The Relationship Between Customer Satisfaction and ...

INTERNATIONAL JOURNAL OF ENGINEERING AND MANAGEMENT Vol. 3, No. 2, July-December 2011, pp. 87-105

IJEM

The Relationship Between Customer Satisfaction and Market Share: The Case of Mobile Sector in Greece D. Drosos*, N. Tsotsolas and P. Manolitzas Technological Education Institute of Piraeus, Business School Management Information System Laboratory Petrou Ralli and Thivon 250 Aigaleo

Abstract: The telecommunications industry is currently one of the technologically most important and fastest growing sectors of the economy. Over the last two decades, mobile communications have become an integral part of this industry, enabling the formation and growth of national income, increasing corporate and government revenues as well as creating new jobs. For the purpose of this paper, the findings of two consecutive six month long surveys will be presented, measuring the satisfaction levels of users of three mobile phone companies which operate in Greece, as well as the relationship of these findings and the changes of market shares of the three companies. For the collection of the data, questionnaires were used in order to better record the customers’ views on the service overall as well as their satisfaction levels on particular aspects of the service. The analysis of the results has been based on the multicriteria MUSA method, which is part of the wider category of aggregation – disaggregation approach and is based on the principles of qualitative analysis regression. The results of the data analysis provide strong indications that the changes in customer’s satisfaction level affect the market share. Keywords: Customer Satisfaction, Market Share, Multicriteria Analysis.

1. INTRODUCTION Over the past two decades, customer satisfaction has formed the basis for businesses that aim at finding themselves at the top of the modern global marketplace. The purpose of a business company is, initially, to meet the customer’s expectations through the products or services offered so that his or her loyalty will be achieved (Boshoff and Gray, 2004). Consumers however, are constantly becoming more demanding, resulting at an ever increasing level of expectations from a product or service. Therefore, the company must continually identify the needs and expectations of the consumer and seek to meet and satisfy them (Gustafsson et al., 2005). Consequently the above factor combined with the increased competition that exists among the leading service providers has led them to adopt a customer driven policy. That is why customer satisfaction is an important tool for businesses today and *

Corresponding Author: [email protected]

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International Journal of Engineering and Management (IJEM)

shapes their strategy. The philosophy of customer satisfaction at least by international standards is nothing new. A research that was completed in 1988 in the United States of America with the participation of 700 top executives working for large companies showed that 64% of these executives, perceived customer satisfaction as their number one priority. The other 36% said that it was amongst their top priorities (Shoultz, 1989). According to Fornell (1992) one of the main drivers for the increased emphasis given to customer satisfaction over the recent years, is that increased customer satisfaction can lead a company to a sustainable competitive position that will in turn create an increase in market share, increase in profits, reduced price elasticity, reduction in operating costs, reduced rework costs and finally a cost reduction of attracting new customers. Satisfaction and thus customer loyalty to a company's products or services is generally considered to be one of the most important driving forces influencing sales. Satisfied customers become loyal customers and also share their positive experiences with other people who are potential customers of the same company. (Fornell et al., 1996). The scope of this paper is to empirically highlight the different aspects of the relationship between customer satisfaction and market share, in the Greek mobile sector. This paper is organized into 4 sections. Section 1, presents the literature, regarding customer satisfaction, and the different views about the relationship between business performance, loyalty, productivity, profitability, reputation, market share and customer satisfaction. Section 2 presents the MUSA (Multicriteria Satisfaction Analysis) method, which is the Decision Support System that was used in order to measure the customer satisfaction. Section 3 presents the methodological frame and the results of our research. Finally, section 4 summarises some concluding remarks and discusses, potential extensions of the research. 2. LITERATURE REVIEW 2.1 Customer Satisfaction The satisfaction of customer, according to Yi (1991), is fixed with two basic ways: “or as a result, or as a process. The first way determines the satisfaction as a final situation or as a result of experience of consumption or use of product or service”. According to another approach “the satisfaction is a cognitive situation of customer, with regard to his sufficient or insufficient remuneration for the sacrifices and the efforts that have overwhelmed” (Howard and Sheth, 1969). Westbrook and Reilly (1983) consider that “satisfaction is a sentimental reaction in the experiences of customer that are related or with concrete products and services, or with the processes of market or still with concrete characteristics of this customer”. Another definition that has been proposed for the satisfaction of customer is the following: “Satisfaction is the result of purchase and use of a product or service, which derives from the customers comparison between the remuneration and the cost of purchase, taking into consideration the expected result” (Churchill and Suprenant, 1982). Alternatively, the satisfaction can be seen as a process, with emphasises on psychological factors of perception and evaluation of the impact: “Satisfaction is an evaluation process based on whether this experience was as

