Assignment: Taking Organizational Measurements-3 pages

In your role as a consultant for Walden Sports, it is important to understand why certain instruments are more effective than others. You have had practice, in this course and others before it, selecting measures to address organizational development problems. This assignment builds upon previous similar assignments in that you will be identifying workplace issues, selecting appropriate measurement tools and strategies, and providing rationale for their use ( DO NOT USE EMPLOYEE SATISFICATION SURVEYS). Make sure to choose a different instrument and items than ones previously used. It is recommended that you go into greater depth and explore additional measurement strategies for this assignment.   

To prepare for the Assignment:

• Identify job attitudes that will be measured at Walden Sports.
• Identify appropriate items and instruments to use in measuring selected job attitudes.
• Review psychometric properties of instruments and measurement items.

By Day 7

Submit a 3- to 5-page paper (not including references) that addresses the following:

Write a report explaining to the client what you plan to measure and how you plan to do so. Your measurement strategy should include existing instruments such as questionnaires as well as specific additional items that you might use to score specific job attitudes. You should include detailed information about the psychometric properties of your measurement tools. Keep in mind that your client may or may not be familiar with job satisfaction questionnaires or psychometric properties, so consider your audience in your writing and be sure to follow APA style.

• Summarize the job attitudes that need to be measured in the organization.
• Summarize the three instruments you might use to measure job satisfaction, organizational commitment, and job involvement in the organization.
• Justify your use of these instruments.
• Summarize the psychometric properties of the instruments.
• Summarize specific items and the scoring method you might use as part of a separate diagnostic survey.

Sunshine Sports Introduction
Program Transcript

BENJAMIN JONES: Hi, I’m Benjamin Jones co-founder of Walden Sports. Come
on in. Thank you for coming in today. As you know, I want to make some
changes that will benefit our employees, and I’m really looking forward to hearing
from you how you might be able to help. There’s a lot to go over. I think I’ll just
start by giving you the lay of the land.

Walden Sports was founded just over 12 years ago. And we’ve expanded our
product line to include everything that adventurous travelers demand from
sleeping bags, to tents, to guide books, maps, even insurance. Our clothing and
equipment sales are $1,420,000 per year with a gross profit of $202,400. We
employ 70 people part-time and full-time distributed over a variety of
departments, including finance, marketing, and operations.

And really exciting, we’ve recently started a mail order division through our
website which has required our establishing a mail order fulfillment department
and an IT department. Business has been so good the last few years we’re able
to donate 5% of our gross profit to charity. Last year, Walden acquired an agency
called Earth Travelers, one of the most respected tour operators in the market,
and we began selling their services in our stores. In the six months that we’ve
been selling these travel agency services we’ve sold 200 vacation packages at
an average cost of $3,340. Walden Sports is 10% commission on the sales has
been $66,800.

In addition, 35 insurance policies have been sold at an average price of $167
yielding $1,754 from a 30% commission. This growth which at first seemed like a
blessing, has caused some major challenges for us though. In the past six
months, we’ve seen a sharp decrease in productivity and an increase in turnover
and absenteeism. Moreover, people don’t seem as energized and motivated as
they once were. There was once a time when our employees would not only
work late but reach out and offer assistance to other employees who are falling
behind in their workload. We don’t see that anymore.

We used to have social activities and happy hour at least once a month to boost
employee morale. Now hardly anybody comes to those activities. Until now,
employees would take great pride in what they did and with whom they worked.
They even took every opportunity to wear the company’s clothing as often as
they could. But not anymore. And all of that is why we’ve asked you here today.
We really need somebody from the outside to come in and find out what’s going
on and tell us what we can do to make things better. Do you think you can help?

© 2012 Laureate Education, Inc.

©2012 Laureate Education, Inc. 1

©2012 Laureate Education, Inc. 2

International Journal of

Environmental Research

and Public Health

Article

The Efficient Measurement of Job Satisfaction:
Facet-Items versus Facet Scales

Angelika Lepold ID , Norbert Tanzer, Anita Bregenzer and Paulino Jiménez * ID

Department of Psychology, University of Graz, 8010 Graz, Austria; angelika.lepold@edu.uni-graz.at (A.L.);
norbert.tanzer@uni-graz.at (N.T.); anita.bregenzer@uni-graz.at (A.B.)
* Correspondence: paul.jimenez@uni-graz.at; Tel.: +43-316-380-5128

Received: 25 May 2018; Accepted: 25 June 2018; Published: 28 June 2018
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Abstract: The measurement of job satisfaction as a central dimension for workplace health and
well-being is crucial to set suitable health- and performance-enhancing management decisions.
Measuring different facets of job satisfaction leads to a more precise understanding about job
satisfaction in research as well as to more specific interventions in companies. This study examines
the measurement of job satisfaction with facet scales (multiple-items for one facet) and facet-items
(one item for one facet). Facet-items are a cost-effective and fast way to measure job satisfaction
in facets, whereas facet scales are more detailed and provide further information.

Results

from
788 bank employees showed that facet-items of job satisfaction were significantly correlated
with the corresponding facet scales and had high factor loadings within the appropriate factor.
Furthermore, the same correlational pattern between facet scales and external criteria was found
for facet-items and external criteria (identification with the company, work engagement, stress,
resources). The findings support the usage of facet-items in companies and in research where cost-
and time-effectiveness is imperative and the usage of facet scales where an even deeper understanding
of job satisfaction is needed. In practice, the usage of efficient measurements is evident, especially in
the upcoming field of eHealth tools.

Keywords: workplace health promotion; job satisfaction; facet-items; facet scales; measurement;
effectiveness

1. Introduction

Is your job making you feel satisfied? Job satisfaction (JS) is one of the most studied fields
of work design research in psychology [1]. The wide interest of JS is valid for research and for
organizations [2]. JS can be seen in two different ways: On one hand, JS is used as a measurement
for well-being of employees [3]. In this respect, JS displays the emotional state of the employees that
is also frequently used as an indicator in workplace health promotion projects to develop specific
interventions [4]. On the other hand, JS is seen in a dynamic process as a predictor and outcome
variable for other job-related factors in the direction of performance [5,6], e.g., work engagement.
Since engaged employees are more productive [7], organizations want to explore the level of JS of
their employees. High JS can be a goal for organizations to reduce their fluctuations and to enhance
their performance, but for the employees by themselves, it is of deep interest to enhance their own
quality of life. JS is defined as a pleasurable or positive emotional state [8] and is developed through
evaluative judgments, affective experiences at work, and beliefs about jobs [9]. It is associated with
important work-related and general outcomes [10,11] as e.g., JS shows a high variance proportion for
the prediction of general life satisfaction [12]. Furthermore, JS and work engagement show a high
positive relationship [13]. Therefore, the measurement of JS plays a fundamental role as organizations
want highly involved and satisfied employees to reach their goals (e.g., [14]). The measurement of JS

Int. J. Environ. Res. Public Health 2018, 15, 1362; doi:10.3390/ijerph15071362 www.mdpi.com/journal/ijerph

http://www.mdpi.com/journal/ijerph

http://www.mdpi.com

https://orcid.org/0000-0002-0457-7048

https://orcid.org/0000-0002-8229-1141

http://www.mdpi.com/1660-4601/15/7/1362?type=check_update&version=1

http://dx.doi.org/10.3390/ijerph15071362

http://www.mdpi.com/journal/ijerph

Int. J. Environ. Res. Public Health 2018, 15, 1362 2 of 19

gives insight into the attitudes of the employees in the company and can be used to support the design
of corporate strategies [15].

A typical way of using JS is by including it as organizational diagnostic variable in employee
surveys [16] to derive actions according to the goals and strategies of the organization. These goals
can be derived with the Balanced Scorecard [17]. The Balanced Scorecard is an instrument to translate
the strategies and goals of a company into precise measurable indicators. The learning and growth
perspective of the Balanced Scorecard, which is one of four perspectives, is the foundation for all other
perspectives. Investments in further education, information technologies, and systems are part of the
learning and growth perspective where the base to reach other defined goals is set. The learning and
growth perspective includes, amongst other indicators, the satisfaction of the employees to increase
productivity and quality [18], where JS can be measured with an employee survey [19]. Recent research
shows that economic measurement is important to get information and to decrease the reaction time to
set actions in a company [20].

As part of most employee surveys, JS can be on one hand considered as a global construct
or on the other hand can be seen as consisting of various facets [21], where, according to Judge
and Kammeyer-Mueller [22], JS is a hierarchical construct. Global JS combines all feelings and
cognitions toward the job whereas the facet approach considers various aspects of the job like work
task, payment, promotion, supervision, or coworkers [15,21]. These different approaches lead to
various measurements of JS [23]. We differentiate the approaches into the goal of assessing global JS or
facets of JS as presented in Table 1.

Table 1. Different forms of measurement of assessing job satisfaction (JS).

Number of Items

Form of JS Multiple-Items Single-Items

JS Global Multiple-items for one global scale of JS Single-item for global score of JS
JS Facets Multiple-items for every facet of JS (facet scales) Single-items for every facet of JS (facet-items)

The contrasts between these approaches can be seen at different levels. JS is often measured
with multiple-items aggregated to global JS [24]. A new way of assessing JS is with one single-item
asking for global JS (e.g., [25]). Global JS is an efficient way of measuring well-being either in a
single-item version or with multiple-items, where the advantage of multiple-items lies in higher
reliability [26]. Measuring dimensions (or facets) of JS can be done with multiple-items aggregated
to different facets of JS [27,28]. Assessing facets of JS is useful to get a deeper insight into the
different organizational processes [14] as also the multidimensional complexity of JS has to be taken
into account [29,30]. The facets that are considered, e.g., by the Job Descriptive Index [27], are the
work by itself, compensation and benefits, attitudes toward supervisors, relations with co-workers,
and opportunities for promotion. But there can be other facets like working conditions [8]. Given the
current measurements of JS, there exist different facets of JS as well as different compositions of
facets [15]. Regarding the idea of an efficient way of measuring JS, which at the same time covers all
important facets, can be seen best presented with the use of single-items where every item describes one
facet of JS, e.g., the facet “satisfaction with working conditions” is assessed with one item (e.g., [20,31]).
We define single-items, which are used as assessment for a single facet of JS, as facet-items.

The aim of this study is to introduce and test a set of JS instruments: an instrument of JS
consisting of different facet scales (Profile Analysis of Job Satisfaction (PAJS); [28]) and a specially
developed screening version are compared. This screening version of the measurement of JS consists
of a battery of facet-items, where every item represents one facet of the facet scales. Instruments
with facet-items have been developed before (e.g., [20,31]) but have included only a small range of
possible facets, focusing strongly on facets measuring JS with social aspects (supervisor, coworkers)
or with task-related aspects (work tasks, payment, career possibilities). To get a deeper insight into
the workplace, a more detailed assessment is needed where a wide range of possible facets must be

Int. J. Environ. Res. Public Health 2018, 15, 1362 3 of 19

considered (e.g., the information processes, the working and vacation times, or working conditions).
The PAJS contains 11 facets with multiple-items for every facet and, therefore, allows a very specific
assessment of the workplace. A screening version with one item for each of the 11 facets could provide
more information than single- or multiple-items of global JS and be at the same time more cost- and
time-efficient than the PAJS. Nonetheless the usage of multiple-item measurements for JS is necessary
to get a deeper insight into the facets and to derive interventions more precisely.

1.1. Measuring Job Satisfaction with Facet-Items versus Facet Scales

Regarding single-items of JS, they need less time and space, are more cost-effective, and may
contain more face validity than scales with multiple-items [32]. Cost- and time-effectiveness is an
important issue for companies. Shorter surveys are more likely to be approved by companies and are
more likely to be completed by the employees or participants in a study [33,34]. Therefore, an economic
measurement will lead to higher participation of employees in an employee survey or in research
studies [20]. These advantages can also be assumed for facet-items of JS [31].

Criticism against single-item measurements refer to the assessment of reliability: the test-retest-
reliability for single-item measurements can be estimated, but the more psychometrically important
estimation of internal consistency cannot be generated [26]. Furthermore, Wanous et al. [32] report
in their meta-analysis test-retest-reliabilities for single-items between 0.45 and 0.69, which is a
large bandwidth. But as Gardner et al. [35] state, it is possible that one “good” item shows better
reliability and validity than many “bad” items. Wanous et al. [32] report correlations at 0.63 between
single-items and scale measures showing that single-items of JS have an acceptable psychometric
quality. Besides that, not only reliability but also validity for the practical usage of scales is at least of
high importance [36].

For other constructs, like work engagement, it was already shown that a short and efficient
measurement can be used [13]: the Utrecht Work Engagement Scale (UWES) measures the three
dimensions of vigor, dedication, and absorption with one item for each dimension and shows
acceptable reliability and validity. For narcissism, a single-item measurement was also developed,
showing high test-retest-reliability and acceptable validity [37]. Even assessing the health status with
global single-items as a valid, reliable, and sensitive measurement can be done [38].

In the present study, facet-items of JS are direct statements. Facet-items in form of questions
in a discrepancy approach [31] can lead to psychometric problems [39]. Furthermore, the used
measurement, in fact the PAJS, contains 11 facets of JS, and therefore, it is even more comprehensive
and easier to derive practical interventions than with less facets. As the measurement of 11 facets with
multiple-items for every scale is costly, a facet-item approach is more efficiently and less cost-intensive.
Therefore, a screening version was developed to measure the facets of JS with facet-items: 11 items
were defined to measure 11 facets. The items included the name of the facet scale and in parentheses
further descriptions of the scale (this is presented in Table 2, see third column). To be efficient,
the circumstance of having items measuring more than one aspect was deliberately accepted, but for
that more comprehensible items were possible.

