investigation of the relationship between service values and loyalty behaviors under high commitment

EMPI RICAL ARTICLE

Investigation of the relationship between service valuesand loyalty behaviors under high commitment

Won-Moo Hur • Hyun Kyung Kim • Hanna Kim

Received: 4 January 2012 / Accepted: 4 June 2012 / Published online: 17 June 2012

� Springer-Verlag 2012

Abstract The aim of this study is to investigate to relationship between service

values, commitment, and customer loyalty. Based on self-administrated survey from

440 mobile service users in South Korea, the proposed model was estimated by a

hierarchical regression. First, the price and the quality values have a positive effect

on repurchase intention under high calculative commitment. Second, price value

also has a positive effect on positive word of mouth under high calculative com-

mitment. Finally, and social value has a positive effect on positive word of mouth

under high affective commitment. We discuss the implications of these findings for

commitment management strategies on the relationship between service values and

customer-loyalty link. Limitations and recommendations for future research are also

presented.

Keywords Perceived value � Commitment type � Loyalty behavior �Mobile service

W.-M. Hur

School of Business Administration, Pukyong National University, 599-1 Deayon3-dong,

Nam-gu, Busan, South Korea

e-mail: [email protected]

H. K. Kim (&)

Division of Business Administration, Hanyang Cyber University, 17 Haengdang-dong,

Seongdong-Gu, Seoul, South Korea


H. Kim

Department of Clothing and Textiles, College of Human Ecology, Chungnam National University,

220 Gung-dong, Yuseong-gu, Daejeon, South Korea


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Serv Bus (2013) 7:103–119

DOI 10.1007/s11628-012-0148-8

1 Introduction

Today, most service businesses, such as finance, mobile service, media, and retail,

have entered the maturity stage and reached saturation. Specifically, some mobile

service companies have experienced a deterioration of profitability because of

intense competition and overinvestment (Kim et al. 2004). In the maturity stage, it is

important to retain existing customers in addition to adding new customers to

increase profit, because acquiring new customers is quite costly from a marketing

perspective. Therefore, these mobile service companies are concerned with

preventing customer defection to competitors, and are thus seeking new revenue

sources by enticing their best customers to purchase additional services. The

purpose of these efforts is to manage positive word of mouth from existing

customers to prevent turnover and encourage the continued use of services, and to

develop cross-selling to increase profits, which can be achieved when customer

loyalty increases.

Customer loyalty provides a company with a sustainable competitive advantage

and can be a key factor in a company’s growth (Lee and Cunningham 2001; Liu

et al. 2011). Thus, a considerable number of studies have attempted to identify

predictors of customer loyalty and have verified the impact of service quality (Lai

et al. 2009; Lee and Murphy 2008), perceived value (Lin and Wang 2006),

satisfaction (Fullerton 2011), trust (Gounaris 2005), and commitment (Cater and

Zabkar 2009; Fullerton 2011; Gounaris 2005) on customer loyalty.

In particular, commitment is known as the key component of maintaining long-

term relationships between a company and its customers; thus, loyalty is formed and

strengthened through commitment (Gustafsson et al. 2005). Commitment can be

interpreted as an emotional concept, even though it has both emotional and rational

meanings from the customer’s perspective (Gilliland and Bello 2002). Therefore,

service providers should understand what commitment means from the customer’s

perspective and determine which types of perceived value form the basis of the

customer’s commitment, which is a major antecedent to customer loyalty. However,

it is unclear whether offering value for money prevents customer defection or even

increases positive word of mouth. Price value, which is the focus of most

companies, is not sufficient to achieve long-term customer loyalty. Therefore, it is

necessary to consider how various marketing activities, such as promotion, price

discounts, and membership programs, influence loyalty behaviors (Ganesh et al.

2000).

Most customers are already committed to their service providers in various ways

because of the mature stage of the mobile service industry. Thus, in this industry, it

is time to provide management strategies in service value to enhance customer

loyalty by commitment type. However, a considerable number of studies regarding

the relationship between value, commitment, and loyalty have been limited to the

mediating effect of commitment in the value-loyalty link (e.g., Bansal et al. 2004;

Fullerton 2011; Gruen et al. 2000; Hur et al. 2010).

