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Improvement of the service quality: an empirical research in the banking sector
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1. INTRODUCTION

Since Vietnam officially joined the WTO, the banking industry became one of the leading industries which attracted various domestic and international investors. The Vietnamese banking industry itself also faced many challenges in term of competition, especially when large foreign financial groups and banks entered Vietnam and the market was considerably divided. Since being in the service industry, the increase in banking competition raised the need of identifying the gap and correspondence between provided services and the necessity to improve the current services and retain customers. Although some banks made some steps to improve their services, in general the implementation of service quality control revealed many limitations and did not receive an appropriate concern. The chances that customers are likely to do their transactions through foreign banks required domestic banks to identify and enhance their services to increase their competition in the market. Based on analyses and evaluations on the models that measured service quality, this research applied SERVQUAL model and its scale, as well as the additional factors that altered the model to be suitable to Vietnamese conditions to measure service quality of banks surveyed. The objectives of the research were: (i) to identify variables to measure service quality; (ii) to measure and prioritize the order of the quality improvement in banking for banks studied and give implications for the management of Vietnamese banks.

2. LITERATURE REVIEW

2.1. Service quality

When a product quality is tangible and measurable through tangible criteria such as appearance and durability, service quality is intangible. It can be seen that accompanied services, like distribution, care service and calling service, played an important role in supplying products. Especially in today’s competitive context, competition gradually leaned its focus towards accompanied services; their importance revealed more clearly.

So far, issues on service quality drew attention of many researchers; many different definitions of service quality were analyzed and discussed (Parasuraman et al., 1985; Zeithaml, 1987). Parasuraman et al. (1985) pointed out that consumers found it was harder to evaluate a service quality than a product quality, and that the perception of a service quality was the result of a comparison between the expectation of a consumer and the performance of the experienced service. The authors also stated that quality evaluation was based upon not only the service results but the process of service delivery. After 1980s, many research confirmed the role of measuring and managing service quality in organizations (Lassar, 2000; Yavas and Yasin, 2001); service quality was considered the essential measurement in organizations. There were two schools of thought related to quality. The Northern Europe school of thought based on the Nordic two-variable model (Gronroos, 1984) considered that service quality consisted of the technical quality and the functional quality. The technical quality related to what were served and the functional quality related to how they were served. The American school of thought bases on the five-variable SERVQUAL model (Parasuraman et al., 1988) supposed that service quality consisted of customers’ experience of tangible aspects, reliability, satisfaction, assurance, and their understanding about the services received. There were many researchers who suggested several tools to measure service quality such as SERVQUAL (Parasuraman et al., 1985), SERVPERF (Cronin and Taylor, 1992). Although many research went agaisnt it especially when it came to the issues of gap score, the SERVQUAL is still the most popularly used scale among service providers. Many research successfully applied the SERVQUAL.

2.2. Service quality measurement

In 1985, Parasuraman, Zeithaml and Berry suggested a method of service quality measurement through 22 items; these factors were measured by Likert scale (7 choices), including customers’ expectation and awareness. By calculating scores of difference among factors being able to measure quality of each variable, the score of each variable was the average score of each item among those selected items. For each responser, quality measured for each variable and responsive variables were calculated according to the formula:

In the formula, SQi was the service quality of the item i, SQi was the service quality of the variable j (measured by i items), Eij was the expected quality for the item i in the variable j, Pij was the perceived quality for the item i in the variable j and nj was the number of items of the variable j. After that, the avarage score for each variable was measured through the results of responsers; a positive score expresseed that the awareness was more than expectation and vice versa.

However, the traditional way of calculation faced the problem that whether the same difference between the perceived quality and the expected quality reflected the difference between the internal evaluation scores? The above problem can be resolved thanks to a difference measurement method that applied the ratio of quality to the score of the expected quality and was suggested by Young-pil Kim et al. (2004). The comparision of the score ratios provided a more comprehensive view on the disparity between the scores of customers’ expectation and perception and allowed to point out the quality difference with the same score disparity among two or many situations. Then, service quality for each item and responsive variables represented the following formula (when SQi, SQj > 1 meaning the implementation was better than expecting and vice versa)

This calculation method was able to classify accordingly to scores aquired to create a priority for the improvement of service quality. This new method possessed more advantages than the traditional calculation; it provided priority for better quality improvement since it was sucessful in solving the above-mentioned problem. With the average scores of each item which customers evaluate for businesses and their competitors. Businesses can conduct an analysis to enhance quality relying on a comparison with competitors. Assuming that there were k banks using the analysis, perception of customers about service quality of each bank was presented through the matrix n x k. There, n was the number of items which were measured and k was the number of banks using the analysis. This measurement was based on the approach of the entropy index (Di) (Sannon and Weaver, 1947) of the item i with pim was the probability distribution between the score of business m in the item i compared with the total score acquired from bank k in the responsive item and Di was calculated as followed:
 

