Month: March 2022

Posted on

A Study on impact of HRM Practices in Selected Construction Companies in Chandigarh

Project Title:

“A Study on impact of HRM Practices in Selected Construction Companies in Chandigarh.”

STATEMENT OF THE PROBLEM:

Employees are encouraged to take more responsibility, communicate more effectively, act creatively, and innovate HRM links remuneration to customer satisfaction metrics. This study helps the importance of Quality circles and its impact on employees productivity which in turn help the Construction Companies to achieve its goals.

OBJECTIVES OF THE STUDY:

  • To find the degree of HRM Practices implemented in the Construction Companies in Chandigarh
  • To study the level of commitment of employees towards their work in Construction Companies of Chandigarh
  • To analyse the techniques used for maintaining quality of work in Construction Companies in Chandigarh
  • To study the impact of HRM practices on employee performance in the Construction Companies.

RESEARCH METHODOLOGY:

SAMPLING DESIGN:

  • Sampling Procedure: The Employees will be randomly selected from the Construction Companies.
  • Sample units: Employees of five selected companies such as L&T, Consort Builders, S.S Constructions, ATS office, Ansal housing having branches in Chandigarh will be part of 100 sampling units.
  • Sample size: The sample size of about 100 employees will be taken for the Study dividing equally among five Construction Companies.
  • Data Collection:

Data will be collected from employee from different departments in an Organization.

  • Primary Data:

The primary data will be collected through questionnaire. About 100 employees would be taken from four selected Construction Companies for the Study.

  • Secondary Data:

The secondary data will be collected from HRM journals, magazines, text books on Management, websites and other publications.

  • Data analysis
  • Statistical tool such as Cross tabulation, charts, graphs, percentages and other suitable tools may be used to analyse the collected Data.

Period of the study:  about 50 days

LIMITATIONS OF THE STUDY: 

  1. The study is confined to HRM practices in Construction companies in Chandigarh only.
  2. The study is Limited to 100 employees working in Construction Companies
  3. The study is limited to for a period of 50 days only.
  4. The opinions and respondents may change over the period of time.
  5. The Data collected may become out-dated in future as new HRM practices may be implemented in future.
Posted on

A study on Technical analysis of Crude oil Futures with reference to Commodity Exchange (COMEX)

 PROJECT SYNOPSIS 

PROJECT TITLE:

“A study on Technical analysis of Crude oil Futures with reference to Commodity Exchange (COMEX).” 

NEED OF THE STUDY:

The Crude oil futures prices have shown a lot of volatility over the years; hence it is necessary to know the various technical and fundamental factors that influence the prices of Crude oil futures which will help the investor in reducing the risk involved in speculation. Since there is cut-throat competition in the present world market there is a need to study factors affecting Crude oil prices Even when Crude oil prices are high there is still a boom in the commodities market of Crude oil prices hence the main purpose and the need for the study are to know the Trend and direction of the Crude oil prices in COMEX   which is the index of other commodity exchanges which will help the investors to assess the level of risk and opportunities for buying and selling attached to it.

The study will give an insight into trading under Crude oil futures Prices of developed countries. The study is expected to identify various factors such as technical and fundamental that will impact price fluctuations of Crude oil in international trading platforms with special reference to COMEX.

OBJECTIVES OF THE STUDY:

  1. To know how Crude oil prices are traded in International Market
  2. To analyze the price fluctuations of Crude oil prices at COMEX
  3. To Conduct the Technical analysis of Crude oil futures using a Candle stick Study for the last year.
  4. To evaluate the trend analysis of Crude oil prices at COMEX
  5. To study the impact of Crude oil prices on investors and provide suitable direction for investing by studying the buying and selling points.

SCOPE OF THE STUDY:

  • The study covers various tools used like Relative strength index, Moving averages, Stochastics, MACD, and Bollinger bands.
  • The study is confined only to Crude oil Futures in the commodity market and the last year’s data is taken.

RESEARCH METHODOLOGY:   The data which is used is secondary in nature.

  • SECONDARY DATA:

The data will be collected from the journals, articles, books, and technical data available at International exchanges websites and Historical Chart Patterns using Candle Sticks. 

DATA ANALYSIS TOOLS:

Technical Tools:

The various technical tools applied on Candle sticks charts such as the Relative strength index, MACD, and Bollinger bands will be used for analyzing Crude oil futures traded at COMEX. 

  LIMITATIONS:

  • Difficulty in getting the live prices of Crude oil prices in absence of online research
  • Use of limited technical tools.
  • Commodity trading is limited to Crude oil prices only.
  • The study is limited only for a certain period of One year.)
  • There may be factors other than those studied in this research that may impact Crude oil prices.
Posted on

A study on project schedule and cost overruns with reference to Construction Company

Title of the project:

A study on project schedule and cost overruns with reference to Construction Company

EXECUTIVE SUMMARY

Project Management offers challenges that can be more visible and accountable than the more mainstream activities within an organization. Projects within organizations can bring disparate parts together through team members who represent their specialisms. Innovation and change has generated increased partnership working across public sector organizations. This emphasizes the importance of Project cost Management used to manage the complexities of these types of projects. Whilst cost reduction draws on generic management skills it is the adaptability of these skills in the context of a project that generates the need for cost, energy and commitment. Aiming for excellence is the key to a successful project.

The present study on Project schedule and Cost Management was undertaken to get knowledge of the effectiveness of cost management strategies in an organization. The present study is taken up with the aim of studying the approach of the Real estate Companies in developing, managing and executing of project cost management tools and techniques used in organization.
The study is done at Hyderabad in Construction Company with the employees from different departments as the respondents of the study. The staffs at different levels of hierarchy were interviewed using questionnaire. The data collected from the primary source and the secondary sources was analyzed using tables and charts. From the study, it was found that the PMS tools and techniques used in the organization are effective and most of the people working on different projects in the organization agree to it.The organization should therefore regularly assess the need for using advanced technology, assessment of risk and involvement of skillful employees who would form part of the project and meet the needs of the Stakeholders involved in the projects.