Therefore, this study explores the moderating role of commitment in the

relationship between various service values and customer loyalty. In particular, the

current research classifies customers into two groups based on the relative strength

104 W.-M. Hur et al.

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of their commitment type: a group with stronger calculative commitment than

affective commitment, and the opposite. Through this classification, this study

provides empirical evidence suggesting more effective ways to use customer

relationship management strategies based on commitment segmentation to establish

customer loyalty, and strategic implications for mature service industries.

2 Theoretical background and hypotheses

The conceptual research model proposes the moderating effect of calculative and

affective commitment in the relationships among four types of perceived value and

loyalty behaviors (i.e., repurchase intention and word-of-mouth communications).

While repurchase intention and word-of-mouth communication have traditionally

been measured as components of a multidimensional measure of behavioral

intention (Zeithaml et al. 1996), this approach allows making an empirical

examination of the differential moderating effects of two types of commitment on

the relationship between the perceived value and the loyalty behaviors.

2.1 Perceived value

In this study, perceived value is defined as a multidimensional construct consisting

of functional (quality and price), emotional, and social values (Sweeney and Soutar

2001). This multidimensional view of value is especially useful in the mobile

service context, where recent research results indicate that perceived value should

include the time and location in which the service process occurred (Heinonen

2004). In the earlier literature, the value dimensions were conceptualized as having

a direct influence on value consumption behavior (Sheth et al. 1991; Pihlstrom and

Brush 2008).

In this study, four types of perceived value as suggested by Sweeny and Soutar

(2001) are modified for mobile service. Emotional value arises through fun or

enjoyable service experiences (Pihlstrom and Brush 2008). Mobile entertainment

contents or service can make people feel good and relaxed, and give people

pleasure. Emotional value is expected to influence the use of mobile information

content, because hedonic value is derived from the interaction with the technology

itself (Yen 2012). Social value is the utility derived from a mobile company or

brand’s ability to enhance one’s social self-concept through symbolic value. Social

value describes consumer consumption motives beyond a service’s functionality.

Consumers have been found to purchase products for reasons other than their

functional properties (Leigh and Gabel 1992). The social status and image

reflected by using innovative mobile services are usually considered major factors

leading to their use (De Marez et al. 2007). Price value is the utility derived as a

result of the reduction of perceived short-term and longer-term costs. Quality

value is the utility derived from the perceived quality and expected performance

of a mobile service.

Relationship between service values and loyalty behaviors 105

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2.2 Commitment

Commitment is a pledge of continuity between relational partners (Cater and Zabkar

2009). It can also be viewed as the attachment one party feels for another party in an

exchange situation (Gruen et al. 2000). At its core, commitment is the act of

maintaining a relationship with a partner (Bansal et al. 2004; Fullerton 2003).

Commitment can be a source of continued competitive advantage, because it offers

a company cost reduction, enhanced profits, positive word of mouth, and price

premium effects. In the last 20 years of relationship marketing research, the

understanding of commitment has significantly expanded. Many marketing

researchers have borrowed from the organizational behavior literature, in which

there is a rich tradition of research on the organizational commitment construct

(Bansal et al. 2004; Fullerton 2003; Jones et al. 2000).

In order to understand customer loyalty from the relationship perspective

(Fullerton 2003; Geyskens et al. 1996), this study proposes calculative and affective

commitments which are well accepted in the marketing context (Verhoef et al.

2002; Brown et al. 1995; Kumar et al. 1994; Geyskens et al. 1996; Gustafsson et al.

2005). Affective commitment is the propensity to continue stable and long-term

transactions through social ties and familiar relations with partners (Fullerton 2003).

Customers with affective commitment voluntarily sustain those relationships that

provide personal and social compensation. The identification or emotional tie is

closely connected to brand image or the consumer’s lifestyle. Affective commit-

ment can result in a strong relationship based on trust, because it is developed

through personal involvement and reciprocity (Garbarino and Johnson 1999; Royo-

Vela and Casamassima 2011).

