factors effective on customer loyalty in the mobile

JOURNAL OF CRITICAL REVIEWS

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636

Factors Effective on Customer Loyalty in the Mobile

Telecommunications Industry: A Comparative Study of

Iran and Iraq

Parviz Kafcheh1, Kadhim Faraj Aref2, Aram Taher3, Bestoon Othman4*

1Assistant Professor of Business Administration, University of Kurdistan, [email protected]

2 Assistant Professor of Management, Sulaimani Polytechnic University, Lecture at Kurdistan Technical

Institute, [email protected] , [email protected]

3 Department of Business Administration, Technical College of Administration, Sulaimani Polytechnic University, Kurdistan, Iraq, [email protected]

4 Department of Business Administration, Koya Technical Institute, Erbil Polytechnic University, Erbil, Iraq.

And Scientific Research and Development Center-Nawroz University-Kurdistan Regional, Iraq.

Email: [email protected]

Received: 10 April 2020 Revised and Accepted: 26 June 2020

Abstract: Nowadays in competitive marketing, companies have to supply customer demands to continue

competing. Considering the various requirements and favorites of different customers and fixing them is necessary

for manufacturing and services companies because the customers are the key to success of the companies and

their absence will undoubtedly lead to the company’s failure. Loyal customers and their constant purchases will make the company successful and creates a competitive advantage for it, so the loyal customers are important for

companies. The current study attempted to examine the effective factors on the loyalty of customers in the mobile

communication industry in Iran and Iraq, and provide applied results for managers. This study was a descriptive

research based on the purpose of applied research and it was a survey research based on the method of data

collection and implementation. A questionnaire was used to collect data and its validity was confirmed by the

professors of the management department. The sample of the society, due to its unlimited number, were selected

384 in Iran and 387 in Iraq, using the Cochran formula, and random sampling method was used in this study.

SPSS and LISREL software’s were used to analyze the data and the collected data was normalized using the

Kolmogorff-Smirnov test. Structural equation modeling was also used to test the hypotheses. Because of the

normal data of the sample, Pearson correlation coefficient was used to determine the correlation between the

existing factors and loyalty. The obtained results showed that there was a positive and significant effect between

research variables. The results of Beta coefficient of LISREL software also indicated that the confidence to operator with 0.60 coefficient ranked first and gained the highest effect on the loyalty of customers in the mobile

communication industry compared to other variables. Satisfaction with 0.54, company image with 0.46, the

quality of perceived services with 0.40, and perceived cost of switching with 0.36 coefficient ranked from the

second to fifth, respectively.

Keywords: Confidence, Remaining customers, Mobile communication industry, Customers' loyalty

I. Introduction

The increase in regional and global competition in markets makes organizations turn to modern methods of

competition for achievement of greater success in the long run. Today, the purpose of marketing is to manage

customer demand and customer loyalty to an organization. Customer satisfaction is not sufficient for a company,

which should make sure that satisfied customers are loyal as well. In general, the major, central point in marketing activities now is to maintain customers and increase their loyalty to the products or services of a company.

Organizations are going through the era of customer-driven economy, where the market is actually governed by

the customer. The competitive market has made organizations care more about customers and consider them and

their satisfaction rather than mass production. Customer expectation, on the other hand, is constantly increasing,

mailto:[email protected]




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and organizations are required to proceed further than primary customer needs by meeting their expectations and

to focus their attention on provision of loyalty through establishment of long-term, mutual, profitable

communication for both parties (Eid, 2016).

Customer loyalty is regarded as a key factor for organizations, and brings them profitability and success. To be

able to manage customer loyalty most properly, organizations must be able to communicate best with their

customers and identify their needs and desires (Ching et al., 2010). Customer loyalty is of great importance for

any service-providing organization. During the past ten years, concern for customer loyalty has increased

considerably, and customer loyalty is regarded today as an instruction for increasing income. This, however, is

perhaps considered as the first step in the evolution of customer orientation (Salari, 2007). Furthermore, the results

of several studies have demonstrated that companies and organizations increase their profitability by increasing the numbers of their valuable, top-ranked customers and their provision with efficient satisfaction. Given the

changing economic conditions, organizations and companies will need to seek a solution to maintain and develop

loyalty in their customers as soon as possible, and the solution is realized only through relationship marketing and

customer maintenance (Soleymani Besheli, 2016). Marketers should make it possible to improve and promote

customer loyalty more than before. The purpose of such a paradigm is to establish long-term relations with

beneficiaries and, most importantly, with customers, so that more customers are maintained, and fewer are lost,

and the contribution by the market and profitability in the organization in the long run is finally assured (Osman

et al., 2009; Yu, 2008).