The Relationship Between Customer Satisfaction and Market Share: The Case of Mobile Sector in Greece

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good as the client believed that is” (Hunt, 1977). “Satisfaction is an evaluation process, which examines whether this choice is consistent with previous convictions of the client” (Engel and Blackwell, 1982). Satisfaction is the reaction of consumers in the evaluation process, which examines the discrepancies between prior expectations and actual performance level of the product as perceived by the consumer after use” (Tse and Wilton, 1988). In general, the most popular definitions of customer satisfaction are based on meeting customers expectations. As explained by Oliver (1996), Gerson (1993) and Vavra (1997), satisfaction is a measure of how the total offered product or service fulfills customer expectations. To reinforce customer orientation on a day-to-day basis, a growing number of companies choose customer satisfaction as their main performance indicator. It is almost impossible, however, to keep an entire company permanently motivated by a notion as abstract and intangible as customer satisfaction. Therefore, customer satisfaction must be translated into a number of measurable parameters directly linked to people’s job -in other words factors that people can understand and influence (Deschamps and Nayak, 1995). 2.2 The Relationship Between Customer Satisfaction and Business Effectiveness It is apparent that during recent years customer satisfaction has become a well-known and established concept in several sciences. Many researches attempted to link customer satisfaction to business performance, loyalty, productivity, profitability, reputation and market share. A number of studies in different industries have shown that higher levels of customer satisfaction lead to greater customer loyalty (Anderson and Sullivan, 1993; Anderson et al., 1997; Bearden and Teel, 1983; Bolton and Drew, 1991; Fornell, 1992; Oliver, 1980; Oliver and Swan, 1989; Yi, 1991). There is considerable disagreement concerning the positive or negative relationship between customer satisfaction and productivity. The Scientific areas of production management and operations research commonly argue that this relationship can be positive. Guru’s of TQM (Crosby, 1979; Deming, 1982; Juran, 1988) believe that the firm that achieves superior levels of customer satisfaction needs to dedicate fewer resources to handling returns, rework, warranties, and complaint management, thus lowering costs and improving productivity. On the other hand Griliches (1971) and Lancaster (1979) claim that there is a negative relationship between customer satisfaction and business performance. Customer satisfactionutility-is modelled as a function of product attributes. Increasing the level of utility-improving raw materials, adding features or service personnel-requires increasing the level of product attributes and, therefore, costs. Another interesting link is the link between corporate reputation and customer satisfaction. Davies et al., (2002) in their study of retailing context demonstrated that there is a positive impact of corporate reputation on customer satisfaction. Walsh et al., (2006), in their study of private energy customers in Germany, found that there is a strongly relationship between customer satisfaction and corporate reputation. Hennig-Thurau et al., (2002) demonstrated that customers, who are satisfied with the performance of a company, are likely to engage in positive word-of-mouth, thus positively reinforcing the company’s reputation.

