




































ASIAN FINANCE & BANKING REVIEW 8(1) (2024), 1-12

 

1 

 

FINANCE & BANKING REVIEW 
  ASFBR VOL 8 NO 1 (2024) P-ISSN 2576-1161   E-ISSN 2576-1188 

Journal homepage: https://www.cribfb.com/journal/index.php/asfbr 

Published by Asian Finance & Banking Society, USA 

DETERMINANTS OF CUSTOMER SATISFACTION IN RETAIL 

BANKING: EMPIRICAL EVIDENCE FROM JAPANESE BANK 

CUSTOMERS                                                          

 
 Yuji Mori (a)1    Yasufumi Ozaki (b)     Kozo Harimaya (c) 

 

(a) Professor, Faculty of Economics, Takasaki City University of Economics, Gunma, Japan; E-mail: y.mori@tcue.ac.jp 

(b) Professor, Faculty of Economics, Kushiro Public University of Economics, Hokkaido, Japan; E-mail: ozaki@kushiro-pu.ac.jp 

(c) Professor, College of Economics, Ritsumeikan University, Shiga, Japan; E-mail: harimaya@fc.ritsumei.ac.jp 

 

 
A R T I C L E I N F O 

 
 

Article History: 
 

Received: 4th March 2024 

Reviewed & Revised: 5th March  

to 11th June 2024 

Accepted: 12th June 2024 

Published: 16th June 2024 

 
Keywords: 

Customer Satisfaction, Ordered Probit 
Analysis, Financial Literacy, Security 

Investment, Financial Services 

Marketing, Retail Banking. 

 
      JEL Classification Codes:  

 

      G2, G20, G21 

       

      Peer-Review Model:  

 

      External peer-review was done through  

      double-blind method. 
 

 
A B S T R A C T 
 
 

As a consumer-oriented service industry, the quality of customer service provided by banks and their 

customers' overall satisfaction with their services are becoming increasingly important. This study 
examines the factors influencing customer satisfaction with banking services provided by Japanese 

regional banks. Using data from the Japan Financial Institution Customer Ratings METER® of about 

200,000 cases, we estimated the factors affecting customer satisfaction using an ordered probit model. 

The results indicate a positive correlation between direct financial services from regional banks and 

customer satisfaction. This relationship is solid when customers hold investment-related products. 

Additionally, we observed that individual customer satisfaction tends to decline with increasing financial 

asset holdings and increase as customers become more financially literate. Furthermore, we noticed that 
customer satisfaction tends to be higher for females than males, younger people than the elderly, and 

occupied customers than for unoccupied customers. The findings of this study suggest that customers 

may be more attracted to regional banks that provide investment information and advice tailored to their 

circumstances. It may be beneficial for regional banks to understand better factors that influence 

customer satisfaction, such as the age and gender of their customers, their level of financial Literacy, 

and the amount of financial assets they have. It would be beneficial for regional banks to consider these 

factors and enhance the quality of their direct interactions with customers and the customer service 

provided by their staff and call centers. This could help regional banks build long-term, ongoing 
relationships with their customers. 

 
 

© 2024 by the authors. Licensee Asian Finance & Banking Society, USA. This article is an open 

access article  distributed under the terms and conditions of the Creative Commons Attribution (CC 

BY) license (http://creativecommons.org/licenses/by/4.0/). 

                                                                  

 

INTRODUCTION 

The past two decades have witnessed a profound transformation within the banking industry, with global and regional shifts 

occurring concurrently. The banking industry must continually adapt to mounting competition from non-banking financial 

institutions, shifting demographics and social trends, the advent of information technology, such as digital banking, FinTech, 

and robot advisors, evolving channel strategies, and new entrants into the banking industry. The banking industry has 

experienced significant disruption from non-banking industries due to government deregulation of the financial services 

sector, changing customer preferences and needs, and regulatory changes (Annin et al., 2014; Byers & Lederer, 2001). 

The expansion of financial product delivery channels has prompted banks to adopt a more assertive approach to 

marketing new and more sophisticated financial products, including investment trusts and mutual funds. This expansion has 

led to an increase in the number of individual investors who are actively engaged in investing in investment trusts and 

mutual funds. In Japan, it has become common practice for inexperienced individual investors to commence their 

participation in the securities market by investing in investment trusts. Furthermore, the continued aging of the population 

has invested in investment trusts, a more popular choice among older people, who have accumulated more assets than the 

younger generation to fund their retirement. In addition, the Japanese government has implemented policies to expand the 

Nippon Individual Saving Account (NISA) and defined contribution pension plans, which have led to a greater prevalence 

of investment in investment trusts by individuals. The entry of individual investors into the securities market through 

investment trust or mutual fund investments has also been observed in emerging Asian countries such as Malaysia, where 

                                                      
1Corresponding author: ORCID ID: 000-0003-2034-2262 
© 2024 by the authors. Hosting by Asian Finance & Banking Society. Peer review under responsibility of Asian Finance & Banking Society, USA.  

https://doi.org/10.46281/asfbr.v8i1.2216 

 
To cite this article: Mori, Y., Ozaki, Y., & Harimaya, K. (2024). DETERMINANTS OF CUSTOMER SATISFACTION IN RETAIL BANKING: 

EMPIRICAL EVIDENCE FROM JAPANESE BANK CUSTOMERS. Asian Finance & Banking Review, 8(1), 1-12. 

https://doi.org/10.46281/asfbr.v8i1.2216 

http://creativecommons.org/licenses/by/4.0/)
http://creativecommons.org/licenses/by/4.0/)
http://creativecommons.org/licenses/by/4.0/)
http://creativecommons.org/licenses/by/4.0/)
https://www.openaccess.nl/en
https://doi.org/10.46281/asfbr.v8i1.2216
https://orcid.org/0000-0003-2034-2262
https://orcid.org/0000-0001-5973-2503
https://orcid.org/0000-0001-5354-4907


Mori et al., Asian Finance & Banking Review 8(1) (2024), 1-12

  

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mutual fund investments by individual investors are becoming increasingly prevalent (Mahdzan et al., 2020; Ripain & 

Ahmad, 2018). 

Comprehensive financial services, including investment advice and financial planning, have become crucial to 

banks' retail business. Moreover, the perspective from which individual customers evaluate financial institutions is 

transforming. In addition to traditional evaluation items such as accuracy and speed, the quality of financial services, 

including customer support and counseling, and customer satisfaction with these services are becoming increasingly 

important (Ananda & Devesh, 2018). It has been proposed that enhancing customer satisfaction also influences bank 

profitability (Anderson et al., 1994; Nagar & Rajan, 2005), and improving customer satisfaction has emerged as a pivotal 

strategic objective for bank management. A substantial body of research has been conducted on evaluating banks' retail 

services and customer satisfaction with their clients, including an analysis of e-banking (Ananda et al., 2023; Cambra-

Fierro et al., 2017; Egala et al., 2021; Kaur et al., 2021; Pakurár et al., 2019). Nevertheless, to date, no study has been 

conducted on customer satisfaction among users of banking services, focusing on their investment advice rather than on a 

specific bank. Instead, we conducted a study on users' data of many banks. 

