cid. cellular phone market. artigo 17-02 trad2 antecedents of customer loyalty: an empirical study...
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Abstract Number:
008-0115
Antecedents of Customer Loyalty: an Empirical Study of Cell Phone
Market
Cid Gonçalves Filho Fumec University
Address: Rua Sevilha 250 / Vila Castela / Nova Lima MG / Brasil / 34.000-000 [email protected]
Phone: 55 31 99815195
Paulo Augusto Gomes-Ferreira Fumec University and OI Telecom
Address: Rua Sevilha 250 / Vila Castela / Nova Lima MG / Brasil / 34.000-000 [email protected]
Phone: 55 31 99815195
Gustavo Quiroga Souki Fumec University
Address: Alameda das Amendoeiras 610 / Ouro Velho / Nova Lima MG / Brasil / 34.000-000
[email protected] Phone: 55 31 99815195
Carlos Alberto Gonçalves
Fumec University Address: Rua Sevilha 250 / Vila Castela / Nova
[email protected] Phone: 55 31 99815195
POMS 19th Annual Conference
La Jolla, California, U.S.A.
May 9 to May 12, 2008
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Antecedents of Customer Loyalty: an Empirical Study of Cell Phone Market
Abstract
The cell phone market is growing in most of the countries. New technologies as 3G and
innovations (as the iPhone®) are bringing new opportunities to firms. Loyalty has been
presented as an important topic to improve profits and performance. But specifically in
this market, the churn of customers remains relatively high, and a representative number
of studies point to satisfaction as the main antecedent of loyalty intentions. The majority
of the previous researches consider externally managed elements as perceived quality
and satisfaction as the main antecedents of loyalty intentions. Thought a survey with
270 respondents, this study includes personal characteristics as inertia and salient
identity as antecedents of loyalty intentions and real loyalty (customer behavior). The
results reveal that most companies fail do create real loyalty, as switching costs (of
service provider) and customers’ inertia presented the strongest impacts on real loyalty.
The conclusions of the present study unfold important recommendations to managers as
practioners.
Keywords: Customer loyalty, satisfaction, value, cell phone
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1. INTRODUCTION
In the past years the mobile telecommunications/cell phone market is going through
great transformations. In this scenery, important processes – such as the break-up of the
industry monopoly, the technological evolution, the new economic context and, above
all, the changes in the offers of mobile telecommunications services – consolidate. The
globalization favored access to new markets, stirring the competition among companies
that didn’t confront each other before. Alongside this phenomenon, society experiences
a revolution of habits, from which consumers – impelled by the technological progress
of telecommunications and computer sciences – increasingly gain access to information
Organizations operating in this market need to adopt marketing strategies that embody a
set of efforts to keep a long-lasting and steady business relationship with its customers –
– in order implement the concept of relationship marketing (MCKENNA, 1993).
According to Morgan and Hunt (1994) relationship marketing is a great upgrade in the
theory and practice of marketing. Gordon (2000) endorses that idea, when he asserts
that it is a derivation of the foundations of traditional marketing, although a very
different.
The importance of studying the mobile telecommunications market is corroborated by
the statistics presented by this industry in last few years (TELECO, 2007). World-
widely, the number of cell phones reached the expressive record of 3.3 billion of mobile
phone accounts in the end of 2007, a growth of 471% compared to 2000. The rate of
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growth of activation of cell phone accounts in the last seven years is impressive. China
continues as the main market, followed by the USA, India, Russia and Brazil.
In Brazil, in 2003 the number of accesses of mobile telecommunications overcame the
fixed telecommunications, confirming a trend observed at other countries. In December
of 2007 Brazil overcame the score of 120 million cell phones, reaching in 2006, a gross
revenue of 140 billion reals, which represents 6.9% of the Brazilian GDP. In this
industry there is a tough competition among cell phone providers, which makes the
safeguarding of customer base an essential concern. Besides the intense competition, the
following considerations about of the cell phone market can be made:
• Brazilian consumers are progressively more savvy and demanding;
• The cell phone market opening - with providers working all over the country;
• The reduction of the prices and subventions cell phones and devices;
• The higher volume of information on competitors, convergence in
telecommunications and high-speed services and technological changes.
In a market with such representativeness, companies should strive to foresee
opportunities and to position themselves properly at the new value system demanded by
customers.
With those facts in mind, the question of the present research emerges:
Which antecedents engender customer loyalty in the mobile telecommunication market?
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2. LITERATURE REVIEW
The theoretical revision ascertains a conceptualization of the main constructs involved
in previous studies of loyalty and relationship, as well as the presentation of models that
aim at explaining the antecedents of loyalty – providing the basis for the generation
hypotheses, and for a proposed model.
LOYALTY
According to Reichheld (1996), the great difference between satisfaction and loyalty
relies on the capacity of the company to link customers’ purchases with their regular
activities. If the achieving of the consumers' satisfaction does not translate into a
certainty that he/she will continue to complete transactions with the organization in
future, it can be affirmed that a loyal customer is characterized per repeating its
purchases regularly, and presents higher odds of disseminating the consumed products
and services, – as well as praising of the brand’s image – among his/her circle of
friends. The loyal consumer will also feel immune to the pressure of competitors, and
will have the capacity to tolerate eventual customer service problems that can arise
occasionally – nevertheless abandoning its chosen provider. (GRIFFIN, 1999).
Loyalty-formation process, according to Oliver (1999), develops in a sequence of
phases where loyalty behavior increases as it moves forward, towards the action phase,
becoming actively loyal. This author criticizes loyalty definitions existent in the
literature, considering them as procedural definitions, in other words, they just describe
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what consumers do, not approaching the psychological meaning of loyalty. Oliver
(1999, p.34) proposes the following definition of loyalty (chart 1):
1 Cognitive Loyalty to information, such as price, characteristics, and so on.
2 Affective Loyalty to a liking: "I buy because I like the product".
3 Conative Loyalty to an intention: "I am committed with the purchase of the product ".
4 Active Loyalty to inertia, associated to overcoming obstacles.
Chart 1- Process of loyalty formation. Adapted from Oliver (1997)
According to Gronroos (1993), among the main antecedents of loyalty found in
consumer behavior literature, the following can be mentioned: satisfaction, trust and
commitment. Satisfaction influences positively future repurchases intentions. Trust
offers a warranty to the consistent and competent behavior of the company,
guaranteeing that the consumer will continue to obtain value in future transactions with
the same supplier. Yet, commitment means that one of the parts involved in the
relationship is somehow motivated to do businesses with the other part.
Bloemer and Kasper (1995) identified two types of loyalty: true loyalty and spurious
loyalty. The main difference among the two concepts is in the fact that true loyalty is
based on a strong commitment with the brand, while spurious loyalty is specifically
based on inertia. In true loyalty, the consumer commits to the brand, so that, every time
he/she needs to buy a certain product, he/she will insist on purchasing one of the same
brand. On the other hand, in the spurious loyalty, the consumer will be able to easily
buy a product from another brand. For that it is enough that consumers feel motivated, –
either by their own or by external factors – to research other options available in the
market.