Int. J. Environ. Res. Public Health 2018, 15, 1362 4 of 19

Table 2. Comparison of the Profile Analysis of Job Satisfaction (PAJS) and the PAJS-Facet-Item (PAJS-FI) 1.

Facet of Job Satisfaction PAJS—Facet Scale Measurement PAJS-FI—Facet-Item Measurement

Information and communication
Three single-items (Sample item: I am . . . with the information about activities in
the company.)

I am . . . with information and communication (activities in company,
treatment of my suggestions, information from the management,
information about innovations).

Demanding work Three single-items (Sample item: I am . . . with my work domain.) I am . . . with how demanding my job is (work domain, responsibility).

Relationship to direct colleagues Four single-items (Sample item: I am . . . with the support of my direct colleagues.)
I am . . . with the relationship to my direct colleagues (team spirit,
work atmosphere, division of work, support).

Relationship to direct supervisor Four single-items (Sample item: I am . . . with the support of my supervisor.)
I am . . . with the relationship to my direct supervisor (support, openness for
problems, arrangement of cooperation between colleagues, praise, criticism).

Organization and management Three single-items (Sample item: I am . . . with the image of the company.)
I am . . . with the organization and management (effort regarding employees,
participation possibilities, image).

Chances of making career
Five single-items (Sample item: I am . . . with my chances of moving up in my company
compared to my colleagues.)

I am . . . with the chances of moving up and making career (compared to my
colleagues, to colleagues from similar companies, to friends, possibility of
making my desired career, possibility of further education).

Working conditions Three single-items (Sample item: I am . . . with my working tools and materials.)
I am . . . with the working conditions (working tools and materials,
working environment, work applications, personal design freedom).

Decision range
Three single-items (Sample item: I am . . . with my participation possibilities concerning
my work domain.)

I am . . . with the decision range (classification of work tasks,
possibility of participation).

Working and vacation times Four single-items (Sample item: I am . . . with the planning of my vacation times.)
I am . . . with working and vacation times (working hours, consideration of
wishes in organizing working hours, vacation times, organization of breaks).

Compensations of the employer Three single-items (Sample item: I am . . . with the payment compared to my colleagues.) I am . . . with compensations of the employer (financial, social, job security).

General framework conditions Three single-items (Sample item: I am . . . with the extended benefits offered to me.)
I am . . . with extended benefits (flexible working-time models,
burnout-package, workplace health management).

1 The three points “ . . . ” refer to the rating-scale from “1, very satisfied” to “5, unsatisfied”. An example for the rating of a single-item of the facet “organization and management” with a
rating of “very satisfied” is “I am very satisfied with the image of the company”.

Int. J. Environ. Res. Public Health 2018, 15, 1362 5 of 19

1.2. Job Satisfaction and External Criteria

On one hand, JS is used as an indicator for well-being, e.g., as an output of changes within
a company inducing organizational health performance interventions [40]. On the other hand,
JS is supposed to be a cause for other outcomes like absenteeism, performance, productivity,
work engagement, organizational inefficiency (like counterproductive behaviour), intention to quit,
or commitment [11,21,41]. In the applied field of organizational psychology, JS is used as a broad
indicator of these outcomes or as an indicator of well-being, concluding that any measurement of JS
either as facet-items or facet scales has to be tested with the respective outcomes as external criteria.
The facets of JS lead to different predictions of behaviour and therefore, different interventions can
be derived [20]. In an international study for example the relational aspect of JS has been identified
as the most important facet for performance [42] and in a study among senior managers in the
forestry and wood-processing sector, base salary was the most important factor for motivation [43].
By using organizational-specific results like the previous one then subsequent steps for changes in an
organization can be developed in a tailored manner.

Organizational identification, declared as a strong affective and cognitive bond between employee
and organization, shows a positive relationship with JS [44], whereas intention to quit is related
negatively to JS [41]. The positive relationship between organizational identification and JS also
occurs when JS is summarized from different facets [45]. Jiménez [46] states that different facets of
JS have influence on intention to quit and organizational identification. Satisfaction with making
career and satisfaction with how demanding the job is are the most important influence factors for
organizational identification.

Furthermore, JS and work engagement can be viewed as two different constructs in organizational
psychology with a positive relationship [13,47] but higher levels of arousal for work engagement than
for JS [13]. The importance of work engagement for todays’ work environment has been proved in
many studies [13]. Different facets of JS are meant to make different predictions of work engagement,
e.g., satisfaction with the work by itself is the key driver of work engagement, whereas satisfaction
with payment is not linked to work engagement [48].

Projects in workplace health promotion aim to enhance resources and to reduce stress. In the end,
these projects should improve well-being, often measured in the form of JS [49]. As job resources are a
positive feature of work environment related to motivational outcomes, resources are of an outstanding
interest for companies [50,51] and are further related to well-being [52]. Stress, seen as a process caused
by a load beyond the level of normal functioning [53], is an indispensable part in workplace health
promotion projects. It has been shown that stress and JS are negatively related, whereas the different
facets of JS are differently important [54].

1.3. Research Questions

1.3.1. Facet-Items in Comparison with Facet Scales of Job Satisfaction

One aim of this study is to compare a facet-item measurement with a facet scale measurement
of JS. The used facet scale measurement, the PAJS, is a standardized approach to measure a wide
range of facets of JS and it is possible to compare the results of an organization with a representative
sample. It is hypothesized that facet-items are significantly correlated to the appropriate facet scale of
the PAJS. Furthermore, intercorrelations between the facets of JS should be moderate [55]. In addition,
the facet-items should show high factor loadings within the appropriate factor in a confirmatory factor
analysis with all items of the PAJS. The findings should provide evidence to use a facet-item approach
to measure JS where cost- and time-effectiveness is imperative.

1.3.2. Facets of Job Satisfaction and External Criteria

In addition, as the validity of a measurement must be checked, this is another aim of the present
study. To test validity, the facet-item measurement as well as the facet scale measurement is related to other

Int. J. Environ. Res. Public Health 2018, 15, 1362 6 of 19

external criteria. External criteria in this study are identification with the company, work engagement,
stress, and resources. Correlations between external criteria and the two measurements of JS should
show similar patterns. To interpret the correlation coefficients, the classification from Cohen [56] was
used, pointing out correlations higher than 0.30 are moderate and correlations higher than 0.50 are
high. The level of correlations between JS and organizational identification should be moderate [44].
Furthermore, relationships between JS and work engagement should be moderate to high [13,47] as
well as relationships between JS and resources and stress [54].

1.3.3. Efficiency of a Facet-Items Approach

To prove the efficiency of the newly developed facet-items approach compared to a facet scales
approach, the comparison between the average answer times of the two measurements is another aim
of the present study. It is hypothesized, that the average answer time for the facet-items measurement
is shorter than for the facet scales approach.

2. Materials and Methods

2.1. Participants and Procedure

The participants in this online-study were 788 employees working for an Austrian bank.
The overall response rate was 53% (total of 1495 employees). The study is a first result in a longitudinal
project about workplace health promotion (“Employee Survey 2015—Main Focus on Psychosocial Risk
Management according to the Austrian Employee Protection Act”) and was conducted in the year
2015. The participation in the workplace health promotion project was voluntary. Nearly half of the
employees were female (49.4%), and the others were male (50.6%). The largest portion had no leading
position (74.6%). In this study, 13.8% of the bank employees had no contact to clients (employees in the
back office), and 74.2% worked full-time, the others part-time. Age was measured in four categories:
13.1% were between 21 and 30 years old, 22.7% between 31 and 40 years, 33% between 41 and 50 years,
and 31.2% were older than 50 years.

The survey was advertised on the intranet of the bank and through e-mail. The bank employees
were asked to participate in the workplace health promotion project (including an employee survey)
that takes place every two years and is conducted by an external, independent research institute.
The first part of the survey included the questionnaires of the typical part of the employee survey,
and in the second part, employees were asked to participate in a research project from the University of
Graz to get some information about the effects of JS. At first, participants had to rate their JS measured
with a screening version (measurement of facet-items). The second part of the survey included the PAJS
(measurement of facet scales). The participation in the study was completely voluntary, anonymous,
and confidential. Participants were promised total data protection. The study was carried out in
accordance with the recommendations of the guidelines of the Ethics Commission of the University of
Graz and approved by the Ethics Commission of the University of Graz from 27 March 2015.

2.2. Measures

2.2.1. Job Satisfaction (Facet Scales and Facet-Items)

The PAJS by Jiménez [28] with 38 items belonging to 11 facets was used to measure the facets
of JS with several items for every facet (facet scales). Three to five items belong to every facet
of the PAJS. This scale for job satisfaction (published at a test publisher [28]) has been used in
organizational diagnostic studies in research and in practice. Studies showed Cronbach’s alpha
for the facets of JS measured with the PAJS from 0.82 to 0.91 [28,57]. Criterion validity for the
PAJS showed in different studies a negative relationship of JS with burnout, intention to quit,
or absenteeism [28,58]. Furthermore, construct validity was proven with the Job Diagnostic Survey by

Int. J. Environ. Res. Public Health 2018, 15, 1362 7 of 19

Hackman and Oldham [59,60]. The practical requirements often requested for a shorter version with
high psychometric quality.

Based on the ideas of being efficient (cost and time), a screening version was developed with
the items of the PAJS to measure the facets of JS with facet-items. Therefore, it was accepted to have
items measuring more than one aspect, but for that getting more comprehensible items. With the
idea of being efficient, for the PAJS-Facet-Item (PAJS-FI) eleven items were developed to measure
eleven facets. The development of the facet-items included the name of the facet scale and in
parentheses the single-items of the facet scales or other descriptions of the scale. As an example,
the facet information and communication with three single-items of the PAJS was measured in the PAJS-FI
with the facet-item “I am . . . (rated from “1, very satisfied” to “5, unsatisfied”) with information and
communication (activities in company, treatment of my suggestions, information from the management,
information about innovations)”. Another example for the facet organization and management is
the facet-item “I am . . . (rated from “1, very satisfied” to “5, unsatisfied”) with the organization and
management (effort regarding employees, participation possibilities, image)”. It seems on one hand
to be trivial to compare these two measurements, on the other hand it is important for practice and
economic science to get valuable results for the practical use of efficient measurements in employee
surveys with scientific accuracy [61]. In Table 2, the different facets as well as the facet-items from the
PAJS-FI and sample items from the facet scales of the PAJS are shown. The facet to which the items
belong is also represented in Table 2.

Employees were asked to indicate their agreement on a five-point scale (1 = very satisfied,
5 = unsatisfied). For an easier interpretation of the results, the values were inverted to get high values
referring to high JS. In the present study, the Cronbach’s alpha for the global JS score in PAJS-FI was
α = 0.89 and for the PAJS also α = 0.89.

2.2.2. Identification with the Company

Identification with the company was measured with four different items [28,47] which were
adapted to the employee survey in the company and contained the aspects of recommendation and
reapplying to the company, identification with the company, and proudness of working in this company.
The items had to be rated on a five-point scale (1 = does apply perfectly, 5 = does not apply at all).
For an easier interpretation, the values of identification with the company were inverted to get high
values referring to high identification. A sample item is “I identify myself strongly with the company”.
Cronbach’s alpha for identification with the company was α = 0.90.

2.2.3. Work Engagement

Work engagement was measured with the short version of the UWES [62]. The UWES-9 includes
nine items pertaining to three dimensions: vigor, dedication, and absorption (three items for each
dimension). Participants were asked to rank their answers on a seven-point scale from 0 (never) to 6
(always/every day). Sample items are “At my work, I feel bursting with energy” (vigor), “I am proud
on the work that I do” (dedication), and “I feel happy when I am working intensely” (absorption).
Cronbach’s alpha for work engagement was α = 0.96.

2.2.4. Resources and Stress

Resources and stress were measured with the Recovery-Stress-Questionnaire for Work [63].
With this measurement, the two dimensions stress and resources can be displayed. In the present
study, a short version of the RESTQ-Work (RESTQ-Work-27) was used. For the dimension stress,
the sub-dimensions social emotional stress and loss of meaning can be generated. The dimension
resources contains the sub-dimensions overall recovery, leisure/breaks, psychosocial resources,
and work-related resources. Employees were asked to rate their answers from 0 (never) to 6 (always).
A sample item for the dimension resources is “In the last 7 days and nights I felt physically relaxed”

Int. J. Environ. Res. Public Health 2018, 15, 1362 8 of 19

and a sample item for the dimension stress is “In the last 7 days and nights I felt down”. Cronbach’s
alpha for resources was α = 0.93 and for stress α = 0.94.

3. Results

Data were analysed using Version 24 of Statistical Package for Social Sciences (SPSS (IBM
SPSS software, Armonk, NY, USA) and using the program Mplus (Version 7.3 (Muthén & Muthén,
Los Angeles, CA, USA)).

3.1. Relationship between Facets of PAJS (Facet Scales) and PAJS-FI (Facet-Items)

To test if facet-item measures belong to the appropriate facet scale, Pearson correlations between
the PAJS-FI facet-items and the PAJS facet scales (scales obtained by aggregation of single-items)
were calculated in SPSS. In Table 3, the correlations between the facets of the PAJS and the PAJS-FI
are displayed.