This study examines the factors that influence customer satisfaction among Japanese regional banks. Japanese 

regional banks maintain a dense branch network within the prefecture of their head office, including urban and regional 

areas. They provide services that are closely linked to individual customers. Concentrating on regional banks was preferable 

to comprehend the patterns of customers utilizing financial services in Japan as a whole, including in the regions, and to 

evaluate the quality and quantity of financial services. 

This study examines the factors influencing customer satisfaction with banking services, focusing on the influence 

of information channels and the content of investment advice. The analysis will consider several socio-demographic factors, 

including the client's age group, gender, asset level, and Financial Literacy. In this study, we employed the Japan Financial 

Institution Customer Ratings METER®, a distinctive and expansive database that has not been extensively utilized to date, 

to investigate the factors influencing customer satisfaction, focusing on socio-demographic variables. We employed an 

ordered probit model to analyze the data. 

The remainder of this paper is organized as follows: The subsequent section reviews the pertinent literature and 

develops the hypotheses. Section 3 presents the data and methodology employed in this analysis. Section 4 presents the 

estimated model's findings, while Section 5 discusses the results. Finally, Section 6 contains concluding remarks. 

 

LITERATURE REVIEW 

Effect of Advice on Customer Satisfaction 

Several studies have demonstrated that individual customers of financial institutions are influenced by the investment advice 

and information provided by financial institutions in the execution of their customers' financial transactions and the amount 

of their investments. Kramer (2012) revealed that financial advisors assisted clients in diversifying their portfolios, reducing 

volatility, and decreasing the turnover ratio. Another study also showed a positive impact on investment performance, 

particularly when investors place trust in their investment advisors (Monti et al., 2014). Bhattacharya et al. (2012) examined 

individual investors in Germany. They found that the advice was received by wealthier male investors who had a more 

extended history with their brokers and that the advice improved efficiency. 

Conversely, other studies indicated that investors needing more financial Literacy should seek investment advisors, 

which does not necessarily imply that they receive advice. Mullainathan et al. (2012) also proposed that financial advisors 

may have a conflict of interest. While financial advisors may encourage individual investors to pursue financial returns more 

strongly, they also strongly recommend active funds that could earn higher fees for investors. 

Previous studies have indicated that investment advice provided by financial advisors may only sometimes benefit 

investors. However, it may facilitate risk-taking, enhance performance, and enhance customer satisfaction. 

 

H1: There is a positive correlation between banks' information or advice and customer satisfaction with banking services. 

 

Effect of Service Quality on Customer Satisfaction 

Another factor that affects customer satisfaction with banks is the quality of banking services. Many empirical studies have 

employed multivariate analysis techniques, such as SERVQUAL or path analysis, frequently utilized in previous marketing 

research, to investigate the relationship between banking services and customer satisfaction within the banking industry. 

These studies have consistently demonstrated that enhancing the quality of banking services can positively impact customer 

satisfaction and have a favorable impact on bank profitability (Boonlertvanich, 2019; Halim et al., 2023; Johnston, 1997; 

Oppewal & Vriens, 2000; Paul et al., 2016; Teeroovengadum, 2022; Varki & Colgate, 2001). 

Uddin (2020) demonstrated that the quality of banking services, including exemplary ATM service, mobile banking, 

and call center quality, is paramount in fostering customer loyalty and enhancing customer satisfaction. The superiority of 

conventional or regular financial advising methods may be more advantageous than e-banking for older clients who have 

more assets but are aware that they could be more financially literate and are cautious about managing their investments. 

Furthermore, it has been demonstrated that the quality of service provided by financial planners or advisors regarding advice, 

including ease of contact, reliability, and empathy, also affects customer satisfaction (Gazi et al., 2021; Jamal & Naser, 

2002). Financial services that prioritize communication with individual customers and aim to resolve their issues enhance 

customer satisfaction. Carsamer (2018) also examined the factors influencing customers' perceptions of Ghana's financial 

products and banking services. The study found that the frequency and regularity of visits by bank employees positively 

influenced customers' perceptions of the bank's services. 

The results indicate that the quality of service to customers, mainly how they are approached, and the human 



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contact that enhances the quality of service are significant factors contributing to satisfaction with bank services. In light of 

the preceding discussion, this study proposes the following hypothesis: 

 

H2: How customers are approached affects their satisfaction with banking services. 

H3: A direct customer approach by salespeople is associated with greater customer satisfaction with banking services. 

 

Effect of Socio-demographic Factors on Customer Satisfaction 

Recent studies have demonstrated that socio-demographic factors significantly influence customer satisfaction with 

financial services (Chattha, 2019; Darko et al., 2017; Gan et al., 2011; Seiler et al., 2013; Widityani et al., 2020). In a study 

of New Zealand electric banking (EB) users, Gan et al. (2006) considered socio-demographic factors. They found that 

individuals with higher incomes were less likely to use EB. In their 2014 study, Okeke and Okpala employed a binomial 

and multi-item logit model to analyze the impact of socio-demographic factors on Nigerian customers' use of EB. Their 

findings indicated that socio-demographic characteristics such as male gender, college graduation, student status, office 

work, and unmarried status were significant. 

Li et al. (2005) employed a multinomial probit model to investigate the factors influencing customers' demand for 

a range of financial products and the ordering patterns of these products. The findings indicated that female and older 

individuals exhibited a heightened sensitivity to their overall satisfaction with the banking institution, relative to male and 

younger individuals, regarding the decision to purchase supplementary financial products. 

Furthermore, socio-demographic factors influence how banks and financial products are perceived. In a study by 

Carsamer (2018), the factors affecting customer perceptions of financial products and banking services in Ghana. The results 

indicated that socio-demographic characteristics, such as age, marital status, and income, contribute to increased awareness 

of available services. Based on this discussion, this study assumes the following hypothesis. 

 

H4: Socio-demographic factors significantly influence customer satisfaction with banking services. 

 

Effect of Financial Literacy on Customer Satisfaction 

A lack of financial Literacy among individual investors is a pervasive issue affecting many global investors (Lusardi & 

Mitchell, 2011). Over the past few decades, many studies have been conducted on the effects of client financial literacy and 

investment advice on investment decisions. In particular, many researchers have studied to assess the impact of financial 

and investment Literacy on judgments about a range of financial products and services, including stock investments, mutual 

fund investments, retirement planning, and mortgage financing. (Fornero & Monticone, 2011; Gerardi et al., 2010; Mahdzan 

et al., 2020; Müller & Weber, 2010; Van Rooij et al., 2011). Nevertheless, the evidence regarding the significance of 

financial Literacy in these financial decisions is inconclusive. Some studies have indicated a significant positive correlation 

between financial Literacy and financial decision-making, whereas others have demonstrated a relatively weak relationship. 