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In the model used in this study, which will be presented later, two terms will be used to
identify loyalty: intentional loyalty and real loyalty. The intentional loyalty can be
understood as a behavioral intention of maintaining a long-term relationship with the
supplier of services, in other words, the objectives that will stimulate customers to
maintain their loyalty to their cell phone provider in the future. The real loyalty differs
of the intentional loyalty, because it expresses the factors that conveyed to loyalty in the
present, and not necessarily the reasons that will retain customer loyalty in the short–,
and long–run.
SATISFACTION
The conceptualization of immediate satisfaction received several definitions, but it can
be perceived that - for most consumer behavior theorists - this theme converges towards
a common denominator. A brief, however classic, definition about satisfaction –
conceived by Fornell et al, (1996) - defines it as the result of customers’ expectations on
the performance of a product or service. A well known definition of satisfaction
(ENGEL, BLACKWELL and MINIARD, 2000, p.161) is that it would be "a post-
purchase evaluation that a chosen alternative at least meets, or, exceeds the
expectations". Therefore, we can realize that satisfaction is reached when the selected
alternative meets previous expectations related to this option.
Another well known definition of satisfaction conveys that this behavior would be the
answer to the need of fulfilling expectations, in other words, “the judgment that a
characteristic of the product or service did offer – a pleasant level of relative
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contentment to the purchase – including higher or lower levels of contentment”
(OLIVER, 1997, p.13).
In order to measure this performance, Engel, Blackwell and Miniard (2000) depict
performance indicators, divided into three categories of expectations, for products
and/or services:
• Positive disconfirmation: performance is better than expected.
• Simple confirmation: performance equal to expectations.
• Negative disconfirmation: performance is worse than expected.
Relationship between Satisfaction and Loyalty
Over the past two decades, much research has been done on the main effects of
satisfaction on customer loyalty. Satisfaction is considered a key-factor in long-term
customer-company relationships (JAP, 2001). Nevertheless, Reichheld (1996) indicates
that just satisfaction is not enough for obtaining long-term results. Satisfaction is an
important step for obtaining customer fidelity. However, it’s becoming less important,
as fidelity can be reached through other mechanisms, such as personal determination,
social links, stiffening competition, and barriers to change. For Oliver (1999)
satisfaction and loyalty are intimately related, yet –, despite the fact that loyal customers
are usually more satisfied than the not loyal ones – there is a belief that satisfaction, by
itself, doesn't guarantee loyalty. Oliver (1999) affirms that satisfaction affects loyalty
when it becomes frequent and accumulative, where individual and successive episodes
of satisfaction form – with other variables – a position of long-term preference for the
brand.
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A classification that places satisfaction as an important antecedent for loyalty – the
ACSI (American Customer Satisfaction Index), proposed by Fornell et al, (1996) –, was
used as one of the references to develop the research model. Satisfaction, for its turn,
has three antecedents: perceived quality, perceived value and customer expectations.
The first determinant of satisfaction is perceived quality, which is the evaluation
conducted by the market served by a recent purchase experience, which is expected to
exert a positive and direct effect over the overall satisfaction. The ACSI model is
presented in figure 1:
Figure 1 – ACSI Model (American Customer Satisfaction Index)
Source: Fornell et al, (1996)
Quality Perceiveid
by the Customer
Customer Expectations
Value Perceiveid
by the Customer
Overall Customer
Satisfaction
Loyalty
Complaints
-
+
+
+
+
+
+ -
+ ANSI
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PERCEIVED QUALITY
As described previously, the perceived quality is directly associated to satisfaction, in
other words, it is the result of a comparison process between consumer expectations and
perceptions of the service performance (PARASURAMAN, ZEITHMAL and BERRY,
1985). Whence, the study of the perceived quality is linked to researches on satisfaction,
since it uses similar reasoning’s based in the disconfirmation of performance for service
expectations. According to conclusions of Parasuraman, Zeithmal and Berry (1985), the
main difference among those two constructs is that satisfaction would be the result of
the evaluation of a specific transaction done by the consumer, while perceived quality is
usually considered as an attitude; in other words, the consumers’ overall evaluation of a
service offer.
PERCEIVED VALUE
Like perceived quality, perceived value is described in the ACSI model as an antecedent
of satisfaction.
Perceived value is considered to be the consumer's overall assessment of the
relationship among the perception of quality received and the perception of cost
disbursed (KOTLER, 2000). Perceived value indicates that – through the eyes of the
consumer – an offer has relevant attributes of value resulting from the difference
between the expected total value (benefits) and total costs. Attributes are concrete
descriptions regarding the intrinsic and extrinsic characteristics of a certain product or
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service. Therefore, perceived value is the value conferred by customers to a product or
service, based on the association among the benefits that it will bring – due to its
attributes and the perceived costs for its acquisition – in comparison to the competition
(ZEITHAML, 1998). Galley (1996), succinctly conceptualized value as the result
between perceived quality and perceived costs. Already Woodruff (1997) sees value as
being the customer's perception about the preferences and evaluations of the product
attributes, of the performance of those attributes and the consequences originated by
use. Once the perceived costs are associated with the perceived value, a brief reflection
on the theme is necessary.
PERCEIVED COSTS
From a basic perspective, cost is more directly associated to the stages of evaluation of
alternatives and choice of the purchase decision process – considering that situations
involving more expensive, complex products and when customers have difficulty
understanding products – will result in higher risk levels. As a consequence, lower
perceived costs will result in higher customer satisfaction levels (SOLOMON, 2002).
Although being an essential part of the perceived risk, the sole existence of uncertainty
doesn't determine the occurrence of risk, once it is directly related to the level of loss
(consequence) derived from the choice made by the consumer. On the other hand,
Solomon (2002) affirms that perceived risk not only depends on traits as the nature of
the product, but also on its category, its complexity or innovativeness, on the
characteristics of the consumers, and on the circumstantial factors involved in the
purchase. Afterwards, several authors identified additional types of perceived risk.
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Solomon (2002) estimates that five kinds of perceived risk, which are: financial, social,
psychological, functional and physical risk.
COMMITMENT
This construct, despite of being a relatively new variable in the relationship marketing
context, is an essential concept to understand the loyalty-formation process, since it is
related to explicit or implicit signs that carry on expectations about the relationship's
continuity among the partners (MORGAN and HUNT, 1994).
For these authors, commitment is obtained when customers believe that maintaining a
relationship with a company is so important and gratifying, that they should spare no
effort to continue it. The committed consumer really cares to keep up a commercial
trade with its supplier, and he/she resists to the offers of the competition. Prado and
Santos (2003), affirm that customer commitment is the axis of the relationship
marketing, once the act of committing is a condition that foments a permanent desire to
continue with the same supplier.
