The Impact of Brand Image and Customer Commitment on Loyalty: An Empirical Study of Automobile Sector

Corporate brand image has been assessed as an important antecedent of customer commitment and loyalty. Corporate brands help companies achieving higher performance, such as sales. A poor brand image will lead to disaster, and lose customers. Marketing exists to deliver more value to satisfy customers as well as build a long-term and mutually profitability relationship with customers. If a firmâ€™s products or services do not satisfy or meet the customerâ€™s needs and wants, all the strategies are insufficient. With loyal customers, companies can have higher market share and reduce the operating cost. This initial study was from relevant literature, then set up research structure and hypotheses. Survey was employed, and respondents were collected from automobile sector in Taiwan. There were 170 usable questionnaires to analyze normality, convergent and discriminant validities, and SEM model by PASW 18 and AMOS 18.0. The research found that corporate brand image significantly affects customer commitment and loyalty, and customer commitment has strong impact on customer loyalty for the sample. Therefore, firms need to specifically focus on a long-term and mutually profitability relationship with a customer and create loyalty as competitive advantages in the markets.


Introduction
Because of global financial crisis in 2007, most countries had high unemployment rates along with low consumer confidence, escalating inflation, and rising gas and food prices (United Nations, 2012). The vehicle markets had a great change in 2008, and Toyota took the place of GM to become the first largest vehicle sales company in the world because of its quality and fuel-efficient vehicles. From 2009 to 2010, Toyota recalled more than 8 million cars and trucks worldwide in several vehicle problems, such as floor mat and accelerator, and halted production and sales briefly. Toyota sales volume is going down again, and its position is replaced by GM and Volkswagen in 2011 due to the workers' strike in France, a 311 earthquake in Japan, and a flood disaster in Thailand. Martenson (2007) indicated that customers to a favorable store image may affect perception of store brand. De Chernatony and Harris (2000) reported that corporate brand is vital because positive corporate brands help companies achieving higher performance, such as sales. Ogba and Tan (2009) announced that a poor brand image will lead to disaster, and lose customers. Marketing exists to deliver more value to satisfy customers as well as build a long-term and mutually profitability relationship with customers (Kotler, 2005). If a firm's products or services do not satisfy or meet the customer's needs and wants, all the strategies are insufficient. The ultimate goal for companies to build customer loyalty is generally the central marketing activities (Eakuru & Mat, 2008;Oliver, 1997). With loyal customers, companies can have higher market share and reduce the operating cost (Aaker, 1997). Reichheld and Sasser (1990) indicated that an improvement of 5 percent in customer retention leads to an increase of 25 percent to 75 percent in profit. Wills (2009) reported that it costs more than five times as much to obtain a new customer than to keep an existing one. Moreover, with loyal customers, for example, companies can increase their revenue. First, loyal customers are less price sensitive, and the premiums of loyal customers increase 8 percent annually in the personal insurance industry (Reichheld & Teal, 1996). Second, loyal customers are willing to purchase frequently, try the firms' other products or services, and bring new customers to the firms (Reichheld & Sasser, 1990). At Northwestern Mutual, the contribution of 55 percent sales is from existing customers (Reichheld & Teal, 1996). Reichheld and Teal (1996) further indicate that customer loyalty provides a foundation for a firm to examine their marketing strategy, relationship quality improvement activities, and value creation program. Day (1969) introduced the concept of commitment to loyalty studies, and reported that commitment to the brand is necessary in determining the loyalty. The study seeks to develop a conceptual framework of brand image on customer commitment and loyalty. Therefore, the purpose of study is to evaluate how corporate brand image affects customer commitment as well as impact on loyalty in automobile sector.