In their research, Jamal and Naser (2002) showed that customer expertise plays a role in influencing customer satisfaction 

in the context of retail banking. In particular, a negative correlation exists between customer expertise and satisfaction, 

indicating that customers with expertise tend to be less satisfied.   

Financial Literacy has been demonstrated to be associated with investment decision-making, specifically the 

selection of financial products and stock investments. In their study, Van Rooij et al. (2011) utilized data from Dutch 

households to investigate the relationship between financial Literacy and investment decisions. Their findings indicated that 

individuals with excellent financial knowledge were likelier to invest in stocks, whereas those with limited financial Literacy 

were less inclined. Conversely, the satisfaction derived from financial advice financial institutions provide is contingent 

upon the clients' financial literacy level. Kramer (2016) posited that financially literate clients are less likely to seek financial 

advice, and additionally, this relationship is more pronounced in households with more significant assets. 

Conversely, Calcagno and Monticone (2015) discovered that individuals with superior financial Literacy were 

more prone to utilize investment advisors. Moreover, Calcagno and Monticone (2015) discovered that individuals with 

elevated financial Literacy were more prone to use investment advisors. Vlašić et al. (2022) also found that individuals with 

low financial Literacy, compared to those with high financial Literacy, were more likely to rely on subjective cues (e.g., 

customer feedback) in generating cognitive loyalty when recommending financial products to others. This study indicates 

that individuals with limited financial Literacy are prone to making decisions that may not be entirely rational. As previously 

discussed, financial Literacy affects the investment behavior of retail customers of financial institutions because it affects 

individuals' asset choices. Furthermore, the presence of investment advice by financial institutions can have a complex 

impact on their decisions and customers' satisfaction with their financial institutions. In light of the preceding discussion, 

this study predicts the following hypothesis: 

 

H5: Customers' financial literacy level significantly influences customer satisfaction with banking services. 

 

MATERIALS AND METHODS 
In this research, a quantitative analysis is performed using the results of a questionnaire survey that includes the satisfaction 

levels of customers of Japanese regional banks. The survey results utilized in this study were derived from the 2019 and 

2020 editions of the Japan Financial Institution Customer Ratings METER®, a database of the results of an online 

questionnaire survey on the evaluation of financial institutions conducted every August among Japanese adult aged 20 and 

over, with approximately 170,000 responses received in each year. Nikkei Research Inc. provides the METER®. The Japan 

Financial Institution Customer Ratings METER® is a database of the results of an online questionnaire survey on the 



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evaluation of financial institutions conducted every August among the general population of individuals aged 20 and over 

nationwide. Each year, the METER® receives approximately 170,000 responses. The individual questionnaire results are 

available for 46 regional banks and 12 second-tier regional banks in the 2019 data set and 45 regional banks and 12 second-

tier regional banks in the 2020 data set, with one fewer regional bank. For this paper, the term "regional banks" encompasses 

the banks above and Saitama Resona Bank. Those who utilized these banks were included in the analysis. 

The questionnaire comprises 30 questions designed to elicit information on various socio-demographic factors for 

each respondent. The questionnaire includes questions regarding the respondents' gender, age, area of residence, Occupation, 

the number of financial assets held, and customer characteristics such as savings and investment style and financial Literacy. 

The questionnaire includes questions about the respondent's relationship with the financial institution. These include the 

points of contact between the respondent and each financial institution, the services provided at the financial institution, and 

the overall satisfaction level of the financial institution used. The 30 questions in this paper address various topics, including 

gender, age, Occupation, financial assets, products and services currently utilized by financial institutions, contact with 

financial institutions within the past year, overall satisfaction with the financial institutions used, and Financial Literacy. 

For reference, these questions are presented in Table 1. The sample size for 2019 was 10,890, while that for 2020 was 

10,601. 

 

Table 1. Customer Satisfaction Factors 

 
Variables Definition 

 Personal attributes and bank competition 

 Gender 

Age 

Female=0; Male=1 

 The class value for each age group is divided into 13 classes, from age 20 to 79 and 80 and above in 5-year age increments. 
Each age group value (e.g., 22 for ages 20 to 24) 

 Occupation 0 for retirees, unemployed persons, and others without regular employment and 1 for those with other regular jobs. 

 Assets Logarithmic value of total financial assets expressed as the median for the class (e.g., 2 million yen for 1 to 3 million yen, etc.) 

 Literacy Financial Literacy; The overall score for the 10 questions was calculated for each individual, with +2 for correct answers, -2 

 HHI Herfindahl-Hirschman Index: Calculated from the share of total deposits by financial institution and business type by 

prefecture. 

 SHR Deposits Market Share: Calculated from total deposits by financial institution and business category by prefecture. 

Contacts viewed in the past year   

 Staff Salespeople visits, phone calls, in-store 

 CallCenter Call center 

 Website Website, Smartphone Apps, Homepage 

 Events Customer events and seminars organized by the bank 

 SNS Social Networking Sites, i.e. Facebook, LINE, Twitter etc. 

 Pop-up Online video commercials and pop-up ads 

 Trainads Train ads, DM flyers, Brochures, and other ads 

 None None 

Products and services currently used; 

 Deposit Deposits and Settlements related (Ordinary and fixed deposits,  Foreign Currency Deposits, Fixed term and fixed amount 
savings (by Japan Post bank), Debit Cards) 

 HLoan Housing Loan 

 Investment Investment (Stock trading, Japanese government bond for individuals, Mutual funds and ETFs, Foreign Currency MMFs,  
REIT, Wrap accounts and fund wrap accounts, Robo Advisor) 

 Insurance Insurance and Private Pensions related (Medical Care Insurance, Yen and foreign currency savings insurance, iDeCo 

(individual-type Defined Contribution pension plan) Fixed and Variable Individual Annuities) 

 

In the banking industry, it has been observed that banks operating in competitive environments strive to establish 

sustainable competitive advantages through enhanced service quality and customer relationships (Petridou et al., 2007). 

Consequently, a variable indicates the degree of competition in the retail business of each regional bank. The Herfindahl-

Hirschman Index (HHI) is calculated from the deposit share in each prefecture where the head office of each regional bank 

is located. This index is employed as a measure of the degree of competition in that prefecture. Additionally, the in-

prefecture deposit share (SHR) is used as a control variable, which indicates the name recognition and influence of the 

relevant regional bank on its customers. The number of samples was 75,690 in 2019 and 2020, including data other than 

METER. In addition to SERVQUAL, there are different methods of analyzing customer satisfaction, such as the National 

Customer Satisfaction Index (NCSI) or nonlinear regression models that estimate customer satisfaction factors (Arbore & 

Busacca, 2009). In recent years, numerous analyses, including ordinal logit and ordinal probit regression models, have been 

employed (Ngo, 2015; Moraru et al., 2022). In this analysis, we used ordered probit regression models, utilized in numerous 

previous studies in recent years. 

 

RESULTS AND DISCUSSIONS 

Descriptive Results 

Table 2 depicts that most respondents (59.9%) are between the ages of 40 and 59, with a slight majority of males (55.3%). 

