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Evaluation of the customer relationship quality and propensity to change mobile telephone operators/Avaliacao da qualidade do relacionamento e a pre-disposicao de troca entre operadoras de telefonia celular.

1. INTRODUCTION

Concern over the relationship with customers, and consequently the value chain generated by them, is becoming stronger among medium and large companies, according to a survey conducted in Brazil in the first half of 2003 by the Peppers & Rogers Group Institute. In search of differentiated attitudes and behaviors such as satisfaction and loyalty, with consequent higher revenue, many Brazilian firms have been investing to improve their relationship with customers.

To operationalize a study to illustrate this situation, we decided to investigate, under the prism of relationship marketing, possible relations between perceived quality and perceived value and the relationship quality, and the association of these, as well as loyalty and a financial result indicator in the mobile telephone sector. Besides this, we investigated the predisposition to change operators, through the use of logistic regression.

The literature on customer loyalty and satisfaction starts from the premise that a satisfied customer will make repeated purchases of the same brand, and that this loyalty translates into greater profits (Reichheld & Sasser, 1990; Fornell, 1992). In the present study we relied on an adaptation of the structural model proposed by Prado (2004) on relationship quality, its antecedents and consequences, adding a financial result variable--lifetime revenue (LTR), and evaluated these constructs and the propensity to change operators expressed by consumers.

We chose the Brazilian mobile telephone sector as the empirical context for two main reasons: (1) this service lends itself well to a relationship study, because customers acquire a line and tend to use it for a medium or long period, and (2) the sector has been growing rapidly (153.7 million lines in the first quarter of 2009) and at the same time is subject to a certain degree of instability among consumers.

According to Teleco, the rate of changing operators, or the churn rate, ranges from 1.9% to 2.7% a month. Further according to information disclosed by Teleco, since the monthly average revenue per user (ARPU) among prepaid users (using calling cards) is as low as one-seventh that of postpaid subscribers, companies have begun to put more emphasis on attracting and keeping users with higher consumption, by offering plans with built-in spending controls that are intermediate between prepaid and postpaid calling. In this sense, we examined the propensity to change operators of consumers, in light of the evaluation of the relationship quality and its antecedents, as well as the financial result declared by the customers.

2. LITERATURE REVIEW

In the literature review we focused on the constructs underpinning the relationship quality along with the antecedents and consequences related to this assessment, and from this formed hypotheses for the model under study.

2.1 ANTECEDENTS OF RELATIONSHIP QUALITY: PERCEIVED QUALITY AND PERCEIVED VALUE

Perceived quality depends on consumers' preferences and perceptions (Holbrook & Corfman, 1985). According to Zeithmal (1988), these perceptions change over time as a result of more information, increased competition and changing expectations. In this respect, the perceived quality can be defined as the judgment of consumers about the superiority or inferiority of the product or service from the standpoint of attitudes, or the difference between consumers' expectation and perception of the product/service. This expectation, in turn, can be defined as the desired or expected product/service (Zeithmal, Berry & Parasuraman, 1996).

The term perceived value was used in various forms by Zeithmal (1988) in an exploratory study, leading him to suppose that the assessment of value is personal and idiosyncratic. Among the groups of responses, four stood out: (1) value is low price; (2) value is what I want from a product; (3) value is the quality I get for the price I pay; and (4) value is what I receive for what I give. Therefore, perceived value is the consumer's perception of the cost-benefit relationship obtained from a supplier.

According to the theoretical exposition, there should be a positive relation between perceived quality and value (Eggert & Ulaga, 2002; Marchetti & Prado, 2004). In the model proposed, we consider both as being antecedents of satisfaction, but the impact of quality on value, with respect to the cost versus benefit evaluation, is expected, so that:

H1: The higher the perceived quality is, the higher the perceived value will be.

2.2 RELATIONSHIP QUALITY

Relationship quality is suggested by Henning-Thurau & Klee (1997) as being the ability of a relationship to meet the needs of the individual/customer. It integrates the constructs of trust, commitment and quality as mediators of customer satisfaction and retention. Prado (2004), following the antecedent-consequent relation logic between satisfaction and perceived quality, proposed an adaptation in the composition of this concept, formed by three variables: satisfaction, trust and commitment. We adopted this second composition in this study.

The concept of satisfaction commonly employed among authors in the area involves subjective comparison (or evaluation) of the expected and received levels of the experience with the good or service (Oliver, 1981; Bergamo & Giuliani, 2009; Barcelos, Baptista & Silva, 2010), which is related to the paradigm of disconformity (Oliver, 1981). The role of perceived quality as an antecedent of satisfaction has been recognized in the studies of Fornell et al. (1996), Jonhson et al. (2001), Prado (2004) and Marchetti & Prado (2004). In this context, we expect that:

H2: The higher the perceived quality is, the higher the customer satisfaction will be. Bolton (1998), McDougall & Levesque (2000), Eggert & Ulaga (2002), Marchetti & Prado (2004) and Bergamo & Giuliani, (2009) also have proposed the existence of a positive relation perceived value and satisfaction. Therefore our third hypothesis is:

H3: The higher the perceived value is, the higher the customer satisfaction will be.

Trust is treated with great importance in relationship marketing, since in its essence it implies the notion of confidence and reliability between the partners in a relationship (Garbarino & Johnson, 1999; Gronroos, 1990; Bergamo & Giuliani, 2009; Barcelos, Baptista & Silva, 2010). Complementing this idea, Morgan & Hunt (1994) argue that this dimension exists in a relationship when one party believes in the integrity and responsibility of the other party to the exchange, and state that the global dynamic of the market brings some premises, such as being an effective competitor requires the company to be a reliable collaborator in the relationship network.

Commitment has been defined as the desire to continue a relationship, and is seen as a good indicator of lasting relationships between the customer and firm (Dwyer, Schurr & Oh, 1987). This variable is commonly studied in inter-organizational and intra- organizational settings (Mavondo & Rodrigo, 2001). Morgan & Hunt (1994) also refer to commitment as a belief that the exchange between partners in a relationship is just as important as guaranteeing the maximum effort to maintain it.

Satisfaction is viewed as one of the elements of the quality of the relationship, and considering the definitions of this quality (satisfaction, trust and commitment), it can be said that these are complementary. As in the empirical model of Prado (2004), we expect a positive association between satisfaction on the one hand and trust and commitment on the other, according to hypotheses H4 and H5:

H4: The higher the satisfaction is, the higher the trust will be in the supplier of the service.

H5: The higher the satisfaction is, the higher the commitment will be to the supplier of the service.

The relation between trust and commitment is also indicated as relevant and positive in the studies of Morgan & Hunt (1994) and Bergamo & Giuliani, (2009). Complementing this assertion, according to Achrol (1991), trust is the greatest determinant of commitment in a relationship. Since the present study examines a highly competitive context (technological development, rivals with little differentiation in competitiveness, among other aspects), we expect this relation, besides being positive, will be an indication of stronger loyalty to the relationship. Therefore, our sixth hypothesis is:

H6: The higher the trust in the supplier of the service, the greater the commitment to it will be.

2.3 CONSEQUENCES OF RELATIONSHIP QUALITY: LOYALTY AND FINANCIAL RESULT

Although this aspect has mainly been analyzed from a more operational perspective, where its concept has been associated with the question of renewed purchasing of a particular product or service (Yi & Jeon, 2003), Oliver (1999, p. 35) attributes a deeper meaning to the judgment of the consumer regarding the best company: "(...) to become a loyal customer, he must believe that a company or its services continue to offer the best alternative". The author also indicates the prior need for trust and commitment to the relationship.

Another definition and classification of this variable can be found in the study of Dick & Basu (1994), who discuss the concept of probability of buying from a determined supplier, in a certain quantity and frequency in a given period. The authors also suggest a classification of loyalty into four categories: (1) loyalty; (2) latent loyalty; (3) false loyalty; and (4) no loyalty. Of these, the first is the result of the intention to buy again and the accompanying attitude, defining the "true" state of loyalty.

In relating the influence of satisfaction on loyalty, Oliver (1999) presents six possible relations between these variables, among which we opt in this study for an approximation of the sixth, where initially the individual is satisfied, and by a cumulative positive process can reach the stage of true loyalty. Bolton (1998) attributes a positive relation in this respect, tested empirically in the mobile telephone market, on the satisfaction and retention time of this relationship, that is, its loyalty.

Furthermore, McDougall & Levesque (2000) and Hurley & Estelami (1998) empirically demonstrated a positive associate between satisfaction, arising from the perception of quality, and future buying intentions, that is, the continuity of the relationship and consequent loyalty of the customer. For these reasons, we expect:

H7: The higher the satisfaction index is, the more loyal customers will be.

After defining loyalty, Oliver (1999) stresses that the best way to reach a state of loyalty is for the customer to believe the company chosen is the best option. Therefore, he considers that besides believing in the company, the consumer must trust the image, information and knowledge, among other factors that enable maintaining the choice over the long term. Also, Gronroos (1997) stresses the importance of the trust and commitment variables in the customer relationship, under the prism of relationship marketing. Based on this, we present hypotheses H8 and H9, also in concordance with multiple studies in the area (Prado, 2004; Oliver, 1999; Bergamo & Giuliani, 2009; Barcelos, Baptista & Silva, 2010):

H8: The greater the trust in the supplier of services, the stronger the loyalty to this supplier will be.

H9: The greater the commitment to the supplier of services, the stronger the loyalty to this supplier will be.

The financial result can be defined as the financial value of a customer over a determined period of steady buying from the supplier of a product/service. A positive financial result means the customer generates a profit for the company over the time frame for calculation. This concept is connected to the relationship logic, since maintaining a loyal customer base translates into more consistent and higher profits. Yeung & Ennew (2000) tested the association between loyalty and profitability, where they expected a positive and significant result. This assumption was borne out by the authors by using the American Customer Satisfaction Index (ACSI) with the annual balance sheets of the 200 largest American companies. Johnson et al. (2001) and Guo & Jiraporn (2005), among others, corroborate this hypothesis. Therefore, our tenth hypothesis is:

H10: The greater the loyalty is, the higher will be the customer's LTR.

Having presented the hypotheses, we now set out the model proposed, according to Figure 1. The model is an expansion of that developed by Prado (2004), studying relationship quality, aggregating a financial indicator (lifetime revenue - LTR) to the factors relationship quality and loyalty.

[FIGURE 1 OMITTED]

3. METHODOLOGY

This study reports the results of a cross-sectional survey (Malhotra, 2001). The dimension is quantitative-descriptive and the method applied is hypothetical-deductive (Gill & Johnson, 1997), based on the theoretical model suggested for testing. To enable the study, the sampling procedure used was non-probabilistic, and also employed the snowball sampling technique, as defined by Malhotra (2001). The number of observations followed the reference of Hair et al. (2005), who suggest 10 observations per item for better fit of the model tested.

All told, we obtained 493 valid responses, 58% (288) from users of prepaid cell phone plans and 42% (205) from postpaid subscribers. The gender distribution between the types of mobile phone users was mainly women among prepaid users (T =48.808, p<0.001) and predominantly men among postpaid users (T=44.012, p<0.001).

