketing opportunity in Malaysia. The constant growth in mobile technology has created a prospect for the restaurant industry to use SPA as a restaurant promotion tool. The growing attention of use of SPA among the Malaysian customer, marketing research remains understudied in the field of SPA based restaurant promotion activities. The aim of this study is to explore the increase in customer acceptance to use SPA based restaurant promotion and to identify the customer preference to use SPA to select the restaurant. Thus, this paper mainly focuses on restaurant information on product and promotion as antecedents of customer acceptance of smart phone apps by underpinning the Unified theory of acceptance and use of technology (UTAUT) model. A conceptual model and hypotheses are tested with a sample of 116 students from a private university at Selangor district, Malaysia. The findings indicate that there is a positive relationship to increase customer acceptance level through SPA based restaurant product information and also strong relationship with the restaurant promotion information. It also indicates that customer acceptance of SPA through experience and satisfaction has a positive significant effect on customer preference to select a restaurant. Based on the results, this paper rounds off with conclusion, recommendations for future marketing research and provides a new marketing strategy to formulate among the restaurant business sector.  2015 American Scientific Publishers. All rights reserved.</text>
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                <text>Balasubramanian K.; Balraj A.; Kumar J.; Jaykumar</text>
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                <text>Advanced Science Letters, Vol-21, No. 5, pp. 1489-1493.</text>
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                <text>&lt;a href="https://doi.org/10.1166/asl.2015.6081" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1166/asl.2015.6081&lt;/a&gt;
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                <text>ISSN: 19366612</text>
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                <text>Balasubramanian K., School of Tourism, Hospitality and Culinary Arts, Taylors University, Malaysia, Karpagam University, Coimbatore, 641402, India; Balraj A., Coimbatore, 641402, India; Kumar J., School of Tourism, Hospitality and Culinary Arts, Taylors University, Malaysia; Jaykumar, School of Hospitality Management, Christ University, Bangalore, 560029, India</text>
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                <text>Puthur, Limson Antony; Karakunnel, Meljo Thomas; Menon, Vishnu Achutha</text>
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                <text>Customer Relationship Management (CRM) Systems: Impact of AI on Post-COVID-19 Student Enrolment in Keralas Higher Education Institutions</text>
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                <text>AI Deployment and Adoption in Public Administration and Organizations;pp.197-212</text>
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                <text>&lt;a href="https://doi.org/10.4018/979-8-3373-2272-8.ch006" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.4018/979-8-3373-2272-8.ch006&lt;/a&gt; &lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/pages/publications/105004517843?origin=resultslist" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/pages/publications/105004517843?origin=resultslist&lt;/a&gt;</text>
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                <text>Puthur L.A., Christ University, India; Karakunnel M.T., Christ University, India; Menon V.A., Institute for Educational and Developmental Studies, Noida, India</text>
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                <text>This study investigates the influence of artificial intelligence (AI) on student enrollment in higher educational institutions in Kerala, with a particular emphasis on the mediating role of customer relationship management (CRM) systems. Employing a descriptive research design, a self-prepared questionnaire was administered to a purposive sample of 200 students, encompassing various educational stages. The findings reveal a significant positive correlation between AI usage and student enrollment, with AI usage accounting for 37.3% of the variance in enrollment outcomes. Furthermore, the analysis indicates that CRM systems partially mediate the relationship between AI and student enrollment, enhancing the effectiveness of AI-driven strategies in the recruitment process. With high reliability demonstrated in the research instrument (Cronbach alpha = 0.827), the study underscores the necessity of integrating AI and CRM technologies to optimize enrollment strategies in the evolving educational landscape.  2025 by IGI Global Scientific Publishing. All rights reserved.</text>
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                <text>Patent Number: 202241008325, Applicant: Dr. Rashmi Rai.&#13;
A customer relationship management system (1) and method of taking feedback thereof comprising a feedback button (2), a mobile application (2A), an electronic unit (4), a computer (5), a mobile (6), a network (7), a server (8), a database (9). The invention provides a feedback button may be a physical three-way button (2) or a three-way digital button. One of them is visible on mobile applications and the second one is visible in the room.</text>
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                <text>K, Lakshmypriya.</text>