Calculative commitment, which is more physical and transaction based, is built

through a rational process. According to this theory, the commitment to products

and services is acquired based on an understanding of the gains and losses that

would be generated if the transaction were terminated (Geyskens et al. 1996; Kumar

et al. 1994). The motivation for maintaining the calculative commitment relation-

ship is based on whether the gains from sustaining the relationship are greater than

the losses generated from terminating the relationship (Johnson 2007). Economic or

price value, such as reduced choice options and high switching costs, help build this

type of commitment (Anderson and Weitz 1992; Geyskens et al. 1996).

Calculative and affective forms of commitment coexist, but their antecedents

differ (Gilliland and Bello 2002). With calculative commitment, economic profit,

switching cost, or some other physical value (e.g., service quality) is the motivation

to continue the transaction. Psychological satisfaction during the transaction,

however, leads to affective commitment.

2.3 Loyalty

Loyalty can be defined as the continuous repurchase of or supporting behavior for a

preferred product or service, regardless of the options and marketing efforts that

encourage switching to competitors (Liu et al. 2011). Loyalty is the relationship

between relative attitudes about the brand, service, store, salespeople, and upholding


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behaviors (Dick and Basu 1994). Research on customer loyalty has been conducted

from different perspectives, including behavioral, attitudinal, and integrated

standpoints (Dick and Basu 1994). The behavioral view defines loyalty as repeated

purchasing (Cho et al. 2002). The attitudinal standpoint has been interpreted as

psychological immersion, because it is measured by a favorable attitude and the

possibility of purchase (Mathieu and Zajac 1990). The integrated perspective has

been conceptualized based on both attitudes and behavior (Dick and Basu 1994).

Recently, researchers have reclassified loyalty as both latent and spurious loyalty,

based on the integrated viewpoint (Dick and Basu 1994), or segmented loyalty,

categorized into active and passive loyalty (Ganesh et al. 2000). This study divided

loyalty behaviors into service retention and positive word of mouth, similar to

earlier research on classifying loyalty (Ganesh et al. 2000; Dick and Basu 1994).

In general, a company attempts to improve market understanding and implement

diverse strategies to pursue customer loyalty. Commitment is directly associated

with loyalty (Dagger et al. 2011), and explains how a customer becomes loyal to a

certain brand (Zeithaml et al. 1996). Several researches have also shown that the

stronger the customer’s commitment, the lower the tendency to switch brands (e.g.,

Ulrich 1989). The customer’s attachment or commitment to a service provider has a

positive effect on continuous transactions or active loyalty (Bettencourt 1997;

Ganesh et al. 2000). Commitment can play a moderating role in forming customer

loyalty.

2.4 Hypotheses

Commitment can be defined as the intention involved in continuing the relationship

with a service provider. Motivations of commitment include both economic effort

and non-economic effort (e.g., time spent and psychological effort) (Dick and Basu

1994). They could also include the loss of loyalty benefits as a result of ending the

current relationship (Heide and Weiss 1995). For example, familiarity with a

provider’s service procedures forms one type of commitment or a switching cost

because this knowledge will become useless if the customer discontinues the

relationship. As the commitment of customers increases, the likelihood of customers

engaging in such behavior will decrease, and this will have a positive effect on

customer loyalty (Burnham et al. 2003; Lam et al. 2004).

Allen and Meyer (1990) suggested that calculative commitment has its roots in

dependence, switching costs, and side bets. In addition, Kumar et al. (1994) defined

calculative commitment as an attachment status based on the economic and rational

values created to maintain relationships. Lee et al. (2003) and Verhoef et al. (2002)

argued that calculative commitment influences the intent to retain relationships.

Overall, calculative commitment based on economic and rational values is related to

loyalty behaviors. For instance, when considering several mobile services, such as

mobile internet, content, and ringtones from other service brands, additional costs

can be generated.

In situations where calculative commitments are high, customers stay with a

service provider because of the tangible value, such as price or quality. Therefore,

this study expects that the relationship between functional value (e.g., price or


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quality) and loyalty behaviors would be large, given the high calculative

commitment. In contrast, with low calculative commitment, customers switch

quickly to other service providers as they perceive low functional value. Here, this

study predicts a positive relationship between functional value, such as price or

quality, and customer loyalty behaviors, given a high calculative commitment.