 Introduction and Objectives of the project:

Introduction:

Objectives of the project:

  1. To analyze project delay time and cost overruns
  2. To study the reasons for cost overruns in pre-execution phase
  3. To study the reasons for schedule overruns in pre-execution phase
  4. To study the reasons for schedule overruns in execution and closing phase
  5. To study the reasons for cost overruns in execution and closing phase
  6. To provide suitable recommendations.

Literature review:

The success or the failure of the project is broadly assessed in three dimensions.

a) Cost

b) Time

c) Product performance

However, the project cannot be called successful or failed on the basis of these three parameters if viewed from the eyes of all the stakeholders involved in it. The same outcome of a project may mean different things to different people.  Management‘s view of what constitutes a successful project may be different from that of a project manager, while developer and users may have different take on the success. The difference in view point is due to different perspectives, motivation and responsibilities associated with the roles.

Methodology and References:

Type of Research Method: The proposed study is a quantitative and descriptive type of study. The major purpose of using such a design is description of the state of affairs as it exists at present.

Sample size: The sample size would be 50 respondent.

Primary data:

Primary data will be collected by following methods:

  1. Observation during the project.
  2. Personal interviews through a questionnaire

Secondary data: The data will be collected from the Magazines, Annual reports, Internet, Text books and brochures.

Data collection: Data will be collected through observation and questionnaire

Data Analysis method: Data will be analyzed by using excel and using graphs, charts and percentages.

TOOLS / TECHNIQUES TO BE USED FOR DATA ANALYSIS:

Descriptive statistics, Charts and graphs

Posted on

A Study on Role of Project Management Information system (PMIS) for successful implementation of Projects

Title of the project: A Study on “Role of Project Management Information system (PMIS)” for successful implementation of Projects.

Objectives of the project:

  • To investigate the contribution of PMIS towards the success of various projects.
  • To study the role of every component of PMIS for the successful implementation of projects.
  • To analyze information instruments for the current management of ongoing projects.
  • To study how to create and maintain an information circulation network for the management of operational activities.
  • To study the importance of Enterprise guidance and project background information.
  • To study information coming from various sources, including formal reports, informal sources, observations, project review meetings, and questioning.
  • To study the interface of PMIS with larger organizational information systems to permit smooth, well-organized interchange of information in support of organizational and project goals.

Problem Statement:

A PMIS consists of people, equipment, and procedure to collect, process, store, combine, and communicate the needed information to users (stakeholders) for carrying out project management functions.

The success of the timely implementation of projects depends on the availability of essential information at the appropriate time. The information is needed for taking various decisions during the selection, planning, execution, and closure of a project. Project Management Information System (PMIS) aims to provide relevant information on time, resulting in improved performance.

Traditionally, this system was manual, paper-based, and labor-intensive. It was slow to respond and update. The advancement of computer and telecommunication technology made a phenomenal change in it.

The features of present PMIS include:

  • Speed: Processes speed up the creation of information within a blink of an eye.
  • Capacity: Ability to process and store large data.
  • Efficient: Fewer people are needed to manage the system.
  • Economic: Provides cost advantage over manual system.
  • Accuracy: Provides better accuracy than a manual system. 

Project Management Information System (PMIS) helps in planning, executing, and closing project management goals. Project managers use PMIS for budget frameworks such as estimating costs at the time of the planning process. Furthermore, the PMIS is employed to build a specific schedule and classify the scope baseline.

The project management team collects information into one database while executing the project management goals. It is used to compare the baseline with the actual achievement of each activity, manage materials, collect financial data, and keep a record for reporting purposes. The PMIS is used to assess the goals to ensure that the tasks were accomplished when the project is closed after that, it is employed to make a final report of the project close.

Methodology to be used:

The research process or methodology is the approach to the entire study- it is the master plan. It is the blueprint for achieving the objectives.

PRIMARY DATA COLLECTION

Data are collected firsthand. The key point here is that the data you collect is unique and research; until it is published no one else has access to it.

There are many methods of collecting primary data and these methods include

  • Questionnaire
  • Interview
  • Focus group interviews
  • Observation
  • Case Studies
  • Diaries
  • Critical incidents
  • Portfolios.

The primary data, which is generated by the above methods may be qualitative or quantitative the nature. 

Questionnaire

The questionnaire is one of the most widely used survey data collection techniques. Because each person is asked to respond to the same set of questions. It provides an efficient way of collecting responses from a large sample prior to quantitative analysis.

Interview

Interviewing is a technique that is primarily used to gain an understanding of the underlying reasons and motivations for people’s attitudes preferences or behavior. Interviews can be undertaken on a personal one-to-one basis or in a group.

SECONDARY DATA COLLECTION

Secondary data is one type of quantitative data that has already been collected by someone else for a different purpose than yours. Examples of secondary data are case studies, government reports, organizational reports, etc.

Statistical Tools for representation and analysis of data

  1. Tabulation
  2. Graphs
  3. Chart
  4. Pareto Analysis
  5. Diagrams

This project will be mostly based on my own experience and case studies of different researchers but I will also use the experience of my colleagues and suggestions of my higher official. An exhaustive amount of data available on the internet, from textbooks, newspapers, and various magazines, and suggestions from a few experts in the field will be analyzed in doing this project.

Posted on

A Study on Green accounting practices with reference to Indian Companies

SCOPE OF WORK

  1.  To make studying the significance and utility of Green accounting and reporting in Indian Companies
  2. To examine and identify the shortcoming in the existing legal and accounting framework for Green accounting and reporting in India.
  3. To critically examine the Green accounting and reporting practices adopted by public and private sector Indian companies with special emphasis on post economic liberalization era.
  4. To find out the difference of opinions between public and private sector Indian companies relating to environmental challenges, protection, and management.
  5. To compare and contrast the accounting and managerial attitudes towards the nature and periodicity of disclosure, cost, and audit of Green accounting and reporting among Indian public and private sector companies.
  6. To suggest measures to streamline the existing Green accounting and reporting and to identify the future prospects of Green accounting and reporting in India in a fast-changing Industrial environment.

