A Bank’s Customer Citizenship Behaviour in the Multinomial Logistic

Regression Model

ADIREK VAJRAPATKUL, NUTTAWUT ROJNIRUTTIKUL*

The KMITL Business School,

King Mongkut’s Institute of Technology Ladkrabang,

P.O. BOX 1 Chalong Krung, 1 Alley, Lat Krabang, Bangkok 10520, Bangkok,

THAILAND

*Corresponding Author

Abstract: - This research aimed to study the factors affecting customer citizenship behavior (CCB) in the banking

industry. The data were collected from questionnaires from bank customers in six districts of Bangkok, Thailand.

The data were analyzed using EFA and MLR techniques. The study identified three latent variables that could

affect the level of CCB, namely good corporate governance, quality of self-service technology, and quality of on-

site service. The results showed that good corporate governance in transparency, accountability, and fairness

significantly improves the level of CCB. In addition, the quality of self-service technology, which provided

convenience to bank customers, could lead to increased CCB. Regarding on-site service quality, the results also

showed that it was an important factor in increasing CCB. In terms of the impact of demographic variables, people

aged 41 to 45, women, and low-income earners were more likely to have high levels of CCB compared to the

reference group. This research emphasizes the need to adhere to corporate governance, quality of self-service

technology, quality of on-site service, and customer characteristics to enhance CCB and bank success.

Key-Words: - Corporate governance, Self-service technology quality, On-site service quality, Customer citizenship

behavior, Bank, Logistic Regression, Thailand.

Received: March 8, 2024. Revised: August 4, 2024. Accepted: September 7, 2024. Published: October 4, 2024.

1 Introduction

Banks are financial institutions that play an important

role in the economic system. They provide essential

financial services to individuals and organizations to

help economic activities continue, which allows the

economy to grow continuously, [1].

By providing credit services, banks enable

business units to increase their investment in existing

businesses or even invest in new businesses, which

helps them expand their businesses. Moreover, banks

play an important role in creating financial

innovations, allowing individuals and business units

to access easier credit. As a result, banks play an

important role in stimulating business growth

through various functions, such as promoting

entrepreneurship and creating employment

opportunities, [2 ] . The development of banking

services is continuous and covers a variety of

important transactions, such as receiving and

transferring money, cash management, foreign

exchange, providing services to import and export

businesses, and risk hedging. These services help

businesses that trade and invest domestically and

internationally operate more efficiently, [3 ] .

Moreover, banks also help improve the financial

status of households through various products and

services, such as deposits, providing financial credit,

insurance, and retirement planning. These financial

services help increase income, returns, and financial

security for households and business units, [3 ]. The

development of financial systems and markets, as

well as financial technology, has increased the

number of financial institutions that provide financial

services. The increase in these financial institutions

has been accompanied by the introduction of new

technologies and regulations that have led to

increased competition in the financial industry. Due

to this increase in competition, financial institutions

have had to develop and expand their services,

especially banks, which have had to expand their

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DOI: 10.37394/23207.2024.21.159

Adirek Vajrapatkul, Nuttawut Rojniruttikul

E-ISSN: 2224-2899

1962

Volume 21, 2024

services beyond deposits and lending to provide

financial services that cover the needs of their

customers and to adopt new technologies such as

FINTECH, [4 ] to increase their market power and

profits, [5 ] . In addition to developing technologies,

many banks have focused on developing good

relationships with customers and creating positive

customer behaviors towards the bank, known as

customer citizenship behavior (CCB). This behavior

refers to voluntary efforts by customers to promote

the bank's operations and services and help other

customers, such as providing suggestions,

recommending services, and participating in various

bank activities, [6].

From the previous studies, it has been shown that

CCB has a direct impact on efficiency, operations,

business growth, customer satisfaction levels,

customer loyalty, and customer retention, which in

turn has a positive effect on the ability of the bank to

generate income and profit, [7 ] . In addition, CCB

helps to promote a sense of community and

collaboration among customers. It helps to create a

better brand image and enhance the reputation of the

bank, [6].