Commitment and Loyalty
Commitment is considered a significant antecedent of loyalty, as from the moment that
it translates into “a permanent desire to maintain an important relationship” (MORGAN
& HUNT 1994: p.20). This statement is endorsed by Thurau, Gwinner and Gremler
(2002), in their Integrative Model of Relationship Marketing Outcomes, which includes
committal in the loyalty formation process. The model is presented in figure 2, bellow:
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Figure 2 – Integrative Model of the Determinants of Key Relationship Marketing Outcomes
TRUST
Trust has been defined in countless ways and by different perspectives. Several
disciplines, including sociology, psychology and economy have been determined to
conceptualize this construct. Morgan and Hunt (1994), affirm that trust exists “when
one party has confidence in an exchange partner’s reliability and integrity”. In literature
the construct trust is cited as a strong inducer of commitment, once it is a pledge of the
consistent and competent performance of the company – guaranteeing safety, lowering
the risk of the purchase, and reducing uncertainties (MORGAN and HUNT, 1994).
Besides, the higher the trust, the higher the odds of customers continuing to maintain
and to increase value of future business transactions with the same supplier;
contributing to the continuity of the relationship and creating loyalty feelings
(GANESAN, 1994).
Confidence
Benefits
Social
Benefits
Special Treatment Benefits
Commitment
Satisfaction
Customer Loyalty
Word of Mouth Comunication
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Relationship among Trust and Commitment
Garbarino and Johnson (1999) explain that the level of trust increases as the parties
(customer– supplier) get involved in riskier transactions, being expected that trust will
increase the probability that both parties will commit to the mutual relationship. One of
the models that reinforce the connection between trust and commitment is the model of
the key mediating variable (KMV) model of relationship marketing developed by
Morgan and Hunt (1994). To these authors, what determines the success of the
relationship marketing strategies is the existence of commitment and trust, since these
concepts work to preserve long-term relationships. That model is presented in figure 3:
Figure 3 – Model of key mediating variables of relationship marketing (KMV).
Source: Morgan and Hunt (1994).
Cost ot termnating
the
Relationship
Benefíts from the
Relationship
Shared
Values
Communication
Confidence
Commitment to the
Relationship
Uncertainty
Cooperation
Propensity to Abandon the
Relationship
Acquiescence
Functional
Conflict
Opportunist
Behaviour
+
+
+
+
+
- -
+
+
+
-
+
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SALIENT IDENTITY
Salient identity is a construct linked to the individual values, therefore is essential in
the study of loyalty as it investigates how personality and the psychological traits
influence purchase decisions (THURAU et al, 2002). To these authors identity is
composed of predisposed attributes in which one individual differs from another,
providing experiences and purchase behaviors related to the personality, personal
values, and psychological characteristics one person. The identities are organized in a
structured way, where one becomes more important than the other. As consequence,
there is a tendency and a higher propensity to adopt behaviors associated to that salient
identity.
Engel, Blackwell and Miniard (2000) argue that when consumers buy certain products
they expect to acquire not only functional or tangible attributes, but also a good
experience – an emotional answer of the compatible use with its identity. That identity
conveys the goals that motivate people, and expresses what defines their purchase
behavior, hence knowing it becomes a useful tool in the understanding of the reasons
that bring a consumer to make a purchase and to adopt purchase behaviors that
distinguish one person from another.
INERTIA
Inertia can be defined as the convenience inherent in a repetitive behavior of purchasing
a brand without resorting to a complex decision–making process. This is a concept of
great importance for companies, since most products require low involvement. For the
inert consumers the process of decision-making process is less complex, as it doesn’t
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requires an active search of information and has low purchase involvement. Hence, the
process of habitual purchase decision can be observed by two focal points: loyalty to the
brand and/or company, and inertia (ENGEL, BLACKWELL and MINIARD, 2000).
Hence, the influence of salient identity on inertia remains little explored in the studies,
but there is a suspicion that, somehow, the individual personality models his/her
behavior and purchase decisions.
Inertia and Loyalty
OLIVER (1999) affirms that inertial loyalty is the last phase of loyalty process, whereas
the conative loyalty becomes an attitude, endorsing the individual's commitment in
repurchasing the brand. The predisposition present in conative loyalty becomes an
attitude, and the purchase decisions are automatic, without much reflection, turning it
into a simple process. That inertial state turn repurchases into a frequent process, and
places customers on a situation where they make automatic decisions related to their
favorite brand without a lot of reflection, disregarding competitive offers. However,
successive episodes of dissatisfaction, such as a decrease in the product’s performance,
the removal of a benefit, or even the shortage of a product can negatively affect loyalty
inertia.
SWITCHING COSTS
Burnham, Frels and Mahajan (2003) consider that switching costs, also known in the
literature as change barriers, is term used to describe all kinds of obstacles prevent the
customer from switching suppliers. The occurrence of costs in the process of change
discourages the individual to persevere. Commercial relationships incur into a
diversified array costs – gathering several kinds all the expenses possible –, turning the
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change of service supplier into a costlier matter. Hence, the effects of the switching
costs in loyalty-formation process have been studied, as it positioned as a construct that
discourages company switching.
Burnham, Frels and Mahajan (2003) developed a typology to measure switching costs
that have higher influence on the consumers. For these authors, the loyalty influenced
by the switching costs is called passive loyalty, since the customer doesn't repeat the
purchases stimulated by satisfactory experiences – but due to the distress caused by the
barriers to the change of supplier. In these authors' conception, the switching costs are
divided in the following way: costs of economic risk, of evaluation, of learning, of
initialization, of benefits loss, of monetary losses and of relationship loss.
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3. THEORETICAL MODEL AND HYPOTHESIS
Based in the models of Fornell, Johnson, Anderson, Tea and Bryant (1996), Thurau,
Gwinner and Gremler (2002), Morgan and Hunt (1994), – as well as on the proposal of
Burnham, Frels and Mahajan (2003), Engel, Blackwell and Miniard (2000), and Oliver
(1999) – among other authors, we recommend the following hypothetical model of
research (figure 4):
Figure 4 – Structural model of loyalty construction process.