Every facet-item showed a moderate to high correlation with the appropriate facet scale,
ranging from 0.50 to 0.82 (p < 0.01). The lowest correlation between facet-items and facet scales was shown for the facet general framework conditions (0.50, p < 0.01) and the highest correlation for the facet relationship to direct supervisor (0.82, p < 0.01). By further examination of the correlations, it can be seen that the facet-item organization and management correlates higher with the facet scale relationship to direct supervisor (0.67, p < 0.01) than with the facet scale organization and management (0.54, p < 0.01).

The intercorrelations between the facets of the PAJS as well as between the PAJS-FI were small to
high and ranged from 0.20 to 0.70 (p < 0.01) for PAJS-FI and from 0.24 to 0.64 (p < 0.01) for PAJS.

3.2. Confirmatory Factor Analysis for PAJS (Facet Scales) and PAJS-FI (Facet-Items)

To test if the facet-items of the PAJS-FI belong to the same factor as the single-items of the facet
scales of the PAJS and show high factor loadings, a confirmatory factor analysis was conducted.
For every facet of JS, the single-items of the PAJS and the facet-item of the PAJS-FI belonging to
the same facet, were modelled as one factor. All 11 facets were put into one higher-order factor.
The confirmatory factor analysis was conducted in the program Mplus.

In Table 4, the standardized factor loadings of PAJS-FI facet-items with the appropriate facet are
shown. The factor loadings of the single-items of the facet scales (PAJS) are not shown in Table 4.
Standardized loadings for the items of the PAJS-FI reached from 0.64 for the facets general framework
conditions and organization and management to 0.85 for the facets relationship to direct supervisor
and relationship to direct colleagues. Model fit also showed appropriate results: χ2 (1116) = 4300.86,
CFI = 0.90, SRMR = 0.07, RMSEA = 0.06.

Int. J. Environ. Res. Public Health 2018, 15, 1362 9 of 19

Table 3. Correlations between Profile Analysis of Job Satisfaction (PAJS, facet scales) and PAJS-Facet-Item (PAJS-FI, facet-items, N = 788) 1.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

1. Communication (FI)
2. Demanding (FI) 0.34
3. Colleagues (FI) 0.21 0.24
4. Supervisor (FI) 0.35 0.31 0.44
5. Organization (FI) 0.49 0.39 0.40 0.70
6. Career (FI) 0.44 0.44 0.26 0.38 0.51
7. Conditions (FI) 0.32 0.34 0.20 0.20 0.32 0.38
8. Decision range (FI) 0.43 0.47 0.32 0.40 0.53 0.46 0.39
9. Time aspects (FI) 0.27 0.37 0.25 0.22 0.24 0.34 0.41 0.36
10. Compensations (FI) 0.32 0.33 0.20 0.27 0.37 0.49 0.30 0.38 0.32
11. Framework (FI) 0.34 0.36 0.25 0.29 0.37 0.37 0.44 0.45 0.50 0.36
12. Communication (FS) 0.73 0.36 0.26 0.39 0.53 0.50 0.37 0.49 0.31 0.41 0.40
13. Demanding (FS) 0.34 0.76 0.28 0.30 0.37 0.47 0.34 0.49 0.39 0.41 0.40 0.40
14. Colleagues (FS) 0.25 0.25 0.80 0.43 0.43 0.33 0.23 0.35 0.28 0.28 0.27 0.31 0.31
15. Supervisor (FS) 0.36 0.33 0.36 0.82 0.67 0.39 0.23 0.43 0.26 0.30 0.29 0.43 0.37 0.41
16. Organization (FS) 0.52 0.40 0.28 0.37 0.54 0.54 0.39 0.47 0.33 0.55 0.41 0.64 0.47 0.37 0.43
17. Career (FS) 0.41 0.45 0.28 0.35 0.49 0.76 0.37 0.47 0.33 0.47 0.38 0.52 0.53 0.36 0.41 0.58
18. Conditions (FS) 0.29 0.35 0.27 0.20 0.28 0.35 0.68 0.33 0.35 0.29 0.40 0.36 0.37 0.32 0.24 0.41 0.40
19. Decision range (FS) 0.42 0.56 0.32 0.38 0.48 0.44 0.40 0.64 0.44 0.39 0.48 0.51 0.64 0.38 0.43 0.50 0.48 0.37
20. Time aspects (FS) 0.29 0.40 0.31 0.33 0.38 0.38 0.40 0.45 0.66 0.38 0.52 0.36 0.46 0.37 0.38 0.41 0.42 0.40 0.57
21. Compensations (FS) 0.31 0.31 0.18 0.23 0.32 0.48 0.25 0.31 0.27 0.74 0.29 0.37 0.37 0.26 0.28 0.48 0.46 0.31 0.31 0.35
22. Framework (FS) 0.34 0.38 0.30 0.27 0.40 0.44 0.50 0.43 0.46 0.49 0.50 0.43 0.47 0.38 0.34 0.56 0.51 0.54 0.53 0.57 0.46

1 Correlations between the facet-items of the PAJS-FI and their corresponding facet scales of the PAJS are printed in boldface. Communication = information and communication,
Demanding = demanding work, Colleagues = relationship to direct colleagues, Supervisor = relationship to direct supervisor, Organization = organization and management,
Career = chances of making career, Conditions = working conditions, Decision range = decision range, Time aspects = working and vacation times, Compensations = compensations of the
employer, Framework = general framework conditions. FI = facet-items, FS = facet scales. All correlations are significant at p < 0.01.

Int. J. Environ. Res. Public Health 2018, 15, 1362 10 of 19

Table 4. Factor loadings in a confirmatory factor analysis for Profile Analysis of Job Satisfaction
Facet-Item (PAJS-FI, facet-items, N = 788) 1.

PAJS-FI Facet-Items Factor Loading

1. Communication 0.79
2. Demanding 0.79
3. Colleagues 0.85
4. Supervisor 0.85
5. Organization 0.64
6. Career 0.78
7. Conditions 0.70
8. Decision range 0.69
9. Time aspects 0.69
10. Compensations 0.77
11. Framework 0.64

1 Standardized factor loadings are only shown for the facet-items of the PAJS-FI. Items of PAJS are not displayed
in the table due to lack of space but are all higher than 0.60. Communication = information and communication,
Demanding = demanding work, Colleagues = relationship to direct colleagues, Supervisor = relationship
to direct supervisor, Organization = organization and management, Career = chances of making career,
Conditions = working conditions, Decision range = decision range, Time aspects = working and vacation times,
Compensations = compensations of the employer, Framework = general framework conditions. All standardized
factor loadings are significant at p < 0.01.

3.3. The Facets of Job Satisfaction and External Criteria

To test validity, the facet-items of the PAJS-FI were correlated with external criteria. The correlations
of the external criteria with the facet-items of PAJS-FI were compared to the same correlations between
the facet scales of the PAJS and the same external criteria. As external criteria identification with the
company, work engagement, stress, and resources were used. In Table 5, the Pearson correlations
between the facet-items of the PAJS-FI and the facet scales of the PAJS with the external criteria
identification with the company, work engagement, stress, and resources, calculated in SPSS, can be
found. To test if differences between the correlations from PAJS and PAJS-FI with the respective
external criteria exist, a test of the difference between two dependent correlations with one variable in
common was calculated [61,64,65]. For that reason, Bonferroni correction was applied [66,67], and the
results were compared with α = 0.0004 (0.05 divided by 143 possibilities). Results showed significant
differences for several facets especially for organization and management (see Table 5).

The correlations between the different items of identification with the company and the facet-items
of the PAJS-FI ranged from 0.23 (relationship to direct colleagues and identify with the company) to
0.44 (demanding work and reapply at the company, chances of making career and proud to work at
the company). Correlations between the facet scales of the PAJS and the items of identification with
the company reached from 0.27 (relationship to direct colleagues and identify with the company) to
0.65 (organization and management and recommendation of the company). The correlations between
identification with the company and the facet scales (PAJS) were always slightly higher than with the
facet-items of the PAJS-FI except for a few single correlations (mainly for the facet compensations of
the employer). The pattern of the correlational structure remained the same for PAJS and PAJS-FI.
Significant results between PAJS and PAJS-FI were found for the facet organization and management.
These differences were analysed additionally and are described below.

For work engagement, the correlations for the facet-items of the PAJS-FI ranged from 0.23
(relationship to direct colleagues and absorption) to 0.61 (demanding work and dedication). The facet
scales of the PAJS and work engagement showed correlations from 0.26 (compensations of the employer
and absorption) to 0.66 (demanding work and dedication). The aforementioned correlations were
slightly higher than with the facet-items of the PAJS-FI except for the facet compensations of the
employer, but the correlational structure was the same for both measurements. Significant results
were found for the facets information and communication, organization and management, chances of
making career, working and vacation times, and general framework conditions.

Int. J. Environ. Res. Public Health 2018, 15, 1362 11 of 19

Table 5. Correlations between facet-items (Profile Analysis of Job Satisfaction Facet-Item, PAJS-FI; on the left) and facet scales (Profile Analysis of Job Satisfaction,
PAJS; on the right) with the external criteria Identification with Company, Work Engagement, Stress, and Resources (N = 788).

External Criteria Left: Facet-Item (PAJS-FI)|Right: Facet Scale (PAJS) 1

Communication Demanding Colleagues Supervisor Organization Career Conditions Decision Range Time Aspects Compensations Framework

Identi-fication
with Company 2

Recommend 0.39|0.45 0.39|0.42 0.28|0.35 0.35|0.35 0.42|0.65 * 0.43|0.45 0.35|0.35 0.41|0.45 0.34|0.39 0.38|0.33 0.36|0.44
Identify 0.28|0.35 0.36|0.41 0.23|0.27 0.26|0.30 0.32|0.52 * 0.39|0.42 0.30|0.33 0.29|0.37 0.27|0.32 0.36|0.33 0.27|0.38
Reapply 0.38|0.44 0.44|0.47 0.24|0.28 0.34|0.39 0.40|0.59 * 0.43|0.47 0.33|0.33 0.41|0.47 0.32|0.40 0.34|0.29 0.36|0.40
Proud 0.33|0.40 0.43|0.46 0.26|0.28 0.33|0.37 0.38|0.64 * 0.44|0.48 0.35|0.34 0.36|0.42 0.29|0.36 0.41|0.37 0.34|0.44

Work Engage-ment
Vigor 0.31|0.40 * 0.50|0.53 0.32|0.36 0.36|0.41 0.44|0.53 0.41|0.45 0.34|0.38 0.47|0.54 0.35|0.45 * 0.34|0.27 0.38|0.46

Dedication 0.33|0.39 0.61|0.66 0.29|0.31 0.33|0.38 0.40|0.56 * 0.41|0.49 * 0.34|0.37 0.48|0.56 0.35|0.42 0.33|0.29 0.37|0.49 *
Absorption 0.31|0.38 0.52|0.56 0.23|0.27 0.30|0.35 0.38|0.52 * 0.39|0.44 0.32|0.34 0.41|0.49 0.29|0.36 0.31|0.26 0.33|0.43

Stress
Soc. em. stress 3 −0.33|−0.37 −0.35|−0.38 −0.32|−0.35 −0.32|−0.35 −0.38|−0.37 −0.34|−0.32 −0.33|−0.30 −0.41|−0.50 −0.34|−0.39 −0.30|−0.21 * −0.34|−0.33

Loss mean. 4 −0.38|−0.45 −0.48|−0.51 −0.36|−0.42 −0.45|−0.50 −0.50|−0.49 −0.43|−0.43 −0.37|−0.35 −0.49|−0.60 * −0.38|−0.43 −0.37|−0.27 * −0.41|−0.39

Resources

Ov. recovery 5 0.35|0.37 0.42|0.44 0.31|0.36 0.36|0.38 0.42|0.37 0.40|0.38 0.34|0.32 0.43|0.50 0.33|0.40 0.28|0.19 * 0.35|0.36
Leisure/breaks 0.29|0.29 0.31|0.31 0.26|0.34 * 0.26|0.29 0.36|0.31 0.31|0.29 0.33|0.29 0.35|0.42 0.34|0.42 0.27|0.22 0.35|0.34

Psychosoc. res. 6 0.22|0.26 0.20|0.24 0.68|0.72 0.42|0.39 0.39|0.29 0.30|0.31 0.22|0.23 0.34|0.32 0.22|0.27 0.22|0.18 0.25|0.31
Work-rel. res. 7 0.39|0.45 0.49|0.55 0.39|0.40 0.49|0.48 0.50|0.43 0.41|0.46 0.37|0.35 0.59|0.63 0.34|0.42 0.29|0.23 0.38|0.43

1 Communication = information and communication, Demanding = demanding work, Colleagues = relationship to direct colleagues, Supervisor = relationship to direct supervisor,
Organization = organization and management, Career = chances of making career, Conditions = working conditions, Decision range = decision range, Time aspects = working and vacation
times, Compensations = compensations of the employer, Framework = general framework conditions. 2 Identification with Company: Single-item measures, Recommend = I would
recommend the company as employer, Identify = I identify myself strongly with the company, Reapply = I would reapply at the company, Proud = I am proud to work at the company.
3 Soc. em. stress = social emotional stress. 4 Loss mean = loss of meaning. 5 Ov. recovery = overall recovery. 6 Psychosoc. res. = psychosocial resources. 7 Work-rel. res. = work-related
resources. A star (*) denotes a significant differences between correlations of PAJS-FI and PAJS with external criteria.

