An Empirical Study on Customer s Satisfaction towards Banking Services of State Bank of India in Gujarat

Transcription

1 [ VOLUME 5 I ISSUE 2 I APRIL JUNE 2018] E ISSN , PRINT ISSN An Empirical Study on Customer s towards anking Services State ank India in Gujarat Dr. Paras Sheth Teaching Assistant, M. J. College Commerce2, Maharaja Krishnakumarsinhji havnagar University, havnagar , Gujarat, India. Received: Feb. 21, 2018 Accepted: April 01, 2018 ASTRACT State ank India s (State ank India) Customer satisfactions has emerged as an important segment overall development State ank India and so far has delivered value to the customers. We classified customer satisfaction into three categories: Not Agree as 0, Neutral as 1 and Agree as 2 to the service satisfaction. Here we studied assess whether there are difference in each these State ank India customer satisfaction perception by Gender and provided Up-gradation technology by State ank India. Three separate logistic regression analysis are conducted on 100 SI customer Gujarat. Key Words:banking service. INTRODUCTION G.S. Sureshchandar (2002) has studied the relationship between service quality and customer satisfaction a factor specific approach. They view customer satisfaction as a multi dimensional construct. Service quality and customer satisfaction are inarguably the two core concepts that are at the crux the marketing theory and practice (Spreng and Mackoy, 1996). Sergio Zani, Lara erzieri (2008) has studied the measuring customer satisfaction using ordinal variables: an application in a survey on a contact center. In today s world intense competition, the key to sustainable competitive advantage lies in delivering high quality service that will in turn result in satisfied customers (Shemwell et al., 1998). The overall satisfaction may be measured by a single direct question or by several manifest variables relating to the different domains satisfaction (Montinaro and Chirico, 2006). These variables are ten on ordinal scale with different numbers categories (Likert scale with 5 modalities, scores from 1 to 5, and so on) (De Luca, 2007). Generally, the responses to the items are scored 1, 2, 3, 4, and 5 (for Likert scales) and so on, to indicate increasing levels customer satisfaction. In this paper we focused on customer perception State ank India. This paper deals with the problem measuring the perception public service quality SI. OJECTIVES OF THE STUDY The main purpose this study is to evaluate customer satisfaction banking service in the State ank India. The main objectives the present study are as follows: 1. To develop a prile SI Customers Gujarat 2. To examine the various provided by SI in Gujarat. 3. To study the customer satisfaction towards the up gradation by the SI banks in Gujarat. 4. To do detailed frequency analyses Customers 5. To analyzed the customer satisfaction to the service State ank India. 6. To compare the customer which group is more satisfy among gender. HYPOTHESIS OF THE STUDY The study is based on the formulation the following hypotheses: H0: There is no significant difference between Gender category and level satisfaction towards service provided by State bank India in Gujarat. H0: There is no significant difference between Up-gradation and level satisfaction towards service provided by State bank India in Gujarat. Method Data Collection: The study depends on primary data. Questionnaires have been used to collect the needed particulars. Questions related to the objectives have been framed after consulting experts. ased on the information gathered through a pilot study, the structure the questionnaire has been restructured. 234 IJRAR- International Journal Research and Analytical Reviews Research Paper