Quality
Costs
Switching Costs
Value
Satisfaction ç
In e rtia
Salient Identity
Trust
Commitment Real loyalty
Intentional Loyalty
H2
H9
H5 H3
H4
H6
H7
H8
H1
H12
H14
H15
H13 H11
H10
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Therefore, the following hypotheses were elaborated (chart 2):
Dependent Independent Hypothesis
Value <-- Quality 1
Satisfaction <-- Quality 2
Trust <-- Quality 3
Value <-- Costs 4
Satisfaction <-- Value 5
Inertia <-- Costs of change 6
Inertia <-- Salient identity 7
Real loyalty <-- Inertia 8
Intentional loyalty <-- Inertia 9
Intentional loyalty <-- Satisfaction 10
Real loyalty <-- Satisfaction 11
Commitment <-- Trust 12
Commitment <-- Satisfaction 13
Real loyalty <-- Commitment 14
Intentional loyalty <-- Commitment 15
Chart 2 – Model’s hypothesis
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4. METHOD
From the standpoint of its objectives the research is descriptive, because it seeks to
describe the factors that determine or contribute to the occurrence of the phenomena and
it deepens the knowledge of the reality (GIL, 1991). From the viewpoint of its nature
this investigation is considered as an applied research, because it aims to generate
knowledge for practical application intended for the elucidation of specific problems.
The research was organized in two stages. The first, characterized by the exploratory
phase, made the use of a qualitative approach, applying two main methods: literature
revision, and in–depth interviews.
To develop the second phase, a survey was conducted in Belo Horizonte, capital Minas
Gerais, the second most populous and fourth largest state by area in the federation,
according to a recent study of IBGE (Brazilian Institute of Geography and Statistics),
Belo Horizonte is the fifth richer city of the country, representing 1.32% of the total of
the wealth produced in Brazil. The sample was composed by 270 respondents, obtained
through personal data, collected during 2007.
A survey was conducted with post-pay consumers of cell phone market, once it is the
modality with higher profitability, and for this reason, it is a constant target of
relationship programs. Thereunto, we conducted a pre–test with 50 respondents, in
order to prove the efficiency of the investigation.
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5. EXPLORATORY PHASE
The exploratory analysis of the data methodologically followed a series of stages that
aimed to verify presuppositions and consistence of data, and to check the reliability and
validity of the measurements and scales, creating a basis to test the proposed
hypotheses. Following, the results of each one of these stages will be demonstrated.
Treatment of Missing Values
After, we pursued to identify underlying processes to the emergence of absent data
(HAIR et al, 1998). In this study, absent answers were not observed in the database.
Therefore, no treatment for this problem was required.
Outliers
Intending to discover possible multivariate outliers, (cases with a very peculiar
combination of answers) we used the Mahalanobis distance (D2) (KLINE, 1998). Under
the supposition of multivariate normality, the value D2 is distributed as a qui-square
with k (number of variables) degrees of freedom, making feasible to classify the
multivariate outliers, in case the associated probability D2 gets to be lower than 0.1%
(TABACHNICK and FIDEL, 2001). Using this procedure in seven successive stages of
classification and exclusion, 40 multivariate outliers were detected. Considering the
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great proportion of extreme multivariate cases, we preferred to retain all the cases for
the comparison of results with, and without, outliers.
Analysis of Normality
A normal univariate and multivariate distribution is essential for the statistic techniques
used in this study. To evaluate the parameters of normality of the data, we used
asymmetry and kurtosis normality tests. Using Kolmogorov-Smirnov test, we identified
that no variable could be considered in group, univariate normal. Furthermore, the
significant values of the deviations unable transformations to produce noticeable results
(Hair et al, 1998). Indeed, the data examined in this study does not reveal univariate
normality patterns. Naturally, the violation of the multivariate normality should be
considered, because the multivariate normality undertakes the normality of the
individual variables.
Linearity Analysis
In first instance we aimed to verify the linear adjustment among the variables, through
significant linear associations and through the verification of the significance of the
relationships. We obtained a matrix with 1.507 (72. 45%) of significant correlation to a
5% of bicaudate significance, in order to show a good linear adjustment among the
variables.
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6. VALIDITY AND RELIABILITY OF THE MEASURES
Dimensionability Analysis
Firstly a factor analysis of the items by construct was executed, in order to verify its
dimensionability. In a general way, we can say that the scales present results coherent
with the suggested unidimensionality premise, excepting the construct quality, which
reveled to be composed by five different, albeit related, dimensions. This fact demanded
a differentiated treatment of this construct when doing the research model estimate.
Reliability Evaluation
We observed that the constructs presented alpha values above the suggested limits of
0.8 in a great many of the variables, while constructs also presented moderate values in
the 0.7 – 0.8 strip. The construct Quality 5 (quality of services) presented alpha values
below the minimum limits, suggesting that this construct should be ignored in the
subsequent stages of reliability evaluation. Finally, it was detected that the construct
Real Loyalty presented low value alpha, which could be anticipated due to the
expressive difference in the variability of the items. The table 1 and table 2 show the
reliability measurements:
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Table 1 – Reliability of Constructs CONSTRUCTS and INDICATORS AVERAGE1 VARIANCE2 CORREL.3 R24 ALPHA DEL.5
Quality 1: Attendance (customer service) (customer service)
α 1=0.81 α 2=0.81
Q11.qual7 18.49 45.11 0.48 0.24 0.82
Q12.qual8 19.49 36.76 0.63 0.45 0.75
Q13.qual9 19.60 35.27 0.76 0.62 0.69
Q14.qual10 20.28 36.60 0.63 0.48 0.76
Quality 2: Equipments α 1=0.80 α 2=0.81
Q7.qual3 8.39 3.23 0.68 0.46 .(a)
Q8.qual4 8.19 4.13 0.68 0.46 .(a)
Quality 3: Coverage α 1=0.79 α 2=0.79
Q5.qual1 7.79 4.59 0.66 0.43 .(a)
Q6.qual2 7.87 3.83 0.66 0.43 .(a)
Quality 4: Status α 1=0.79 α 2=0.79
Q15.qual11 5.94 7.81 0.66 0.43 .(a)
Q16.qual12 6.81 5.67 0.66 0.43 .(a)
Quality 5: Services α 1=0.38 α 2=0.39
Inv_Q9.qual5 3.37 7.52 0.24 0.06 .(a)
Q10.qual6 7.46 4.76 0.24 0.06 .(a)
Costs α 1=0.79 α 2=0.79
Q17.cust1 32.03 148.88 0.32 0.12 0.80
Q18.cust2 32.16 141.81 0.46 0.23 0.77
Q19.cust3 31.70 139.06 0.56 0.43 0.75
Q20.cust4 31.58 128.17 0.66 0.55 0.73
Q21.cust5 30.93 142.27 0.46 0.26 0.77
Q22.cust6 34.13 134.39 0.57 0.44 0.75
Q23.cust7 34.19 134.30 0.61 0.49 0.74
Value α 1=0.85 α 2=0.85
Q24.val1 23.42 70.88 0.72 0.62 0.80
Q25.val2 23.32 70.06 0.79 0.69 0.78
Q26.val3 23.30 73.99 0.71 0.54 0.80
Inv_Q27.val4 25.75 80.00 0.47 0.22 0.87
Q28.val5 23.54 79.21 0.61 0.41 0.83
Costs of change α 1=0.70 α 2=0.70
Q29.custm1 22.90 87.43 0.36 0.22 0.69
Q30.custm2 22.64 76.05 0.58 0.36 0.60
Q31.custm3 23.26 71.00 0.55 0.32 0.61
Q32.custm4 23.22 79.00 0.46 0.27 0.65
Q33.custm5 24.11 90.63 0.34 0.12 0.69
Salient identity α 1=0.75 α 2=0.75
Q35ident.1 22.02 82.51 0.52 0.34 0.70
Q36.ident.2 21.90 73.79 0.68 0.57 0.65
Q37.ident.3 22.16 76.66 0.63 0.49 0.67
Q38.ident.4 22.84 81.94 0.45 0.22 0.73
Q40.ident.6 22.55 88.57 0.33 0.14 0.77
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Observations: 1) scale average, in case the item is excluded; 2) scale variance, in case the item is excluded; 3) Average inter-item correlation revised; 4) multiple R2; 5) low alpha value limit, in case the item is erased. α 1 is the value of the alpha estimates obtained for the rough data. α 2 is the alpha value obtained thru standardized estimates. Inv means that the indicator was inverted before the alpha value was calculated.