Additionally, most respondents (55.3%) have regular jobs, which may include homemakers/househusbands or older, non-

retired persons. The respondents' mean and median financial assets were 18.71 million and 4.5 million, respectively. Those 

who scored 0 or more correct answers exhibited a financial literacy level exceeding 60%. 48% of respondents indicated that 

they had contacted a financial institution in some form, with 24.3% stating that they had done so through direct contact with 

staff and 13.1% via the institution's website. 

 



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Table 2. Descriptive Statistics (n=215,010) 

 
Variables  Frequency Percentage Variables Frequency Percentage 

Gender   Occupation   

Male 128,725 59.9 Yes 118,899 55.3 

Female 86,285 40.1 No 96,111 44.7 
Age   Literacy   

     ~29 18,644 8.7    Below -1 24,753 11.5 

30~39 33,646 15.6           0 57,704 26.8 
40~49 48,447 22.5       1－10 100,812 46.9 

50 ~59 52,982 24.6 11－20 31,741 14.8 

60 ~69 41,835 19.5    

70 ~79 17,698 8.2    

80 and above 1,758 0.8    
Financial Assets (million yen)  Contacts viewed in the past year 

~  300 56,193 26.1 Staff 56,429 24.3 

300~ 1,000 46,768 21.8 CallCenter 3,566 1.5 
1,000~ 3,000 28,089 13.1 Website 30,474 13.1 

3,000~ 5,000 9,403 4.4 Events 1,602 0.7 

5,000~10,000 6,908 3.2 SNS 2,536 1.1 
10,000~50,000 2,810 1.3 Pop-up 10,936 4.7 

50,000 and above  792 0.4 Trainads 6,142 2.6 

No Answer 64,047 29.8 None 121,004 52.0 

 
The Results for the entire sample 

Table 3 presents the probability distribution of customer satisfaction with regional banks in 2019 and 2020. Consequently, 

the highest probability of customer satisfaction in 2019 (2020) was 0.504 (0.496) for the category "neutral," followed by 

0.352 (0.362) for the category "satisfied." The ranking was identical in both years. The proportion of respondents who rated 

their satisfaction as "very satisfied," "dissatisfied," and "very dissatisfied" was 0.078 (0.079), 0.048 (0.045), and 0.018 

(0.017), respectively, in 2019 (2020). These values were all shallow and exhibited minimal variation between the two years. 

The total probability of customer satisfaction (highly satisfied and satisfied) was 0.430 (0.441) in 2019 (2020), while the 

total likelihood of dissatisfaction (highly unsatisfied and unsatisfied) was 0.066 (0.062) in both years. Satisfaction was 

significantly higher than dissatisfaction. Nevertheless, given that the total satisfaction probability is below neutral, regional 

banks should analyze the reasons behind the high number of customers who responded neutrally. This analysis should 

inform the development of marketing and management strategies designed to increase the satisfaction of these customers. 

 

Table 3. Probability Distribution of the Level of Satisfaction 

 
  2019 2020 2019 & 2020 

Category / Particulars   Observations Probability Observations Probability Observations Probability 

P(Y=1) Highly Dissatisfied 1,983 0.018 1,807 0.017 3,790 0.018 

P(Y=2) Dissatisfied 5,268 0.048 4,805 0.045 10,073 0.047 

P(Y=3) Neutral 54,849 0.504 52,655 0.496 107,504 0.500 
P(Y=4) Satisfied 38,313 0.352 38,436 0.362 76,749 0.357 

P(Y=5) Highly Satisfied 8,496 0.078 8,398 0.079 16,894 0.079 

Total 108,909        1 106,101       1 215,010   1 

 

Logistic Regression Results: Analysis for all services 

Table 4 presents the estimated FY 2019 and FY 2020 results, respectively. The results of these estimates confirm that the 

statistically significant values in both the 2019 and 2020 estimates were the specific variables required to increase customer 

satisfaction. Total financial assets (Assets) are negatively correlated with customer financial literacy score (Literacy) and 

positively correlated with customer satisfaction with regional banks. These findings support Hypothesis 1. 

Next, the explanatory variables indicating competition between banks demonstrate a positive and significant impact 

(P < 0.05) on customer satisfaction. This impact is evidenced by the degree of oligopoly (HHI). In other words, as 

competition among regional banks intensifies, they can conduct more sophisticated financial marketing analysis and offer 

more complex services to attract and retain existing customers. These results are interpreted as improved product suitability 

for customers and higher levels of customer satisfaction. Conversely, the deposit share (SHR) was not significant.  

In terms of demographic variables, gender (Gender), age (Age), and occupational status (Occupation) were found 

to have a significant (p < 0.05) impact on customer satisfaction in both the 2019 and 2020 estimates. This impact indicates 

that customer satisfaction is typically higher among females than males, younger individuals than older ones, and those with 

employment than those without.  

 

Table 4. Ordered Logistic Regression Results of Customer Satisfaction 

 
 2019 2020 

 Coef. Z stats.  Coef. Z stats.  

Gender -0.085 -8.680 *** -0.075 -7.170 *** 

Age -0.008 -22.260 *** -0.009 -23.880 *** 
Occupation -0.064 -7.060 *** -0.089 -9.370  

Assets -0.018 -6.610 *** -0.019 -6.510 *** 



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Literacy -0.007 -9.310 *** -0.006 -7.560 *** 

HHI 0.000 -2.210 ** 0.000 -3.600 *** 

SHR 0.000 -0.110  -0.001 -2.230 ** 

Staff 0.290 18.750 *** 0.303 17.250 *** 

CallCenter 0.235 7.950 *** 0.205 5.800 *** 

Website 0.169 11.090 *** 0.158 9.150 *** 

Events 0.102 2.460 ** 0.079 1.480  

SNS 0.020 0.570  0.051 1.140  

Pop-up 0.043 2.280 ** 0.015 0.690  

Trainads 0.056 2.410 ** 0.056 2.100 ** 

None -0.128 -7.780 *** -0.114 -6.170 *** 

Deposits 0.494 24.190 *** 0.493 21.240 *** 

HLoan 0.207 11.580 *** 0.243 12.930 *** 

Investment 0.168 9.520 *** 0.198 10.150 *** 

Insurance 0.111 5.370 *** 0.110 4.770 *** 

A number of obs. 75,690   75,690   

Log-likelihood／
Pseudo R2 

-85327.3 0.0273  -79954.08 0.0274  

Note. ***, ** and * represent the statistically significant coefficients at significance levels of 1, 5, and 10 percent, respectively.  

 

Additionally, the impact of any benefits received by customers from regional banks on their satisfaction is 

considered through the channels through which they contacted the financial institution within a year. The impact of staff 

and call centers on customer satisfaction is significant, with a p-value of less than 0.01 in both the 2019 and 2020 estimates. 

