Determining Customer Satisfaction On Automated Teller Machine Biology Essay

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Implication of information technology (IT) has revolutionized the banking business in a tremendous way. Several technologies have been adopted and various technologies may also come up in the near future. Among those IT implications automated teller machine (ATM) is also one of the technologies. The idea of self-service in retail banking developed through independent and simultaneous efforts in Japan, Sweden, the United Kingdom and the United States. In the USA, Luther George Simjian has been credited with developing and building the first automatic teller machine. The first ATM was put into use in 1959 in the Kingsdale Shopping Center in Upper Arlington, Ohio. This suburb of Columbus, Ohio created a shopping center where the Galbraith Farm used to be located that also featured the world's first The Limited Store. (wikipedia). Introduction of automated teller machines (ATMs) has enabled customers to do banking without visiting the branch. In 2010-11 the number of ATMs witnessed a growth of 24 per cent over the previous year. More than 65 per cent of the total ATMs belong to public sector banks at end march 2011, (Oxford ,2012, Economic survey report 2011-12).

Review of Literature

Citibank was one of the first U.S. banks to introduce automatic teller machines in the 1970s, in order to give 24-hour access to accounts. (Wikipedia). On September 2, 1969, Chemical Bank installed the first ATM in the U.S. at its branch in Rockville Centre, New York. The first ATMs were designed to dispense a fixed amount of cash when a user inserted a specially coded card. (1969: the year everything changed - Google Books. Google Books. Retrieved February 11, 2011) A Chemical Bank advertisement boasted "On Sept. 2 our bank will open at 9:00 and never close again. ( Popular Mechanics. Google Books. Retrieved February 11, 2011.) The staff users are more satisfied in all respects than the non-staff ATM users. (Customer Satisfaction of ATM Service: A Case Study of HSBC ATM).

Objectives and hypothesis

To identify

the difference of satisfaction between gender.

the difference of satisfaction among difference age group.

the difference between different income group.

the difference satisfaction between different profession.

the difference satisfaction between banks.

To measure the overall satisfaction among the respondent

From the above objectives, following hypothesis are framed for further analysis:

Ho1: there is no significant difference of satisfaction between genders.

Ho2: there is no difference satisfaction observed between different age group.

Ho3: there is no difference satisfaction observed between different income groups.

Ho4: there is no different satisfaction observed between different professions.

Ho5: there is no difference satisfaction observed between banks.

After analyzing the data and validating the objectives and testing the hypothesis respective recommendation and strategies will be highlighted for the betterment of the business firm as well as customer.

Research methodology

Method of Data collection, sample size and statistical tools:

One of the major concerns of this article is to find out the factors that affect the use of ATM card and their psychological and mental perception towards the high end banking technology applied in today's banking business further it attempts to find out the various satisfaction level between different age groups, profession wise, income wise and gender wise. This paper attempts to find out the level of customer satisfaction towards the selected nationalized banks in Imphal. Further it tries to find out the factor affecting the customer satisfaction and suggest the various measures to improve the banking services in the State.

4.2 Data analysis:

Data collected through structure questionnaire were analyzed using MS Excel and SPSS. Data analysis methods include t-test, ANOVA test, factor analysis and customer satisfaction index analysis. The Customer Satisfaction Index represents the overall customer satisfaction index over the fourteen variables.

5. Data analysis and Discussion:

Data's were collected for fourteen variables through structure questionnaire on five pint Likert Scale. The analysis is done base on various demographic profile of the customer and banks.

5.1 Consumer profile

Table 1.

Demographic profile of consumer and banks

Gender

Profession

Age

Male

65.9%

Student

48.8%

Bellow20

29.3%

Female

34.1%

Salaried

17.1%

20-40

36.6%

Businessman

22.0%

40-60

17.1%

Wage earner

12.2%

Above60

17.1%

Income

Banks

ATM card used

Bellow15000

43.9%

Allahabad Bank

4.9%

Own ATM's

63.4%

15000-30000

22.0%

UBI

4.9%

Parent ATM's

9.8%

30000-45000

14.6%

Axis Bank

2.4%

Both own & parent

26.8%

Above45000

19.5%

HDFC Bank

2.4%

SBI

80.5%

ICICI Bank

4.9%

Table 1 depicts the demographic profile of customer and it is found that in case of gender 65.9% of the respondents represent male and female represent 34.1%. In case of profession 48.8% were student, salaried were 17.1% and businessman and wage earner were 22% and 12.2% respectively. It the classification of income bellow fifteen thousand is 43.9%, fifteen to thirty thousand were 22% and thirty to forty five thousand and above forty five thousand was 14.6% and 19.5% respectively. 80.5% of the respondent were belong to SBI whereas Allahabad, UBI, ICICI, Axis and HDFC banks were 4.9%, 2.4% respectively. 63.4% percent of the customer used their own ATM cards whereas 9.8% and 26.8% of the customer used their parent, both own and parents ATM cards.