Methodology

Public and private sector companies that play a vital role in the social responsibility of multifarious nature both have been included in this study. The present study covers only accounting and reporting on environmental aspects since the liberalization of the economy.

The method adopted to solve out the problems is based on the primary data. Primary data for this research work will be collected through questionnaires from the employees of public and private companies in India. There is little use of Secondary data gathered from government reports, journals, newspapers, magazines, and websites. The data so collected will properly be classified, tabulated, and analyzed according to the objectives of the study using the Percentage Method.

Timeline

 The period for the study for doing the project work is one month.

EXECUTIVE SUMMARY:

In recent years, Environmental pollution becomes severe and the stakeholders are considerably worried about the issue which paved the way for the growing concern about the implementation of green accounting. In this paper, an attempt is made to discuss the theoretical foundation of green accounting and reporting practices with special reference to India. Green accounting and awareness have given more important as it is the need of the day.

Objectives of Green Accounting

The objectives of green accounting and reporting are as follows:

  1. To help in the negotiation of the concept of environment and to determine the enterprise’s relationship with society as a whole and the green pressure group in particular.
  2. To segregate and collaborate all Environmental related flows and stocks of resources.
  3. To minimize green impacts through improved product and process design.
  4. To ensure effective and efficient management of natural resources.

OBJECTIVES OF STUDY

  1. To make studying the significance and utility of Green accounting and reporting in Indian Companies
  2. To examine and identify the shortcoming in the existing legal and accounting framework for Green accounting and reporting in India.
  3. To critically examine the Green accounting and reporting practices adopted by public and private sector Indian companies with special emphasis on post economic liberalization era.
  4. To find out the difference of opinions between public and private sector Indian companies relating to green challenges, protection, and management.
  5. To compare and contrast the accounting and managerial attitudes towards the nature and periodicity of disclosure, cost, and audit of Green accounting and reporting among Indian public and private sector companies.
  6. To suggest measures to streamline the existing Green accounting and reporting and to identify the future prospects of Green accounting and reporting in India in a fast-changing Industrial environment.

RESEARCH METHODOLOGY:

Research Design:

Public and private sector companies that play a vital role in the social responsibility of multifarious nature both have been included in this study. The present study covers only accounting and reporting on green aspects since the liberalization of the economy.

Posted on

A Study on the Impact of TQM Practices with reference to IT Sector

The present study was undertaken with the objective of getting insight into the importance and the effect of quality management in an organization. The study aims to analyze the need for managing quality across various functions of the organization. The study is done at Hyderabad in IT organizations with the employees as the respondents of the study. The sampling technique used was convenience sampling. The respondents were asked to fill out the questionnaires and thus the primary data is collected. Secondary data was collected from various sources like books, survey reports, the web, etc. The study is based on the hypothesis that the organization does not manage quality well.

From the study, it was found that the organization implements total quality management and is thus able to manage well the quality of all the processes. Further, it was found that the employees are not much aware of the TQM in their organization. However, the employees feel that the rules and policies in the organization are not comfortable and it does not support individual efforts.

It is suggested to the organization that the employees should be clearly informed of the quality management system in the organization. The employees should be actively involved in the quality circles and each employee should be communicated with the quality circle meetings, their agenda, etc. Further, the organization should revise its rules and policies in order to make the employees comfortable at work and regular feedback should be taken in order to maintain the whole system effectively

Need for the Study:

Employees are encouraged to innovate TQM links remuneration to customer satisfaction metrics. This study helps the importance of Quality circles and their impact on employee’s productivity which in turn help the organization to achieve its goals.

OBJECTIVES of the study:

  1. To find the degree of TQM implemented in the IT Companies in Hyderabad
  2. To study the level of commitment of employees towards their work in IT Companies in Hyderabad
  3. To analyze the techniques used for maintaining quality in IT Companies in Hyderabad
  4. To study the opinions of employees towards quality management of IT Companies in Hyderabad
  5. To study the impact of TQM on employee performance in IT Companies.

HYPOTHESIS: 

Hypotheses Testing: 

Hypothesis 1:

Null hypothesis: The organization does not manage quality well.

Alternative Hypothesis: The organization manages quality well. 

Hypothesis 2:

Null hypothesis: There is a relationship between quality and employee productivity.

Alternative Hypothesis: There is a relationship between quality and employee productivity.

Research Methodology:

Scope of the Study:

The study focuses on the effective use of TQM in IT Companies. The study is confined to certain factors which are described in quality management in an organization. The study explains the employee efficiency of working and it determines the employee abilities to their work. By benchmarking the performance and setting quality standards when dealing with clients of the companies. 

Research Design: The research design that was used in this research is partly exploratory (secondary data) and partly descriptive (primary Data) in nature.

  • Sampling Procedure: The Employees were randomly selected from the IT Companies.
  • Sample units: Employees of IT Companies having branches in Hyderabad form part of 100 sampling units. The Major five IT Companies taken for the study were as follows:
  1. TCS
  2. Accenture
  3. Infosys
  4. Tech Mahindra
  5. WIPRO
  • Sample size: The sample size of about 100 employees was taken for the Study and divided equally among IT Companies i.e 20 employees each from among five companies (20*5)
  • Data Collection:

Data were collected from employees from different departments in an Organization.

  • Primary Data:

The primary data was collected through a questionnaire. About 100 employees would be taken from four selected IT Companies for the Study.

  • Secondary Data:

The secondary data was collected from HR journals, magazines, textbooks on Management, websites, and other publications.

  • Data analysis
  • A statistical tool such as Cross tabulation, charts, graphs, percentages, and other suitable tools may be used to analyze the collected Data.