In this case, the index entropy Di (Sannon and Weaver, 1947) can be used to measure the level of dispersion or the concentration of each item i compared with the correlation of this item in the industry (particularly banking industry). This was a suitable approach with the identification of the level of business effort in quality improvement (Yong-pil Kim et al., 2004) to create a compatative strategy relying on the differences. According to this, entropy Di of the item i would receive the value between 0 to 1 and the higher Di towards value 1 the more perceived quality of customers for item i was responsive (Sannon and Weaver, 1947). The ratio (importance) of items was identified according to two levels: the level of service quality of the business which was evaluated by the customers and the prioritize competative ratio Di and there, the ratio Fi (Fi was the priority of improvement of the item i) was suitable for combining the two above levels in order to define the priority to enhance the improvement of the item i (Hwang and Yoon, 1981) was calculated as the following formula: .
3. RESEARCH METHODOLOGY
 
3.1. The size of the samples and data collection

Since a questionnaire was used to obtain data, we were careful to ensure that the questionnaire was complete and concise; and that it would allow us to achieve our research objectives. A pilot was conducted among 30 customers of banks in Danang City. The research then was conducted on a sample of 1400 customers; the interviewers were graduates in business administration field of University of Economics (academic year 2008 and 2009). Data was collected from October 2009 to December 2009. The number of questionaires collected was 1,214, however, those that lacked information were rejected; therefore, there were finally 1,134 questionaires were used forthe data processing.

3.2. Validity and reliability

The research was conducted through exploring the factor analysis in order to evaluate the service quality measurement scales in Vietnamese banking (Churchill, 1979). In exploring factor analysis session, by using extracted principal component method, viramax rotation, the results showed that the two items DB4 and DC5 had a factor loading coefficient less than 0.5 and therefore, rejected these items (Hair et al., 2009). After rejecting 3 items (factor loading <0.5), we reconducted the factor analysis process with 25 items, the results showed that KMO = 0.898 and sig.=0.000 < 0.05; thus, we were able to affirm that the data was suitable to do the factor analysis. Through the results, we confirmed that there were 6 factors existing in the model:

(1) Tangibles (TA);

(2) Assurances (AS);

(3) Reliability in service providing process (RS);

(4) Reliability in keeping promises to customers (RP);

(5) Sympathy and Response;

(6) Branch network and ATM (BN).

We examined reliability of the constructs by calculating the Cronbach’s alpha coefficient for multi-item scales. According to Hair et al. (2009), values above 0.7 were acceptable. A result of this process showed that good reliability of the measures was demonstrated, as all of the alpha values were higher than the value of 0.7.

Table 1: Components of the service quality measurement scale in banking services

TA1

Modern equipment

Component 1:

Tangibles

TA2

Spacious facilities

TA3

Neat employees/staff

AS1

Bank’s reputation in serving capability

Component 2:

Assurances

AS2

Employees are reliable to customers

AS3

Safety in transactions

AS4

Courteous, elegant employees

AS5

Employees have expertise knowledge to answer customers

RS1

Implementing services right in the first time

Component 3:

Reliability in services providing process

RS2

Care about solving problems faced by customers

RS3

Pay attention not to have errors/mistakes happened

RS4

Employees handle transactions skilfully

RS5

Employees inform customers when services will be done

RP1

Provide services on the quality companies committed to provide

Component 4:

Reliability in keeping promises to customers

RP2

Provide services at the time companies committed to provide

RP3

Sufficient enclosed documents in doing services

SR1

Bank have programs showing their care for customers

Component 5:

Sympathy and response

SR2

Each employee show their care for customers

SR3

Bank has flexible transaction schedule

SR4

Employees understand customers’ demand

SR5

Provide cutomers with services quickly

SR6

Employees are willing to help customers

SR7

Employees are never too busy to answer customers’ requests

BN1

Having a wide network of branches

Component 6:

Branch networks

BN2

Having a convinient network of ATM

4. THE ANALYSIS RESULTS

4.1. Profile of the respondents

With the size of 1,134 samples assembled including 8 banks in Vietnam, Vietcombank had 303 samples (accounted for 26.71%), EAB (21.25%), Agribank (14.55%), and Techcombank (13.66%).