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                <text>Winning in the E-Commerce business race at a competitive age like this requires proper usage of Customer data. Using that database and grouping it in similar segments in terms of spending expenditure, observation time, sex, and location so that every customer falls in a segment of characteristics. This mechanism is called Customer Segmentation. In the modern era of highly compatible technological advancements, Machine Learning Algorithms are being vastly used to bring solutions to these difficult yet essential services. In the field of research methods like simple clustering based on purchase behaviour, buyer targeting or automated customer promotion mechanism by dividing into two major categories, have been worked on. However, ensemble algorithms have come handy where different clustering algorithms are combined to deliver best segmentation. Lately combination techniques like clustering and classification mechanism have also delivered good results where, not only segmentation is done but also classification of existing and new customers are possible into the clusters. Depending on that an effective customer relationship management can really benefit the company to a huge extent. Unlike other studies where clustering was performed directly on RFM table, a different approach was taken in this study where, one dimensional clustering was done individually on Recency, Frequency, Monetary columns, then an overall score was calculated and customers were classified into three segments. However, for a new customer depending on his purchase behaviour he/she also can be classified into any of the categories.  2022 IEEE.</text>
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                <text>The motive of this work is to classify and categorize customers depending on their familiar traits/characteristics so as to enable a company or a firm to adequately market their products to each category more attractively and competently. It is imperative for a firm to educate themselves with each and every detail about the customer, such as age group, sexuality, social class, purchase pattern etc as it paves way for customer segmentation. Businesses may utilize segmentation to make better use of their marketing resources, get a competitive advantage over competitors, and, most importantly, display a deeper understanding of their consumers' requirements and desires. Customer segmentation, when combined with customer targeting and positioning, creates the foundation for strategic marketing. A manager can find new marketing possibilities and create or adjust the product to satisfy the demands of potential clients using the notion of strategic marketing. The product's quality level determines its position in the market's overall offering. It's a crucial aspect in selecting which market segment a collection will target. The commercial world has gotten more competitive over time, as enterprises like these have to fulfil their consumers' demands and aspirations, attract new customers, and enhance their bottom lines. In this research, I have put the spotlight on the information used by firms for the purpose of customer segmentation in the most valuable manner. In addition to that, I have portrayed different models of customer segmentation and the benefits reaped by a business in implementing them.   2022 IEEE.</text>
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                <text>This study aims to empirically measure the distinctive characteristics of customers who did and did not order food through Online Food Delivery services (OFDs) during the COVID-19 outbreak in India. Data are collected from 462 OFDs customers. Binary logistic regression is used to examine the respondents characteristics, such as age, patronage frequency before the lockdown, affective and instrumental beliefs, product involvement and the perceived threat, to examine the significant differences between the two categories of OFDs customers. The binary logistic regression concludes that respondents exhibiting high-perceived threat, less product involvement, less perceived benefit on OFDs and less frequency of online food orders are less likely to order food through OFDs. This study provides specific guidelines to create crisis management strategies.  2020 John Wiley &amp;amp; Sons Ltd</text>
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                <text>International Journal of Consumer Studies, Vol-45, No. 3, pp. 396-408.</text>
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                <text>&lt;a href="https://doi.org/10.1111/ijcs.12630" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1111/ijcs.12630&lt;/a&gt;
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                <text>ISSN: 14706423</text>
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                <text>Mehrolia S., School of Business and Management, Christ University, Bangalore, India; Alagarsamy S., School of Business and Management, Christ University, Bangalore, India; Solaikutty V.M., The American College, Madurai, India</text>
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                <text>Customers satisfaction towards online banking services of public sector banks</text>
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                <text>At present the banking industry around the world has been undergoing a rapid transformation. The deepening of information technology has facilitated better tracking and fulfillment of commitments, multiple delivery channels for online customers and faster resolution of issues. Customer satisfaction is important criteria for banks sustenance, now banks are offers online banking services according to the customer needs and requirements. This study analysed customers satisfactions towards online banking services of public sector banks in Tiruchirappalli district. It is understand from the present study that bank websites and technology platforms has to offer various knowledge features on financial services. To retain the existing customers, banks has to conduct regular surveys on the customer satisfaction. The results of the study shows that variables like prompt response, security and Website design and ease of use are top three factors affected customer satisfaction.  IJSTR 2020.</text>
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                <text>Kiran G.; Appasaba L.V.; Raja M.; Muthu Gopalakrishnan M.; Chotai N.</text>
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                <text>International Journal of Scientific and Technology Research, Vol-9, No. 4, pp. 3368-3372.</text>
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                <text>ISSN: 22778616</text>