Given the high correlation between customer value and customer satisfaction (Ball

et al. 2006; Lam et al. 2004), calculative commitment may have an impact on the

relationship between perceived value and loyalty, similar to the satisfaction–loyalty

linkage (Jones et al. 2000). In addition, Liu et al. (2011) suggested that calculative

commitments, such as switching costs, are typically continuously developed and

that they may reduce the relative importance of price or quality value for customer

loyalty behaviors, such as repurchase intention or positive word of mouth. The

following series for hypothesis 1 is proposed;

H1-1 If calculative commitment is stronger than affective commitment, then price

value has a positive influence on repurchase intention.

H1-2 If calculative commitment is stronger than affective commitment, then

quality value has a positive influence on repurchase intention.

H1-3 If calculative commitment is stronger than affective commitment, then price

value has a positive influence on word of mouth.

H1-4 If calculative commitment is stronger than affective commitment, then

quality value has a positive influence on word of mouth.

When customers have an affective commitment toward a service provider, they

are involved with the service provider and enjoy being affiliated with it (Allen and

Meyer 1990). Under a high affective commitment state, they perceive their

relationship with service providers as being in a friendship (Fullerton 2011; Jones

et al. 2000). Thus, the highly affective committed customers reward the service

provider with customer loyalty (Fullerton 2011). As the nature of affective

commitment is based on identification and emotional ties, customers tend to identify

with and become attached to the service provider which delivers psychological

offerings (e.g., social and emotional value experiences).

The affective commitment of the customer being high or low also determines the

strength of the link between service values and customer loyalty. Lee et al. (2001)

showed that psychological variables (e.g., switching cost) moderate the relationship

between customer satisfaction and loyalty, which is one of outcome variables of

service value. In addition, Yang and Peterson (2004) suggested that affective

commitment plays a moderating role in perceived value-customer loyalty link.

Wang (2010) also showed that commitment moderates the relationship between

brand images related to social value and customer loyalty. At the same time,

virtually no empirical study to date has examined the role of affective commitment

in the relationship between psychological service values, such as social or emotional

values, and loyalty (Woodruff 1997). Given the correlation between perceived

value, switching cost, customer satisfaction, and loyalty, it may be assumed that

affective commitment may impose a similar impact on the relationship between


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psychological service values and customer loyalty behavior (e.g., repurchase

intention or word of mouth). Thus, the hypothesis 2 follows:

H2-1 If affective commitment is stronger than calculative commitment, then

emotional value has a positive influence on repurchase intention.


social value has a positive influence on repurchase intention.


emotional value has a positive influence on word of mouth.


social value has a positive influence on word of mouth.

3 Methodology

3.1 Measurement scales

The questionnaire included items derived from the services marketing and loyalty

literature. The selected scales were English based and required double translation.

The English questionnaire was translated into Korean using the process recom-

mended by Brislin (1970). Seven-point Likert-type scales measured the constructs

(see Table 1). Three items to measure price value and four items to measure quality

value were adapted from Pihlstrom and Brush (2008) and Sweeney and Soutar

(2001). The reliability factors of the two scales were .76 and 79, respectively. Three

items to measure emotional value and three items to measure social value were

adapted from Pihlstrom and Brush (2008) and Sweeney and Soutar (2001), with

reliability factors of .90 and .83, respectively. Calculative commitment was

measured using four items adapted from Verhoef et al. (2002) and Kumar et al.

(1994), with scale reliability of .75. To assess affective commitment, three items

based on Verhoef et al. (2002) and Kumar et al. (1994) were used, with scale

reliability of .90. Three items to measure repurchase intention and three items to

measure word of mouth were adapted from Pihlstrom and Brush (2008), with

reliability factors of .80 and .88, respectively.

3.2 Data collection and participant characteristics

The hypothesized model was examined in the mobile service setting. As suggested

in the introduction section, the ideal context to test our research model should show

high levels of competition, diffusion of information among customers about offers

and marketing activities, and substantial customer involvement in service usage

(Raimondo and Costabile 2008). Based on these criteria, we collected data on

mobile services. This context represents some unique characteristics for the

following reasons. First, all of the major competitors have been systemically

investing in both communication and loyalty programs (Raimondo and Costabile

2008). Second, mobile consumers are generally involved in the consumption of


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Table 1 Scale items and construct evaluation