Period of the study:  about 45 days

 LIMITATIONS OF THE STUDY:

The following are the Limitations of the Study.

  1. The period of the study is limited to 45 days approximately
  2. As the data was collected during the working hours of the employees, they may not respond promptly.
  3. This research was limited to about 100 Employees of Selected IT Companies in Hyderabad.
  4. The Data collected may become outdated in the future as new TQM practices may be implemented in the future.

CONCLUSION

The project report on Total Quality Management was undertaken with the objective of getting an insight into the importance and the effect of quality management in an organization. The study aims to analyze the need for managing quality across various functions of the organization. The present study focuses on understanding the degree of TQM implemented and the techniques used for maintaining it in the organization. The study aims to find out the opinion of the employees towards quality management in their organization.

The study is done at Hyderabad in IT organizations with the employees as the respondents of the study. The sampling technique used was convenience sampling. The respondents were asked to fill out the questionnaires and thus the primary data is collected.

From the study, it was found that the organization implements total quality management and is thus able to manage well the quality of all the processes. Further, it was found that the employees are not much aware of the TQM in their organization. However, the employees feel that the rules and policies in the organization are not comfortable and it does not support individual efforts.

It is suggested to the organization that the employees should be clearly informed of the quality management system in the organization. The employees should be actively involved in the quality circles and each employee should be communicated with the quality circle meetings, their agenda, etc. Further, the organization should revise its rules and policies in order to make the employees comfortable at work and regular feedback should be taken in order to maintain the whole system effectively.

Posted on

A study on Online Digital Operations with reference to Engineering Colleges Libraries at Hyderabad

RATIONALE OF THE STUDY:

The present study is undertaken with the objective of knowing the digital resources available in Engineering Colleges and its impact on Students learning Methods. The study aims to analyze the need for managing quality education through the use of modern technology in the field of Library science and making Technical education more effective through access to the digital knowledge tools.

OBJECTIVES OF THE STUDY:

  • To Study the scope of Digital Knowledge resources in Engineering College libraries at Hyderabad.
  • To study the use of different Knowledge resources available to the students in Engineering College libraries at Hyderabad.
  • To find out the problems faced by students in accessing and sharing of knowledge.
  • To recommend suitable measures to improve the Knowledge resources by Engineering Colleges.

SCOPE OF THE STUDY

The Scope of the Study is limited to Selected Engineering students to find out the available digital resources and its impact on student learning. 

RESEARCH METHODOLOGY

 RESEARCH DESIGN:

  1. Exploratory Research: This Research will be helpful in Collecting Secondary Data.
  2. Descriptive Research: This Research will be undertaken by collecting primary data using Questionnaire and interviewing Engineering Students from selected Colleges in Hyderabad.

 SAMPLING DESIGN:

Sampling Frame: The sample frame will be taken from among the List of Engineering Colleges located in Hyderabad.

Sampling technique: Convenience sampling

Sample size: 100

Sampling Units: Students from top Engineering Colleges in Hyderabad will form part of Sampling Units. A sample of 100 students from the following Engineering colleges form the Sampling units

  • University College of Engineering, Osmania University (UCE),
  • TKR Engineering College(TKREC)
  • Chaitanya Bharthi Institute of Technology(CBIT)
  • Vasavi College of Engineering and Technology(VCET)
  • Mahatma Gandhi Institute of Technology (MGIT)
  • CSE department, JNTUH.

 DATA COLLECTION:

Primary data: Data to be collected using Questionnaire from among the Top Six Engineering Colleges in Hyderabad.

Secondary data: Data from journals, magazines, books, Newspaper articles, and the internet may form part of the secondary data.

Data Analysis Tools: Charts, graphs, and Tables will be used for analysis.

LIMITATIONS OF THE STUDY:

  • This study is limited to 100 samples from engineering students at Hyderabad.
  • The Study is conducted in Hyderabad city only
  • The study will be limited to a period of 40-50 days approximately.
  • The opinions of the respondents may change over a period of time.

DIRECTIONS FOR FURTHER RESEARCH:

The present study will be a torch bearer for upcoming research students, academicians, and Colleges because nowadays most of the top Engineering colleges are well equipped with digital resources and are playing important role in students learning with e-journals, websites, e-books, and open files.  To Engineering Students, the benefits of these developments are enormous. However, the intensity of our knowledge requirements, and the volume of information potentially available, demand still better ways of organizing and managing library information.

Posted on

A Study on Capital Asset Pricing Model (CAPM) with reference to selected Banking Stocks traded at BSE

 Project synopsis

RATIONALE OF THE STUDY:

The Study on the capital asset pricing model in equity shares of banking companies will be undertaken with the objective of getting an insight into the concept of investments, market risk, security market line, undervalued and overvalued stocks, the risks, and the returns. The study aims to determine the market risk involved in the investments and the factors affecting the market risk and to determine the required rate of returns. The other objectives of the study are to observe the security market line and the degree of volatility of the Banking industry and undervalued and overvalued stocks.

OBJECTIVES OF THE STUDY: 

  • To observe the risk-free rate and evaluate the relationship between risk and return involved in equity share prices of the banking industry.
  • To observe the significant risk of shares (market risk or systematic risk).
  • To observe the relationship between the security market line and the capital market line
  • To develop the inputs required for applying the capital asset pricing model.
  • To produce a benchmark for evaluating various investments and finding out whether the stocks are under or overvalued. 

RESEARCH METHODOLOGY

Method of data collection:

 The Historical data of share prices for the period of one year will be collected from the BSE index for the study.

Source of data

Secondary data will be collected from respective websites like Bseindia.com, Moneycontrol.com, and other financial Journals. 

Period of the study

The study will be done for a period of 30-40 days.

Data analysis tools:

Appropriate data tools like Beta, Mean, and Standard deviation will be used.  