This study recognizes the importance of CCB to

banks and tries to explore the factors affecting CCB

in banks by using Exploratory Factor Analysis (EFA)

and Logistic Multinomial Analysis techniques. To

meet this objective, this study organizes the rest of

the works as follows. Section 2 presents the academic

work that supports the research framework. Later,

Section 3 describes the research methodology.

Section 4 presents the results. Then, Section 5

provides discusses.

2 Literature Review

The following are concepts utilized in this work.

2.1 Customer Citizenship Behavior

Customer citizenship behavior ( CCB) refers to

voluntary, helpful behaviors performed by customers

beyond their pre-defined roles' expectations towards

fellow customers or the retailer, [ 8 ] . CCB is the

useful, constructive actions exhibited by customers

that an organization values or appreciates. In this

manner, customers are recognized as a firm's human

resource, and they may even replace employees or be

viewed as organizational members who co-create

value for firms, [9]. CCBs are behaviors that are not

required for the production and/ or delivery of a

successful product or service but can help improve

organizational performance. It comprises customers'

voluntary extra-role behaviors during or after service

delivery, [1 0]. CCB can be measured by combining

several dimensions, such as recommendations,

providing feedback to the organization, helping other

customers, and advocacy, [11]. CCB can be

measured by the combination of several dimensions,

such as positive word of mouth ( WOM), display of

affiliation, partnership, cooperation, presenting

feedback to the company, dissatisfied customer

voice, policing of others, flexibility [12], compliance,

altruism, personal initiative [13], customer

participation, customer cooperation, positive word-

of-mouth [14] and customer advocacy, [15].

2.2 Corporate Governance

The term "governance" is derived from the Latin verb

“gubernare,” which means "to steer" and typically

refers to the steering of a ship, [16]. Corporate

governance fosters investor confidence and trust,

ensures business integrity, and creates long-term

value, [17]. Corporate governance involves all

stakeholders, encompassing various parties,

including shareholders, employees, suppliers,

customers, creditors, neighboring communities, and

the public. Extreme proponents of stakeholder theory

advocate including the environment, animal species,

and future generations as stakeholders, [18]. Thus,

reflecting on the governance can be done through

their perception. Corporate governance can be

measured by several principles, e.g., transparency,

interdependence, accountability, fairness, social

awareness, discipline, and responsibility [19],

corporate reputation (ability to provide valued

outcomes to stakeholders) [20] and customer

complaint management, [21].

2.3 Self-Service Technology Quality

Technology has become one of the most important

parts of a service firm’s infrastructure and an integral

part of the human elements of service for service

firms’ growth and development strategies, [22].

Particularly, "self-service technologies" (SSTs) have

been recognized by firms as an essential tool for

serving their customers, as this technology allows

consumers to produce their own service experiences

without any direct involvement of service personnel,

[23]. Thus, improving the service quality of this

technology is a key strategy to foster firms’ business

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Adirek Vajrapatkul, Nuttawut Rojniruttikul

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1963

Volume 21, 2024

growth. In the banking business, this self-service

technology includes ATMs, SMS banking, mobile

phone banking, and Internet banking. This

technology quality can be measured based on several

concepts, e.g., ease of use, convenience, cost savings,

safety, and control [24]; convenience, user interface,

time-saving, low risk of error service, customization

[25]; functionality; enjoyment, security/privacy,

assurance, design, convenience, and customization

[26].

2.4 On-site Service Quality

The phrase service quality represents how well the

service level matches customer expectations.

Implicatively, its quality is often harder to measure

than the qualitative issue of a tangible product.

Service quality can be measured based on several

concepts, e.g., the retail service quality scale used in

the retail business measures service quality on 5

dimensions based on the SERVQUAL model [27],

i.e., tangible, reliability, responsiveness, empathy,

and assurance. Although this model is widely used

for measuring on-site service quality, it falls short of

the SERVPERF model [28], which measures only

perceptions.

Due to the limitations of the previous empirical

studies in directly connecting corporate governance,

self-service technology quality, on-site service

quality, and customer citizenship behavior, the

following investigation of the earlier works can only

show the possible linkage between them.

Corporate governance research shows that one

aspect of CCB, customer loyalty, increases if

customers know or are cognizant of the reputations

of bank officials and management. Customers

generally show more loyalty towards financial

institutions whose personnel and officials are always

willing to help them with their needs. The presence

of competent management and integrity, indicative of

good corporate governance, were identified as

potential customer loyalty factors, [20].