Construct Items k* a CR AVE

Price value The price of this mobile service is acceptable .78 .76 .79 .58

This mobile service is good value for money .94

This mobile service is better value for money than what I would

pay for the same via other channels (internet/store)

.49

Quality value I value the option of using this service instantly via my mobile

device

.57 .79 .81 .59

Using the mobile service makes my life easier .86

Using the mobile service is an efficient way to manage my time .84

Using the mobile service is an efficient way to manage my time .90

Emotional

value

Using the mobile service gives me pleasure .94 .90 .84 .76

Using this mobile service makes me feel good .77

Using this mobile service makes me feel relaxed .75

Social value Using the mobile service helps me to feel accepted by others .83 .83 .85 .65

Using this mobile service makes a good impression on other

people

.73

Using this mobile service gives me social approval .73

Calculative

commitment

Because it is difficult to stop my mobile service, I remain a

customer of this mobile service

.57 .75 .75 .50

I remain a customer because it is difficult to take my mobile

service to another

.70

I remain a customer because it costs much time and energy to

switch my mobile service to another mobile company

.73

It would be too costly for me to switch form this service right

now

.61

Affective

commitment

I have a favorable feeling of my mobile service .68 .90 .90 .69

I remain a customer because of a strong attachment to my

mobile service

.70

I want to remain a customer because I feel a strong sense of

belonging with my mobile service

.73

Repurchase

intention

Next time, when I need this type of service, I will choose this

service provider

.77 .80 .80 .58

I intend to continue using services of this service provider in

the future

.72

I will use more services offered by this service provider in the

future

.79

Word of

mouth

I would gladly forward valuable message I have received from

my service provided to my friends

.83 .88 .87 .69

I mention this service provider to others quite frequently .85

I am proud to tell others that I use this service provider’s

services

.81

Goodness-of-fit v2712 = 534.04, p \ 0.05; GFI = .91; NNFI = .97; CFI = .98; AGFI = .89;

RMSEA = .05, SRMR = .05

* Significant at p \ .01


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mobile services. Finally, the investigation of the relationship between commitment

and loyalty has been under mobile service contexts in previous research (Hur et al.

2010; Raimondo et al. 2008).

In this research setting, participants were drawn from four convenience samples

of undergraduate and graduate business students at a large South Korean

university, employees of a household product firm, and retail employees. Both

businesses were located in a South Korean metropolitan area. A total of 1,012

questionnaire copies were distributed to the four convenience samples, with

440 surveys completed, providing a response rate of just \45 %. Participants

completed the surveys in a mobile setting and were asked to reflect on their

relationship with their usual mobile service provider. The sample distribution was

as follows: gender: male, 55.7 %, female, 44.3 %; age distribution: 19–24, 56.1 %;

25–29, 26.8 %, and over 30, 17.1 %.

4 Data analysis and results

4.1 Test of measurement model

We conducted a confirmatory factor analysis to determine the convergent and

discriminant validity of the measurement scales. The results showed an acceptable

model fit: v(271)2 = 534.04, p \ .05; CFI = .98, GFI = .91, and RMSEA = .05.

Next, we tested for convergent validity by checking that all items significantly (all

t values larger than 10.35) and substantially (all standardized parameter larger than

.50) loaded onto the expected latent construct. All constructs showed satisfactory

levels of extracted average variance (all composite reliability values [.75). We

Table 2 Discriminant validity

Price

value

Quality

value

Emotional

value

Social

value

Affective

commitment

Calculative

commitment

Repurchase

intention

Word

of

mouth

Price value .58

Quality value .17 .59

Emotional value .15 .61 .76

Social value .20 .53 .62 .65

Affective

commitment

.43 .15 .16 .25 .69

Calculative

commitment

-.11 .10 .15 .07 .04 .50

Repurchase

intention

.32 .26 .15 .74 .03 .73 .58

Word of mouth .33 .14 .26 .26 .26 .68 -.05 .69

Mean 3.78 4.48 3.91 3.53 3.59 4.02 3.85 3.43

S.D 1.18 1.36 1.30 1.21 1.26 1.25 1.13 1.24

The numbers in diagonal are AVE


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checked the condition for discriminant validity among constructs as suggested by

Fornell and Larcker (1981). All AVEs were larger than any squared correlation

among constructs, suggesting that discriminant validity was achieved (see Table 2).

