Статті в журналах: "Flipkart"

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Uttam, Yeramalla. "Aspect-Based Sentiment Analysis on Flipkart Data." International Journal for Research in Applied Science and Engineering Technology 11, no. 5 (May 31, 2023): 5498–503. http://dx.doi.org/10.22214/ijraset.2023.52620.

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Abstract: This research In this paper, an Aspect-Based Sentiment Assessment (ABSA) model using the The Long Short-Term Memory (LSTM) network for analyzing info on Flipkart sentiment The suggested model seeks to identify and extract certain elements of a product or service, as well as to characterise their related sentiment polarity as positive, negative, or neutral. On a Flipkart dataset that is open to the public, experiments were run to assess the effectiveness of the suggested model. The LSTMbased ABSA model surpasses other baseline models, according to the results, achieving an accuracy of above 90%. The suggested approach is also capable of locating and extracting the key features of a good or service that influence consumers' opinions. This research provides a valuable contribution to the field of sentiment analysis on Flipkart data, and has significant practical implications for Flipkart companies seeking to improve customer satisfaction and loyalty

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Kalakata, Aishwarya, Apoorv Anand, and Pranav Saxena. "Flipkart : Driving Ecommerce During COVID-19." Management Dynamics 21, no. 1 (April 21, 2022): 7–13. http://dx.doi.org/10.57198/2583-4932.1005.

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Tiwari, Sadhana. "Impact of COVID -19 Era on Supply Chain Management and Logistics of Flipkart Company." VEETHIKA-An International Interdisciplinary Research Journal 8, no. 4 (December 31, 2022): 25–27. http://dx.doi.org/10.48001/veethika.2022.08.04.005.

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Supply chain management has restructured how a business can be accomplished not only in India but also throughout the world. Currently Indian having over 500 million internet user which secured the 2nd position in the world after China. The hefty number of internet user sky rocketed E retailing market in India with consumer preferences. Flipkart is one of the big names in E retiling market of India getting over 10000 orders per day. The aim of this research paper to do a deep study of supply chain management and logistics that how Flipkart making the goods available to the consumer at distinct location through over India in given period of time at a minimal cost. Modern technology and network they have implemented over the years to run smooth operations and take a glance at impact of COVID -19 on E commerce business with reference to Flipkart

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Malhotra, Gunjan, and Ranjana Aggarwal. "GROWTH PROSPECTS OF E-RETAILING IN ELECTRONIC GOODS MARKETS." International Journal of Management & Entrepreneurship Research 1, no. 2 (June 21, 2020): 71–88. http://dx.doi.org/10.51594/ijmer.v1i2.7.

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E-retailing has emerged as a significant player in the retail industry in India. The major cutthroat competition happens between Flipkart, Amazon, and Snap deal. These merchants have a significant competitive edge on electronic goods over other merchants in Indian online shopping portals. Thus, the purpose of this paper is to understand and analyses the universal perception and satisfaction quotient of customers in India concerning to the purchase of electronic goods via these e-commerce merchants. We have used hypothesis testing and analysis of variance to understand customer satisfaction and customer perception. The results show that overall customer satisfaction is the highest for Flipkart. Also, the physical appeal and the quality of the product are the main reasons which impact the customer's perception toward not shopping online. This study is original in itself because it is limited to the purchase of electronic goods only from the emerging e-retail merchants- Flipkart, Snap deal, and Amazon in India.

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Bhaskaran, P. Bala, and Nasheman Bandookwala. "Walmart’s Acquisition of Flipkart: Emerging Paradigm of the Digital Era." South Asian Journal of Business and Management Cases 9, no. 1 (December 18, 2019): 24–39. http://dx.doi.org/10.1177/2277977919881404.

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The case is set around the acquisition of majority shares of Flipkart by Walmart. The case traces the evolution of Flipkart as a startup and explores the context of acquisition by Walmart as well as the strategic fit between the two firms. Technological changes—mainly the proliferation of internet, mobile technology and the consequent digitization—have irretrievable impacts on the retail segment in terms of convergence of on-line and off-line retail and globalization of the markets. The case explores the emerging digitization scenario and its impact on the retail segment as a trigger to the merger process. Flipkart as an Indian startup had to re-incorporate outside India due to policy restrictions on fundraising. The case points to the inadequacies in the Indian policy regime with respect to startup fundraising and differential voting rights. Based on international comparisons, the case triggers discussion on the directions to policy changes if India hopes to create a congenial start-up ecosystem and if the dream of Digital India is to be achieved.

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Mishra, Dr Ashamayee, and Prof Sujata Rath. "Impact of Flash Sales on E-Commerce Industry in India." International Journal for Research in Applied Science and Engineering Technology 10, no. 7 (July 31, 2022): 4794–98. http://dx.doi.org/10.22214/ijraset.2022.46048.

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Abstract: The Indian E-commerce industry is developing multifolds and is relied upon to reach $20 Billion by 2020. This is because of evolving outlook of the Indian clients and simplicity of shopping on the web. Significant Indian E-trade organizations have concocted techniques year on year to draw the clients – Flash deals one among them. Streak deals like Flipkart's – 'Large Billion Day', Amazon. In's-'Incredible Indian Shopping Festival' and Snap deal's-'Unpack Zindagi(Unbox Life)' give limited time deals on profoundly limited costs on significant Indian celebrations. Information identified with the blaze deals of 3 significant online retailers from 2011 to 2016 wiz Flipkart, Snapdeal and Amazon, was gathered from secondary sources to analyze the effect of Flash deals on E trade organizations concerning deals, incomes, site traffic and coordination’s. The analysis will help internet business organizations comprehend the effect of glimmered deals for them.

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Mishra, Dr Somabhusana Janakiballav. "Customer Perception Towards Amazon and Flipkart: A Comparative Analysis." International Journal for Research in Applied Science and Engineering Technology 10, no. 5 (May 31, 2022): 2147–57. http://dx.doi.org/10.22214/ijraset.2022.42770.