It has been demonstrated that direct human contact with customers is an effective means of improving satisfaction. Contact 

via the website (Website) and train ads and direct mail (Trainads) also demonstrated a significant impact on customer 

satisfaction (P < 0.01). Conversely, events/seminars (Events) and pop-up and TV online ads (Pop-ups) significantly 

impacted customer satisfaction in 2019. However, this impact was insignificant in 2020. The effect of the global pandemic 

has resulted in a substantial decline in the ability of regional banks to organize events and seminars for their customers. This 

decline has been attributed to the loss of customer benefits associated with such events.  

Conversely, the 2019 and 2020 estimates revealed that social networking services (SNS) had no significant impact 

on satisfaction. Given that Japanese regional banks operate in rural areas, have a large number of older customers, and still 

need to have a high level of trust in social media information, it is likely that contact through this channel did not affect 

satisfaction levels. About the financial products they do business with, those who do business with a regional bank exhibited 

a positive and significant (P < 0.01) correlation with satisfaction for all products. We found that the services of deposits and 

settlements (Deposits), housing loans (HLoan), investment management (Investment), and insurance and private pensions 

(Insurance) have a more significant influence on customer satisfaction than in FY 2019. The level of significance was found 

to be higher in FY2020.  

Table 5 presents the marginal effects, or the probability changes in the dependent variable for a one-unit change in 

the independent variable, for the estimated results in 2019 and 2020. The direction of the effect is contingent upon the sign 

of the coefficient. Values greater than zero indicate an effect of increasing satisfaction, while values less than zero imply an 

impact of decreasing satisfaction. The direction of the effect is contingent upon the sign of the coefficient. Values greater 

than zero indicate an effect that increases satisfaction, while values less than zero imply an effect that decreases satisfaction.  

Regarding the customer benefits, the results indicate that the marginal effects for the categories "satisfied" and 

"very satisfied" categories are positive and significant. Furthermore, the impact of “satisfied " was higher than that of "very 

satisfied." The marginal effects for events and seminars (Events) and pop-up and TV online advertising (Pop-up) were 

positive and significant for "satisfied" and "very satisfied" in 2019 but not substantial in 2020. The significance of this factor 

has now been eliminated. The above marginal effects indicate that if regional banks intensify or continue their efforts to 

utilize these channels and benefits to their customers, the probability of customer satisfaction and high satisfaction will 

increase. 

Consequently, it can be posited that the strengthening and enhancement of contact from these channels can reduce 

the probability of customers being "unsatisfied" or "very dissatisfied." Recognizing the significance of contacts from the 

distribution channel and the benefits provided to customers' needs is essential. This is because highly satisfied customers 

are more likely to form long-term relationships with the regional bank, which can deliver several performance outcomes to 

the customer or the bank while also providing significant benefits to the regional bank. 

Among the socio-demographic variables, Gender, Age, and Occupation negatively affected satisfaction in the 2019 

and 2020 estimates. Gender was positively correlated with satisfaction and high satisfaction, while Occupation was 

negatively correlated with satisfaction and high satisfaction. It can be concluded that satisfaction is higher among females 

than males, among those who are unemployed than those who have a job, and among those who are younger than those who 

are older. This result may be attributed to the fact that longer relationships with regional banks and experience in asset 

management may lead to more rigorous evaluations of their services. The amount of financial assets (Assets) and customers’ 

financial literacy scores (Literacy) exhibited a negative effect (negative marginal effect for satisfaction and high satisfaction) 

in both 2019 and 2020. This result suggests that customers with more outstanding asset holdings and higher levels of 

financial Literacy are less satisfied with the services provided by regional banks. Therefore, these affluent and financially 

literate customers may seek more sophisticated services and professional advice. 

 

 

 



Mori et al., Asian Finance & Banking Review 8(1) (2024), 1-12

  

7 
 

Table 5. Marginal Effects of Benefits Received on Customer Satisfaction 

 
 2019 2020 

 Highly 
Dissatisfied 

1 

Dissatisfied 

 

2 

Neutral 

 

3 

Satisfied 

 

4 

Highly 
Satisfied 

5 

Highly 
Dissatisfied 

1 

Dissatisfied 

 

2 

Neutral 

 

3 

Satisfied 

 

4 

Highly 
Satisfied 

5 

Gender 0.004 

(0.000) 

0.007 

(0.000) 

0.021 

(0.000) 

-0.021 

(0.000) 

-0.013 

(0.000) 

0.003 

(0.000) 

0.006 

(0.000) 

0.019 

(0.000) 

-0.017 

(0.000) 

-0.011 

(0.000) 

Age 0.000 
(0.000) 

0.001 
(0.000) 

0.002 
(0.000) 

-0.002 
(0.000) 

-0.001 
(0.000) 

0.000 
(0.000) 

0.001 
(0.000) 

0.002 
(0.000) 

-0.002 
(0.000) 

-0.001 
(0.000) 

Occupation 0.003 

(0.000) 

0.005 

(0.000) 

0.016 

(0.000) 

-0.015 

(0.000) 

-0.010 

(0.000) 

0.004 

(0.000) 

0.007 

(0.000) 

0.023 

(0.000) 

-0.021 

(0.000) 

-0.013 

(0.000) 

Assets 0.001 

(0.000) 

0.002 

(0.000) 

0.004 

(0.000) 

-0.004 

(0.000) 

-0.003 

(0.000) 

0.001 

(0.000) 

0.002 

(0.000) 

0.005 

(0.000) 

-0.004 

(0.000) 

-0.003 

(0.000) 

Literacy 0.000 
(0.000) 

0.001 
(0.000) 

0.002 
(0.000) 

-0.002 
(0.000) 

-0.001 
(0.000) 

0.000 
(0.000) 

0.000 
(0.000) 

0.002 
(0.000) 

-0.001 
(0.000) 

-0.001 
(0.000) 

HHI 0.000 

(0.028) 

0.000 

(0.027) 

0.000 

(0.027) 

0.000 

(0.027) 

0.000 

(0.027) 

0.000 

(0.000) 

0.000 

(0.000) 

0.000 

(0.000) 

0.000 

(0.000) 

0.000 

(0.000) 

SHR 0.000 

(0.914) 

0.000 

(0.914) 

0.000 

(0.914) 

0.000 

(0.914) 

0.000 

(0.914) 

0.000 

(0.026) 

0.000 

(0.026) 

0.000 

(0.026) 

0.000 

(0.026) 

0.000 

(0.026) 

Staff -0.014 
(0.000) 

-0.025 
(0.000) 

-0.072 
(0.000) 

0.067 
(0.000) 

0.043 
(0.000) 

-0.014 
(0.000) 

-0.025 
(0.000) 

-0.077 
(0.000) 

0.071 
(0.000) 

0.045 
(0.000) 

CallCenter -0.011 

(0.000) 

-0.020 

(0.000) 

-0.059 

(0.000) 

0.055 

(0.000) 

0.035 

(0.000) 

-0.009 

(0.000) 

-0.017 

(0.000) 

-0.052 

(0.000) 