4.2 Common method bias

Most research studies agree that the common method variance is a potentially

serious biasing threat in behavioral research, especially with single-informative

surveys (Rodrıguez-Pinto et al. 2011). According to Podsakoff et al. (2003), method

bias can be controlled through both procedural and statistical remedies. We address

procedural remedies by protecting respondent anonymity, reducing evaluation

apprehension, improving item wording, and separating the measurement of the

predictor and outcome variables. We also applied the following statistical remedy.

We used a confirmatory factor-analytic approach to Herman’s one-factor analysis.

All measures of goodness of fit indicated a worse fit for the one-factor model than

for the original measurement model. Therefore, common method bias was

considered non-problematic with this dataset.

4.3 Control variables

The hypotheses above represent our main theoretical predictions. In addition to the

constructs that constitute these hypotheses, several other considerations—brand,

age, and gender—were included to evaluate their effects on our dependent variables.

First, respondents were customers of the three major mobile phone service providers

in South Korea. Following previous studies (e.g., Steenkamp et al. 2003), we

included two dummy variables (brand 1, brand 2) in subsequent analyses to control

for provider-specific effects (e.g., brand image, coverage, reputation, and satisfac-

tion) that could have biased the results (Raimondo and Costabile 2008). Second,

demographic factors such as gender, age, and education played an important role in

influencing repurchase intention and word of mouth (Sullivan and Drennan 2005).

Third, the length of the relationship and the monthly payment for mobile services

were also control variables in our main models (Verhoef et al. 2002).

4.4 Testing the hypotheses

Before testing our hypotheses, we divided subjects into two groups based on the

mean values of calculative and affective commitment and a comparison between

two types of value. In other words, the samples were categorized according to the

relative strength of calculative and affective commitments. The high-calculative-

commitment group (n = 256) had stronger calculative commitment than affective

commitment. The high-affective-commitment group (n = 184) had stronger

affective commitment than calculative commitment. The mean value of calculative

commitment in the former group is 4.34 and that of affective commitment in the

latter group is 4.26.

Then, we estimated a hierarchical regression model. We used mean scores as the

inputs for the constructs. Moreover, in the regression model, we included (a) the


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natural logarithm of relationship age, (b) several control variables (gender, age,

education years, monthly payment, and subscription brand), and (c) four types of

perceived value. To test for the moderating effect of commitment type on the

relationship between service values and loyalty behaviors (repurchase intention and

word of mouth), hypotheses 1–2 were tested using ordinary least square (OLS)

subgroups. A subgroup analysis was adopted because it is the most appropriate

analysis when the moderating variable is categorized (Sharma et al. 1981).

In the regression model with repurchase intention as the dependent variable, after

analyzing all samples, the result indicated that price value (b = .25, p \ .01),

quality value (b = .16, p \ .01), and emotional value (b = .15, p \ .01), affected

repurchase intention, but social value (b = -.05, p [ .01) did not. In the high-

calculative-commitment group, price value (b = .13, p \ .05) and quality value

(b = .18, p \ .05) positively affected repurchase intention, indicating that H1-1 and

H1-2 are accepted. In the high-affective-commitment group, emotional value and

social value did not positively affect repurchase intention, which means H2-1 and

H2-2 are rejected (see Table 3).

Next, the regression model with word of mouth as the dependent variable was

analyzed. In all samples, price value (b = .29, p \ .01), emotional value (b = .13,

p \ .05), and social value (b = .14, p \ .01) positively affected word of mouth.

However, quality value did not (b = -.04, p [ .05). For the high-calculative-

commitment group, price value (b = .18, p \ .01) positively affected word of

mouth, but quality value did not (b = -.03, p [ .05). Therefore, H1-3 is accepted,

and H1-4 is rejected. In the high-affective-commitment group, social value

Table 3 Regression model results (repurchase intention)

All group High affective

commitment

group (n = 184)

High calculative

commitment

group (n = 256)

