iBusiness, 2013, 5, 182-189
http://dx.doi.org/10.4236/ib.2013.53B038 Published Online September 2013 (http://www.scirp.o rg/journal/ib)
Quality as Determinant Factor of Customer Satisfaction:
Case Study of Zai n-Kuwait*
Hasan A Abbas
Department of Information Systems, College of Business Admin, Kuwait University, Kuwait.
Received 2013
ABSTRACT
The potential of mobile communications market in Kuwait is enormous. Therefore, I test customer satisfaction in the
Kuwaiti mobile market by examining the quality construct. In our study, quality is measured through the dimensions:
interaction quality, environment quality, and outcome quality. Our results show that outcome quality is the most in-
fluential construct over satisfaction. Also, the results find that interaction quality is not significant and carries no im-
portant associa tion with customer satisfaction.
Keywords: Quality; Satisfaction; Struct ure d Equation Mod e ling
1. Introduction
Kuwait is one of the countries that scores highly in ap-
plications of communication technologies and mobile
phone s marke t. This market a nd its se rvices are flourish-
ing exponentially. This is not only the case in Kuwait,
but, instead, this is true in the whole region a s well.
In accordance with new devices and new communica-
tion t echno logie s suc h as s mart p hones a nd 4G techno lo-
gies, the competition is increases and becomes more in-
tense in this field. For this reason, companies are com-
peting aggressively to keep and increase customer satis-
faction.
The goal of this research is to highlight the test and
measure the importance of association between the qual-
ity construct a nd custo mer satisfact ion in Ku waiti mobile
market. Specifically, my aim is to present a theoretical
research model to explore the degree of satisfaction with
a specific mobile service provider (MSP ).
The paper is divided into the following sections:
communication in the next sectio n. Section 3 prese nts th e
theoretical background. Section 4 presents data reduction.
Section 5 builds the first model. Section 6 discusses fit-
ness of the conceptual model. Sections 7 and 8 comprise
a discussion and limitations respectively.
2. The Global and Kuwaiti Communication
Markets
International reports continuously state that worldwide
income of communication sector scored over than a tril-
lion and a half dollars in year 2010. This indicator means
that an increase of 3.4% over the year before (2009).
Also reports show that an increase of 9% in marketing
and mobile advertisements has been reached compared to
years before recession[31].
Latest report by International Telecommunication Un-
ion (ITU) in 2012 emphasizes the fact that worldwide
mobile subscriptions has reached level of 6 billion,(80%
of those from developed countries, 660 million new
members were added in 2011 )[21].The situatio n is simi-
lar in Kuwait. B ased on scientific figures b y ITU, mobile
subscri bers passed landline users by 5.1% [20] (see Ta-
ble 1 for Gulf Cooperation Council penetration rates for
2009. Source: [20], [22]).
Table 1. GCC penetration rates for 2009 (per 100 inhabi-
tants).
Mobile Fixed Line Internet Broadband
Bahrain 177.1 30.1 53.0 13.0
Kuwait 129.9 18.5 36.9 03.4
Oman 139.5 10.5 51.5 44. 0
Qatar 175.4 20.2 4 0.0 29.8
Saudi Arabia 174.4 16.2 38.0 10.8
United Arab
Emirates 232.1 33.9 75.0 14.1
*This project is supported by Kuwait Founda
tion for the Advanced of
Sciences (KFAS 2010-1103-05).

Quality as Determinant Facto r of Customer Satisf action: Case Study of Zain-Kuwait
183
Even though Kuwait has lower penetration than some
GCC countries, it still considered as one of the highest
globally and indicates vast space for potential increase.
ITU says that Kuwait stands as one of the highest pene-
tration rates worldwide e xceeding 15 0% [22]. “Kuwait,
in 62nd position, is the laggard in the region in terms of
embracing ICT (Information and Communications
Technology). Despite a fairly good ICT-related infra-
struct ure development, t he high costs o f accessing it and
the population’s relatively low level of skills are affect-
ing the ICT re adiness of the countr y. As a result, Kuwait
depicts fairly poor rates of ICT usage (67th) that, coupled
with a less business friendly environment for entrepre-
neurship (56th) than other Gulf Cooperation Council
states, result in lo w levels of ICT impacts (93rd).” [14, p.
26].
This is why the investment in Kuwait in this sector is
encouraging due to the fact that it has solid market in
addition to very complicated and advanced infrastructure,
which not utilized fully yet. The three major main pla yes
in mobile sector in Kuwait are Zain, Wataniya, and Viva.
Furthermore, there is a very good chance to add fourth
competitor if constit utio nally passed.