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Abstract: In the world of business, the competition is very high. Every firm, every corporation is in the race to win more and more customers as if they are in a war with one another where one organization attacks another with their strategies and other defends itself. As a world of red ocean where everyone is attacking one another and there’s always danger around them. This war can be distinctively seen in the e-commerce industry. The e-retails websites try to overtake their competitors by adopting new and advanced technologies and strategies to gain better goodwill in the market, which will ultimately increase their web traffic. This study is an insight of the scenario of the two giants e-commerce e-retailers of India. It aims to check the difference between these two giants in India viz. Amazon India and Flipkart under the customer perception towards them. Keywords: Amazon India, Flipkart, E-commerce, Customer Perception

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Kumari, Priyanka. "Comparing Customer Attitude towards Amazon and Flipkart in Patna." International Research Journal on Advanced Science Hub 2, Special Issue ICSTM 12S (December 1, 2020): 4–8. http://dx.doi.org/10.47392/irjash.2020.252.

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Sen, Mr Arpan, and Prof Sneha Kanade. "COMPARATIVE ANALYSISOF AFFILIATE MARKETING PROGRAM OF FLIPKART AND AMAZONINDIA ." International Journal of Social Science and Economic Research 6, no. 4 (April 30, 2021): 1165–73. http://dx.doi.org/10.46609/ijsser.2021.v06i04.004.

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Dutta, Nirankush, and Anil K. Bhat. "Flipkart: journey of an Indian e-commerce start-up." Emerald Emerging Markets Case Studies 4, no. 7 (November 26, 2014): 1–14. http://dx.doi.org/10.1108/eemcs-03-2014-0064.

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Subject area Principles of management, Marketing, Finance, Strategy, Supply Chain Management, Entrepreneurship. Study level/applicability Master's Degree level courses, after students have been taught most of the basics related to management, marketing, finance, strategy, supply chain management and entrepreneurship. Case overview Founded in 2007 with an initial investment of less than USA $10,000, Flipkart has come a long way to become the largest E-commerce player in India with a registered user base of 9.6 million and valued at USA $1.6 billion. Efficient use of various marketing strategies has catapulted the company to its success. Till now, they have overcome most of the hurdles successfully. However, a lot needs to be discussed to find out ways to meet the challenges thrown by its competitors, to maintain its supremacy over other online e-retailers and continue its exponential growth to meet USA $1 billion sales by 2015. Expected learning outcomes After discussion of the case study, the student should be able to appreciate general business processes and develop basic analytical skills to resolve challenges faced by a fast-growing online start-up company in an emerging country like India. At the end, the students should be able to prepare a marketing plan for their own business within a stipulated budget. Supplementary materials Teaching notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes.

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Tej, Jaidam Ram, Jyotirmoy Banerjee, and Narendra Varma Dasararaju. "Size and Fit Recommendations for Cold Start Customers in Fashion E-Commerce." International Journal on Cybernetics & Informatics 12, no. 1 (January 30, 2023): 1–10. http://dx.doi.org/10.5121/ijci.2023.120102.

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Fashion e-commerce is expected to grow rapidly over the next few years. One of the main hurdles in fashion e-commerce is to recommend the right size to customers which helps customers in having a better online shopping experience. Hence Size and fit recommendation is an important problem which helps improve the confidence of a customer for making a purchase on an e-commerce platform. This also reduces the returns in fashion e-commerce. In this work we propose a novel bayesian probabilistic approach for non-personalised product size recommendation for customers. We use maximum likelihood estimation for estimating the parameters of our model. We use customer purchase and returns history to infer the true product size. Given a product we provide size recommendations to a customer, i.e. we suggest a customer to buy a size small, large or same size. In experiments with flipkart shoes datasets our model leads to an improvement of 3-4% AUC over the existing baseline. In Online AB testing for flipkart shoes categories our approach shows a performance improvement of returns by 12- 24 bps.

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Anand, Sonu. "A Comparative Study on customer satisfaction between Amazon and Flipkart." Journal of Management and Service Science (JMSS) 3, no. 1 (2023): 1–10. http://dx.doi.org/10.54060/jmss.v3i1.30.

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The best management programmers recognize the importance of combining theoretical knowledge with real-world application. Training is an integral part of the curriculum because it provides students with the hands-on experience and broad perspective they need to succeed in their chosen fields. Indicative of the state of the economy and the country as a whole, it serves as a useful gauge. It's essential for success in the business world. The average graduate student has more self-assurance, intelligence, and worldview than the average person. Marketing research is essential to the success of modern businesses. In my opinion, this methodical and illuminating approach to market preparation is the way to go. This method has applications beyond simple commerce. I've decided to zero in on this topic because I believe it's crucial to acquire as much information as possible about any given topic, be it an idea, an event, an organization, a location, or a person. The first step is to fully immerse oneself in the relevant market in order to study its dynamics and locate openings to meet the felt or felt requirements.

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Kiruthika, S., U. Sneha Dharshini, K. R. Vaishnavi, and R. V. Vishwa Priya. "Sentiment Analysis of Flipkart Product Reviews using Natural Language Processing." International Journal of Recent Technology and Engineering (IJRTE) 12, no. 2 (July 30, 2023): 54–62. http://dx.doi.org/10.35940/ijrte.b7774.0712223.

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In this contemporary world, people depend more on ecommerce sites or applications to purchase items on-line. People purchase items on-line based upon the scores and evaluates offered by individuals that purchased items previously which identifies the success or failing of the item. Furthermore, business suppliers or manufacturers identify the success or failing of their item by evaluating the evaluates offered by the clients. In current system, a number of techniques were utilized to evaluate a dataset of item evaluates. It likewise provided belief category formulas to use a monitored discovering of the item evaluates situated in 2 various datasets. The proposed speculative methods examined the precision of all belief category formulas, and ways to identify which formula is more precise. Additionally, the existing system unable to spot phony favorable evaluates and phony negative reviews with discovery procedures. One of the most popular works was done "Bad" and "Outstanding" seed words are utilized by him to determine the semantic positioning, factor smart shared info technique is utilized to determine the semantic positioning. The belief positioning of a file was determined as the typical semantic positioning of all such expressions. Semantic Positioning of context independent viewpoints is identified and the context reliant viewpoints utilizing linguistic guidelines to infer positioning of context unique reliant viewpoint are thought about. Contextual info from various other evaluates that discuss the exact same item function to identify the context indistinct-dependent viewpoints were drawn out.

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Amawate, Vibhas, and Madhurima Deb. "Post acquisition brand identity: acquisition of Flipkart group by Walmart Inc." Emerald Emerging Markets Case Studies 11, no. 2 (June 23, 2021): 1–21. http://dx.doi.org/10.1108/eemcs-12-2018-0274.