Int. J. Environ. Res. Public Health 2018, 15, 1362 12 of 19

Concerning stress (sub-dimensions social emotional stress and loss of meaning) the correlations
between the facet-items of the PAJS-FI and stress reached from −0.30 (compensations of the employer
and social emotional stress) to −0.50 (organization and management and loss of meaning). For the
facet scales of the PAJS and stress the correlations reached from −0.21 (compensations of the employer
and social emotional stress) to −0.60 (decision range and loss of meaning), higher than the correlations
with the facet-items of the PAJS-FI except for the facets organization and management, chances of
making career, working conditions, compensations of the employer, and general framework conditions.
Significant differences via Steiger’s Equations were found for the facets decision range as well as
compensations of the employer.

Resources (sub-dimensions overall recovery, leisure/breaks, psychosocial resources, work-related
resources) showed correlations from 0.20 (demanding work and psychosocial resources) to 0.68
(relationship to direct colleagues and psychosocial resources) for the facet-items of the PAJS-FI. For the
facet scales of the PAJS, the correlations ranged from 0.18 (compensations of the employer and
psychosocial resources) to 0.72 (relationship to direct colleagues and psychosocial resources). Most of
the facets showed higher correlations for the facet scales of the PAJS and resources than for the
facet-items of the PAJS-FI except for a few single correlations. The structural pattern for the facet scales
(PAJS) and the facet-items (PAJS-FI) with stress and resources was the same. Significant differences
were found for the facets relationship to direct colleagues as well as compensations of the employer.

In sum, the correlational structures between the facet scales (PAJS) and external criteria were the
same like between facet-items (PAJS-FI) and external criteria. Most correlations showed a moderate
to high level, except for the facets compensations of the employer, working and vacation times,
and relationship to direct colleagues, and a few single correlations.

As the most significant comparisons between PAJS and PAJS-FI resulted for the facet organization and
management, further reliability analyses were explored. The internal consistency for the three single-items
for the facet organization and management from PAJS was α = 0.85, whereas reliability analysis
including the facet-item organization and management showed α = 0.83 (analysed with Cronbach’s
alpha). A more stricter analysis with McDonald’s coefficient omega (omega hierarchical; [68]) showed
ωh = 0.85 vs. ωh = 0.78. Furthermore, item selectivity was lowest for the facet-item. These coefficients
present that the reliability is stronger in the multiple-item version compared to the reliability including
the facet-item.

3.4. Efficiency of the Short Version PAJS-FI

A t-test for dependent samples was calculated to see if the answer time for the measurement
PAJS is different from the answer time for the PAJS-FI. People who interrupted the survey were
excluded from the analysis. The test showed that for answering the items of the PAJS (M = 195.92 s,
SD = 188.24), the answer time lasted significantly longer than for the facet-items of the PAJS-FI
(M = 43.74 s, SD = 83.52, t(577) = −18.34, p < 0.01). The answer time was measured in seconds.

4. Discussion

This paper aimed to test a comprehensive facet-item measurement of JS that includes the
assessment of eleven facets of JS. Furthermore, the facet-item measurement was compared to a
facet scale measurement of JS to analyse construct and criterion validity. The results showed that
the facet-items of JS were significantly and highly related to the facet scales. Additionally, results of
a confirmatory factor analysis showed that the facet-items loaded highly within the appropriate
factor for each facet scale. Furthermore, correlations with external criteria were acceptable showing
valid measurements.

4.1. Comparison between Facet-Items and Facet Scales of Job Satisfaction

JS has been introduced as a global construct measured with one single-item or with multiple
items or as a construct representing different facets measured with facet-items or with multiple

Int. J. Environ. Res. Public Health 2018, 15, 1362 13 of 19

items aggregated to facets (facet scales). The usage of facets is useful for a deeper understanding of
organizational processes [14], and therefore, efficiency plays a major role.

Regarding the first research question, we conclude with the high correlations of the facet scales
with the facet-items (diagonal in bold in Table 3) that both versions can be used for their different
usages. This seems at first sight trivial, but the goal of the study was to develop an efficient
measurement for practical use without forgetting precise, scientific standards. Therefore, the simple
correlations were analysed, and additionally, a confirmatory factor analysis has been conducted.
As expected, the correlations between the facet scales of PAJS and the facet-items of the PAJS-FI were
high, and it is summarized that the PAJS-FI showed appropriate correlations for the eleven facets.
Moreover, confirmatory factor analysis showed for all eleven facets that the facet-items of the PAJS-FI
had high loadings within the appropriate factor. Single-item approaches, like the PAJS-FI for facets of
JS, are useful where cost- and time-effectiveness plays an important role [20], whereas multiple-item
measurements, like the PAJS, are needed in research and organizations to measure relatively complex
constructs reliably [26].

Looking into the details, it can be seen, that the facet-item organization and management showed
a high correlation with the facet scale relationship to direct supervisor (0.67). This is not surprising
as the organization and the management of a company has much in common with the supervisors
of a company, because the management depends on supervisors. Moreover, employees can assess
their direct formal leaders better than management [69]. On the contrary, the facet scale organization
and management did correlate at a moderate level (0.37) with the facet-item relationship to direct
supervisor. Closer examined, the facet-item organization and management includes the nearer
description “efforts regarding employees” (see Table 2). Such efforts depend on people who manage a
company. The employees possibly have their supervisor in mind when thinking about management
and do not include the satisfaction with the organization in their assessment. We suggest to strengthen
the aspect of satisfaction with the organization in a next version of the PAJS-FI.

4.2. Job Satisfaction and External Criteria

By looking at the correlations with external criteria (identification with company, work engagement,
stress and resources) to answer the second research question, it was shown that the correlations
visible looked higher for the facet scale approach, but not in a statistical comparison of the different
correlations. The level of correlations was mostly moderate to high, except for the facets compensations
of the employer, working and vacation times, and relationship to direct colleagues, and a few single
correlations. The correlations showed that the level of correlations for different facets of JS with
external criteria is different, as hypothesized.

The correlational structure remained the same for the facet scales of the PAJS and the facet-items
of the PAJS-FI. The higher identification with the company was, the higher was JS, no matter which
measurement (PAJS or PAJS-FI) was used. For identification with the company, the facet organization
and management showed significantly higher correlations with PAJS than with PAJS-FI. As already
suggested, the facet organization and management in PAJS-FI should be further investigated as
Cronbach’s alpha dropped when including the facet-item. Work engagement seems to have much
in common with JS [48]. Here, also the correlational structure for PAJS and PAJS-FI remained the
same: the higher work engagement was, the higher was JS. Stress (sub-dimensions social emotional
stress and loss of meaning) and JS shared a negative relationship for the facet scales of the PAJS as
well as for the facet-items of the PAJS-FI, whereas the relationship between resources (sub-dimensions
overall recovery, leisure/breaks, psychosocial resources, work-related resources) and JS was positive.
Summarized, the PAJS-FI and PAJS showed similar internal consistencies whereas the PAJS-FI has a
shorter test-length.

The correlations with external criteria were the same for the facet-items of the PAJS-FI and for
the facet scales of the PAJS, except for a few correlations and especially for the facet organization and
management. Schaufeli et al. [13] also concluded in their approach of getting a shorter version of the

Int. J. Environ. Res. Public Health 2018, 15, 1362 14 of 19

UWES scale, that an expectable consequence and drawback of this shortening is that the coefficient
alpha is reduced. We therefore made a deeper analysis for the facet organization and management and
found a lower internal consistency in this facet which may explain the differences between the two
versions of the PAJS. A facet scales approach is more accurate and therefore, different correlations may
remain between the two compared measurements. On the other hand, the correlational structure is in
the same direction as described before. The differences have to be kept in mind when interpreting the
results with the PAJS-FI.

4.3. Efficiency of the PAJS-FI

As it was shown, the relative answer time for PAJS was much longer than for PAJS-FI. To answer
the PAJS-FI, employees needed 44 s whereas the answer time for the items of the PAJS took more than
three minutes. An efficient measurement should not be to simply have a shorter version replacing
a longer version with the drawback of possibly losing information. Instead, the shorter version
should lead to approximately the same information and show first results, e.g., in employee surveys.
Shorter measurements meet the demands of survey participants as otherwise research has to assess
fewer constructs or assess constructs with fewer items [13]. In employee surveys it is useful to have
short measurements to gain as much information as possible [32,61] as there are often also time
constraints [61]. On the other side, the more precise the facets of JS are measured, the more detailed
interventions in a company can be derived. Therefore, the usage of multiple-item measurements of JS
is as legitimate as the usage of facet-items for efficient measurement.

4.4. Limitations

One limitation in this study is the specific sample of employees working in the bank sector.
In agreement with the participating bank, there is no permission to show descriptive data (means and
standard deviations), only the relative relationships. As the interest of this study was to compare
the two different versions PAJS and PAJS-FI, and not to show specific results from bank employees,
the relative relationships suffice. For this study, it was important to test a sample that can participate
in a study where the PAJS and the PAJS-FI are presented at one measure point. This leads to another
limitation in the study: the completion of PAJS and PAJS-FI was not randomized. Bank employees had
to first fill out the PAJS-FI, and in a second step, they had to complete the PAJS.

External criteria like job performance or turnover-rates and their relationship with facet-items of
JS might be interesting and should be further investigated. Moreover, test-retest reliabilities would be
of further interest.

4.5. Practical Implications: Advantages and Disadvantages—The Right Placement for the Right Instrument

JS is seen as a predictor for various outcomes [11] and is therefore a useful variable for
organizational development and hence supports making management decisions [2]. But also as an
indicator for well-being, JS is important [57]. This can be seen in dynamic views of JS e.g., from Büssing
and Bissels [5] or Jiménez [6]. These system theoretical oriented views consider especially the facets of
JS and draw the attention to the qualitative forms of JS. A result of JS can be seen in a “satisfied” rating
but this judgment possibly could be evaluated as a “resigned work satisfaction” [5]. Knowing more
about different aspects of the working life with facets of job satisfaction supports to understand
possible coping strategies of employees which in turn influence the organization.

Employee surveys, especially when measuring JS, are an important instrument for organizational
diagnosis by using the subjective assessment of a company [11]. Such employee surveys should be
adopted to companies and therefore, the results should lead to topics discussed in the management
area of the company and to implementations in the strategy of a company, e.g., in the Balanced
Scorecard [16].

There are many advantages for a facet-item approach to measure the facets of JS: Cost-effective
and short questionnaires need less time and space [32], and the response rate may be higher for shorter

Int. J. Environ. Res. Public Health 2018, 15, 1362 15 of 19

questionnaires [33]. According to Schaufeli et al. [13], shorter forms of questionnaires help to fulfil
the requirements of employee surveys in companies: Due to time constraints, researchers either need
to assess fewer constructs or have to assess the constructs with fewer items, which is especially the
case in employee surveys. In this case, the usage of PAJS-FI is supported. Of course, multiple-item
measures of the facets of JS (facet scales) have their use and advantages. They are because of the
single-items even more differentiated for the employees as well as for the companies to generate
interventions. One fundamental advantage of multiple-item measures is the estimation of internal
consistency reliability, where high reliability is essential for statistical analysis to minimize effects of
error [26]. In cases where small differentiations and the estimation of reliability is needed, the usage of
PAJS is advised.

Another application area for efficient and short measurements is in the upcoming field of eHealth
tools. In this area shorter “scales” and even visual analogue scales are also used as single-item
measures [70] and can be part of workplace health promotion projects. With eHealth tools using visual
analogue scales or the approach of facet-items, it is possible for supervisors to get short and efficient
feedback [71]. This feedback has to be valid and accurate despite usage of short versions [72].

5. Conclusions

Facet-item and facet scale measurements of JS have both their areas of application. The aim of this
study was to show that a facet-item measurement can be a replacement for a facet scale measurement
of JS with multiple-items. In an online study, bank employees filled out both versions of assessments
of JS, and by comparing the structural resemblance of the two measurements, it was demonstrated that
facet-items are an appropriate approach. Facet-items can be an approach to measure the facets of JS in
employee surveys efficiently, but facet scales are also appropriate when the facets should be measured
more accurately. Which approach is used depends on the goals that should be reached. In projects
where efficiency plays a major role, facet-item measures are preferred. This is especially the case in
larger studies [32] or in practice when using eHealth tools [70]. In research or organizations where an
even deeper understanding of JS with the aim of deriving interventions is needed, facet scale measures
have a lot of advantages. This study showed that both approaches are appropriate measures.

As we could see that both forms for measuring JS can be seen as equivalent, they both help in
deriving steps for interventions in organizations. In a next step of analyses, the sociological factors
have to be regarded too. For example, if there are differences between groups like in gender [73] or
in age [74], then the organization has to consider special actions and has to look up for the reasons.
Here, the more detailed version of JS has advantages over the PAJS-FI. Typically, it can be advised in
practice to think about the usage of the short versus long version of any scale in advance, if possible.
If there are already some hypotheses regarding special facets, then the longer version could be helpful.
In the other case when the facet-items had been used, then the next step in practice could be to
investigate the results in small groups [75] (e.g., with so called “health circles”) where the effects are
discussed to see which special aspects of the facets are important.

Furthermore, the usage of approaches to measure JS can also be examined in other areas of work,
which has been shown in other studies [76,77]. In practice, it is recommended to define at first the
goals of measuring JS. In workplace health promotion projects or employee surveys, where efficiency
is a main aim and a lot of other constructs are explored, a facet-item measurement is preferred. In cases
where the facets of JS should be explored and differentiated, the usage of a facet scale measurement
is advised. This study showed for practice that short and efficient measurements are appropriate to
measure the facets of JS.