3. Literature Review and Study Constructs
3.1. Satisfaction
One of most critical a nd strategic goa ls for an y fir m is to
keep customer satisfaction to its highest levels. Thus, all
firms inves t grea t deal of effo rt and mone y and t o clar ify
and to continuously modify their strategies to reach this
goal. According to the literature, satisfaction is needed
for two reasons: because of its close association and ef-
fect over customer retention and market share incremen-
tal, and, two, because of its ability to increase a firm’s
revenue and profits [15], [16].
What is found in the literature is that all firms in the
communications market face almost similar challenges
and is competing in a standard market. The services con-
tinue to become similar and close to each other. This is
why firms fight to distinguish themselves through adopt-
ing different marketing programs and to compete over
value-added services [43].
The research and development departments in those
firms continuously try hard to figure out and clarify va-
guene ss among their market. They alwa ys aim to uncover
constructs that effect mostly on customer satisfaction.
Marketing research strongly insists on the positive rela-
tion between customer satisfaction and the future beha-
vior and intentions to rep urchase the service [8], [11].
According to study by [17], customer satisfaction is
not static but instead dynamic, very complicated, and
highl y reflec tive of e nvironment. Studie s such as [7] and
[10] mentio n that satisfaction can be divided to be trans-
action-specific satisfaction and cumulative satisfaction.
First type of satisfaction is related to degree of satisfac-
tion that customer feels pertaining a specific transaction.
The second type of satisfaction is more general. Cu-
mulative satisfaction is customer’s overall satisfaction
feelings towards general reaction after experiencing
many transactions. According to [24], both types of sa-
tisfaction (transaction-specific and cumulative) are com-
plimentary, which means that they do not contradict each
other and the purposes for each type is different [43].
Oliver [34] claims that customer satisfaction has cogni-
tive roots and effected by the emotions of the customer
(both positive and negative), which are developed from
experience and contact with the firm [40], [33], [43],
[29].
[29] also [43] define customer satisfaction as “an ef-
fective state representing an emotional response”. Dif-
ferent researches [32], [7], [11] , [28], [30], and [42] stu-
died satisfaction before and after experience of transac-
tion with firms and reached to a widely acceptance that
consumer’s expectation and satisfaction are closely re-
lated.
Efforts by [12] and [13] prove that groups of con-
structs are directly responsible and positively determine
customer satisfaction, those constructs are: system quali-
ty, information quali ty, and service qualit y. Other studies
explored satisfaction and found that satisfaction can also
be affected and determined through justice, which is also
another important construct [41], [1]. Because of rare
research and publications that discuss the associations
between satisfaction and quality [43] and in Arab world,
this research addresses this side and fills the gap by ex-
amining a moderate Arabian culture such as Kuwait.
Satisfaction is known to be the final product and the
critical strategic good of any firm. Thus, what strategic
look of those firms are continuously following is to keep
customer continuation and incremental satisfaction with
the firm. All though literature views and clearly concen-
trates over the critical relation that relates continuing
relationship to customer satisfaction [32], [11], [5] our
research do not test the relationships between customer
satisfactio n and c onti nuing r elat ionship , hopin g it will be
cove red t hroug h our future researc h projects.
3.2. Service Quality
Service quality has been studied intensively in the litera-
ture and research departments of many sectors. Stud y by
the authors [6] defines service quality as “consumers’
overall impres sion of the relative i nferiorit y or superiori-
ty of the organization and its services” [6, p. 77]. It is
important to highli ght the po int that service quality is not
a one-dimensional construct. Instead, group of studies
emphasizes the opposite and proofed that service quality
is a multidimensional. In other terms, service quality,

Quality as Determinant Facto r of Customer Satisf action: Case Study of Zain-Kuwait
184
according to this group of studies, is hard to be measured
in its standalone status [18], [36]. For example, [18]
splits service q uality and di vides it into two mai n dimen-
sions: technical quality and functional quality. Further-
more, [36] introduces his own model and expands service
quality into five perspectives as his research framework
(reliability, responsiveness, assurance, empathy, and tan-
gibil ity). Their proje ct shows a 2 2-item instrument called
SERVQUAL, result that widely used commercially and
scientifica ll y worldwide.
SERVQUAL model is been validated through many
projects [9], [27], [43]. This validation emphasized the
importance of the multidimensionality of service quality
in mobile services. In different terms, this group of stu-
dies proposed that service quality of mobile sector con-
tains three primary dimensions: interaction quality, out-
come quality, and environment quality.
Interaction quality is defined by [27, p. 232] as the
“quality of customer’s interaction with the mobile service
provider during the service delivery”, which comprises
enough and trustful expertise, professional problem
solving, and show information richness. Second, Zhao
and his colleagues define environment quality as “the
consumer’s evaluat ion of the quality of equip ment that is
used, the extent to which the interface is well designed,
and the extent to which the service is delivered under
proper contexts” [43, p. 3]. Finally, [18, p. 38] defines
outcome quality as “what the customer is left with when
the production process is finished.”
