Wednesday, 20 November 2019

Application Of Factor Analysis In Job Satisfaction Of Employees In IT Companies

  Mr Maheshkumar Mohite, Dr R V Kulkarni, with title "Application Of Factor Analysis In Job Satisfaction Of Employees In It Companies" Published in "International Journal of Scientific & Engineering Research Volume 10, Issue 11, November-2019 Page Number 749- 759 ISSN 2229-5518" http://www.ijser.org

Abstract:

 

Employees from IT companies are facing various problems in his or her job that’s an effect on job satisfaction. Technical companies are struggling to secure his or her employees happiness and own business life. Employees are the backbone of any organization. Employers are always thinking about the employee. The present research paper highlighted factors influenced on Job satisfaction of employees and know level of job satisfaction of employees. Factor analysis statistical method used for data analysis. This Research concentrated on gender-wise factor which is influenced by job satisfaction. Employee means respondents are working in Information Technology companies. The researcher has selected 370 respondents from selected IT companies of Kolhapur city as a sample for the study; Adopted Convenience and simple random sampling technique; Primary data and secondary data used for this research.  Collected data was analyzed, interpreted with the help of suitable statistical tools such that factor analysis, percentage, mean, etc. Research Result shows that level of job satisfaction of employee and important factor which are influenced on (or an effect on) job satisfaction of employees.

Key Words: factor analysis, job satisfaction in gender-wise, application of factor analysis

Introduction:

Job satisfaction is the focal point of all companies for internal and external growth. In today’s globalized era, it has become very difficult to maintain customers of IT Companies. Needs and expectations differ from customer to customer, employee to employee, employee to employer and employee to customer. Upgraded Information Technology expectations are increasing day by day. Technical Employees and Employers are under pressure. Lots of computation found in IT business. Indian Technical industry has been witnessing severe competition and rapidly changing business. Everyday winning in the modern business world is the most important role handled by IT employees. It has resulted in increased expectations of smart consumers and customers. Job satisfaction most essentials to every company. IT companies are always run satisfaction surveys for the company’s growth. In this research paper, the researcher has studied factors showing Job satisfaction of Employee.

Objective:

 

·         To know the level of job satisfaction of employees in IT Companies

·         To identify the factor influenced on Job Satisfaction of employees (gender-wise) using factor analysis.

Methodology:

 

The Descriptive research methodology was selected to discover the important factors of Job satisfaction from Information Technology employees. Respondents or employees from selected IT companies of Kolhapur City.  The author has explored job satisfaction factors. Hence, the present research is exploratory. The primary data has been gathered through a simple random & convenience sampling method used. To accomplish the stated objective primary data was collected through a self- designed structured questionnaire. The questionnaire comprises a scale to assess the factors in terms of employee prefer. The study is conducted in selected IT companies in Kolhapur city. The employees from these and willing to fill up the questionnaire (include a demographic question gender, the highest qualification, 48 statements by five-point Likert Scale for observation, etc) is the sample unit under the study. The Researcher has used the combination of MSQ and Job Satisfaction Survey to identify and measure the level of Job Satisfaction. Single Global Rating & Summation Job facets used to reach the research objective. Secondary data collected through review article, books, blogs, etc. Total of 370 respondents have filled the questionnaire, and it is the sample size of the study. Suitable statistical tools have been applied to analyse the collected data such as percentages, averages, factor analysis, with the help of SPSS, MS Excel, XLStat application software. Project Duration: 10 January 2018 to 10 July 2019

 

Theoretical background:

 

(1)  Locke in 1969, 1976 was defined job satisfaction as "a pleasurable or positive emotional state resulting from the appraisal of one's job or job experiences.”

(2)  Author1 stated in the article title ’Human Resources Management Practices in Modern World’ that “Modern Human Resources (M-HR) was defined bringing clarity, simplicity, enhancing, maintaining, capturing, assigning & caring human in personal, organisation and within organisation. M-HR aim is trying to fulfill requirement of employee, employer, upcoming candidate and unselected candidate.” Again he was explained, “Modern Human Resources Management (M-HRM) is a process of bringing people, employee, employer, unselected candidate, and organisation and other than organisation together so that the goals, mission and objectives of each are met. M-HRM focusing systematically, effectively manages, maintain, control, develop human.” It was designed to maximize employee performance for organizations and country