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Learning outcomes The learning outcomes are as follows: factors to be considered in devising the best post-acquisition brand identity and outline market research techniques, which can be used to identify the best-suited post-acquisition brand identity strategy. Case overview/synopsis The case study discusses the brand strategy, which Walmart Inc needs to adopt post its acquisition of Flipkart Pvt. Ltd (Flipkart) Group in India. Flipkart had acquired Myntra Designs Pvt. Ltd (Myntra) and Novarris Fashion Trading Private Limited (Jabong), but had kept their brand identity intact; Walmart Inc was faced with the decision on moving ahead with the brand strategy of keeping individual brand identities or merging all of these into a single brand identity. The study aims to provide valuable insights into the decision-making process adopted by Walmart Inc. It includes also the role of cause-related marketing in the positioning of Myntra as a socially responsible brand. The case study opted for an exploratory research design study using the qualitative research method of in-depth interviews. In total, 10 experts in the area of marketing, market research and marketing communication were interviewed. The qualitative data were analyzed using a template approach, which analyzes the text using a codebook or an analysis guide. The analysis guide already has clearly defined themes or categories. As the qualitative interviews progress, these themes get revised. These themes are analyzed qualitatively rather than statistically. The case study suggests to the management of Walmart Inc that they need to merge Myntra and Jabong based on the degree of similarity of consumer demographics, income/social class of buyers, brand identity and buying behavior. Myntra needs to retain as opposed to Jabong, as Myntra is perceived to be a socially responsible brand that creates a purchase disposition in the minds of the consumers. A more extensive quantitative study would offer better generalizability. It was not feasible to conduct a quantitative study due to time constraints. This research would have used advanced brand imagery assessment techniques such as multi-dimensional scaling to suggest if an overlap exists between consumer segments of Myntra and Jabong. The case study provides a decision-making framework to firms and individuals who are part of organizational teams to create a post-acquisition brand strategy in the e-commerce market. The case study fulfills a need for many academicians and practitioners to understand the decision-making process followed in devising a post-acquisition brand strategy in India. Complexity academic level Senior undergraduates; Master of Business Administration; Executive Master of Business Administration. Supplementary materials Teaching Notes are available for educators only. Subject code CSS 8: Marketing.

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Mahapatra, Durga Madhab, Ashok K. Mohanty, and Arundhati Patajoshi. "India's Online Business Restructuring: A Case Study of Flipkart. Com and Myntra." Training & Development Journal 6, no. 1 (2015): 82. http://dx.doi.org/10.5958/2231-069x.2015.00010.4.

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Bhardwaj, Lalit Kumar, Rishav Kumar, Harshit Khatana, and Althaf Shanavas. "Impact of COVID-19 on the business operations of Flipkart in NCR." International Journal of Research in Marketing Management and Sales 3, no. 1 (January 1, 2021): 25–28. http://dx.doi.org/10.33545/26633329.2021.v3.i1a.64.

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Pooja, P., and G. Divya. "Legitimate User Review Based on Sentiment Analysis." International Journal for Research in Applied Science and Engineering Technology 11, no. 6 (June 30, 2023): 3854–59. http://dx.doi.org/10.22214/ijraset.2023.54216.

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Abstract: Item surveys assume a significant part in choosing the offer of a specific item on the online business sites or applications like Flipkart, Amazon, Snap deal, and so on. In this, we propose a structure to identify counterfeit item surveys or spam audits by utilizing Opinion Mining. The Opinion mining is otherwise called Sentiment Analysis. In assumption investigation, we attempt to sort out the assessment of a client through a piece of text. We first take the audit and check if the survey is identified with the item with the assistance of Decision tree.

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Dhankar, Raj S., and Kunjana Malik. "Flipkart: Turning Brick And Mortar Market Into A Click Market- A Case Study." Prestige International Journal of Management & IT - Sanchayan 04, no. 01 (June 15, 2015): 94–99. http://dx.doi.org/10.37922/pijmit.2015.v04i01.009.

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Jamnani, Ajay. "E-Commerce: Big Billion Day-A case study with special reference to Flipkart." Asian Journal of Management 7, no. 3 (2016): 219. http://dx.doi.org/10.5958/2321-5763.2016.00033.0.

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Dey, Subrato Kumar. "“Study of customer satisfaction on online products in nagpur city with reference to flipkart”." South Asian Journal of Marketing & Management Research 9, no. 9 (2019): 41. http://dx.doi.org/10.5958/2249-877x.2019.00044.4.

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Saraswathy, Beena. "The Flipkart-Walmart Deal in India: A Look into Competition and Other Related Issues." Antitrust Bulletin 64, no. 1 (February 12, 2019): 136–47. http://dx.doi.org/10.1177/0003603x18823619.

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The Competition Commission of India approved India’s highest-valued acquisition, Flipkart by Walmart, within the first phase of investigation itself, stating that it is “not likely to have an appreciable adverse effect on competition in India.” Unlike many other retail acquisitions, there has been strong protest from the traders and retailers’ organization to stop the deal and for the creation of an exclusive e-commerce policy and regulator. Meanwhile, the Draft National E-Commerce Policy, 2018, suggested greater regulatory scrutiny for mergers and acquisitions that may distort competition. In this context, the present study looked into the competition dimension of the deal and other related issues. The study suggests to evolve a regulatory system with long-term vision to sustain and support the domestically grown innovations while making the competition assessment more flexible to accommodate the challenges posed by digital revolution.

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Rahardja, Untung. "Masalah Etis dalam Penerapan Sistem Kecerdasan Buatan." Technomedia Journal 7, no. 2 (August 24, 2022): 181–88. http://dx.doi.org/10.33050/tmj.v7i2.1895.

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Kecerdasan buatan adalah salah satu teknologi yang banyak digunakan oleh semua jenis mulai dari bisnis kecil hingga besar termasuk Amazon, Netflix, Flipkart, YouTube antara lain untuk meningkatkan sistem dan proses mereka, menghasilkan lebih banyak pendapatan dan mengambil keputusan yang tepat. Sistem otomatis dan mobil self-driving adalah beberapa contoh yang hebat dari kecerdasan buatan. Namun, selama perkembangan ada beberapa masalah etika yang muncul dan yang perlu ditangani untuk membuat keseimbangan yang baik antara kecerdasan buatan, etika bisnis dan manusia. Sehingga tujuan utama pengembangan kecerdasan buatan adalah untuk kemajuan masyarakat dan bukan menentangnya. Penelitian ini membahas beberapa masalah kritis yang muncul akibat penerapan kecerdasan buatan dan menyarankan cara untuk menangani masalah tersebut.