Table 2

Awareness level of Banks

From the above Table 2 it is observed that the awareness level of banks in Imphal is highest with State Bank of India whereas Axis bank and United Bank of India are in second and third position scoring 68% and 63% respectively.

Table 3

Positive features of ATM

In case of variable positive features of ATM used by the customer from the above Table 3 it can be inferred that time saving is the major concern for using ATM services scoring 75%. Easy to use and cash withdrawal are in second and third concern scoring 73% and 63% respectively.

Table4

Service avail with ATM

From the above Table 4 it is observed that most of the customer used ATM services for withdrawing cash scoring 87% of response and checking of account balance is in the second place of utility.

5.2 Comparison of satisfaction level through various demographic profiles

5.2.1 Factor analysis:

Factor analysis is done to reduce the factors. Fourteen factors were classified into four groups such as ease of use, timeliness, security and courtesy respectively. The extraction method is principle component analysis and Varimax rotation. The total variance explains in Table 5 and rotated matrix is shown in Table 6.

Table 5.

Total Variance Explained

Component

Initial Eigen values

Extraction Sums of

Squared Loadings

Rotation Sums of Squared Loadings

Total

% of Variance

Cumulative %

Total

% of Variance

Cumulative %

Total

% of Variance

Cumulative %

1

3.073

21.949

21.949

3.073

21.949

21.949

2.538

18.126

18.126

2

2.266

16.187

38.136

2.266

16.187

38.136

2.260

16.144

34.270

3

1.795

12.819

50.955

1.795

12.819

50.955

2.199

15.705

49.975

4

1.393

9.948

60.903

1.393

9.948

60.903

1.530

10.928

60.903

5

1.253

8.954

69.856

6

.916

6.539

76.396

7

.699

4.992

81.388

8

.624

4.455

85.843

9

.488

3.488

89.331

10

.456

3.260

92.591

11

.393

2.805

95.396

12

.310

2.217

97.613

13

.194

1.383

98.996

14

.141

1.004

100.000

Extraction Method: Principal Component Analysis.

Here the total variance explains that the fourteen factors is 61% of the total variables which are grouped and name accordingly in the rotated component matrix shown in Table 3. The extraction method used here is Principal Component Analysis. The rotation method is Varimax with Kaiser Normalization.

Table 6.

Rotated Component Matrix

Factors

Component

Ease of use

Timeliness

Security

Courtesy

To avoid queue

.033

.766

.038

-.260

Needless cash carry

-.099

.819

-.307

.087

Transaction on non banking hour

.207

.696

.032

.106

Merchant visit

.044

.426

.276

.246

Easy to use

.097

-.134

.049

-.847

Less Error

.775

.023

.207

.011

Speed of transaction

-.032

.440

.319

.418

Running all time

.789

.052

.310

.018

Dealing by Bank

.736

.174

-.143

-.080

Location of ATM booth

.576

-.046

-.145

.509

Amount of transaction

.425

-.292

.114

.471

Service duration

-.225

.000

.719

.042

Availability of service

.227

-.039

.768

-.018

Waiting time

.305

.042

.788

-.018

Extraction Method: Principal Component Analysis.

Rotation Method: Varimax with Kaiser Normalization.

The above five factors are used for the testing of hypothesis related to demographic factors of the customer.

5.2.2 t-test and ANOVA test for demographic comparison

The t-test for the gender wise comparison and one way ANOVA test for age, profession, income and bank wise comparison are shown in the following table 7.

Table 7.

t- test and ANOVA results

Factors

Gender

(t-test)

Age

(ANOVA)

Profession

(ANOVA)

Income

(ANOVA)

Banks

(ANOVA)

Ease of use

0.380

0.215

4.035*

1.406

0.351

Timeliness

0.061

0.100

1.794

0.380

2.816

Security

0.635

1.037

0.501

0.694

0.349

Courtesy

0.369

0.116

2.180

0.262

1.303

*= significant at 0.05 significance level.

In case of the gender group difference of satisfaction there is no any difference in satisfaction. The case is same for age wise classification also. But there is a difference in satisfaction in terms of profession with the variable ease of use which is shown in Table 9. The group difference of satisfaction in income wise and bank wise for the variables that is ease of use, timeliness, security and courtesy there is no difference found in the analysis as it is observed in Table 10 and 11.