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Many researchers have accepted the view that customer satisfaction is positively related with the desired business performance. At the same time many studies have shown that customer satisfaction has measurable effects on the customer’s intention to repurchase the offered product or service, (Bolton and Drew, 1991; Mittal et al., 1999; Oliver and DeSarbo, 1988), customer loyalty, (Anderson and Sullivan, 1993; Bolton, 1998; Ittner and Larcker, 1998; Mittal and Kamakura, 2001) as well as the fulfillment of the company’s financial goals. (Anderson and Mittal, 2000; Fornell et al., 1996; Rust and Zahorik, 1993, Jones and Sasser, 1995, Chaudhuri and Holbrook, 2001; Fournier, 1998; Oliver, 1999). Zeithaml (2000) gives an overview of findings of research on aspects of the relationship between customer satisfaction and business performance. Nelson et al., (1992) found positive evidence on the direct relationship between customer satisfaction and business performance in hospital settings with higher profitability. Aaker and Jacobson (1994) found better stock return linked to improved quality perceptions; Anderson et al., (1994) found a significant association between customer satisfaction and accounting return on assets. Ittner and Larckner (1996) found that shareholder value is highly elastic with respect to customer satisfaction. On the other hand, many researchers claim that there is a negative relationship between customer satisfaction and business performance. Tornow and Wiley (1991) concluded that there is a negative correlation between customer satisfaction and gross profit. In another study, Wiley (1991) found that all dimensions of customer satisfaction are negatively related to financial performance. In an article on service quality and its impact on profits, Schneider (1991) concluded that customer satisfaction does not always have a positive impact on profits. During the recent years several models have been implemented in order to examine the relationship between customer satisfaction and profitability. Heskett et al., (1994) demonstrated the Service – Profit Chain Model which suggests that employee satisfaction leads to customer satisfaction, which leads to corporate profitability. Other researchers (Rust et al., 1995; Rust et al., 2002; Gustafsson and Johnson, 2002) suggest that improvements in total quality, lead to improved customer satisfaction, which leads to a higher lever of customer loyalty, which can result to a higher profitability for an enterprise. Other researches (Buzzell and Gale, 1987; Jacobson and Aaker, 1987; Gale, 1992; Hallowell, 1996) show that higher customer satisfaction translates into higher than normal market share growth. However, Fornell (1992), based on data collected from 25,000 consumers who reported their degree of satisfaction with the consumption of products and services from 32 industries, he reported that customer satisfaction and market share do not always have a parallel direction. Hellofs and Jacobson (1999), using empirical data show that increases in market share may negatively affect the consumers’ perception of quality in at least two ways: Indirectly by creating negative network externalities and directly by the loss of exclusivity and the loss of the image of using a product as a result of its increased market share and the product’s popularity. Actually, there are two contradicting approaches regarding the relationship between customer satisfaction and market share. Empirical findings have established a positive relationship between market share and quality, while the latter is directly related to customer satisfaction under the


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notion that the greater the buyer’s perceived quality, the greater the satisfaction he derives from the product or the service (Kordupleski et al., 1993; Kroll et al., 1999; Oliver 1997). This positive association may be considered as an indication that by enhancing the quality of the company’s output over and above the level of quality that characterizes the products of its main competitors, the company will probably gain a competitive advantage. On the other hand there are researches that have provided evidences according to which the relationship between customer satisfaction and market share is not always positive (Hellofs and Jacobson, 1999). This negative association has also been suggested by Fornell (1992) whose findings confirmed that in industries where customers’ tastes are heterogeneous while the producers’ offer is standardised, customer satisfaction is negatively associated with market share. Based on the above contradicting approaches, Gounaris et al., (2001) discussed the hypotheses that the relationship between customer satisfaction and market share is moderated by the degree of homogeneity of the customers’ preferences as well as by the degree of heterogeneity of the producers’ offerings. More specifically, the research concluded that in markets where customers’ preferences are homogeneous, market share and customer satisfaction are positively related, while in markets where customers’ preferences are heterogeneous, market share and customer satisfaction are not related. Based on the findings of the aforementioned research we are going to evaluate the relationship between customer satisfaction and market share in the Greek mobile sector. One of the main characteristic of this specific market is that all three competitors are offering products and services with great degree of similarity. Furthermore, the mobile market in Greece is characterized as mature given the fact that by the end of 2009 there were more than 20.290.000 Connections. Most of the customers have definitely decided which provider meets better their needs throughout the years. On the other hand the cost for changing from one provider to the other is practically zero. So, we assume that if a customer is not satisfied from the services provided by one company, he/she can easily change provider. For the reason we would expect the overall satisfaction level of customers of the three mobile providers to be at similar level. The question is what is actually happening if a customer for some reasons starts to express lower level of satisfaction. Is this event an indication that the customer would probably change provider? Based on the above thoughts we are discussing in this paper the hypothesis that the changes in customers’ satisfaction levels lead to changes regarding the market shares in a market where the degree of homogeneity of the customers’ preferences is high. The assessment of market’s homogeneity/ heterogeneity won’t be based on the potential structural differences of our sample because all three competitive companies offer a big range of products and services to cover the different customers’ demographic profiles. In this study, we follow the same approach as Gounaris et al., (2001), and we assess the homogeneity/ heterogeneity of the sample based on the extent to which the customers’ degree of satisfaction depending on the personal demographic characteristics.