II. Theoretical Framework

2.1 Customer Loyalty

Customer loyalty is a term used to refer to conditions where the customer is at a higher level of satisfaction, has

constant purchase, disregards the competitors, and praises the organization in others’ presence. Loyalty is

categorized into two distinct notions: brand preference, known as attitudinal loyalty, and market share, referred to

as behavioral loyalty. Loyalty is defined as the development of commitment in a customer to trade with a particular

organization and purchase goods and services frequently (Susanna H. and Larsson, 2004). However, there is also

a comprehensive definition according to which loyalty is used to refer to a powerful commitment to purchase a

superior product or service again in the future, such that the same brand or product is purchased despite the

potential influences and marketing efforts of the competitors (Othman et al., 2020; Cronin et al., 2000).

The first step for provision of loyalty is to identify the factors and stimuli providing loyalty among customers.

Customer loyalty is a fundamental notion affected by a variety of factors and conditions, different in effectiveness

from one organization to another and from one store to another given the business type. It is of great importance

to identify these factors accurately and to specify the effectiveness of each in helping managers to make correct decisions (Bahreynizade and Purdehghan, 2014). Turner and Wilson (2006) demonstrated that an attitudinally

loyal customer is less suspicious of negative information on the brand than one who is not loyal. Furthermore,

once loyalty to a brand increases, the income gained from loyal customers is remarkable and worthy of

examination most of the time (Matoos, 2009). Lost customers impose high operating costs to the supplier, since

the supplier has to make an investment for a new customer. Therefore, the ability to extend relations with

customers and to retain loyal ones will result in long-term success of the organization (Othman et al ., 2019; Wang

et al., 2007).

Marketing costs are reduced for an organization through customers made loyal for the following reasons.

1. Loyalty reduces customers’ learning costs particularly in service markets.

2. Customers’ positive word-of-mouth marketing enables the company to reduce its marketing costs.

1) Companies with large groups of loyal customers also hold great shares of the market.

2) Loyal customers are willing to spend higher prices for their favorite brands.

3) It is more costly to attract new customers than to retain the present customers, particularly when they are satisfied and loyal.

4) Loyal customers gain greater incomes for brands through increase in their purchases and their repetition.

5) The customers of a brand are resistant to competitors’ marketing strategies, and defend their favorite trade names.

6) In highly competitive markets, customer loyalty provides the brand with sustained competitive

advantages.


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7) Loyal, devoted customers pay less attention to extra information than others when purchasing things.

Moreover, they will ignore them more easily if encountered with problems with the products (Ebrahimi, 2012).

2.2 Satisfaction

Customer satisfaction involves a customer’s feeling about or attitude toward a product or service after using it.

Customer satisfaction is the major result of a marketer’s activity, functioning as a relationship between different

steps of consumer buying behavior. Satisfied customers are likely to continue repeating their purchase and also to recommend it to others (Othman et al ., 2019; Tronvoll, 2010). Satisfaction is the only value for a company that

causes positive financial outcomes. The results obtained through service management demonstrate that

development and coordination are determined to a large extent by loyalty, and behavioral loyalty is itself a direct

outcome of customer satisfaction (Morrisson, 2010). As approved by many pundits, customer satisfaction can be

defined as a result obtained from a comparison made by the customer between his expected performance before

purchase and the perceived actual performance and costs paid for (Khatab et al ., 2019b; Beerli et al., 2004).

2.3 Perceived Cost of Switching

According to the literature, factors that prevent customers from switching are classified in three general groups:

the costs of switching, interpersonal relations, and the attractiveness of the alternatives (Jones et al., 2002).

Customers examine competitive attractiveness at the time of probable switching by considering the benefit-cost

ratio (Kumar, 2013). Research has demonstrated that the quality of the perceived attractiveness considerably affects customer loyalty. Therefore, customers purchase a brand or service again according to their perceptions of

the attractiveness of the other alternatives given the competitive conditions. In many cases, a customer is loyal to

a brand or service since it is difficult to switch to another.

Jones et al. (2002) have classified the factors preventing switching broadly into two groups: interpersonal relations

and the attractiveness of the alternatives. Moreover, some researchers have added customer fatigue, categorized

as a type of artificial loyalty. Customer fatigue refers to the case of customers that may continue to cooperate with

the company even if they have numerous reasons for dissatisfaction. Colgate (2014), for instance, stated that a

very low percentage of financial institutions switch between businesses, which may indicate customer fatigue or

the factors preventing switching.

2.4 Trust

Schoorman et al. (2007) define trust as the tendency to depend on an exchange partner that the individual trusts.

Lymperopoulos et al. (2010) define trust as a psychological state consisting of the ratio of vulnerability acceptance

to the positive expectation behavior from others. Trust in a brand can be assumed as the security felt by the

consumer in his interactions with the brand, which is the basis of this perception and conception, and can meet

interests and comfort. This definition has a few components. Firstly, trust in a brand involves the idea that the

individual tends to put himself at risk, trusting the value commitment provided to him by the brand (Ahmad et al.,

2020; Sadq et al., 2020; Delgado and Baster, 2001).