B (SE) b B (SE) b B (SE) b

Brand 1 -.16 (.11) -.07 .17 (.20) .08 -.04 (.15) -.02**

Brand 2 -.19 (.14) -.07 -.31 (.25) -.12 -.34 (.19) -.12

Payment -.04 (.02) -.10* -.01 (.03) -.04 -.06 (.02) -.17**

Gender -.18 (.10) -.08 -.27 (.16) -.13 -.11 (.14) -.05

Age .00 (.01) .03 -.00 (.01) -.02 .00 (.01) .02

Education -.02 (.05) -.02 -.01 (.07) -.01 .02 (.08) .02

Ln relationship age .15 (.04) .17** .20 (.07) .24** .14 (.06) .16*

Price value .24 (.04) .25** .23 (.06) .28** .13 (.07) .13*

Quality value .13 (.05) .16** .09 (.08) .11 .15 (.06) .18*

Emotional value .13 (.05) .15** .12 (.08) .14 .12 (.07) .14*

Social Value -.05 (.05) -.05 -.08 (.08) -.09 -.03 (.07) -.03

R2(Adj. R2) .21 .21 .18

F value 10.03** 3.31** 4.60**

* p \ .05, ** p \ .01


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(b = .18, p \ .05) positively affected word of mouth, meaning H2-4 is accepted.

Emotional value (b = -.00, p [ .05) did not positively affect word of mouth, so

H2-3 is rejected (See Table 4).

5 Discussion and conclusions

A customer’s loyalty to an organization with which he or she does business is an

important consequence of the relationship. While consumers have to be satisfied as

members of a relational dyad, the commitment they have toward their relational

partner is an important driver of their repurchase intention and willingness to

recommend the services (Fullerton 2011). However, given the previous lack of

discussion on the role of commitment type and service values in the customer loyalty

relationship, this study explores and compares the effects of service values and type of

commitment on repurchase intention and word of mouth. Expanding recent findings

on the mediating role of commitments in customer loyalty (e.g., Cater and Zabkar

2009; Bansal et al. 2004; Fullerton 2011), the results of this research contribute to the

relationship marketing literature by revealing how each type of commitment

influences the relationship between service values and loyalty behaviors.

5.1 Theoretical implications

First, this study shows that both price value and quality value influence repurchase

intention when calculative commitment is stronger than affective commitment. The

Table 4 Regression model results (word of mouth)

All group (n = 437) High affective commitment

group (n = 184)

High calculative

commitment group

(n = 256)

B (SE) b B (SE) b B (SE) b

Brand 1 .03 (.13) .12 .43 (.22) .18 .10 (.16) .04

Brand 2 -.14 (.16) -.04 -.32 (.28) -.10 -.23 (.20) -.07

Payment -.01 (.02) -.02 .00 (.03) .01 -.03 (.03) -.08

Gender -.30 (.11) -.12** -.44 (.18) -.19* -.23 (.16) -.10

Age .02 (.01) .10* .01 (.01) .04 .02 (.01) .10

Education -.04 (.06) -.03 -.04 (.08) -.04 -.02 (.09) -.01

Ln relationship age .06 (.05) .06 .04 (.08) .05 .08 (.06) .09

Price value .30 (.05) .29** .28 (.07) .30** .19 (.07) .18**

Quality value -.03 (.05) -.04 -.00 (.08) -.01 -.02 (.06) -.03

Emotional value .13 (.06) .13* .00 (.09) .00 .18 (.07) .21*

Social value .15 (.06) .14** .17 (.09) .18* .09 (.08) .09

R2(Adj. R2) .18 .23 .11

F value 8.07** 3.76** 3.52**

* p \ .05, ** p \ .01


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results of this study confirm the results of earlier studies (e.g., Lee et al. 2003;

Verhoef et al. 2002), which showed that calculative commitment was closely related

to economic or instrumental factors. However, whereas price value affects word of

mouth, quality value does not. According to Harrison-Walker (2001), the impact of

service quality on word-of-mouth communication varies by industry. Perceived

quality in the mobile service industry could depend on individual users’ time and

amount of cell phone usage, and thus might be irrelevant to their recommendations

to others.

In addition, emotional value positively influences repurchase intention and word

of mouth (Pihlstrom and Brush 2008), although calculative commitment is stronger

than affective commitment. This result could be understood as a phenomenon

specific to the mobile service industry, which provides plentiful information and

entertainment content for various smart devices, leading to an increase in users.