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3. THE MUSA METHOD The MUSA (Multicriteria Satisfaction Analysis) method of Grigoroudis and Siskos (Grigoroudis and Siskos, 2002; Siskos and Grigoroudis, 2002) has been chosen to be used in order to measure customer satisfaction in this research. The basic principle of MUSA is the aggregation of individual judgements into a collective value function, assuming that customer’s global satisfaction depends on a set of criteria representing service characteristic dimensions (Figure 2). The global satisfaction is denoted as a variable Y and the set of criteria is denoted as a vector X = (X1, X2,…,Xn). MUSA was chosen over other statistical, econometrical methods because it gives reliable answers to the following criticism of other methods, namely: 1. Most of the statistical models that are used to analyze consumers’ behavior cannot deal with qualitative variables, and whenever this happens, the variables are a priori encoded which results to a loss of the information provided by the consumer. 2. In several methods strong hypotheses are concerned which is difficult to be proved. These hypotheses may refer either to consumer behavior or to the estimation model (e.g. satisfaction assessment using a specific probability function). 3. Many methods focus mostly on the description of the characteristics which affect customer’s satisfaction and not on the synthesis of these characteristics to a global satisfaction index. 4. Finally, several methods need information which is difficult to be collected (e.g.: customers’ expected utility, tradeoffs, etc) This preference disaggregation methodology is implemented through an ordinal regression based approach in the field of multicriteria analysis used for the assessment of a set of a marginal satisfaction functions in such a way, that the global satisfaction criterion becomes as consisted as possible with customer’s judgments (Jacquet-Lagreze and Siskos, 1982; Siskos, and Yannacopoulos, 1985). According to the survey, each customer is asked to express his/her own judgements, namely his/her global satisfaction and his/her satisfaction with regard to a set of discrete criteria, representing characteristics of the provided products and services. Based on these assumptions, the problem is approached as a problem of qualitative regression and solved via special linear programming formulations where the sum of deviations between global satisfaction evaluation expressed by customers and the one resulting from their multicriteria satisfaction evaluations is minimized. The main results from the aforementioned preference disaggregation approach are focused on global and partial explanatory analysis. Global explanatory analysis lays emphasis on customers’ global satisfaction and its primary dimensions, while partial explanatory analysis focuses on each criterion and their relevant parameters separately. Satisfaction analysis results, in more detail, consist of: • Global satisfaction index: it shows in a range of 0-100% the level of global satisfaction of the customers; it may be considered as the basic average performance indicator for the organisation.


•

•

• •

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Global demanding index: it shows in a range of -100%-100% the demanding level of customers according to the following: • demanding index 100%: extremely demanding customers • demanding index 0%: “normal” customers • demanding index –100%: non-demanding customers Criteria/sub-criteria satisfaction indices: They show in a range of 0-100% the level of partial satisfaction of the customers according to the specific criterion/sub-criterion, similarly to the global satisfaction index. Weights of criteria/sub-criteria: they show the relative importance within a set of criteria or sub-criteria. Demanding indices: they show in a range of -100%-100% the demanding level of customers according to the specific criterion/sub-criterion, similarly to the global demanding index.

Figure 1: Performance/Importance Diagram

Combining weights and satisfaction indices, a series of “Performance/Importance” diagrams can be developed (Figure 1). Each of these diagrams is divided into quadrants according to performance (high/low), and importance (high/low), that may be used to classify actions: • Status quo (low performance and low importance): Generally, no action is required. • Leverage opportunity (high performance/high importance): These areas can be used as advantage against competition.