2 [VOLUME 5 I ISSUE 2 I APRIL JUNE 2018] e ISSN , Print ISSN Cosmos Impact Factor Selection Sample Customers for Opinion Survey: This study has attempted to elicit the effect demographic variables on SI Customers behavior the Gujarat. We collected primary data from the customer s living in Gujarat during the period Jan. 01, 2017 to Dec. 31, 2017 through a Structured Questionnaire. At random, a nominal number 100customers were identified though it forms an inadequate sample size. Finally their socio economic priles were examined besides eliciting and analyzing their opinions on the SI. Out the 110 respondents selected, 10 respondents did not respond and the balances 100 were included in the study. They represent different socio-economic backgrounds. All the respondents selected under convenient sampling method were interviewed with a simple questionnaire during the period from Jan. 01, 2017 to Dec. 31, We ask customer whether you agree that State ank India Gujarat adopt technology Up-gradation into two categories: Not Agree as 1 and Agree as 2. Table-1 revels that 40% customers are satisfy with State ank India. 55% customers are Female and 45% customers are Male. 74% customers are Agree that State ank India adopt technological Up-gradation. Table-1: Case Processing Summary State ank India s Customer Gender Up-gradation Category N Marginal Percentage % % % % % % % Valid % Total Subpopulation 4 - We take satisfaction as a dependent variable and Gender & Up-gradation as independent variable. Further we apply multiple logistic regression models. The model fitting information is given in Table-2. Model Table-2: Model Fitting Information Intercept Only Model Fitting Criteria Likelihood Ratio Tests -2 Log Likelihood Chi-Square df Sig. Final From, Table-2 we get Chi-square value with p-value It leads us to conclude that at least one the regression coefficients in the model is not equal to zero. The estimated Multiple Logistic Regression Coefficients for not Customer to Neutral Customer State ank India, Gujarat models are shown in Table-3. Table-3: Parameter Estimates Multiple Logistic Regression Model on with SI service 95% Confidence Interval for Exp() ( with SI service) Not Intercept Wald df Sig. Exp() ound Upper ound Male Research Paper IJRAR- International Journal Research and Analytical Reviews 235

3 [ VOLUME 5 I ISSUE 2 I APRIL JUNE 2018] E ISSN , PRINT ISSN Technology in SI Intercept Male Neutral Technology in SI a. The reference category is: 2.00 ( with SI service) With regard to comparison with SI service with not satisfied with SI, there are Statistically Significant difference between Male and Female (p-value = ) and Customers who Agree and Not Agree with Up-gradation Technology in State ank India-Gujarat (p-value = 0.002) at 5% level significance value. Male Customers are nearly 9 times more likely to with SI service. With regard to comparison with SI service with Neutral with SI, there are no Statistically Significant difference between Male and Female (p-value = 0.742) and Customers who Agree and Not Agree with Up-gradation Technology in State ank India-Gujarat (p-value = 0.841) at 5% level significance value. The multiple logit for male compares to female is 2.19 for preferring not satisfies with SI to satisfy with SI. Male are more likely than females to prefer not satisfied with SI service to Satisfies with SI service. The multiple logit for Not Agree customer with Up-gradation Technology in SI compares to agree with Up-gradation Technology in SI is for preferring not satisfies with SI to satisfy with SI. Not Agree customer with Up-gradation Technology in SI are more likely than agree with Up-gradation Technology in SI to prefer not satisfied with SI service to Satisfies with SI service. The multiple logit for male compares to female is for preferring Neutral with SI to satisfy with SI. Male are more likely than females to prefer Neutral with SI service to Satisfies with SI service. The multiple logit for Not Agree customer with Up-gradation Technology in SI compares to agree with Up-gradation Technology in SI is for preferring Neutral with SI to satisfy with SI. Not Agree customer with Up-gradation Technology in SI are more likely than agree with Up-gradation Technology in SI to prefer Neutral with SI service to Satisfies with SI service. The estimated Multiple Logistic Regression Coefficients for Neutral Customer to Customer State ank India, Gujarat models are shown in Table-4. Table-4: Parameter Estimates Multiple Logistic Regression Model on not with SI service 95% Confidence Interval for Exp() (Not with SI service) Wald df Sig. Exp() Intercept ound Upper ound Male Neutral.482 Technology in SI Intercept Male IJRAR- International Journal Research and Analytical Reviews Research Paper