2.5 Service Quality

The quality of any phenomenon is part of its nature, regarded as one of its components. It is difficult and

ambiguous to provide a precise description of the word quality (Khatab et al., 2019a). From the perspective of the

2000 quality system, quality is used to refer to all the features meeting customer needs; therefore, any product holding the features that meet customer needs is a quality product. It is not difficult to define and assess the quality

of products of physical nature, and their quality can be determined and assessed through specification of

quantitative standards for them. In the service sector, however, it is so difficult to address quality, where the

difficulty results from the particular features of service. These features follow.

Service is an intangible, invisible process.

Service is inseparable, in that it cannot be separated from its provider.

Service is variable, in that it is not bound by widespread standards, and even one individual provides his

service differently at two different times.


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Service is mortal, in that it is consumed as soon as provided, and cannot be saved for later use (Rashid

et al., 2019; Loveluck and Wright, 2000).

2.6 Corporate Image

The corporate image is an image of a company on its customers’ minds. It results from a process obtained from

the consumers’ ideas, emotions, and experiences with respect to the services provided by the company. These

emotions, experiences, and ideas reappear in the individuals’ memories, and a mental image of the relevant

company takes shape (Aydin and Özer, 2005). The corporate image is a conception of all beliefs, thoughts, and

impressions of a particular situation (Kadhim et al., 2020; Baloglu and Brinberg, 1997).

A favorable image should be planned and defined as accurately as the other marketing variables including brand, pricing, product, advertisement, distribution, etc. Before each imaging plan is implemented, a profound

examination of the available image of the company is required. For ensuring that a correct image is received by

the beneficiaries, the entire imaging plan should be coordinated, pursue the same issue and idea, and support a

unique message. Furthermore, since the corporate image is based on the beneficiaries’ perceptions, and is not

necessarily real, it has been suggested that regular feedback be provided for expression of the beneficiaries’ real

image of the company (Bandariyan, 2009).

2.7 Conceptual Model and Hypotheses

Given the above information, the present research is conducted to investigate the effects of some factors on

customer loyalty. The hypotheses of the research are as follows.

First hypothesis. Perceived service quality has a significant effect on customer loyalty in the mobile telecommunications industry.

Second hypothesis. Corporate image has a significant effect on customer loyalty in the mobile

telecommunications industry.

Third hypothesis. Trust in the operator has a significant effect on customer loyalty in the mobile


Fourth hypothesis. Perceived cost of switching has a significant effect on customer loyalty in the mobile


Fifth hypothesis. Satisfaction has a significant effect on customer loyalty in the mobile


Sixth hypothesis. There is a significant difference between the factors effective on customer loyalty in

the mobile telecommunications industries in Iran and Iraq.

Figure 1- Conceptual Model of the Research

Customer

loyalty

Service quality

Corporate image

Trust

Perceived cost of switching

Satisfaction

H5

H4

H3

H2

H1


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III. Methodology

The present research is categorized as a practical study in terms of purpose. It is of the correlational type in terms

of methodology. Moreover, this research is classified as a descriptive study in terms of data collection method

(research plan), describing the features of a sample and generalizing them then to the population. Descriptive

studies can in turn be of a number of types, and this one is considered as a survey. In a survey, the relationships

between variables are described, predicted, and analyzed. Furthermore, this research is a cross-sectional study in

terms of data collection time. A questionnaire has been used in this research as an instrument for data collection.

The research population under investigation consists of the customers of the Iranian and Iraqi mobile

telecommunications companies. In many practical areas, a researcher seeks to specify the parameters of the

society, but a direct access through a census of the population is impossible for him. In such conditions, samples of the population should unavoidably suffice the researcher to infer the parameters in question. A sample is a

smaller group from the population selected for observation and analysis. A certain induction can be made of the

characteristics of an entire population through an observation of the characteristics of a sample selected from the

population.

For obtaining a sample of Iranian and Iraqi mobile telecommunications industry customers in this research, the

random sampling method has been utilized, where each member of the population has the same chance of being

selected. There are several methods of sampling. One of them is to use the Cochran formula, which is as stated

below for an infinite population:

.

Based on the Cochran formula for an infinite population, a sample of size 384 is needed. For the purposes of the present research, the designed questionnaire has been distributed in Iran and Iraq, and the above Cochran formula

has been used for specification of sample size given that the populations in both countries have been infinite.

Sample size has been 384 people in Iran and 387 people in Iraq. The individuals in the samples are ones using one

of the operators available in Iran and Iraq.

Given that the present research is a practical field study, two methods as follows have been used for data collection.