Author Contributions: A.L. and P.J. formulated the objectives, designed the method, supervised the data
assessment and worked together on the last draft of the paper. A.L. wrote the first draft of the paper, prepared the
current state of the literature and carried out the data assessment. A.L. analysed the data with the support of
N.T. A.B. and N.T. supported the administration and quality assurance. P.J. developed the questionnaire Profile
Analysis of Job Satisfaction Facet-Item (PAJS-FI). All authors reflected the results and discussion.

Int. J. Environ. Res. Public Health 2018, 15, 1362 16 of 19

Funding: This research received no external funding.

Acknowledgments: This publication was printed with the financial support of the University of Graz.

Conflicts of Interest: The authors declare no conflict of interest.

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http://creativecommons.org/

http://creativecommons.org/licenses/by/4.0/.

• Introduction

Measuring Job Satisfaction with Facet-Items versus Facet Scales
Job Satisfaction and External Criteria
Research Questions
Facet-Items in Comparison with Facet Scales of Job Satisfaction
Facets of Job Satisfaction and External Criteria
Efficiency of a Facet-Items Approach

• Materials and Methods

Participants and Procedure
Measures
Job Satisfaction (Facet Scales and Facet-Items)
Identification with the Company
Work Engagement
Resources and Stress

Results
Relationship between Facets of PAJS (Facet Scales) and PAJS-FI (Facet-Items)
Confirmatory Factor Analysis for PAJS (Facet Scales) and PAJS-FI (Facet-Items)
The Facets of Job Satisfaction and External Criteria
Efficiency of the Short Version PAJS-FI

• Discussion

Comparison between Facet-Items and Facet Scales of Job Satisfaction
Job Satisfaction and External Criteria
Efficiency of the PAJS-FI
Limitations
Practical Implications: Advantages and Disadvantages—The Right Placement for the Right Instrument

• Conclusions

References

Eura s ian Journal of Educational Research 85 (2020) 205-224

Eurasian Journal of Educational Research

www.ejer.com.tr

The Role of Self-Efficacy in Job Satisfaction, Organizational Commitment,
Motivation and Job Involvement*

Selcuk DEMIR1

A R T I C L E I N F O A B S T R A C T

Article History: Purpose: Self-efficacy belief procures teachers to root

for each other’s development in some issues such as

ameliorating new methods to conduct much more
effective teaching. A school with a high level of self-
efficacy teachers makes a great contribution in order
to corroborate self-efficacy perceptions of students.

When examining it on a model with many attitudinal
variables, self-efficacy belief, an important concept in
terms of education quality, has been deemed
significant so as to propound the effects of self –

efficacy more clearly. This study aimed to determine
the relationship between self-efficacy and job
satisfaction, organizational commitment, motivation

and job involvement.
Research Method: 321 teachers from 33 schools that

were selected randomly with the cluster sampling
method from the middle schools in the province of

Received: 21 Dec. 2018

Received in revised form: 04 Jan. 2020

Accepted: 11 Jan. 2020
DOI: 10.14689/ejer.2020.85.10

Keywords

self-efficacy, attitudinal outputs,
mediation effect, performance,
productivity

Hatay city center in the 2017-2018 academic year have composed the sampling of this

study.

Findings: The more teachers’ self-efficacy beliefs increased, the more their job satisfaction,

organizational commitment, motivation and job involvement increased. Both job satisfaction
and organizational commitment partially mediated the relationship between teachers’ sense

of self-efficacy and motivation. Self-efficacy beliefs positively affected teachers’ job
involvement through the full mediation effect of job satisfaction and motivation.
Organizational commitment and motivation fully mediated the relationship between teachers’
self-efficacy and job involvement.
Implications for Research and Practice: It is crucial for school administrators to contribute to

amend and strengthen self-efficacy perceptions of teachers if they hope teachers to take
positive attitudes towards their work much more frequently and to take the edge off negative
attitudes.

© 2020 Ani Publishing Ltd. All rights reserved

*This study was partly presented at the 5th International Eurasian Educational Research Congress in Antalya,

02 May – 05 May, 2018
1 Ministry of National Education E -mail: selcuk_demirs@hotmail.com, TURKEY ORCID:
https://orcid.org/0000 -0003-2904-6443

206 Selcuk DEMIR
Eurasian Journal of Educational Research 85 (2020 ) 205-224

Introduction

In developing countries, teachers are the most important members of the education

system. These countries want to recruit teachers with high quality. Teachers’ efficacy

is crucial for having a successful education system. In relation to getting teachers with
high self-efficacy, some work-related attitudes become prominent such as job

satisfaction, organizational commitment, motivation and job involvement. The

concept of self-efficacy enables teachers to develop positive attitudes to their work
environment. Teachers with high self-efficacy believe that since they have a great

degree of professional capabilities in teaching and managing challenging tasks, they

could attain their full potential. It has been remarked that these obtained beliefs
positively mirror on all the students. So , students feel powerful and become more

successful at managing challenging problems, learning subjects and even learning to

learn in their schools.

Former studies have shown that so as to promote positive attitudes and effective

strategies to cope with negative attitudes, self-efficacy is a magnificent organizational

facilitator (Betoret & Artiga, 2010). Teachers’ senses of self-efficacy influence their
attitude and behavior in the classroom. Self-efficacy beliefs redound on the energy

they expend whilst teaching, the goals they set, and their perceptions of self –

confidence (Demir, 2018a; Tschannen-Moran & Woolfolk Hoy, 2001).

There appear to be no available studies in which all these performance variables

are examined together in the literature. Commonly, there are individual studies
examining the links between self-efficacy and various positive and negative attitudes.

This study provides to enlighten how teachers’ self-efficacy level is associated with job

satisfaction, organizational commitment, motivation and job involvement. These
indicators are crucial for obtaining performance. it has been anti cipated theoretically

and practically to present better perspectives for the current status of teachers in

educational organizations. This study could also generate links between alternative
theoretical models.

Theoretical Foundations

Self-Efficacy

Self-efficacy is defined as individuals’ beliefs that they are capable of reaching the
goals and performing the specific tasks (Bandura, 2002; Hefferon & Boniwell, 2011;

Luszczynska, Scholz, & Schwarzer, 2005; Robbins, Decenzo, & Coulter, 2013;

Schermerhorn et al., 2011). Self-efficacy is expressed as ‘the power of I can’ (Hefferon
& Boniwell, 2011: 104). Research has indicated that individuals who have a high level

of self-efficacy attach on their competences about competing with the challenges and

obstacles more than individuals with a less level of self-efficacy. A low level of self-
efficacy causes individuals to decrease or dissolve their efforts to cope with the

challenges and obstacles (Cetin & Basim, 2014; Robbins et al., 2013).

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The understanding of an employee’s capacity and competence impact his/her

perceptions, motivation and performance (Tschannen-Moran & Woolfolk Hoy, 2001;
Tschannen-Moran, Woolfolk Hoy, & Hoy, 1998; Woolfolk & Hoy, 1990). If employees

despair of succeeding in a task, they won’t endeavor to perform (Lunenburg &

Ornstein, 2012). Self-efficacy beliefs affect the preferences we decide on, the effort we
make, our level of motivation, how we feel about ourselves or others, the duty and

how long we insist on when we are exposed to obstacles (Hefferon & Boniwell, 2011).

Self-efficacy can aid teachers to live up to their full potential in teaching.

Job Satisfaction

Job satisfaction has been one of the most common and most investigated concepts

because of its connections with the other important phenomena relevant to work
(Ozkalp & Kirel, 2010). Job satisfaction is described as the degree to which an

individual has positive and negative feelings about a job, other workers and work

environment (Schermerhorn et al., 2011). Job satisfaction is pr evalently known as an
internal reaction against the work conditions (Gkolia, Belias, & Koustelios, 2014). The

internal reaction is emotional and attitudinal response (Schermerhorn et al., 2011).

Many studies have unveiled the connections between job satisf action and other
variables in organizations (Schermerhorn et al., 2011). A meta-analysis of nine studies

involving 1739 workers found out a significant positive relationship between job

satisfaction and motivation. This meta-analysis study also showed satisfaction with
the manager was positively correlated with motivation (Kinichi, McKee -Ryan,

Schriesheim, & Carson, 2002). Another meta-analysis of 87 studies involving 27.925

has revealed that job satisfaction is positively related to job involvement (Brown, 1996).
Based on these findings it has been considered that chuffed teachers are motivated to

do their best for effective teaching to students, so this state provides teachers to devote

themselves to their job.

Organizational Commitment

Organizational commitment is a more general concept with reference to job

satisfaction (Kreitner & Kinichi, 2009). Job satisfaction is just involved in an
individual’s degree of satisfaction with the job, whereas organizational commitment

is about an individual’s commitment to both job and in business (Guney, 2012).

Organizational commitment refers to what extent an employee is dedicated to his/her
organization and its goals (Schermerhorn et al., 2011). The concept of organizational

commitment has three facets as affective commitment, normative commitment and

continuous commitment (Allen & Meyer, 1990; Meyer & Allen, 1991). Affective
commitment includes positive feelings such as emotional attachment and

identification with the employing organization. Continuance commitment stands for

the degree of employing organization commitment which is concerned with the losses
(labor, time and money) quitting the organization. Finally, normative commitment

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means to persist with remaining in an organization because of the feeling of obligation

(Allen & Meyer, 1990; Allen & Meyer, 1996; Meyer & Allen, 1991).

People strongly committed to employing organization s to identify with their
organization and take pride in being a member of their organization (Schermerhorn et

al., 2011). Committed workers have a desire for their work and feel a deep affection to

their work, but uncommitted workers do not have a wish or energy for their work and
don’t care about this case (Robbins et al., 2013). Studies showed that a higher level of

organizational commitment was associated with a higher level of positive job-related

attitudes and behaviors (Kreitner & Kinichi, 2009). In the related literature
organizational commitment has a positive correlation with job involvement and job

performance and negative turnover (Kreitner & Kinichi, 2009; Schermerhorn et al.,
2011). These findings are extremely important because managers can increase

productivity and efficiency by investing and strengthening teachers’ organizational

commitment. In light of the findings, it’s claimed that faithful teachers have a great
desire and energy for teaching the students, feel a deep affection to their job and pull

through with flying colors.

Motivation

Although administrators have a consensus that motivation is an important
indicator of job performance in the organizations, they don’t have a general agreement

on the description of motivation. The concept of motivation is derived from “movere”

(to move) in Latin words (Lunenburg & Ornstein, 2012). Motivation is generally a
psychological process including energy, direction, and persistence of a person’s effort

that is goal-directed (Robbins et al., 2013). Many motivation theories have been
developed to express the reason why people decide to take the plunge and processes

which provide motivation. Most motivation theories agree that the least supplied need

of people is the best motivator for them (Donmez, 2013).

Motivation has been one of the most conspicuous in administration because of its

relations with job performance, productivity and efficacy (Donmez, 2013; Lunenburg

& Ornstein, 2012). According to Han and Yin (2016) teacher motivation is a vital factor
that has a relationship with several variables in education like student motivation,

teaching practice and teachers’ psychological satisfaction and well -being. They also

indicate that motivation is essential for determining how to attract and retain teachers’
energy and persistence in teaching activities. Although every teacher has a different

personality and need, administrators should motivate them in the common vision in

the direction of organizational aims.

Job Involvement

The concept of job involvement reflects to what extent an individual is actively

involved with his/her job tasks (Schermerhorn et al., 2011). People with high job
involvement are dedicated to and identify with their work roles (Kreitner & Kinichi,

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2009; Robbins et al., 2013). Working beyond expectations to finish the given task is

extremely important for people with high job involve ment (Kreitner & Kinichi, 2009)
because they consider performance is necessary for protecting their self -esteem

(Robbins et al., 2013). Brown (1996) has found out in a meta-analysis study in

connection with thousands of people that job involvement has a positive association
with job satisfaction, organizational commitment and intrinsic motivation and

negatively correlated to intentions to leave the organization. This finding implies that

school administrators can enhance teachers’ level of job involvement b y providing
positive work environments that support job satisfaction, organizational commitment

and motivation.

The Relationships between Self-efficacy, Job Satisfaction, Organizational
Commitment, Motivation and Job involvement

Self-efficacy is a self-confident perception of teachers that is considered as a crucial

impact on student learning. The perceptions of self-efficacy often influence teachers’

thinking models, behaviors, level of commitment, and job performance (Caprara,
Barbaranelli, Steca, & Malone, 2006; Yang, Kao, & Huang, 2006). Self-efficacy is an

organizational adjuvant to procure positive outcomes (Betoret & Artiga, 2010;

Hefferon & Boniwell, 2011). Related studies have found a favorable tie between self-
efficacy and affirmative attitudes such as job satisfaction (Caprara et al., 2006; Gkolia

et al., 2014), organizational commitment (Busch, Fallan, & Pettersen, 1998; Mulvaney,

2014), motivation (Rosario, Blas, & Valle, 2009; Tschannen-Moran & Woolfolk Hoy,
2001; Tschannen-Moran et al., 1998; Woolfolk & Hoy, 1990) and job involvement (Yang

et al., 2006). Studies showed the relationship between job satisfaction and mot ivation

and job involvement (Brown, 1996; Kinichi et al., 2002; Kreitner & Kinichi, 2009;
Ozkalp & Kirel, 2010; Schermerhorn et al., 2011). Many studies also revealed

organizational commitment and motivation and job involvement were correlated with

each other (Brown, 1996; Kreitner & Kinichi, 2009; Schermerhorn et al., 2011).