Our data analysis entailed verification of the content validity of the dimensions of the variables proposed in the model and testing the model and study hypotheses between the groups generated from the database. To operationalize the measurement of the variables, we adapted the following scales from the study of Prado (2004): perceived value (4 items), satisfaction (4 items), trust (7 items), commitment (9 items) and loyalty (6 items). The perceived quality scale was adapted from surveys conducted by the National Telecommunications Agency (Anatel) (1). To measure the financial return (LTR), we used the model of Francisco-Maffezzolli (2007), which in turn is derived from the model proposed by Ryals (2005). We used two data sources, first by gathering information directly from customers and second by gathering data on the companies in the database.

The process of analyzing the results involved the following main steps: (1) preparation of the database and verification of the descriptive statistics by univariate and multivariate analysis; (2) verification of the measurement model for the structural analysis proposed with the use of exploratory factorial analysis of the internal consistency of each dimension, defined by Cronbach's Alpha, and confirmatory factorial analysis to establish the convergent and discriminant validity of each construct of the model; (3) calculation of the profitable lifetime, involving definition of parameters to estimate the value of the financial result; (4) generation of the groups for analysis; (5) verification of the proposed structural model by means of structural equations; and (6) use of logistic regression to verify the propensity to change operators.

4. RESULTS

The results are presented in the following order: characterization of the sample; a brief description of the data preparation and verification of the model for measurement proposed; generation of the groups; and presentation of the overall results obtained with the model.

4.1 CHARACTERIZATION OF THE SAMPLE

Of all the respondents 53% were women and 47% were men. The characterization of purchasing power, according to the Brazilian scheme of ranking economic classes (A at the top to D at the bottom), was 38% B2, 27% B1, 26%C, 7% A2, 1% D and 1% A1. The breakdown by operators was 51% for Tim, 22% Vivo, 16% Claro and 11% Oi (Brasil Telecom). Among the operators, there was a larger concentration of postpaid users of Tim and of prepaid users of Claro. This information is proportional to the presence of each operator in the base.

The average relationship duration for all the operators together was 49.2 months (SD=34.944), broken down into 41.8 months (SD=27,598) among prepaid users and 59.6 months (SD=41.091) for postpaid subscribers. This information was obtained directly from the responses.

Regarding the past pattern of changing operators, 56% of the 493 respondents had previously used at least one other operator. Therefore, the data were only obtained regarding the relationship with the current operator. The question on the intention to switch revealed that 69% of the respondents had thought in the past about changing to another operator, and of these 308 respondents, 55% said they might switch in the next six months, while 37% said they might do so in the next year.

The respondents were asked the amount spent per month in order to obtain an average value to estimate the profitable lifetime. Among prepaid users, the monthly figure was R$ 25.00 (SD=11.150), while among postpaid users it was R$ 128.00 (SD=91.348). These high standard deviations demonstrate the great heterogeneity of use patterns in the sample studied.

4.2 PREPARATION OF THE DATA AND VERIFICATION OF THE MODEL

The result of the factorial analysis confirmed the one-dimensional character of satisfaction (Alpha of 0.912), perceived value (Alpha of 0.887) and loyalty (Alpha of 0.896). This one-dimensional character also was true of trust and commitment, with Alphas of 0.896 and 0.912. Only the perceived quality supported more than one dimension, these being quality of customer response services (Alpha of 0.894), technical quality (Alpha of 0.876) and payment conditions (Alpha of 0.733).

The subsequent factorial analysis to confirm the 47 indicators proposed initially led to keeping 44 of them because of the high model fit. We also employed the compound trust value (CTR), which should be greater than 0.7, and the average variance (AVE), which should be greater than 0.5 (Hair et al., 2005), as indicators of convergent validity. We considered the results obtained to be plausible for the analysis made. We observed the discriminant validity by the pairwise correlation of the variables and by observing the difference between the free and the fixed Chi-square (1). The acceptable values should be lower than 3.5. The results demonstrated there was no overlap of the constructs. The same procedure was used

by Moura (2005). The goodness-of-fit indices of the structural model, considering only the latent variables, were acceptable and satisfactory according to the parameters given by Hair et al (2005): [chi square] = 643.629, GL = 155, p<0.001, [chi square]/GL = 4.152, NFI = 0.925, CFI = 0.942 and RMSEA = 0.080.

4.3 DETERMINATION OF THE FINANCIAL RESULT INDICATOR

To determine the financial result indicator (lifetime revenue, or LTR), given the limitations of the field survey (mainly the impossibility of obtaining the usage history of each customer directly from the operator), we used the following calculation structure. First we obtained the gross revenue and EBITDA margin reported by each company. This margin includes the operational contribution of each company. Due to the lack of precise information on the costs per customer of each operator, we used this indicator on each respondent to find the individual contribution. In the case of prepaid users who reloaded their credits in an interval shorter or longer than a month, we converted the values to a monthly period.

The principle utilized to determine the value was the sum between the historical value and the future value, considering the financial formulas for future value and present value, respectively. The discount rate was the Selic rate (the benchmark rate in Brazil). The previous time with the operator and projected future retention were obtained from the respondents. To determine the projected continuity time, we treated this element as the expectation of staying with the present operator, according to the following formula:

LTR = HV (historical value) + FV (future value) HV = M [(1 + i).sup.n], where:

M = contribution margin (monthly value declared by the respondent x EBITDA margin of the operator) i = Selic rate n = number of months with the operator declared by the respondent.

FV = M [(1 + i).sup.n], where:

M = contribution margin (monthly value declared by the respondent x EBITDA margin of the operator) i = Selic rate n = intention to stay with the same operator (in months) declared by the respondent.

4.4 GROUPS FOR ANALYSIS OF THE PROPENSITY TO CHANGE OPERATORS

Among the 493 respondents, as observed in the categorization of the sample, there was considerable heterogeneity, including gender, age and type of calling plan, among others already discussed in item 4.1. Therefore, we used information declared by the respondents to assign the condition "will change (1)" or "will not change (0)" operator.

Of the respondents, 308 stated they were predisposed to switch, of whom 48% were women and 52% men, 57% used prepaid calling cards and 43% were postpaid subscribers. Of the consumers with lower propensity to change (185), 61% were women and 39% men, while 60% used prepaid plans and 40% used postpaid ones. Therefore, there was no significant difference in the composition of the two groups only by the categorical variables gender and type of calling plan.

To further verify the differences between the groups (those who declared they would change- Group 1 or not change - Group 2), we contrasted the weighted average or each latent variable between the groups, as presented in Table 1:
Table 1: Difference between the Groups

Groups **        Variables        t-value    Significance    Mean

            Loyalty *             T=11.639     p<0.001        4.93
NC                                                            6.32
C           Trust *               T=10.078     p<0.001        3.91
NC                                                            5.01
C           Commitment *          T=11.069     p<0.001        3.77
NC                                                            4.97
C           Satisfaction*         T=10.200     p<0.001        4.64
NC                                                            5.85
C           Perceived value *     T=7.762      p<0.001        5.30
NC                                                            6.17
C           Perceived quality *   T=8.092      p<0.001        4.71
NC                                                            5.35
C           LTR (lifetime         T=0.009      P=0.993      6,446.68
NC            revenue)                                      6,458.16
C           Time with the         T=0.345      P=0.730       59.79
NC            operator (months)                              58.61

Groups **   Standard         Total
            Deviation     Observations

               1.44           308
NC             1.17           185
C              1.27           308
NC             1.11           185
C              1.24           308
NC             1.11           185
C              1.34           308
NC             1.15           185
C              1.23           308
NC             1.17           185
C              0.90           308
NC             0.82           185
C           12,496.85         308
NC          15,514.42         185
C             31.94           308
NC            39.32           185

* The constructs were evaluated by the weighted average

** C= Change (1) / NC = Not Change (0)

Source: Pepared by the authors


In the differences presented, besides the considerations already made about the indicators leading to the classification of the groups, consideration can also go to the distinction of the general evaluations. In this respect, Group 1 (intention to change operator) showed significantly lower values for the constructs loyalty, trust, commitment, satisfaction, perceived value and perceived quality regarding the respective operator. This assessment appears coherent, since those who declared higher loyalty and relationship quality intended to stay with their existing operator for a longer period.

We should note that the time with the company and revenue contributed to the company did not show significant differences between the two groups. According to the customer relationship literature, more loyal customers should be more profitable and remain with the company longer. However, these premises were not found in our sample. This situation might be the result of the heterogeneity of the sample or a reflection of the dynamic of the mobile telephone market, such as the intensity of competition. Due to the non-probabilistic nature of the sample, it is not possible to extrapolate these results to other users.

5. TESTING THE MODEL AND THE HYPOTHESES

We tested the structural model using six latent variables and one directly observable variable, as already presented. The results of the hypothesis testing are shown in Table 2, with the contrasts between the groups observed:
Table 2--Standardized Coefficients (paths) Estimated for the
Theoretical Relations Proposed in the Model

Structural Relation          Groups   Standardized   t-value *
                                      Coefficient

Perceived Quality [right      C          0.751        8.861 *
  arrow] Perceived Value     NC          0.690        7.664 *
Perceived Quality [right      C          0.505        5.179 *
  arrow] Satisfaction        NC          0.182        2.385 *
Perceived Value [right        C          0.390        4.658 *
  arrow] Satisfaction        NC          0.766        9.286 *
Satisfaction [right           C          0.634        9.621 *
  arrow] Trust               NC          0.669        8.239 *
Satisfaction [right           C          0.354        5.569 *
  arrow] Commitment          NC          0.354        4.648 *
Trust [right arrow]           C          0.629        8.063 *
  Commitment                 NC          0.685        7.122 *
Satisfaction [right           C         -0.033       -0.389
  arrow] Loyalty             NC         -0.285       -0.915
Trust [right arrow]           C          0.111        0.865
  Loyalty                    NC         -0.581       -0.961
Commitment [right             C          0.792        4.411 *
  arrow] Loyalty             NC          0.680        1.974 *
Loyalty [right arrow]         C         -0.035       -0.588
  LTR                        NC          0.031        0.411

Structural Relation          Groups   Hypothesis    Hypothesis
                                                   Verification
                                                      Status

Perceived Quality [right      C          H1          Confirmed
  arrow] Perceived Value     NC                      Confirmed
Perceived Quality [right      C          H2          Confirmed
  arrow] Satisfaction        NC                      Confirmed
Perceived Value [right        C          H3          Confirmed
  arrow] Satisfaction        NC                      Confirmed
Satisfaction [right           C          H4          Confirmed
  arrow] Trust               NC                      Confirmed
Satisfaction [right           C          H5          Confirmed
  arrow] Commitment          NC                      Confirmed
Trust [right arrow]           C          H6          Confirmed
  Commitment                 NC                      Confirmed
Satisfaction [right           C          H7        Not Confirmed
  arrow] Loyalty             NC                    Not Confirmed
Trust [right arrow]           C          H8        Not Confirmed
  Loyalty                    NC                    Not Confirmed
Commitment [right             C          H9          Confirmed
  arrow] Loyalty             NC                    Not Confirmed
Loyalty [right arrow]         C         H10        Not Confirmed
  LTR                        NC                    Not Confirmed

* Results significant at 0.001

Group C (change): [chi square]  = 604.257 GL = 180. p<0.001,
[chi square] /GL = 3.357, NFI = 0.870. CFI = 0.904 and
RMSEA = 0.088

Group NC (not change): [chi square]  = 446.085 GL = 180. p<0.001,
[chi square] /GL = 2.478, NFI = 0.857, CFI = 0.908 and
RMSEA = 0.090

Source: Prepared by the authors


The fit indices of both models can be considered plausible according to confirmatory factor analysis (CFA). However, we believe a base with more observations for each group could offer better fit. The result of the overall model was based on 493 observations, 185 in Group NC (not willing to change) and 308 in Group C (willing to change), as already presented.

