Relationship between Service Quality and Customer Satisfaction - Case Study Example

Relationship between Service Quality and Customer Satisfaction: Case study of Bank of America Name: Tutor: Course: Date: Introduction The purpose of this study was to find out and determine the customer satisfaction levels from services offered by the Bank of America. Many banks attest to the fact that higher levels of customer satisfaction engender greater customer loyalty, which as a result generates goods income streams in future. In fact, many institutions banks included implemented superior quality services in their operations and thus commanding the market as leaders with regard to sales and long-term customer retention and loyalty. The Bank of America is a limited banking corporation with its headquarters based in Charlotte, North Carolina. It was founded in 1904 by Amadeo Giannini. The business engagements of the company include commercial banking, personal finance, private banking, global banking, corporate, and investment banking. Being the largest holding bank in the United States by Assets, its operations span the whole region of the U.S and in other countries globally. The Bank of America is regarded as one of the rapidly growing global finance centers worldwide. It’s global corporate and investment banking divisions are in the United States, Europe and Asia. The main factor which has contributed to the rapid growth of the bank is its core to be the leading bank in the domestic market. It has achieved this through key acquisitions, which has made the Bank of America, the largest issuer of credit, debit and prepaid cards in the world. The main competitors of the Bank of America on a national and international level include: Citigroup, Wells Fargo and JPMorgan & Company. Current studies on the efficiencies of bank branches generally fail to account for the dynamic roles of bank branches. The empirical studies are crucial in showing relationships between customer loyalty and service quality in the banking system. Service quality is very significant in the analysis of the banks’ performance, since their survival entirely relies on the levels service quality provided. Excellence in service quality is attained through customer loyalty which is a fundamental objective of any business firm, drawn from the merits of customer retention. At present, the rising awareness among bank customers of their rights, highly competition and changing demands needs steady progress in quality service if bank customers are to remain loyal. This case study seeks to establish whether the customers of Bank of America are delighted by the services offered to them, which ultimately is the issue behind customer loyalty. The understanding of the customers’ behaviour and attitudes will consequently enable the management at Bank of America to assess the potential of customer segmentation of its investment products and services. Problem statement Service quality and customer satisfaction are most critical elements in attaining organizational objectives. Banks try to have regular customers delighted by the service offered. Therefore, service quality has a pivotal responsibility in establishing customer satisfaction. In some way, quality has to be managed and understood across the service system of the organization. Thus, service quality is regarded as the most critical aspect. Service quality and customer satisfaction have developed alongside parallel tracks. The construct relation of both variables is presently the controversial and passionate subjects. In all aspects like relevance of emotion and reference object establish the extent of satisfaction or quality specifically significant based on the impact on customer retention. Satisfaction derived from transaction relates to value and complemented by product. On the other hand, service based quality influences attitude to customers owing to ephemeral characters and emotional resolve on the construct of satisfaction. The study considers the importance of customer satisfaction and service quality. However, customer satisfaction varies among different individuals. Significance of the study When the competitive environment is considered, there will be need for the bank to have a strategic plan that differentiates it from another. It can be attained by the superior service quality delivery. If this is proven, the practice of outstanding service quality will lead to greater customer satisfaction, sales, market share and increased revenues. Research approach and objectives of the study The major objective of the study is to establish the influence of the service quality on customer satisfaction. The specific objectives are; To determine whether the performance of investment with the provider influence the overall customer satisfaction level To evaluate if the fees and commissions charged influence the overall customer satisfaction level To establish whether online services offered influence the overall customer satisfaction level To determine if there is a relationship between quality of service and the overall customer satisfaction level To evaluate whether age and gender influence the overall customer satisfaction level Hypotheses To achieve the objectives of the case study, several hypotheses corresponding to the research questions and objectives were formulated as follows; Table 1 Research questions and the corresponding hypotheses 1. Research question: Does performance of investment with the provider influence the overall customer satisfaction. Hypothesis 1 H0: There is no relationship between performance of investment with the provider and the overall customer satisfaction Ha: There is a relationship between performance of investment with the provider and the overall customer satisfaction 2. Research question: Does the amount of fees and commissions charged influence the overall customer satisfaction. Hypothesis 2 H0: There is no relationship between fees and commissions charged and the overall customer satisfaction. Ha: There is a relationship between fees and commissions charged and the overall customer satisfaction. 