(3)  Author1 stated in the article title ‘Job Satisfaction Factors of Employee in Virtual Workplace: Review’ stated that there was following important Factors that influenced on job satisfaction which are Place, Work, Time, Stress, Gender, Age, Experience, Immediate superior, Relationship, Communication, Technology, Payment, Policy, Security, Responsibility, Personal, dependency, Guidance, Achievement, Traveling, Social, Status, Trust, Feedback, Help, Psychology and Law

(4)  Article shared by venkatesh was reviewed definition of Fieldman and Arnold told that Job satisfaction will be defined as the amount of overall positive effect or feeling that has been individuals and it will  towards their jobs. Andrew Brin has defined Job satisfaction is the amount of pleasure or contentment associated with a job. If you like your job intensely, you will experience high job satisfaction also told that If you dislike your job intensely, you will experience job dissatisfaction. The Author told that organizational, work environmental; work itself and personal factor effect on Job satisfaction.

(5)  Factor analysis and Reliability Analysis: “Both are statistical techniques used to reduce a larger set of measured items (i.e, observed variables) into a smaller set of latent constructs. According to study, firstly use factor analysis to organize the items into constructs and then use reliability analysis to determine how well each construct holds together”. According to review ‘Majority Researchers typically use factor analysis first to organize the items into constructs and then use reliability analysis to determine how well each construct holds together also be sure reliability of items that must be reliable’

(6)  Principal Component Analysis used for data reduction. It requires a large sample size. Varimax with Kaiser Normalization was used to reduce groups of variables to theoretically important latent variables.

(7)  Factor Loading & Name assigning to the factor: Researchers1 Study told that the higher the absolute value of the loading, the more the factor contributes to the variable. Firstly, looked or see the all content of variable (in simple say items or observed statements)  that load onto the same factor to trying to identify more common themes if available, otherwise items measured highly correlated to provide reasonable bases for factor name decision and secondly, check all items reliability of each component by statistics test. Items must be reliable during factor name assigned.

(8)  Kaiser-Meyer-Olkin Measure did for Sampling Adequacy (considered 0.5 above value for adequacy) (According to study 0.00 to 0.49 unacceptable, 0.50 to 0.59 miserable, 0.60 to 0.69 mediocre, 0.70 to 0.79 middling, 0.80 to 0.89 meritorious, 0.90 to 1.00 marvelous.) & Bartlett’s Test of Sphericity (if Sig. p < 0.05, rejection of hypothesis). Both of these Test indicates that data is suitable for conducting factor analysis.

(9)  According to Marsh, H. W., Morin, A. J., Parker, P. D., & Kaur, G. (2014) Advantage of Factor analysis is resolving the common problem, in real contexts, of non-zero cross-loading and Disadvantages of factor analysis is Fit indexes, data-drive structure without theory, problems with measurement errors, you can´t include common variance of the method and, most important, it can´t be used to test structural equation models.

 

Data analysis and interpretation:

 

Data was collected & then after it is analyzed and interpreted as,

 

(a) Table 1 Showing Demographic Analysis

 

Variable

F

%

1

Gender

Male

166

45 %

Female

204

55 %

2

Highest Qualification

Polytechnic Diploma

39

11 %

Graduate

175

47 %

Post Graduate

108

29 %

Doctorate (Ph.D.)

27

7 %

Technical Courses

21

6 %

 

Interpretation 1:

 

Out of 100% of respondent Male employees were 45% and Female employees were 55%. Majority of female employees are more. Qualifications of Respondents with Polytechnic Diploma are 11 %, Graduate are 47 %, Post Graduate are 29 %, Doctorate (Ph.D.) are 07 %, and Technical Courses are 6 %. Maximum Graduated respondents are working in IT companies.

 

(b) Table 2 Showing Male & Female and Overall Responses with the percentage.

 

Respondent

Counted Received response from respondents

Total

SD

D

U

A

SA

Male

41 (25%)

47 (28%)

12 (7%)

45 (27%)

21 (13%)

166 (100%)

Female

62 (30%)

67 (33%)

6 (3%)

43 (21%)

26 (13%)

204 (100%)

Overall

103 (28% )

114 (31%)

18 (5 %)

88 (24%)

47 (13%)

370 (100%)

Source: Primary Data |

 

Interpretation 2:

Out of 370 (100%) Male 166 (45%) and Female 204 (55%) responded.  Female respondents are more than male employees. Respondent was responded 103 (28% ) as SD, 114 (31%) as D, 18 (5 %) as U, 88 (24%) as A and 47 (13%) as SA with summation from observed statements. The Majority of respondents show below disagree responded with statements, which means respective observed statements are important for satisfaction. Note that decided score such as, ‘1: Strongly Dissagree (SD)’,’2: Disagree (D)’,’3: Undecided (U)’,’4: Agree’ (A), ‘5: Strongly Agree (SA)’.