Hypothesis 1, supported by the findings of Eggert & Ulaga (2002) and Marchetti & Prado (2004), showed a positive and significant relationship. The interpretation of this relationship indicates a situation where the higher the perceived quality is (defined by technical quality, excellence of customer response and payment conditions), the greater will be the impact on the perceived value (defined by effort, time and cost of the relationship). Both groups proved this situation ([beta]=0.751, p<0.001 for Group C and [beta]=0.690, p<0.001 for Group NC). This situation indicates that regardless of the customer profile in terms of propensity to switch brands (particularly in the context of mobile phone operators), the assessments of quality and value are important. The association between perceived quality and satisfaction (H2), with this order of antecedent and consequence, has been recognized in the studies of Fornell et al. (1996), Jonhson et al. (2001) and Marchetti & Prado (2004), among others.

Perceived value is also considered to be an antecedent of satisfaction and constitutes the economic dimension (cost versus benefit) of the proposed model. This relation, already noted by Bolton (1998), McDougall & Levesque (2000), Eggert & Ulaga (2002) and Marchetti & Prado (2004), is positive and relevant, as observed in Group C. However, perceived quality is not the only antecedent of satisfaction according to the literature. Therefore, it might be that other elements, such as trust and commitment, are relevant for people to tend to stick with brands.

Hypotheses 4, 5 and 6, which replicate the proposal of Prado (2004) about the quality of the relationship, were borne out by both groups (C and NC). Garbarino & Johnson (1999) also found evidence of a complementary association between these variables, making the positive and significant relation between satisfaction, trust and commitment plausible.

Although studies such as those by McDougall & Levesque (2000), Hurley & Estelami (1998), Bergamo & Giuliani (2009) and Barcelos, Baptista & Silva (2010) empirically demonstrate the positive and significant relation of satisfaction with the intention to purchase and continue the relationship (these being loyalty indicators), it should be mentioned that there is a good deal of controversy in the literature about this relation. Some authors, such as Jones & Sasser (1995), have mentioned an association that is not necessarily linear in this relationship (satisfaction - loyalty). Those authors also comment that environmental characteristics, such as high cost of switching, promotional advantages and governmental regulations, are among factors that stimulate false loyalty and a 'weak' relation with satisfaction, since in this context the relationship time is not solely defined by the user's choice, but also by other variables that offer convenience or impose constraints. In the present study, both groups did not prove this association, as the result of hypothesis 7 demonstrates.

Hypothesis 8, which posits a significant association between trust and loyalty, was not confirmed in either of the two groups. According to Oliver (1999), the continuity of the relationship between a company and consumer occurs partly by the latter's belief that the choice is best. At this moment, the trust in the brand, the company or its image (for example) is a strong indicator of loyalty to it. This relation, however, rejected in the setting of mobile phone service, can be understood by the Brazilian context itself, by considering some elements, such as the complaint rates among all operators in the country, according to the records of Procon (the consumer compliant office), and perhaps the characteristics of the market structure (oligopoly).

The association of commitment with loyalty, present in H9, was confirmed only for group C. This result agrees the those of Groonros (1997) and Bergamo & Giuliani (2009), in affirming the importance of this construct on the continuity of a relationship, and also with Oliver (1999) regarding the comprehension of loyalty by phases, where the higher the commitment is, the greater will be the probability of turning a situation of affective or conative loyalty into loyalty of action.

With respect to hypothesis 10, where we expected a positive association between loyalty and the financial index (LTR), although the literature generally indicates this positive association exists (Yeung & Ennew, 2000; Johnson et al., 2001; Guo & Jiraporn, 2005), some authors question the linearity and significance of the affinity of the constructs. Gurau & Ranchhod (2002) comment on the difficulty of obtaining a positive relation, considering the subjectivity of measuring the latent variables or the bias that cross-referencing the data can have due to some other factor. These limitations raised by the authors include the type of data collection (cross sectional). It is possible that longitudinal monitoring might offer more concrete information. Therefore, we consider that this hypothesis was not borne out in either group.

In complementary form to the study objectives, we also observed the indirect effects in the structural model. The values in Table 3 show the results obtained:
Table 3--Indirect Effects between the Latent Constructs of the
Structural Model

Indirect effects between the         Standardized     Standardized
constructs of the model              coefficients *   coefficients *
                                       (Group NC)       (Group NC)

Perceived Quality [right arrow]      0.293 *          0.529 *
  Satisfaction
Perceived Quality [right arrow]      0.506 *          0.476 *
  Trust
Perceived Value [right arrow]        0.247 *          0.513 *
  Trust
Perceived Quality [right arrow]      0.601 *          0.577 *
  Commitment
Perceived Value [right arrow]        0.294 *          0.622 *
  Commitment
Satisfaction [right arrow]           0.399 *          0.458 *
  Commitment
Perceived Quality [right arrow]      0.506 *          0.492 *
  Loyalty
Perceived Value [right arrow]        0.247 *          0.530 *
  Loyalty
Satisfaction [right arrow]           0.666[??] *      0.976 *
  Loyalty
Trust [right arrow] Loyalty          0.498*          0.900 *

* values significant at 0.001

Source: Analysis of the data from the project


The indirect effects demonstrate that in general (7 of the 10 indirect relations) the constructs for evaluating the relationship, particularly those that explain satisfaction and loyalty, can be observed with greater weight among the evaluations of the group that would not change operators. The investigation of these effects is relevant since the next step of the study was to verify the predisposition to change operators, considering the possible explanatory power of these constructs. Therefore, direct and indirect effects can help the comprehension of the behavior of these variables, since the linearity of some relations, such as between satisfaction and loyalty, may not be sufficient to understand the results obtained.

6. EVALUATION OF THE PROPENSITY TO CHANGE MOBILE TELEPHONE OPERATORS

Besides the structural assessment carried out, which demonstrates the predominance of linear relations between the constructs analyzed, to assess the respondents' propensity to change operators we used a logistic regression model in complementary form to try to map the willingness to change. This analytic model follows the principles of multiple regression, with the condition that the dependent variable must be categorical, according to the following formula:

[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] (1)

So that:

[Y.sub.i] = 1 [right arrow] P([Y.sub.i] = 1) = [[pi].sub.i] [Y.sub.i] = 0 [right arrow] P([Y.sub.i] = 0) = 1 - [[pi].sub.i] (1)

In this case, the independent variables can be categorical or continuous. The origin equation explains the probability that Y will occur when Xi occurs (Field, 2005). Therefore, to evaluate which elements can affect the consumers' condition of "will change" or "will not change" mobile phone operators, we tested (in continuous variable character) the constructs for evaluating the relationship with the respective weighted means. We also tested categorical variables such as gender, type of calling plan (prepaid or postpaid), and continuous ones such as time of relationship with the operator (in months) and the declared value of the investment in the services, indicated in this study as the LTR.

This analysis entailed two steps. In the first, we selected cases randomly, according to the random transformation of the numbers by SPSS. For this purpose we selected 70% of the sample, or 348 cases. The results from this initial portion of respondents indicated acceptable fit indices for the situation analyzed. Therefore, we considered step 2 (according to the forward LD model) as being the most adequate (Chi-square=86.858; SD=2; p<001). The Hosmer & Lemeshow value was also adequate (Chi-square=3.009; SD=8; p=0.934). The predictive capacity was 73%. The most relevant variables were satisfaction and loyalty, respectively, with exp(B) values of 0.593 for loyalty and 0.616 for satisfaction.

Subsequently we performed logistic regression on the entire database, with the forward LR method. This method automatically calculates various models until attaining the best fit. In particular, in this study this led to the choice of model 2 (step 2), with Chi-square = 131.616, SD=1, p<0.001. According to the Hosmer & Lemeshow fit index (Chi-square = 3.519, SD = 8, p=0.898), the values are plausible (other fit indices: -2log likelihood=520.813 / Cox & Snell=0.234 / Nagelkerke R square= 0.319). The predictive power of the model is 73.4%. The values confirmed the results found in the test conducted with part of the sample, which was chosen randomly.

Of the variables tested, only loyalty and satisfaction were relevant to identify factors that can affect the propensity to change operators, as shown in Table 4.

With respect to this result, we highlight that the other constructs (quality, trust, commitment and perceived value), although also indicated in the literature as variables that can affect consumers' propensity to change suppliers, were not distinctive for this propensity in the present study. This suggests a reflection on the results of the structural model. Despite the direct and positive relations between the constructs, as presented in Table 2, the number of factors that might have been very important in determining the propensity to switch is reduced (here we suggest the role of satisfaction and loyalty), as well as being nonlinear. Therefore, we believe the use of complementary analytical models is helpful, since what is sought is to explain, from different perspectives, the effect of the consumer's evaluation of the variables studied.

According to the values presented in Table 1, the constructs loyalty and satisfaction were more important, which can already indicate greater relative importance of these items in the explanation of this model, besides corroborating the results of the logistic regression.

It is also important to note that according to the relationship literature, the value of the financial result and time of the relationship with the operator should be higher and significant for the NC group. However, we did not obtain this result. This situation might be due to the sample's profile (non-probabilistic and highly heterogeneous), or the profile of the sector itself, in which frequent special promotions and offers to consumers lead to a particular and hard-to-predict behavioral pattern.

Therefore, it can be said that the more unsatisfied the consumer is, the greater will be the tendency to switch. Utilizing the value of Exp(B) as a reference, we calculated the probability of changing according to the elements evaluated. With respect to loyalty, the probability of changing went down to 0.362 ((0.569)/1+0.569), while for satisfaction this decline was to 0.389 ((0.638)/1+0.638). This situation demonstrates the importance of these elements in the evaluation of the consumer in relation to the respective purchasing behavior.

7. DISCUSSION OF THE RESULTS

The context of mobile telephone service demonstrated, according to the structural analysis, that satisfaction is not a determining factor (at least among the consumers analyzed) of loyalty. Satisfaction alone did not show a direct and linear positive association on the continuity of the relationship. An opposite situation was observed by Moura (2005), who found a positive and relevant relation between these variables, also in the mobile telephone sector. This situation demonstrates that further studies of this question are necessary. The averages obtained to measure satisfaction were higher in that study than in the present one. Besides the specificity of the state, other differences, such as the use of a 5-point Likert scale by Moura, might explain the contrasting results obtained.

On the other hand, these two variables demonstrate higher influence on the comprehension of the intention to change operators among the consumers studied. Therefore, it is possible to suggest that although we did not observe a direct and linear relation between satisfaction and loyalty, the assessment of these two elements is relevant to the propensity to change. According to the values indicated in Table 3, this relation is relevant, and according to the results of the logistic regression, individuals who are less satisfied tend to be lees loyal, and thus more likely to switch operators (at least in the short term, as declared by the respondents).