Table 8

Multiple Comparisons:

Tuckey HSD for Age Groups

Dependent Variable

(I) Age

(J) Age

Mean Difference (I-J)

Std. Error

Ease of use

Bellow20

20-40

-.181

.399

40-60

-.228

.490

Above60

-.382

.490

20-40

Bellow20

.181

.399

40-60

-.047

.472

Above60

-.201

.472

40-60

Bellow20

.228

.490

20-40

.047

.472

Above60

-.154

.551

Above60

Bellow20

.382

.490

20-40

.201

.472

40-60

.154

.551

Timeliness

Bellow20

20-40

-.119

.401

40-60

-.269

.493

Above60

-.113

.493

20-40

Bellow20

.119

.401

40-60

-.149

.474

Above60

.006

.474

40-60

Bellow20

.269

.493

20-40

.149

.474

Above60

.155

.554

Above60

Bellow20

.113

.493

20-40

-.006

.474

40-60

-.155

.554

Security

Bellow20

20-40

-.584

.387

40-60

-.291

.475

Above60

.060

.475

20-40

Bellow20

.584

.387

40-60

.293

.457

Above60

.643

.457

40-60

Bellow20

.291

.475

20-40

-.293

.457

Above60

.351

.534

Above60

Bellow20

-.060

.475

20-40

-.643

.457

40-60

-.351

.534

Courtesy

Bellow20

20-40

.187

.401

40-60

-.014

.492

Above60

-.024

.492

20-40

Bellow20

-.187

.401

40-60

-.201

.474

Above60

-.211

.474

40-60

Bellow20

.014

.492

20-40

.201

.474

Above60

-.010

.553

Above60

Bellow20

.024

.492

20-40

.211

.474

40-60

.010

.553

*= significant at 0.05 significance level.

Above Table 8 shows the significant difference of satisfaction among each age group for all the four factors that is ease of use, timeliness, security and courtesy where "*"means significant difference at 0.05 significance level. The significant difference analysis for profession groups is shown in Table 9.

Table 9

Multiple Comparisons:

Tuckey HSD for Profession Groups

Dependent Variable

(I) Profession

(J) Profession

Mean Difference (I-J)

Std. Error

Ease of use

Student

Salaried

.937

.396

Businessman

1.119*

.362

Wage earner

.286

.451

Salaried

Student

-.937

.396

Businessman

.182

.455

Wage earner

-.650

.528

Businessman

Student

-1.119*

.362

Salaried

-.182

.455

Wage earner

-.832

.503

Wage earner

Student

-.286

.451

Salaried

.650

.528

Businessman

.832

.503

Timeliness

Student

Salaried

.760

.427

Businessman

.134

.390

Wage earner

-.504

.486

Salaried

Student

-.760

.427

Businessman

-.625

.490

Wage earner

-1.264

.569

Businessman

Student

-.134

.390

Salaried

.625

.490

Wage earner

-.638

.542

Wage earner

Student

.504

.486

Salaried

1.264

.569

Businessman

.638

.542

Security

Student

Salaried

.375

.448

Businessman

.419

.409

Wage earner

.001

.510

Salaried

Student

-.375

.448

Businessman

.044

.514

Wage earner

-.374

.597

Businessman

Student

-.419

.409

Salaried

-.044

.514

Wage earner

-.418

.569

Wage earner

Student

.000

.510

Salaried

.374

.597

Businessman

.418

.569

Courtesy

Student

Salaried

-.525

.421

Businessman

.325

.385

Wage earner

-.866

.479

Salaried

Student

.525

.421

Businessman

.851

.483

Wage earner

-.341

.561

Businessman

Student

-.325

.385

Salaried

-.851

.483

Wage earner

-1.192

.535

Wage earner

Student

.866

.479

Salaried

.341

.561

Businessman

1.192

.535

*= significant at 0.05 significance level.

In case of the variable profession it is observed from the above table 9 that there is a significant difference between student and business man in terms of ease of use, but in case of other variables there is no significant difference found where "*"means significant difference at 0.05 significance level. The significant difference analysis for the income groups is shown in Table 10.