Furthermore, it was determined that properly

implemented corporate governance can serve as a

tool to enhance equity, transparency, and

accountability in the banking sector, which is key to

building up customer relationships, trust, satisfaction,

and loyalty, [29]. With regards to self-service

technologies, a preceding study brought to light the

fact that some aspects of the technology, including

perceived control, do not affect customer satisfaction

significantly; on the other hand, an interesting effect

was found on that dimension by the perceived

easiness of the technology, [30]. This means that

customers are most likely contented with services

that have simple usage procedures. In another study,

self-service technology’s effect on CCB was

investigated, and it was found that this technology

could promote trust and increase CCB, [31]. As a

result of being more comfortable with self-service

technologies, customers feel more secure with their

banking services and develop a stronger connection

to service delivery in the bank. A survey researching

the impact of SST on behavioral intentions and users'

loyalty found that SST positively influences users'

perceptions of flexibility, control, and efficiency,

[32]. This makes it clear that when customers can

exploit self-service technology for their satisfaction

and loyalty, CCB may grow.

Prior research has demonstrated that service

quality enhances customer engagement and loyalty.

Good service quality increases the likelihood that

customers will be satisfied with the service they

receive, increasing customer engagement and loyalty.

In addition, customers are more likely to be pleased

when commitments, requests, and expectations are

met and executed accurately, [33]. Also, it was

discovered that key aspects of service quality, such as

dependability, responsiveness, and assurance, were

directly linked to customer retention. The study also

showed that all service quality dimensions had

positive effects statistically significant on repurchase

intention. These researches show that service quality

is a major predictor of customer engagement,

satisfaction, retention, and loyalty. The results in

service quality are a main factor in customer

satisfaction, guaranteeing repeat business even in

after-sales relationships, [34].

3 Methodology

In this work, we employ the Multinomial Logistic

Regression (MLR) technique to test our hypotheses

since we considered the model imposed by a

nonmetric dependent variable predicted by 4 metric

variables. Even though the suggested size of the

sample is at least 400 units with 10 units of the

sample size per group of the dependent variable [35],

we do our best under the limitation problem of the

available data. We construct the model explained in

the following steps to estimate the opportunity for the

countries under study to fall into the target group.

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Adirek Vajrapatkul, Nuttawut Rojniruttikul

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1964

Volume 21, 2024

Let define

j

y

by:

0

1

j

y





,

0,1j

From sigmoid function [36], we have:

 

1

11

iy

p y x e





,

1,2,...,in

. (1)

where

10

1

n

ii

i

yx









represents the usual linear

regression equation and

i

x

is independent variables

and

 

11i

p y x

is the occurrence probability of the

interested evince.

0



and

i



are a constant and

contribution of

i

x

to

p

. Although

1

y

is infinite,

 

11i

p y x

is bounded by 1 and 0 as the special

property of the logistic function.

By manipulating ( 1) , we obtain the following

logit equation [37] for the estimation purpose

Logit

 

11i

p y x

=

 

1

0

1

ln 1

11

n

i

i i i

i

p y x b b x

p y x























, (2)

where

 

1

i

p y x





is the odds of the event under

interest and

i



denotes the residual term.

Now, let define

j

y

by:

0

1

2

3

4

j

y











,

0,...,4j

From (2), we have the equation form, which we

apply to the multinomial logistic regression case

where

0j

is excluded for reference purposes as

follows:

 

1

j

y

j j i Jy

j

e

p y j x e







, (3)

where

,,

1

n

j j i j i j

i

yx









. Therefore, the

probabilities for the reference category and the

particular alternative

j

are as follows:

 

1

11 4

1

11j

y

iy

j

e

p y x e







,

.

 

4

44 4

1

41j

y

iy

j

e

p y x e







. (4)

and

 

00 4

1

01j

iy

j

p y x e







, (5)

Combining ( 4) , ( 5) , ( 6) , we obtain the

following logit models, [38].

Logit

 

1

p

=

 

4

11

1 ,1 ,1 ,1

1

00

ln 1

0

i

i i i

i

p y x b b x

p y x





















,

.