In contrast, trust, considered to be a fundamental ingredient for a satisfactory customer relationship (Garbarino & Johnson, 1999; Dwyer, Schurr & Oh, 1987; Morgan & Hunt, 1994), was shown to be a preceding construct of loyalty by Prado (2004) and Sidersmukh, Singh & Sabol (2002). Although a direct association was rejected here, the impact of trust on commitment was relevant, making it possible to consider that trust exercises a certain influence on loyalty through the user's commitment. In the real setting, it is plausible to imagine that the user receives certain stimuli to trust the operator (such as image, response to customer complaints and queries and quality of the services, among others). Development of a feeling of trust by the company tends to trigger the desire to continue the relationship by the customer and the belief that the company is the best option to resolve the customer's problems and needs. This fact, if confirmed, tends to keep the customer loyal to the company. However, this variable appears not to have a direct effect on the propensity to change operators, according to the result of the logistic regression.

Added to this context is the positive influence of satisfaction on commitment, as proposed by Prado (2004) and Bergamo & Giuliani (2009), based on the premise that the consumer's commitment leads to a lasting relationship with the company. Therefore, satisfaction is taken as one of the vectors that cause that commitment. Besides this, there is the positive and significant effect of perceived value on satisfaction, which allows inferring the valorization of the economic perspective proposed by Zeithmal (1988) and corroborated by Marchetti & Prado (2004), in the evaluation of customer satisfaction. We observed these findings only in the structural analysis, so despite the positive and significant impact of this association, we suggest that future studies should investigate, from other perspectives, the influence and explanatory power of these constructs on the propensity to change.

Finally, from the standpoint of relationship marketing, the lack of statistically significant confirmation of the relations proposed in hypotheses 7, 8 and 10, and partially in 2 and 9, might have been due to the particular nature of the sector, or the heterogeneous profile of the sample, facts that again urge future investigations specifically according to user profile.

8. FINAL CONSIDERATIONS

Although we recognize it is not possible to generalize the empirical findings reported here, we can highlight as the main contribution of this study the use of logistic regression to understand (and try to predict) consumer behavior, as well as the effort to establish the complementarity of the results, obtained by testing the structural model.

The relation between satisfaction, loyalty and the financial result index were not confirmed in direct and linear form (results obtained by using structural equations), especially the association between satisfaction and loyalty on the one hand and the financial result on the other. This situation suggests a certain restiveness, since the theoretical premises imply a positive relation of these two pairs of constructs.

The logistic regression showed that customer satisfaction and loyalty are essential elements to determine the propensity to change operators. In other words, the evaluation of these variables is relevant, but not linear, as demonstrated by the results of the structural model. These results corroborate the premises found in the customer relationship literature.

Therefore, we suggest that the use of logistic regression, as a way to understand the propensity of customers to change suppliers, can help better understand the results obtained. The SEM basically demonstrated linear relations between the variables. In contrast, the logistic regression permitted recognition of the independent variables that best explain the behavior. Therefore, the complementary use of these statistical tools allowed a better understanding of the propensity of mobile phone users to change operators.

In closing, this study reflects the richness of the information on the interactions between the behavioral aspects and financial result in evaluation of the customer relationship by companies and suggests that the systematized control of this information can support the marketing strategies of mobile telephone operators.

Received on 01/27/2010; reviewed on 05/31/2010; accepted on 08/12/2010; available in 10/21/2011

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(1) The scale was adapted from the customer satisfaction survey conducted by Anatel in 2004.

Eliane Cristine Francisco Maffezzolli [[dagger]]

Pontificia Universidade Catolica do Parana (PUCPR)

Paulo Henrique Muler Prado [[OMEGA]]

Universidade Federal do Parana (UFPR)

Wesley Vieira da Silva [[yen]]

Pontificia Universidade Catolica do Parana (PUCPR)

Renato Zancan Marchetti [[pounds sterling]]

Pontificia Universidade Catolica do Parana (PUCPR)

Corresponding authors:

[[dagger]] Doctorate in business administration from Parana Federal University (UFPR).

Institution: Pontifical Catholic University of Parana (PUCPR)

Address: Rua Imaculada Conceicao, 1155, Prado velho, Curitiba/PR, 80215901.

E-mail: eliane.francisco@pucpr.br

Telephone: (41) 3271 1476

[[OMEGA]] Doctorate in business administration from Getulio Vargas Foundation (FGV).

Institution: Parana Federal University (UFPR).

Address: Av. Pref. Lothario Meissner, 632 2 andar, Jardim Botanico, Curtiba/PR 80210-170.

E-mail: pprado@ufpr.br

Telephone: (41) 3360-4365

[[yen]] Ph.D. in production engineering from Santa Catarina Federal University (UFSC).

Institution: Pontifical Catholic University of Parana (PUCPR).

Endereco: Rua Imaculada Conceicao, 1155, Prado Velho, Curitiba/PR, 80215901.

Email: wesley.vieira@pucpr.br

Telephone: (41) 3271 1476

[[pounds sterling]] Dr. es Sciences de Gestion, HEC-Paris.

Institution: Pontifical Catholic University of Parana (PUCPR).

Address: Rua Imaculada Conceicao, 1155, Prado Velho, Curitiba/PR, 80215901.

E-mail: renato.zancan@pucpr.br

Telefone: (41) 3271 1476

Note from the Editor: This article was accepted by Antonio Lopo Martinez.

This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 Unported License
Table 4: Significant Variables in the Logistic Regression

Variable         B       Wald    Exp(B)

Loyalty        -0.569   29.141     0.569
Satisfaction   -0.449   16.530     0.638
Constant        6.101   97.865   446.114

* values significant at p<0.001.

Source: Prepared by the authors


1. INTRODUCAO

A preocupacao do relacionamento com clientes e, consequentemente, na cadeia de valor gerada por este, tem-se intensificado entre empresas de medio e grande porte, segundo consta em pesquisa realizada no Brasil no primeiro semestre de 2003 pelo Instituto Peppers and Roggers Group. Em busca de atitudes e comportamentos diferenciados como satisfacao, lealdade e consequente aumento de receita, muitas empresas brasileiras tem se preocupado em investir em relacionamento.

Para operacionalizar um estudo que ilustrasse tal situacao, optou-se por verificar na otica do marketing de relacionamento, possiveis relacoes entre a qualidade percebida e valor percebido, sobre a qualidade do relacionamento e a relacao destes, somados a lealdade e um indicador de resultado financeiro. Alem disso, o estudo preve uma avaliacao sobre a predisposicao de troca entre operadoras de telefonia celular, com o uso de regressao logistica.

A literatura sobre lealdade e satisfacao parte da premissa que um cliente satisfeito possa realizar compras repetidas por uma mesma marca, podendo chegar em um estagio de lealdade, e consequentemente, de rentabilidade. (REICHHELD E SASSER 1990; FORNELL 1992). Desta forma, o presente estudo fez uma adaptacao entre o modelo estrutural proposto por Prado (2004) sobre a Qualidade no Relacionamento, seus antecedentes e consequentes, agregou uma variavel de resultado financeiro, chamada de LTR (lifetime revenue), e preve a avaliacao destes construtos e a propensao a troca declarada pelo consumidor.

O contexto empirico utilizado foi o da telefonia celular brasileira por dois principais motivos: (1) Este servico e enquadrado sob a otica de relacionamento, considerando que o consumidor adquire uma linha e tende a utiliza-la num periodo de medio e longo prazo, e (2) devido as caracteristicas do setor, o qual revela numeros de crescimento otimistas (153.7 milhoes de linhas ate o primeiro trimestre de 2009) e ao mesmo tempo demonstra certa instabilidade entre os consumidores.

De acordo com a Teleco, a taxa de churn, ou seja, troca de prestadoras de servico por clientes, tem variado de 1,9% a 2,7%, mensalmente entre as operadoras. Ainda segundo informacoes divulgadas na Teleco, visto que a ARPU (receita media mensal por usuario) dos usuarios de pre-pago chega, em algumas operadoras, a ser 7 vezes menor que os de pos-pago, passou-se a dar maior enfase a aquisicao e fidelizacao de usuarios com maior consumo, promovendo planos de controle, intermediarios entre o pos e pre pago. Neste sentido, o estudo proposto preve uma possibilidade de verificar a pre-disposicao de troca dos consumidores, tendo em vista a avaliacao da qualidade do relacionamento e seus antecedentes, bem como o resultado financeiro declarado pelo consumidor.

2. REVISAO DE LITERATURA

A revisao de literatura aborda os construtos formadores da qualidade do relacionamento, bem como os antecedentes e as consequencias relacionadas a esta avaliacao, na forma de hipoteses do modelo em estudo.

2.1 ANTECEDENTES DA QUALIDADE DO RELACIONAMENTO: QUALIDADE PERCEBIDA E VALOR PERCEBIDO

A qualidade percebida depende das preferencias e percepcoes dos consumidores (HOLBROOK e CORFMAN, 1985). Zeithmal (1988) considera ainda que estas percepcoes mudam com o tempo como resultado de mais informacao, aumento de competicao e mudanca de expectativas. Nesse sentido, a qualidade percebida pode entao ser compreendida como o julgamento do consumidor sobre a excelencia ou inferioridade do produto numa otica atitudinal, ou ainda ser a diferenca entre a expectativa e a percepcao do consumidor sobre o produto. Esta expectativa por sua vez pode ser definida como o servico desejado ou a adequacao do servico esperado (ZEITHMAL, BERRY e PARASURAMAN, 1996).

Ja o termo valor percebido foi utilizado de varias formas por Zeithmal (1988) em estudo exploratorio, levando a autora a supor que a avaliacao do valor e pessoal e idiossincratica. Dos quatro grupos de respostas mais aparentes, dentre eles: (1) valor e preco baixo; (2) valor e o que eu quero em um produto; (3) valor e a qualidade que eu tenho pelo preco que eu pago; (4) valor e o que eu recebo pelo o que eu dou. Considera-se entao valor percebido como a percepcao do consumidor sobre a relacao custo-beneficio sobre a manutencao da relacao com um fornecedor.

Conforme a exposicao teorica sugere-se, portanto, a relacao positiva esperada entre qualidade e valor percebidos (EGGERT e ULAGA, 2002; MARCHETTI e PRADO, 2004). No modelo proposto considera-se que ambos sao antecedentes da satisfacao, porem o impacto da qualidade no valor, no que tange a sua avaliacao de custo versus beneficio, e esperado de forma que:

H1: Quanto maior a qualidade percebida, maior sera o valor percebido.

2.2 QUALIDADE DO RELACIONAMENTO

A Qualidade do Relacionamento e sugerida por Henning-Thurau e Klee (1997) como o nivel adequacao de um relacionamento em atender as necessidades do individuo/cliente, integrando para isto os construtos de confianca, comprometimento e qualidade enquanto mediadores da satisfacao e retencao do consumidor. Prado (2004), seguindo a logica de relacao antecedente-consequente entre satisfacao e qualidade percebida propos uma adaptacao na composicao deste conceito, a ser formado por tres variaveis: a satisfacao, a confianca e o comprometimento. Esta segunda composicao foi adotada neste estudo.

