ISSN: 1306-3057 THE PROPOSED POLICY IN DIGITAL FINANCIAL SERVICE ENHANCEMENT OF KRUNG ... Consequently, Thai financial institutions, especially public banks develop new technology

Eurasian Journal of Analytical Chemistry ISSN: 1306-3057

THE PROPOSED POLICY IN DIGITAL FINANCIAL SERVICE ENHANCEMENT OF KRUNG THAI BANK IN

THAILAND Panitee Karnsomdee, Ph.D.*

* Lecturer, Faculty of Liberal Arts and Management Science, Kasetsart University, Thailand

E-Mail: [email protected]

Received 09 January 2018 ▪ Revised 04 February 2018 ▪ Accepted 27 March 2018

Abstract: The rapid changing landscape of digital technology makes financial institutions,

service-based businesses, develop digital system to support financial service providing. Bank

customers always expect excellent service quality, especially for ‘fintech’ platform as this

business model affecting customer perceived value and the choice of bank. Most financial

institutions in Thailand have realized the digitalized world and offered new technology to

securely provide financial transactions. Digital financial service of Krung Thai Bank, called

‘Krung Thai Next’, has launched to promote digital financial service through accessible and

convenience application. This research was designed to investigate two antecedent factors,

digital service quality and digital customer perceived value, affecting on customer decision

behavior on digital financial service of Krung Thai Bank in Sakon Nakhon Province, Thailand.

This research further proposed enhancement policy in digital financial service of public

financial institutions in Thailand. This research was a quantitative research method. The

samples of 400 Krung Thai Bank Customers were determined by simple random sampling. Data

were collected through 5-point Likert scale questionnaire surveys with Cronbach’s alpha

coefficient of 0.972. Data were analyzed by descriptive statistics and inferential statistics

including the Pearson Product-Moment Correlation and Multiple Regression Analysis. The

results of the research revealed that customers’ opinion on digital service quality, digital

customer perceived value, and customer decision behavior on digital financial service were at

the highest levels with mean scores of 4.25, 4.27 and 4.23, respectively. The research results

from hypotheses testing found that digital service quality and digital customer perceived value

predict customer decision behavior on digital financial service up to 76.20% (Adjusted R-

Square 0.762) at 0.05 significant levels. The digital service quality and digital customer

perceived value were two antecedent factors that significantly affected on customer decision

behavior on digital financial service of Krung Thai Bank in Thailand. The enhancement policies

in digital financial service of public financial institutions in Thailand were to create digital

channel, enable environment, and provide excellent service quality for digital financial service

as well as to develop financial consumer protection rule and regulations in order to ensure the

security of digital technology platform.

Keywords : Digital Financial Service, Digital Service Quality, Digital Customer Perceived

Value, Proposed Policy

mailto:[email protected]

380 Panitee Karnsomdee et.al

INTRODUCTION

Digital financial service seems to be very convenience for the demands of the 21st century bank customers as they become more technology literate. The new platform of banking digital financial service delivers targeted customers more choices and enhance customer perceived value. Accordingly, most financial institutions have to concentrate on quality of digital banking service as this factor is one of the critical key successes in digitalized era. The perceived value of bank customers in responding to their expectations is necessary to build customers decision making in using digital financial banking. Consequently, Thai financial institutions, especially public banks develop new technology platform to serve customers with excellent digital service quality of tangibility, reliability, responsiveness, assurance, and empathy. In order to increase customer perceived value, financial institutions including Krung Thai Bank in Sakon Nakhon Province, Thailand were launched many campaign to drive customer decision making behavior on using digital financial service such as prestige, value for money, and coordination. Although the influence of service quality and customer perceived value on customer decision behavior is well explored, a context of digital financial service that explains new financial technology platform remains unclear. The importance of the above reasons is the cause of the research.