Purpose of the study

It’s vital for schools to be effective by having teachers with a greater level of self-

efficacy and consequently positive attitudes. Related literature brings into the gap that
much more studies about the self-efficacy phenomenon are necessary in educational

research. Moreover, no study could enucleate the relationship between self-efficacy

and job satisfaction, organizational commitment, motivation and job involvement in
only one study, and accordingly, it can be notified that this study presents a new model

as per theoretical assumptions. This study has been implemented in order to

determine the positive consequences of teachers’ self-efficacy levels at school
organizations. The hypothesized model of this research is given in Figure 1.

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Figure 1. The Hypothesized Model

According to the hypothesized model in figure1, the hypothesis of this study was

formulated as the following:

H1: Self-efficacy belief positively affects teachers’ level of job satisfaction.

H2: Self-efficacy belief positively affects teachers’ level of organizational

commitment.

H3: Self-efficacy belief positively influences teachers’ level of motivation.

H4: Self-efficacy belief has a positive impact on teachers’ level of job

involvement.

H5: Self-efficacy belief positively affects teachers’ motivation through the

mediating effect of job satisfaction.

H6: Self-efficacy belief positively affects teachers’ motivation through the
mediating effect of organizational commitment.

H7: Self-efficacy belief positively affects teachers’ level of job involvement through

the mediating effect of job satisfaction, organizational commitment and motivation.

Method

Research Design

This study has rejoiced in correlational design. Firstly , self-efficacy, job satisfaction,

organizational commitment, motivation and job involvement levels of the teachers
have been discovered through scales. Then, the relationships among these variables

have been explored.

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Research Sample

The population of the research was composed of teachers working at secondary

schools at Hatay city center in Turkey in the 2017-2018 academic year. 33 secondary
schools have been chosen randomly by the help of the cluster sampling method and

the scales have been conducted to all the teachers at these schools. 321 teachers have

agreed to take part as a sample of this study.

59.8% of the teachers were male (f = 192) and 40.2% were female (f = 129) who

responded as participants of this study. 77.9% of the participants were married (f =

250), whereas 22.1% of them were single (f = 71). The most common age range of the
participants has been 31-40 years old (f = 131), with a percentage of 40.8%. The majority

of the participants (f = 163) had 1 to ten years of professional experience with a

percentage of 50.8%.

Research Instruments and Procedures

Data of this study have been gathered by means of five -point Likert-type scales.

The scales of Self-Efficacy, Job Satisfaction, Organizational Commitment, Motivation,
and Job Involvement were applied to obtain the research data. On the data gathered

in this study, exploratory and then confirmatory factor analyses were performed.

Validity and Reliability

Self-efficacy Scale has been improved by Schmitz and Schwarzer (2000) and

adapted to Turkish by Yilmaz, Koseoglu, Gercek and Soran (2004). A two factor scale

consisting of eight items presented a good fit to the data (explained variance = 57.107
%, Bartlett = 0.000, KMO = 0.806, χ² =46.538, df =18, χ²/df =2.585, P-value = 0.000,

RMSEA = 0.070, IFI = 0.958, TLI = 0.933, CFI = 0.957). Cronbach’s Alpha has been 0.787

for the overall scale. Cronbach’s Alpha coefficients of two dimensions were as follows;
Coping business behavior: 0.725, Innovator business behavior: 0.772.

To measure job satisfaction, a global job satisfaction measure has been wielded. Job

satisfaction has been developed by Griffin et al. (2010) and adapted by Karakus et al.
(2019). A one-factor scale containing five items has acclimated with the data (explained

variance =58.858%, Bartlett = 0.000, KMO = 0.804, χ² = 9.289, df = 5, χ²/df = 1.858, P-

value = 0.098, RMSEA = 0.052, IFI = 0.994, TLI = 0.988, CFI = 0.994). Cronbach’s Alpha
coefficient has been 0.782 for the scale.

Organizational commitment scale was developed by Karakus and Aslan (2009).

This one-factor scale was in accordance with the data (explained variance = 49.052 %,
Bartlett = 0.000, KMO = 0.857, χ² = 23.508, df = 14, χ²/df = 1.679, P-value = 0.052,

RMSEA = 0.046, IFI = 0.988, TLI = 0.982, CFI = 0.988). Cronbach’s Alpha of the scale

has been evaluated as 0.812.

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Motivation at work scale was developed by Gagné, et al. (2010) and translated into

Turkish by Akbolat and Isik (2012). These three factor-scale fit to the data well

(explained variance = 75.226 %, Bartlett = 0.000, KMO = 0.842, χ² = 36.585, df = 17, χ²/df
= 2.152, P-value = 0.004, RMSEA = 0.060, IFI = 0.982, TLI = 0.971, CFI = 0.982).

Cronbach’s Alpha of the overall scale was 0.856. Cronbach’s Alpha coefficients of three

dimensions has been determined as below; Specific regulation: 0.850, Intrinsic
motivation: 0.846 and Introject regulation: 694.

Job involvement scale was developed by Griffin et al. (2010) and adapted to

Turkish by Demir (2018b). A single factor scale consisting of three items presented a
good fit to the data (explained variance = 71.783%, Bartlett = 0.000, KMO = 0.704, χ² =

2.445, df = 1, χ²/df = 2.445, P-value = 0.118, RMSEA = 0.067, IFI = 0.995, TLI = 0.995,
CFI = 0.986). Cronbach’s Alpha of this scale was calculated as 0.803.

Data Analysis

The collected data were analyzed using SPSS. Data were determined to have a

linear and normal distribution. Also, the relationships among the research variables
were detected with regard to the multicollinearity problem (Tolerance > .2, VIF < 10).

AMOS has been benefitted for confirmatory factor analyses (CFA) and structural

equation modeling (SEM) to unveil the dealings among these constructs regarding the
proposed model (Arbuckle, 2009). CFA was performed separately for each scale in this

study.

CFA is performed after exploratory factor analysis and presents real statistical
values (Kline, 2011). CFA tests and confirms whether the data set is suitable for the

proposed model or not. SEM has common usage in scientific studies by the virtue of
revealing measurement errors regarding observed or unobserved variables and direct

and indirect influences of variables in the proposed model (Meydan & Sesen, 2015).

AMOS is one of the SEM software programs that are available for examining the
relationships among the constructs as correlational and causative in the multivariate

studies (Bayram, 2013; Byrne, 2010; Kline, 2011; Meydan & Sesen, 2015). As a

consequence of these reasons, this study has utilized SEM via AMOS.

RMSEA, IFI, TLI, CFI, X2/df (CMIN/DF) and the level of significance (p) fit

indexes have been noted for the assessment of the goodness of fit model. With RMSEA

value being between 0 and 0.08; X2/sd value between 0 and 3; p-value being between
0.01 and 0.05, and the values of IFI, CFI, and NFI between 0.90 and 1.00 reveal good fit

indexes (Byrne, 2010; Kline, 2011). In exploratory and confirmatory factor analyses, the

least boundary of factor loads are taken as 0.30. If there is a restricted number of items
in a scale prepared in the field of social sciences, the lowest boundary can be

minimized to 0.30 for factor load (Buyukozturk, 2012; Costello & Osborne, 2005) .

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Results

Descriptive Statistics and Correlations

The values of descriptive statistics and correlations are given in Table 1.

Table 1.

Descriptive Statistics and Correlation Matrix of the Variables in the Study

Variables X Sd. std er. 1 2 3 4 5

1.S.E. 3.786 .536 .029 1

2.Sat. 4.145 .680 .037 .288** 1

3.Com. 3.072 .792 .044 .249** .203** 1

4. Mot. 3.752 .695 .038 .328** .617** .365** 1

5.Inv. 3.406 0.940 .052 .247** .434** .279** .527** 1

*p<.05, **p<.01

Notes: S. E.: Self-efficacy, Sat.: Job satisfaction, Com.: Organizational commitment, Mot.:

Motivation, Inv.: Job involvement.

According to the mean scores, self-efficacy, job satisfaction and motivation levels
of teachers are slightly high (4). Also, their organizational commitment and job

involvement are at a moderate level (3). With reference to the correlation matrix, self-

efficacy has a positive correlation with job satisfaction, organizational commitment,
motivation and job involvement. Job satisfaction, organi zational commitment,

motivation and job involvement are all positively correlated with each other. All of the

variables are correlated with each other at a 0.01 significance level.

In line with the modification indices, five items were deleted and three er ror

covariances were added to the model. Respectively C8, C2, M10, M11 and M12 items

were deleted. C8 (0.138) and C2 (0. 140) were deleted because they had low factor
loading under .30. M10, M11 and M12 have been obliterated since their error variance

has been so high and it increased chi-square of the model too much. Error covariances

have been supplemented between S4 and S5, I1 and I2, M1 and M3 because the errors
are related to each other. The measurement model shows that the scales exhibited a

goodness of fit index for the data (x2 = 825.930, df = 446, x2/df = 1.852, IFI = .914, TLI

= .903, CFI =

.913, RMSEA = .052).

At this model, all the latent variables have significant
and high correlations with each other (Figure 2). The measurement model with

standardized coefficients is given in Figure 2.

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Figure 2. The Measurement Model

Notes: SEfficacy: Self-efficacy, JSat.: Job satisfaction, OCom.: Organizational commitment, Mot.:

Motivation, Inv.: Job involvement, Coping: Coping business behavior, Innovator: Innovator

business behavior. Fit indices: x2 = 825.930, df = 446, x2/df = 1.852, IFI = .914, TLI = .903, CFI =

.913, RMSEA = .052).

After presenting the good fit of the measurement model, the covariances between

the latent variables have been cleared and one-way paths have been interlarded these

latent variables according to the theoretical assumptions. The paths of SEfficacy → JInv
(ß = -.036, p = .635), JSat → OCom (ß = .090, p = .133) and OCom → JInv (ß = .093, p =

.094) has been erased because of their insignificant path coefficients (Table 1). The final

structural model presented a good fit to the data (x2 = 830.522, df = 449, x2/df = 1.850,
IFI = .914, TLI = .903, CFI = .913, RMSEA = .052).

Deletions of the insignificant paths for the final structural equation model are
presented in Table 1.

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Table 1.

Deletions of the Insignificant Paths for the Final Structural Equation Model
x2 df x2/df ∆x2 IFI TLI CFI RMSEA

1. Saturated model 825.930 446 1.852 – .914 .903 .913 .052

2. SEfficacy → JInv 826.149 447 1.848 0.004 .914 .904 .913 .051

3. JSat → OCom 827.757 448 1.848 0.000 .914 .904 .913 .051

4. OCom → JInv 830.522 449 1.850 0.002 .914 .903 .913 .052

Notes: SEfficacy.: Self-efficacy, JSat.: Job satisfaction, OCom.: Organizational commitment, JInv.:
Job involvement.

The final structural model which has standardized path coefficients has been
presented in Figure 3.

Figure 3. The Structural Equation Model

Notes: SEfficacy: Self-efficacy, JSat.: Job satisfaction, OCom.: Organizational commitment, Mot.:
Motivation, Inv.: Job involvement, Coping: Coping business behavior, Innovator: Innovator

business behavior. Fit indices: x2 = 825.930, df = 44 6, x2/df = 1.852, IFI = .914, TLI = .903, CFI =

.913, RMSEA = .052).

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According to the structural model that yields the fit indices, as teachers’ self –

efficacy beliefs enhance, job satisfaction, organizational commitment, motivation and

job involvement levels increase. Both job satisfaction and organizational commitment
partially mediate the relationship between teachers’ sense of self -efficacy and

motivation. Self-efficacy beliefs positively affect teachers’ job involvement through the

full mediation effect of job satisfaction and motivation. Organizational commitment
and motivation fully mediate the relationship between teachers’ self -efficacy and job

involvement (Figure 3).

Discussion, Conclusion and Recommendations

Previous studies have demonstrated that teachers’ self-efficacy beliefs concerned

with teaching practices and managing challenges are highly correlated to the extent
that they are confident about their potential to accomplish the new achievements on

their profession (Rosario et al., 2009). When the related literature was examined there

is no available research including and regarding the sense of self-efficacy, job
satisfaction, organizational commitment, motivation and job involvement altogether.

This study conducted a model for better understanding of the present level of self-

efficacy beliefs of teachers in educational organizations. Structural equation modeling
also collaborated on a conceptual model in which teachers’ self -efficacy beliefs

predicted their job satisfaction, organizational commitment, motivation and job

involvement.

This study revealed that self-efficacy beliefs positively affects teachers’ job

satisfaction, organizational commitment, motivation and job involvement. Similarly,

other studies revealed that sense of self-efficacy positively affects job satisfaction
(Caprara et al., 2006; Gkolia et al., 2014), organizational commitment (Busch et al., 1998;

Mulvaney, 2014; Tsai, Tsai, & Wang, 2011), motivation (Rosario et al., 2009; Tschannen-

Moran & Woolfolk Hoy, 2001; Tschannen-Moran et al., 1998; Woolfolk & Hoy, 1990)
and job involvement (Yang et al., 2006). In the related literature, self-efficacy refers to

an organizational facilitator to attain positive outcomes (Betoret & Artiga, 2010;

Hefferon & Boniwell, 2011). The perceptions of self-efficacy have an impact on
teachers’ behaviors, level of commitment, and job performance (Caprara et al., 2006;

Yang et al., 2006). These results reveal the accuracy of hypothesizes stated in H1, H2,

H3, and H4.