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Udhwani, Mayank. "Remedying The Mischief Created By E-Commerce Entities In India." World Competition 43, Issue 3 (September 1, 2020): 385–414. http://dx.doi.org/10.54648/woco2020020.

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E-commerce entities like Flipkart and Amazon have been alleged to be in violation of the laws governing foreign direct investment [‘FDI’] in India. Additionally, the business model adopted by them appears to be in contravention of the Competition Act, 2002. On 26 December 2018, the Department for Promotion of Industry and Internal Trade [‘DPIIT’] had issued Press Note 2 (2018 Series) which introduced a series of changes in the FDI norms in the e-commerce sector. (These changes have been incorporated in the FDI Policy vide Foreign Exchange Management (Transfer or Issue of Security by a Person Resident outside India) (Fifth Amendment) Regulations, 2019, dated 31 January 2019, Notification No.FEMA.20(R) (6)/2019-RB, available at, https://rbi.org.in/Scripts/BS_FemaNotifications.aspx?Id=11496 [Last accessed on: 21 April 2020].) The Press Note was purportedly introduced to protect the interest of small and medium sized enterprises in India. In this article, the author argues that the changes which are introduced by the Press Note go against the very purpose of their introduction as it leaves every stakeholder in a worse off situation by allowing easy circumvention. After highlighting the issues arising from amendments introduced by the Press Note in Part I of this article, the author delineates the anti-competitive nature of the business model of the e-commerce entities in Part II of this article. The author proposes that the appropriate method to remedy the problem surrounding the e-commerce sector would have been to make the appropriate amendments under Competition Act, 2002 rather than to opt for the FDI route. Foreign Direct Investment, Competition Law, Foreign Exchange Law, Amazon, Flipkart, e-commerce entities, private equity, anti-competitive practices, circumvention of FDI norms, India

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Siddhapura, Akbarhusen M., and Abuzar H. Vora. "A Study on Consumer Behaviour Towards Online Shopping in North Gujarat." Integrated Journal for Research in Arts and Humanities 3, no. 2 (March 31, 2023): 191–95. http://dx.doi.org/10.55544/ijrah.3.2.32.

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The rising in the number of internet users in our country gives great hope for online shopping. If Internet marketers know the factors that influence customer behavior and relationships, they can create marketing strategies that change people's ability to reach loyal customers and retain existing online customers. This research paper is available on Amazon, Flipkart, myntra etc. It focuses on the consumption habits of people in the North Gujarat who do business online through e-commerce sites. As the Internet has changed the way consumers do business, many companies facing the digital revolution have changed their business services online by making purchases easy and accessible while offering customers more discounts to compete in a competitive environment like Shopping.

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Mohammed, Muzakkiruddin Ahmed. "Sentiment Based Product Recommendation System for E-Commerce Using Machine Learning Approaches." International Journal of Innovative Research in Computer Science & Technology 10, no. 6 (2022): 120–37. http://dx.doi.org/10.55524/ijircst.2022.10.6.20.

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Today, e-commerce is a thriving industry. We do not need to approach every customer to accept their orders here. A business creates a website to offer things to clients, who can then purchase the stuff they need within the same website. These e-commerce firms include well-known ones like Amazon, Shopify, Myntra, Flipkart, and Ajio. To create a product recommendation system for the end customers, we will be using the data set of e-commerce product reviews in this final project. A sentiment analysis model will be used to enhance the suggestions. Under this final project, we will develop a sentiment analysis engine utilising a variety of machine learning approaches before selecting the model that produces the best results.

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Anand, Dr Raghu G., and Dr Mala K. M. "A Study on the Rise of E-Commerce from Indian Perspective- Flipkart and Its Liquidation Market." International Journal for Research in Applied Science and Engineering Technology 10, no. 8 (August 31, 2022): 715–23. http://dx.doi.org/10.22214/ijraset.2022.46264.

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Abstract: This paper examines the growth and different segments of electronic commerce in India. As e-commerce is one of the top growing businesses in India and provides a great market potential for investments, foreign Investors are funding e-commerce sector. The study concludes that there would be a prospective growth of e-commerce in India, if the Government provide a legal security and framework for e-commerce and the domestic and international trade are allowed to expand their basic rights such as intellectual property, privacy, prevention of fraud, consumer protection, etc. India is rapidly marching towards becoming a digitally empowered society. The widespread acceptance of Digital is being seen as a catalyst for overall economic growth, and with the combination of favourable demographics and policy reforms, India presents a unique and powerful growth story. With improving data affordability, consumption growth and newer financial products, the e-commerce market is set to grow, be it across e-tail, travel, consumer services or online financial services.

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Agrawal, Noopur, Aditya P. Tripathi, and Priti Jagwani. "Identifying Factors Influencing E-WOM on Social Networking Sites." International Journal of Open Source Software and Processes 13, no. 1 (January 1, 2022): 1–22. http://dx.doi.org/10.4018/ijossp.311838.

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The aim of present research is to examine the influence of identified factors on efficacy of electronic word-of-mouth (e-WOM) for selected e-retailers on social media platform Twitter, applying data mining technique through python software programming. Taking the use of different programming and context as a research gap, the relationship among three important factors viz; network related, text related and time related factors and their influence on e-WOM has been examined on randomly tracked 2582 tweets about two of the reputed Indian e-retailers, Snapdeal and Flipkart. This study may be of immense help to e-retailers in identifying their reference customers (influential customers) on social media platform which in turn may be channelized for the purpose of viral marketing and other communication campaigns.

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Dileep Kankatala and B.Indira. "SENTIMENTAL ANALYSIS OF CUSTOMER PRODUCT REVIEWS USING MACHINE LEARNING." international journal of engineering technology and management sciences 6, no. 6 (November 28, 2022): 378–81. http://dx.doi.org/10.46647/ijetms.2022.v06i06.067.