That is, such entertainment contents are becoming critical attributes for a customer–

service provider relationship, as mobile services users for hedonic purposes (Lee

and Murphy 2008).

Second, when affective commitment is stronger than calculative commitment,

emotional value fails to influence both repurchase intention and word of mouth.

Furthermore, social value does not affect repurchase intention, but does influence

word of mouth. Affective commitment produces a stronger link to customer loyalty

than calculative commitment, since affective commitment is a desire-based

attachment by nature, which means customers are loyal because they want to be

loyal (Evanschitzky et al. 2006). Thus, the findings of this study explain that

customers who are affectively committed to a brand are willing to engage in loyalty

behaviors regardless of perceived emotional or social value. Meanwhile, because

affective commitment stems from identification, shared values, and belongingness

(Fullerton 2003), social bonds developed through social interaction are closely

related to affective commitment, which influences personal relationships, including

word-of-mouth communication (Cater and Zabkar 2009).

Finally, price value influenced repurchase intention and word of mouth for both

the high-affective-commitment and high-calculative-commitment groups, even

though different perceived values asymmetrically influenced loyalty behaviors

based on the relatively higher commitment type. This could be because mobile

service, the target of this study, is at a mature stage. Because the price competition

in the mature service stage is intense owing to the small distinctions between

services, price-related factors significantly affect loyalty behaviors.

5.2 Practical implications

The findings provide some practical ideas concerning marketing strategies for the

mobile telecom service industry from a customer value perspective. Since most

existing customers in a mature market are already committed to a service provider

either calculatingly or affectively, customer loyalty is more effectively established

by offering benefits designed to form commitments based on an understanding of

customer motives, rather than indiscriminately providing a diverse range of values

to customers. In situations in which the customer’s type of commitment was not


123

considered, it appeared that diverse service values were effective in improving

loyalty behavior. However, after specifically analyzing the customer’s type of

commitment, this study suggests that a sophisticated customer relationship

management strategy is required, along with a value-offering strategy that addresses

existing customers’ segmentation and the market segment characteristic in terms of

type of commitment.

To put it concretely, it is important to strengthen brand-related factors in the

customer-relationship management strategy in the context of high affective

commitment to create positive word of mouth among consumers. In recent studies,

the customer–brand relationship (e.g., Park et al. 2009; Morrison and Crane 2007), it

has been suggested that a brand’s symbolic and experiential aspects need to be

strengthened to enhance the relationship between product and service. For example,

by creating and supporting brand-connected communities or programs, brands can

make customers feel they belong to a certain group or that they are part of an active

social community, strategies that are effective in encouraging positive word of

mouth.

In addition, even though both price and quality value influence customers’

repurchase intentions when calculative commitment is stronger than affective

commitment, quality value is more effective than price value. This suggests that a

strategy of quality improvement and service differentiation would be more effective

than price discounts to induce repeat purchases. However, our results show that

price value is essential in word-of-mouth effects because quality value fails to

generate positive word of mouth with high calculative commitment. Thus,

marketers should provide their customers with a variety of calling plans for

higher-priced, value-added services, since price value creates stronger loyalty

behaviors (i.e., word of mouth) than do quality value.

5.3 Limitations and future research

Several limitations are inherent in this study. First, it limited service value to four

dimensions: price, quality, emotional, and social value. In previous studies, many

researchers have classified perceived values differently (Sheth et al. 1991; Pihlstrom

and Brush 2008; Sweeney and Soutar 2001). This classification of service

dimensions from various perspectives is a way to generalize the results. Second,

we drew our sample from South Korean mobile users, which may create a

generalization constraint. Therefore, the results of this study need to be validated in

other countries. As is common for such studies, it is possible that the relationships

we found were biased by the omission of inconsiderable variables. Future research

should rely on experimental design that provides more internally valid tests of the

associations of the model. The final limitation concerns the type of study carried

out, since it was based on information obtained at a specific moment in time. Future

research could carry out a longitudinal study to analyze how types of perceived

value and commitment affect loyalty outcomes over time.

Acknowledgment The work was supported by 2012 College of Business Administration Research Fund

in Pukyong National University.


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investigation of the relationship between service values and loyalty behaviors under high commitment

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