The first method is that of examining documents. In this research, the theoretical framework and research

background have first been developed through reference to library resources, use of search engines in the relevant

Internet databases and cataloguing of the relevant documents. Databases such as ScienceDirect, Emerald,

ProQuest, ERIC, and ResNet have been used as English resources, and Iranian Research Institute for Information

Science and Technology, Scientific Information Database, Civilica, Modiryar, E-Modiran, MgtSolution, etc. have

been used as Persian resources. Other library resources for information collection include library research on books pertaining to research, accredited scientific journals, and domestic scientific-research journals. The second

method is the field method. The main data collection instrument in the survey step has been the questionnaire.

The designed questionnaire was randomly distributed in parts of Iran and Iraq.

IV. Findings

In this section, the researcher uses different methods of analysis to provide a solution to the developed problem

or to decide whether or not to confirm the hypothesis or hypotheses considered for the research. Therefore, it

should be noted that it is not sufficient to analyze the obtained data to find the answers to the research questions;

it is also necessary to interpret the data. The data should first be analyzed, and the results of the analysis should

then be interpreted. The information needed for the present research has been collected from the questionnaires

used for testing. This information was analyzed through the application of statistical tests appropriate to the research hypotheses in the SPSS 24 and LISREL 8.7 software environments. This section presents the collected

results and the analyses made of the data based on statistical inference using the appropriate statistical techniques

for confirmation or rejection of the research hypothesis. In this section, the collected data are first summarized

and classified using the indicators in descriptive statistics for description of the features of the sample. Then, the

descriptive statistics, including the means and standard deviations of the research variables, are provided. Next,

the hypotheses are confirmed or rejected using the inferential statistics indicators.

4.1 Descriptive Statistical Analysis

The results obtained from the collected sample are summarized in the following table.


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Table 1- Results Obtained from the Descriptive Statistics of the Collected Data

Variab

le

Countr

y Choice

Numbe

r

Percenta

ge

Variab

le

Countr

y Choice

Numbe

r

Percentag

e

Gende

r Iran Male 223 58.1 Age Iran Below 20 67 17.4

Female 161 41.9 21-30 185 48.2

Iraq Male 230 59.4 31-40 74 19.3

Female 157 40.6 41-50 37 9.6

Degree Iran

High School

Diploma and

Below

96 25 50 and

Above 21 5.5

Associate 31 8.1 Iraq Below 20 77 19.9

Bachelor’s 146 38 21-30 95 24.5

Master’s and

Above 111 28.9 31-40 151 39

Iraq

High School

Diploma and

Below

81 20.9 41-50 48 12.4

Associate 69 17.8 50 and

Above 16 4.1

Bachelor’s 187 48.3

Additi

onal

Service

s

Iran Conversati

on 202 52.6

Master’s and

Above 50 12.9 SMS 10 2.6

Opera

tor

Used

Iran Hamrah

Aval 200 52.1

Internet,

etc. 172 44.8

Irancell 161 41.9 Iraq Conversati

on 301 77.8

Other 23 6 SMS 6 1.6

Iraq Asiacell 281 7./6 Internet,

etc. 80 20.7

Korek

Telecom 95 24.5

Other 11 2.8

4.2 Inferential Statistical Analysis

A) Investigation of the Hypothesis of Data Normality Using the Kolmogorov-Smirnov (K-S) Test

For utilization of statistical techniques, it should first be specified whether or not the collected data have normal distribution, because parametric tests can be used for testing the hypotheses if the collected data are normally

distributed, and nonparametric tests are employed otherwise. For this purpose, the results obtained from the

Kolmogorov-Smirnov test in the case of each of the dependent and independent variables are examined in this

step, and the appropriate tests are selected based on the obtained results for verification of the research hypotheses.

{𝐻0: 𝑇ℎ𝑒 𝑑𝑎𝑡𝑎 𝑐𝑜𝑛𝑐𝑒𝑟𝑛𝑖𝑛𝑔 𝑣𝑎𝑟𝑖𝑎𝑏𝑙𝑒 𝑖 ℎ𝑎𝑣𝑒 𝑛𝑜𝑟𝑚𝑎𝑙 𝑑𝑖𝑠𝑡𝑟𝑖𝑏𝑢𝑡𝑖𝑜𝑛.𝐻1: 𝑇ℎ𝑒 𝑑𝑎𝑡𝑎 𝑐𝑜𝑛𝑐𝑒𝑟𝑛𝑖𝑛𝑔 𝑣𝑎𝑟𝑖𝑎𝑏𝑙𝑒 𝑖 𝑙𝑎𝑐𝑘 𝑛𝑜𝑟𝑚𝑎𝑙 𝑑𝑖𝑠𝑡𝑟𝑖𝑏𝑢𝑡𝑖𝑜𝑛.


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Given the results in the following table, 𝐻0 will result if the significance level value is greater than the error value,

and 𝐻1 will be confirmed if the significance level value is smaller than the error value.