3. Research question: Does the online services offered influence the overall customer satisfaction. Hypothesis 3 H0: There is no relationship between online services offered and the overall customer satisfaction. Ha: There is a relationship between online services offered and the overall customer satisfaction. 4. Research question: Does the quality of service influence the overall customer satisfaction. Hypothesis 4 H0: There is no relationship between the quality of service and the overall customer satisfaction. Ha: There is a relationship between the quality of service and the overall customer satisfaction. 5. Research question: Does age and gender influence the overall customer satisfaction. Hypothesis 5 H0: Age and gender do not influence the overall customer satisfaction. Ha: Age and gender influence the overall customer satisfaction. . Data description and analysis a) Data description Table 2 below indicates the descriptive statistics of the characteristics of the sample survey data. Of the 500 respondents sampled, 84.2% were male, while the female constituted 15.8%. Most of these participants were aged between 69 – 75 years of age. Furthermore, most the respondents included in the survey were married (86.4%), while 2.1% of the participants were single/ never married. 28.5% of the respondents had a college degree, 15.0% had a professional degree, while 8.6% of the respondents had no college degree. Table 2: Descriptive statistics Overall Data Variable N Percentage (%) Gender Male 411 84.2% Female 77 15.8% Age 27 - 57 56 11.6% 58 - 68 127 26.4% 69 - 75 165 34.3% 76 - 90 133 27.7% Marital status Married 421 86.4% Widowed 48 9.9% Divorced 8 1.6% Single/ Never married 10 2.1% Education No college 42 8.6% Some college 89 18.2% College graduate 139 28.5% Some graduate school 51 10.5% Master’s degree 94 19.3% Professional degree 73 15.0% Number of dependents One 20 39.2% Two 25 49.0% Three or more 6 11.8% b) Data analysis Regression analysis To evaluate the hypotheses formulated for the case study, regression analysis was used. Hypothesis 1 The null hypothesis for regression stated that there is no relationship between performance of investment with the provider and the overall customer satisfaction. The assumptions of regression were checked; it appeared that the data was normally distributed, ratio scale, and has a linear relationship. The dependent variable in the regression model established was the overall customer satisfaction, while performance of investment with the provider was the independent variable. Hypothesis 2 The null hypothesis for regression stated that there is no relationship between fees and commissions charged and the overall customer satisfaction. The assumptions of regression were also checked; it appeared that the data was normally distributed, ratio scale, and has a linear relationship. The dependent variable in the regression model was the overall customer satisfaction, while fees and commission charged was the independent variable. Hypothesis 3 The null hypothesis for regression stated that there is no relationship between online services offered and the overall customer satisfaction. The assumptions of regression were also checked; it appeared that the data was normally distributed, ratio scale, and has a linear relationship. The dependent variable in the regression model was the overall customer satisfaction, while the independent variable was online services offered. Hypothesis 4 The null hypothesis for regression stated that there is no relationship between quality of service and the overall customer satisfaction. The assumptions of regression were also checked; it appeared that the data was normally distributed, ratio scale, and has a linear relationship. The dependent variable in the regression model was the overall customer satisfaction, while the independent variable was quality of service. Hypothesis 5 The null hypothesis for regression stated that age and gender does not influence the overall customer satisfaction. The assumptions of regression were also checked; it appeared that the data was normally distributed, ratio scale, and has a linear relationship. The dependent variable in the regression model was the overall customer satisfaction, while the independent variables were age and gender. Findings and interpretations a) Findings Table 3: Relationship between performance of investment with provider and the overall customer satisfaction (H1) Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .727a .528 .527 .54333 a. Predictors: (Constant), Performance of investments with this provider ANOVA a Model Sum of Squares df Mean Square F Sig. 1 Regression 133.032 1 133.032 450.638 .000b Residual 118.968 403 .295 Total 252.000 404 a. Dependent Variable: Recoded Overall Satisfaction b. Predictors: (Constant), Performance of investments with this provider Coefficients a Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) -.450 .113 -3.965 .000 Performance of investments with this provider .556 .026 .727 21.228 .000 a. Dependent Variable: Recoded Overall Satisfaction The regression coefficient of performance of