(c) Table 3 Showing Male & Female and Overall Responses, mean, Standard Deviation

.

 Q

No

Observation / Items / Questions /Statements

Male

Female

Overall

M_N = 166

F_N = 204

N = 370

Mean

SD

Mean

SD

Mean

SD

1

Pays & Benefits Comparing With Other IT Company

2.16

1.19

1.91

0.99

2.02

1.09

2

Present Salary, Wages

2.08

1.17

1.75

0.96

1.90

1.07

3

Co-workers Help

3.12

1.42

2.83

1.51

2.96

1.48

4

Team Members Support

2.24

1.11

2.05

1.03

2.14

1.07

5

Its Ok Job In Itself

2.19

1.20

1.79

0.96

1.97

1.09

6

Sufficient Info For Work

2.58

1.33

2.26

1.21

2.40

1.27

7

Supervisor Help

2.27

1.22

1.84

0.91

2.04

1.08

8

Other Departmental Supervision

3.06

1.36

2.89

1.38

2.97

1.38

9

Employee Policy Is On Paper Only

3.75

1.20

3.83

1.20

3.80

1.20

10

T & C Of Customer

2.91

1.36

2.61

1.37

2.75

1.37

11

Team Members Trust

2.51

1.31

1.99

1.10

2.22

1.22

12

Listening With Each Other By Work Members

2.27

1.21

2.03

1.07

2.14

1.14

13

Physical Working Condition At Work

2.29

1.23

1.83

1.09

2.04

1.18

14

Physical Working Condition In Client Organization

2.02

1.26

1.82

0.96

1.91

1.11

15

Hope Of Better Post In This Company

2.21

1.25

1.75

0.93

1.96

1.11

16

Work Is Challenging

2.19

1.25

1.88

0.99

2.02

1.12

17

Work Is To Fast

3.82

1.25

3.79

1.35

3.80

1.30

18

Feel Relax During Work

2.37

1.32

2.10

1.20

2.22

1.26

19

Finding Exact Fault

3.53

1.34

3.22

1.50

3.36

1.44

20

Feel Alone In Critical Work

3.92

1.28

3.94

1.20

3.93

1.24

21

Technical Changes Affected On Mental

3.63

1.24

4.06

1.07

3.87

1.17

22

Stressfully Work

4.05

0.97

4.05

1.08

4.05

1.03

23

Assigned Work Is Positive

2.22

1.17

1.89

1.08

2.04

1.13

24

Work Life Policy Good

2.27

1.33

1.99

1.19

2.11

1.26

25

Location Of Work Wellness

2.71

1.35

2.19

1.30

2.42

1.34

26

Expect In Home City Work

3.85

1.09

3.96

1.12

3.91

1.11

27

Social Media Effect On My  Satisfaction

4.07

1.09

4.15

1.05

4.12

1.07

28

Organisation Famous In Social Site

2.08

1.11

1.82

1.09

1.94

1.10

29

Immediate Superior Talk

3.81

1.14

4.11

1.03

3.98

1.09

30

Skipping Question By Senior

3.51

1.28

3.34

1.42

3.42

1.36

31

Caring Your Health

2.37

1.26

1.86

1.01

2.09

1.16

32

Meditation Provides

1.99

0.98

1.85

0.91

1.91

0.94

33

Well With Upgrade Technical Skill

2.30

1.24

2.73

1.49

2.54

1.40

34

Less Time Given During Learning

3.93

1.00

4.07

1.00

4.01

1.00

35

Future Opportunity For Learning

2.69

1.39

2.35

1.40

2.50

1.41

36

Best Training Provider

2.53

1.38

2.03

1.10

2.26

1.26

37

Business Strategy Focused

3.20

1.36

2.64

1.51

2.89

1.47

38

Leader Understood Business Climate

2.69

1.37

2.24

1.21

2.44

1.30

39

Support By Manager For Training

2.39

1.37

1.75

1.03

2.04

1.23

40

Developing Employees

2.32

1.25

1.94

0.98

2.11

1.12

41

Organization Culture

2.64

1.38

2.24

1.34

2.42

1.37

42

Promotion Of Learning And Creativity Activity

2.60

1.32

2.12

1.14

2.33

1.24

43

Customer Service Is Good

2.44

1.38

2.75

1.55

2.61

1.48

44

Received Customer Focus Training

3.58

1.37

3.41

1.45

3.48

1.42

45

Communicated Well Of Company Goal

2.16

1.12

1.80

0.97

1.96

1.06

46

Idea Sharing In Company

2.12

1.15

1.86

0.93

1.98

1.04

47

Feedback

2.01

1.08

1.86

1.06

1.93

1.07

48

Guidance

2.54

1.34

2.28

1.27

2.40

1.31

 