0.048 

(0.000) 

0.030 

(0.000) 

Website -0.008 

(0.000) 

-0.014 

(0.000) 

-0.042 

(0.000) 

0.039 

(0.000) 

0.025 

(0.000) 

-0.007 

(0.000) 

-0.013 

(0.000) 

-0.040 

(0.000) 

0.037 

(0.000) 

0.023 

(0.000) 

Events -0.005 
(0.014) 

-0.009 
(0.014) 

-0.025 
(0.014) 

0.024 
(0.014) 

0.015 
(0.014) 

-0.004 
(0.140) 

-0.006 
(0.140) 

-0.020 
(0.140) 

0.019 
(0.140) 

0.012 
(0.140) 

SNS -0.001 

(0.567) 

-0.002 

(0.567) 

-0.005 

(0.567) 

0.005 

(0.567) 

0.003 

(0.567) 

-0.002 

(0.255) 

-0.004 

(0.255) 

-0.013 

(0.255) 

0.012 

(0.255) 

0.008 

(0.255) 

Pop-up -0.002 

(0.023) 

-0.004 

(0.023) 

-0.011 

(0.022) 

0.010 

(0.022) 

0.006 

(0.022) 

-0.001 

(0.490) 

-0.001 

(0.490) 

-0.004 

(0.490) 

0.003 

(0.490) 

0.002 

(0.490) 

Trainads -0.003 

(0.016) 

-0.005 

(0.016) 

-0.014 

(0.016) 

0.013 

(0.016) 

0.008 

(0.016) 

-0.003 

(0.036) 

-0.005 

(0.036) 

-0.014 

(0.036) 

0.013 

(0.036) 

0.008 

(0.036) 

None 0.006 

(0.000) 

0.011 

(0.000) 

0.032 

(0.000) 

-0.030 

(0.000) 

-0.019 

(0.000) 

0.005 

(0.000) 

0.009 

(0.000) 

0.029 

(0.000) 

-0.027 

(0.000) 

-0.017 

(0.000) 

Deposits -0.023 

(0.000) 

-0.042 

(0.000) 

-0.123 

(0.000) 

0.115 

(0.000) 

0.074 

(0.000) 

-0.022 

(0.000) 

-0.040 

(0.000) 

-0.126 

(0.000) 

0.115 

(0.000) 

0.073 

(0.000) 

HLoan -0.010 

(0.000) 

-0.018 

(0.000) 

-0.051 

(0.000) 

0.048 

(0.000) 

0.031 

(0.000) 

-0.011 

(0.000) 

-0.020 

(0.000) 

-0.062 

(0.000) 

0.057 

(0.000) 

0.036 

(0.000) 

Investment -0.008 
(0.000) 

-0.014 
(0.000) 

-0.042 
(0.000) 

0.039 
(0.000) 

0.025 
(0.000) 

-0.009 
(0.000) 

-0.016 
(0.000) 

-0.051 
(0.000) 

0.046 
(0.000) 

0.029 
(0.000) 

Insurance 
-0.005 

(0.000) 

-0.009 

(0.000) 

-0.028 

(0.000) 

0.026 

(0.000) 

0.017 

(0.000) 

-0.005 

(0.000) 

-0.009 

(0.000) 

-0.028 

(0.000) 

0.026 

(0.000) 

0.016 

(0.000) 

Note. Values in parentheses are p-values. 
 

The Results for Satisfaction of Customers Holding Investment-related Products.  

For Japanese regional banks, the provision of retail financial services, particularly in deposit-taking and settlement, 

represents a long-standing and historically significant aspect of their business. However, these services have traditionally 

been characterized by low profitability and a high degree of competitive intensity. 

The preceding analysis indicates that the satisfaction levels of customers of the same regional bank who utilize 

only traditional deposit and payment services will differ from those of customers who purchase investment-related products 

through the regional bank's channels. Since customer satisfaction and loyalty have become increasingly important for these 

products, this section will focus on investment-related products.  

The estimation results, as presented in Table 6, indicate that in both the 2019 and 2020 estimates, statistically 

significant values were also observed for customers holding investment-related products. This result is a specific variable 

that is required when increasing customer satisfaction. The significance of financial assets (Assets) in the overall estimation 

has been eliminated in these estimation results. Conversely, the financial literacy scores of customers are positive and both 

significant (P < 0.05), exerting an impact on customer satisfaction with their regional bank. 

Next, an examination of the competitive landscape among banks reveals that the oligopoly Herfindahl-Hirschman 

Index (HHI) exerts a positive and significant (P < 0.05) influence on customer satisfaction in 2019. However, this impact 

has yet to be evident in the 2020 estimates. In contrast to deposit settlement services, the services offered by regional banks 

for investment-related products are of critical importance. However, in 2020, due to the impact of the spread of the novel 

coronavirus, banks were likely to have encountered difficulties in their sales activities, and human contact with customers 

could have been more extensive. This result indicates that the effect on customer satisfaction is no longer significant. 

About the remaining socio-demographic variables, only age (Age) exhibited a statistically significant (P < 0.05) 

impact on customer satisfaction in both the 2019 and 2020 estimates, while the other variables were not found to be 

significant. In other words, the results indicated that younger customers tend to be more satisfied with investment-related 

products than older customers in terms of age. 

 

 

 



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8 
 

Table 6. Ordered Logistic Regression Results of Customer Satisfaction with Investment Products 

 
 2019 2020 

 Coef. Z stats.  Coef. Z stats.  

Gender -0.046 -1.380  -0.020 -0.560  

Age -0.006 -4.460 *** -0.004 -3.130 *** 
Occupation -0.010 -0.300  -0.010 -0.270  

Assets -0.011 -0.990  0.009 0.710  

Literacy 0.009 3.400 *** 0.011 4.140 *** 

HHI 0.000 2.500 ** 0.000 1.030  

SHR 0.000 0.090  -0.001 -0.480  

Staff 0.357 8.450 *** 0.378 8.530 *** 

CallCenter 0.220 3.760 *** 0.267 4.100 *** 

Website 0.169 4.820 *** 0.185 4.970 *** 

Events 0.093 1.620  0.015 0.240  

SNS -0.017 -0.340  0.091 1.570  

Pop-up -0.045 -0.810  -0.009 -0.150  

Trainads 0.019 0.300  0.119 1.680 * 

None -0.151 -2.630 *** -0.106 -1.820 * 

Deposits 0.290 6.660 *** 0.277 5.940 *** 

HLoan 0.245 3.990 *** 0.151 2.350 *** 

Insurance 0.150 3.120 *** 0.144 2.840 *** 

A number of obs. 5,219   4,935   

Log-likelihood／
Pseudo R2 

-6675.15 0.0343  -6100.70 0.0367  

Note. ***, ** and * represent the statistically significant coefficients at significance levels of 1, 5, and 10 percent, respectively.  