The objectives of this research were as follows. (1) To investigate the levels of digital service quality, digital customer perceived value, and customer decision behavior on digital financial service of Krung Thai

Bank in Sakon Nakhon Province, Thailand. (2) To explore the influence of digital service quality and digital customer perceived value on customer decision behavior on digital financial service of Krung Thai Bank in Sakon Nakhon Province, Thailand. (3) To apply the results of the research and propose enhancement policy in digital financial service of public financial institutions in Thailand. The paper begins with a review of the concepts related to digital service quality and digital customer perceived value affecting on customer decision behavior on digital financial service in order to conceptualize the framework and state the hypotheses. Next, the research methodology, analysis of data and research findings are described. Finally, conclusion and discussion of the research results as well as managerial implications and policies for future research are presented.

LITERATURE REVIEW

A. Digital Service Quality

The financial institutions, service-based businesses, aimed at providing excellent service quality to targeted customers to build competitive advantage, as it is influence on various key factors such as customer satisfaction, customer perceived value, and customer expectation as stated by Amin, M. et al. [1] and Wu, H.C. [2]. Parasuraman, A. et al. [3] defined service quality as the perception of the customer in responding to the action of buying or the expectation achieving on product purchasing. Grönroos, C. [4] and Zeithaml, V.A. et al. [5], are other researchers in the field of service quality that explains service quality as the comparison between customers’ expectation on the present service receiving and their experience of the previous service delivery as well as the assessment of customers between services expecting to services providing. It can be seen that many previous researches have analyzed the service quality based on what customer is expect and what they actually receive. Therefore, service quality is one of the most significant factors to enhance customer satisfaction, customer perceived value, and finally, customer decision making behavior, especially for the new financial service providing with digital technology platform. As the new digitalized platform can serve the bank customers with tangibility, reliability, responsiveness, assurance, and empathy, several instruments from various researches have been developed to measure and explain service quality dimensions. Service quality model (SERVQUAL) developed by Zeithaml, V.A. et al. [5] is the most commonly used measurement tool which compares the service quality receiving to the service quality expecting as stated by Ali, J.F. and Amin, M. [6] and Ali, J.F. et al. [7]. The instrument items propose five dimensions by which customers evaluate service quality: tangibility, reliability, responsiveness, assurance, and empathy. Reliability truly focuses on the outcome of service delivery while the other four dimensions largely concern on the process of service delivery. The conceptual framework of this research was applied service quality model (SERVQUAL) based on Zeithaml, V.A. et al. [5] which including five dimensions; tangibility, reliability, responsiveness, assurance, and empathy to the context of digital technology in financial institutions. Many previous research studies have empirically explored the relationships among service quality, customer perceived value and customer decision behavior as stated by Caruana, A. & Mosahab, R. et al. [8]; Fullerton, G. [9]; Cronin, J.J., Brady M.K., & Hult, G.T. [10]; consequently, this research study aimed to investigate such relationships.

381 Eurasian Journal of Analytical Chemistry

B.Digital Customer Perceived Value

Perceived value has become a significant criterion in the development of business strategies to build, connect, and deliver value to the targeted customer as stated by Kotler, P. & Keller, K. [11]. Gallarza, M.G. & Saura, I.G. [12] defined perceived value as the measurement of assessing the customer perception between actual cost and perceived benefit. The level of customer perceived value is the difference between the service receiving and the visible expectations identified by recognition of customers on the service providing and the service demand. If the service customer receiving is lower than its expectation, negative perceived value occurs. However, if the level of the service meets the expectation, positive perceived value happens and effects on the decision making behavior as stated by Kotler, P. [13]. Dodds, W.B. et al. [14] said that there were the relationships among service quality, customer satisfaction, customer perceived value, and behavioral intention. The conceptual framework of this research was applied the dimensions of customer perceived value developed by Olaru, D. et al. [15] and Nasution, H.N. and Mavondo, F.T. [16] as well as the researcher’s own context on digital financial service in which specified the basic theory of three categories as follows; prestige, value for money, and coordination. High customer satisfaction and perceived value brings about various advantages that support profitable firms, including increase revenues, maintain long-term customer retention, improve corporate image and enhance decision making behavior as stated by Ahearne, M. et al., [17]. As many previous research studies have revealed that there were the relationships among service quality, customer perceived value and customer decision behavior in banking service sector as stated by Cronin, J.J., Brady M.K., & Hult, G.T. [10]; Emre, S.D. [18] and Subrahmanyam, A. and Raja, S.B. [19]; consequently, this research study aimed to investigate such relationships.