Mean Of Means

2.75

0.67

2.53

0.83

2.63

0.75

{Source: Primary Data, SPSS output}

 

Interpretation 3:

 

Above analysis shows Out of 370 (100%) employees given responses. In this male 166 (45%) and female 204 (55%) given response. Male employees: summation of job satisfaction response that is mean of means 2.75 st dev 0.67 and  Female employees: summation of job satisfaction response that is mean of means 2.53 std dev 0.83. Total 370 (100%) Overall Job satisfaction mean value is 2.63 st dev 0.75. The Majority of employees found Female employees are more. Response responsed by five point Likert Scale. There were used observed 48 statements are in positive theme; response obtained and taken the appropriate scoring decision for analysis such as ‘1: Strogly Disagree’,’2: Disagree’,’3: Undecided’,’4: Agree’,‘5: Strongly Agree’. The level of Satisfaction score are categorized by Very low (1.0 to 1.8 mean value), low (1.8 to 2.60 mean value), medium (2.61 to 3.40 mean value), high (3.41 to 4.20 mean value) and very high (4.21 to 5.00) level of satisfaction. According to a study it was concluded that there was ‘Medium Level of Job Satisfaction’ found in Male respondent whose summation score is 2.75. There were ‘Low Level of Job Satisfaction’ found in Female respondent whose summation score is 2.53. There were ‘Medium Level of Job Satisfaction’ found in overall respondents in Information technology companies.

 

(d) Factors Analysis:

 

The researcher was interested to know the important factors that are contributed to job satisfaction to understand the factors exploratory factor analysis (Principle component) technique is used.  Firstly, a researcher was decided for Reliability Analysis for checked-out item or variable are suitable for analysis. Item N= 48, Overall Respondent O_N is 370, Male Respondents, M_N = 166 and For Female Respondents, F_N = 204.

 

(d.1) Reliability Analysis Staus:

 

Below result shows Reliability status of items by without deleted any item,  

 

(d.1.a) For Overall respondents O_N = 370, N of Item 48. The Cronbach’s Alpha coefficient is 0.87 mean 126.28 variance 485.174 st dev 22.02. The Scale is reliable, all items.

 

(d.1.b) For Male Respondents, M_N = 166, Item 48.  The Cronbach’s Alpha coefficient is 0.883 mean 132.19 variance 555.369 st dev 23.56. The Scale is reliable, all items.  

 

(d.1.c) For Female Respondents, F_N = 204, Item 48.  The Cronbach’s Alpha coefficient is 0.78 mean 121.47 variance 378.724 std dev 19.46. The Scale is reliable, all items. Next, the researcher was decided for conducting Factor Analysis of Male Respondents M_N= 166 of items 48.

 

Next, Researcher are conducting factor analysis of Male respondents total counted 166 and observation/ items/ statements 48, see below.

 

(d.2) (Male Respondents)  Factor Analysis : M_N= 166 of items 48

 

(d.2.1) Kaiser-Meyer-Olkin & Bartlett’s test: (Male Respondents only): Firstly did Kaiser-Meyer-Olkin Measure for Sampling Adequacy (consider 0.5 above value for adequacy) & Bartlett’s test of Sphericity (if Sig. p < 0.05, rejection of hypothesis). Both of these tests indicates that data is suitable for conducting factor analysis. According to data analysis (KMO is 0.809  & p is 0.0000 ) that means data is suitable for conducting factor analysis.