According to previous discussion, study research
model is depicted in Figure 1.
4. Sampling and Data Reduction through
Factor Analysis
A special instrument was designed specifically for this
study. We asked population to give us their opinion re-
garding their mobile service usage. The study instrument
measures research constructs: interaction quality, envi-
ronment qualit y, outcome quality, and satisfaction.
Before initiating the data collection stage, a small
sample is used to examine t he validit y of the st udy ques-
tionnaire. A fter that a ra ndo m sample size o f 512 mobile
users are collected. The initial results of reliability coef-
ficient for the Cronbach’s alpha show acceptance consis-
tenc y in the i nstru ment. A mong stud y populat ion, 41 .6%
male (frequency = 213) and 58.4% (frequency = 299)
female. The marital status is divided between 46.9%
(frequency = 240) married and 53.1% (frequency = 272)
single. Tab l e 2 shows the demographics of the sample .
Data reduction through factor analysis test is followed
in studies to “remove redundancy that might exist be-
tween questions within dimension; and third to reveal
any patterns t hat might exist bet ween questions” [2]. Ta-
ble 3 shows study factor loadings
Table 2. Demographic distribution of st udy sample.
Demographics
Frequency
Percentage
Gender
Male
213
41.6
Female
299
58.4
TOTAL 512 100
Marital Status Married 240 46.9
Single 272 53.1
TOTAL 512 100
Age Less than 20 70 13.7
Less than 30 255 49.8
Less than 40 109 21.3
Less than 50 49 9.6
Over 5 0
29
5.7
TOTAL 513 100
Academic Background Secondary or less 12 2.3
High s chool 94 18.4
Two years 97 18.9
Bachelor 273 53.3
Master 29 5.7
Missing 7 1.4
TOTAL 512 100
Income Less than 200 19 3.7
Less than 500 35 6.8
Less than 1000 121 23.6
Less than 1500 108 21.1
Less than 2000 78 15.2
Less than 2500 53 10.4
Less than 3000 42 8.2
More 51 10.0
Missing 5 1.0
TOTAL 512 100
Nationality Ku waiti 424 82.8
Arab 48 9 .4
Other 40 7.8
TOTAL 512 100
.
5. Conceptual Model
Figure 1 shows study research model followed by the
three hypotheses.
The following are research hypo theses:
H1: Interaction quality (INQ) is positively associated
with customer sa tisfaction (SAT).
H2: Environment quality (ENQ) is positively asso-

Quality as Determinant Facto r of Customer Satisf action: Case Study of Zain-Kuwait
185
ciated with customer satisfaction (SAT).
H3: Outcome quality (OUQ) is positively associated
with customer sa tisfaction (SAT).
Table 4 shows the reliability and explained variance.
It is clear from Table 4 that all reliabilities of the study’s
measurements above 70%. Also all variances are above
60%. This means that these percentages are acceptable
scientifically and conforms to the literature (see for de-
tails [19]).
Table 3. Factor loa dings of study constructs.
Component
1 2 3 4 5 6 7 8
INQ1 .794
INQ2 .848
INQ3 .843
INQ4 .762
INQ5 .654
INQ6 .553
ENQ1 .756
ENQ2 .821
ENQ3 .797
ENQ4 .753
OUQ1 .705
OUQ2 .760
OUQ3 .726
OUQ4 .671
SAT1 .702
SAT2 .692
SAT3 .705
SAT4 .739
SAT5 .656
SAT6 .710
SAT7 .645
SAT8 .693
SAT9 .692
SAT10 .683
6. Fitness of Conceptual Model and Latent
Constructs Validation
I use the Lisrel 8.54 software to test the goodness of fit of
the conceptual model. Table 5 shows t he results.
To ensure fitness of our model, Further testing is fol-
lowed. According to [19], since Cronbach reliability test
expects unidimensionality, “this is why further analysis
through construct composite reliability is needed to en-
sure that the existence of the internal consistency in the
measurements per each construct. The composite relia-
bility can be calculated as follows:” [1, p. 12] Variance
extracted is another reliability test. “The variance ex-
tracted is used to evaluate the overall amount of ex-
plained variations accounted for by the construct” [3].
The composite reliability and variance extracted can be
computed as follows:
Figure 1. Research model
Table 4. Ex plained variance and reliability.
Measurements
Cronbach Reliability
Coefficient
Explained
Varia nce
1
INQ (1, 2, 3)
88.6%
81.551%
2
ENQ (2, 3, 4)
86.2%
78.417%
3 OUQ (2, 3, 4) 90.6% 84.260%
4
SAT (1, 2, 3, 4)
94.4%
85.588%
Table 5. Goodness of fit.