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Today, computerized surveys assume a vital part in improving worldwide correspondences among purchasers and impacting buyer purchasing conduct. Online business monsters like Amazon, Flipkart, and so forth give a stage to purchasers to share their experience and give genuine bits of knowledge about the exhibition of the item to future purchasers. To extricate significant experiences from an enormous arrangement of surveys, grouping of surveys into positive and negative opinion is required. Opinion Analysis is a computational report to remove emotional data from the text. In the proposed work, surveys have been characterized into positive and negative opinions utilizing Sentiment Analysis. Out of the different arrangement models, Naïve Bayes, Support Vector Machine (SVM) and Decision Tree have been utilized for characterization of audits. The assessment of models is finished utilizing 10 Fold Cross Validation

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Bajpai, Prateek, Nikhil Suryawanshi, Asmita Orse, Harsh Srivastava, and Prof Megha Patil. "E-Learning Recommendation System." International Journal for Research in Applied Science and Engineering Technology 10, no. 5 (May 31, 2022): 1915–18. http://dx.doi.org/10.22214/ijraset.2022.42706.

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Abstract: A Recommendation System is a system that is used to recommend any product based on the user’s rating. In the Recommendation System, we are searching for any product based on the reviews, if any product shows the best ratings, then we can select that product. Recommendation System has been used in a wide range of applications like Amazon, Netflix, Flipkart, Facebook, etc. E-Learning System is a system which helps to teach all the students in virtual way. Computers or Laptops and with Internet are used for working an E-Learning. E-Learning becomes a part of the Recommendation system. In this system, they are recommending those websites which is best to teach you, live doubt session like Coding Ninjas, Udemy, Edureka, Byjus, etc. Keywords: Recommendation System, E-Learning, Collaborative-Filtering, Content-Filtering, Hybrid-Filtering, Myers-Briggs Type Indicator(MBIT), Deep Learning.

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Nguyen, Thành, and Karthik Kannan. "Welfare Implications in Intermediary Networks." Information Systems Research 32, no. 2 (June 2021): 378–93. http://dx.doi.org/10.1287/isre.2020.0970.

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Competitive pressures have forced many traditional companies to evolve into a platform-based business model. Trade commissions and even supreme courts recognize the need for economic analysis as the nature of competition changes in the market. There have been many mergers and acquisitions across platform-based businesses. In the ride-sharing sector, Lyft and Didi Chuxing were initially in a partnership to thwart Uber but Uber merged its operation with Didi Chuxing eventually. Amazon and Walmart competed fiercely to buy the Indian online retailer Flipkart, which Walmart eventually won. Traditional antitrust models studying the implications of mergers do not consider the underlying network structure of these intermediary markets. This is the main focus of our model and analysis. We provide a network measurement to evaluate the effect of mergers on welfare. Our analysis shows that because of the underlying networks mergers can sometimes improve welfare.

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Shishodia, Dinesh. "Movie Recommendation System." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (June 30, 2021): 4919–24. http://dx.doi.org/10.22214/ijraset.2021.35929.

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This paper represents the overview of Approaches and techniques used in Movie Recommendation system. Recommendation system is used by many companies like Netflix, Amazon, Flipkart etc. It makes the user experience better and decrease the user efforts. It plays a very vital role in our day-to-day life. It is used in recommending Movies, Articles, News, Books, Music, Videos, People (Online Dating) etc. It learns from the user past behavior and based on that behavior it recommends item to the user. Likewise, in Movie Recommendation system movie is recommended to the user on the basis of movies watched, liked, rated by the user. In year 2020, approximate 10,000 movie were launched according to IDMB data. It saves a lot of times and efforts of the user by suggesting movies according to user taste and user don’t have to select a movie from a large set of movies.

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Suryawanshi, Nikhil Satish, Harsh Shrivastav, Prateek Bajpai, Asmita Orse, and Prof Megha Patil. "Institute Recommendation System Based on Online Review Comments and Machine Learning." International Journal for Research in Applied Science and Engineering Technology 10, no. 3 (March 31, 2022): 965–68. http://dx.doi.org/10.22214/ijraset.2022.40788.

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Abstract: Recommendation system has become a necessity in real world. In recommendation system, we are searching any product based on the reviews, if any product shows the best ratings, then we can select that product. Recommendation system has been used in wide range of application like, amazon, Netflix, Flipkart, Facebook etc. Now institution also become a part of recommendation system. In institution recommendation system, we select those colleges which is having a best reviews, which meets our eligibility criteria and our branch also. Recommendation system helps the user to discover the information and settle on a right choices where they do not have the required learning to judge a specific item. Only Naves Bayes algorithm is best algorithm in this system that we can easily check, and recommends them. This system has been used in education. Keywords: Artificial Intelligence, Machine Learning, Artificial Immune System, Naives Bayes, Decision Tree, Collaborative Filtering, Content Filtering, Hybrid Filtering

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Saggu, Amrit Kaur, and Adwitiya Sinha. "Social Influence Analysis for Information Diffusion in Complex Commercial Network." International Journal of Knowledge and Systems Science 11, no. 1 (January 2020): 22–59. http://dx.doi.org/10.4018/ijkss.2020010102.

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Social influence causes ideas to diffuse across the globe and track the rate at which awareness spans through online social communities. The users with better connectivity and higher interactivity bear greater potentials of spreading as well as perceiving the social trend. This concept has been further considered in the research to identify such prospective users in social network with high probability of influencing the opinions of others to whom they are connected. For the experimentation, Twitter profiles of 1900 followers from three major e-commerce portals, including Amazon, Snapdeal, and Flipkart, have been extracted to serve as the social network for conducting research. Acquired data is further narrowed down to yield a set of influential users in terms of central and centrally active, which are parameterized by neighborhood size and frequency of Twitter activity of individuals. Diffusion analysis is further performed on the derived set of key influencers to track the rate at which information propagates in the network.

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Sunderaraj, R., and M. Loheswari. "A Study on Internet Marketing and its Impact on Buying Behaviour of Traders in Sivakasi, Tamil Nadu." Asian Journal of Managerial Science 4, no. 1 (May 5, 2015): 18–22. http://dx.doi.org/10.51983/ajms-2015.4.1.1187.

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Marketing provides services in order to satisfy the customers. Internet marketing refers to advertising and marketing efforts that use the web and e-mail to drive direct sales via e-commerce as well as sales leads from websites or emails. Internet marketing is a growing business, mainly because more and more people use the internet every day. Internet marketing is the marketing of products or services over the internet. The internet has brought many unique benefits to marketing included low cost in distributing information and media to a global audience. E-Commerce is fundamentally changing the way consumers shop and buy goods and services. Consumers have begin to learn how to act in an ever-changing electronic marketing environment. Like any diffusion of innovation, there is a learning curve for most consumers to behave in e-commerce in a way they feel the most comfortable. Some of the most popular web sites for online shopping are Myntra.com, flipkart, jabong, eBay etc.,

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Purohit, Amit. "Sentiment Analysis of Customer Product Reviews using deep Learning and Compare with other Machine Learning Techniques." International Journal for Research in Applied Science and Engineering Technology 9, no. VII (July 10, 2021): 233–39. http://dx.doi.org/10.22214/ijraset.2021.36202.