 

Table 7. Marginal Effect of Customer Satisfaction with Investment Products 
 

 2019 2020 

 Highly 
Dissatisfied 

1 

Dissatisfied 

 

2 

Neutral 

 

3 

Satisfied 

 

4 

Highly 
Satisfied 

5 

Highly 
Dissatisfied 

1 

Dissatisfied 

 

2 

Neutral 

 

3 

Satisfied 

 

4 

Highly 
Satisfied 

5 

Gender 0.003 

(0.170) 

0.006 

(0.169) 

0.009 

(0.168) 

-0.008 

(0.168) 

-0.010 

(0.168) 

0.001 

(0.574) 

0.002 

(0.573) 

0.004 

(0.574) 

-0.003 

(0.574) 

-0.004 

(0.573) 

Age 0.000 
(0.000) 

0.001 
(0.000) 

0.001 
(0.000) 

-0.001 
(0.000) 

-0.001 
(0.000) 

0.000 
(0.002) 

0.000 
(0.002) 

0.001 
(0.002) 

-0.001 
(0.002) 

-0.001 
(0.002) 

Occupation 0.001 

(0.767) 

0.001 

(0.767) 

0.002 

(0.767) 

-0.002 

(0.767) 

-0.002 

(0.767) 

0.001 

(0.788) 

0.001 

(0.788) 

0.002 

(0.788) 

-0.002 

(0.788) 

-0.002 

(0.788) 

Assets 0.001 

(0.324) 

0.001 

(0.324) 

0.002 

(0.323) 

-0.002 

(0.323) 

-0.002 

(0.324) 

0.000 

(0.477) 

-0.001 

(0.477) 

-0.002 

(0.477) 

0.001 

(0.477) 

0.002 

(0.478) 

Literacy -0.001 
(0.001) 

-0.001 
(0.001) 

-0.002 
(0.001) 

0.001 
(0.001) 

0.002 
(0.001) 

-0.001 
(0.000) 

-0.001 
(0.000) 

-0.002 
(0.000) 

0.002 
(0.000) 

0.002 
(0.000) 

HHI 0.000 

(0.014) 

0.000 

(0.013) 

0.000 

(0.012) 

0.000 

(0.012) 

0.000 

(0.012) 

0.000 

(0.306) 

0.000 

(0.305) 

0.000 

(0.305) 

0.000 

(0.305) 

0.000 

(0.305) 

SHR 0.000 

(0.927) 

0.000 

(0.927) 

0.000 

(0.927) 

0.000 

(0.927) 

0.000 

(0.927) 

0.000 

(0.632) 

0.000 

(0.632) 

0.000 

(0.632) 

0.000 

(0.632) 

0.000 

(0.632) 

Staff -0.023 

(0.000) 

-0.043 

(0.000) 

-0.068 

(0.000) 

0.058 

(0.000) 

0.076 

(0.000) 

-0.021 

(0.000) 

-0.042 

(0.000) 

-0.078 

(0.000) 

0.064 

(0.000) 

0.077 

(0.000) 

CallCenter -0.014 

(0.000) 

-0.026 

(0.000) 

-0.042 

(0.000) 

0.036 

(0.000) 

0.047 

(0.000) 

-0.015 

(0.000) 

-0.030 

(0.000) 

-0.055 

(0.000) 

0.045 

(0.000) 

0.054 

(0.000) 

Website -0.011 

(0.000) 

-0.020 

(0.000) 

-0.032 

(0.000) 

0.027 

(0.000) 

0.036 

(0.000) 

-0.010 

(0.000) 

-0.020 

(0.000) 

-0.038 

(0.000) 

0.031 

(0.000) 

0.037 

(0.000) 

Events -0.006 
(0.106) 

-0.011 
(0.105) 

-0.018 
(0.104) 

0.015 
(0.105) 

0.020 
(0.104) 

-0.001 
(0.809) 

-0.002 
(0.809) 

-0.003 
(0.809) 

0.003 
(0.809) 

0.003 
(0.809) 

SNS 0.001 

(0.733) 

0.002 

(0.733) 

0.003 

(0.733) 

-0.003 

(0.733) 

-0.004 

(0.733) 

-0.005 

(0.117) 

-0.010 

(0.117) 

-0.019 

(0.116) 

0.015 

(0.116) 

0.019 

(0.116) 

Pop-up 0.003 

(0.420) 

0.005 

(0.419) 

0.009 

(0.419) 

-0.007 

(0.419) 

-0.010 

(0.419) 

0.001 

(0.884) 

0.001 

(0.884) 

0.002 

(0.884) 

-0.002 

(0.884) 

-0.002 

(0.884) 

Trainads -0.001 
(0.765) 

-0.002 
(0.765) 

-0.004 
(0.765) 

0.003 
(0.765) 

0.004 
(0.765) 

-0.007 
(0.097) 

-0.013 
(0.094) 

-0.024 
(0.094) 

0.020 
(0.095) 

0.024 
(0.094) 

None 0.010 

(0.010) 

0.018 

(0.009) 

0.029 

(0.009) 

-0.025 

(0.008) 

-0.032 

(0.009) 

0.006 

(0.073) 

0.012 

(0.067) 

0.022 

(0.069) 

-0.018 

(0.067) 

-0.022 

(0.069) 

Deposits -0.019 

(0.000) 

-0.035 

(0.000) 

-0.056 

(0.000) 

0.047 

(0.000) 

0.062 

(0.000) 

-0.015 

(0.000) 

-0.031 

(0.000) 

-0.057 

(0.000) 

0.047 

(0.000) 

0.056 

(0.000) 

HLoan -0.016 

(0.000) 

-0.029 

(0.000) 

-0.047 

(0.000) 

0.040 

(0.000) 

0.052 

(0.000) 

-0.008 

(0.021) 

-0.017 

(0.019) 

-0.031 

(0.018) 

0.026 

(0.019) 

0.031 

(0.019) 

Insurance 
-0.010 
(0.002) 

-0.018 
(0.002) 

-0.029 
(0.002) 

0.024 
(0.002) 

0.032 
(0.002) 

-0.008 
(0.005) 

-0.016 
(0.005) 

-0.030 
(0.005) 

0.024 
(0.005) 

0.029 
(0.005) 

Note. Values in parentheses are p-values. 

 

The influence of the benefits received by customers on their satisfaction with the financial institution is gauged by 

examining the channels through which they contacted the institution within one year. The results of the overall estimation 

are consistent with those of the two-year estimates, with staff (Staff) and call centers (CallCenter) having a significant 

impact (P < 0.01) in both 2019 and 2020. As anticipated, investment-related products possess intricate content, rendering 

direct human contact with customers a productive strategy for enhancing customer satisfaction. Furthermore, contact via 



Mori et al., Asian Finance & Banking Review 8(1) (2024), 1-12

  

9 
 

the website (Website) also had a significant impact on customer satisfaction (P < 0.01), as it allows for the communication 

of complex and large amounts of information to customers via the website, which is also effective in improving satisfaction. 

Conversely, train ads and direct mail (Trainads) are significant in the overall estimate but not for investment-related products. 