Table 2: Sample size by bank

Name of the Bank

Number of samples

Percentage

EAB

244

21.51

Agribank

165

14.55

Vietcombank

303

26.71

Techcombank

155

13.66

BIDV

54

4.76

ACB

71

6.26

Military Bank

70

6.17

Maritime Bank

72

6.34

Total

1134

100

Of the total 1,134 interviewees, 525 were males and 609 were females; most of them were between 18 to 25 years old (accounted for 40.7%) and between 25 – 35 (27.7%).

Table 3: Sex, age, job, education of the interviewees

Quantity

%

Quantity

%

Sex:

Education:

Male

525

46.3

Secondary

108

9.5

Female

609

53.7

High school

156

13.8

Age:

Vocational College

241

21.3

18 - 25

461

40.7

Undergraduate

583

51.4

25 - 35

314

27.7

Postgraduat

45

4,0

35 - 45

136

12.0

Income (VND):

45 - 55

115

10.1

< 1   million

197

17.4

55 – 65

108

9.5

1 - 2 million

311

27.4

Job:

2 - 3 million

293

25.8

Students

182

16.0

3 - 4 million

148

13.1

Officials

642

56.6

4 - 6 million

96

8.5

Businessmen

157

13.8

6 - 8 million

51

4.5

Armed forces

82

7.2

8 - 10 million

32

2.8

Retired

71

6.2

> 10 million

6

0.5

Most of interviewees were officials (642 people, made up 56.6%) and students with 16.0%. The research focused on the officials because they were employed and working in companies that pay salaries through ATM accounts and involve in services of receiving and transfering money.

Regarding to education, the group having a bachelor degree was dominant with 583 respondents (51.4%). The next group having a vocational or a associate degree was with 241 interviewees (21.3%). In terms of income, the group having the highest number of interviewees was the group having income of 1-2 million (accounted for 27.4%) and from 2-3 million with 25.8%. Information about service usage duration, frequency of using and services used is presented in the following table:

Table 4: Information about banking transactions of respondents

Related information

Frequency

Percentage (%)

Usage duration

Less than 1 years

198

17.5

1- less than 2 years

492

43.4

2 – less than 3 years

265

23.4

More than 3 years

179

15.8

Frequency / month

1 times

327

28.0

2 – 4 times

593

52.3

5 – 8 times

157

13.8

More than 9 times

57

5.0

According to the interviewees, services used most were ATM (742), depositing savings (574), transfering and receiving money (243) or using individual credit.

Table 5: Services used by respondents

Services used

Frequency

Deposit savings

574

Deposit payment

88

Overseas national currency remittances

181

Transfer, receive money

243

ATM services

742

Individual credit

209

4.2. Scores of services quality and priority for quality improvement for each bank

With the two methods of calculation given in the theory section, the research calculated scores of service quality for each measurement item and total service quality for each bank surveyed, the results for each bank (for both calculation methods) was presented in the table 6 and 7.

In table 6, the calculation method of ratio scores provided a more comprehensive view on service quality that banks conducted, even when scores for each item in the distance scores method produced equal quality (equal improvement priority), ratio scores method also gave the results of how much service quality implemented meet the customers’ expectation. For instance, with EAB bank, the two items AS5 and SR6 had the same distance scores of -0.178 but the response level compared with customers’ expectation was different from ratio score method with the scores were 0.968 and 0.967 respectively (it meant that the implentation of EAB in service quality meet 96.8% of the customers’ expectation).

Simultaneously, the calculation results in table 7 introduced the priority of service quality improvement established for each bank basing on the calculation method with Entropy (Di) and Fi. This way allowed banks to be aware of the improvement priority for each item. For example, with EAB bank, the two factors AS5 and SR6 bore the same service quality (-0.178) but the priority for improvement was different (item AS5 ranked 13th and SR6 ranked 15th).

5. IMPLICATIONS FOR MANAGEMENT PRACTICE IN VIETNAM'S BANKS

5.1. General meaning of establishing priority coefficients for service quality measurement

At the business level, the establishment of quality improvement priority allows banks to identify the current level of the service quality (based on its customers’ points of view), establish competitive improvement of the service quality. Concurrently, banks can compare service quality between different period and contribute to the evaluation of banks’ operation effectiveness. At the level of industry, the service quality measurement can be implemented to assess service quality among banks in the industry and compare and rank banks in terms of providing services, as well as provide the macro planners with a foudation to prioritize quality improvement in the industry.

5.2. Implications in building banks’ strategies

Measuring the service quality is a foundation and an activity conducted throughout the strategic planning process of all banks, all the activities 1, 2, 3, 4, 5 are around the focus in order to shorten the gap between the customers’ expectation and perception about the service quality provided by the bank.