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Sentiment analysis is defined as the process of mining of data, view, review or sentence to Predict the emotion of the sentence through natural language processing (NLP) or Machine Learning Techniques. The sentiment analysis involve classification of text into three phase “Positive”, “Negative” or “Neutral”. The process of finding user Opinion about the topic or Product or problem is called as opinion mining. Analyzing the emotions from the extracted Opinions are defined as Sentiment Analysis. The goal of opinion mining and Sentiment Analysis is to make computer able to recognize and express emotion. Using social media, E-commerce website, movies reviews such as Face book, twitter, Amazon, Flipkart etc. user share their views, feelings in a convenient way. Sentiment analysis in a machine learning approach in which machines classify and analyze the human’s sentiments, emotions, opinions etc. about the products. Out of the various classification models, Naïve Bayes, Support Vector Machine (SVM) and Decision Tree are used maximum times for the product analysis. The proposed approach will do better result as compare to other machine learning techniques.

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Athavale, Nachiket, Shubham Deshpande, Vikash Chaudhary, Jatin Chavan, and S. S. Barde. "Framework for Threat Analysis and Attack Modelling of Network Security Protocols." International Journal of Synthetic Emotions 8, no. 2 (July 2017): 62–75. http://dx.doi.org/10.4018/ijse.2017070105.

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Nowadays everything is computerized including banking and personal records. Also, to boost business profits, businessmen have changed their way of operations from physical way to electronic way, for example Flipkart. But as these developments benefit the developer they also increase the chance of exposing all of customer's personal details to malicious users. Hackers can enter into the system and can steal crucial or sensitive information about other authentic users and in case of banks leads to frauds. Security thus, becomes an important issue for all companies and banks. Intrusion detection systems help such companies by detecting in real time whether an intrusion is carried on or not. Here the authors are developing a signature based intrusion detection system which will scan incoming packets and send a warning message to system administrator. Also, the authors are implementing a framework and provide it to all the users so that developing intrusion detection based system similar to ours. The advantage of using framework is that it can be upgraded and re-defined whenever it is needed.

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Nellutla, Akash Phaniteja, Manoj Hudnurkar, Suhas Suresh Ambekar, and Abhay D. Lidbe. "Online Product Reviews and Their Impact on Third Party Sellers Using Natural Language Processing." International Journal of Business Intelligence Research 12, no. 1 (January 2021): 26–47. http://dx.doi.org/10.4018/ijbir.20210101.oa2.

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The purpose of this paper is to gain insights from the online product reviews of e-commerce sites such as Flipkart and Amazon and analyze its impact on third party sellers. To judge the authenticity of a product, reviews are more useful than ratings, since ratings do not give a complete picture. It is always preferred to consider both the product and seller reviews to have a seamless delivery and defect less product. In this paper, natural processing methods are used to gain insights by considering online reviews of a product. Methods such as sentiment analysis, bag of words model help to understand the impact of online product reviews on the seller's ratings and their performance over some time. The reviews are categorized into positive, negative, and neutral using sentiment analysis. Further, topic modeling is done to find out the topic reviews are majorly referring to. The seller reviews for a specific product after analysis are compared with the overall seller reviews to judge the authenticity. The results of this paper would be beneficial to both the consumers and sellers.

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Arora, Radhika. "The Influence of Trust and Brand Image on Purchase Intention in Online Shopping: A Comparative Study between Amazon and Flipkart." Adarsh Journal of Management Research 10, no. 2 (September 18, 2017): 1. http://dx.doi.org/10.21095/ajmr/2017/v10/i2/141452.

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Dr. Saraswathy C, M. Gokulanathan,. "“A STUDY ON EFFECTIVENESS OF ONLINE SHOPPING WITH SPECIAL REFERENCE TO CHENNAI CITY”." Psychology and Education Journal 58, no. 1 (January 20, 2021): 5043–48. http://dx.doi.org/10.17762/pae.v58i1.1727.

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Online shopping is current technology has hundreds of purchasing styles and the maximum famous of the times. An digital trade which to take part the shoppers and consumer for directly purchase goods from a dealer over the Internet the use of by a web browser. We come to understand that there are different names given to this such as electronic internet-shop, digital shop, digital store, Internet keep, online store, internet-save, web-store, virtual keep and online storefront, using the cell in application we've, Mobile trade describes purchasing from an internet keep’s mobile optimized online website online or applications. There are so many benefits in on line purchasing. An on-line keep arouses the internal analogy of purchasing services or products the manner is called enterprise-to-customer in online shopping. In the case of a business buying from some other business, the procedure is called enterprise-to-business in online buying. The largest of those online retailing businesses are Amazon.Com, flipkart, Alibaba and eBay are all source of online purchasing. The popularity of the advertising and marketing discussion board is important. In this study discussion effectiveness of online shopping and problems are discuss of this study.

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Gayathri, T., and S. Preethi. "Leveraging Networking Groups for Social Shopping with Special Reference to Instagram." ComFin Research 8, no. 4 (October 1, 2020): 38–50. http://dx.doi.org/10.34293/commerce.v8i4.3435.

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The advent of the Internet and the gradual digitization of select services mark the beginning of a new era in E-commerce and Online access to some facilities that minimize both time and human energy. For example, booking tickets for train travel, air travel, and even bus travel were brought to the fingertips of families which had to otherwise spend a lot of time in long queues before booking counters. Subsequently, other service providers also entered the field with more sophisticated services like booking accommodation, guided tours, and even packaged travel plans. Yatra.com, Make-my-trip, Goibibo, IRCTC, and Red bus are some of the best examples for pioneering efforts that made a considerable impact on services of this kind. In the meantime, the digital platform began to be exploited by new-players who entered the fray with products in almost all walks of life, such as clothing and fashion, beauty care, electronic goods, consumer durables, and even essentials of life such as groceries, fruits, and vegetables. The entry of big- players such as Flipkart and Amazon took online shopping to the next level.

