This paper presents the major organizational justice factors influence on employee engagement in a context of banking sector in Trincomalee District. Based on principal component analysis (PCA), correlation and descriptive statistical analysis of the factors believed to influence that organizational justice on employee engagement therefore clustered into principal component. The sampling test conducted using Bartlett’s test of sphericity and KMO measure of sampling adequacy (MSA) to ascertain the level relationship and the pattern between variables was found to be very significant with MSA (0.940).The result of the analysis found to have four components displayed eigenvalues greater than 1. Therefore, the entire factor can be put into four principal components which accounted for 77.650% of the total variance. Statistically there was strong interrelationship among the variables in the (PCA) with p-value <0.05 .The principal components are feedback, unbiased, Pay and Stresses and Strains and pay and effort

Ravichandran, D.

English

IR South Eastern University of Sri Lanka

Principal Component Analysis of Influence of 
Organizational Justice on Employee 
Engagement 
 
Ravichandran. D 
Department of Business and Management Studies, Trincomalee Campus, Eastern University 
Sri Lanka. 
Abstract  
 This paper presents the major organizational justice factors influence on employee 
engagement in a context of banking sector in Trincomalee District. Based on 
principal component analysis (PCA), correlation and descriptive statistical analysis 
of the factors believed to influence that organizational justice on employee 
engagement therefore clustered into principal component. The sampling test 
conducted using Bartlett’s test of sphericity and KMO measure of sampling 
adequacy (MSA) to ascertain the level relationship and the pattern between 
variables was found to be very significant with MSA (0.940).The result of the 
analysis found to have four components displayed eigenvalues greater than 1. 
Therefore, the entire factor can be put into four principal components which 
accounted for 77.650% of the total variance. Statistically there was strong 
interrelationship among the variables in the (PCA) with p-value <0.05 .The 
principal components are feedback, unbiased, Pay and Stresses and Strains and pay 
and effort. 
 
Keywords: Organizational justice, principal component analysis and employee 
engagement 
 
Introduction  
There are many studies conducted in the field of factor analysis. Most of the articles are 
concerned with the concerns of western countries. A few abridged studies are found available 
in Bangladesh and other similar countries, but no detailed study is seen on it. Therefore, the 
authors took interest to somewhat cover this research gap. The study was undertaken to 
understand the factor analysis and its application in social and management science researches. 
Increasing attention has been paid in recent years to the issue of organizational justice and its 
impacts on organizational outcomes. Organizational justice, a term coined by Greenberg 
(1987) refers to employee perceptions of fairness in the workplace. The organizational justice 
of an organization provides job satisfaction to the employees its leads to employee engagement 
towards the organization. William Kahn in 1990 described the term employee engagement on 
the basis of Goffman’s 1961 role behavior speculation. This theory proposes that employee 
attitudes are formed by the demands and regulations of other employees. Thus ‘employees’ 
attitudes can be calculated by investigation about their roles; the term “role” is taken from the 
theatrical world.  William Kahn recommended that employees can perform the responsibilities 
that are no mentioned in their job descriptions. Employee Engagement is the level of 
commitment and involvement an employee has towards his organization and its values.  An 
engaged employee is aware of business context, and works with colleagues to improve 
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performance within the job for the benefit of the organization.  It is a positive attitude held by 
the employees towards the organization and its values. Engaged employees are fully involved 
in, and enthusiastic about their work. In addition, this research intended to examine the 
influence of organizational justice on employee engagement at the selected banks in 
Trincomalee District. 
Objectives of The Study 
The following three objectives were under taken for the study: 
1.  To determine a set of organizational justice factors influence on employee engagement  
2.  To rank the organizational justice factor influence on employee engagement with 
respect to their importance; and   
3.  To offer some policy implications to enhance the organizational justice on employee 
engagement at the banks in Trincomalee District. 
Literature Review 
Organizational justice 
Organizational justice is the study of the concerns about fairness in the workplace. Concerns 
about distribution of resources have to do with distributive justice, concerns about fairness of 
decision-making procedures have to do with procedural justice, and concerns regarding 
interpersonal treatment have to do with interactional justice (Greenberg, J. 1990). 
Distributive justice 
The research on distributive justice in organizations today focuses primarily on people's 
perceptions of the fairness of the outcomes they receive, that is, their evaluations of the end 
state of the allocation process (Cropanzano & Greenberg, 1997). 
Procedural justice 
Procedural justice is defined as the fairness of the processes that lead to outcomes. When 
individuals feel that they have a voice in the process or that the process involves characteristics 
such as consistency, accuracy, ethicality, and lack of bias then procedural justice is enhanced 
(Leventhal, 1976). 
 