C.Customer Decision Behavior on Digital Financial Service

In the concept of customer behavior, customer decision making on purchasing new product or adopting new service, especially for service-based business is a critical topic as stated by Wu, W.W. [20]. Purchase decision behavior is defined as the extent to which the customer concerns on interest and bring about making on selection. Customer decision making behavior can also be defined as the customer behavior on goal setting, possible alternatives gathering, alternative choices evaluating, optimal alternatives selecting, and making a purchase. The five stages of customer decision making have been established based on Gupta, A. et al. [21] as follows; problem recognition, information search, evaluation of choices, purchase decision, and post purchasing stage. In digital financial service, customer seems to be very convenience for decision making on banking transaction as customers have more choices. The perceived value of bank customers in responding to their expectations is necessary to build customers decision making in using digital banking. Customer in digital banking service intended to consider cost saving and time saving as well as the satisfaction with the digital channel in order to make decision on digital financial service. There are three main conceptualizations of customer decision as stated by Bowen, J. and Chen, S. [22]; a behavioral perspective, an attitude perspective, and a composite construct combining both a behavioral and an attitudinal dimension. The conceptual framework of this research was applied customer decision behavior on digital financial service, in which characterized by two major components; an attitude aspect and a behavioral aspect. As many researchers investigated a model for the relationship of service quality, customer satisfaction, customer perceived value and digital financial service decision behavior and found strong relationships among such variables as stated by Mosahab, R. et al. [23]; more investigation in financial institutions in Thailand should be further explored. To conclude, from the literature reviews cited above, it can be seen that there are some relationships among these three variables to further investigate and conceptualize in the conceptual framework with hypotheses development.

CONCEPTUAL FRAMEWORK AND HYPOTHESES

From the reviews of the literature, the conceptual framework of this research was presented in Figure 1. It describes the influence of digital service quality and digital customer perceived value on customer decision behavior on digital financial service of Krung Thai Bank in Sakon Nakhon Province, Thailand. The conceptual framework has been tested on the basis of three bodies of knowledge including digital service quality, digital customer perceived value and customer decision behavior on digital financial service, cited above, as well as the researcher’s own context about the relationship among variables. Base on the reviews of the literature of the constructs with the conceptualization of the relationships among variables, the hypotheses suggested by the conceptual framework can be laid out as follows:

H1: Digital service quality had a significantly positive influenced on digital customer perceived value of Krung Thai Bank in Sakon Nakhon Province, Thailand.


H2: Digital customer perceived value had a significantly positive influenced on customer decision behavior on digital financial service of Krung Thai Bank in Sakon Nakhon Province, Thailand.

H3: Digital service quality had a significantly positive influenced on customer decision behavior on digital financial service of Krung Thai Bank in Sakon Nakhon Province, Thailand.

Fig 1:

The research hypotheses can be described in the forms of structural equations in order to describe the relationship among variables and predict the dependent variable for hypotheses testing. The symbols used to represent the variables stated in the conceptual framework were presented as follows:

DSQ = Digital Service Quality

DPV = Digital Customer Perceived Value

CDB = Customer Decision Behavior on Digital Financial Service

The structural equation can be explained as follows:

DPV = β1 DSQ .………. (1)

CDB = β2 DPV .………. (2)

CDB = β3 DSQ .………. (3)