Literature Review
Corporate brand image: Davies, Chun, Da Silva and Roper (2003) indicated that anything can be a brand, such as a company, corporate or name. Keller (1993) defined brand image is a perception about a brand held in consumer memory. Corporate brands are intangible assets for companies that are difficult to imitate, and it is different from products brands as emphasizing the important of brand values (De Chertanony, 1999). Ind (1997) reported that when consumers purchase products from a company, they not only buy products but also receive a set of values form the company. Corporate brands are a sum of values representing the corporate (Ind, 1997), and a positive corporate brand image is not only help companies to increase competition but also encourage consumers to re-purchases (Porter & Claycomb, 1997). Consumers more favorable the image has higher perceived in quality, value, satisfaction and loyalty (Johnson, Andreessen, Lervik, & Cha, 2001).
Customer commitment: Customer commitment indicated as a result of expected outcomes from a market offering, such as buying of a product, psychological ego of identifying with brand (Ogba & Tan, 2009). Moorman, Zaltman and Deshpande (1992) reported that customer commitment is an enduring attitude for a particular brand or firm, and connected to its brands or products. Commitment is an enduring desire as an exchange partner believing and maintaining a valued relationship with another (Morgan & Hunt, 1994;Moorman, Zaltman & Deshpande, 1992). Ogba and Tan (2009) examined the effects of brand image on customer loyalty and commitment in China. ANOVA and correlation analysis were employed, and findings support the hypotheses that brand image positively influence customer loyalty and boost customer commitment. In the study, the relationship between customer commitment and loyalty did not been tested.
Customer loyalty: Oliver (1997) indicated that customer loyalty is defined as a deeply held commitment to re-purchase a preferred product or service in the future. With loyal customers, companies can maximize their profit because loyal customers are willing to (1) purchase more frequently; (2) spend money on trying new products or services; (3) recommend products and services to others; and (4) give companies sincere suggestions (Reichheld & Sasser, 1990). Thus, loyalty links the success and profitability of a firm (Eakuru & Mat, 2008).Customer loyalty is commonly distinguished in three approaches including behavioral loyalty approach (Grahn, 1969); attitudinal loyalty approach (Bennett & Rundle-Thiele, 2002;Jacoby, 1971;Jacoby & Chestnut, 1978), and integration of attitudinal and behavioral loyalty approach (Dick & Basu, 1994;Jacoby, 1971;Jacoby & Chestnut, 1978;Oliver, 1997).
The attitudinal loyalty helps to examine the factors of loyalty, to avoid switching behavior (Caceres & Paparoidamis, 2007), and to predict how long customers will remain loyal (Jacoby & Chestnut, 1978). Therefore, viewing loyalty as an attitude-behavior relationship allows integrated investigation of antecedents and consequences of customer loyalty (Dick & Basu, 1994).

Corporate brand image, customer commitment and loyalty:
Corporate image has been assessed as an important antecedent of loyalty (Wu, 2011). Martineau (1958) stated that if consumers favor image of the store, they will probably develop a certain degree of loyalty, and Aaker (1991) suggested that a strong brand with high equity will have a large number of committed customers, leading to high and continues interaction and communication between customers and brands. Selnes (1993) also confirmed the influence of corporate brand image on brand loyalty. However, Davies and Chun (2002) found that corporate brand image had an indirect influence on brand loyalty via customer satisfaction when personality traits are used to portray corporate brand image in an off-line setting. Customer commitment can be considered as commitment to an organization or its foci including its brand, brand associations, such as brand image and brand reputation, and it should be conceptualized that customers can express emotional feelings and desire to maintain relationship with a brand rather than simply from repeat purchase (Ogba & Tan, 2009 H3 (Bowen & Shoemaker, 2003;Eakuru & Mat, 2008;Ibrahim & Najjar, 2008). Customer loyalty is the consequence of commitment is approved (Dorsch, Swanson, & Kelley, 1998;Ibrahim & Najjar, 2008).
Based on the literature review, the theoretical propositions inform the development of following hypothesized model and research hypotheses.

Figure 1: Hypothesized Model
Research hypotheses: H1: The corporate brand image is a direct path and is a factor that significantly affects the customer commitment.
H2: The customer commitment is a direct path and is a factor that significantly affects the customer loyalty.
H3: The corporate brand image is a direct path and is a factor that significantly affects the customer loyalty.