LIMITATIONS OF THE STUDY

  • The study will be based on secondary data only.
  • The study will be limited to banking stocks only
  • The time for the project is limited to 30-40 days

SCOPE FOR FURTHER RESEARCH:

The study covers information related to the equities share of the banking sector. It also covers the systematic risk and unsystematic risks of banking companies. The study is confined to only one Sector i.e., the banking industry, and the entire study is based on their Stock prices for a period of the last two years. The present study gives an insight into this issue by analyzing the capital asset pricing model Analysis in Equity share prices of the Banking industry.

Posted on

A Study on Consumer buying behaviour with reference to Amazon.in

RATIONALE OF THE STUDY: 

  • To study the consumer buying experience at Amazon.in in Hyderabad.
  • To identify opportunities and the interest of the buyers towards online retailing transactions at Amazon.in
  • To understand the offers and discounts provided by Amazon.in
  • To study the problems and dissatisfaction that may be experienced by the customers Amazon.in.

OBJECTIVES OF THE STUDY:

1. To study the consumer buying behaviour towards Amazon.in in Hyderabad

2. To know the factors that influences the Consumers to do purchasing from Amazon.in.

3. To find out the problems faced by young consumers in buying online retail products from Amazon.in.

4. To come out with suitable suggestions towards making online purchases at Amazon.in.

SCOPE OF THE STUDY:

The scope of the study is limited to the buying behaviour of consumers at Hyderabad who do online shopping from Amazon.in. The Main reason of the present study is to find out the online retailing experience of the consumers and their attitude and satisfaction levels. The study also focuses on factors that influence in doing online shopping at Amazon.in and the problems faced by them during placing the order and receiving the product.

RESEARCH METHODOLOGY:

a) RESEARCH DESIGN:

Both Descriptive and exploratory research will be used for this project study. The research of this study involves in both field survey& literature survey, to identify the scope & potential marketing challenges of purchasing from Amazon.in.

Nature of the Data: Primary & secondary data will be used in this project study

Primary data: The descriptive research will be conducted by using primary data which will be collected through the personal interviews using questionnaire as a data collection tool, to identify the scope of retail ecommerce business in India. The primary data is accurate & highly reliable in nature.

Field Study: Field study will be used to collect the primary data from the sample trough the interviews by using questionnaire as data collection tool.

Secondary data: The exploratory research will be conducted by using secondary data which will be collected from various published sources such as retail and e-commerce Journals such as International journal of electronic commerce, Indian Journal of retailing, Indian Journal of Marketing, E commerce magazines, Business Magazines Text books on Retail Management, E-commerce and websites on online retailing and Amazon.in.

b) SAMPLING DESIGN:

Sampling Frame: The Sampling frame will be taken from the population residing in urban Areas in Hyderabad.

Sample Size: The study will be conducted on a sample of 100 Consumers who are frequent buyers from Amazon.in from Hyderabad city.

Sample units: The sample units will be taken from among the 100 consumers residing in selected areas in Hyderabad. The Consumers who are making their online purchases from Amazon.in may be considered for the study.

Sampling Method: This study will be undertaken by using Convenience and Area sampling.

Data Analysis: Charts, tables and percentage analysis will be used for the study.

LIMITATIONS OF THE STUDY: 

  • The primary data will be collected only from online buyers. 
  • The survey will be conducted in only in Hyderabad city only. 
  • The data will be collected only from the urban consumers, who might be aware of the process of online transactions & have their own bank accounts.
  • The views and opinions of the respondents may change over the period of time.

DIRECTION FOR FURTHER RESEARCH: At present there is a lot of demand for online purchasing. The present study will focus on the purchasing behaviour towards Amazon.in and finding out suitable solutions to make purchasing more interesting and will be a torch bearer for future researchers and online retailing companies can benefit from such survey.

Focusing on the post-purchase experience is the next frontier for online retailers. Now, retailers are extending the customer hand-holding postpurchase with beautiful branded interfaces, delivery visibility, and personalized content. By streamlining customers’ paths to purchase and bringing them back directly into the loyalty loop, brands can convert one-time shoppers into lifelong brand advocates.

Posted on

Latest CSE Python Projects on ML & AI – 2022

These are the Latest CSE Python Projects on Machine Learning, Deep Learning, Artificial Intelligence, Big Data, Blockchain Technology, Cloud Computing, Data Mining, Networking, Network Security, and Cyber Security domains.

Download the Projects List Here – Python Projects on ML & AI – 2022

Python Projects List – 2022

These are the latest Python Machine Learning & Deep Learning projects for the year 2022.