 

(d.2.2) Factor Extraction: (Male Respondents only)

 

Total Variance Explained

Component

Initial Eigenvalues

Extraction Sums of Squared Loadings

Rotation Sums of Squared Loadings

Total

% of Variance

Cumulative %

Total

% of Variance

Cumulative %

Total

% of Variance

Cumulative %

1

18.452

38.442

38.442

18.452

38.442

38.442

13.002

27.088

27.088

2

7.638

15.913

54.355

7.638

15.913

54.355

5.473

11.401

38.489

3

2.934

6.112

60.467

2.934

6.112

60.467

5.293

11.027

49.517

4

2.682

5.587

66.055

2.682

5.587

66.055

4.582

9.545

59.062

5

2.048

4.267

70.321

2.048

4.267

70.321

2.761

5.752

64.814

6

1.593

3.319

73.640

1.593

3.319

73.640

2.603

5.422

70.236

7

1.081

2.252

75.893

1.081

2.252

75.893

2.499

5.207

75.443

8

1.062

2.212

78.105

1.062

2.212

78.105

1.278

2.662

78.105

9

0.992

2.066

80.170

 

 

 

 

 

 

<Note: Eigenvalues greater than 1 (one) is sufficient for the decision of identifying factor, so Component 10 to 47 not wrote here. >

48

0.012

0.026

100.00

 

 

 

 

 

 

Extraction Method: Principal Component Analysis. | SPSS output

 

The above table shows that all factors are extractable from the analysis along with their eigenvalues, the percentage of variance attributable to each factor, the cumulative variance of the factor and previous factors. From the above table, it is identified that there are Eight factors with eigenvalues greater than 1 (one).

 

(d.2.3) Factor rotation (Male Respondents only) :

 

In this study researcher used Extraction Method was Principal Component Analysis. Rotation Method was Varimax with Kaiser Normalization & at least 0.40 for noting the significant factor) 8 components were extracted from 48 variables. The researcher considered factor scores of at least 0.40 for noting the significant factor, as the sample size was 370 in this study. The variable which has the highest loading on the particular factor has been assigned under that certain factor.

 

(d.2.4) Factor Loading and Assigning Name, Decision: (Male Respondents only):

 

Factor loading and Final Label is assigned to the factor. Next is tested the reliability of items (with the deleted items for fitting reliable). Correlation value of items (or variable) was sorted high to low loading in the related components. The following table shows component or factor, factor loading, Correlation value, reliability test value and final name assigned to the particular component.  

 

Q No

Particular

Items

Value

Reliability Test

*Final Name Assigned

Cronbach's Alpha

16

Factor 1

Work Is Challenging

0.859

0.943

Challenging Work in Excellent Physical Working Condition

14

Physical Working Condition In Client Organization

0.889

40

Developing Employees

0.844

15

Hope Of Better Post In This Company

0.821

46

Idea Sharing In Company

0.818

42

Factor 2

Promotion Of Learning And Creativity Activity

0.861

0.933

Promotion Of Learning, Creativity Activity in Business Climate

38

Leader Understood Business Climate

0.842

25

Location Of Work Wellness

0.830

41

Organization Culture

0.829

11

Team Members Trust

0.748

19

Factor 3

Finding Exact Fault

0.790

0.877

Accurate Fault Finding and Diagnosis

30

Skipping Question By Senior

0.716

44

Received Customer Focus Training

0.715

37

Business Strategy Focused

0.676

3

Co-workers Help

0.610

8

Other Departmental Supervision

0.597

32

Factor 4

Meditation Provides

0.805

0.735

Meditation

47

Feedback

0.693

24

Work-Life Policy Good

0.585

28

Organisation Famous In Social Site

0.735

23

Factor 5

Assigned Work Is Positive

0.755

0.856

Positive Work Life Policy

24

Work-Life Policy Good

0.755

8

Factor 6

Other Departmental Supervision

0.704

0.835

Departmental Supervision

10

T & C Of Customer

0.675

37

Business Strategy Focused

0.671

9

Employee Policy Is On Paper Only

0.610

31

Factor 7

Caring Your Health

0.753

0.861

HealthCare

13

Physical Working Condition At Work

0.737

36

Best Training Provider

0.727

27

Factor 8

Social Media effect On My  Satisfaction

0.450

0.618

Social Media

22

Stressfully Work

0.450

 

Finally author concluded that, These are Eight important Factor influenced on Job Satisfaction of Male Employee in Information Technology Companies that are (1) Challenging Work in Excellent Physical Working Condition (2) Promotion of Learning, Creativity Activity in Business Climate (3) Accurately Fault Finding and Diagnosis (4) Meditation (5) Positive Work Life Policy (6) Departmental Supervision (7) Healthcare (8) Social Media. Next, the researcher was decided for conducting Factor Analysis of Female Respondents F_N= 204 of items 48.

Next, Researcher are conducting factor analysis of Female respondents total counted 204 and observation/ items/ statements 48, see below.