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•

Transfer resources (high performance/low importance): Organisation’s resources may be better used elsewhere. • Action opportunity (low performance/high importance): These are the criteria/subcriteria that needs attention. The above methodology has been successfully implemented in many customer satisfaction surveys. Moreover, it has been used in similar research related to customer satisfaction (Siskos and Grigoroudis, 2002). 4. METHODOLOGICAL FRAME This research process consists of the steps below (Hayes, 1992): • Preliminary analysis: Customer satisfaction research objectives should be specified in this stage; preliminary market and customer behavioural analysis should be conducted in order to assess satisfaction dimensions (customers' consistent family of criteria). • Questionnaire design and conducting survey: Using results from the previous step, this stage refers to the development of the questionnaire, the determination of survey parameters (sample size, collection data form, etc.) and the survey conduction. • Analysis: The implementation of the model is included in this stage providing several results as described in the previous paragraph. Analysis is performed into the total set of customers, as well as into distinctive customer segments. Provided results involve basic descriptive statistical models, as well as the multicriteria preference disaggregation MUSA model. • Results: Using the results from the analysis stage, final proposals for company's improvement strategy can be formulated; a reliability testing process for the results of the model is also included in this stage. 5. CUSTOMER SURVEY 5.1 Customer Conduction The results presented in this paper come from two sequential satisfaction surveys, the first one conducted from July to December 2008 and the second one from July to December 2009. For the implementation of these two surveys a structured questionnaire was developed which was addressed to customers of the three mobile telecommunications companies of Greece (Vodafone, Wind, and Cosmote). A total of 1050 usable questionnaires were returned during the first survey and 1612 during the second one. For the purposes of this research a web site was constructed. Through the web site the customer had the opportunity to answer a web based questionnaire. 5.2 Satisfaction Criteria The main satisfaction criteria for the survey consists of: • Products - Services: Satisfaction from the services and products of each mobile phone company


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•

Network: This dimension refers to the network of the mobile company

•

Stores: This criterion refers to the location of stores and the network of branches that have been developed by the companies

•

Human Resources: This criterion measures the satisfaction that a client gains when communicating with the staff of the mobile operator in the branch or through the contact center.

•

Customer service: Refers to consumer satisfaction from the services

•

Prices: This dimension focuses on the costs of services

•

Web Page: This criterion indicates the satisfaction from the website of each company.

We must mention that the set of satisfaction criteria in this survey is based on bibliographical research. Many researchers (Grigoroudis et al., 1999; Tsintarakis et al, 2001; Grigoroudis and Siskos, 2010; Michelis et al., 2001; Krassadaki et al., 2002; Manolitzas et al., 2010) introduce questionnaires in order to measure the customer satisfaction in several different sectors like banks, shipping, airlines, food and drinks, information technology and the public sector. Each of the 7 criteria above is divided into sub-criteria, which appear in the following figure.

Figure 2: Hierarchical Structure of Customer Satisfaction Dimensions

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6. RESULTS 6.1 Sample The sample selected with random sampling and constituted customers from all the mobile companies in Greece. All the information about our sample presented in Table 2 Table 1 Sample Information 1st Research

2nd Research

Male Female

46.80% 53.20%

48.57% 51.43%

Age

55

22.00% 39.70% 20.20% 13.20% 4.90%

21.40% 41.69% 21.09% 10.55% 5.27%

Educational Level

Lower Secondary School Upper Secondary School Vocational Training Graduate Postgraduate/Doctorate

2.60% 27% 19.70% 21.20% 29.50%

1.99% 30.66% 18.75% 20.04% 28.56%

Single Married Married with children Divorce

56.00% 21.50% 21.60% 0.90%

54.02% 19.43% 24.57% 1.98%

4000 €

65.90% 55.90% 34.50% 5.30% 2.00%

32.75% 52.75% 32.88% 7.31% 3.59%

Gender

Family Status

Income Level

In the first as well as in the second survey the biggest portion of the respondents was customers of Cosmote and the smallest one customers of Wind. This ranking reflects the actual market shares of the three companies during the survey periods. Table 2 Mobile Companies Market Share 1st Research

2nd Research

Vodafone

36.00%

33.00%

Cosmote

38.90%

44.50%

Wind

25.10%

22.50%


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6.2 MARKET HOMOGENEITY/HETEROGENEITY Following the approach of Gounaris et al. (2001), we assessed the homogeneity/heterogeneity of the mobile service market based on the extent to which the consumers’ degree of satisfaction with the consumption of a given brand varies depending on the personal demographic characteristics. In order to examine the degree of market homogeneity/heterogeneity that characterised this market, we investigated the extent to which the buyers’ satisfaction level (overall, as well as partial on the criteria) with the use of the services provided by the three companies varies depending on the personal demographic characteristics. For the evaluation of the aforementioned correlation we chose to use two measures depending on the nature of the scale of each variable: • Chi-square test for nominal demographic variables • Spearman’s correlation coefficient for demographic ordinal variables The demographic variables which were filled in the questionnaire were: gender, age, education level, family status and income level. Table 3 Correlation of Customer Satisfaction and Respondents’ Demographic Characteristics (Nominal Variables) Satisfaction Criteria