investments with the provider; B = .556, implies that better performance of the investments with the provider increases the overall customer satisfaction level. Based on the ANOVA results, the relationship between performance of investment with provider and the overall customer satisfaction level is statistically significant relationship, F (1, 403) = 450.64, p = .000. Therefore, reject the null hypothesis. Table 4: Relationship between fees or commission charged and the overall customer satisfaction (H2) Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .481a .232 .230 .68151 a. Predictors: (Constant), Fees or commissions charged ANOVA a Model Sum of Squares df Mean Square F Sig. 1 Regression 55.358 1 55.358 119.190 .000b Residual 183.458 395 .464 Total 238.816 396 a. Dependent Variable: Recoded Overall Satisfaction b. Predictors: (Constant), Fees or commissions charged Coefficients a Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) .482 .130 3.690 .000 Fees or commissions charged .338 .031 .481 10.917 .000 a. Dependent Variable: Recoded Overall Satisfaction The regression coefficient of fees or commissions charged; B = .338, implies that more reasonable and competitive the fees or commission charged increases the overall customer satisfaction level. Based on the ANOVA results, the relationship between fees or commissions charged and the overall customer satisfaction level is statistically significant relationship, F (1, 395) = 119.90, p = .000. Therefore, reject the null hypothesis. Table 5: Relationship between online services offered and the overall customer satisfaction (H3) Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .530a .281 .278 .63547 a. Predictors: (Constant), Online services offered ANOVA a Model Sum of Squares df Mean Square F Sig. 1 Regression 34.062 1 34.062 84.348 .000b Residual 87.227 216 .404 Total 121.289 217 a. Dependent Variable: Recoded Overall Satisfaction b. Predictors: (Constant), Online services offered Coefficients a Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) -.089 .211 -.423 .673 Online services offered .414 .045 .530 9.184 .000 a. Dependent Variable: Recoded Overall Satisfaction The regression coefficient of online services offered; B = .414, implies that better online services offered tends to increases the overall customer satisfaction level. Based on the ANOVA results, the relationship between online services offered and the overall customer satisfaction level is statistically significant relationship, F (1, 216) = 84.35, p = .000. Therefore, reject the null hypothesis. Table 6: Relationship between quality of service and the overall customer satisfaction (H4) Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .731a .534 .533 .53396 a. Predictors: (Constant), Quality of service ANOVA a Model Sum of Squares df Mean Square F Sig. 1 Regression 137.342 1 137.342 481.709 .000b Residual 119.748 420 .285 Total 257.090 421 a. Dependent Variable: Recoded Overall Satisfaction b. Predictors: (Constant), Quality of service Coefficients a Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) -.960 .132 -7.291 .000 Quality of service .599 .027 .731 21.948 .000 a. Dependent Variable: Recoded Overall Satisfaction The regression coefficient of quality of service; B = .599, implies that higher quality of service increases the overall customer satisfaction level. Based on the ANOVA results, the relationship between quality of service and the overall customer satisfaction level is statistically significant relationship, F (1, 420) = 481.71, p = .000. Therefore, reject the null hypothesis. Table 7: Relationship between age and gender and the overall customer satisfaction (H5) Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .113a .013 .008 .78701 a. Predictors: (Constant), Gender of Household Head, Recoded Age ANOVA a Model Sum of Squares df Mean Square F Sig. 1 Regression 3.488 2 1.744 2.815 .061b Residual 268.814 434 .619 Total 272.302 436 a. Dependent Variable: Recoded Overall Satisfaction b. Predictors: (Constant), Gender of Household Head, Recoded Age Coefficients a Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 1.476 .172 8.593 .000 Recoded Age .050 .039 .062 1.299 .195 Gender of Household Head .221 .106 .100 2.085 .038 a. Dependent Variable: Recoded Overall Satisfaction The regression coefficient of age; B = .050, implies that the overall customer satisfaction level tends to increase with age, while the regression coefficient of gender; B = .221, implies that the overall customer satisfaction level is higher among female than male. Based on the ANOVA results the relationship between age and gender, and the overall customer satisfaction level is not statistically significant relationship, F (2, 434) = 2.82, p = .061. Therefore, fail to reject the null hypothesis. Discussions and managerial implications The sample data provided has been quite insightful in the evaluation of the relations between the specific factors mentioned and the overall customer satisfaction. The study found out that the performance of investments with provider, fees or commissions charged, online services offered and quality of service quality affects the overall customer satisfaction. However, the findings of the study did not provide sufficient evidence to indicate that age and gender influence the overall customer satisfaction. The study will help strategic managers on how to draw and retain bank customers. Consequently, maintaining the long-term customer requires that organizations ensure the right supply of products and services accompanied by deserved promotion and other rewards. Merchandise and quality