Table 10

Multiple Comparisons:

Tuckey HSD for Income Groups

Dependent Variable

(I) Income

(J) Income

Mean Difference (I-J)

Std. Error

Ease of use

Bellow15000

15000-30000

-.612

.402

30000-45000

-.574

.464

Above45000

-.698

.419

15000-30000

Bellow15000

.612

.402

30000-45000

.038

.519

Above45000

-.086

.479

30000-45000

Bellow15000

.574

.464

15000-30000

-.038

.519

Above45000

-.124

.532

Above45000

Bellow15000

.698

.419

15000-30000

.086

.479

30000-45000

.124

.532

Timeliness

Bellow15000

15000-30000

-.140

.418

30000-45000

-.409

.483

Above45000

.147

.435

15000-30000

Bellow15000

.140

.418

30000-45000

-.269

.540

Above45000

.287

.498

30000-45000

Bellow15000

.409

.483

15000-30000

.269

.540

Above45000

.556

.553

Above45000

Bellow15000

-.147

.435

15000-30000

-.287

.498

30000-45000

-.556

.553

Security

Bellow15000

15000-30000

.552

.413

30000-45000

.169

.477

Above45000

-.036

.430

15000-30000

Bellow15000

-.552

.413

30000-45000

-.383

.533

Above45000

-.588

.492

30000-45000

Bellow15000

-.169

.477

15000-30000

.383

.533

Above45000

-.205

.546

Above45000

Bellow15000

.036

.430

15000-30000

.588

.492

30000-45000

.205

.546

Courtesy

Bellow15000

15000-30000

-.096

.420

30000-45000

.353

.485

Above45000

-.050

.437

15000-30000

Bellow15000

.096

.420

30000-45000

.449

.542

Above45000

.046

.500

30000-45000

Bellow15000

-.353

.485

15000-30000

-.449

.542

Above45000

-.403

.556

Above45000

Bellow15000

.050

.437

15000-30000

-.046

.500

30000-45000

.403

.556

*= significant at 0.05 significance level.

The above Table 10 shows the significant difference of satisfaction among different income groups where "*"means significant difference at 0.05 significance level. In all four variable groups there is no significant difference in case of income groups. The significant difference analysis within the banks is shown in Table 11.

Table 11

Multiple Comparisons:

Tuckey HSD for Banks

Dependent Variable

(I) Bank having Account

(J) Bank having Account

Mean Difference (I-J)