X2 values for demographic variables Gender

Overall Satisfaction Product - Services

Family status

1st survey

2nd Survey

1st survey

2nd Survey

0.122

0.651

0.825

0.097

0.015*

0.015*

0.013*

0.087

Network

0.146

0.025*

0.672

0.200

Stores

0.168

0.471

0.225

0.047*

Human resources

0.701

0.464

0.535

0.188

Customer services

0.674

0.144

0.260

0.090

Prices

0.423

0.074

0.055

0.081

Web page

0.153

0.006**

0.362

0.123

Significance levels:

** significant between 0.000 and 0.010, * significant between 0.010 and 0.050, Table 4 Correlation of Customer Satisfaction and Respondents’ Demographic Characteristics (Ordinal Variables)

Satisfaction Criteria

Spearman’s correlation coefficient for demographic variables Age

Overall Satisfaction

Educational Level

1st Survey

2nd Survey

0.048

0.022

1st Survey 0.051

2nd Survey 0.033

Income Level 1st Survey

2nd Survey

0.010

0.062*

Table Cont’d

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Table 4 Cont’d Product - Services

0.063*

–0.008

0.117*

0.071*

0.033

–0.001

Human resources

0.116*

0.029

Customer services

0.085

0.072*

Prices

0.000

–0.045

Web page

0.026

–0.090**

–0.042

Network Stores

Significance levels:

0.043

0.079*

–0.054

0.023

0.089

0.050

0.036

0.045

0.034

–0.002

–0.016

–0.036

0.074

0.023

0.040

–0.014

0.043

0.008

0.018

0.056*

–0.024

–0.043

–0.024

–0.057*

–0.003

–0.013

–0.015

** significant between 0.000 and 0.010, * significant between 0.010 and 0.050,

According to the results presented in Tables 3 and 4, mobile market in Greece is characterised by homogeneity. More specifically, as the results suggest, the only significant correlations are observed between two demographic characteristics, namely gender and age, and satisfaction from web page criterion. These results indicate a homogeneous pattern of the drivers that create satisfaction in this particular market. 6.3 Criteria Weights By comparing the criteria weights produced by MUSA method according to the customers’ responses it is shown that there are no important differences among the three different companies. As it is presented in Table 5 for Vodafone in both surveys the highest weight is calculated for criterion “Network” with 22.1 % and 22.5% respectively. On the other hand the lowest weight is allocated to the criterion “Prices” with 9.9% and 11.8% correspondingly. Table 5 Criteria Weights Criteria

VODAFONE

WIND

COSMOTE

2008

2009

2008

2009

2008

2009

Product - Services

14.30%

13.70%

25.00%

23.40%

14.20%

14.20%

Network

22.10%

22.50%

14.30%

14.30%

21.30%

14.90%

Stores

14.30%

12.50%

14.50%

12.00%

14.30%

14.20%

Human Resources

14.30%

13.80%

12.30%

12.50%

14.30%

14.90%

Customer Service

13.20%

12.50%

14.30%

13.40%

14.30%

14.30%

Prices Web Page Total

9.90%

11.80%

9.30%

12.30%

10.00%

9.60%

11.90%

13.20%

10.30%

12.10%

11.60%

17.90%

100.00%

100.00%

100.00%

100.00%

100.00%

100.00%

Moving to the next company, Wind, it is shown in Table 5 that also in both surveys the calculated weights for the satisfaction criteria are similar. Particularly, the most important criterion in both surveys is “Products - Services” (25% and 22.6%). The least important criterion


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for the same company is the “Prices” for the first survey with 9.4% and for the second survey the criterion “Stores” with 12%. As far as the third company, Cosmote, is concerned, it is actually the only company in which some differences of the criteria importance are observed in the two surveys. Particularly, it is shown in Table 5 that for the survey conducted in 2008 the most important criterion by far, was “Network” with 21.3% while for the next survey in first position the criterion “Web Page” was found with 17,9%. This difference could exist due to the fact that in the period between the first and the second survey, Cosmote carried out some big changes concerning its marketing approach that also affected the company's web site, which was fully adapted to the new company image. As a result of this change the web page operated as a medium for improved communication with current customers and as a tool to attract new customers. On the other hand in both surveys the least important criterion was the “Prices” with 10% and 9.6% respectively. It is also worth to mention that all other criteria present minor differences between the two surveys. 6.4 Global Satisfaction Analysis As it is shown in Table 6, the overall results for both surveys are positive given the fact that the average global satisfaction indices for all three companies have high values, over 75%. In the first survey Vodafone has the highest value with 83.83 %, second in the row is Cosmote with very small difference (83.53%) and the lowest (81.82%) value has been calculated for Wind. So, it is obvious that customers of these companies are very satisfied. As far as the second survey is concerned (in 2009) that the only company that improves its performance is Cosmote showing in this survey the highest value with 83.95%. The other two companies are presenting lower values in comparison to the results of the first survey, namely 75.77% for Vodafone and 77.49% for Wind. Table 6 Satisfaction Indices 1st Research