Table 2 – Reliability of Constructs (continued)
CONSTRUCTS & INDICATORS AVERAGE1 VARIANCE2 CORREL.3 R24 ALPHA DEL.5
Inertia α 1=0.79 0.79
Q41.in1 20.73 70.19 0.55 0.32 0.76
Q42.in2 19.66 71.68 0.56 0.37 0.76
Q43.in3 19.47 67.68 0.65 0.44 0.73
Q44.in4 20.37 66.90 0.63 0.43 0.73
Q45.in5 19.84 77.17 0.47 0.29 0.78
Trust α 1=0.92 0.92
Q46.conf1 29.01 68.61 0.76 0.59 0.90
Q47.conf2 28.33 73.26 0.76 0.60 0.90
Q48.conf3 28.17 69.52 0.77 0.60 0.90
Q49.conf4 28.23 66.90 0.85 0.75 0.88
Q50.conf5 28.02 72.45 0.80 0.69 0.90
Commitment α 1=0.85 0.85
Q51.comp1 19.28 85.23 0.51 0.32 0.86
Q52.comp2 20.57 74.79 0.67 0.47 0.82
Q53.comp3 20.43 74.32 0.69 0.50 0.81
Q54.comp4 21.23 73.00 0.69 0.56 0.81
Q55.comp5 21.19 69.43 0.75 0.64 0.80
Satisfaction α 1=0.94 0.95
Q54.satisf1 34.24 121.16 0.77 0.68 0.94
Q55.satisf2 33.57 125.01 0.87 0.78 0.93
Q56.satisf3 34.58 124.50 0.79 0.65 0.94
Q57.satisf4 33.13 126.45 0.84 0.75 0.93
Q58.satisf5 33.51 124.26 0.87 0.82 0.93
Q59.satisf6 33.57 125.76 0.87 0.77 0.93
Intentional loyalty α 1=0.89 0.89
Q60.leal1 40.05 213.61 0.82 0.71 0.86
Q61.leal2 39.96 219.66 0.80 0.83 0.86
Q62.leal3 39.91 225.54 0.75 0.61 0.87
Q63.leal4 40.23 216.48 0.81 0.83 0.86
Q64.leal5 40.01 225.32 0.69 0.50 0.87
Inv_Q65.leal6 41.96 255.67 0.30 0.12 0.91
Q66.leal7 40.02 246.54 0.44 0.24 0.90
Q67.leal8 40.51 226.99 0.74 0.58 0.87
Real loyalty α 1=0.49 0.66
q4.Time 10.15 7.81 0.39 0.17 0.30
inv_q70a 12.27 10.58 0.50 0.25 0.46
Inv_q70b 5.02 2.48 0.45 0.26 0.37
Source: Research data Observations: 1) time scale, in case the item is excluded; 2) scale variance, in case the item is excluded; 3) Average inter-item correlation revised; 4) multiple R2; 5) low alpha value limit, in case the item is erased. α1 is the alpha value of the estimates obtained
26
for the rough data. α2 is the alpha value obtained thru standardized estimates. Inv means that the indicator was inverted before the alpha value was calculated.
As the scales that measured the constructs presented reliable results, from the internal
consistency perspective (CHURCHILL and IACOBUCCI. 2003), we proceeded the
evaluation of the validity of the measurements. A first component of the construct
validity is the convergent validity, which indicates if strong enough correlations exist
among the different measures of the same construct, in order to attest that such
measures are reflexes of the same latent construct. Bagozzi et al, (1991) suggest using
the Confirmatory Factorial Analysis to evaluate the convergent validity of the
constructs.
Convergent Validity
The validity of the construct has as second component the discriminant validity, which
is obtained when scales conceived to measure different constructs measure empirically
different latent variables (NUNNALY and BERNSTEIN. 1994), based on the
significance criteria of the factorial loads of Bagozzi et al, (1991), all indicators
presented convergent validity with its constructs. It is observed that most of the
measures reached appropriate baselines. Seeking to maintain the measurement
parsimony of the model, we preferred to exclude measures that presented less than 40%
of shared variance with its indicators. An exception was made to real loyalty construct,
wherein considering the use of measures especially conceived for this study, and
assuming that the indicators are valid measures of the construct, we preferred to
maintain all indicators in the final measurement model.
27
Discriminant Validity
We employed a method suggested by Fornell and Larcker (1981) to evaluate the
discriminant validity. These authors suggest comparing the average variance extracted
from the constructs’ indicators with the shared variance among the theoretical
constructs (R2). Therefore, if two scales, – conceived to measure different constructs –
share more variance among each other, than [what they share] among its indicators –
they would incur into a violation of the discriminant validity. All the constructs’ pairs
tested showed discriminant validity; therefore, we can attest that the additional
constructs yet presented this other component of the construct validity.
7. Test of the Research Model
The Structural Equations modeling was used to test the model due to its capacity to
work with measurement problems and multiple relationships among constructs with just
one tool (TABACHNICK and FIDEL, 2003). However, we should emphasize that this
technique needs relatively big samples (there is: a higher number of respondents), and
that increases: a) as the violation of normality is observed; b) as the model gets more
complex.
