RP

RESEARCH PROJCT

Aim
 “To identify factors affecting employee’s retention and its impact on performance
of organization: A study on Hilton Hotel”
Objectives
 To understand conceptual framework of employee’s retention and turnover
 To identify factors that impacts on employee’s satisfaction and enhance turnover
rate in Hilton Hotel.
 To examine relationship between employee’s retention and company’s
performance.
 To find strategies that can help in improving retention rate of workers.
Aim and Objectives

 Present study is qualitative in nature thus, researcher has used inductive
research approach
 Individual has used questionnaire technique to find out factors that
enhance employee turnover rate and its impact on overall performance of
organization.
 This is considered as the best method because an individual is able to find
out real facts related to employee retention and its impact on company’s
performance
Research Methods

3
7
2
3
Less than 1 year
1-2 year
3-5 year
More than 5 year
Theme 1: Time length of working in organization

Poor wages
Inflexible working hours
Strict regulation
Frequent changes in
practices
0 1 2 3 4 5 6
4
5
4
2
Series1
Theme 2: Major factor that creates difficulty
for you to perform their duties well

Highly satisfied Satisfied Dissatisfied Highly dissatisfied
0
1
2
3
4
5
6
7
8
2
3
7
3
Series1
Theme 3: satisfied with current working
environment of Hilton Hotel

5
3
7 Yes
No
Sometimes
Theme 4: Do you get incentives or
rewards in your organization

6
3
5
1
Good salaries
Flexible working hours
Involvement of employees in decision
making
Training and development
Theme 5: Strategy that you feel happy
and can hold you in company for longer
duration

Aruna, M. and Anitha, J., 2015. Employee retention enablers: Generation Y
employees. SCMS Journal of Indian Management. 12(3). pp.94.
Beynon, M. J. and et.al., 2015. Investigating the impact of training influence
on employee retention in small and medium enterprises: a regression‐type
classification and ranking believe simplex analysis on sparse data. Expert
Systems. 32(1). pp.141-154.
REFERENCES