Interactional justice 
Interactional justice concerns fairness of how individuals treat one another not only when 
resources are distributed but in everyday interactions, as well. Interactional justice is defined 
by sociologist John, G. (2001) as the "...degree to which the people affected by decision are 
treated by dignity and respect. It is important that a high degree of interactional justice exists 
in a subordinate/supervisor relationship in order to reduce the likelihood of counter productive 
work behavior. 
 
Employee engagement 
Kahn (1990,p. 694) defines personal engagement as the harnessing of organization members‘ 
selves to their work roles; in engagement, people employ and express themselves physically, 
cognitively, and emotionally during role performances. Personal disengagement refers to the 
uncoupling of selves from work roles; in disengagement, people withdraw and defend 
themselves physically, cognitively, or emotionally during role performances (p. 694). Thus, 
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according to Kahn (1990, 1992), engagement means to be psychologically present when 
occupying and performing an organizational role.  
Conceptual Framework 
 
 
 
  
 
 
 
 
Figure 1 
(Source: Abdul KhaliqAlvi and AbdusSattarAbbasi, 2012) 
 
Methodology 
 
Sampling Design 
Out of total population of selected banks in Trincomalee District, only 200 (68%) employees 
are selected as sample by using stratified sampling method. The paper begins with sampling 
test conducted using Bartlett’s test of sphericity and KMO measure of sampling adequacy 
(MSA) to ascertain the level relationship and the pattern between variables.  
 
Data Collection 
The study totally depends on primary data. The primary data were collected through 
questionnaire following direct personal interviewing technique from 200 staff of selected 
banks in Trincomalee District. The questionnaire was developed with two parts namely part I  
Research Information and part II Personal Information. 
 
Measures 
The questionnaire was administrated to staff of selected banks in Trincomalee District. A five 
points Likert type summated rating scales of questionnaire from strongly disagree 1 to strongly 
agree 5 were adopted to identify the engagement. 
 
Tool of Data Analysis 
The present study has used a sophisticated method of statistics - FA using varimax rotation 
analyzing the data collected. In order to obtain interpretable characteristics and simple 
structure solutions, researchers have subjected the initial factor matrices to varimax rotation 
procedures (Kaiser, 1958). Varimax rotated factors matrix provides orthogonal common 
factors. Finally ranking of the indicators has been made on the basis of factor scores. 
 
Distributive 
 Justice 
Interactional  
Justice 
Procedural  
Justice 
Employee  
Engagement 
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Reliability and Validity 
The reliability value of our surveyed data was 0.940 for organizational justice. If we compare 
reliability value with the standard value alpha of 0.7 advocated by Cronbach (1951), a more 
accurate recommendation (Nunnally & Bernstein’s, 1994) or with the standard value of 0.6 as 
recommendated by Bagozzi & Yi’s (1988) we find that the scales used by researcher are 
sufficiently reliable for data analysis. Regarding validity, Kasier – Meyer –Olkin (KMO) 
measure of Sampling Adequacy is a measure of whether or not the distribution of value is 
adequate for conducting FA. As per KMO measure, a measure of >0.9 is marvellous, >0.8 is 
meritorious, >0.7 is middling, >0.6 is mediocre, >0.5 is miserable and <0.5 is unacceptable. 
 
Table 1: KMO and Bartlett’s test 
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .829 
Approx. Chi square 2308.864 
Bartlett's Test of Sphericity df 105 
Sig. .000 
Source: Survey data 
Appropriateness of the Collected Data 
Bartlett’s test of sphericity (Barlett, 1950) is the third statistical test applied in the study for 
verifying its appropriateness. This test should be significant i.e., having a significance value 
less than 0.5. In the present study, test value of Chi  Square 2308.964 is highly significant (as 
also given in table  2) indicating that the data is appropriate for the factor analysis. 
 
Factor Analysis 
 
After examining the reliability of the scale and testing appropriateness of data as above, we 
next carried out factor analysis is to measure the engagement. For this, we employed Principal 
Component Analysis (PCA) followed by the varimax rotation, (Generally, researchers’ 
recommend as varimax). It is worth mentioning out here that factor loading greater than 0.30 
are considered significant. 0.40 are considered more important and 0.50 or greater are 
considered very significant (Hair, Anderson, Tatham, and Black, 2003).  
 