RESEARCH METHODOLOGY

This research aimed to investigate the influence of digital service quality and digital customer perceived value on customer decision behavior on digital financial service of Krung Thai Bank in Sakon Nakhon Province, Thailand. The research was a quantitative research method. The samples of 400 Krung Thai Bank customers in Sakon Nakhon Province were determined from 1,149,472 populations by using simple random sampling based on Taro Yamane formula [24]. Data were collected through 5-point Likert scale questionnaire surveys. This research was cross-sectional as the data were collected at a single point of time from the key respondents. Content validity was applied to ensure the accuracy of an assessment instrument. Cronbach’s alpha was conducted to test for reliability with Cronbach’s alpha coefficient of digital service quality, digital customer perceived value, and customer decision behavior on digital financial service of 0.934, 0.924, and 0.941, respectively as shown in Table 1. The Cronbach’s alpha value of the scale of all variables is greater than 0.700, so it shows that the scale has very good reliability. Accordingly, data were analyzed by descriptive statistics including frequency, percentage, mean, standard deviation; and inferential statistics including the Pearson’s Product-Moment Correlation and Multiple Regression Analysis. The research results can be significantly analyzed with 95% confidence interval.

Conceptual Framework

3


Table 1:

V. ANALYSIS OF DATA AND RESULTS OF THE STUDY

The research results were analyzed by using the statistical package for social science. The research findings and the hypotheses testing in this research were described as follows.

For description of the respondents, the research findings revealed that the survey data of Krung Thai Bank customers were made up of 65.20% female. The average ages of Krung Thai Bank customers were in between 20-29 years up to 44.80%. In terms of the marital status, Krung Thai Bank customers were single of 58.30%. For the education, Krung Thai Bank customers had earned Bachelor’s Degree of 67.00%. In addition, they were government officer or state enterprise officer up to 43.80%. The average monthly income is in between 10,00120,000 Baht up to 39.20% as stated in Table 2.

Cronbach’s Alpha Coefficient of Variables

Variables Cronbach’s Alpha

Digital Service Quality 0.934

Digital Customer Perceived Value 0.924

Customer Decision Behavior on Digital Financial Service 0.941


Table 2: Description of the Respondents

* TR denotes total respondents.

For descriptive statistics, the collected data were analyzed by using means and standard deviations. The means scores of Krung Thai Bank customers’ opinion on digital service quality, digital customer perceived value, and customer decision behavior on digital financial service were at the highest levels; mean scores of 4.25, 4.27, and 4.23, respectively. To explain in details of digital service quality; tangibility, reliability, responsiveness, assurance, and empathy mean scores were at 4.21, 4.47, 4.36, 4.31, and 4.23, respectively. In addition, digital customer perceived value dimensions; prestige, value for money, and coordination mean scores were at 4.30, 4.25, and 4.25, respectively.

For inferential statistics, the analysis of the correlation coefficient between the two independent variables was investigated. Pearson's Product-Moment Correlation was used to determine the relationship of the independent variables. The objective was to find the magnitude of correlation among the variables and to test for Multi-collinearity. Thus, correlation analysis between the independent variables was presented in Table 3.


Table 3:

Table 3 revealed the relationship between the independent variables that correlation coefficients (r) were exceeding 0.800. As Hair et al. [25] described on the relationship between the variables that it must be less than 0.800 otherwise it may cause multi-collinearity. This research described that the relationship between the independent variables with the highest value of 0.854, which was exceeding 0.800, accordingly the test for the collinearity statistics of tolerance and VIF should be performed. The tolerance value was more than 0.200 and the VIF value was less than 10, thus multi-collinearity problem was not found. Therefore, it can be tested by using Multiple Regression Analysis, a linear model, in order to investigate the influence of digital service quality and digital customer perceived value on customer decision behavior on digital financial service.

The research results from hypotheses testing on the influence of digital service quality and digital customer perceived value on customer decision behavior on digital financial service of Krung Thai Bank in Sakon Nakhon Province, Thailand were presented in Table 4.