Logit

 

4

p

=

 

4

44

4 ,4 ,4 ,4

1

00

ln 4

0

i

i i i

i

p y x b b x

p y x





















. (6)

The marginal effects are the slope of the

prediction function at a given value of the

explanatory variable, which informs about the change

in predicted probabilities due to a change in a

particular predictor. These effects allow for the

conclusion of the direction and magnitude of the

relationship between an independent and dependent

variable, which can be written as follows, [39].

 

i

j j kj i

k

p y j x

ME p b b

x



  



, (7)

This study in questionnaires was brought into

play to collect data on demographic information

concerning participants and the perception of CCB,

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Adirek Vajrapatkul, Nuttawut Rojniruttikul

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1965

Volume 21, 2024

which was measured using a 5-point Likert scale and

an instrument developed earlier by [13], [40].

Three academicians employed the item objective

congruence index (IOC) [41] to validate the

questionnaire. Additionally, the reliability of the

questionnaire was assessed through the

administration of 30 pilot questionnaires, which

resulted in a Cronbach's alpha [42] value greater than

the cutoff criterion of 0.7. After successfully

verifying validity and reliability, hard copies of the

questionnaires were distributed to the target

population within the study area. From the 1,000

questionnaires handed out, we received 531 back. We

then analyzed the questionnaires and found only a

few incomplete ones, so with a total of 450

questionnaires, we started to explore them. These

forms were inputted into an exploratory factor

analysis to determine their construct validity.

The study was conducted using primary data

collected from bank customers who live in six

districts of Bangkok Metropolitan, including Min

Buri, Lat Krabang, Saphan Sung, Bangkapi, Lat

Phrao, and Chatuchak, in 2022. The data collection

procedure used surveys as tools, followed by

stratified and random sampling techniques in

different districts.

4 Main Results

Table 1 illustrates 450 valid data sets split into five

categories of customer citizenship behavior (CCB)

that differ from very low to very high. The

percentage column shows that 47.1 percent of the

valid cases have been classified as having extremely

high CCB. The model’s effectiveness was checked

using the Chi-square test represented in Table 2. The

chi-square value equals 196.584, and the

corresponding p-value is 0.000, confirming that the

dependent variable has a significant relationship with

the set of independent variables system. According to

the Nagelkerke R-square in Table 3, the variation

among the eight predictor variables accounted for

42.60 percent of the total variation in CCB level.

Using a very high level of CCB as the reference

category, Table 4 (Appendix) reveals the following

outcomes. At the neutral level of CCB (level 3), self-

service technology quality (SST) is negative and

statistically significant (

B

= -2.001,

..SE

= 0.483,

P value

= 0.000) . This indicates that for every

one-unit increase in SST, the odds of reaching the

neutral level change by a factor of

()Exp B

= 0.783

percent, indicating a decline in the odds. This

suggests that the likelihood of a customer having a

very high level of CCB increases with the SST level.

This interpretation also extends to on-site service

quality (OQS) and corporate governance (CGG).

Comparing customers in group 5 (41–45-year-olds)

to those in group 8 (56–60-year-olds) reveals that

group 5 customers are significantly more likely to

have a very high level of CCB at a 5 percent

significance level. With education, however,

customers with a high school diploma or a high

school vocational certificate are significantly more

likely to have a neutral level of CCB than those with

a bachelor's degree or higher.

Moreover, compared to a very high level of

CCB, the SST, OQS, and CGG are negative and

statistically significant at 5 percent, 10 percent, and 5

percent, respectively. This indicates that the

likelihood of attaining the high-level change

decreases with each unit increase in SST, OQS, and

CGG. This suggests that the greater the SST, OQS,

and CGG levels, the greater the likelihood that a

customer will have a very high level of CCB.

Females are more likely than males to have

extremely high levels of CCB at the 10 percent

significant level. With education, however,

customers in groups 1 and 4 are significantly more

likely to have a high level of CCB, at a 10 percent

and 5 percent significance level, respectively,

compared to those beyond a bachelor's degree. Also,

customers in income group 1 (less than 5,000 baht)

are likelier to have a high CCB level than those with

incomes above 50,000 baht.