4 [VOLUME 5 I ISSUE 2 I APRIL JUNE 2018] e ISSN , Print ISSN Cosmos Impact Factor Technology in SI a. The reference category is: (Not with SI service) With regard to comparison with SI service with Neutral with SI, there are Statistically Significant difference between Male and Female (p-value = 0.008) and there are no Statistically Significant difference between Customers who Agree and Not Agree with Up-gradation Technology in State ank India-Gujarat (p-value = 0.462) at 5% level significance value. Male Customers are nearly 7 times more likely to with SI service. With regard to comparison with SI service with Neutral with SI, there are Statistically Significant difference between Male and Female (p-value = 0.030) and between Customers who Agree and Not Agree with Up-gradation Technology in State ank India-Gujarat (p-value = 0.001) at 5% level significance value. The multiple logit for male compares to female is 1.91 for preferring Neutral with SI to not satisfy with SI. Male are more likely than females to prefer not satisfied with SI service to Satisfies with SI service. The multiple logit for Not Agree customer with Up-gradation Technology in SI compares to agree with Up-gradation Technology in SI is for preferring Neutral with SI to not satisfy with SI. Not Agree customer with Up-gradation Technology in SI are more likely than agree with Up-gradation Technology in SI to prefer Neutral with SI service to not Satisfies with SI service. The multiple logit for male compares to female is 0.08 for preferring satisfies with SI to not satisfy with SI. Male are more likely than females to prefer satisfies with SI service to not satisfy with SI service. The multiple logit for Not Agree customer with Up-gradation Technology in SI compares to agree with Up-gradation Technology in SI is for preferring satisfies with SI to not satisfy with SI. Not Agree customer with Up-gradation Technology in SI are more likely than agree with Up-gradation Technology in SI to prefer satisfies with SI service to not Satisfies with SI service. The estimated Multiple Logistic Regression Coefficients for Neutral Customer to not Customer State ank India, Gujarat models are shown in Table-5. (Neutral satisfaction with SI ) Not Technology in SI Table-5: Parameter Estimates Multiple Logistic Regression Model Wald df Sig. Exp() Intercept % Confidence Interval for Exp() ound Upper ound Male Intercept Male Technology in SI a. The reference category is: (Neutral satisfaction with SI ) Research Paper IJRAR- International Journal Research and Analytical Reviews 237

5 [ VOLUME 5 I ISSUE 2 I APRIL JUNE 2018] E ISSN , PRINT ISSN With regard to comparison Neutral with SI service with Not satisfied with SI, there are no Statistically Significant difference between Male and Female (p-value = 0.953) and there are Statistically Significant difference etween Customers who Agree and Not Agree with Up-gradation Technology in State ank India-Gujarat (p-value = 0.003) at 5% level significance value. With regard to comparison Neutral with SI service with satisfied with SI, there are no Statistically Significant difference between Male and Female (p-value = 0.742) and there are Statistically Significant difference etween Customers who Agree and Not Agree with Up-gradation Technology in State ank India-Gujarat (p-value = 0.04) at 5% level significance value. The multiple logit for male compares to female is for preferring not satisfies with SI to Neutral with SI. Male are less likely than females to prefer not satisfied with SI service to Neutral with SI service. The multiple logit for Not Agree customer with Up-gradation Technology in SI compares to agree with Up-gradation Technology in SI is for preferring not satisfies with SI to Neutral with SI. Not Agree customer with Up-gradation Technology in SI are more likely than agree with Up-gradation Technology in SI to prefer not satisfied with SI service to Neutral with SI service. The multiple logit for male compares to female is for preferring satisfied with SI to Neutral with SI. Male are less likely than females to prefer satisfied with SI service to Neutral with SI service. The multiple logit for Not Agree customer with Up-gradation Technology in SI compares to agree with Up-gradation Technology in SI is for preferring satisfied with SI to Neutral with SI. Not Agree customer with Up-gradation Technology in SI are more likely than agree with Up-gradation Technology in SI to prefer satisfied with SI service to Neutral with SI service. References: 1. G. S. Sureshchandar, ChandrasekharanRajendran, R. N. Anantharaman, (2002) "The relationship between service quality and customer satisfaction a factor specific approach", Journal Services Marketing, Vol. 16 Issue: 4, pp Sergio Zani, Lara erzieri (2008) Measuring Customer Using Ordinal Variables: An Application In A Survey On A Contact Center Statistical Applicata Vol. 20, n. 3-4, Dr. Savita Vaghela, Priya Vyas And Paras Sheth (2017) The variable Influencing to extra-curricular activities universities Gujarat: an empirical study IJRAR, Dr. Mayuri M Pandya, Monica Sharma And Aum Dave(2017) Empirical studies on teaching methods on student academic performance, IJRAR, IJRAR- International Journal Research and Analytical Reviews Research Paper