Related studies revealed that self-efficacy has a direct impact on job satisfaction

(Caprara et al., 2006; Gkolia et al., 2014). Kinicki et al. (2002) found in their meta –

analysis that job satisfaction positively influences motivation. Self -efficacy also
positively predicted motivation (Rosario et al., 2009; Tschannen-Moran & Woolfolk

Hoy, 2001; Tschannen-Moran et al., 1998; Woolfolk & Hoy, 1990). Similar to these
findings, this current study pointed out that self-efficacy is a predictor for teachers’

motivation through the partial effect of job satisfaction. Therefore, hypothesis V was

confirmed.

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Related studies revealed a positive relationship between self-efficacy and

organizational commitment (Busch et al., 1998; Mulvaney, 2014; Tsai et al., 2011).
Researchers found out that organizational commitment is an important predictor for

obtaining work motivation (Battistelli et al., 2013; Lunenburg & Ornstein, 2012). As

mentioned, self-efficacy also positively predicted motivation (Rosario et al., 2009;
Tschannen-Moran & Woolfolk Hoy, 2001; Tschannen-Moran et al., 1998; Woolfolk &

Hoy, 1990). Similar, to these findings, this study revealed that self-efficacy is a

predictor of teachers’ motivation through the partial effect of organizational
commitment. Therefore, hypothesis VI was confirmed.

If teachers have perceptions of self-efficacy, they will be gratified with their job and

devote themselves to their organization due to managing the given tasks effectively.
Positive perceptions enable to an increase in other set s of perceptions. All of these

positive emotions together provide teachers to be more motivated in their professions.

Brown (1996) showed the relationship between job satisfaction, organizational
commitment, motivation and job involvement. Previous studies (Donmez, 2013;

Lunenburg & Ornstein, 2012; Saygin & Saygin, 2016) indicate that motivation is

positively correlated with job performance. If teachers have a sense of self -efficacy,
they are satisfied with their job and committed to their job ; therefore, they are highly

motivated to do challenging tasks. Murray (2014) indicates that positive attitudes

provide high performance and fondness of work. Similar , to these findings, this
present study also showed that self-efficacy is a predictor of teachers’ level of job

involvement through the partial effect of job satisfaction, organizational commitment,

and motivation. Hence hypothesis VII was confirmed.

This current study pointed out that job satisfaction has a direct and indirect impact

on job involvement. Similarly, Demir (2018b) found that teachers’ level of job

satisfaction positively influences their job involvement. On the contrary, Knoop (1995)
revealed that nurses’ level of job involvement isn’t correlated with their overall job

satisfaction, but only in the aspects of satisfaction with work and promotion

opportunities. It has been extrapolated that taking a different consequence aside from
current studies may be gathered by taking samples from organizations in different

cultural structures or differentiation of scale factor structures.

Even if organizations have all these sources such as raw material, capital related to
economy and state of the art technology, if they are not with skilled employees who

have positive attitudes and behaviors, they will suffer extreme hardship. Creating a

struggling organization is just possible by qualified individuals. Given these realities,
this study examined how to increase teachers’ positive attitudes. This study clears up

that self-efficacy is a predictor of job satisfaction, organizational commitment,
motivation and job involvement. In the related literature, these terms are known as

performance variables. Motivation and job involvement levels of the teachers increase

By increasing their self-efficacy beliefs, job satisfaction and organizational
commitment. In this way, teachers wage the education and training activities

influentially and exuberantly.

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School administrators should be recommended to struggle to enhance the teachers’

self-efficacy beliefs in order to increase positiv e attitudes at schools, in this way

teachers’ performance can enhance. Furthermore, educational programs may be edited
on the purpose of increasing teachers’ perception of self-efficacy. Educational

programs are extremely important for developing personal experiences and feeling

competent.

As limitations, this study focuses on the educational environment. Th is makes it

difficult to make a comparison for any profit organization. The researcher

recommends a quantitative study combined with a qualitative study to reveal in-depth
relations among these variables. In spite of these restrictions, the outcomes of this

study present valuable new aspects regarding the relationship between self -efficacy,
job satisfaction, organizational commitment, motivation and job i nvolvement as they

are applied to the profit and non-profit organizations.

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222 Selcuk DEMIR
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Öz Yeterliğin İş Doyumu, Örgütsel Bağlılık, Motivasyon ve İşe

Sargınlıktaki Rolü

Atıf:

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Research, 85, 205-224, DOI: 10.14689/ejer.2020.85.10

Özet

Problem Durumu: Örgütler; ekonomi ile ilişkili sermayeye ve her türlü ham maddeye

ve teknolojiye sahip olsalar da pozitif tutum ve davranışlar ı olan, nitelikli çalışanlara

sahip olmadıkça pek çok zorlukla karşılaşırlar. Yaşayan ve rekabet eden bir örgüt, öz
yeterlik inançları olan çalışanlarla oluşturulabilir. Öz yeterlik inançları yüksek

düzeyde olan öğretmenler, işlerini yaparken kapasitelerini tam olarak kullanabilir ve

zorlu görevleri başarabilir. Bu kişilerin öz yeterlik algılarının yüksek düzeyde olması,
işe karşı geliştirdikleri tutum ve davranışlarını da olumlu etkiler. Eğitim örgütlerinde,

kritik değişkenlerle ilişkili olduğu bilinen öz yeterl ik algısına ilişkin sınırlı sayıda

araştırma bulunmaktadır. Ayrıca eğitim örgütlerinde iş doyumu, örgütsel bağlılık,
motivasyon ve işe sargınlık değişkenlerinin öz yeterlikle bir arada işlendiği bir

araştırmaya rastlanılmamıştır. Bu araştırma alternatif mo deller üretilmesine ve

kavramlar arasındaki ilişkilerin daha iyi anlaşılmasına olanak sağlamaktadır.

Araştırmanın Amacı: Bu çalışmada; öğretmenlerin öz yeterlik inançları ile iş doyumu,

örgütsel bağlılık, motivasyon ve işe sargınlık düzeyleri arasındaki i lişkinin açığa
çıkarılması amaçlanmaktadır.

Yukarıdaki araştırmanın amacı bağlamında şu hipotezler test edilmiştir:

H1: Öğretmenin sahip olduğu öz yeterlik inancı, iş doyum düzeyini pozitif olarak
etkilemektedir.

H2: Öğretmenin sahip olduğu öz yeterlik inancı, örgütsel bağlılık düzeyini pozitif

olarak etkilemektedir.

H3: Öğretmenin sahip olduğu öz yeterlik inancı, motivasyon düzeyini pozitif

olarak etkilemektedir.

H4: Öğretmenin sahip olduğu öz yeterlik inancı, işe sargınlık düzeyini pozitif
olarak etkilemektedir

H5: Öğretmenin sahip olduğu öz yeterlik inancı, iş doyumunun aracılık etkisiyle

motivasyon düzeyini pozitif olarak etkilemektedir.

H6: Öğretmenin sahip olduğu öz yeterlik inancı, örgütsel bağlılığın aracılık

etkisiyle motivasyon düzeyini pozitif olarak etkilemektedir.

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Eurasian Journal of Educational Research 85 (2020) 205-224

223

H7: Öğretmenin sahip olduğu öz yeterlik inancı; iş doyumu, örgütsel bağlılık ve

motivasyonun aracılık etkisiyle işe sargınlık düzeyini pozitif olarak etkilemektedir.

Araştırmanın Yöntemi: Bu çalışmada iki ya da daha fazla değişken arasındaki

ilişkilerinin yönünü ve düzeyini ortaya koyan ilişkisel tarama deseni kullanılmıştır.

Araştırmanın çalışma evreni; 2017-2018 eğitim öğretim yılında Hatay il merkezindeki
ortaokullarda görev yapan öğretmenlerdir. Bu araştırmada küme örnekleme yöntemi

kullanılmıştır. Hatay il merkezindeki her ortaokul bir küme olarak değerlendirilip

okullar rastgele seçilmiştir. Seçilen 33 okulda görev yapmakta olan 321 öğretmen, bu
araştırmanın örneklemini oluşturmaktadır. Veri lerin toplanmasında; öz yeterlik

ölçeği, iş doyumu ölçeği, örgütsel bağlılık ölçeği, motivasyon ölçeği ve işe sargınlık

ölçeği olmak üzere beş farklı ölçekten yararlanılmıştır .

Araştırmanın Bulguları: Öğretmenlerin bu araştırmada, yararlanılan ölçme

araçlarındaki maddelere katılım düzeylerini ortaya koyan aritmetik ortalama ve

standart sapma değerleri incelendiğinde; öz yeterlik, iş doyumu ve motivasyon
düzeylerinin kısmen yüksek düzeyde olduğu görülmüştür. Öğretmenlerin örgütsel

bağlılık ve işe sargınlık düzeyleri nin ise orta düzeyde olduğu açığa çıkarılmıştır.

Öğretmenlerin öz yeterlik algıları; iş doyumu, örgütsel bağlılık, motivasyon ve işe
sargınlık düzeyleriyle pozitif korelasyona sahiptir. Öğretmenlerin öz yeterlik inançları

ile iş doyumu ve işe sargınlık düzeyleri arasında pozitif bir korelasyon bulunmaktadır.

Bunun yanı sıra iş doyumu, örgütsel bağlılık, motivasyon ve işe sargınlık düzeyleri
birbiriyle pozitif anlamlı ilişkilidir. Bütün değişkenler , birbiri ile .001 anlamlılık

düzeyinde ilişkilidir. Yapısal eşitlik modellemesi analizi ile test edilen ve en iyi uyum

değerlerini üreten yapısal modele göre; öğretmenlerin sahip oldukları öz yeterlik
inançları; iş doyumu, örgütsel bağlılık, motivasyon ve işe sargınlık düzeyleri üzerinde

pozitif bir etkiye sahiptir. Öğretmenlerin öz yeterlik algıları; iş doyumu ve örgütsel

bağlılık düzeylerinin kısmı aracılık etkisi ile motivasyon düzeylerini arttırmaktadır.
Öğretmenlerin öz yeterlik inançları; iş doyumu ve motivasyonun tam aracılık etkisiyle

işe sargınlık düzeylerini arttırmaktadır. Öğretmenl erin öz yeterlik algıları, örgütsel

bağlılık ve motivasyonun tam aracılık etkisi ile işe sargınlık düzeyleri üzerinde pozitif
bir etkiye sahiptir. Öz yeterlik; örgütsel bağlılık ve motivasyonun tam aracılık etkisi

ile öğretmenlerin işe sargınlık düzeylerini arttırmaktadır.

Sonuç ve Öneriler: Bu araştırma; öz yeterlik inancının öğretmenlerin olumlu tutumsal

çıktılarını nasıl arttırdığı konusunda önemli bilgilere ışık tutacak şekilde

tasarlanmıştır. Bu araştırma; öz yeterlik inancının iş doyumu, örgütsel bağl ılık,

motivasyon ve işe sargınlık değişkenlerini etkilediğini ortaya çıkarmaktadır. Öz
yeterlik; bireylerin işten elde ettikleri memnuniyetlerini, okullarına bağlılıklarını,

çalışmaya duydukları isteklerini, gayret düzeylerini ve zorlu görevler karşısında
gösterdikleri çabaları arttırmaktadır. Bu araştırma diğer örgütlerde olduğu gibi eğitim

örgütlerinde de önemli performans çıktıları sunan öz yeterlik, iş doyumu, örgütsel

bağlılık, motivasyon ve işe sargınlık kavramlarına yoğunlaşılması açısından diğer
çalışmalara da kuramsal çerçeve oluşturmaktadır. Bu araştırmayla birlikte

öğretmenlerin öz yeterlik inançlarının önemine ilişkin bir bakış açısı sunulmaktadır.

Ayrıca öğretmenlerin yapabileceklerine inanç duymalarını sağlayan, bu yolla
okuldaki olumlu tutumlarını arttıran ve eğitim çevrelerine katkılar sunan öz yeterlik

224 Selcuk DEMIR
Eurasian Journal of Educational Research 85 (2020 ) 205-224

kavramı ile bazı anahtar değişkenlere ilişkin yapısal bir model üretilmiş ve bu model

ampirik olarak test edilmiştir. Eğitim örgütleri öğretmenlerin; daha huzurlu, iş

doyumları, bağlılıkları ve motivasyonları yüksek, işe sargınlıkları fazla olmalarına
katkı sunacak ortamlar oluşturabilmelidir. Bu araştırmada ortaya koyulan ilişkilerin

nedenlerinin derinlemesine incelendiği çalışmaların tasarlanmasıyla bu kavramlara

ilişkin daha iyi bir anlayış sunulabilir.

Anahtar Sözcükler: Öz yeterlik, tutumsal çıktılar, aracılık etkisi, performans, verimlilik.

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Breach of Psychological Contract and Job Involvement: Does

Organizational

Cynicism

Mediates the Relationship?

Muhammad Nadim
*
,Seerat Fatima

†
, Sana Aroos

‡

And Muhammad Haroon Hafeez
§

ABSTRACT
This research study examined the association between breach of

psychological contract & job involvement of nurses working in public

health care sector of Pakistan. Specifically, this study has introduced

organizational cynicism as a mediator between breach of psychological

contact and job involvement. By using self-administered survey, we

collected data from 162 nurses employed in various public sector

hospitals in Pakistan. Findings of this study highlighted that breach of

psychological contract causes decrease in job involvement of nurses

among public sector hospitals and this association is partially

mediated through organizational cynicism. Implications for practice

and future research directions are highlighted.