Such conditions implicate in the increase of the chi-square statistics and the consequent
penalization to the adjustment of the model (KLINE. 1998). Therefore, the indicators
were randomly aggregated to allow the use the reported modeling. In this model 24
observable variables were attained, generating a covariance matrix comprising 300 non–
redundant observations (24x[25]/2). Thus, the number of observations in the sample
28
was quite close to the number of observations in the covariance matrix. Considering
such specifications, we started to test the model using the maximum verisimilitude
method developed by Bastin and Gevers (1985). The results of the proposed model are
presented in figure 5:
29
Figure 5 – Theoretical Model: theoretical relations proposed and empirical values of the relations
The indicators of adjustment of the model are presented in Table 4:
INDEX VALUE DESIRABLE
Absolute adjust
Chi-square (χ2) 582.04 N.A
Degrees of freedom (gl) 232.00 N.A
Probability <0.001 > 0.05
RMSEA 0.07 < 0.08
Probability (RMSEA < 0.08) 0.90 > 0.90
GFI 0.85 >0.90
Incremental adjust
AGFI 0.80 >0.90
CFI 0.91 >0.90
NFI 0.85 >0.90
NNFI (Tucker Lewis Index) 0.89 >0.90
Parsimonious Adjust
χ2/gl 2.51 < 4
PGFI 0.66 N.A
PNFI 0.72 N.A
Table 4 – Adjust Indicators of the model with all the constructs Source: Research data Notes: The column value presents the estimates the adjustment of the model, while the desirable column
corresponds to the limits accepted in the literature (HAIR et al, 1998). N.A.: means non–applicable.
Source: AMOS 4 Exit.
Custos Custos
Qualidade Qualidade
Valor R 2 =0,70 Valor
R 2 =0,70
Identidade Saliente
Identidade Saliente
Custos de mudan ç a
Custos de mudan ç a
In é rcia R 2 =0,24
R2
In é rcia R 2 =0,24
R2
Satisfa ç ão R 2 =0,88
Satisfa ç ão R 2 =0,88
Lealdade intencional R 2 =0,82
Lealdade intencional R 2 =0,82
Lealdade real
R 2 =0,07
Lealdade real
R 2 =0,07
Confian ç a R 2 =0,81
Confian ç a R 2 =0,81
Comprometi mento
R 2 =0,39
Comprometi mento
R 2 =0,39
0,66***
0,23**
0,98*** 0,90***
- 0,06 NS
0,10 NS
0,45***
0,27*
0,73***
0,20***
0,18***
0,48***
- 0,04 NS
0,05 NS 0,16 NS
0,18***
χ 2 = 584,04 NFI=0,85 G.l = 232 RFI=0,83 χ 2 / G.l = 2,52 IFI=0,91 GFI = 0,85 TLI=0,89 AGFI = 0,66 CFI=0,91 RMSEA=0,07 HOELTER (5%)=125
Custos Costs
Qualidade Quality
Valor R 2 =0,70 Value
R 2 =0.70
Identidade
Saliente Salient
Identity
Custos de mudan ç a
Switching Costs
In é rcia R 2 =0,
24
In ertia R 2 =0.24
R2
Satisfa ç ão R 2 =0,88
Satisfaction R 2 =0.88
Lealdade intencional R 2 =0,82
Intentional Loyalty i R 2 =0,82
Lealdade real
R 2 =0,07
Real Loyalty R 2 =0.07
Confian ç a R 2 =0,81
Trust R 2 =0.81
Comprometi mento
R 2 =0,39
Commitment
R 2 =0.39
0.66***
0.23**
0.98*** 0.90***
- 0.06 NS
0.10 NS
0.45***
0.27*
0,73***
0,20***
0,18***
0,48***
- 0,04 NS
0,05 NS 0.16 NS
0.18***
χ 2 = 584,04 NFI=0,85 G.l = 232 RFI=0,83 χ 2 / G.l = 2,52 IFI=0,91 GFI = 0,85 TLI=0,89 AGFI = 0,66 CFI=0,91 RMSEA=0,07 HOELTER (5%)=125
30
The statistical test was not capable of not rejecting the null hypothesis of equality
among the covariance matrixes of the collected data –, estimated through the proposed
model (p-value equals to zero). Therefore, the absolute adjust didn't exist. The RMSEA
value is lower than 0.08, indicating an acceptable adjustment of the model. The
incremental indexes were higher than 0.8 (NFI = 0.85, TLI = 0.89), what is advisable
according to HAIR et al, (1998). The other main incremental adjust indexes (GFI, NFI,
and CFI) come near to the cut–off value of 0.90. Another result that contributes to the
acceptance of the model is the normalized chi-square (²/gl), whose value should be
under 3.0. As the result was 2.923, we can conclude that the model is acceptable.
DEPENDENT INDEPENDENT PAT REG T VALUE SIG
Value <-- Quality 0.66 0.93 6.69 0.00
Value <-- Costs -0.23 -0.28 -2.58 0.01
Satisfaction <-- Quality 0.98 1.43 8.86 0.00
Trust <-- Quality 0.90 1.20 10.97 0.00
Satisfaction <-- Value -0.06 -0.06 -0.67 0.50
Inertia <-- Costs of change 0.10 0.09 1.02 0.31
Inertia <-- Salient identity 0.45 0.40 4.67 0.00
Commitment <-- Trust 0.16 0.17 1.07 0.29
Commitment <-- Satisfaction 0.48 0.46 3.16 0.00
Intentional loyalty <-- Satisfaction 0.73 0.75 12.63 0.00
Real loyalty <-- Satisfaction -0.04 -0.01 -0.39 0.70
Real loyalty <-- Inertia 0.27 0.10 2.04 0.04
Intentional loyalty <-- Inertia 0.18 0.20 3.71 0.00
Real loyalty <-- Commitment 0.05 0.02 0.44 0.66
Intentional loyalty <-- Commitment 0.20 0.21 3.51 0.00
Value <-- Quality 0.66 0.93 6.69 0.00
Value <-- Costs -0.23 -0.28 -2.58 0.01
Satisfaction <-- Quality 0.98 1.43 8.86 0.00
Trust <-- Quality 0.90 1.20 10.97 0.00
Satisfaction <-- Value -0.06 -0.06 -0.67 0.50
Inertia <-- Costs of change 0.10 0.09 1.02 0.31
Inertia <-- Salient identity 0.45 0.40 4.67 0.00
Table 5 - Result of the hypothesis of the proposed model Source: Research data
31
8. RESULTS DISCUSSION
According to the premises of the ACSI model, the first hypothesis – relating the impact
of perceived quality on perceived value, presenting a standardized Beta of 0.66, – was
confirmed. As the perceived value is the consumers´ correlation between benefits and
perceived costs, we can consider that better value perceptions can be obtained through
the increase of the perceptions of perceived quality, as suggested Fornell et al, (1996).
The proposed hypothesis 2 – based in the ACSI model (Fornell et al, 1996), which
considered quality as an important antecedent of satisfaction, was confirmed, presenting
a standardized coefficient of 0.98. This result corroborates to the results of Fornell et al,
(1996), from the contributions of ACSI. Therefore, we identified a convergence
between theory and the found result.
Hypothesis 3, which aimed at verifying the impact of perceived quality on trust, was
confirmed, presented an average weight of 0.81. This hypothesis corroborates the
studies of Thurau, Langer and Hansen (2001), which describes that quality and trust are
mutually dependent. The confirmation of this hypothesis also supports the theoretical
suppositions of Boulding et al, (1993), alleging that when a service provider operates to
increase quality – trust also tends to increase – allowing the consumer to make safe
predictions about the future behaviors of that particular company.