service are critical in the current competitive market, as it is equally essential in honing customer experiences. An entity with the ability of catering for customers needs will undoubtedly gain customers loyalty, resulting in potential referrals and repeat business. A business focusing on service delivery gains a lot of value from its customers. This will provide probable environment for repeat business. The survey feedback is a true testament that the hypothesis on customer satisfaction correlates positively with service quality attributes. Marketing of bank products and services requires adherence and implementation of service quality program to the latter. The critical factors that influence the overall customer satisfaction level are all essential. Therefore, the management will now be required to not only pay attention to the profit objective, but also desire to meet the needs of its customers. The marketing research and forecasting team have a huge task in recommending intensive training programs on customer-relations for all the tellers and front facing staff. In this circumstance, the bank is able to fortify its core competency with regard to customer satisfaction. Reference List Thomke, S., 2007, How Bank of America Turned Branches into service – Development laboratories. Retrieved from: http://hbsw.hbs.edu/item/3459.html Appendices Frequency statistics Gender of Household Head Frequency Percent Valid Percent Cumulative Percent Valid Male 411 82.2 84.2 84.2 Female 77 15.4 15.8 100.0 Total 488 97.6 100.0 Missing System 12 2.4 Total 500 100.0 Recoded Number of Dependent Children Frequency Percent Valid Percent Cumulative Percent Valid One 20 4.0 39.2 39.2 Two 25 5.0 49.0 88.2 Three or More 6 1.2 11.8 100.0 Total 51 10.2 100.0 Missing System 449 89.8 Total 500 100.0 Recoded Age Frequency Percent Valid Percent Cumulative Percent Valid 27 to 57 Years 56 11.2 11.6 11.6 58 to 68 Years 127 25.4 26.4 38.0 69 to 75 Years 165 33.0 34.3 72.3 76 to 90 Years 133 26.6 27.7 100.0 Total 481 96.2 100.0 Missing System 19 3.8 Total 500 100.0 Recoded Marital Status Frequency Percent Valid Percent Cumulative Percent Valid Now Married 421 84.2 86.4 86.4 Now Not Married 66 13.2 13.6 100.0 Total 487 97.4 100.0 Missing System 13 2.6 Total 500 100.0 Recoded Education Frequency Percent Valid Percent Cumulative Percent Valid No College 42 8.4 8.6 8.6 Some College 89 17.8 18.2 26.8 College Graduate 139 27.8 28.5 55.3 Some Graduate School 51 10.2 10.5 65.8 Master's Degree 94 18.8 19.3 85.0 Professional Degree 73 14.6 15.0 100.0 Total 488 97.6 100.0 Missing System 12 2.4 Total 500 100.0 SPSS Regression outputs Hypothesis 1 Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .727a .528 .527 .54333 a. Predictors: (Constant), Performance of investments with this provider ANOVA a Model Sum of Squares df Mean Square F Sig. 1 Regression 133.032 1 133.032 450.638 .000b Residual 118.968 403 .295 Total 252.000 404 a. Dependent Variable: Recoded Overall Satisfaction b. Predictors: (Constant), Performance of investments with this provider Coefficients a Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) -.450 .113 -3.965 .000 Performance of investments with this provider .556 .026 .727 21.228 .000 a. Dependent Variable: Recoded Overall Satisfaction Hypothesis 2 Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .481a .232 .230 .68151 a. Predictors: (Constant), Fees or commissions charged ANOVA a Model Sum of Squares df Mean Square F Sig. 1 Regression 55.358 1 55.358 119.190 .000b Residual 183.458 395 .464 Total 238.816 396 a. Dependent Variable: Recoded Overall Satisfaction b. Predictors: (Constant), Fees or commissions charged Coefficients a Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) .482 .130 3.690 .000 Fees or commissions charged .338 .031 .481 10.917 .000 a. Dependent Variable: Recoded Overall Satisfaction Hypothesis 3 Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .530a .281 .278 .63547 a. Predictors: (Constant), Online services offered ANOVA a Model Sum of Squares df Mean Square F Sig. 1 Regression 34.062 1 34.062 84.348 .000b Residual 87.227 216 .404 Total 121.289 217 a. Dependent Variable: Recoded Overall Satisfaction b. Predictors: (Constant), Online services offered Coefficients a Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) -.089 .211 -.423 .673 Online services offered .414 .045 .530 9.184 .000 a. Dependent Variable: Recoded Overall Satisfaction Hypothesis 4 Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .731a .534 .533 .53396 a. Predictors: (Constant), Quality of service ANOVA a Model Sum of Squares df Mean Square F Sig. 1 Regression 137.342 1 137.342 481.709 .000b Residual 119.748 420 .285 Total 257.090 421 a. Dependent Variable: Recoded Overall Satisfaction b. Predictors: (Constant), Quality of service Coefficients a Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) -.960 .132 -7.291 .000 Quality of service .599 .027 .731 21.948 .000 a. Dependent Variable: Recoded Overall Satisfaction Hypothesis 5 Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .113a .013 .008 .78701 a. Predictors: (Constant), Gender of Household Head, Recoded Age ANOVA a Model Sum of Squares df Mean Square F Sig. 1 Regression 3.488 2 1.744 2.815 .061b Residual 268.814 434 .619 Total 272.302 436 a. Dependent Variable: Recoded Overall Satisfaction b. Predictors: (Constant), Gender of Household Head, Recoded Age Coefficients a Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 1.476 .172 8.593 .000 Recoded Age .050 .039 .062 1.299 .195 Gender of Household Head .221 .106 .100 2.085 .038 a. Dependent Variable: Recoded Overall Satisfaction Read More