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                <text>Kiran G., Welingkar Institute of Management, India; Appasaba L.V., Department of MBA, VTU  Belagavi, India; Raja M., Research Department of Commerce, Bharathidasan University Constituent College, Tiruchirappalli, Kumulur, Lalgudi, India; Muthu Gopalakrishnan M., School of Business Studies and Social Sciences Christ (Deemed to be University, Bengaluru, 567006, India; Chotai N., Jain University, Bengaluru, India</text>
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                <text>Customized mask region based convolutional neural networks for un-uniformed shape text detection and text recognition</text>
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              <elementText elementTextId="98908">
                <text>Deep neural networks; Optical character-recognition; Region based convolutional neural networks; Region of interest; Text detection; Text recognition</text>
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                <text>In image scene, text contains high-level of important information that helps to analyze and consider the particular environment. In this paper, we adapt image mask and original identification of the mask region based convolutional neural networks (R-CNN) to allow recognition at 3 levels such as sequence, holistic and pixel-level semantics. Particularly, pixel and holistic level semantics can be utilized to recognize the texts and define the text shapes, respectively. Precisely, in mask and detection, we segment and recognize both character and word instances. Furthermore, we implement text detection through the outcome of instance segmentation on 2-D feature-space. Also, to tackle and identify the text issues of smaller and blurry texts, we consider text recognition by attention-based of optical character recognition (OCR) model with the mask R-CNN at sequential level. The OCR module is used to estimate character sequence through feature maps of the word instances in sequence to sequence. Finally, we proposed a fine-grained learning technique that trains a more accurate and robust model by learning models from the annotated datasets at the word level. Our proposed approach is evaluated on popular benchmark dataset ICDAR 2013 and ICDAR 2015.  2023 Institute of Advanced Engineering and Science. All rights reserved.</text>
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                <text>Channegowda R.H.; Karthik P.; Srinivasaiah R.; Shivaraj M.</text>
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                <text>International Journal of Electrical and Computer Engineering, Vol-13, No. 1, pp. 413-424.</text>
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                <text>All Open Access; Gold Open Access; Green Open Access</text>
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                <text>ISSN: 20888708</text>
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                <text>Channegowda R.H., Department of Electronics and Communication Engineering, K S School of Engineering and Management, Ghousia College of Engineering, Visvesvaraya Technological University, Karnataka, India; Karthik P., Department of Electronics and Communication Engineering, K S School of Engineering and Management, Visvesvaraya Technological University, Karnataka, India; Srinivasaiah R., Department of Computer science and Engineering, Christ Deemed to be University, Karnataka, Bengaluru, India; Shivaraj M., Department of Electronics and Communication Engineering, Ghousia College of Engineering, Visvesvaraya Technological University, Ramanagaram, Karnataka, India</text>
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                <text>Customized SEIR Mathematical Model to Predict the trends of Vaccination for Spread of COVID-19</text>
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                <text>The uncertainty in life plans, restrictions on physical classrooms, loss of jobs, large number of infections and deaths due to COVID-19 are some significant causes of concern for the public as well as Governments all over the globe. Moreover, the exponential increase in the number of infected people in a short time is responsible for the collapse of the health industry during the pandemic caused by COVID-19. The health experts recommended that the quick and early diagnosis followed by treatment of patients in isolation is a way to minimize its spread and save lives. The objective of this research is to propose a customized SEIR model to predict the trends of vaccination in the USA. The experimental results prove that the Moderna vaccine reports the efficacy of 93%, which is higher than the Pfizer and Johnson and Johnson vaccines.  2022 ACM.</text>
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                <text>Alluhaidan A.S.; Poonia R.C.; Prabu P.; Alluhaidan M.S.</text>
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                <text>ACM International Conference Proceeding Series, pp. 77-80.</text>
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                <text>Alluhaidan A.S., Department of Information Systems, College of Computer and Information Science, Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia; Poonia R.C., Department of Computer Science, CHRIST (Deemed to Be University), Karnataka, Bangalore, India; Prabu P., Department of Computer Science, CHRIST (Deemed to Be University), Karnataka, Bangalore, India; Alluhaidan M.S., Ministry of Defense, Riyadh, Saudi Arabia</text>
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                <text>Cutting across the Durand: Water dispute between Pakistan and Afghanistan on river Kabul</text>
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                <text>Afghanistan; Pakistan; River Kabul; River Kunar; transboundary waters</text>
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                <text>All nations firmly believe in the absolute sovereignty over the waters flow in their areas and that only riparian states have any legal right, apart from an agreement, to use the water from the shared river. To address some of their water concerns, the co-riparian states compete to have more quantity of waters. Significantly, no water agreement exists between upper riparian Afghanistan and lower riparian Pakistan, despite sharing nine big and small rivers. The simmering water dispute between them on the River Kabul is rarely noted mainly because it is overshadowed by their political tensions, differences, and the dispute over the Durand Line. Using an analytical framework, this article examines three aspects of the River Kabul water dispute: its context, identifying the challenges that hinder a formalized bilateral agreement from being implemented, and its future.  2020 Policy Studies Organization</text>