Events and seminars (Events) and pop-up ads and TV online ads (Pop-up) are significant in the overall estimate, but not for 

investment-related products. Given the nature of the products, namely investment-related products, social networking and 

train advertising did not significantly impact customer satisfaction. Another factor that may have influenced the results in 

2020 was the difficulty in reaching customers due to the global pandemic caused by the novel coronavirus, COVID-19. 

The marginal effect estimates in Table 7 demonstrate that for benefits received by customers, staff (Staff), call 

center (CallCenter), and contact via the website (Website) in 2019 and 2020, the marginal effects for "satisfied" and "very 

satisfied" were positive and significant in both years. Furthermore, the marginal effect for "very satisfied" was higher than 

for "satisfied." The results indicated a positive and significant marginal effect for Train Ads and Direct Mail (Trainads) in 

2020 about the categories of "satisfied" and "very satisfied." 

The marginal effects for the categories "satisfied" and "very satisfied" for events and seminars (Events) and pop-

up and TV online advertising (Pop-up) were not significant in the model estimates for both 2019 and 2020. The marginal 

effects were insignificant for the model estimates of "satisfied" and "very satisfied." The results of the marginal above 

impact indicate that customer satisfaction with investment-related products is positively correlated with higher levels of 

satisfaction when approached directly by regional banks. Regional banks are also more proactive in approaching customers 

with investment-related products, i.e., those with higher marginal returns per customer, to increase customer satisfaction 

and loyalty. 

Among the socio-demographic variables, only age (Age) demonstrated a negative effect, as evidenced by a negative 

marginal effect on satisfaction and a high level of satisfaction. This effect was statistically significant in the 2019 and 2020 

marginal effect estimates. Nevertheless, the effect was relatively modest in magnitude. The variables gender (Gender), 

Occupation (Occupation), and assets held (Assets) were all found to be insignificant. Financial Literacy exhibited a positive 

marginal effect for 2019 and 2020 regarding satisfactory and highly satisfactory outcomes. This result suggests that 

customers with higher levels of financial Literacy are more satisfied with the services provided by regional banks. 

Nevertheless, the effect is relatively modest in size. This result contradicts the overall estimate, indicating that for 

customers with high financial Literacy, the direct approach from the regional bank positively affects satisfaction, albeit 

modestly. This result implies that although customers are satisfied with the approach from the regional bank, it cannot be 

ruled out that they may be seeking further quality improvement, namely a higher level of service and more specialized 

advice.  

DISCUSSIONS 

The model estimation in this study demonstrated that, in addition to direct salesperson contact, customer satisfaction was 

influenced by various demographic variables, including age, occupational status, total financial assets, and Financial 

Literacy. Furthermore, the study revealed that the convenience of web-based contact also influenced customer satisfaction. 

Conversely, an analysis of total financial assets and the ownership of investment-related products revealed that customers 

with higher financial assets and those with investment-related products exhibited a more pronounced impact on satisfaction. 

In particular, contacts from staff and call centers were a positive indicator, indicating that direct human contact was 

more practical for increasing customer satisfaction than e-banking, such as social networking. This result is related to the 

specific context of banking service provision in Japan, where the continued effectiveness of in-person financial advice from 

physical branches, particularly for customers with limited financial Literacy, is particularly evident in rural areas. 
 

CONCLUSIONS 

While we know the importance of e-banking services, this study analyzed customer satisfaction with face-to-face financial 

services, which are the predominant type of service banks offer to retail customers in Japan. In particular, we examined the 

quality of banking services, focusing on the importance of human contact, including information provision and personnel 

involvement. As anticipated, the results demonstrated that e-banking services, human contact, and investment advice 

significantly impact customer satisfaction. 

The Japanese banking system plays a more significant role than direct finance, particularly in the local economy. 

Nevertheless, the level of customer satisfaction with regional banks' retail services needs to be sufficiently examined. Most 

previous studies focus on a single bank or employ few respondents. This study contributes to the existing literature by 

focusing on unique data from a large sample of customers drawn from Japanese regional banks with an extensive branch 

network in rural and urban areas.  

The novel aspect of our research approach is that we consider customer contact as a determinant of customer 

satisfaction, in contrast to numerous studies that have investigated customer satisfaction through different service quality 

dimensions. Moreover, our study incorporates several socio-demographic factors into the econometric modeling as 

determinants of customer satisfaction. 

The findings of this study demonstrate the significance of customer satisfaction in the retail financial sector of 

regional banks. In-person financial advice and services remain a highly valued aspect of the industry despite the growing 

prominence of e-banking services. Individual customer behavior is in a state of constant flux. As consumers become more 

informed, financially literate, and more experienced in investing, they will change their investment decisions and risk-taking 

levels. It will be crucial for banks to enhance their financial marketing techniques, including identifying consumer profiles, 

providing tailored services, monitoring the factors influencing customer satisfaction with customer service, and 

implementing AI in addressing customers' financial issues. Improving customer service is an increasingly important aspect 

of bank management strategy, as it enhances customer satisfaction and profitability. 



Mori et al., Asian Finance & Banking Review 8(1) (2024), 1-12

  

10 
 

Although this study contributes to the existing literature, it needs to be more comprehensive in understanding more 

detailed factors such as convenience, environment, quality, prices, and e-banking. Additionally, there are limitations in 

understanding information such as customers' income and education. Consequently, a future research direction would be to 

consider supplementing the data set with a data set of variables that can proxy for these factors. A further direction of this 

study will be to provide more evidence for these results by using e-banking-specific validation. 

 

 
Author Contributions: Conceptualization, Y.M., Y.O. and K.H.; Methodology, Y.M. and Y.O.; Software, Y.M. and Y.O.; Validation, Y.M. and Y.O.; 
Formal Analysis, Y.M.; Investigation, Y.M.; Resources, Y.M. and Y.O.; Data Curation, Y.M. and Y.O.; Writing – Original Draft Preparation, Y.M.; 

Writing – Review & Editing, Y.M.; Visualization, Y.M.; Supervision, Y.O. and K.H.; Project Administration, Y.O. and K.H.; Funding Acquisition, K.H. 

Authors have read and agreed to the published version of the manuscript. 
Institutional Review Board Statement: Ethical review and approval were waived for this study due to that the research does not deal with vulnerable 

groups or sensitive issues. 

Funding: This research was supported by JSPS KAKENHI Grant Number JP 23K01478. 
Acknowledgements: We would like to acknowledge all faculty members, staffs, and fellows of Takasaki City University of Economics, Kushiro Public 

University of Economics and Ritsumeikan University, each of whom has provided advice and guidance throughout the research process. Thanks all for 

your unwavering support. 
Informed Consent Statement: Informed consent was obtained from all subjects involved in the study. 

Data Availability Statement: The data presented in this study are available on request from the corresponding author. The data are not publicly available 

due to restrictions. 
Conflicts of Interest: The authors declare no conflict of interest.                                                                                                                                                                                                                                   

 

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