The hypothesis 4 was confirmed, once the impact of perceived costs on perceived value
presented a positive average coefficient of +0.23, with p<0.001. The most important
attributes of the construct perceived costs, identified in the research, were (average
32
answers in a 0–to–10 scale): consumers’ psychological costs of not receiving responses
to solicitations (8.0), risks of receiving poor quality services (7.5), and the risks
involved the quality of connections (7.2). We can suggest, therefore, that solving
complaints engenders a higher impact on the costs perceived by customers. Since the
psychological friction of a solicitation not assisted it was mentioned as the main
offender of this construct.
The rejection of the hypothesis 5, which proposed the relationship between the
perceived value and satisfaction, can be related to the equivalence of the prices
practiced among the providers. As observed in the qualitative interviews, there is a little
difference among the providers of mobile telecommunications in matters related to
perceived equivalent cost. This situation is favored by the performance of the industry
competitors’ due to the linearity of the practiced prices. Therefore, the customer incurs
little risk in terms of financial expenditure when he/she switches from one provider to
another, suggesting that the true competitive differential is represented by quality of the
services rendered to the customers.
Hypothesis 6 – that aimed to measure the impact of the switching costs on inertia – was
also rejected. Once salient identity, hypothesis 7, as the antecedent main of inertia
(0.45) was taken into account. The strengthening of the connection among these two
constructs confirms the salient identity studies developed by Engel, Blackwell and
Miniard (1995), which affirms that the individual's personality models his/her purchase
behavior, especially the risk–averted ones, and those with the intention of remaining in
the same course of action.
33
It can also be verified in the obtained results, what the main antecedents of the
commitment the trust are (? = 0.16) and satisfaction (? =0.45). Therefore, what the
hypotheses 12 and 13, correlate, respectively, trust and satisfaction with the
commitment, are confirmed, reinforcing the studies of Thurau, Gwinner and Gremler
(2002). As the construct satisfaction is the one that exerts most influence on the
commitment – in this model –, we observed in order to retain committed consumers,
companies should offer quality, since this construct strongly influences customer
satisfaction. Consequently, quality perception should be monitored as a way of
obtaining the customer's commitment to the brand.
Loyalty Antecedents
The hypotheses 8 and 9, aimed to identify the impacts of inertia on real loyalty and
intentional loyalty were proven (0.27, and 0.28, respectively). Despite of the fact that
intentional loyalty had a higher influence of the constructs satisfaction (0.73), and
commitment (0.20), confirming the hypotheses 10 and 15 – it can be inferred that real
loyalty, in other words – the reasons that take the consumers not to switch providers – is
more strongly influenced by inertia (0.27) than by satisfaction or commitment (0.05).
We can consider, therefore, that inertia is the cause that the loyalty to provider is
reached without a complex decision-making process. This statement is proven by the
qualitative research data, showing that most interviewees affirmed that remain attached
to their provider for one or two basic reasons –, such as the wide coverage, modern
equipments, favorable financial conditions or special treatment –, which discourage
them to seek the competition. When some of these factors cease to be offered, the state
of inertia state tends break, indicating levels of opportunistic behavior. In other words,
34
the comfort zone where the consumer resides, motivated by some essential attribute,
makes him/her loyal to its cell phone provider.
Analysis of the Alternative Model
Taking into account a model construction strategy (HAIR et al, 1998), we tested a
model that aimed to alter the results of the original model, according to the predictive
contribution of the constructs (statistical significance). After observing the modification
indexes and some theoretical and practical considerations, the following model (figure
6) was obtained.
Figure 6 – Alternative Model. Source: research data
Relationships, unpredicted in the original model, but obtained thru empiric data
evidences can be observed. Also, indexes of adjustment – superior to the original
model, especially with reference to the difference between chi-square statistics in
relation to the degrees of freedom and to GFI. NFI e CFI indexes, – can be noticed.
Costs
Quality
Value R
2=0,69
Salient Identity
Change Costs
Satisfaction R
2=0,88
Intentional Loyalty R
2=0,83
Real Loyalty R
2=0,15
CommitmentR
2=0,49
0,64***
-0,26**
0,94***
0,90***
0,29***
0,25***
0,18***
0,69***
0,20***
0,33***
0,54***
0,13*
Fit
χ2= 497,04 NFI=0,88
G.l= 233 RFI=0,85
χ2/G.l= 2,13 IFI=0,93
GFI = 0,87 TLI=0,92 AGFI=0,83 CFI=0,93 RMSEA=0,06 HOELTER (5%)=146
Trust R
2=0,81
Inertia R
2=0,44
0,19***
0,49***
Intentional Loyalty
35
INDEX VALUE DESIRABLE
Absolute Adjust
Chi-square (χ2) 497.04 N.A
Degrees of freedom (gl) 233 N.A
Probability <0.001 > 0.05
RMSEA 0.06 < 0.08
Probability (RMSEA < 0.08) 0.99 > 0.90
GFI 0.87 >0.90
Incremental Adjust
AGFI 0.83 >0.90
CFI 0.93 >0.90
NFI 0.88 >0.90
NNFI (Tucker Lewis Index) 0.92 >0.90
Parsimonious Adjust
χ2/gl 2.13 < 4
PGFI 0.67 N.A
PNFI 0.74 N.A
Table 6 – Ajdust indicators of the model with all the constructs
Source: Research data
Notes: The column value presents the estimates of the model ajustment, while the column desirable corresponds to the limits
accepted in the literature (HAIR et al, 1998). N.A means non–applicable. Source: Exit of AMOS 4.
In the alternative model the intentional loyalty receives higher influence of satisfaction
than in the original model, being, by its turn, strongly related to quality. Yet, the quality
has a strong relationship with trust and the perceived value, reinforcing the evidences
found in the original model. In the alternative model satisfaction also appears as an
antecedent of inertia, a fact that can, perhaps, be explained by the equity in the
customers’ perceptions of quality offered by the cell phone providers, discouraging
them switching of providers. Another important contribution is the impact of the
switching costs in the real loyalty, initially not measured by the initial model.
Consumer behavior theories suggest that higher satisfaction leads to higher loyalty, but
the relevance of the switching costs in the process of loyalty construction can be
verified in the alternative model. Even when unsatisfied, customers stay with the same
36
provider because of the exit barriers associated to the process of supplier switching.
This model reinforces the perception that not only the constructs usually associated to
the process of loyalty construction, as satisfaction, trust and commitment – influence
customer retention –, it shows that switching costs also play an important role in the
process. The switching costs showed in the alternative model present higher correlation
with inertia, which, in turn, exerts a higher influence on real loyalty there than in the
original model. The connection between inertia and salient identity are also reinforced
in the model.