Table 2- Results of the Normality Test of the Independent Variables

Factor Significance Level

(Sig.) Error Value Hypothesis Status Conclusion

Costs of Switching 0.247

0.05 𝐻0

It is normal.

Corporate Image 0.163 It is normal.

Trust 0.603 It is normal.

Service Quality 0.201 It is normal.

Satisfaction 0.149 It is normal.

Table 3- Results of the Normality Test of the Dependent Variable

Factor Significance Level

(Sig.) Error Value Hypothesis Status Conclusion

Customer Loyalty 0.264 0.05 𝐻0 It is normal.

B) Statuses of the Independent Variables in the Mobile Telecommunications Industry

For investigating and answering this question, the population mean test has been used. Based on the scores obtained from the sample and a conducted one-sample T test, the analysis results are shown in Table 9. As

observed, the p-values or, in other words, their Sig. values are less than the value α = 0.05 for all the independent

variables (costs of switching, corporate image, trust, service quality, and satisfaction). Therefore, the null

hypothesis, stating that the values of the independent variables are 3 (the moderate level), has not been confirmed.

Furthermore, the mean difference between the two numbers shown in the column pertaining to the 95-percent

confidence interval does not involve zero, which itself confirms that the null hypothesis is rejected. Moreover, the

observation that the upper and lower bounds of the distance are positive for the variables corporate image and

service quality suggests that the means of these independent variables are greater than 3, and the observation that

the upper and lower bounds of the distance are negative for the variables costs of switching, trust, and satisfaction

suggests that the means of these independent variables are less than 3. Given the means concerning this dimension,

let us consider a score less than 2 as critical, one between 2 and 3 as improper, one equal to 3 as moderate, one

between 3 and 4 as proper, and one between 4 and 5 as good. In that case, the overall results can be explained as follows. For the independent variables, the variable costs of switching, with a mean of 2.957, is in moderate status,

corporate image, with a mean of 3.151, is in proper status, trust, with a mean of 2.708, is in improper status,

service quality, with a mean of 3.12, is in proper status, and satisfaction, with a mean of 2.866, is in improper

status in the mobile telecommunications industry from the perspectives of the respondents in both Iran and Iraq.

The statuses of the independent variables in the mobile telecommunications industries in Iran and Iraq are well

indicated in Table 9.

Table 4- Population mean test H0 = 3

Variable Mean Standard

Deviation

T

Statistic

Sig.

Value

Lower

Bound

Upper

Bound

Variable

Status Ranking

Costs of

Switching 2.957 0.505 -2.354 0.019 -0.079 -0.007 Moderate 3

Corporate

Image 3.151 0.66 6.353 0.000 0.104 0.198 Proper 1

Trust 2.708 0.74 -10.952 0.000 44300- -0.24 Improper 5

Service Quality

3.12 0.614 5.423 0.000 44400 441.3 Proper 2


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Satisfaction 2.866 0.678 -5.484 0.000 441.0- -0.086 Improper 4

C) Status of Customer Loyalty in the Mobile Telecommunications Industry

As observed, the p-value or, in other words, the Sig. value, which is 0.000, is less than the value α = 0.05, so the

null hypothesis, stating that the value of customer loyalty is 3 (the moderate level), has not been confirmed.

Furthermore, the mean difference between the two numbers shown in the column pertaining to the 95-percent

confidence interval does not involve zero, which itself confirms that the null hypothesis is rejected. Moreover, the

observation that the upper and lower bounds of the distance are negative suggests that mean customer loyalty is

less than 3. Given the mean, let us consider a score less than 2 as critical, one between 2 and 3 as improper, one

equal to 3 as moderate, one between 3 and 4 as proper, and one between 4 and 5 as good. In that case, the overall

results can be explained as follows: in terms of customer loyalty, the population is in improper status, with a mean

of 2.897. Customer loyalty status in the mobile telecommunications industry is well indicated in Table 9-4.

Table 5- Population Mean Test H0 = 3

Variable Mean Standard

Deviation T Statistic Sig. Value

Lower

Bound

Upper

Bound

Variable

Status

Customer

Loyalty 2.897 0.632 -4.522 0.000 -0.148 -0.058 Improper

D) Hypotheses

Given that the collected data are normal, Pearson’s test of correlation is used for testing the correlation between

the factors mentioned in the research and customer loyalty. The value of correlation of each factor and the relevant

Sig. value appear in the table below. The following hypothesis is examined for confirmation or rejection of the

value of correlation.