Sendo assim, o conceito de satisfacao comumente trabalhado entre autores da area trata da comparacao (ou avaliacao) subjetiva dos niveis esperados e recebidos da experiencia com o bem ou servico (OLIVER, 1981; BERGAMO e GIULIANI, 2009; BARCELOS, BAPTISTA; SILVA, 2010), o qual esta relacionado ao paradigma da desconformidade (OLIVER, 1981). A relacao da qualidade percebida enquanto antecedente da satisfacao foi reconhecida nos estudos de Fornell et al (1996), Jonhson et al (2001), Prado (2004), Marchetti e Prado (2004). Neste contexto, espera-se que:

H2: Quanto maior a qualidade percebida, maior sera a satisfacao do consumidor.

Bolton (1998), McDougall e Levesque (2000), Eggert e Ulaga (2002), Marchetti e Prado (2004), Bergamo e Giuliani, (2009), tambem propoem a existencia de uma relacao positiva entre o valor percebido e a satisfacao. Sendo assim, e apresentada a H3 deste estudo:

H3: Quanto maior o valor percebido, maior sera a satisfacao do consumidor.

A confianca e tratada com grande importancia no marketing de relacionamento, visto que em sua essencia esta implicita a nocao de confidencia e confiabilidade entre parceiros numa relacao (GARBARINO e JOHNSON, 1999; GRONROOS, 1990; BERGAMO e GIULIANI, 2009; BARCELOS, BAPTISTA; SILVA, 2010). Complementando esta concepcao, Morgan e Hunt (1994) argumentam que esta dimensao existe num relacionamento quando uma parte acredita na integridade e responsabilidade do respectivo parceiro de troca, e afirmam que a dinamica global em que o mercado esta imerso traz algumas premissas como: para ser um competidor eficaz, requer que a empresa seja um cooperador confiavel na rede de relacionamento.

O comprometimento tem sido conceituado como o desejo de continuar um relacionamento e manter sua continuidade, alem de ser visto como um bom indicador de relacoes duradouras entre cliente e empresa (DWYER, SCHURR e OH, 1987). Esta variavel e estudada comumente em ambientes interorganizacionais e intraorganizacionais (MAVONDO e RODRIGO, 2001). Morgan e Hunt (1994) tambem se referem ao comprometimento como uma crenca de que a troca entre parceiros num relacionamento e tao importante como garantir o maximo de esforco para mante-lo.

A satisfacao e tida como um dos elementos da qualidade do relacionamento, e considerando suas definicoes constitutivas (satisfacao, confianca e comprometimento), podese dizer que sao complementares. A exemplo do modelo empirico de Prado (2004) e esperada uma relacao positiva entre satisfacao, confianca e comprometimento, conforme hipoteses H4 e H5:

H4: Quanto maior a satisfacao, maior sera a confianca no fornecedor de servico.

H5: Quanto maior a satisfacao, maior sera o comprometimento com o fornecedor de Servico.

A relacao entre confianca e comprometimento tambem foi delineada como relevante e positiva no estudo de Morgan e Hunt (1994) e Bergamo e Giuliani, (2009). Complementando esta afirmacao, Achrol (1991) acredita que a confianca e a maior determinante do comprometimento do relacionamento. Como o estudo em questao trata de um contexto altamente competitivo (desenvolvimento tecnologico, concorrentes proximos em nivel de concorrencia, entre outros), espera-se que esta relacao alem de ser positiva seja indicio de fortalecimento na lealdade para com o relacionamento. Neste contexto e apresentada a H6:

H6: Quanto maior a confianca no fornecedor de servicos, maior sera o comprometimento com este.

2.3 CONSEQUENTES DA QUALIDADE DO RELACIONAMENTO: LEALDADE E RESULTADO FINANCEIRO (LTR)

Apesar de primeiramente ter sido analisada numa otica mais operacional, onde seu conceito estava associado a questao de re-compra de um determinado produto ou servico (YI e JEON, 2003), Oliver (1999, p.35) atribui um significado mais profundo no que tange o julgamento de melhor opcao do consumidor pela empresa: "(...) para um consumidor se tornar leal, ele deve acreditar que uma empresa ou seu servico continua a oferecer a melhor alternativa a ser consumida". Neste trecho o autor tambem ja deixa um indicio da necessidade antecedente de confianca e comprometimento com o relacionamento.

Outra definicao e classificacao desta variavel pode ser encontrada nos estudos de Dick e Basu (1994) os quais atribuem o conceito de probabilidade de compra de determinado fornecedor, quantidade e sequencia de compras neste fornecedor num dado periodo. Os autores sugerem ainda uma classificacao em que a lealdade e tida sob quatro categorias: (1) lealdade; (2) lealdade latente; (3) falsa lealdade e (4) sem lealdade. Destas a primeira e resultado da intencao de recompra e da atitude, definindo o 'verdadeiro' estado de lealdade.

Ao relacionar a influencia da satisfacao sobre a lealdade, Oliver (1999) apresenta 6 possiveis relacoes entre estas duas variaveis, dentre as quais, se opta neste estudo por uma aproximacao da sexta, onde num momento inicial se tem o individuo satisfeito e por um processo cumulativo positivo, pode-se chegar ao estagio de lealdade. Bolton (1998) atribui uma relacao positiva, testada empiricamente em ambiente de telefonia celular, sobre a satisfacao e o tempo de retencao deste no relacionamento, ou seja, a lealdade do mesmo.

Ainda, McDougall e Levesque (2000), Hurley e Estelami (1998) comprovaram empiricamente que ha uma associacao positiva entre a satisfacao, advinda da percepcao de qualidade, sobre as intencoes futuras de compra, ou seja, a continuidade do relacionamento e consequente lealdade do individuo. Por estes motivos se espera:

H7: Quanto maior o indice de satisfacao, maior sera a lealdade.

Segundo a definicao de lealdade, Oliver (1999) ressalta que o julgamento da melhor opcao para se chegar a um estado de lealdade, e o consumidor acreditar que a empresa escolhida e a melhor opcao. Sendo assim, considera-se que alem do individuo acreditar na empresa, ele deve confiar na imagem, informacao, conhecimento, entre outros fatores que possibilitem a manutencao da escolha por um longo prazo. Ainda Gronroos (1997) ressalta a importancia das variaveis confianca e comprometimento na continuidade de uma relacao na otica de marketing de relacionamento. Desta forma, sao apresentadas as hipoteses H8 e H9,

tambem em concordancia estudos da area (PRADO, 2004; OLIVER, 1999; BERGAMO e

GIULIANI, 2009; BARCELOS, BAPTISTA; SILVA, 2010):

H8: Quanto maior a confianca no fornecedor de servicos, maior sera a lealdade com este.

H9: Quanto maior o comprometimento no fornecedor de servicos, maior sera a lealdade com este.

Entende-se por resultado financeiro o valor financeiro de um cliente considerando um tempo determinado de permanencia com a empresa fornecedora de um produto/servico. Um resultado financeiro positivo indica que o cliente e capaz de gerar lucro para a empresa no tempo estimado de calculo. Este conceito esta conectado a logica de relacionamento na medida em que manter clientes fieis sugere uma base de clientes consistente e rentavel. Yeung e Ennew (2000) testaram a relacao entre lealdade e rentabilidade, onde se esperava resultado positivo e significativo. Esta suposicao foi comprovada pelos autores por meio do uso do resultado do indice ACSI com o balanco anual das 200 maiores empresas estadunidenses. Tambem Johnson et al (2001), Guo e Jiraporn (2005), entre outros, corroboram com esta hipotese. Sendo assim, e apresentada a H10 deste estudo:

H10: Quanto maior o nivel de lealdade, maior sera o indice de LTR do consumidor.

Apos a apresentacao das hipoteses, apresenta-se o modelo proposto de estudo conforme Figura 1. O modelo e uma ampliacao dos estudos de Prado (2004) sobre qualidade do relacionamento, e agrega ao modelo de qualidade do relacionamento e lealdade um indicador de resultado financeiro, chamado de LTR.

[FIGURE 1 OMITTED]

3. METODOLOGIA

Este estudo refere-se a um survey de carater cross sectional (MALHOTRA, 2001). A dimensao da pesquisa e tracada como quantitativo-descritiva e o metodo aplicado trata-se de um hipotetico-dedutivo (GILL e JOHNSON, 1997), tendo em vista o modelo teorico sugerido para teste. Para a viabilizacao do estudo, o procedimento amostral utilizado foi caracterizado por nao probabilistico, tendo ainda sido utilizada a tecnica amostral por bola-de-neve, conforme definido por Malhotra (2001). O numero de observacoes a serem realizadas no estudo seguiu a referencia de Hair et al (2005) que sugere, no minimo, 10 observacoes por item para maior adequacao do modelo testado.

Ao final, foram 493 respostas validas sendo elas, 58% (288) referentes a usuarios de celular pre-pago e 42% (205) de usuarios de celular pos-pago. A distribuicao de genero entre os tipos de celular ocorreu de forma predominante significativa de mulheres entre os prepagos (T =48,808, p<0,001) e de homens entre os pos-pago (T=44,012, p<0,001).

A analise dos dados contempla a verificacao da validade de conteudo das dimensoes das variaveis propostas no modelo e o teste do modelo e hipoteses de estudo, entre os grupos gerados a partir da base de dados. Para operacionalizar a mensuracao das variaveis foram adaptadas do estudo de Prado (2004) as escalas de valor percebido (4 itens), satisfacao (4 itens), confianca (7 itens), comprometimento (9 itens) e lealdade (6 itens). A escala de qualidade percebida (3 itens) foi adaptada dos estudos da Anatel (1). Para a mensuracao do retorno financeiro (LTR) foi utilizado o modelo de Francisco-Maffezzolli (2007), sendo este derivado do modelo proposto por Ryals (2005). Desta forma, duas fontes de dados foram utilizadas: Primarias--para coleta das informacoes diretamente com o consumidor, e secundarias--para coleta de informacoes sobre as empresas presentes na base de dados para o calculo de LTR.

O processo de analise de resultados foi submetido a seis principais etapas: (1) preparacao da base, onde foi verificada a estatistica descritiva univariada e multivariada; (2) verificacao do modelo de mensuracao para a analise estrutural proposta com uso de analise fatorial exploratoria da consistencia interna de cada dimensao, definida pelo Alpha de Cronbach e a analise fatorial confirmatoria para estabelecer a validade convergente e discriminante de cada construto do modelo; (3) determinacao do calculo do tempo de vida rentavel, onde foram definidos os parametros para estimar o valor de resultado financeiro do projeto; (4) geracao dos grupos para analise; (5) verificacao do modelo estrutural proposto por meio de equacoes estruturais, e (6) uso de regressao logistica para verificar a disposicao de troca, conforme apresentado na sequencia.

4. RESULTADOS

A apresentacao dos resultados esta disposta na seguinte ordem: caracterizacao da amostra, breve descricao da preparacao dos dados e verificacao do modelo para a mensuracao proposta, geracao dos grupos, sendo por fim apresentado com maior enfase os resultados obtidos com o modelo.