  1. Characterizing And Predicting Early Reviewers For Effective Product Marketing On Ecommerce Websites
  2. Semi-Supervised Machine Learning Approach For DDoS Detection
  3. 5g-Smart Diabetes Toward Personalized Diabetes Diagnosis With Healthcare Big Data Clouds
  4. Credit Card Fraud Detection Using Random Forest & Cart Algorithm
  5. Driver Drowsiness Monitoring System Using Visual Behaviour And Machine Learning
  6. E-Assessment Using Image Processing In ∞Exams
  7. Automating E-Government Using Ai
  8. Eye Ball Cursor Movement Using OpenCV
  9. Filtering Instagram Hashtags Through Crowdtagging And The Hits Algorithm
  10. Converging Blockchain and Machine Learning for Healthcare
  11. Suspicious Activity Detection
  12. Use Of Artificial Neural Networks To Identify Fake profiles
  13. Video-Based Abnormal Driving Behaviourdetection Via Deep Learning Fusions
  14. Crop Yield Prediction And Efficient Use Of Fertilizers
  15. Fake Images Detection
  16. Opinion Mining For Social Networking Sites
  17. Image Classification Using Cnn (Convolution Neural Networks) Algorithm
  18. Cyber Threat Detection Based On Artificial Neural Networks Using Event Profiles
  19. Analysis Of Women’s Safety In Indian Cities Using Machine Learning On Tweets
  20. Construction Site Accident Analysis Using Text Mining And Natural Language Processing Techniques
  21. Performance Comparison Of SVM ,Random Forest, And Extreme Learning Machine For Intrusion Detection
  22. Accident Detection System
  23. A Data Mining-Based Model For Detection Of Fraudulent Behaviour In Water Consumption(Standalone)
  24. Detection Of Lung Cancer From Ct Image Using Svm Classification And Compare The Survival Rate Of Patients Using 3d Convolutional Neural Network(3d Cnn)On Lung Nodules Data Set
  25. Automatic Facial Expression Recognition Using Features Extraction Based On Spatial & Temporal Sequences Using Cnn & Rnn Algorithm
  26. Facial Expression Recognition And Their Temporal Segments From Face Profile Image Sequences Using Yolo Object Detection Algorithm
  27. Cartoon Of An Image
  28. Bird Species Identification Using Deep Learning
  29. A Deep Learning Facial Expression Recognition Based Scoring System For Restaurants
  30. Seer Cancer Incidence Using Machine Learning With Data Analysis
  31. Loan Prediction Dataset Using Machine Learning With Data Analysis
  32. User-Centric Machine Learning Framework For Cyber Security Operations Center
  33. Recolored Image Detection
  34. Robust Malware Detection For IoT Devices Using Deep Eigenspace Learning
  35. Modeling And Predicting Cyber Hacking Breaches
  36. Image-Based Appraisal Of Real Estate Properties
  37. Heart Disease Prediction
  38. Crop prediction using machine learning
  39. Face mask detection using artificial intelligence
  40. Facial attendance system using artificial intelligence
  41. Skin disease prediction using deep learning
  42. Fruit disease prediction using deep learning
  43. Malaria disease prediction using deep learning
  44. Phishing email detection using convolutional neural network
  45. Type 2 diabetes prediction using machine learning
  46. Suicidal tweets detection using machine learning
  47. web community questions and answering
  48. currency recognize system using artificial intelligence
  49. Fake news Detection using machine learning
  50. Detection of fake online reviews using semi-supervised and supervised learning
  51. mobile price prediction using machine learning
  52. Vigorous malware detection for the internet of things devices using machine learning
  53. Estimating the price of houses using machine learning
  54. Predicting the strength of the concrete pillars used in industrial infrastructure
  55. Passive Aggressive Classifier for Detection of Encrypted VPN
  56. speech emotion recognition using mlp algorithm
  57. face emotion recognition system using artificial intelligence
  58. Data Analysis by Web Scraping using Python
  59. A Decision Tree-based Recommendation System for Tourists
  60. A Machine Learning Model for Average fuel consumption in Heavy Vehicles
  61. Density-Based Smart Traffic Control System UsingCanny Edge Detection Algorithm for CongregatingTraffic Information
  62. Image Classification Using CNN (Convolution Neural Networks) Algorithm
  63. Prudent Fraud Detection in Internet Banking
  64. Twitter sentimental analysis
  65. Android malware detection using Machine learning techniques
  66. Missing Child Identification System using DeepLearning and Multiclass SVM
  67. Emotion-Based Music recommendation system
  68. Stress Detection in IT Professionals
  69. Cryptocurrency Price Analysis with Artificial Intelligence
  70. Object detection using artificial intelligence
  71. Using Deep Learning to Predict Plant Growth and Yield in Greenhouse Environments
  72. Human Activity Recognition
  73. Deep Learning Model for Detecting COVID-19 on Chest X-Ray Using Convolutional Neural Networks
  74. Encryption And Decryption Algorithm Based On Neural Network
  75. FAMD: A Fast Multi-feature Android Malware Detection Framework, Design, and Implementation
  76. Image Super-Resolution using Convolution Neural Networks and Auto-encoders
    Lip Reading using Neural Networks and Deep learning
  77. Image Segmentation with Mask R-CNN
  78. Open Pose: Real-time Multi-Person 2D Pose Estimation using Part Affinity Fields
  79. Tuning Malconv: Malware Detection With Not Just Raw Bytes
  80. A Hybrid Fuzzy Logic-based Deep Learning Approach for Fake Review Detection and Sentiment Classification of Amazon Food Reviews
  81. News Text Summarization Based on Multi-Feature and Fuzzy Logic
  82. An Android Malware Detection Approach Based on SIMGRU
  83. Access Control and Authorization in Smart Homes: A Survey
  84. Spam Detection for Youtube Comments
  85. Animal Classification using Facial Images with Score-Level Fusion
  86. An Enhanced Anomaly Detection in Web Traffic Using a Stack of Classifier Ensemble
  87. Automatic Corpus Creation and Annotation for Natural Language Processing of Telugu
  88. Blockchain for Secure EHRs Sharing of Mobile Cloud-Based E-Health Systems
  89. CaptionBot for Assistive Vision
  90. A joint multi-task CNN for cross-age face recognition
  91. Cyber security Tools for IS Auditing
  92. Cyber Threat Detection Based on Artificial Neural Networks Using Event Profiles
  93. A Deep Learning Approach for Effective Intrusion Detection in Wireless Networks using CNN
  94. Digital Image Encryption Algorithm Based on Elliptic Curve Public Cryptosystem