Methodology
A quantitative, non-experimental and explanatory (correlational) study was conducted to assess the relationships among corporate brand image on customer commitment and loyalty.
Instrumentation: A four-part questionnaire for the study was developed by the researchers in order to measure the research variables. In the questionnaire, seven of the items were designed to examine corporate brand image according to the theory of Ind in 1997 and De Chernatony and Harris in 2000; six of the items were designed to examine customer commitment according to the theory of Ogba and Tan (2009) and Morgan and Hunt (1994); and six of the items were developed to test customer loyalty according to the theory of Reichheld and Sasser in 1990. All variables are by means of a five-point Likert scale, and ranged from strongly agree (5)  The validity of the construct was measured using the convergent and discriminant validity. The convergent validity was used to determine whether scale items converged on a single construct during measurement (Steenkamp & Van Trijp, 1991). This was determined from the evaluation of the factor loadings (which must be at least 0.5), composite reliability (at least 0.6) and average extracted variance (at least 0.5) in the study (Hair et al. 2010;Fornell & Larcker, 1981). The discriminant validity is the extent to which a construct is truly distinct and unique, and this measure captures phenomena that other measures do not (Hair et al. 2010). Hair et al. (2010) indicated that the goodness-of-fit of the overall model is indicated by how well it reproduces the observed covariance matrix among the indicator items.
It can be classified into the following four categories: Chi-square measures including chi-square, degree of freedom (df) and probability. Measures of absolute fit, including the goodness-of-fit index (GFI), root mean square error of approximation (RMSEA), root mean square residual (RMR), standardized root mean square residual (SRMR) and normed chi-square. Incremental fit measures including the normed fit index (NFI) and the comparative fit index (CFI). Parsimony fit measures including the adjusted goodness-of-fit index (AGFI) and the parsimony normed fit index (PNFI).Chi-square (χ 2 ) is a basic measurement of the differences between the observed and estimated covariance matrices (Hair et al. 2010). A smaller value of χ 2 is more desirable in that it supports the proposed theoretical model, but values of χ 2 also increase as the sample size increases. The p-value should be large and not statistically significant (p > 0.05) between the two matrices (Jöreskog & Sörbom, 1992).
GFI was an early attempt to produce a fit statistic. The range of possible GFI values is between 0 and 1, and if the value is 0.90 or higher the fit is considered to be good (Hair et al. 2010); however, MacCallum and Hong (1997) suggested that the GFI value could decrease to 0.80 in usage. RMSEA tries to correct for both the sample size and complexity of the model by including each in its computation. Steiger (1990) suggested that RMSEA values below 0.10 indicate a good fit. Hair et al. (2010) indicated that RMR is problematic because it is related to the scale of the covariances. An alternative statistic is SRMR, which is useful for comparing the fit across models. Jöreskog and Sörbom (1992) indicated that an acceptable SRMR value would be 0.05 or less. The normed chi-square is given by χ2/df, and its value should be 3 or less to indicate a better fit between the observed and modeled values (Hair et al. 2010).NFI is the ratio of the difference in the value of χ 2 between the fitted and null models, divided by the value of χ 2 for the null model (NFI = 1 is a perfect model; Hair et al. 2010). Bentler (1992) suggested that the value of NFI should be 0.90 or above. The CFI is an improved version of NFI. It ranges between 0 and 1, with values above 0.90 being associated with a good fit (Hair et al. 2010;Gerbing & Anderson 1992). AGFI takes into account different degrees of complexity in the model, and its value is usually lower than that of the GFI in complex models (Hair et al. 2010). MacCallum and Hong (1997) recommended that the value of AGFI should be 0.80 or higher to indicate a good fit. The PNFI adjusts the NFI by multiplying it by the parsimony ratio; high values represent a better fit (Hair et al. 2010). Wu (2009) indicated that the value of the PNFI should be 0.50 or above to indicate a good fit.