Keywords: Breach of psychological contract (BPC), Job involvement,

Organizational cynicism, Pakistan.

Introduction

Once an individual joins an organization, many contracts are signed

containing terms and conditions of employment. But it is often seen that

many employees do not recognize that they are also entering intoone

moretype of contract that is not written nor enunciated. This unwritten

agreement or common expectation between employer and employees is

called a psychological contract (Rousseau, 1989).

A psychological contact breach is defined as employees’ insight

that their organization has proved unsuccessful to execute some duties or

commitments coupled with perceived mutual promises

(Tetrick&Gakovic, 2003). The breach of contract causes several

depressing upshots in an organization which include organizational

cynicism (O’Leary- Kelly & Johnson, 2003).Organizational cynicism

refers to an employee’s negative attitude towards his organization,

consisting of three dimensions:(1) a strong perception that his employing

organization lacks truthfulness or integrity; (2) negative affect with

respect of his employing organization; and (3) tendencies of arrogant and

unproductive behaviors directed towards one’s employing organization

representing these beliefs and affect (Brandes, Dean&Dharwadkar,

1998).

On the other hand, job involvement is considered as a type of the

job attitudes(Janasz, Forret, Haack&Jonsen, 2013). Employee’s high job

involvement is a necessary condition for effective functioning of the

organization because it results in a number of positive consequences for

the organization including high job satisfaction, high commitment, lower

intentions to quit (McElroy et al., 1995) low tendency to leave the work

early, high effort level and performance (Blau& Ryan,

1997).However,job involvement in nursing profession is lacking in

developing countries like Pakistan due to multiple reasons including low-

graded status of nurse, lack of career advancement, inadequate incentives

and aloofappointments, and poor working conditions (Khowaja, 2009).

*
Muhammad Nadim, University of the Punjab, Jhelum Campus, Jhelum,

Pakistan. E-mail: rananadeem@pujc.edu.pk
†
Seerat Fatima , Institute of Management Sciences, Bahauddin Zakariya

University, Multan, Pakistan
‡
Sana Aroos , Capital University of Science and Technology, Islamabad

§
Muhammad Haroon Hafeez, Institute of Management Sciences, Bahauddin

Zakariya University, Multan, Pakistan

Breach of Psychological Contract… Nadim, Seerat & Haroon

Journal of Managerial sciences 99 Volume XIII Number 3

In the field of organizational behavior, there is dearth of research that

explicates the association between BPC and job involvement. Existing

literature had highlighted that BPC can have negative association with

various job attitudes (Schmit, Amel& Ryan, 1993). Since, job

involvement is also an important type of job attitudes(Janasz, Forret,

Haack&Jonsen, 2013) therefore, it is reasonable to argue that job

involvement can be influenced by BPC. Additionally, many nurses

experience BPC and organizational cynicism at some time or another but

not all of them leave their jobs because of it. Why do some nurses simply

continue to work in a cynic environment? Whether there job involvement

decrease due to their perception of organizational cynicism or not? In

developing countries like Pakistan, there is much research linking

BPC

and various jobattitudes but there is little research establishing the

linkage between BPC and job involvement (De Hauw& De Vos, 2010).

Consequently, this study concentrate on this scarcity by developing the

research question “Does breach of psychological contract leads to

decrease in job involvement and does organizational cynicism mediates

this relationship?” This study will have imperative implications for the

nursing sector of Pakistan. Further, it intends to add to the existing body

of literature both theoretically and empirically by illuminating the critical

role of organizational cynicism in explaining the association between

BPC and job involvement.

Literature Review
Breach of Psychological contract (BPC) and Job involvement

BPC denotes employee’s perception that their organization has proved

unsuccessful to perform some duties associated with perceived mutual

promises(Tertrick&Gakoviv, 2003). Thus far many researches had

studied the constructiveeffects of fulfillment of psychological contract on

employees and organizational performance. However, there is scant

literature showing the negative effects that BPC may have on employee’s

attitude & behavior. Substantial research highlighted that perception of

BPC is negatively correlated with employee’s job performance, OCB,

and commitment with one’s employing organization (Turnley, et al.,

2000; Sheng, et al., 2007) satisfaction with job and loyalty with the

organization (Lester, et al., 2002; Tufail et al., 2017).When employer

fails to meet its responsibilities or obligations it can be a principal reason

of employees frustration and consequent lower job involvement.

Job involvement denotes the extent to which an individual is

cognitively worried, intensely tied up, and concerned with respect to his

or her job (Paullay et al., 1994). Job involvement is one of the major

factors contributing to organizational capacity to effectively meet the

needs of this competitive and turbulent business environment. Social

exchange theory Blau (1964) maintains that the relationships between

persons are based upon mutual social obligations. When one party fulfills

its obligations adequately the other will also do the same. It means, there

is the principle of reciprocity that the action on the part of one person

shapes the response of other(Mitchell &Cropanzano, 2005).When

employers fail to fulfill its duties or obligations, then breach of

psychological contract arise (Robinson & Morrison, 1997) which can

result in lower job involvement (Cropanzano and Mitchell, 2005; De

Hauw& De Vos, 2010). Therefore, frustration aggression theory lends

support to create a link between BPC and job involvement and

constructing the first hypothesis:

H1.BPC is negatively associated with

job involvement of nurses.

Breach of Psychological Contract… Nadim, Seerat & Haroon

Journal of Managerial sciences 100 Volume XIII Number 3

Organizational Cynicism as a Mediator

Cynicism and its consequences to the employees and organizations are

primarily studied by Golden et.al.(1977).In the existing research studies,

cynicism refers to an attitude highlighted by a dislike for and suspicion

about others. Organizational cynicism according to Dean is an

employee’s negative attitude toward his organization, consisting of three

dimensions: (1) a strong perception that organization lacks truthfulness;

(2) negative affect and (3) tendencies of arrogant and unproductive

behaviors representing those beliefs and emotions (Dean et al., 1998).

There are various factors which contribute towards the

development of organizational cynicism in employee which include high

stress level, increased complexity in the organization, low social support,

miscommunication, low autonomy, work-role clash, BPC, incompetent

management, trust deficitand hostile work atmosphere have been

illuminated in the existing studies as the predictors of organizational

cynicism among others (Cole, et al., 2006;O’leary- Kelly and Johnson,

2003;Tükeltürk, et al., 2012).

On the other hand, organizational cynicism can cause a number

of undesirable outcomes among employees, e.g. minimum level of

commitment towards the organization, reduced job satisfaction (O’leary-

Keller and Johnson, 2003) decreased employee’s performance,

commitment with the unions (Bashir and Nasir, 2013) and lower job

involvement (Brown and Leigh, 1996). BPC negatively influences the

employee’s conviction which leads to changes in behaviors and attitudes

of employees (Robinson and Morrison, 1997)Frustration causes

aggressive or hostile behavior among employees resulting inflow job

involvement (Brown and Leigh, 1996). Through this study it is argued

that since organizational cynicism results in employee frustration

(Andersson, 1996), which can result in low job involvement. Hence,

organizational cynicism is expected to act as a mediator between BPC

and job involvement. Accordingly, the second hypothesis of this study is:

H2.Organizational cynicism mediates the relationship between BPCand

job involvement of nurses.

Research Model

The following is the research model of this study

Methodology

Population Sample and Sampling Technique

The population of this study was nurses of public health care sector of

Pakistan. However, due to limited access to the target population as well

as time and financial constraints convenience sampling technique was

employed to gather the required data from nurses. By using self-

administered survey method, initially, 300 questionnaires were

distributed among nursing staff of public hospitals in various cities of

Pakistan. Out of these 300 questionnaires, 183 questionnaires were

received back, 21 questionnaires were incomplete and were excluded

from the study. Consequently, 162 responses were finally retained for

analysis representing a response rate of 54%. To warrant secrecy and to

obtain true and honest information, nurses were directed not to write

Breach of

Psychological

Contract

Job

Involvement
Organizational

Cynicism

Breach of Psychological Contract… Nadim, Seerat & Haroon

Journal of Managerial sciences 101 Volume XIII Number 3

their in the questionnaire. Further, they were assured that their responses

will be kept secret.

Instrumentation

We adopted questionnaires from earlier studies. We used Robinson and

Morrison (2000) five item BPC Scale. To measures organizational

cynicism, Dean et al. (1998) 13-item scale was used. Similarly, Kanungo

(1982) 10-itmes Job involvement Questionnaire (JIQ) was used to

measure level of nurses’ job involvement. All the questionnaires used

were in the shape of five-point likert scale with “Strongly disagree” (1)

to “Strongly agree”(5) response range. Data were also captured on

demographic variables of age, tenure, marital status and employment

status.

Data Analysis And Results

Table 1 indicates the relation ship among variables and their reliabilities

measures. A significant positive correlation (r= .767, p < .01)is observed

among BPC and organizational cynicism. On the other hand, a negative

correlation (r= -.686, p < .01)is detected between BPC and job

involvement. Finally, organizational cynicism and job involvement are

also found negatively correlated (r= -.671, p < .01).

Table: 1 Correlations and reliabilities (in parentheses).

Mean S.D 1 2 3

BPC 3.54 .776 (.764)

OC 3.39 .732 .767** (.836)

JI 2.39 .858 -.686** -.671** (.768)

BPC= Breach of psychological contract; JI = Job Involvement, OC =

Organizational Cynicism;

n = 162. *P<.05 **p<.01

Table 2 depicts results about the hypothesized relationships

among the study variables. The overall model of envisaging job

involvement from BPC is significant (F = 177.25, P <.01). Our

investigation controlled for the effects of age, gender and working

experience. The results of the regression analysis highlighted that BPC is

a significant negative predictor of job involvement (β = -.712, p < .01).

Hence, we found strong support for first hypothesis of the study that

increase in BPC would lead to decrease in job involvement. This

relationship is also verified from statistically significant bivariate

correlation between BPC and job involvement.

Table 2 Regression analysis results

Predictors Job Involvement

βt R
2
ΔR

2

Step 1

Control Variables .012

Step 2

BPC -.712** -7.516 .771 .759

a. Predictors: (Constant), Age

b. Predictors: (Constant), Age, Organizational Cynicism,

BPC

Values are unstandardized beta weights* p<.05**p<.01

Breach of Psychological Contract… Nadim, Seerat & Haroon

Journal of Managerial sciences 102 Volume XIII Number 3

We performed the mediation analysis through SPSS script by

Preacher and Hayes(2008),for indirect effects. We performed

bootstrapping and requested 5000 samples; a bias-corrected 95% CI is

shaped for ab. For this 95% CI, the LL is -.4220 and UL is -.0332.

Different criterion might be applied to evaluate the significance of the

indirect path. In this study, both a&b coefficients are statistically

considerable, and the bootstrapped CI for ab did not include zero. So, the

indirect effect of BPC on job involvement through organizational

cynicism is statistically significant. The direct path from BPC to job

involvement (c′) was also found to be significant; therefore, the effect of

BPC on job involvement is only partially mediated by organizational

cynicism. These results are summarized in table 3 below.

Table 3Upshots of Mediation
IV Effect

of IV

on M

Effect of

M on DV

Direct

effect

Total

effect

BS 95% CI

LL UL

BPC

.84**

-.28**

-.73**

-.96**

-.422

-.033

CI: 95%, Number of Bootstraps: 5000, ** P < .01

Conclusions And Implications

In general, our results supported the hypotheses of the current study. The

first hypothesis of this study which was designed to explore the relation

between BPC and job involvement is accepted. The negative relationship

between these variables suggests that BPC decreases job involvement of

nurses. Since, due to limited job opportunities in Pakistan

(Qayyum&Siddiqui, 2007), many nurses cannot afford to leave their job

when there is BPC instead, they may decrease their job involvement as a

way of reprisal to the organizational strategies and policies. Hence, the

nurses exhibiting lower job involvement in public sector hospitals of

Pakistan, is actually a response for their perception of BPC. This study

also highlighted that the relation between BPC and job involvement

cannot be comprehensively clarified until organizational cynicism is not

incorporated in the model. Existing literature tinted that the contract

disobedience on the part of employer does influence the workers faith

eventually originates change in their behavior and attitude (Robinson &

Morrison, 1997) as well as magnification of organizational cynicism

(Andersson, 1996; O’Leary-Kelly and Johnson 2003). Thus, BPC

increases organizational cynicism and ultimately diminishes job

involvement. The findings of current study can be useful for decision

makers and administrator of public sector hospitals. Most of the nurses in

their informal discussion with the authors had pointed out that

management makes false promises regarding their benefits and career

prospects. Since, the health sector is one of the important and sensitive

sectors, hospitals must be cautious in making promises with their nursing

staff because this is the key for their successful functioning.

Limitations And Future Research

While these upshots of the current study facilitate us to better understand

job involvement of nurses in public sector hospitals of Pakistan, there are

some limitations of this study which needs to be tackled by future

searchers. The findings of this study are based upon a more restricted

sample using convenient sampling technique, however more

sophisticated sampling technique can grant more extensive picture on

this issue. Likewise, this study is cross sectional in nature, the results

might be different if longitudinal data were collected. Since

organizational cynicism reasonably mediated the relationamongBPC and

Breach of Psychological Contract… Nadim, Seerat & Haroon

Journal of Managerial sciences 103 Volume XIII Number 3

job involvement; future scholars should explore some other possible

mediating variables as well.

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