According to Table 2 the data returned a value sampling adequacy of 0.829 indicating 
meritorious. Bartlett’s test of Sphericity is a measure of the multivariate normality of the set 
of distributions. It also tests whether the correlation matrix conducted within the factor analysis 
is an identity matrix. factor analysis would be meaningless with an identity matrix. A 
significance value <0.05 indicates that the data DO NOT produce an identity matrix and are 
thus appropriately multivariate normal and acceptable for factor analysis (George and Mallery, 
2003). The data within this study returned a significance value of 0.000, indicating that the 
data was acceptable for factor analysis. 
When the original ten characteristics were analysed by the Principal Component Analysis 
(PCA) with varimax rotation, four characteristics extracted from the analysis with an Eigen 
value of >1, which explained 77.650 percent of the total variance. The result of the factor 
analysis is presented in Table 2. The factor loadings have ranged from 0.870 to .586. The 
higher a factor loading, the more would its test reflect or measure as characteristics. The 
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characteristic getting highest loading becomes the title of each group of characteristics e.g. 
feedback– title of characteristics group I and the like. Further, the present study has interpreted 
the characteristics loaded by variables having significant loadings of the magnitudes of 0.50 
and above (Pal, 1986; Pal and Bagi,1987). 
 
Table 2: Principal Component Analysis – Varimax Rotation of Characteristics. Rotated 
Component Matrixa 
Name of the characteristics Component  
1 2 3 4 Communalities 
Feedback .870    .794 
Unbiased .751    .747 
Consistency .715    .817 
Employee concern .639    .694 
Correctable .586    .655 
Unbiased  .775   .747 
Trust  .771   .884 
Timely feedback  .771   .865 
Ethical procedures  .670   .831 
Individual point of view  .618   .694 
Pay Stresses and Strains   .820  .723 
Employee treatment   .683  .814 
Pay and Performance   .596  .638 
Pay Effort 
Pay and responsibilities 
   .855 
.774 
.871 
.760 
Eigen Value  7.990 1.465 1.185 1.034  
Proportion of Variance 53.265 9.767 7.722 6.896  
Cumulative variance 
explained 
53.265 63.032 70.754 77.650 
 
 
Extraction Method: Principal Component Analysis. 
Rotation Method: Varimax with Kaiser Normalization. 
Source: Survey data 
 
Component I: Feedback –This Component was represented by five Components with factor 
loadings ranging from .870 to .586. They were Feedback, unbiased, consistency, employee 
concern and correctable. This Component accounted for 53.265% of the rated variance. 
Component II: Unbiased – five Components with factor loadings ranging from .775 to .618. 
A variance of 9.767% was explained by this Component  
Component III: Pay Stresses and Strains- This Component was represented by three 
Components with factor loadings ranging from .820 to .596. They were Pay Stresses and 
Strains, employee treatment and pay for performance. This Component accounted for 7.722% 
of the rated variance. 
Component IV: Pay Effort Only two components are with 0.855 and 0.774. A variance of 
6.896% was explained by this characteristic. 
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Scree Plots 
Scree plots are formed by plotting the number of factors against their respective eigen value 
(Hackett and Foxall, 1999). It is a graph of the eigen values against all the factors. The graph 
is useful for determining how many factors to retain. 
 
 
Figure 2- Scree plot 
Source: Survey data 
 
Ranking of the above components in order of their importance, along with factor score, is 
shown in Table 4. The importance of these components, as perceived by the respondents, has 
been ranked on the basis of factor score. 
Table 3: Ranking of Components according to their importance 
Organizational Justice Factor Score Ranking 
Component-1: Feedback 0.185 4 
Component-II: Unbiased 0.217 3 
Component- III: Pay Stresses and Strains 0.274 2 
Component- IV: Pay Effort 0.451 1 
Source: Survey data 
Conclusion 
Many factors actually describing the factors that contribute to employee engagement. This 
paper deals with the problem of putting the factors that contribute to employee engagement in 
Trincomalee District into principal component thereby reducing the factor into major factors. 
The paper finally presented four principal components which are stipulated in the proposed 
model. Factor Analysis attempts to simplify complex and diverse relationships that exist 
among a set of observed variables by uncovering common dimensions or factors that link 
together the seemingly unrelated variables and consequently provides insight into the 
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significance of underlying structure of the data. The present study identified four factors of 
employee commitment which accounted for 77.650% of the total variance and displayed 
eigenvalues greater than 1. Therefore, the entire factor can be put into four principal 
components statistically there was strong interrelationship among the variables in the (PCA) 
with p-value <0.05 .The principal components are pay and effort, Pay and Stresses and Strains, 
unbiased and feedback. These are ranked as first, second, third, and fourth respectively with 
respect to their importance. Outcomes of the study would benefit the academicians, 
researchers, policy makers and practitioners. 
Suggestions 
Managers should enhance two-way communication, ensure that employees have all the 
resources they need to do their job, give appropriate training to increase their knowledge and 
skill, establish reward mechanisms in which good job is rewarded through various financial 
and non-financial incentives, build a distinctive corporate culture that encourages hard work 
and keeps success stories alive, develop a strong performance management system which holds 
managers and employees accountable for the behavior they bring to the workplace, place focus 
on top performing employees to reduce their turnover and maintain or increase business 
performance. Finally, employees always expecting something from the organization if their 
expectations are satisfied only employees ready to put their effort to the organization, so 
making pleasant working environment create employees engagement towards the 
organization. 
 