  95. Toward Universal, Word Sense Disambiguation Using Deep Neural Networks
  96. An Expert System for Insulin Dosage Prediction
  97. An Efficient Gait Recognition Method for Known and Unknown Covariate Conditions
  98. Self-Diagnosing Health Care Chatbot using Machine Learning
  99. Machine learning Models for diagnosis of the diabetic patient and prediction insulin dosage
  100. An Improved Approach to Movie Recommendation System
  101. Efficient Privacy-Preserving Machine Learning for Blockchain Network
  102. Sentiment Analysis to Classify Amazon Product Reviews Using Supervised Classification Algorithms
  103. A Deep Learning Approach for Effective Intrusion Detection in Wireless Networks using CNN
  104. SE-Enc: A Secure and Efficient Encoding Scheme Using Elliptic Curve Cryptography
  105. Secure Image Transmission Using Chaotic-Enhanced Elliptic Curve Cryptography(JAVA)
  106. Predicting Stock Market Trends Using Machine Learning and Deep Learning Algorithms Via Continuous and Binary Data a Comparative Analysis
  107. Multimedia summarization
  108. Quality Risk Analysis for Sustainable Smart Water Supply Using Data Perception
  109. Android Permission Control App(ANDROID)
  110. Increasing the Performance of Machine Learning-Based IDSs on an Imbalanced and Up-to-Date Dataset
  111. Fake Image Identification
  112. Non-Binary Image Classification using Convolution Neural Networks
  113. Robust Intelligent Malware Detection Using Deep Learning
  114. Construction site accident analysis using text mining and natural language processing techniques
  115. Cyber Threat Detection Based on Artificial Neural Networks Using Event Profiles
  116. Data Recovery
  117. Context-Based Image Processing Using Machine Learning Approaches
  118. A Knowledge-Based Recommendation System That Includes Sentiment Analysis and Deep Learning
  119. Robust Intelligent Malware Detection Using Deep Learning
  120. Rossman Stores Sales Prediction
  121. A Driving Decision Strategy (DDS) Based on Machine learning for an autonomous Vehicle
  122. A Machine Learning-Based Lightweight Intrusion Detection System for the Internet of Things
  123. A Model for prediction of consumer conduct using a machine learning algorithm
  124. An automatic garbage classification system based on deep learning
  125. Detection of fake online reviews using semi-supervised and supervised learning
  126. Forensic Scanner Identification Using Machine Learning
  127. Use of Artificial Neural Networks to Identify Fake Profiles
  128. Analysis and Prediction of Industrial Accidents Using Machine Learning
  129. Credit Card Fraud Detection Using Random Forest & Cart Algorithm
  130. Identification of covid-19 spreaders using multiplex networks approach
  131. Object Tracking Using Python from Video
  132. Software Defect Estimation Using Machine Learning Algorithms
  133. MamaBot: A System Based on ML and NLP for Supporting Women and Families during Pregnancy
  134. Deep Texture Features for Robust Face Spoofing Detection
  135. Prediction of loan eligibility of the customer
  136. Using Deep Learning to Predict Plant Growth and Yield in Greenhouse Environments
  137. A Malware Detection Method for Health Sensor Data Based on Machine Learning
  138. Blood Cell Types Classification Using CNN
  139. Feature extraction for classifying students based on their academic performance
  140. Hazard Identification and Detection using Machine Learning Approach
  141. Effective Heart Disease Prediction using Hybrid ML Algorithms
  142. Noise Reduction in Web Data A Learning Approach Based on Dynamic User Interests
  143. Online Book Recommendation System by using Collaborative filtering and Association Mining
  144. Sentiment Analysis Using Telugu SentiWordNet
  145. Soil Moisture Retrieval using Groundwater Dataset using Machine Learning
  146. A Time-Series prediction model using long-short-term memory networks for the prediction of Covid – 19 data
  147. Detection of Cyber Attacks in Network using Machine Learning Techniques
  148. Duplicate Question Detection with Deep Learning in Stack Overflow
  149. Machine Learning Techniques Applied To Detect Cyber Attacks On Web Applications
  150. Performance Analysis and Evaluation of Machine Learning Algorithms in Rainfall Prediction
  151. A Machine Learning Model for Average Fuel Consumption in Heavy Vehicles
  152. Accident Detection
  153. BAT Deep Learning Methods on Network Intrusion Detection Using NSL-KDD Dataset
  154. Online Book store
  155. Data Poison Detection Schemes for Distributed Machine Learning
  156. Detecting At-Risk Students With Early Interventions Using Machine Learning Techniques
  157. Detection of Possible Illicit Messages Using Natural Language Processing and
    Machine Learning-Based Approaches for Detecting COVID-19 using Clinical Text Data
  158. Personalized effective feedback to address students’ frustration in an intelligent tutoring system
  159. Research on Recognition Model of Crop Diseases and Insect Pests Based on Deep Learning in Harsh Environments
  160. Smart contract-based access control for health care data vehicle Pattern Recognition using Machine & Deep Learning to Predict Car Model
  161. Analysis of Women’s Safety in Indian Cities Using Machine Learning on Tweets
  162. Analyzing and estimating the IPL winner using machine learning
  163. Characterizing and predicting early reviewers for effective product marketing on eCommerce websites
  164. Crime Data Analysis Using Machine Learning Models
  165. Detection of fake online reviews using semi-supervised and supervised learning
  166. Detection of Malicious Code Variants Based on Deep Learning
  167. Detection and classification of fruit diseases using image processing & cloud computing
  168. Grape Leaf Disease Identification using Machine Learning Techniques
  169. Effective Heart Disease Prediction Using Hybrid Machine Learning Techniques
  170. Missing Child Identification System using Deep Learning and Multiclass SVM
  171. Music & Movie Recommendation
  172. Network Intrusion Detection using Supervised Machine Learning Technique with Feature Selection
  173. Prediction of Hepatitis Disease Using Machine Learning Technique
  174. Skin Disease Detection and Classification Using Deep Learning Algorithms
  175. Spammer Detection and Fake User Identification on Social Networks
  176. Using Deep Learning to Predict Plant Growth and Yield in Greenhouse Environments
  177. Using Data Mining Techniques to Predict Student Performance to Support Decision
  178. Making in University Admission Systems