2nd Research

Vodafone

83.83%

75.77%

Cosmote

83.53%

83.95%

Wind

81.82%

77.49%

6.5 Criteria Satisfaction As it can be seen in Table 7 for Vodafone for both 2008 and 2009, the criterion with the lowest satisfaction is that of the pricing policy with rates 60.7% and 56.42% respectively. The criterion with the highest satisfaction for 2008 is that the network reaches a rate of 87.1% and for 2009 is that of Products - Services with the rate reaches 84.52%. Noteworthy is the variation shown in the test Network between two years where satisfaction in 2009 decreases to 70.25%. Regarding the other criteria show a slight downward variation.

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International Journal of Engineering and Management (IJEM) Table 7 Average Satisfaction Indices

Criteria

VODAFONE

WIND

COSMOTE

2008

2009

2008

2009

2008

2009

Product - Services

80.80%

84.52%

87.3%

75.83%

80.20%

82.66%

Network

87.10%

70.25%

80.4%

85.21%

86.30%

84.35%

Stores

85.70%

79.75%

85.2%

83.58%

85.20%

84.97%

Human Resources

81.20%

78.79%

77.7%

80.38%

81.00%

84.01%

Customer Service

78.70%

74.39%

78.9%

75.51%

79.90%

81.02%

Prices

60.70%

56.42%

56.7%

60.79%

60.10%

61.04%

Web Page

75.30%

73.14%

70.6%

69.9%

74.10%

83.27%

In the case of Wind the criterion with the lowest satisfaction rate for both years is the pricing policy rates 56.7% and 60.79% respectively. The criterion with the highest satisfaction for 2008 is the criterion of Products - Services with 87.3% and for 2009 the criterion of Network with 85.21%.Remarkable for Wind company is the diversification which is outlined in the criterion of Products - Services whose satisfaction decreases about 12%.In the other criteria we did not observe any significant variation worthwhile any particular reference. And the third mobile operator (Cosmote) alike the previous two, shows the lowest satisfaction rate in the test Pricing. The satisfaction of this criterion in 2008 reached 60.1%, respectively, while for 2009 showed a marginal improvement, reaching 61.4%. The criterion with the highest satisfaction rate in 2008 was the Network (86.3%) while in 2009 the Human Resources with 84.01%. 7. RELATIONSHIP BETWEEN SATISFACTION AND MARKET SHARE The main objective of this study is to examine the correlation between the changes of customer satisfaction with the changes of the respective market shares which are occupied by three mobile phone companies in the Greek market. The relationship between customer satisfaction and market share will be based on the information available for the respective market shares of subscribers and revenue. According to data of table 8 Cosmote in comparison with two other companies, Vodafone, Wind increased its market share in the category of Subscribers. Cosmote market share increased from 39.4% in 2008 to 44.4% in 2009. Consequently, the market shares of the two other companies have been decreased with a greater reduction in the rate of Wind. Table 8 Market Share Based on the Subscribers, Adapted from Greek Mobile Companies Mobile Companies

Year 2008

Year 2009

Cosmote

39,4 %

44,4 %

Vodafone

33,0 %

31,6 %

Wind

27,6 %

24,0 %


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Similar views show market shares in the category of revenues. As it is shown in table 9 Cosmote rate was increased from 38.8% in 2008 to 45.1% in 2009. Corresponding rates for the other two mobile operators have a significant reduction. Table 9 Market Share Based on the Revenue, Adapted from Greek Mobile Companies Mobile Companies

Year 2008

Year 2009

Cosmote

38,8%

45,1%

Vodafone

36,2%

31,9%

Wind

25,0%

23,0%

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