 

(d.3) (Female Respondents) Factor Analysis: F_N= 204 | items 48

 

(d.3.1) Kaiser-Meyer-Olkin & Bartlett’s test: (Female Respondents only) : According to data analysis (KMO is 0.780  & p is 0.0000 ) that means data is suitable for conducting factor analysis.

 

 

(d.3.2) Factor Extraction: (Female Respondents) F_N= 204 (Female Respondents only)

 

Total Variance Explained

Component

Initial Eigenvalues

Extraction Sums of Squared Loadings

Rotation Sums of Squared Loadings

Total

% of Variance

Cumulative %

Total

% of Variance

Cumulative %

Total

% of Variance

Cumulative %

1

17.978

37.453

37.453

17.978

37.453

37.453

11.985

24.968

24.968

2

7.175

14.947

52.401

7.175

14.947

52.401

6.433

13.401

38.369

3

3.593

7.486

59.887

3.593

7.486

59.887

4.560

9.500

47.869

4

2.567

5.348

65.235

2.567

5.348

65.235

3.323

6.924

54.792

5

2.221

4.627

69.863

2.221

4.627

69.863

2.956

6.157

60.949

6

1.511

3.148

73.010

1.511

3.148

73.010

2.794

5.820

66.769

7

1.327

2.765

75.775

1.327

2.765

75.775

2.774

5.779

72.549

8

1.275

2.657

78.432

1.275

2.657

78.432

2.050

4.271

76.820

9

1.204

2.509

80.941

1.204

2.509

80.941

1.645

3.428

80.247

10

1.046

2.179

83.120

1.046

2.179

83.120

1.379

2.873

83.120

11

0.860

1.792

84.912

 

 

 

 

 

 

<Note: Eigen values greater than 1 (one) is sufficient for decision of identifying factor, so Component 12 to 47 not wrote here. >

48

0.007

0.015

100.000

 

 

 

 

 

 

Extraction Method: Principal Component Analysis.| SPSS output

The above table shows that all factors are extractable from the analysis along with their eigenvalues, the percentage of variance attributable to each factor, the cumulative variance of the factor and previous factors. From the above table, it is identified that there are Ten factors with eigenvalues greater than 1 (one).

 

(d.3.3) Factor rotation (Female Respondents only):

 

In this study researcher used Extraction Method was Principal Component Analysis. Rotation Method was Varimax with Kaiser Normalization & at least 0.40 for noting the significant factor) 9 components were extracted from 48 variables. The researcher considered factor scores of at least 0.40 for noting the significant factor, as the sample size was 370 in this study. The variable which has the highest loading on the particular factor has been assigned under that certain factor.

 

(d.3.4) Factor Loading and Assigning Name, Decision: (Female Respondents only):

 

Factor loading and Final Label is assigned to factor. Next is tested reliability of items (with the deleted items for fitting reliable). A Correlation value of items (or variable) was sorted high to low loading in the related components. The following table shows component or factor, factor loading, Correlation value, reliability test value and final name assigned to particular component. 

 