Table 4:

***. Predictor is significant at the 0.000 level

In addition, the research results from hypotheses testing can be described in the following diagram as presented in Figure 2 as well as in the form of structural equations as presented below:

Fig 2: Research Results from Hypotheses Testing

DPV = 0.834 DSQ .………. (4)

(30.155)

CDB = 0.854 CPV .………. (5) (32.713)

Correlation Analysis between Independent Variables

VARIABLES DSQ DPV CDB

MEAN 4.25 4.27 4.23

S.D. 0.498 0.582 0.603

DSQ 1

DPV 0.834** 1

CDB 0.814** 0.854** 1

**. Correlation is significant at the 0.01 level.

Research Results from Hypotheses Testing

Model Unstandardized Coefficients Standardized Coefficients

t Sig. Beta Std. Error Beta

H 1 DSQ : CPV 0.974 0.032 0.834 30.155 0.000***

H 2 : CPV CDB 0.884 0.027 0.854 32.713 0.000***

H 3 : DSQ CDB 0.985 0.035 0.814 28.002 0.000***

Adjusted R 2 = 76.20% S.E.E = 0.294 F = 640.29


CDB = 0.814 DSQ .………. (6)

(28.002)

The hypotheses testing found that digital service quality and digital customer perceived value can predict customer decision behavior on digital financial service of Krung Thai Bank in Sakon Nakhon Province, Thailand up to 76.20% (Adjusted R-Square 0.762) at 0.05 significant levels. The digital service quality had a statistically significant direct influenced on digital customer perceived value with standardized coefficients (β) of 0.834. The digital customer perceived value had a statistically significant direct influenced on customer decision behavior on digital financial service with standardized coefficients (β) of 0.854. The digital service quality had a statistically significant direct influenced on customer decision behavior on digital financial service with standardized coefficients (β) of 0.814. To explain in details, the measurement factors of digital service quality and digital customer perceived value should be further investigated to find the most impact for recommendation. The symbols used to represent the predictors stated as follows:

CPV = Customer Perceived Value

CDB = Customer Decision Behavior on Digital Financial Service

DSQ1 = Tangibility CPV1 = Prestige

DSQ2 = Reliability CPV2 = Coordination

DSQ3 = Responsiveness

DSQ4 = Assurance

DSQ5 = Empathy

CPV3 = Value for Money

The research findings on measurement factors revealed the statistically significant positive influenced of tangibility, assurance, empathy on customer perceived value with standardized coefficients (β) of 0.486, 0.124, and 0.246, respectively. Furthermore, prestige, coordination, and value for money had statistically significant positive influenced on customer decision behavior on digital financial service with standardized coefficients (β) of 0.261, 0.288, and 0.380, respectively as presented in the forms of structural equations below:

CPV = 0.486 DSQ1 + 0.124 DSQ4 + 0.246 DSQ5

(11.137) (2.808) (5.211)

..…….. (7)

CDB = 0.261 CPV1 + 0.288 CPV2 + 0.380 CPV3

(6.195) (5.651) (8.229)

……… (8)

In conclusion, according to hypotheses testing, digital service quality and customer perceived value had significantly positive influenced on customer decision behavior on digital financial service of Krung Thai Bank in Sakon Nakhon Province, Thailand. The proposed enhancement policies in digital financial service of public financial institutions in Thailand are as follows. Firstly, public financial institutions in Thailand need to create smart digital channel platform with value for money and enabling security environment for digital financial service in order to increase new customers using digital banking or digital financial service through accessible and convenience application. Secondly, public banks in Thailand have to provide excellent service as well as maintain good relationship with targeted customers in order to interact with their customers to immediately solve some technology problems or system errors as digital platform is the new technology in providing financial transactions. Thirdly, the Bank of Thailand (BOT) has to develop financial consumer protection rules and regulations in order to ensure the system security of digital technology platform as BOT is the central organization to regulate all financial institutions as well as to support financial service providing in the digitalized world to the people in Thailand.