{

𝐻0: 𝜌 = 0 𝑇ℎ𝑒 𝑓𝑎𝑐𝑡𝑜𝑟 𝑢𝑛𝑑𝑒𝑟 𝑖𝑛𝑣𝑒𝑠𝑡𝑖𝑔𝑎𝑡𝑖𝑜𝑛 𝑙𝑎𝑐𝑘𝑠 𝑎 𝑠𝑖𝑔𝑛𝑖𝑓𝑖𝑐𝑎𝑛𝑡 𝑒𝑓𝑓𝑒𝑐𝑡 𝑜𝑛 𝑐𝑢𝑠𝑡𝑜𝑚𝑒𝑟 𝑙𝑜𝑦𝑎𝑙𝑡𝑦 𝑖𝑛 𝑡ℎ𝑒 𝑚𝑜𝑏𝑖𝑙𝑒 𝑡𝑒𝑙𝑒𝑐𝑜𝑚𝑚𝑢𝑛𝑖𝑐𝑎𝑡𝑖𝑜𝑛𝑠 𝑖𝑛𝑑𝑢𝑠𝑡𝑟𝑦.

𝐻1: 𝜌 ≠ 0 𝑇ℎ𝑒 𝑓𝑎𝑐𝑡𝑜𝑟 𝑢𝑛𝑑𝑒𝑟 𝑖𝑛𝑣𝑒𝑠𝑡𝑖𝑔𝑎𝑡𝑖𝑜𝑛 ℎ𝑎𝑠 𝑎 𝑠𝑖𝑔𝑛𝑖𝑓𝑖𝑐𝑎𝑛𝑡 𝑒𝑓𝑓𝑒𝑐𝑡 𝑜𝑛 𝑐𝑢𝑠𝑡𝑜𝑚𝑒𝑟 𝑙𝑜𝑦𝑎𝑙𝑡𝑦 𝑖𝑛 𝑡ℎ𝑒 𝑚𝑜𝑏𝑖𝑙𝑒 𝑡𝑒𝑙𝑒𝑐𝑜𝑚𝑚𝑢𝑛𝑖𝑐𝑎𝑡𝑖𝑜𝑛𝑠 𝑖𝑛𝑑𝑢𝑠𝑡𝑟𝑦.

Table 6- Results of Pearson’s Test of Correlation Between Different Factors and Customer Loyalty

Factor Loyalty

Correlation Coefficient Sig. N

Perceived Service

Quality 0.351 0.000 771

Corporate Image 0.418 0.000 771

Trust in the Operator 0.499 0.000 771

Perceived Cost of

Switching 0.105 0.000 771

Satisfaction 0.430 0.000 771

Given the results in Table 11, 𝐻0 will result if the significance level value is greater than the error value, and 𝐻1

will result if the significance level value is smaller than the error value. Based on the results in the above table,

since significance level is less than 0.01 for all the factors, 𝐻1 (the research hypothesis) is confirmed, and its

opposing hypothesis, stating that there is no relationship between the different factors and customer loyalty, is

rejected. As observed, there is a significant positive relationship between the above factors and customer loyalty

at the 99-percent level, and the correlation coefficient is 0.351 for perceived service quality, 0.418 for corporate

image, 0.499 for trust in the operator, 0.105 for perceived cost of switching, and, finally, 0.430 for satisfaction.

E) Hypothesis Testing Using Structural Equation Modeling

Structural equation modeling has been used for testing the research hypotheses and ranking them in terms of

effectiveness on the dependent variable. Structural equation modeling is a comprehensive approach for testing

hypotheses concerning the relationships between the observed and latent variables, sometimes referred to as


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covariance structure analysis, causal modeling, or LISREL. Azar (2002) also argues that one of the most

powerful, appropriate methods of analysis in behavioral and social science is multivariate analysis, as the models

are multivariate in such cases, and cannot be solved with a bivariate method (where one independent variable is

considered along with one dependent variable each time). Covariance structure analysis, or structural equation

modeling, is one of the major methods of analyzing complex data structures and one of the new methods for

investigation of causal relationships, equivalent to analysis of different variables, representing the simultaneous

effects of variables on each other in a theory-based structure. With this method, the acceptability of a theoretical

model in a particular population can be tested using correlational, non-experimental, and experimental data.

Structural equation modeling with the LISREL software has been used for assessment of the factors effective on

customer loyalty and specification of the coefficients of each. Covariance structure analysis, or structural equation modeling, is one of the major methods of analyzing complex data structures and one of the new methods for

investigation of causal relationships, equivalent to analysis of different variables, representing the simultaneous

effects of variables on each other in a theory-based structure. This method can be used for solving a multivariate

conceptual model, which cannot be solved using a bivariate method (where one independent variable is considered

along with one dependent variable each time). In other words, a structural model is simply an explanation of the

causal relationships among latent variables. The purpose of the model is to detect the direct and indirect effects

of exogenous latent variables on endogenous latent variables.