Q No

Particular

Items

Value

Reliability Test

*Final Name Assigned

Cronbach's Alpha

25

Factor 1

Location Of Work Wellness

0.836

0.964

Suitable Work Location

40

Developing Employees

0.825

31

Caring Your Health

0.814

41

Organization Culture

0.808

38

Leader Understood Business Climate

0.798

12

Listening With Each Other By Work Members

0.797

42

Promotion Of Learning And Creativity Activity

0.795

11

Team Members Trust

0.792

35

Future Opportunity For Learning

0.779

6

Sufficient Info For Work

0.770

45

Communicated Well Of Company Goal

0.757

39

Support By Manager For Training

0.753

46

Idea Sharing In Company

0.742

15

Hope Of Better Post In This Company

0.740

36

Work Is Challenging

0.738

13

Physical Working Condition At Work

0.717

4

Team Members Support

0.704

30

Factor 2

Skipping Question By Senior

0.789

0.919

Attain Query

8

Other Departmental Supervision

0.771

37

Business Strategy Focused

0.757

3

Co-workers Help

0.749

19

Finding Exact Fault

0.747

44

Received Customer Focus Training

0.746

10

T & C Of Customer

0.680

24

Factor 3

Work Life Policy Good

0.759

0.870

Positive Work Life Policy

23

Assigned Work Is Positive

0.729

32

Meditation Provides

0.713

47

Feedback

0.711

48

Factor 4

Guidance

0.645

0.784

Guidance

18

Feel Relax During Work

0.645

15

Factor 5

Hope Of Better Post In This Company

0.844

0.897

Hope of Better Position

13

Physical Working Condition At Work

0.749

7

Supervisor Help

0.728

23

Assigned Work Is Positive

0.725

5

Its Ok Job In Itself

0.72

2

Factor 6

Pays & Benefits Comparing With Other It Company

0.645

0.849

Salary, Wages, Pay & Benefits

1

Present Salary, Wages

0.645

16

Factor 7

Work Is Challenging

0.783

0.820

Challenging Work

14

Physical Working Condition In Client Organization

0.676

24

Work Life Policy Good

0.592

22

Factor 8

Other Departmental Supervision

0.587

0.717

Work Stress

9

Employee Policy Is On Paper Only

0.544

20

Feel Alone In Critical Work

0.484

36

Factor 9

Best Training Provider

0.312

0.476

Training Provider

28

Organisation Famous In Social Site

0.312

 

Finally author concluded that, these are Nine important Factor influenced on Job Satisfaction of Female Employee in Information Technology Companies that are (1) Suitable Work Location (2) Attain Query (3) Positive Work Life Policy (4) Guidance (5) Hope of Better Position (6) Salary, Wages, Pay & Benefits (7) Challenging Work (8) Work Stress (9)Training Provider

 

Finding:

 

(1)  According to the study there was found that the level of satisfaction varies in gender-wise. 

(2)  A study found that the medium level of job satisfaction seen in the overall IT employees, medium level job satisfaction is seen in Male employee and low-level job satisfaction is seen in Female employee from the IT companies. Female employees are less satisfies toward her job.

(3)  According to a research study, it was seen that Job Satisfaction depends on various factors. There is different or the same factors influenced in job satisfaction. In the case of Gender-wise employee’s job satisfaction; there was seen that job satisfaction factors are slightly different. In the Male & Female employees, there was found Challenging work and positive work-life policy are the most common factors influence on job satisfaction.

(4)  It was seen in the male employee that there are eight factors influenced in job satisfaction these are (a) Challenging Work in Excellent Physical Working Condition (b) Promotion of Learning, Creativity Activity in Business Climate (c) Accurately Fault Finding and Diagnosis (d) Meditation (e) Positive Work-Life Policy (f) Departmental Supervision (g) Healthcare (h) Social Media.

(5)  It was seen in the female employee that there are nine factors influenced on job satisfaction these are (a) Suitable Work Location (b) Attain Query (c) Positive Work Life Policy (d) Guidance (e) Hope of Better Position (f) Salary, Wages, Pay & Benefits (g) Challenging Work (h) Work Stress (i) Training Provider

 

Suggestion:

 

(1)  IT companies are sure from employees that what they need from companies. A satisfied employee gets more benefit to business than unsatisfied employees.

(2)  Male and Female employees have a different mentality, physically and indoor-outdoor workability.

(3)  According to the study of Male employees who are working in IT companies are expecting a challenging work with the need of good Physical Working Conditions. Be sure about learning Promotion, Creativity Activity is working in Business Climate, Find out accurately find & diagnosis the fault. Meditation requires in male employees to reduce work pressure. There are requiring Work-Life Policy by the positive way. Departmental Supervision is good or not be sure about it. Companies should maintain the health of employee and find out social Media affection on job satisfaction.

(4)  According to study Female Employees from IT Companies are expecting the Suitable Work Location and Attain Query during work. They are also expecting Positive Work-Life Policy. Female employees require well guidance from companies. They are waiting for a better Position in companies so be choosing suitable candidate and promote to better position.  Salary, Wages, Pay & Benefits are important in female employees. They are requiring a challenging Work. You must try to reduce work Stress in female candidate and they require better training provider.

(5)  IT companies should treat and understand gender-wise job satisfaction.

 

 

Conclusion:

 