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Agrawal, Yash, Atharva Phad, and Piyush Pawara. "Fashion HUB an Online Shopping App." International Journal for Research in Applied Science and Engineering Technology 10, no. 5 (May 31, 2022): 2068–72. http://dx.doi.org/10.22214/ijraset.2022.42680.

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Abstract: Since the global spread of Covid 19 across the world It has been and epidemic which has caused various losses in various fields, and has had a significant impact on small scale businesses. Covid cases have risen sharply in the second wave leading to a heavy loss in local businesses. So in order to tackle this problem, we came up with the idea which will help such small scale businesses. As we have seen rapid increase in users of ecommerce websites such as Amazon, Flipkart, Myntra and many others ecommerce websites people are mostly switching towards online shopping But many people still doubts the quality of online products So we will be trying to connect the local shopkeepers to local customers as the trust issues increases in this case and smooth solution of the issue is possible as compared to that of other e commerce websites. This project concentrates not only on the sake of local vendors but as well as of customers. As to better manage the online selling process, we need to comw up with a better approach of online selling web development app which is “Fashion HUB”.

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Dhanwal, Sanyogita. "PURPOSE AND EXTENT OF USE OF SOCIAL MEDIA BY STUDENTS." Gujarat Journal of Extension Education 35, no. 2 (June 25, 2023): 115–21. http://dx.doi.org/10.56572/gjoee.2023.35.2.0023.

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Social media is most modernistic form of media and acquire many features and characteristics. It have many facilities on same channel like as texting, communicating, images sharing, audio and video sharing, fast publishing, gaming, blogging, linking with all over world, direct connecting. Survey type research was conducted through the questionnaire. Locale of the study was in Hisar district of Haryana state. For the present investigation two private and two governments higher secondary schools (i.e. four schools) were selected from both the areas. Thus total sample comprised of 160 students were selected randomly. A well-structured interview schedule was developed for the data collection and data were quantified and interpreted by using suitable statistical tools to draw meaningful inference. Results highlighted that students keep themselves updates with latest know and how through newspaper, television, mobile phones, and mobile with internet connections. Majority of the students were aware and utilizing social media such as facebook, whatsapp, youtube, messenger and wikipedia etc. and most preferred application from online shopping was amazon and flipkart. They were generally spent more than two hours on social media irrespective of their locale.

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Menon, Balakrishnan. "The influence of e-relationship quality and e-service quality on customer loyalty in the context of Flipkart online retailer services." Journal of Customer Behaviour 17, no. 1 (August 31, 2018): 121–37. http://dx.doi.org/10.1362/147539218x15333820725155.

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Pathak, Atul Arun. "Seller side HR perspectives during M&A deals." Strategic Direction 32, no. 6 (June 13, 2016): 19–22. http://dx.doi.org/10.1108/sd-03-2016-0034.

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Purpose This paper aims to focus on the HR issues that seller organizations face during the pre-deal stage of mergers and acquisitions (M&A). It recommends the HR strategies that strategies that seller-side organizations need to adopt to improve their chances of successful M&A. Design/methodology/approach The paper explores the HR-related issues faced by seller-side organizations. It highlights the key dilemmas and challenges involved at this stage of M&A deals. It recommends the HR strategies that seller companies can follow during the pre-deal stage of an M&A deal. Findings What the seller’s HR leaders do (and do not do) during the run up to an M&A deal can significantly affect the success of the post-deal integration and future success of the combined firm. During the pre-deal phase of an M&A journey, HR leaders face a range of dilemmas. They have to decide whether to maintain business as usual or change their HR strategy, decide when to hide information and when (and what) to communicate internally and also have to prepare the seller organization for an HR audit by the buyer firm. Practical implications HR leaders in seller organizations need to continue to increase the value of the organization by continually aligning the HR strategy to the organization’s overall corporate and business strategy. During the early stages of the deal, they have to camouflage certain confidential details. When the deal is at an advanced stage, HR leaders have to communicate extensively with employees about the deal. They need to ensure that the organization is prepared for an HR audit by prospective buyers. However, they also have to ensure that the reasons for the seller organization’s success are not revealed fully and prematurely. Social implications It concedes that during an M&A deal, the HR leaders of a seller organization need to balance the interests of multiple stakeholders. These include the firm’s owners, top managers, employees and key customers. Those who are unable to do this effectively and consistently may end up harming the interest of the seller organization during an M&A deal. Originality/value The paper considers the highly dynamic e-commerce industry in India. It is a sector that is seeing rapid growth. Many new players are entering the market and the battle is for size and scale. In such a scenario, companies such as Flipkart are using the M&A route to scale up inorganically. Recently, Flipkart acquired Myntra, a strong player in the online retailing of fashion garments. The paper provides insights in to the challenges faced by the seller organization’s HR managers during the pre-deal stage of M&A transactions and recommends strategies that they should follow.

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Jayakumar, Tulsi. "Behavioral lessons from Flipkart’s Big-Billion Day sale." Competitiveness Review 26, no. 4 (July 18, 2016): 453–75. http://dx.doi.org/10.1108/cr-03-2015-0019.

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Purpose The purpose of this paper is to understand the behavioral lessons and managerial implications of deep discount strategies used by e-commerce firms to gain a competitive advantage over rivals. The paper seeks to understand the behavioral aspects of consumer and competitor response to such online sales, particularly with reference to e-satisfaction and e-loyalty. The case study seeks to: understand the behavioral aspects of utility and customer satisfaction; understand the behavioral aspects influencing customer attitudes, preferences and choice; understand heuristics involved in consumer decision-making; and understand possible firm strategies based on a thorough analysis of behavioral influencers of customer decisions. Design/methodology/approach The paper follows a case study approach. Secondary data sources from the library, company website and newspaper articles have been used to build a case which would encourage students to discuss and analyze the application of principles of behavioral economics to marketing problems faced especially by e-retailers. It uses Flipkart’s botched-up Big-Billion Day sale to drive home lessons in behavioral economics to marketers. Findings With growing internet penetration, e-retail presents high potential in India along with its BRICS peers. However, the task of grabbing customer mindshare, as also a share of wallet of the growing Indian purchasing power through monster discounts and deals by e-tailers may not work. Firms such as Flipkart may strategize using principles of behavioral economics including confirmatory bias, framing effects, reference points, principles of loss aversion, heuristics and the peak–end rule to influence customer decision-making in their favor. They must also guard against any incidents/events which invoke the representativeness heuristic or negative confirmatory biases towards e-commerce portals. Practical implications E-tailers in countries like India should understand the behavioral implications of deep discount strategies and deals offered by them as a means of gaining competitive advantage. Attention to e-service outcome quality and e-service recovery is important. Originality/value The case is unique in its applications of behavioral economics principles to e-retailing in India. It seeks to apply behavioral principles to a major e-commerce marketing event in India. With the e-commerce industry likely to boom in India, the case study provides unique insights into competitive pricing strategies adopted by e-retailers and the feasibility thereof.