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                <text>Ranjan A.; Chatterjee D.</text>
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                <text>World Water Policy, Vol-6, No. 2, pp. 246-258.</text>
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                <text>ISSN: 2639541X</text>
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                <text>Ranjan A., Institute of South Asian Studies, National University of Singapore, Singapore, Singapore; Chatterjee D., Christ University, Bengaluru, India</text>
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              <elementText elementTextId="291049">
                <text>Irfan, Mohammad; Parameswaran, S.; Singh, Kashish Ajit; Kismawadi, Early Ridho</text>
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                <text>Cutting-edge technologies for economic well-being: The transformative power of AI and blockchain</text>
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                <text>Driving Socio-Economic Growth With AI and Blockchain;pp.229-248</text>
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                <text>&lt;a href="https://doi.org/10.4018/979-8-3693-8664-4.ch010" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.4018/979-8-3693-8664-4.ch010&lt;/a&gt; &lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/pages/publications/105001368780?origin=resultslist" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/pages/publications/105001368780?origin=resultslist&lt;/a&gt;</text>
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                <text>Irfan M., Christ University, Bengaluru, India; Parameswaran S., Christ University, Bengaluru, India; Singh K.A., Christ University, Bengaluru, India; Kismawadi E.R., IAIN Langsa, Indonesia</text>
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                <text>This paper explores the transformative impact of cutting-edge technologies, specifically AI and blockchain, on economic well-being. It begins by examining how AI-driven solutions are revolutionizing industries, enhancing decision-making processes, and improving financial inclusion. Blockchain technology is discussed for its potential to increase transparency, reduce fraud, and streamline financial transactions, thereby fostering trust and efficiency. The synergy between AI and blockchain is highlighted as a powerful driver for economic growth, enabling decentralized finance, secure data management, and scalable innovation. The paper further explores how these technologies are unlocking new opportunities for sustainable development, particularly in emerging markets. It concludes by emphasizing the role of AI and blockchain in shaping a future of economic prosperity, with a focus on inclusivity, sustainability, and long-term well-being.  2025, IGI Global Scientific Publishing.</text>
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                <text>ISBN: 979-836938666-8; 979-836938664-4;</text>
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              <elementText elementTextId="291060">
                <text>Restricted Access; Hardcopy may be available in the library</text>
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                <text>Cyanogenic glycosides: A sustainable carbon and nitrogen source for developing resilient Janus reversible oxygen electrocatalysts for metal-air batteries</text>
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              <elementText elementTextId="127890">
                <text>Most of the transition metal based heteroatom doped carbon electrocatalysts, utilizes the fossil fuel derived commercially available precursors as source of nitrogen and carbon which may question our environmental generosity. Herein, we have developed Ni-based efficient bifunctional electrocatalysts using apple seeds (that contains cyanogenic glycosides) as the precursor for nitrogen and carbon. With tuning the temperature, we were able to optimize the nitrogen doping up to ?3 at.%. The optimized electrocatalyst catalyses the oxygen reduction reaction (ORR) process with muted peroxide generation (for 0.7500.1 V the % HO2 ? generation ?3 - 2%), preferential 4e? reduction pathways (n ? 3.93 to 3.98 in 0.750.1 V range) and electron transfer via inner-sphere electron transfer mechanism which ensures the maximum utilization of instituted active centres owing to the direct interaction of reactant species. Alike to ORR, the superior oxygen evolution reaction (OER) performance with smaller Eonset, EJ=10, Tafel slope and enduring accelerated stability test advocates its potential as a bifunctional oxygen electrocatalyst. Moreover, smaller potential gap ?E (EJ10_OER - E1/2_ORR) of 0.845 V further warrants the energy efficient OER/ORR process. A porotype of Al-air battery system using our catalysts as oxygen electrode and chocolate wafer as anode material is well capable of powering the light emitting diodes. This study hopefully opens a new avenue to explore cyanogenic glycosides plants product to develop multifunctional electrocatalysts.  2019 Elsevier Ltd</text>
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              <elementText elementTextId="127891">
                <text>Nandan R.; Nanda S.</text>
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              <elementText elementTextId="127892">
                <text>Carbon, Vol-155, pp. 155-165.</text>
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                <text>Elsevier Ltd</text>
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                <text>&lt;a href="https://doi.org/10.1016/j.carbon.2019.08.053" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1016/j.carbon.2019.08.053&lt;/a&gt;
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              <elementText elementTextId="127896">
                <text>All Open Access; Green Open Access</text>
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