Based on the model, banks operate and communicate not only in accordance with the subjective opinions of its managers but also customers’ expectation about implementation of service quality and whether banks capture customers’ expectation correctly. With what banks did and conveyed to customers, banks can start to gather customers’ evaluation to know the level of the current service quality to create a reasonable communication strategy (based on customers’ points of view).

Additionally, businesses can analyze the service quality standard in terms of competition to prioritize urgent factors in quality improvement. Doing this step not only helps businesses to improve the current way of operation to be more appropriate to customers’ expectation but also to compete with other rival banks. With changed created, businesses will communicate with customers, change customers’ expectation and perception about the service quality offered by businesses. Doing this can help narrow the gap between customers’ expectation and perception about service quality, improve the competition capacity – the primary factor in doing banking business (Huy and Thao, 2008).
 

6. CONCLUSION

Quality measurement scale SERVQUAL can be used broadly in service organizations to improve the service quality. This method involves the understanding of targeted customers. The result gained from measuring perception about the service quality and compare with what customers expect can be used in quality improvement. In banking businesses where competition is fierce, the main reason customers may leave a business is because of poor services. It is not because of having no services. Therefore, we can realize the necessity of checking the present services to upgrade services to enhance the competitive advantages. It can be said that quality improvement in banking services is condidered the survival in the competition among organizations providing finance services. Measuring the service quality will help banks capture and conduct enhancements needed for services provided. Moreover, classification of scores in measuring quality allows organizations to focus their resoursces on improving services attributes needing the most concern.

REFERENCES

Vietnamese

· Lê Văn Huy and Phạm Thị Thanh Thảo, 2008. “Phương pháp đo lường chất lượng dịch vụ trong lĩnh vực ngân hàng: Nghiên cứu lý thuyết”, Tạp chí ngân hàng, 23-29.

· Minh Đức, Sửa đổi Thông tư 13: Một từ nhỏ, giá trị lớn..
 
· UNDP, 2005. “Nghiên cứu khả năng cạnh tranh và tác động của tự do hoá dịch vụ tài chính: Trường hợp ngành ngân hàng”.

English

· Bahia, K. and Nantel, J. 2000. A Reliable and Valid Measurement Scale for the Perceived Service Quality of Banks. The International Journal of Bank Marketing. 18, (2), 84-91.

· Churchill Jr., G. A. 1979. A paradigm for developing better measures of marketing constructs. Journal of Marketing Research, 16, 64–73.

· Cronin, J. J. and Taylor, S. A. 1992. Measuring Service Quality: A Reexamination and Extension. Journal of Marketing, 56 (July), 55-68.

· Gronroos, C. 1982. ‘’Strategic Management and Marketing in the Service Sector’’, Swedish School of Economics and Business Administration, Helsingfors.

· Gronross, C. 1984. A Service Quality Model and Its Implications. European Journal of Marketing. 18, 36-44.

· Hair, J. F. Jr., Black, W. C., Babin, B. J. and Anderson, R. E. (2009), Multivariate Data Analysis (7th edition), Prentice-Hall, 816 pgs.

· Lisa J. M. C. 2004. Measuring service quality: A review and critique of research using SERVQUAL, International Journal of Market Research, 46, 4, 479-498.

· Lotfollah N., Ram R. B. 2006. Service quality: A Case Study of a Bank, The Quality Management Journal, 13, 3, 35-44.

· Parasuraman, A., Zeithaml, V.A. and Berry, L.L. 1985. A Conceptual Model of Service Quality and Its Implications for Future Research, Journal of Marketing, Fall 1985, 41-50.

· Parasuraman, A., Zeithaml, V.A. and Berry, L.L. 1988. SERVQUAL: a multi-item scale for measuring consumer perceptions of the service quality, Journal of Retailing, 64, 1, 12 - 40.

· Ugur Y. and Martin B. 2007. Service quality assessment: a comparison of Turkish and German bank customers, Cross Cultural Management: An International Journal, 11, 2, 161-168.

· Yong-pil Kim, Seok-hoon Lee and Deok-gyun Yun. 2004. Integrating current and competitive service-quality level analyses for service-quality improvement programs, Managing Service Quality, 14, 4, 288-296.

· Zeithaml, V.A. 1988. Consumer Perceptions of Price, Quality, and Value: A Means-End Model and Synthesis of Evidence. Journal of Marketing, 52 (July), 2-22.
 
 
 
 
Source: The Vietnam’s Socio-Economic Development Review - No.64, December 2010
 
 
 
Truong Ba Thanh Le Van Huy