4.1 CARACTERIZACAO DA AMOSTRA

Do total de respondentes, 53% foram mulheres e 47% homens. A caracterizacao de poder de compra, segundo o criterio Brasil, indicou 38% B2, 27% B1, 26%C, 7% A2 e 1% D e 1% A1. Em relacao a proporcao de operadoras existentes na base, 51% dos casos foram Tim, 22% Vivo, 16% Claro e 11% Brasil Telecom. Entre as operadoras houve maior concentracao de pos-pagos na Tim e de pre-pagos na Claro. Esta informacao ocorreu de forma proporcional a presenca total de cada operadora na base.

O tempo de duracao medio de relacionamento com cada operadora foi de 49,2 meses (dp=34,944). Sendo 41,8 (dp=27,598) entre pre-pagos e 59,6 (dp=41,091) pos-pagos. Esta informacao foi perguntada diretamente ao cliente.

Sobre o historico de uso, 56% dos 493 avaliadores ja tiveram mais de uma operadora. Sendo assim, os dados foram obtidos considerando o relacionamento com a atual operadora. A intencao de troca mencionada revelou que 69% do total ja pensaram em trocar de operadora. Destes 308 respondentes, 55% trocaria possivelmente em menos de 6 meses e 37% possivelmente em 1 ano.

O valor e tempo de recarga foram perguntados tambem diretamente com o objetivo de obter um valor medio para estimar o tempo de vida rentavel. Desta forma, entre usuarios de pre-pagos, na media o valor mensal de contribuicao foi de R$ 25,00 (dp=11,150). Ja entre os usuarios de pos-pago foi de R$ 128,00 (dp=91,348). Dos dados apresentados e possivel verificar a alta variabilidade indicada pelo desvio padrao, o que demonstra grande heterogeneidade na amostra do estudo.

4.2 PREPARACAO DOS DADOS E VERIFICACAO DO MODELO

O resultado da analise fatorial confirmatoria constatou o carater unidimensional da satisfacao (Alfa de 0,912), do valor percebido (Alfa de 0,887) e da lealdade (Alfa de 0,896). Tambem a confianca e o comprometimento rejeitaram o carater multidimensional proposto e carregaram apenas uma unica dimensao com respectivos Alfas de 0,896 e 0,912. Apenas o construto qualidade percebida suportou mais de uma dimensao, sendo elas: qualidade dos servicos e atendimento (Alfa de 0,894) qualidade tecnica, 0,876 e condicoes de pagamento (Alfa de 0,733).

Posteriormente, na analise fatorial confirmatoria dos 47 indicadores propostos inicialmente, 44 foram mantidos com o melhor valor de ajustamento do modelo. Foram tambem observados os valores de confiabilidade composta (CONF), os quais deveriam estar acima de 0,7 e de variancia media extraida (AVE), os quais deveriam estar acima de 0,5 (Hair et al, 2005), como indicadores de validade convergente. Os resultados obtidos foram considerados plausiveis para a analise efetuada. A validade discriminante foi observada por meio da correlacao das variaveis duas a duas, sendo entao observada a diferenca entre o quiquadrado livre e o fixo (1). Os valores aceitaveis deveriam ser inferiores a 3,5. Os resultados demonstraram que nao houve sobreposicao de construtos. O mesmo procedimento foi observado em Moura (2005). Os indices de ajustamento do modelo estrutural, considerando ainda apenas as variaveis latentes, foi aceitavel e satisfatorio segundo Hair et al (2005): [X.sup.2] = 643,629, GL = 155, p<0,001, [X.sup.2]/GL = 4,152, NFI = 0,925, CFI = 0,942 e RMSEA = 0,080.

4.3 DETERMINACAO DO INDICADOR DE RESULTADO FINANCEIRO

Para a determinacao do indicador de resultado financeiro (LTR), dadas as limitacoes encontradas em campo (como a impossibilidade de acesso aos historicos do cliente diretamente na operadora), foi utilizada a seguinte estrutura de calculo: Receita bruta mencionada pelos clientes e a margem EBITDA (relacao entre EBITDA, ou seja, lucro liquido antes dos impostos, e receita liquida). Esta margem contempla a contribuicao operacional de cada empresa. Devido a falta de informacoes precisas sobre o detalhamento dos custos por cliente em cada operadora, este indicador foi utilizado sobre cada cliente para verificar a margem de contribuicao individual. No caso de usuarios de celular pre-pago em que as recargas foram indicadas em periodo superior ou inferior a um mes, os valores foram convertidos ao periodo mensal para que o calculo pudesse ser efetuado.

O principio utilizado para a determinacao do valor foi a soma entre o valor historico e valor futuro, considerado as formulas financeiras de valor futuro e valor presente, respectivamente. A taxa de desconto utilizada foi a taxa de juros Selic. O tempo historico e o tempo projetado de permanencia na carteira foram informacoes obtidas diretamente com o cliente. Para determinar o tempo projetado de continuidade, este elemento foi tratado como expectativa de permanencia com a operadora, conforme formula a seguir:

LTR = VH (valor historico) + VF (valor futuro) VH = M [(1 + i).sup.n], onde:

M = Margem de contribuicao (valor declarado mensal do cliente x margem Ebitda da operadora)

i = taxa de juros Selic

n = tempo historico de meses declarado pelo cliente.

VF = M [(1 + i).sup.n], onde:

M = Margem de contribuicao (valor declarado mensal do cliente x margem Ebitda da operadora)

i = taxa de juros Selic

n = intencao de continuidade (em meses), declarado pelo cliente.

4.4 GRUPOS PARA ANALISE DA PROPENSAO DE TROCA DE OPERADORA

Entre os 493 respondentes, conforme observado na categorizacao da amostra, ha uma consideravel heterogeneidade na base total, desde genero, idade, tipo de celular, entre outros aspectos ja comentados no item 4.1. Sendo assim, foi utilizada uma informacao declarada pelo consumidor durante a coleta de dados primaria, na condicao de "trocar (1)" ou "nao trocar (0)" de operadora de celular, considerado o atual servico recebido.

Ressalta-se que entre os consumidores que estariam pre-dispostos para a troca, 308 casos, sendo 48% mulheres e 52%homens, e 57% celulares pre-pagos e 43% pos-pagos. Ja os consumidores com menor pre-disposicao para troca, 185 casos, sao compostos de 61% mulheres e 39% homens, e 60% celulares pre-pagos e 40% pos-pagos. Sendo assim, nao ha diferenca significativa entre a composicao dos grupos apenas pelas variaveis categoricas genero e tipo de celular.

Para verificar ainda as diferencas de avaliacao entre os grupos (que declararam "troca" --GRUPO 1 ou "nao troca"--GRUPO 2), foi contrastada a media ponderada de cada variavel latente entre os grupos, com as respectivas diferencas, conforme segue apresentado na Tabela 1:
Tabela 1: Diferenca entre Grupos

Grupos **   Variaveis           Valor t    Significancia    Media

T           Lealdade *          T=11,639      p<0,001        4,93
NT                                                           6,32
T           Confianca *         T=10,078      p<0,001        3,91
NT                                                           5,01
T           Comprometimento *   T=11,069      p<0,001        3,77
NT                                                           4,97
T           Satisfacao *        T=10,200      p<0,001        4,64
NT                                                           5,85
T           Valor percebido *   T=7,762       p<0,001        5,30
NT                                                           6,17
T           Qualidade           T=8,092       p<0,001        4,71
NT            percebida *                                    5,35
T           LTR (indicador de   T=0,009       P=0,993      6.446,68
NT            receita)                                     6.458,16
T           Tempo com empresa   T=0,345       P=0,730        59,79
NT            (meses)                                        58,61

Grupos **   Desvio Padrao   Total de casos

T               1,44             308
NT              1,17             185
T               1,27             308
NT              1,11             185
T               1,24             308
NT              1,11             185
T               1,34             308
NT              1,15             185
T               1,23             308
NT              1,17             185
T               0,90             308
NT              0,82             185
T             12496,85           308
NT            15514,42           185
T              31,94             308
NT             39,32             185

* Os construtos foram avaliados por meio de media ponderada

** T = Trocar (1) / NT = Nao Trocar (0)

Fonte: Elaborado pelos autores


Nas diferencas apresentadas, alem das consideracoes ja realizadas sobre os indicadores que deram origem aos grupos, pode ser ainda considerada a distincao das avaliacoes gerais, onde, o grupo 1 (intencao de troca de operadora) apresenta avaliacoes significativamente menores para os construtos de lealdade, confianca, comprometimento, satisfacao, valor percebido e qualidade percebida com a respectiva operadora. Tal avaliacao parece coerente, uma vez que, aqueles que declaram maior avaliacao de lealdade, e qualidade do relacionamento, intencionam ficar com os servicos da empresa por mais tempo.

E relevante salientar que os valores de tempo com a empresa, bem como o indicador de receita com a empresa, nao demonstraram diferenca significativa. Segundo a literatura de relacionamento, espera-se que clientes mais leais sejam mais lucrativos e permanecam por maior tempo com a empresa. No entanto, tal premissa nao foi verificada na amostra analisada. Tal situacao pode ser uma condicao da propria composicao heterogenea da amostra, ou ainda, ser um reflexo da dinamica do mercado de telefonia celular, como a intensidade da concorrencia. Salienta-se que, devido ao carater nao-probabilistico, e reconhecida a incapacidade de extrapolacao para os demais usuarios.

5. TESTE DO MODELO E HIPOTESES

O modelo estrutural foi testado com o uso de 6 variaveis latentes e uma diretamente observavel, conforme ja apresentado. O resultado das hipoteses testadas pode ser observado na Tabela 2, com os contrastes entre os grupos observados:
Tabela 2--Coeficientes Padronizados (Paths) Estimados para as
Relacoes Teoricas Propostas no Modelo

Relacao Estrutural              Grupos   Coef.         t-value *
                                         Padronizado

Qualidade Percebida [right      T         0,751         8,861 *
  arrow] Valor Percebido        NT        0,690         7,664 *
Qualidade Percebida [right      T         0,505         5,179 *
  arrow] Satisfacao             NT        0,182         2,385 *
Valor Percebido [right arrow]   T         0,390         4,658 *
  Satisfacao                    NT        0,766         9,286 *
Satisfacao [right arrow]        T         0,634         9,621 *
  Confianca                     NT        0,669         8,239 *
Satisfacao [right arrow]        T         0,354         5,569 *
  Comprometimento               NT        0,354         4,648 *
Confianca [right arrow]         T         0,629         8,063 *
  Comprometimento               NT        0,685         7,122 *
Satisfacao [right arrow]        T        -0,033        -0,389
  Lealdade                      NT       -0,285        -0,915
Confianca [right arrow]         T         0,111         0,865
  Lealdade                      NT       -0,581        -0,961
Comprometimento [right arrow]   T         0,792         4,411 *
  Lealdade                      NT        0,680         1,974 *
Lealdade [right arrow] LTR      T        -0,035        -0,588
                                NT        0,031         0,411

Relacao Estrutural              Grupos   Hipotese   Status de
                                                      Verificacao
                                                        da hipotese

Qualidade Percebida [right      T         H1          Confirmada
  arrow] Valor Percebido        NT                    Confirmada
Qualidade Percebida [right      T         H2          Confirmada
  arrow] Satisfacao             NT                    Confirmada
Valor Percebido [right arrow]   T         H3          Confirmada
  Satisfacao                    NT                    Confirmada
Satisfacao [right arrow]        T         H4          Confirmada
  Confianca                     NT                    Confirmada
Satisfacao [right arrow]        T         H5          Confirmada
  Comprometimento               NT                    Confirmada
Confianca [right arrow]         T         H6          Confirmada
  Comprometimento               NT                    Confirmada
Satisfacao [right arrow]        T         H7        Nao-Confirmada
  Lealdade                      NT                  Nao-Confirmada
Confianca [right arrow]         T         H8        Nao-Confirmada
  Lealdade                      NT                  Nao-Confirmada
Comprometimento [right arrow]   T         H9          Confirmada
  Lealdade                      NT                  Nao-Confirmada
Lealdade [right arrow] LTR      T        H10        Nao-Confirmada
                                NT                  Nao-Confirmada

* Resultados significativos a 0,001

Grupo T (troca): [chi square] = 604,257 GL = 180, p<0,001,
[chi square]/GL = 3,357, NFI = 0,870, CFI = 0,904 e
RMSEA = 0,088 Grupo NT (nao troca): [chi square] = 446,085
GL = 180, p<0,001, X2/GL = 2,478, NFI = 0,857, CFI = 0,908 e
RMSEA = 0,090

Fonte: Elaborado pelos autores


Os indices de ajustamento de ambos os modelos podem ser considerados plausiveis, ja que ao rodarem juntos na CFA proporcionaram ajustes mais adequados. Entretanto, entendese que uma base com mais observacoes para cada um dos grupos pode oferecer melhor adequacao. O resultado do modelo trata da avaliacao dos 493 casos observados, sendo 185 do grupo NT (Nao Trocaria) e 308 do grupo T (Trocaria), conforme ja apresentado.