Therefore, we can conclude that nations capable

of enhancing their SST, OQS, and CGG will increase

their CCB. Age and gender will also increase the

level of CCB, whereas education and income will

decrease it in this instance.

The evidence of the positive effects of SST,

OQS, and CGG on CCB can be examined by

examining the marginal effects shown in Table 5.

Based on Table 5, it was determined that a one-point

increase in SST decreased the probability of falling

into the neutral level of CCB by 12.04 percent and

increased the likelihood of falling into the very high

level of CCB by 17.56 percent. If OQS increases by

1 point, the probability of falling into the neutral

level of CCB decreases by approximately 9.96

percent, and the likelihood of falling into the very

high level of CCB increases by roughly 13.77

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Volume 21, 2024

percent. An increase of 1 point in CGG reduces the

probability of falling into the high level of CCB by

approximately 7.70 percent. In contrast, it increases

the likelihood of falling into the very high level of

CCB by roughly 12.23 percent.

Thus, the marginal effect analysis results

demonstrate that SST, OQS, and CGG can positively

affect the level of CCB.

Table 1. Valid number of CCB in each group

CBCLASSS

Frequency

Percent

3

66

14.7

4

172

38.2

5

212

47.1

Total

450

100

Source: Author’s calculation

Table 2. Model Fitting Information

Model

Model Fitting Criteria

Likelihood

Ratio Tests

-2 Log

Likelihood

Chi-

Square

df

Sig.

Intercept

857.967

Final

661.384

196.584

52

0.000

Source: Author’s calculation

Table 3. Pseudo R-Square

Cox and Snell

0.369

Nagelkerke

0.426

McFadden

0.229

Source: Author’s calculation

Table 4. Marginal effect analysis

Var.

Marginal

effect

Std. errs.

Z

P-value

TT

1

-

.1203769

.0368007

-3.27

0.001

2

-

.0552104

.0560508

-0.99

0.325

3

.1755873

.0512243

3.43

0.001

QS

1

-

.0995943

.0369013

-2.70

0.007

2

-

.0380958

.0556563

-0.68

0.494

3

.1376901

.0513011

2.68

0.007

CG

1

-

.0453127

.0296319

-1.53

0.126

2

-

.0769614

.0455584

-1.69

0.091

Var.

Marginal

effect

Std. errs.

Z

P-value

3

.1222741

.041921

2.92

0.004

1=CCB level 3, 2=CCB level 4, 3=CCB level 5,

Source: Author’s calculation

5 Discussion

The study results are consistent with previous

research findings, highlighting the need for banks to

improve their competitiveness by developing

corporate governance, which involves increasing

transparency, accountability, and fairness, promoting

trust and customer loyalty, [18]. The analysis of this

research results shows that improving corporate

governance significantly increases the chances of

banks achieving higher CCB levels. This indicates

that bank customers are more likely to engage in

positive behaviors and voluntarily support the

activities and businesses of the bank when they

perceive the bank as well-managed and trustworthy,

[20], [29].

Regarding SST, the analysis results show that

higher SST quality increases the chances of

achieving very high CCB levels. An increase in SST

quality was found to reduce the chances of attaining

neutral CCB levels but increase the chances of

achieving very high CCB levels. These findings are

consistent with previous studies that explored the

impact of transaction service quality on perceived

flexibility, creating a sense of control and enhancing

efficiency, which in turn lead to building trust among

customers and contribute to increasing CCB levels,

[26], [31]. The analysis also supports the findings of

previous studies found that SSTs help increase

customer satisfaction and loyalty because SSTs such

as ATMs, mobile banking, and internet banking

provide customers with convenience, which is a

factor in creating satisfaction and loyalty, [24], [25]

and leads to opportunities to increase the level of

CCB.

For the level of on-site service quality, which is

an important foundation for increasing customer

satisfaction and loyalty, the results of the data

analysis show that improving the quality of service

on-site significantly increases the chances of higher

CCB levels. Increasing the quality of on-site services

reduces the chances of neutral CCB levels but

increases the chances of high CCB levels. This result

supports previous studies' findings that service

quality is directly linked to customer satisfaction,

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DOI: 10.37394/23207.2024.21.159

Adirek Vajrapatkul, Nuttawut Rojniruttikul

E-ISSN: 2224-2899

1967

Volume 21, 2024

loyalty, and engagement [34], which can lead to

increased CCB levels.