7. CONCLUSIONS
Academic Implications
Under the academic perspective, some conclusions, taken from the results of this study,
can be emphasized. The present study aimed to investigate – besides other aspects – the
influence of psychological aspects on consumer behavior. Therefore, the first and
maybe, the main academic implication of this dissertation is the interrelation of the
constructs linked to psychological factors the consumer, such as the inertia and salient
identity, in the process of loyalty construction – opening an opportunity for a more
detailed understanding, accompanied of empiric base, of the consumer decision process
and it´s relations to individual psychological traits. This subject deserves attention, once
it has a wide scope to be academically developed and was the target of very few
directional researches, besides having a high managerial value.
Due to the growing interest in the understanding of the loyalty antecedents for the
customer value management (REICHHELD. 1996), the understanding of the impact of
37
psychological aspects – along the functional ones – becomes critical, especially when
the results point to a higher effect of inertia, and of switching costs on loyalty. It is
suggested, then, that in order to create a series of consistent researches on the impacts of
the psychological aspects on loyalty new studies should be made, therefore, building the
theory of the consumer's behavior, similarly to what occurred with other functional
constructs, such as satisfaction, quality and perceived value.
The development of a new measurement model for the antecedents that induce loyalty
in the cell phone market, including, in the same spectrum, different constructs – that did
not relate to each other before – also provides an important contribution. The
application of this mechanism is suggested for other cities and countries, as well as for
other markets, even if adaptations for use in other industries, are necessary.
Another important point to be considered is the introduction and characterization of two
new dimensions of loyalty: intentional loyalty and real loyalty. Future studies can
explore these two new concepts in the cell phone market, as well as in other ones.
It was possible to propose a nomological network of constructs that explains the process
of loyalty formation in the cell phone market, contributing to validate the satisfaction
model of Fornell et al, (1996), since it enable the identification that quality of services
of the cell phone providers is a decisive factor in attaining customer loyalty.
Therefore, this study considered different constructs related to the process of loyalty
construction in a single model, including new dimensions of loyalty, besides constructs
related to psychological aspects. Hence, additional studies to investigate more deeply
38
the direct relationship of loyalty with these, and other constructs to be explored – such
as image, identity, brand strength, and social benefits, – are highly recommended. A
deeper investigation on the switching costs is also made necessary. The sequence of the
study in a traverse way to bring about new relationships among the constructs also
considered in the model.
Managerial Implications
The found results indicate that cell phone providers should, above all, maximize
customer satisfaction and introduce switching costs, in order to increase loyalty. The
quality of the rendered services obtained low score in the qualitative interviews, and
identified that this construct, by its turn, behaves as the main antecedent of satisfaction.
As quality perceptions increase, satisfaction state also improves, increasing its impact
on the real loyalty. Once, nowadays, quality is not satisfactory enough, the switching
costs and inertia exert a higher impact. Above all, the cell phone providers have to focus
on the quality of its services, acquire a market–oriented vision, and become closer with
its customers.
As identified in the research, most customers become loyal to the providers due to some
offered benefit and for the cost of change. In the moment that providers identify the
most important benefits in the customer's perception, it will start to reinforce them in its
offer of services, improving their quality. The results of this research indicate that the
providers should constantly measure its sensibilities to variations related to the services
performance, in order to address its efforts to continuous improvement of quality, in a
39
search for a competitive differential. Hence, those companies will be collecting
subsidies to invest in the improvement of their services.
Among the factors that constitute the quality of the services, – the quality of the
connections, aggregate value services, and customer service quality stand out. This
suggests that, although, during the past years cell phone providers have improved the
quality of their receptions and connections through solid investments in technology
coverage, the available data indicates that this attribute still maintains its importance.
Besides, cell phone providers need to concentrate their efforts in the development of
services of aggregate value and content, in order to offer entertainment ans information
services to its consumers –, an accomplishment that offers competitive differential to
the providers.
In the customer support area, the providers should address efforts to minimize the
customer service inconveniences, making available a variety of customer service
channels, besides implementing higher quickness in dealing with customers’ complaints
and solicitations. It was perceived by this work that cell phone customers of the
researched area desire to establish relationships with providers that sponsor agile
attendance (customer service), fulfills its promises, that solve customers complaints in a
fast, efficient, uncomplicated, and unbureaucratic way.
As described previously, the switching costs should exist in order to increase loyalty
indexes. Among the switching costs identified in the research, the financial costs and
psychological costs stand out. These costs of change, however, should be part of a set of
service that offers quality, since the switching costs associated to the insatisfaction
40
generates a false loyalty, where the customer is hostage of the provider and the
continuity of the affiliation is solely motivated by the exit barriers. Along, with the
switching costs, the customer should take satisfaction and pleasure in its relationship
with the provider.
It was also detected that the consumers possess low identity with the providers, in other
words, most of the times the relationship is merely commercial, without psychological
associations – of affectivity and complicity on the customer’s side. It is also necessary
that the companies improve their level of knowledge on their customers, its preferences,
desires and needs, creating a process of systematic diagnosis of its customer base.
Starting from the collection of information, it is possible to unfold actions that meets the
customers needs –, capable of addressing efforts to increase the affective ties,
consequently, elevating the degree of customers commitment to the company. With this
information makes possible to the providers to segment its customer’s base, and from it
develop actions to increment their loyalty. Among these actions, the accumulated
benefits, privilege points relationship programs – stand out the. It is important for the
company to personalize and differentiate services through the use of CRM, not only in
the sense of increasing the costs of change, but also to achieve an effective relationship
with its clientele. It also key that the company conducts its communication and the
advertising efforts – including direct mail – in a structured way, accordingly to the
customers profile – as those are also actions that seek to increase their loyalty. This
way, higher levels of emotional involvement of commitment will be generated.
Finally, another interesting action would be identifying the inert consumer's profile,
which is already in provider’s current base of customers, and to attract new customers
41
with the same profile. The inert customer can be identified through satisfaction
researches with the existing customers. It is known that inert customers are more
resistant to change, whence capturing and retaining them can be a good step to increase
loyalty levels.
Limitations
About the limitations of the research can consider that the longitudinal cut would be
more appropriate to evaluate the process of loyalty construction of along time. If loyalty
develops from the commencement of a series of factors, the diagnosis of a situation can
suffer alterations with the passing of time. Another fact to be emphasized is the low R2
presented by real loyalty. Perhaps the inclusion of a higher number of constructs can
explain this loyalty type in a better and more complete way.
From the premise that the main purpose of this research was the identification of the
antecedents of loyalty in a specific sector of the economic activity, the cell phone
market, we cannot make inferences to other types of businesses. In studies of this nature
results can only be generalized in relation to theoretical foundations, and not in relation
to data analysis, and interpretations of qualitative and quantitative results. Therefore, we
suggested that this model should be applied not only in other sectors of the economy,
but also in the B2B context.
42
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