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Agnani, Divyansh, Abhishek Bavkar, Samarth Salgar, and Sheetal Ahir. "Predicting E-commerce Sales & Inventory Management using Machine Learning." ITM Web of Conferences 44 (2022): 03040. http://dx.doi.org/10.1051/itmconf/20224403040.

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Due to prevalent transition from visiting physical stores to online shopping, predicting customer behaviour in the e-commerce market is gaining increasing importance. Over the past few years, e-commerce marketplaces such as Flipkart and Amazon have observed a manifold increase in both sales and market share of retail products sold. During this period, many traditional retailers and wholesalers have set up their e-commerce portfolios to stay relevant in the marketplace. However, due to lack of technology penetration in the Medium, Small, & Micro Enterprises (MSMEs) sector, the technological tools required by them are largely absent. One key issue for small businesses in e-commerce has been to forecast how many products their business will sell, thereby introducing another big issue of predicting how much inventory of a product they need to hold, to match up with demand. This is partly due to the massive scale and opportunities opening for them by participating in an open, large marketplace such as e-commerce. The COVID-19 pandemic has also drastically changed consumer shopping trends and behaviours: consumers have changed their preference to buying online. Thus, Indian small businesses need to have the ability to forecast demand more accurately than ever before.

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Deva Hema, D., J. Tharun, G. Arun Dev, and N. Sateesh. "A Robust False Spam Review Detection Using Deep Long Short-Term Memory (LSTM) Based Recurrent Neural Network." Journal of Computational and Theoretical Nanoscience 17, no. 8 (August 1, 2020): 3421–26. http://dx.doi.org/10.1166/jctn.2020.9198.

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Our day-to-day activity is highly influenced by development of Internet. One of the rapid growing area in Internet is E-commerce. People are eager to buy products from online sites like Amazon, embay, Flipkart etc. Customers can write reviews about the products purchased online. The purchasing of good through online has been increasing exponentially since last few years. As there is no physical contact with goods before purchasing through online, people totally rely on reviews about the product before purchasing it. Hence review plays an important role in deciding the quality of the product. There are many customers who give online reviews about the product after using it. Hence the quality of the product is decided by the reviews of the customers. Thus, detection of fake reviews has become one of the important task. The proposed system will help in finding such fake reviews about the product, so that the fake reviews can be eliminated. Therefore, the purchasing of the products will be totally based on the genuine reviews. The proposed system uses Deep Recurrent Neural Network (DRNN) to predict the fake reviews and the performance of the proposed method has compared with Naïve Bayes Algorithm. The proposed model shows good accuracy and can handle huge amount of data over the existing system.

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Mahapatra, Durga Madhab, and Soumendra Kumar Patra. "A New Destination of Online Travel Business: A Case Study." SEDME (Small Enterprises Development, Management & Extension Journal) 46, no. 2 (June 2019): 130–37. http://dx.doi.org/10.1177/0970846419852520.

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Technology is the lifeblood of the online travel business. Over the last two years, mobile has proved to be the biggest game changer. The possibilities and scalability of business are faster with cloud. Further, the Indian online hotel industry was expected to be USD1.8 billion by 2016 which was USD0.8 billion in the year 2015. India is among the top five traffic sources for ‘trip advisor’ globally. These are early days for online booking in India. India’s biggest online travel firms are seeking to dominate hotel bookings as the industry ventures beyond low-margin airline ticketing. The companies like MakeMyTrip and Goibibo have been offering cheap flight tickets and travel packages. The digital revolution in India, driven by the roll-out of 4G, reducing costs, increasing smartphone penetration and increasing time spent on mobile phones will ensure that digital architecture will also grow at a faster clip compared to traditional media. Thus, the growth of digital advertising during 2017 (`82.02 billion), 2018 (`108.51 billion), 2019 (`143.54 billion) and 2020 (`189.86 billion) as per Dentsu Aegis Network. Online travel portal MakeMyTrip has formed a partnership with Flipkart to allow consumers to book domestic flights tickets and other travel services directly through the e-commerce firm’s portal.

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T., Banerjee,, and Bhattacharya, S. "Analyzing Customer Engagement Online Using Gamification." CARDIOMETRY, no. 24 (November 30, 2022): 662–72. http://dx.doi.org/10.18137/cardiometry.2022.24.663672.

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Purpose: The purpose of the study is to investigate the impact of gamification options on customer engagement while shopping online. We further investigate the impact of gamification on customer experience and sales. Methodology: A study was conducted on E-commerce websites, which have gamification options (like Flipkart and Amazon). These websites were analyzed for games, which had brand collaborations. The games with immersion-related features such as badges/ medals, points/score, leader-boards, /high-score lists were considered. The users on the leader boards were interviewed. Interviewees were transcribed and analyzed for understanding their level of engagement, which was measured by expressed feelings or affiliations towards the brand; posts on their social media accounts, the recommendation to their friends, and finally, if they purchased products of that particular brand. A list of standardized questions using a 7-point Likert Scale was used to measure brand awareness and affiliation. Practical Implications: Brands can use this study to understand the customer’s engagement level to strategize before investing in gamification activities online. Originality: The article is based on social media analysis of customer engagement through Gamification in-e-commerce website and the assessment of brand association through interviews. Multiple sourcing helps in reducing common method bias to a minimum.

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Guru Prasad, Puttu, Dr K. . V. L. Somasekhar, Dr M. . S. Narayana, and Dr K. . Vijay Kumar. "The Candor and Probity of Employer Branding Strategies and Statutory Compliance of H.R Policies in Maintaining Delighted Employees at Flipkart - A Case Study." Emperor International Journal of Finance and Management Research 05, no. 06 (2019): 01–07. http://dx.doi.org/10.35337/eijfmr.2019.5601.

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