A hipotese 1, apoiada nas constatacoes de Eggert e Ulaga (2002) e Marchetti e Prado (2004), previa uma relacao positiva e significativa. A interpretacao desta relacao permeia a situacao onde, quanto maior a qualidade percebida (definida por qualidade tecnica, de atendimento e de condicoes de pagamento), maior o impacto na avaliacao do valor percebido (definido por esforco, tempo e custo do relacionamento). Ambos os grupos comprovaram esta situacao ([beta]=0,751, p<0,001 para o grupo T e [beta]=0,690, p<0,001 para o grupo NT). Tal situacao pode trazer a reflexao que, indiferente ao perfil do consumidor em relacao a tendencia de troca ou nao de marcas de consumo (em especial no contexto de telefonia celular), a avaliacao de qualidade e valor sao importantes. A relacao entre qualidade percebida e satisfacao (H2), sendo esta ordem respeitada como antecedente e consequencia, respectivamente, foi reconhecida nos estudos de Fornell et al (1996), Jonhson et al (2001), Marchetti e Prado (2004), entre outros.

O valor percebido e tambem considerado um antecedente da Satisfacao e contempla a dimensao economica (custo versus beneficio) do modelo proposto. Esta relacao ja observada em Bolton (1998), McDougall e Levesque (2000), Eggert e Ulaga (2002) e Marchetti e Prado (2004) e positiva e relevante, conforme observado do grupo T. Entretanto, e relevante considerar o fato da qualidade percebida nao corresponder ao unico antecedente da satisfacao, de acordo com a literatura. Portanto, pode ser que para as pessoas que tenham tendencia a manterem-se com as marcas, sem trocas constantes, outros elementos, como a confianca e o comprometimento, sejam mais relevantes.

As hipoteses 4, 5, e 6 as quais replicam a proposta de Prado (2004) sobre a qualidade do relacionamento foram comprovadas pelo grupo T e NT. Garbarino e Johnson (1999) evidenciam a possivel complementaridade entre tais variaveis, tornando plausivel a relacao positiva e significativa entre satisfacao, confianca e comprometimento.

Apesar de estudos como McDougall e Levesque (2000),Hurley e Estelami (1998), Bergamo e Giuliani (2009) e Barcelos, Baptista e Silva (2010), comprovarem empiricamente a relacao positiva e significativa da satisfacao em relacao a intencao de compra e continuidade do relacionamento, sendo estes, indicadores da lealdade do individuo, e relevante mencionar que esta relacao e encontrada na literatura de forma controversa. Alguns autores como Jones e Sasser (1995) comentam sobre uma relacao nao necessariamente linear deste relacionamento (satisfacao--lealdade). Alias, os autores comentam que caracteristicas ambientais como alto custo de troca, vantagens promocionais e regulamentacoes governamentais, sao alguns fatores que estimulam a falsa lealdade e uma relacao 'fraca' com a satisfacao, visto que neste contexto o tempo de relacionamento nao e definido unicamente pela escolha do usuario, mas por outras variaveis que oferecem conveniencia ou certa limitacao. No presente estudo, ambos os grupos nao comprovaram tal relacao, conforme a hipotese 7 demonstra.

A hipotese 8, que previa uma relacao significativa entre a confianca e a lealdade, nao foi confirmada por nenhum dos dois grupos. Para Oliver (1999) a continuidade da relacao entre empresa e consumidor ocorre em partes pela crenca de que a escolha e a mais adequada. Neste momento, a confianca na marca, na empresa ou na imagem (por exemplo) seriam fortes indicadores para a lealdade a mesma. Esta relacao, no entanto, rejeitada no ambiente de telefonia celular, pode ser compreendida pelo proprio contexto brasileiro, se for considerado alguns elementos como as taxas de reclamacao entre todas as operadoras no pais, de acordo com os registros do Procon, e talvez as caracteristicas da propria estrutura do mercado (oligopolio).

A relacao do comprometimento com a lealdade, presentes na H9 foi confirmada apenas pelos dois grupos. Este resultado concorda com Groonros (1997) e Bergamo e Giuliani (2009) ao afirmar a importancia deste construto na continuidade de um relacionamento, e tambem com Oliver (1999) ao propor a compreensao da lealdade por fases, onde, quanto maior o comprometimento, maior a probabilidade de desencadear uma situacao de lealdade afetiva ou conativa em lealdade de acao.

Ja a hipotese 10, onde era esperada uma relacao tambem positiva entre a lealdade e o indice de retorno financeiro (LTR), apesar da relacao positiva apontada para esta hipotese (YEUNG e ENNEW, 2000; JOHNSON et al, 2001; GUO e JIRAPORN, 2005), alguns autores ja questionaram sobre a linearidade e a significancia da afinidade dos construtos. Gurau e Ranchhod (2002) comentam sobre a dificuldade de obter uma relacao positiva considerando a subjetividade da mensuracao das variaveis latentes e o vies que o cruzamento de dados pode ter devido algum outro fator. Nas limitacoes levantadas pelos autores, foi mencionado o tipo de coleta (cross sectional). E possivel que acompanhamentos longitudinais possam oferecer informacoes mais concretas. Sendo assim, em ambos os grupos nao houve comprovacao desta hipotese.

De forma complementar aos objetivos do estudo, tambem foram observados os efeitos indiretos no modelo estrutural. Os valores da Tabela 3 demonstram os resultados obtidos:
Tabela 3--Efeitos Indiretos Entre Os Construtos Latentes Do
Modelo Estrutural

Efeitos Indiretos entre os            Coeficientes     Coeficientes
construtos modelo                     padronizados *   padronizados *
                                        (Grupo T)        (Grupo NT)

Qualidade Percebida [right              0,293 *        0,529 *
  arrow] Satisfacao
Qualidade Percebida [right              0,506 *        0,476 *
  arrow] Confianca
Valor Percebido [right arrow]           0,247 *        0,513 *
  Confianca
Qualidade Percebida [right              0,601 *        0,577 *
  arrow] Comprometimento
Valor Percebido [right arrow]           0,294 *        0,622 *
  Comprometimento
Satisfacao [right arrow]                0,399 *        0,458 *
  Comprometimento
Qualidade Percebida [right              0,506 *        0,492 *
  arrow] Lealdade
Valor Percebido [right arrow]           0,247 *        0,530 *
  Lealdade
Satisfacao [right arrow]                0,666[??] *    0,976 *
  Lealdade
Confianca [right arrow] Lealdade        0,498 *        0,900 *

* valores significativos a 0,001

Fonte: Analise de dados do projeto


Os efeitos indiretos demonstram que, de forma geral (7 das 10 relacoes indiretas), os construtos de avaliacao do relacionamento, em especial, que explicam a satisfacao e a lealdade, podem ser observadas com maior peso entre as avaliacoes do grupo que nao trocaria. A investigacao destes efeitos e relevante na medida em que o passo seguinte do estudo foi o de verificar a pre-disposicao de troca entre operadoras, considerando o possivel poder de explicacao destes construtos. Sendo assim, efeitos diretos e indiretos podem auxiliar na compreensao do comportamento destas variaveis, uma vez que a linearidade de algumas relacoes, por exemplo, entre satisfacao e lealdade, pode nao ser suficiente para compreender os resultados obtidos.

6. AVALIACAO DA PRE-DISPOSICAO DE TROCA ENTRE OPERADORES DE TELEFONIA CELULAR

Alem da avaliacao estrutural realizada, a qual demonstra de forma predominante relacoes lineares entre os construtos analisados, para avaliar a pre-disposicao de troca dos respondentes, foi utilizado de forma complementar um modelo de regressao logistica para se tentar mapear a disposicao de troca do consumidor. Este modelo analitico segue os principios da regressao multipla com a condicao da variavel dependente ser categorica, conforme formula descrita abaixo:

[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII]

Neste caso, as variaveis independentes podem ser categoricas ou continuas. A equacao de origem explica a probabilidade de Y ocorrer quando Xi ocorrerem (FIELD, 2005). Sendo assim, para avaliar quais elementos podem intervir na condicao de "troca" ou "nao troca" dos consumidores, em relacao as respectivas operadoras de telefonia celular, foram testados (em carater de variavel continua) os construtos de avaliacao do relacionamento com as respectivas medias ponderadas. Tambem foram testadas variaveis categoricas como genero, tipo do celular (pre ou pos pago), e continuas como o tempo de relacionamento com a operadora (em meses) e o valor declarado de investimento com o servico, indicado neste estudo como o LTR.

Para conduzir essa analise duas etapas foram realizadas. Na primeira, foram selecionados casos aleatorios, de acordo com a transformacao aleatoria de numeros pelo SPSS. Foi entao selecionada 70% da amostra, ou seja, 348 casos. Os resultados com esta parte inicial de respondentes indicaram indices de ajuste aceitaveis para a situacao analisada. Sendo assim, foi considerado o step 2 (segundo o modelo Forward:LD) como o de maior adequacao (Chi-square=86,858; df=2; p<001). O valor Hosmer e Lemeshow tambem foi adequado (Chisquare=3,009; df=8; p=0,934). A capacidade de previsao foi de 73%. As variaveis de maior relevancia para o modelo foram satisfacao e lealdade respectivamente, com valores exp(B) de 0,593 para lealdade e 0,616 para satisfacao.