CONCLUSIONS AND FUTURE WORK

This research aimed to investigate the influence of digital service quality and digital customer perceived value on customer decision behavior on digital financial service of Krung Thai Bank in Sakon Nakhon Province, Thailand. This research further proposed enhancement policy in digital financial service of public financial institutions in Thailand. The research results revealed that digital service quality and digital customer perceived value had significantly influenced on customer decision behavior on digital financial service. Thus, the following suggestions from the research findings can be applied as management


policies and guidelines for financial institutions in Thailand. Firstly, excellent service quality; especially for tangibility, assurance, empathy, seems to be very critical success factor to raise digital customer perceived value and keep targeted bank customers in the long run. To increase customer perceived value for the bank customers, system consistency, system security, and customer care service should be strengthening. Smart digital channel platform with value for money and enabling security environment for digital financial service can increase new customers using digital banking or digital financial service through accessible and convenience application. Secondly, all digital customers perceived value dimensions; prestige, coordination, and value for money, can enhance customer decision behavior on digital financial service in the long run. Maintaining good relationship with targeted customers and interaction with their customers can immediately solve some technology problems or system errors on financial transactions. Thirdly, the Bank of Thailand (BOT) has to develop financial consumer protection rules and regulations in order to ensure the system security of digital technology platform. To conclude, digital service quality and digital customer perceived value had significantly positive influenced on customer decision behavior on digital financial service of Krung Thai Bank in Sakon Nakhon Province, Thailand. However, there are many other factors that can be expected to enhance customer decision behavior on digital financial service such as new digital technology platform, financial institution corporate image, digital service environment, or digital customer motivation for further research.

REFERENCES [1]. Amin, M., Yahya, Z., Ismayatim, W.F., Nasharuddin, S.Z. and Kassim, E. (2013). Service Quality

Dimension and Customer Satisfaction: An Empirical Study in the Malaysian Hotel Industry. Services Marketing Quarterly, Vol. 34 No. 2, Pp. 115-125.

[2]. Wu, H.C. (2013). An Empirical Study of the Effects of Service Quality, Perceived Value, Corporate Image, and Customer Satisfaction on Behavioral Intentions in the Taiwan Quick Service Restaurant Industry. Journal of Quality Assurance in Hospitality and Tourism, Vol. 14 No. 4, Pp. 364-390.

[3]. Parasuraman, A., Zeithaml, V.A. and Berry, L.L. (1994). Reassessment of Expectations as a Comparison Standard in Measuring Service Quality: Implications for Further Research. Journal of Marketing, Vol. 58 No. 1, Pp. 111-124.

[4]. Grönroos, C. (2007). Service Management and Marketing: Customer Management in Service

[5]. Competition. 3rd ed., John Wiley and Sons Ltd., England.

[6]. Zeithaml, V.A., Parasuraman, A., and Berry, L.L. (1990). Delivering Quality Service – Balancing Customer Perception and Expectations. New York: The Free Press.

[7]. Ali, J.F. and Amin, M. (2014). The Influence of Physical Environment on Emotions, Customer Satisfaction and Behavioral Intentions in Chinese Resort Hotel Industry. Journal for Global Business Advancement, Vol. 7 No. 3, Pp. 249-266.

[8]. Ali, J.F., Khan, A. and Rehman, F. (2012). An Assessment of the Service Quality Using Gap Analysis: A Study Conducted at Chitral, Pakistan. Interdisciplinary Journal of Contemporary Research in Business, Vol. 4 No. 3, Pp. 259-266.

[9]. Caruana, A. (2002). Service Loyalty: The Effects of Service Quality and the Mediating Role of Customer Satisfaction. European Journal of Marketing, Vol. 36 No. 7, Pp. 811-828.

[10]. Fullerton, G. (2003). When Does Commitment Lead to Loyalty? Journal of Service Research, Vol. 5 No. 4, Pp. 333-344.