In the case of the impact of demographic factors,

i.e., age, gender, education, and income, on CCB, it

was found that younger customers aged 41-45 years

and women have higher CCB levels. In addition,

customers with low income tend to have high CCB

levels, while customers with high incomes have low

CCB levels. These results provide insights into the

behavior of different demographic groups towards

services and opportunities for CCB development.

Therefore, strategies consistent with the factors

affecting CCB found in this study will increase the

chances of banks successfully increasing their CCB

levels.

6 Theoretical Implication

This research has provided evidence of the

connections between corporate governance, self-

service technology, on-site service quality, and CCB.

The CCB improvement framework developed in this

research could be extended by adding other potential

factors or layers of variables that are expected to

impact CCB. These may include customer trust in the

bank, customer experience of the services, customer

satisfaction with the services, and customer loyalty.

7 Managerial Implication

Implementing corporate governance in banks is

important. Good governance policies and practices

are an effective way to improve corporate

governance. Such policies and practices should

clearly state the roles and responsibilities of bank

representatives and provide reasons for how the bank

provides services to customers. In addition, banks

should improve the quality of services, as the quality

can affect customer feedback or the bank's

reputation. Banks may design new service processes

by applying technology and modern management

methods, such as welcoming and caring for

customers from the beginning to the end of the

service process through technology. Banks may also

create a service environment that provides

convenience and allows service recipients to enjoy

themselves while receiving services. These methods

will increase the opportunity to improve the CCB

level and the bank's long-term success.

8 Limitations and Future Research

The study has some limitations. First, the study was

conducted in limited samples and only within the

banking sector. Second, the study does not consider

some potential factors and layers of variables that

could affect CCB. Future research could expand the

sample size and get into other sectors to overcome

these limitations. Moreover, in the future, researchers

may include other potential factors and layers, e.g.,

through structural equation modelling techniques, to

better reflect the complexities of the CCB

determinants.

9 Conclusion

With the increasing competition in the banking

industry and customer expectations, banks have to

focus on building customer citizenship behavior

(CCB) to retain customers and increase the chances

of creating business success. Therefore,

understanding the factors that affect the level of CCB

is important for bank executives. Therefore, to

provide data to support the development of CCB

strategies for banks, this study aims to examine the

factors that affect the level of CCB of bank

customers. This study used data from residential

bank customers in six districts of Bangkok, Thailand,

and applied exploratory factor analysis (EFA) and

multinomial logistic regression techniques to the data

from 4 5 0 valid questionnaires. The EFA latent

variable analysis found three significant latent

variables, i.e., self-service technology quality, on-site

service quality, and corporate governance. After

analyzing with multinomial logistic regression and

incremental impact techniques, the results indicated

that banks could achieve the highest level of CCB by

improving corporate governance, self-service

technology quality, and on-site service quality.

Therefore, banks should focus on practices that

support the improvement of these factors.

Acknowledgements:

This research is supported by the business school,

King Mongkut’ s Institute of Technology

Ladkrabang, Thailand.

WSEAS TRANSACTIONS on BUSINESS and ECONOMICS

DOI: 10.37394/23207.2024.21.159

Adirek Vajrapatkul, Nuttawut Rojniruttikul

E-ISSN: 2224-2899

1968

Volume 21, 2024

Declaration of Generative AI and AI-assisted

technologies in the writing process

During the preparation of this work, the authors used

Grammarly to rewrite and check grammar. After

using this tool/service, the authors reviewed and

edited the content as needed and take full

responsibility for the content of the publication.

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APPENDIX

Table 5. Parameter Estimates

BCLSSa

B

Wald

Sig.