Posteriormente, foi conduzido o modelo de regressao logistica para toda a base de dados, com o metodo forward LR. Sendo assim, sao calculados automaticamente varios modelos, ate o melhor ajuste. Em especial, neste estudo e considerado o modelo 2 (step2), com Chi-square = 131,616, df=1, p<0,001. Segundo o indice de ajuste Hosmer e Lemeshow (Chi-square = 3,519, df = 8, p=0,898), os valores sao plausiveis (Outros indices de ajuste: 2log likelihood=520,813 / Cox&Snell=0,234 / Nagelkerke R square= 0,319). O poder de previsao do modelo e de 73,4%. Os valores confirmaram os resultados encontrados no teste realizado com parte da amostra, sendo esta escolhida de forma aleatoria.

Sobre as variaveis em teste, apenas lealdade e satisfacao foram relevantes para identificar fatores que podem interferir sobre o comportamento de troca, conforme mostra a Tabela 4.

Sobre este resultado, destaca-se que os demais construtos (qualidade, confianca, comprometimento e valor percebido), apesar de tambem serem indicados na literatura como variaveis que podem intervir na atitude do consumidor em manter ou trocar de fornecedor, nao foram distintivos para o comportamento de troca no presente estudo, o que sugere uma reflexao sobre os resultados do modelo estrutural. Apesar das relacoes diretas e positivas entre os construtos, conforme apresentado na Tabela 2, as informacoes que podem ser determinantes para o comportamento de troca sao reduzidas (sugere-se aqui o papel da satisfacao e da lealdade), bem como nao lineares. Sendo assim, entende-se que o uso de modelos analiticos complementares sao uteis na medida em que se busca explicar, sob diferentes perspectivas, o efeito da avaliacao do consumidor sobre as variaveis estudadas.

De acordo com os valores apresentados na Tabela 1, os construtos lealdade e satisfacao foram maiores, o que pode ja indicar maior importancia relativa destes itens na explicacao deste modelo, alem de corroborar com os resultados da regressao logistica.

Tambem parece relevante comentar que, conforme a literatura de relacionamento, o valor de resultado financeiro e o tempo de relacao com a operadora deveriam ser maiores e significativos para o grupo NT. No entanto, tal resultado nao foi observado. Esta situacao pode ser compreendida pelo perfil da amostra (nao probabilistico e com grande heterogeneidade), ou ainda pelo proprio perfil do setor analisado, no qual as promocoes e ofertas disponiveis ao consumidor conduzem a uma dinamica de comportamento diferenciada e pouco previsivel.

Sendo assim, e possivel dizer que quanto mais insatisfeito estiver o consumidor, maior sera a tendencia a troca. Utilizando o valor Exp(B) como referencia, calcula-se a probabilidade de troca de acordo com os elementos avaliados. Sendo assim, com relacao a lealdade, a probabilidade de troca do consumidor e reduzida para 0,362 ((0,569)/1+0,569). Ja a satisfacao oferece uma condicao de reducao de troca de operadora de 0,389 ((0,638)/1+0,638). Tal situacao demonstra a importancia destes elementos sobre a avaliacao do consumidor em relacao ao respectivo comportamento de compra.

7. DISCUSSAO DOS RESULTADOS

O contexto de telefonia celular demonstrou, conforme a analise estrutural, que a satisfacao nao e determinante (ao menos para os consumidores analisados) da lealdade. Apenas por estarem satisfeitos, nao foi constatada de forma direta e linear a expectativa positiva de continuidade do relacionamento. Situacao oposta foi observada em Moura (2005), que comprova a relacao positiva e relevante entre as variaveis tambem no contexto de telefonia celular. Esta situacao demonstra que ainda sao necessarios outros estudos que investiguem e aprofundem o assunto. Segundo o trabalho da autora, as medias obtidas para mensurar a satisfacao foram superiores do que as registradas neste estudo. Alem da especificidade do estado, outras variantes como o uso de escala likert de 5 pontos podem ter sido alguns fatores determinantes para o contraste dos resultados obtidos.

Por outro lado, estas duas variaveis demonstraram maior influencia sobre a compreensao da intencao de troca entre os consumidores. Sendo assim, e possivel sugerir que apesar de nao ter sido observada relacao direta e linear entre a satisfacao e lealdade, a avaliacao destes dois elementos e relevante para o comportamento de troca. De acordo com os valores indiretos apontados na Tabela 3, a relacao e relevante. De acordo com os resultados da regressao logistica, individuos que se manifestam com menor avaliacao sobre a satisfacao e lealdade, tendem a trocar de operadora (ao menos no curto prazo, conforme declarado pelos respondentes).

Ja a relacao da confianca, considerada um ingrediente fundamental para o desempenho satisfatorio do relacionamento (GARBARINO e JOHNSON, 1999; DWYER, SCHURR e OH, 1987; MORGAN e HUNT, 1994), foi comprovada como construto antecedente da lealdade em Prado (2004) e Sidersmukh, Singh e Sabol (2002). Apesar de a relacao direta ter sido rejeitada, o impacto da confianca no comprometimento foi relevante, o que torna possivel considerar que a confianca exerce certa influencia na lealdade por intermedio do comprometimento do usuario. No ambiente pratico e plausivel imaginar que o usuario do servico receba certos estimulos para confiar na operadora (como a imagem, o atendimento, os servicos prestados, entre outros). Ao desenvolver o sentimento de confianca pela empresa (em caso positivo), tende a ser desencadeado o desejo de continuidade e da crenca de que a empresa e a melhor opcao para resolver seus problemas e necessidades. Este fato, se confirmado, tende a manter o cliente leal a companhia. No entanto, esta variavel parece nao impactar diretamente a pre-disposicao para troca de operadora, conforme resultado da regressao logistica.

Soma-se a este contexto a influencia positiva da satisfacao sobre o comprometimento, conforme proposta de Prado (2004) e Bergamo e Giuliani (2009), com base na premissa de que o comprometimento do consumidor levaria a uma relacao duradoura entre o cliente e a empresa. Dessa forma, a satisfacao e tida como um dos vetores que ocasionam tal comportamento. Alem disto, salienta-se o peso positivo e significativo da variavel valor percebido sobre a satisfacao, o qual permite a inferencia da valorizacao da perspectiva economica proposta por Zeithmal (1988) e reforcada por Marchetti e Prado (2004), na avaliacao da satisfacao do consumidor. Estas constatacoes foram observadas apenas na analise estrutural, sendo assim, apesar do impacto positivo e significativo das hipoteses, sugere-se que estudos futuros investiguem sob outras perspectivas a influencia e o poder de explicacao destes construtos sobre o comportamento de troca.

Por fim, sob a otica do marketing de relacionamento, a nao comprovacao estatistica das relacoes propostas nas hipoteses 7, 8, 10 e parcialmente na 2 e na 9, pode ter ocorrido pela particularidade do segmento, como a estrutura de oferta, ou pelo perfil heterogeneo da amostra, fato que pode sugerir investigacoes futuras especificas por perfil de usuario.

8. CONSIDERACOES FINAIS

Embora seja reconhecida a despretensao de generalizacao dos achados empiricos reportados neste documento, e possivel destacar como principal contribuicao o uso de regressao logistica para compreender (e tentar prever) o comportamento do consumidor, bem como buscar a complementaridade dos resultados, obtidos com o teste do modelo estrutural.

De forma direta e linear (resultados obtidos com o uso de equacoes estruturais), em especial, a relacao entre satisfacao, lealdade e o indice de resultado financeiro nao foram confirmados. Tal situacao sugere certa inquietacao, uma vez que as premissas teoricas implicam na relacao positiva destes construtos, respectivamente.

Salienta-se que, por meio do uso de regressao logistica, a satisfacao e a lealdade do consumidor sao elementos relevantes e essenciais para determinar o comportamento de "troca" do consumidor. Ou seja, a avaliacao de tais variaveis e relevante, porem nao lineares, conforme demonstrado nos resultados do modelo estrutural. Tal resultado proporciona condicoes de confirmar as premissas encontradas na literatura sobre a avaliacao do relacionamento com o consumidor.

Sendo assim, sugere-se que o uso de regressao logistica, como forma de compreender a disposicao de troca do consumidor, proporcionou melhor compreensao dos resultados obtidos. A SEM demonstrou basicamente relacoes linerares entre variaveis. Ja o uso de regressao logistica permite reconhecer as variaveis independentes que melhor explicam o comportamento observado. Desta forma, o uso destas ferramentas estatisticas permitiu, de forma complementar uma a outra, a compreensao da disposicao do consumidor em trocar de operadora.

Por fim, o estudo expressa a riqueza de informacoes provenientes das interacoes entre as bases comportamentais e de resultado financeiro na avaliacao do relacionamento com as empresas, e sugere que o controle sistematizado destas informacoes possa auxiliar estrategias de marketing das operadoras de telefonia celular.

Recebido em 27/01/2010; revisado em 31/05/2010; aceito em 12/08/2010; disponivel em 21/10/2011

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Eliane Cristine Francisco Maffezzolli ([dagger]) Pontificia Universidade Catolica do Parana (PUCPR)

Paulo Henrique Muler Prado ([OMEGA])

Universidade Federal do Parana (UFPR)

Wesley Vieira da Silva ([yen])

Pontificia Universidade Catolica do Parana (PUCPR)

Renato Zancan Marchetti([pounds sterling])

Pontificia Universidade Catolica do Parana (PUCPR)

Correspondencia autores *:

([dagger]) Doutora em administracao pela Universidade Federal do Parana (UFPR).

Vinculacao: Pontificia Universidade Catolica do Parana (PUCPR)

Endereco: Rua Imaculada Conceicao, no.1155, Prado velho, Curitiba/PR, 80215901.

E-mail: eliane.francisco@pucpr.br

Telefone: (41) 3271 1476

([OMEGA]) Doutor em administracao pela Fundacao Getulio Vargas (FGV).

Vinculacao: Universidade Federal do Parana (UFPR).

Endereco: Av. Pref. Lothario Meissner, 632 2[degrees] andar, Jardim Botanico, Curtiba/PR 80210170.

E-mail: pprado@ufpr.br

Telefone: (41) 3360-4365

([yen]) Doutor em engenharia de producao pela Universidade Federal de Santa Catarina (UFSC).

Vinculacao Pontificia Universidade Catolica do Parana (PUCPR).

Endereco: Rua Imaculada Conceicao, no.1155, Prado velho, Curitiba/PR, 80215901.

Email: wesley.vieira@pucpr.br

Telefone: (41) 3271 1476

([pounds sterling]) Dr. em Sciences de Gestion, HECParis.

Vinculacao: Pontificia Universidade Catolica do Parana (PUCPR).

Endereco: Rua Imaculada Conceicao, no.1155, Prado velho, Curitiba/PR, 80215901.

E-mail: renato.zancan@pucpr.br

Telefone: (41) 3271 1476

Nota do Editor: Esse artigo foi aceito por Antonio Lopo Martinez

Esta obra esta licenciada sob a Licenca Creative Commons--Atribuicao-Uso nao-comercial-Compartilhamento pela mesma licenca 3.0 Unported License

(1) A escala foi adaptada da pesquisa de satisfacao da Anatel de 2004.
Tabela 4: Variaveis Significativas da Regressao Logistica

Variavel       B       Wald    Exp(B)

Lealdade     -0,569   29,141    0,569
Satisfacao   -0,449   16,530    0,638
Constante     6,101   97,865   446,114

* valores significativos a p<0,001.

Fonte: Elaborado pelos autores
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