Research Paper:
HR analytics using R-machine learning algorithm
- Multiple linear regression analysis
Author: Dr.A.M.Mahaboob Basha
Research Paper Published on:
03 January 2021
Team Presentation
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Muskan Kothari�A041
Siya Gupta�A001
Priyangi Jain�A013
Tanya Sabharwal�A021
Ananya Sharma�A016
Introduction
It provides new insights to readers and analysis not published by any other.
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Literature Review
M R S Surya Narayana Reddy et al
Lot of influence by existing HRD practices on employee performance.
Federici et al
Investigate whether career planning and development will enhance the performance of employee.
Lina Hamdan Mahmoud Al-Abbadi
Employee commitment and dedication mediates the significant positive impact on employee performance.
Srinibash Dash & Uma Charan Patti
HRM is a continuous process and contemporary issues need to be handled.
Employee growth and high performance in IT companies.
Zeinab Inanlou & Ji-Young Ahn
Communication, trust, commitment, innovativeness, participation, employee training are positive influences.
Jae Young Lee et al
Top management assistance, employee attitude, employer – employee reationships plays significant role.
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Literature Review
Sagwa et al
Mediating role of employee outcomes plays a significant role in HRMP and firm performance.
Tehmina Sattar et al
Employee engagement role between job satisfaction and job perofrmance.
Vermeeran B et al
HR practices are directly and indirectly linked to financial, organisational and human resource outcomes.
Ahmed Mohammed Sayed Mustafa & Julian Seymour Gould-Williams
High performance HR practices have positive influence.
Daniel Eseme Gberevbie
Strategic HR practices enhances employee competency.
Rebecca R Kehoe & Patrick M Wright
Strategic HR development practices influence firm level performance.
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Research Objective
1.
To know the impact of various HRD practices and its impact on predictor (job satisfaction).
2.
To make effectiveness in the decision making process of human resource management.
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Research Methodology
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Research Methodology
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Important terminology
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Exploratory Data Analysis and Interpretation
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Data Validation Test
Scatter Plot Matrix
All variables show positive relationship towards employee job performance.
All the independent variables show strong relationship with employee job performance.
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Corrgram
Here, almost all variables show positive relationship.
Here, maximum variables showed positive tendency with the job performance.
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Standardized Residuals
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The point 266 is an outlier and will impact the regression value.
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Normal Q-Q Plot
Here we can see that the data is normally distributed .
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Standardized residuals
with fitted value
The scale value shows that all independent variables influence EJP and all points are concentrated in the middle.
Correlation Matrix Plots
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Employee Job Performance and Employee Compensation
Higher the compensation, higher will be the employee job performance. Almost all variables have shown the positive tendency towards, employee job performance.
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Employee Job Performance and Training and Development
Employee job Performance is positively associated with the training and development.
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Employee Job Performance and Coaching and Counseling
The scatter plot matrix and the coaching & counseling showed positive tendency in the analysis.
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Employee Job Performance and Performance Appraisal
We can conclude that the employee performance depends on the employee performance appraisal.
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Employee Job Performance and Career Planning and Development
The straight line shows neutral tendency, that is, employee job performance is slightly being influenced by career planning and development.
Conclusion
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Limitations
1.
The employee data sets available in the industry are often noisy and sparse.
2.
Statistics are not sufficient to deal with individuals.
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3.
Machine learning is not necessarily the best tool.
Future Scope
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Future Scope
Algorithm is an effective tool to:
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Thank you !
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