Results
Data collection lasted for one month, and there were 182 questionnaires collected from Toyota, but 12 questionnaires were incomplete or invalid. All questionnaires were coded for statistical analysis using the were sufficient for research in social science and for factor analysis. The extraction and rotation sums of the squared loading of the total variance explained were 74.321%. Five items remained for each dimension which could therefore now be applied. The three dimensions of Cronbach's coefficient alpha were between .899 and .915, which surpassed the criteria and indicated an internal reliability of the consistency of the instruments used in the present study that was appropriate for research in social science. As a result of EFA, three factors and 15 items were therefore derived to identify the construct.
The univariate normality of the skewness and kurtosis values and the multivariate normality were used to assess the normality. The most commonly used critical values of univariate normality are ±3 and ±10 (Kline, 1998). In the study, all the values of skewness were between .211 and -.544, and the values of peakedness lay between .133 and -1.097. The observed variables all had univariate normal distributions.
The value of Mardia statistic is for multinormality measurement, and it is constructed a test based on skewness and kurtosis. Bollen (1989) indicated that if the value of Mardia is smaller than p (p+2), p indicating the amount of observed variables, all dimensions are multinormality. In the study, the value of Mardia is 17.348, smaller than 15(15+2), indicating multivariate normality distribution. In the structural models, all the factor loading estimates were higher than .76, the composite reliability (CR) values ranged from .908 to .912, and the extracted average values of variance lay between .663 and .674. This evidence supports the convergent validity of the measurement model, as shown in Tables 1.  Bagozzi and Phillips (1982) stated that metrics support discriminant validity if the upper and lower limits of the computed confidence interval did not include the number 1. In the present research, a model was constructed for each of the 3 paired correlations of the latent variables. Then, the correlation was set between the two constructs to 1, and a 95 percent confidence interval was applied in order to apply a bootstrap. As the results, all values of paired correlations of the latent variables were between.573and .905, the number 1 is not included with the upper and lower limits of the confidence interval, which indicates discriminant validity among the theoretical constructs. The results of the SEM model shown in Figure 2 were obtained using AMOS 18.0, and the model fits are reported in Table 2. The overall model fit χ 2 was 195.565 with 87 degrees of freedom. The p-value associated with this result was .000.The p-value was significant using a type I error rate of .05; thus, the χ 2 goodness-of-fit statistic does not indicate that the observed covariance matrix matches the estimated covariance matrix within the sampling variance.
According to previous research, a number of indices are available to evaluate model fits (Bentler, 1992;Fornell and Larcker, 1981;Jöreskog and Sörbom, 1992), but no single index or standard is generally agreed; hence, multiple criteria should be used to evaluate the overall fit of the theoretical model (Hair et al., 2010;Bagozzi and Yi, 1988

Conclusion
The study explores the impact of corporate brand image affects customer commitment as well as impact on customer loyalty in automobile sector. Following the outcomes of literature review and frameworks, three hypotheses were assessed. The results of this study show that the corporate brand image is a direct path and is a factor that significantly affects the customer commitment. The finding supports H1, and the result is consistent with the findings of Johnson, Andreessen, Lervik & Cha, (2001); and Davies et al. (2003).For hypothesis 2, the results indicate that the customer commitment is a direct path and is a factor that significantly affects the customer loyalty. Therefore, this hypothesis is supported, and the result is consistent with the findings of Eakuru and Mat (2008).For hypothesis 3, the results indicate that the corporate brand image is a direct path and is a factor that significantly affects the customer loyalty.
Based on the research results, the corporate brand image significantly affects customer commitment and loyalty, and customer commitment has strong impact on customer loyalty for the sample. Therefore, firms have to specifically focus on these factors in order to build a long-term and mutually profitability relationship with a customer and create loyalty as competitive advantages in the market. From the data of respondents, Toyota should also pay more attention to female, young customers who are under 25 years old, and consumers who have annual income under $15,000for increasing market share. The study focuses on automobile industry in Taiwan, and adopts only a quantitative research method. Although the SEM provides a good fit to the hypothesized model, future research could use a different design to examine the causal relationships posited by the theories, such as marketing mix (4Ps) and relationship quality, to explore other antecedents on loyalty for making long-term customer delight, and should be conducted in other industries and other Asian countries or different global regions.