[11]. [10]Cronin, J.J., Brady, M.K., and Hult, G.T. (2000). Assessing the Effects of Quality, Value, and Customer Satisfaction on Consumer Behavioral Intentions in Service Environments. Journal of Retailing, Vol. 76 No. 2, Pp. 193-218.

[12]. [11]Kotler, P. and Keller, K. (2011). Marketing Management, 14th ed., Upper Saddle Reiver, NJ: PrenticeHall.

[13]. [12]Gallarza, M.G., and Saura, I.G. (2006). Value Dimensions, Perceived Value, Satisfaction and Loyalty: An Investigation of University Students’ Travel Behavior. Tourism Management, Vol. 7, Pp. 437-452.

[14]. [13]Kotler, P. (2000). Marketing Management: Analyzing Consumer Marketing and Buyer Behavior (The Millennium). New Jersey: Prentice Hall.

[15]. [14]Dodds, W.B., Monroe, K.B., and Grewal, D. (1991). Effects of Price, Brand, and Store Information on Buyers’ Product Evaluations. Journal of Marketing Research, Vol. 28, Pp. 307-319.


[16]. [15]Olaru, D., Purchase, S., and Peterson, N. (2008). From Customer Value to Repurchase Intentions and Recommendations. Journal of Business and Industrial Marketing, Vol. 23 No. 8.

[17]. [16]Nasution, H.N. and Mavondo, F.T. (2008). Customer Value in the Hotel Industry: What Managers Believe They Deliver and What Customer Experience. International Journal of Hospitality Management, Vol. 27, Pp. 204-213.

[18]. [17]Ahearne, M., Mathieu, J. and Rapp, A. (2005). To Empower or Not to Empower Your Sales Force? An Empirical Examination of the Influence of Leadership Empowerment Behavior on Customer Satisfaction and Performance. Journal of Applied Psychology, Vol. 90 No. 5, Pp. 945-955.

[19]. [18]Emre, S.D. (2014). Assessing the Effects of Satisfaction and Value on Customer Loyalty Behaviors in Service Environments: High-speed Railway in Turkey as a Case Study. Management Research Review, Vol. 37 No. 8, Pp. 706-727.

[20]. [19]Subrahmanyam, A. and Raja, S.B. (2016). The Effects of Service Quality on Student Loyalty: The Mediating. Journal of Modeling in Management, Vol. 11 No. 2, Pp. 446-462.

[21]. [20]Wu, W.W. (2008). Choosing Knowledge Management Strategies by Using a Combined ANP and DEMATEL Approach. Expert Systems with Applications, Vol. 35 No. 3, Pp.828-835.

[22]. [21]Gupta, A., Su, B.C., and Walter, Z. (2004). An Empirical Study of Consumer Switching from Traditional to Electronic Channels: A Purchase-Decision Process Perspective. International Journal of Electronic Commerce, Vol. 8 No. 3, Pp. 131-161.

[23]. [22]Bowen, J. and Chen, S. (2001). The Relationship between Customer Loyalty and Customer Satisfaction. International Journal of Contemporary Hospitality Management, Vol. 13 No. 4/5, Pp. 213-217.

[24]. [23]Mosahab, R., Mahamad, O. and Ramayah, T. (2010), Service Quality, Customer Satisfaction and Loyalty: A Test of Mediation. International Business Research, Vol. 3 No. 4, Pp. 72-80.

[25]. [24]Yamane, T. (1973). Statistics an introduction analysis. 2nd ed. New York: Harper & Row. [26]. [25]Hair, J.F., Black, W.C., Babin, B.J., Anderson, R.E. (2010). Multivariate data analysis. 7th ed.

Prentice Hall, Englewood Cliffs.

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ISSN: 1306-3057 THE PROPOSED POLICY IN DIGITAL FINANCIAL SERVICE ENHANCEMENT OF KRUNG ... Consequently, Thai financial institutions, especially public banks develop new technology