Normed Fit Index (NFI) 0.980
Non-Normed Fit Index (NNFI) 0.980
Incremental Fit Index (IFI) 0.990
Relative Fit Index (RFI) 0.970
Critical N (C N) 192.850
Root Mean Square Residual (RMR) 0.033
Stand ar dized R MR 0.033
Goodness of Fit Index (GFI) 0.900
Adjusted Goodness of Fit Index (AGFI) 0.870
Parsimony Normed Fit Index (PNFI) 0.800
Comparative Fit Index (CFI) 0.990
( )
( )
2
2
Composite Reliabilit yStandardized loadings
Standardized loadingserror
=
+
∑
∑∑
(1)
( )
( )
2
2
Variance extracted
Standardized loadings
Standardized loadingserror
=+
∑
∑∑
(2)
Table 6 presents these two tests as well as the coeffi-
cient for the determination of the R2.
One last test is important to valid ate the researc h mod-
el that is a discriminant validity test. This test is needed
to ensure no appearance of overlapping among mea-

Quality as Determinant Facto r of Customer Satisf action: Case Study of Zain-Kuwait
186
sure ment s. “In other words, the questions that are used in
the survey should not be overlapped where one question
can measure two or more items. The discriminant validi-
ty test is acceptable as long as the result is less than or
equal to 0.85” [1, p. 12]. It is computed a s follows:
( )
,
xy
xy
Corrx y
DV rel rel =∗
(3)
Table 7 shows the discriminant validity test results of
the research model.
Path Analysis and Verification of Proposed
Research Model
After verifying the goodness of fit of the research model,
the study’s hypotheses need to be tested for the signific-
ance of the paths between the study’s constructs in the
research model.
It is clear from Table 8 and Figure 2 that two out of
three o f the study hypotheses are verified and found to be
signific a nt . A n exception is the case of interaction quality.
The association between interaction quality and satisfac-
tion found to be non-significant.
7. Discussion
Contrary to study of [43], our study does not find any
difference between two types of satisfaction (transaction
and cumulative). Our study treated both as one satisfac-
tion. This non-difference treatment of satisfaction is
supported by many studies [42], [23], [4], [25], [26].
Moreover, our study shows difference from studies of
[43] and [18] in the quality (different from our study,
those two studies measure quality and justice over satis-
faction). Except for interaction quality that was not sig-
nificant, all other constructs are found to be significant
and have positive effects on satisfaction.
8. Conclusions and Limitations
Although different studies show the important associa-
tion between satisfaction and continuing relationships
(see [35] for more references), our aim here is not to fo-
cus on continuation but instead to study the effect of
quality factor over customer satisfaction. Quality factor
is successfully divided into three dimensions and in ac-
cordance to the literature, the three dimensions are: inte-
raction qualit y, envir on me nt q uali t y, and o utc o me q uali t y.
Although customer satisfaction is discussed in the litera-
ture as two types (transaction and cumulative), we here
treated it as a one dimension.
Table 6. Construct composite reliability, variance extracted,
and coefficient for the d etermination of R2.
Construct Construc t Composite
Reliabili ty Variance Extracted R2
Interaction
Quality 91.82% 78.95% --
Environmental
Quality 89.31% 73.61% --
Output
Quality 93.87% 83.63% --
Satisfaction 96.11% 86.07% 70%
Table 7. Discriminant validity test results of the research
mode l.
Construct INQ ENQ OUQ SAT
INQ 0.789551a
ENQ 0.386476b 0.736183a
OUQ 0.560085 b 0.589734b 0.836361a
SAT 0.521593
b
0.539656
b
0.758012
b
0.860731
a
Table 8. Path analysis.
Path Hypotheses Path Co e fficient Standard E rror t-value p-value Significant or not significant
Interaction Quality (INQ) →
Satisfaction (SAT) H1 0.03 0.04 0.91 0.181 NS
Envi r onment Quality (ENQ)
→ Satisfaction (SAT) H2 0.06 0.04 1.75 0.04 S
Output Quality (OUQ) →
Satisfaction (SAT) H3 0.28 0.05 5.87 0.00 S
Figure 2. Path coefficients of research model.
The study was able to verify two hypotheses out of
three. The interaction quality was found to be
non-significant.
However, customer satisfaction lacks to include many
other factors such as social norm, image, privacy, and
security, which found to be important by other studies
[39], [38], [37].

Quality as Determinant Facto r of Customer Satisf action: Case Study of Zain-Kuwait
187
9. Acknowled gements
Author wants to thank Kuwait Foundation for the Ad-
vanced of Sciences for supporting this project. (KFAS
2010-1103-05).
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