Satisfied in the job will get more benefits to employees and employers. Job satisfaction depends on various factors. Gender-wise research study has been shown that satisfaction in jobs various, different than by considering all employees. Treating to employees by conducting individual information regarding dissatisfaction towards job then it helps to increase employee enhancing strategy.  An IT employee has a medium level of job satisfaction. It has been clear that below are certain Factors influenced by Job Satisfaction. Study clearly seen that factor influenced on job satisfaction in Male Employee from IT Companies that are Challenging Work in Excellent Physical Working Condition, Promotion of Learning, Creativity Activity in Business Climate, Accurately Fault Finding and Diagnosis, Meditation, Positive Work-Life Policy, Departmental Supervision, Healthcare, and Social Media is very important role in job satisfaction. In case of female employees from IT companies study clearly seen that factor influenced on job satisfaction that are Suitable Work Location, Attain Query, Positive Work-Life Policy, Guidance, Hope of Better Position, Salary, Wages, Pay & Benefits, Challenging Work, Work Stress and Training Provider is very important role in job satisfaction. Mind and human ability are different in Male employees and Female employees. Both they are skilled and taking various role and responsibility to complete customer and company’s technology demands. Job satisfaction role affects business. Organizational studies are focusing on employee satisfaction for company’s has better future. Carefully understanding the various Job satisfaction factor by gender-wise will help overall growth. Every employee needs a happy working life.

 

 

Reference:

 

Journal

·       M D Mohite (April 2019), “Human Resources Management Practices in Modern World” published inInternational Journal of Innovative Knowledge Concepts’ Volume VII, Issue 4, April, 2019 On 27th April, 2019 ISSN: 2454-2415

·       M D Mohite, Dr. Kulkarni (2/3/2019) ‘Job Satisfaction Factors of Employee in Virtual Workplace: Review“, Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456- 6470, Conference Issue, March 2019, pp.38-42, Presented by Maheshkumar in  national conference “Fostering Innovation, Integration and Inclusion Through Interdisciplinary Practices in Management’ organised by CSIBER, Kolhapur  

·       Mr. M D Mohite,  Dr. R.V. Kulkarni (2019), "Job Satisfaction Factors of Employee in Virtual Workplace: Review" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456- 6470, Special Issue  Fostering Innovation, Integration and Inclusion Through Interdisciplinary Practices in Management , March 2019, pp.38-42

·       Richard A. Kass &Howard E. A. Tinsley (2018), “ Factor Analysis”, Journal of Leisure Research, Volume 11, 1979 - Issue 2 Pages 120-138 | Published online: 13 Feb 2018

·       Amery D. Wu, Bruno D. ZumboSheila K. Marshall (2014), “A method to aid in the interpretation of EFA results: An application of Pratt’s measures, SAGE Journals, First Published January 6, 2014,  

·       Marsh, H. W., Morin, A. J., Parker, P. D., & Kaur, G. (2014). Exploratory structural equation modelling: An integration of the best features of exploratory and confirmatory factor analysis. Annual review of clinical psychology, 10, 85-110

 

Books

·       Stanley A Mulaik, (25, 2009), Foundations of Factor Analysis, 2nd Edition

·       Dennis Child (2006), Essentials of Factor Analysis, 3rd edition

 

Presentation:

·       Power Within (2019), “Factor Analysis, Research Methodology & Statistics”, published in https://www.youtube.com/watch?v=zwzdbi03Tco , Date 7/6/2019

·       M. D. Mohite (2019), job-satisfaction-factor-of-employees-in-virtual-workplace”, Published in slideshare.net

·       M. D. Mohite (2019), “human-resources-management-in-media-entertainment “  Published in slideshare.net

·       Dr. Todd Grande (2016),  “Interpreting SPSS Output for Factor Analysis”, published in youtube.com/watch?v=g_3kaSnq-DY , 17 march 2016

·       Qasim Raza, (2013), Factor Analysis in Research, Published in slideshare.net, Date Jul 18, 2013

 

E-Source:

·       Wikipedia (March 2019) open access journal, “Human Resource Management_, Satisfaction__, Job__”

·       Ruben Geert van den Berg (2019), Sigma Plus Statistiek, spss-tutorials.com/spss-factor-analysis-tutorial/

·       UNISTAT(2019), on Factor Analysis,  unistat.com/guide/factor-analysis/

·       Statistics How To (2019), statisticshowto.datasciencecentral.com/kaiser-meyer-olkin___ , /bartletts-test___,  /factor-analysis-2

·       tandfonline (2019) on tandfonline.com/doi/abs/10.1207/s15327574ijt0502_4?journalCode=hijt20

·       Anila Titus (2015), motivational techniques, slideshare.net/anilatitus/motivational-techniques-49834213

·       Filipa Castanheira (2014),  link.springer.com/referenceworkentry/10.1007%2F978-94-007-0753-5_1992

·       Venkatesh(2012),“factors influencing-job-satisfaction-with-diagram” published in yourarticlelibrary.com

·       Neha Aulakh (2012), (101843412) scribd.com/document/79808271/Job-Satisfaction

 

 


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