Exp(B)

3

Intercept

16.351

45.543

.000

SST

-2.001

17.187

.000

.135

OQS

-1.571

11.094

.001

.208

CGG

-1.038

7.016

.008

.354

[GEN=0]

-.525

1.723

.189

.592

[GEN=1]

0b

[AGE=1]

-.674

.453

.501

.510

[AGE=2]

-1.144

1.569

.210

.319

[AGE=3]

-.391

.189

.664

.676

[AGE=4]

-1.175

1.511

.219

.309

[AGE=5]

-2.631

6.910

.009

.072

[AGE=6]

-1.403

2.253

.133

.246

[AGE=7]

-1.713

2.301

.129

.180

[AGE=8]

0b

[EDU=1]

1.252

1.612

.204

3.496

[EDU=2]

1.370

2.580

.108

3.934

[EDU=3]

2.024

5.538

.019

7.571

[EDU=4]

1.180

2.114

.146

3.254

[EDU=5]

0b

[OCC=1]

.261

.079

.779

1.299

[OCC=2]

-.163

.029

.864

.849

[OCC=3]

.069

.005

.946

1.072

[OCC=4]

-1.427

1.582

.208

.240

[OCC=5]

0b

[INC=1]

.986

.406

.524

2.680

[INC=2]

-.260

.050

.824

.771

[INC=3]

.347

.091

.763

1.415

[INC=4]

-.388

.117

.732

.679

[INC=5]

-.777

.444

.505

.460

[INC=6]

1.142

1.129

.288

3.134

[INC=7]

1.337

1.408

.235

3.806

[INC=8]

0b

4

Intercept

7.246

22.917

.000

SST

-.787

5.996

.014

.455

OQS

-.557

3.255

.071

.573

CGG

-.751

8.781

.003

.472

[GEN=0]

-.445

3.139

.076

.641

[GEN=1]

0b

[AGE=1]

-.286

.187

.666

.751

[AGE=2]

-.342

.333

.564

.710

[AGE=3]

-.195

.106

.744

.823

[AGE=4]

-.164

.068

.794

.849

[AGE=5]

-.793

1.660

.198

.452

[AGE=6]

-.203

.112

.738

.816

[AGE=7]

-.762

1.175

.278

.467

[AGE=8]

0b

[EDU=1]

1.111

3.619

.057

3.038

[EDU=2]

.495

1.004

.316

1.640

[EDU=3]

.734

2.294

.130

2.083

WSEAS TRANSACTIONS on BUSINESS and ECONOMICS

DOI: 10.37394/23207.2024.21.159

Adirek Vajrapatkul, Nuttawut Rojniruttikul

E-ISSN: 2224-2899

1971

Volume 21, 2024

BCLSSa

B

Wald

Sig.

Exp(B)

[EDU=4]

.925

3.893

.048

2.523

[EDU=5]

0b

[OCC=1]

.987

2.441

.118

2.684

[OCC=2]

.881

1.976

.160

2.414

[OCC=3]

.791

1.331

.249

2.205

[OCC=4]

.118

.024

.876

1.126

[OCC=5]

0b

[INC=1]

1.937

4.103

.043

6.939

[INC=2]

.224

.119

.730

1.251

[INC=3]

.010

.000

.988

1.010

[INC=4]

-.271

.182

.670

.763

[INC=5]

.010

.000

.987

1.011

[INC=6]

.561

.826

.363

1.753

[INC=7]

.022

.001

.975

1.022

[INC=8]

0b

a. The reference category is: 5.00. b. This parameter is set

to zero because it is redundant.

Source: Author’s calculation

Contribution of Individual Authors to the

Creation of a Scientific Article (Ghostwriting

Policy)

The authors equally contributed in the present

research, at all stages from the formulation of the

problem to the final findings and solution.

Sources of Funding for Research Presented in a

Scientific Article or Scientific Article Itself

The business school, King Mongkut’s Institute of

Technology Ladkrabang, Thailand.

Conflict of Interest

The authors have no conflicts of interest to declare.

Creative Commons Attribution License 4.0

(Attribution 4.0 International, CC BY 4.0)

This article is published under the terms of the

Creative Commons Attribution License 4.0

https://creativecommons.org/licenses/by/4.0/deed.en_

US

WSEAS TRANSACTIONS on BUSINESS and ECONOMICS

DOI: 10.37394/23207.2024.21.159

Adirek Vajrapatkul, Nuttawut Rojniruttikul

E-ISSN: 2224-2899

1972

Volume 21, 2024