Std. Error

Ease of use

Allahabad Bank

UBI

-.700

1.043

Axis Bank

-.658

.952

HDFC Bank

-.617

.952

SBI

-.827

.763

ICICI Bank

-1.277

1.043

UBI

Allahabad Bank

.700

1.043

Axis Bank

.042

.952

HDFC Bank

.083

.952

SBI

-.127

.763

ICICI Bank

-.577

1.043

Axis Bank

Allahabad Bank

.658

.952

UBI

-.042

.952

HDFC Bank

.041

.852

SBI

-.169

.633

ICICI Bank

-.619

.952

HDFC Bank

Allahabad Bank

.617

.952

UBI

-.083

.952

Axis Bank

-.041

.852

SBI

-.211

.633

ICICI Bank

-.661

.952

SBI

Allahabad Bank

.827

.763

UBI

.127

.763

Axis Bank

.169

.633

HDFC Bank

.211

.633

ICICI Bank

-.450

.763

ICICI Bank

Allahabad Bank

1.277

1.043

UBI

.577

1.043

Axis Bank

.619

.952

HDFC Bank

.661

.952

SBI

.450

.763

Timeliness

Allahabad Bank

UBI

-1.927

.903

Axis Bank

-.191

.824

HDFC Bank

-2.327

.824

SBI

-1.322

.660

ICICI Bank

-.783

.903

UBI

Allahabad Bank

1.927

.903

Axis Bank

1.736

.824

HDFC Bank

-.401

.824

SBI

.604

.660

ICICI Bank

1.144

.903

Axis Bank

Allahabad Bank

.191

.824

UBI

-1.736

.824

HDFC Bank

-2.137

.737

SBI

-1.132

.548

ICICI Bank

-.592

.824

HDFC Bank

Allahabad Bank

2.327

.824

UBI

.401

.824

Axis Bank

2.137

.737

SBI

1.005

.548

ICICI Bank

1.544

.824

SBI

Allahabad Bank

1.322

.660

UBI

-.604

.660

Axis Bank

1.132

.548

HDFC Bank

-1.005

.548

ICICI Bank

.539

.660

ICICI Bank

Allahabad Bank

.783

.903

UBI

-1.144

.903

Axis Bank

.592

.824

HDFC Bank

-1.544

.824

SBI

-.539

.660

Security

Allahabad Bank

UBI

.244

1.043

Axis Bank

-.801

.952

HDFC Bank

-.528

.952

SBI

-.372

.763

ICICI Bank

-.723

1.043

UBI

Allahabad Bank

-.244

1.043

Axis Bank

-1.045

.952

HDFC Bank

-.771

.952

SBI

-.615

.763

ICICI Bank

-.966

1.043

Axis Bank

Allahabad Bank

.801

.952

UBI

1.045

.952

HDFC Bank

.274

.852

SBI

.430

.633

ICICI Bank

.079

.952

HDFC Bank

Allahabad Bank

.528

.952

UBI

.771

.952

Axis Bank

-.274

.852

SBI

.156

.633

ICICI Bank

-.195

.952

SBI

Allahabad Bank

.372

.763

UBI

.615

.763

Axis Bank

-.430

.633

HDFC Bank

-.156

.633

ICICI Bank

-.351

.763

ICICI Bank

Allahabad Bank

.723

1.043

UBI

.966

1.043

Axis Bank

-.079

.952

HDFC Bank

.195

.952

SBI

.351

.763

Courtesy

Allahabad Bank

UBI

.248

.982

Axis Bank

-.556

.896

HDFC Bank

-1.514

.896

SBI

-.151

.718

ICICI Bank

-.654

.982

UBI

Allahabad Bank

-.248

.982

Axis Bank

-.804

.896

HDFC Bank

-1.762

.896

SBI

-.399

.718

ICICI Bank

-.902

.982

Axis Bank

Allahabad Bank

.556

.896

UBI

.804

.896

HDFC Bank

-.958

.801

SBI

.405

.595

ICICI Bank

-.098

.896

HDFC Bank

Allahabad Bank

1.514

.896

UBI

1.762

.896

Axis Bank

.958

.801

SBI

1.363

.595

ICICI Bank

.860

.896

SBI

Allahabad Bank

.151

.718

UBI

.399

.718

Axis Bank

-.405

.595

HDFC Bank

-1.363

.595

ICICI Bank

-.503

.718

ICICI Bank

Allahabad Bank

.654

.982

UBI

.902

.982

Axis Bank

.098

.896

HDFC Bank

-.860

.896

SBI

.503

.718

*= significant at 0.05 significance level.

In case of the variable bank there is no significant difference found as it is observed in the above Table 11 where "*"means significant difference at 0.05 significance level in all four variable that is ease of use, timeliness, security and courtesy.

Table 12

Dislike with ATM

From the above Table 12 it is observed that the various phenomenons where customers don't prefer with ATM are machine breakdown and the second is poor money quality and thirdly the card locking. The reason in which a particular ATM booth is not working is shown in Table 13.

Table 13

Reason for ATM booth not working

Majority of the customer found that a particular ATM booth is not working because the machine is out of service as well as there is no money to displace, this factor has a response of 78%. And 12% of the respondent agrees that there is no money to deliver and the remaining 10% agrees that the machine found to be out of service.

5.3 Measuring level of satisfaction

Measuring level of satisfaction through total Customer Satisfaction Index is shown in Table 14. All the fourteen variables were asked to the customer that is used in the factor analysis.

Table 14

Total Customer Satisfaction Index

Factors

Important score

Weighted

factor

Satisfaction

score

Weighted

score

To avoid queue

3.121951

6.894769

3.048780

0.210206

Needless cash carry

3.756098

8.295268

3.634146

0.301462

Transaction on non banking hour

3.439024

7.595019

3.585366

0.272309

Merchant visit

2.804878

6.194519

2.951220

0.182814

Easy to use

3.634146

8.025942

3.975610

0.319080

Less Error

2.804878

6.194519

3.073171

0.190368

Speed of transaction

3.170732

7.002499

3.365854

0.235694

Running all time

2.560976

5.655865

2.292683

0.129671

Dealing by Bank

3.268293

7.217961

3.121951

0.225341

Location of ATM booth

2.926829

6.463846

2.682927

0.173420

Amount of transaction

3.146341

6.948634

2.975610

0.206764

Service duration

3.097561

6.840903

3.097561

0.211901

Availability of service

2.731707

6.032923

2.439024

0.147144

Waiting time

2.731707

6.032923

2.365854

0.142730

Total

 

 

 

2.948906

 

 

 

2.948906*2

5.897812382

 

Total Customer Satisfaction Index

58.97812382

It is observed from the above Table 14, the Customer Satisfaction Index observed is 58.978%, which need attention on certain areas where weighted satisfaction is less like ATM should made run all the time, waiting time, availability of service, and amount of transaction etc..

Table 15

Recommendation for ATM

When the recommendation for ATM given by the respondent is observed as it is found in the above Table 15 the number of ATM booth should be increase in new location with better customer service. The withdrawal limit should be increased and there should be better currency quality, security measures should be increase.

Conclusion

Due to the advancement and development in information technology banking practices has been changing rapidly in various dimensions. The satisfaction with ATM users will definitely enhance the performance of service provider to some extent with respect to certain demographic groups. This article may of some use for the further research in improving on certain areas.

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