Contribution of The Study 
It is hoped that the study will contribute greatly to the literature of employee engagement. 
Besides, suggestive recommendations will have much effect on improving employee 
engagement. The suitable policy formulation based on the findings of the study, to the best 
interest of the academic professionals as well as of the country will go a long way to open a 
new era in the field of the country’s human resource development. 
 
Implications for Future Research 
This present study examines an influence of organizational justice on employee engagement 
at selected banks in Trincomalee District.  First implication is that in this study only dealt with 
identifying influence of organizational justice on employee engagement but further research 
can be done other work related outcomes such as employee satisfaction and employee turnover 
intentions.  Second implication is this study only covered seven banks  employees in 
Trincomalee District so in future scope will be expand beyond the research area it will be 
effective and useful.  
 
Reference 
Bagozzi, R. P., and Yi, Y. (1988), “On the Evaluation of Structural Equation Models.” Journal 
of the Academy of Marketing Science, Vol.16, No.1, pp. 74 95. 
Cronbach, L.J. (1951), Coefficient Alpha and the Internal Structure of tests, Psychometrika, 
16 (3):297-334. 
George, D. and Mallery. P. (2003). SPSS for Windows Step by Step: A Simple Guide and 
Reference, 11.0 update (4th edition). 
Goffman, E., (1961), Encounters: Two studies in the sociology of interaction. Indianapolis, 
IN: Bobbs- Merrill. 
Gorsuch, R.L. (1983). Factor Analysis (2nd ed). Hillsdae, NJ: Erlbaum. 
5th Annual International Research Conference- 2016 
Faculty of Management and Commerce- SEUSL
290
Greenberg J (1987), “Reactions to procedural injustice in payment distributions: Do the means 
justify the ends?” J. Appl. Psychol., 72: 55-71. 
Hackett Paul,M.W. and Foxall Gordon,R.(1999). A Factor Analytic Study of Consumers’ 
Location Specific Values: A Traditional High Street and a Modern Shopping Mall: 
In Hooley. 
Kahn, A.W. (1990), Psychological conditions of personal engagement and disengagement at 
work. Academy of Management Journal, 33: 692-724. 
Kasier, H.F. (1974), “Index of Factorial Simplicity.” Psycometrica, Vol.39, pp.31 36 
Nimalathasan, B and Mohammed, N. A. (2010), Quality of work life practices of academic 
professionals in Bangladesh: a factor analytical approach, International Journal of 
Research in Commerce & Management, Vol.1 
Nimalathasan, B.  (2009), Factor Analysis: Nature, Mechanism and Uses in Social and 
Management Science Research: Journal of Cost and Management Accountant, 
Bangladesh. XXXVII (2):15-25(Published). 
Nunnally, J. C., and Bernstein. (1994), “Ira Psychometrics Theory.” McGraw Hill, New York 
Pal, Y. (1986): A Theoretical Study of Some Factor Analysis Problems and Pal,Y. and Bagai, 
O.P. 1987): A Common Factor Better Reliability Approach to Determine the 
Number of Interpretable Factor. Paper presented at the IX Annual Conference of the 
Indian Society for Probability and Statistics held at Delhi, University of Delhi, India. 
Yarhands Dissou Arthur, Emmanuel Harris , Jonathan Annan (2012)  Principal Component 
Analysis of Customer Churns in Ghanaian Telecommunication Industry American 
International Journal of Contemporary Research Vol. 2 No. 12; December 2012. 
 
 
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Principal component analysis of influence of organizational justice on employee engagement.

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