Diagram 1- Structural Model of the Research in Standard Estimation Mode (First to Fifth Research

Hypotheses)


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Diagram 2- Structural Model of the Research in Significant Figures Mode (First to Fifth Research

Hypotheses)


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646

Table 7- Results of Testing the (First to Fifth) Research Hypotheses Using the Structural Equation Model

Hypothesis Path Direction Path

Coefficient T Ranking

First Perceived service quality has a positive effect on customer

loyalty in the mobile telecommunications industry. 0.40 3/96 4

Second Corporate image has a positive effect on customer loyalty

in the mobile telecommunications industry. 0/46 4/04 3

Third Trust in the operator has a positive effect on customer

loyalty in the mobile telecommunications industry. 0/60 7/47 1

Fourth

Perceived cost of switching has a positive effect on

customer loyalty in the mobile telecommunications

industry.

0/36 2/67 5

Fifth Satisfaction has a positive effect on customer loyalty in the

mobile telecommunications industry. 0/54 6/55 2

Based on the structural equation model and the statistics available in Table 16, the first to fifth research hypotheses

were confirmed, since the path coefficient T of all the variables has been greater than 1.96, which causes all the hypotheses to be confirmed. It is observed that trust in the operator (with an effect size of 0.60 and a significance

figure of 7.47) has had the greatest effect on customer loyalty, and is ranked first among the variables. Satisfaction

(with an effect size of 0.54 and a significance figure of 6.55) is ranked second, corporate image (with an effect

size of 0.46 and a significance figure of 4.04) is ranked third, perceived service quality (with an effect size of 0.40

and a significance figure of 3.96) is ranked fourth, and, finally, perceived cost of switching (with an effect size of

0.36 and a significance figure of 2.67) is ranked fifth (last).

Sixth hypothesis. There is a significant difference between the factors effective on customer loyalty in the mobile

telecommunications industries in Iran and Iraq.

{𝐻0: 𝑇ℎ𝑒 𝑚𝑒𝑎𝑛 𝑠𝑐𝑜𝑟𝑒𝑠 𝑜𝑓 𝑡ℎ𝑒 𝑟𝑒𝑠𝑒𝑎𝑟𝑐ℎ 𝑣𝑎𝑟𝑖𝑎𝑏𝑙𝑒𝑠 𝑖𝑛 𝐼𝑟𝑎𝑛 𝑎𝑛𝑑 𝐼𝑟𝑎𝑞 𝑎𝑟𝑒 𝑒𝑞𝑢𝑎𝑙.

𝐻1: 𝑇ℎ𝑒 𝑚𝑒𝑎𝑛 𝑠𝑐𝑜𝑟𝑒𝑠 𝑜𝑓 𝑡ℎ𝑒 𝑟𝑒𝑠𝑒𝑎𝑟𝑐ℎ 𝑣𝑎𝑟𝑖𝑎𝑏𝑙𝑒𝑠 𝑖𝑛 𝐼𝑟𝑎𝑛 𝑎𝑛𝑑 𝐼𝑟𝑎𝑞 𝑎𝑟𝑒 𝑢𝑛𝑒𝑞𝑢𝑎𝑙.

Table 8- Results of the independent-samples T test conducted for investigation of whether there are

differences between the factors effective on customer loyalty in Iran and Iraq

Hypothesis Countr

y

Numbe

r

Mea

n

Standard Deviatio

n

Standar

d Error

Mean Differenc

e

T Statisti

c

Degree of

Freedo

m

Level of Significanc

e

Costs of

Switching

Iran 384 2.92

9 0.469 0.024

-0.056 -1.55 769 0.122

Iraq 387 2.98

5 0.537 0.027

Corporate

Image

Iran 384 3.13

4 0.613 0.031

-0.034 -0.717 769 0.473

Iraq 387 3.16

8 0.703 0.036

Trust

Iran 384 2.82

3 0.723 0.037

0.23 4.359 769 0.000

Iraq 387 2.59

4 0.739 0.038


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647

Service

Quality

Iran 384 3.13

9 0.585 0.03

0.038 0.825 769 0.395

Iraq 387 3.10

1 0.642 0.033

Satisfactio

n

Iran 384 2.93

5 0.675 0.034

0.137 2.82 769 0.005

Iraq 387 2.79

8 0.675 0.034

It is observed based on the information available in Table 8 and the test results that there has not been a significant

difference for the variables costs of switching, corporate image, and service quality given that Sig. > 0.05, and the

respondents from Iran and Iraq have had similar attitudes toward these variables, finding them appropriate at the

same levels in the mobile telecommunications industry. For the variables trust in the operator and satisfaction,

however, there have been significant differences given that Sig. < 0.05. Based on the observed means, the

respondents in Iran, with the means 2.823 and 2.935, have had more positive attitudes than those in Iraq, with the

means 2.594 and 2.798, toward the variables trust in the operator and satisfaction, respectively.

There are significant differences between Iran and Iraq in customer loyalty in the mobile telecommunications

industry.