Latest CSE Python Projects on ML & AI – 2022

  1. An automated system to limit COVID-19 using facial mask detection in a smart city network
  2. Analysis and Prediction of COVID-19 using Time Series Forecasting
  3. Analysis and prediction of occupational accidents
  4. Analysis of Women’s Safety in Indian Cities Using Twitter Data
  5. Artist Recommendation System using Collaborative Filtering
  6. A-Secure-Searchable-Encryption-Framework-for-Privacy-Critical-Cloud-Storage-Services
  7. Authorship Identification Using Text Mining
  8. Automated word prediction in Telugu language using a Statistical approach
  9. Biometric Steganography Using Mid Position Value Technique
  10. Classification of COVID-19 Using Chest X-ray
  11. Covid-19 future forecasting
  12. Covid19 Social Distance Monitoring System Using YOLO
  13. Credit Card Fraud Detection
  14. Detection and Classification of Fruit Diseases
  15. Diabetic Retinopathy Detection
  16. Early prediction of Diabetes Mellitus using intensive care data to improve clinical decisions
  17. E-Certificates Issue Services Using Blockchain
  18. Face to Emoji using OpenCV and haar cascade classifier
  19. Facial Emotion Recognition using ML Algorithms
  20. Fake Job Recruitment Detection
  21. Fusion Approach to Infrared and Visible Images
  22. High-value customers identification for an E-Commerce company
  23. Image Caption And Speech Generation Using LSTM and GTTS API
  24. Image Deblurring
  25. IoT based Attendance System using Blockchain
  26. Malicious Application Detection Using Machine Learning
  27. Money Laundering Detection Using Machine Learning Methods
  28. Music Genre Classification using ML algorithms
  29. Object Detection and Alert System for Visually Impaired People
  30. Object detection and localization
  31. Offline Signature Forgery Detection
  32. People count on Surveillance Video
  33. Politeness Transfer A Tag and Generate Approach
  34. Prediction Analysis Using Support Vector Machine In Cardiovascular Ailments
  35. Product Recommendation System Using ML Technique
  36. Rice Crop Disease Detection
  37. Sign Language Translator for Speech Impaired
  38. Skin Lesion Classification
  39. StellarStudent Social Web Application for Colleges
  40. Survival of Heart Failure Prediction Using Feature Scaling
  41. Text Summarization Method
  42. Text to Image Generator using GAN
  43. Vessel detection from spaceborne images
  44. HR Analysis of Employee Attrition & Performance
  45. Analysis of Forest Fire Area Prediction
  46. Prediction of Chronic Kidney Disease Using Machine Learning
  47. Predicting the Resale Price of a Car
  48. Prediction Of Diabetes Mellitus
  49. Prediction of Exact Niche using Bank Data
  50. Prediction of Insurance Claims using Health Analysis
  51. Sales Prophesy in Business using ML
  52. Prediction Of Taxi Fare Using Exploratory Analysis
  53. Prediction of customer churn in the telecom industry
  54. Estimation Of Wine Quality Using Chemical Analysis Data
  55. The Simpsons Character Recognition
  56. IMDB Movie Review Analysis Using Bidirectional LSTM
  57. Pattern Recognition of IRIS Flower based on Artificial Intelligence
  58. Recommendation System
  59. Zomato Review System
  60. Drug Review Prediction
  61. Web Traffic Prediction
  62. Building a Model for MNIST Dataset using Convolutional
  63. Toxic Comment Detection
  64. Sonar Prediction
  65. Accuracy analysis using Fashion MNIST dataset
  66. Survival Analysis Of Diabetes
  67. Wine Quality Prediction
  68. Bank Churn Model
  69. Survival Analysis (Human Breast Cancer Prediction)
  70. Black Friday Sales Data Analysis Prediction
  71. Bank Marketing
  72. Breast Cancer Classification
  73. Company Turnover Predictor
  74. Pneumonia Prediction
  75. Employee Attrition Prediction
  76. Intelligent Album Creator
  77. Predicting The Readmission To Hospitals For Diabetic Patients
  78. Communication Through Gesture
  79. Twitter Sentiment Analysis
  80. Smart Security System Using Image Recognition
  81. Text Generation
  82. Crop Health Assistant using Artificial intelligence
  83. Air Quality Prediction
  84. Suspicious activity Detector
  85. Watch Bot
  86. Pneumonia Detection Using CNN
  87. Sentiment analysis of Twitter comments
  88. Motor Health Prediction
  89. Real or fake face Detection
  90. predicting simpson Characteristics
  91. The Sorting Hat
  92. Analysis of Airline reviews using NLP
  93. Heart Disease Prediction
  94. Cereal Analysis
  95. Fertilizer Prediction
  96. Turbine power prediction
  97. Kidney Disease Analysis
  98. Analysis of Accidents in 2017
  99. A Machine Learning Approach to Predict Crime Rate Analysis
  100. Advertising Based on Usage
  101. Life Expectancy
  102. Abalone Age Prediction
  103. Exploring the Bitcoin Cryptocurrency
  104. Predicting High Potential Employees and Employees at Risk
  105. Insurance Purchase Prediction
  106. MNIST Classification using CNN
  107. Vehicle resale value Prediction
  108. University Admission Prediction
  109. Automatic Challan Generation
  110. Smart investment Prediction
  111. Smart Security using Artificial Intelligence
  112. Bike Buyer Prediction
  113. Best Crop Prediction
  114. Taxi Fare Prediction
  115. Resale Values of Predicting Cars
  116. Power Consumption Prediction
  117. Health Insurance Prediction
  118. Health Monitoring System
  119. Crime Rate Prediction
  120. Assert Failure Prediction
  121. Adult Census Income Prediction Using Random Forest
  122. Smart Predictors
  123. Nutrition Analysis Using Image Classification
  124. Liver Patient Analysis
  125. Flood Prediction
  126. Customer Recommendation System
  127. Crop Protection Using Deep Learning Techniques
  128. Communication Using Gestures
  129. Car Performance Prediction
  130. Avalanche Prediction
  131. 3D Printer Material Prediction
  132. Income Prediction Using Random Forest
  133. Term Deposit Subscription Prediction
  134. Advertisement popularity Prediction
  135. Google Review of Places Certificates
  136. Blood Cell Image Prediction