{𝐻0: 𝑇ℎ𝑒 𝑚𝑒𝑎𝑛 𝑐𝑢𝑠𝑡𝑜𝑚𝑒𝑟 𝑙𝑜𝑦𝑎𝑙𝑡𝑦 𝑠𝑐𝑜𝑟𝑒𝑠 𝑖𝑛 𝐼𝑟𝑎𝑛 𝑎𝑛𝑑 𝐼𝑟𝑎𝑞 𝑎𝑟𝑒 𝑒𝑞𝑢𝑎𝑙.

𝐻1: 𝑇ℎ𝑒 𝑚𝑒𝑎𝑛 𝑐𝑢𝑠𝑡𝑜𝑚𝑒𝑟 𝑙𝑜𝑦𝑎𝑙𝑡𝑦 𝑠𝑐𝑜𝑟𝑒𝑠 𝑖𝑛 𝐼𝑟𝑎𝑛 𝑎𝑛𝑑 𝐼𝑟𝑎𝑞 𝑎𝑟𝑒 𝑢𝑛𝑒𝑞𝑢𝑎𝑙.

Table 9- Results of the Independent-Samples T Test Conducted for Investigation of Whether There is a

Difference in Customer Loyalty Between Iran and Iraq

Hypothesi

s

Countr

y

Numbe

r

Mea

n

Standard

Deviatio

n

Standar

d Error

Mean

Differenc

e

T

Statisti

c

Degree

of

Freedo

m

Level of

Significanc

e

Customer

Loyalty

Iran 384 2/98 0.629 0.032

0/165 3/645 769 0/000 Iraq 387 2/81

5

0.625 0.032

It is observed based on the information available in Table 9 and the test results that there has been a significant

difference in customer loyalty given that Sig. < 0.05. Based on the observed means, the respondents in Iran, with

the mean 2.98, have been more loyal to the mobile telecommunications industry than those in Iraq, with the mean

2.815.

V. Conclusion and Suggestions

In the present research, the first to fifth hypotheses were confirmed. The results concerning the beta coefficient in LISREL demonstrated that trust in the operator has been ranked first with a coefficient of 0.60, and has been the

most effective variable on customer loyalty in the mobile telecommunications industry. Satisfaction (with a

coefficient of 0.54) has been ranked second, corporate image (with a coefficient of 0.46) has been ranked third,

perceived service quality (with a coefficient of 0.40) has been ranked fourth, and, finally, perceived cost of

switching (with a coefficient of 0.36) has been ranked fifth (last), less effective than the other variables on

customer loyalty in the mobile telecommunications industry.

The operating companies should take customers’ perception of service quality into consideration, and increase

customer satisfaction through increases in service quality (coverage, convenience, successful calls, etc.), which in

turn increases customer loyalty to the company. The operators should enhance the quality of the service provided

by the company, and focus on the technologies of the day and the amusing aspects, all of which help provide

customers with satisfaction, and affect their satisfaction positively, thereby increasing customer satisfaction and customer loyalty. Customers pay plenty of attention in the telecommunications industry to service quality, and the

issue should be taken into account seriously, prioritizing improvements in service quality in companies, given the


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particular conditions of service companies, discussed in Section 2. Thus, customers can be made loyal to the

company, so that the competitive conditions are maintained for it.

A service provision company can acquire a powerful competitive position by presenting a positive image to

customers’ minds. Consideration of the activities of the company on the part of the senior managers of the

organization and care for meeting the needs and improving service provision causes a positive image of the

company to take shape in customers’ minds. Maintenance of the positive image of the company and customers’

positive perception of it should be taken into consideration. Thus, if a positive image is established of the company,

both the image persists in the customers’ perception, and the competitive advantage increases the future income

and profit of the company.

Furthermore, the following suggestions may be practical for success of a company:

increasing the geographical coverage of the cellphone operator so that more regions are covered by the

service

accelerating response to customer’s complaints

establishing a voice of the customer department and evaluating the performance of the department staff

via customers

offering an online billing system to increase customers’ trust in the operator

providing a variety of new services so that different customer needs are covered by the operator

participating in social activities admired by the society

emphasizing the staff’s innovation and creation of competitive advantage

utilizing a customer satisfaction survey system at the company

instructing the staff to behave well toward customers to obtain their satisfaction identifying different age groups’ needs, preferences, and motivations for continuing their contact with

the operator

considering different scores for loyal customers and offering incentives to subscribers that have attracted

customers to the organization by recommending the operator

considering plans for satisfying older customers as beneficial subscribers and establishing loyalty in them

by increasing the lengths of their contact with the organization

holding direct and indirect polls for identification of different subscribers’ expectations and realization

of their evaluations of the operator and its services

improving the subscriber complaint handling system for satisfaction of customers.

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