Behavioral Intentions of Bank Employees to Implement Green Finance

Abstract

To understand the behavioral intentions of bank employees to implement green finance, this study explores the impact of attitude, subjective norm, and perceived behavioral control on behavioral intention based on the theory of planned behavior. In addition, this study also examines whether internal measures have moderating effects on the relationship between attitude, subjective norm, perceived behavioral control, and behavioral intention. By collecting 123 questionnaires from 18 September 2022 to 18 October 2022, this study uses hierarchical regression to discuss the aforementioned issues. In order to avoid the possible bias of the regression model, the variance inflation factor (VIF) is applied to detect multicollinearity problems. The empirical results of this study find that bank employees’ attitudes, subjective norms, perceived behavioral control, and internal measures to implement green finance have a significant and positive impact on behavioral intention. In addition, the coefficients of VIF in all regression models are smaller than 10, indicating that the multicollinearity problems are not serious in this study. Therefore, our inferences are not affected by correlations between independent variables in the regression model. The research finding also shows that the interaction effects of internal measures and attitude, subjective norm, and perceived behavioral control do not have a positive moderating effect on behavioral intention. The implications of this study are that it can be provided as a reference for the banking industry to help them to improve the comprehensive thinking of employees in the implementation of green financial behavioral intentions.

1. Introduction

The United Nations adopted the Paris Agreement in 2015 and also announced 17 Sustainable Development Goals (SDGs) for 2030. Since then, human beings have begun to pay attention to the issue of sustainable development, so green finance has also emerged. In November 2016, the Paris Agreement, under the framework of the United Nations Framework Convention on Climate Change, came into effect. Consequently, the industrial structure and development guidelines of countries around the world have reached a new milestone. In response to the UN’s goal of keeping Earth’s temperature rise below 1.5 °C by 2030, the Taiwanese government promulgated the Greenhouse Gas Reduction and Management Act (this Act has been amended and was renamed the Climate Change Response Act on 15 February 2023) in July 2015. Article 4 of the law clearly stipulates that “the long-term national Greenhouse Gas (GHG) emission reduction goal shall be to reduce GHG emissions to no more than 50% of 2005 GHG emission by 2050”. Article 8 also formulates that “The Executive Yuan shall invite relevant central government agencies, non-governmental organizations, experts and scholars to determine and review the division, integration, implementation and compilation of the work of GHG reduction and climate change adaptation”. As for the GHG reduction and climate change adaptation, it includes green finance and incentive mechanisms for GHG reduction.

In 2016, in order to advance towards the goal of sustainable development and to be in line with international standards, the National Council for Sustainable Development (NCSD) of the Executive Yuan referred to the SDGs and developed Taiwan’s SDGs, which were completed in 2018. In the following year, relevant corresponding indicators were also determined. However, the difficulty after setting the goals is how to take into account sustainable development while pursuing national economic growth. The first question is where the huge amount of funding will come from, so financial institutions that play the role of allocating social resources are immediately regarded as the main force that guides all sectors of society to pay attention to sustainable development. In the international arena, relying on the influence of the financial market to promote sustainable development has already extended from focusing on green (environmental) aspects to covering the three major aspects of environment, social, and governance (referred to as ESG). Lee (2019) [1] pointed out that the policy development of green finance can also be called sustainable finance or ESG finance. More importantly, the influencing factor of the environment can be included in the business management strategy to mitigate the impact on the environment due to business operations, and ultimately promote the sustainable development of the social environment and the national economy in order to meet the targets.

In order to guide Taiwan towards green and low-carbon growth, the Executive Yuan has asked the Ministry of Finance (MOF), the Financial Supervisory Commission (FSC), the National Development Council (NDC), and other ministries and commissions to jointly handle green financial matters, and since 2017, the “Green Finance Action Plan 1.0” has been promoted, covering investment, credit granting, talent cultivation, capital market financing, information disclosure, promoting the deepening of green financial products or services, and promoting the concept of green sustainability. In addition to the sustainable development of the financial industry and assisting the green energy industry to obtain the funds needed for business turnover and industrial development, the plan also hopes to use the power of the financial market to encourage enterprises, consumers, and investors to pay attention to green sustainability, and let Taiwan transform into a green investment, low-carbon economy (FSC, 2017) [2]. After releasing the “Green Finance Action Plan 1.0” in August 2020, the FSC also released the “Green Finance Action Plan 2.0” with the concept of encouraging financial institutions to support green and sustainable industries. In order to comply with the international development trend and achieve the goal of net zero emissions by 2050, the “Green Finance Action Plan 3.0” was released in September 2022, hoping to gather consensus from all parties and bring positive trends to financial and various other industries (FSC, 2022) [3]. The three core strategies of “Green Finance Action Plan 3.0” are achieving the goal of net zero emissions, working together to deepen sustainable development, and promoting overall industry carbon reduction through investment and financing and strengthening climate resilience and risk response capabilities. These strategic objectives are aligned with the Principles for Responsible Banking (PRB) announced by the United Nations in September 2019.

In January 2022, the International Finance Corporation (IFC), a subsidiary of the World Bank, issued the “Guidelines for Blue Finance” to promote the achievement of the SDGs. In September 2022, all pan-public banks in Taiwan signed up to the Equator Principles Association (EPA), which will increase the environmental and social risk assessment of credit cases, regularly monitor and exert control after the approval of loans, implement responsible finance, avoid improper financing from causing major risks to the environment and society, and control the use of funding sources. All of these measures show that the banking industry is making every effort to contribute towards green finance. In order to promote the development of the green financial market, international organizations such as the Asia Pacific Loan Market Association (APLMA), the Loan Market Association (LMA), and the Loan Syndications and Trading Association (LSTA) jointly issued the “Sustainability Linked Loan Principles”, “Green Loan Principles”, and other green financial standards and principles based on nothing more than to achieve the common goal of sustainable development. Based on the aforementioned descriptions, the financial industry has two specific meanings in green finance: “sustainable development of the financial industry” and to “use the influence of the financial industry to guide various industries and enterprises to pay attention to ESG issues”. Green finance can be said to be an important core of international financial policy development.

Clark (2022) [4] pointed out that the implementation of ESG and sustainable finance requires the active participation of different stakeholders, and must be effectively put into practice. It is also necessary for every department from the front desk to the back office to have consistent consensus. Driven by the aforementioned ESG issues, financial institutions have successively launched financial products linked to ESG in recent years, and employees who are stakeholders of financial institutions are the souls of the effective implementation of green finance. Consequently, this motivated us to explore the behavioral intentions of bank employees to implement green finance.

The theory of planned behavior (TPB) argues that people may be influenced by external and irrational factors when they engage in a specific behavior. In addition to rational attitude and subjective norm, the control variable of perceived behavior, which directly affects behavioral intention and actual behaviors, can be considered. This study is based on the framework of the TPB, and expands the theory by adding an internal measures variable to predict the behavioral intentions of bank employees to implement green finance. We construct research hypotheses through the perspectives of attitude, subjective norm, perceived behavioral control, and internal measures, respectively, to investigate whether these arguments have an impact on the behavioral intentions of bank employees when implementing green finance. Under the trend of green finance, whether the bank’s internal measures may have a moderating effect among the variables is also an interesting issue that this study intends to explore. Accordingly, we propose that the bank’s internal measures have moderating effects on the relationship between attitude, subjective norm, perceived behavioral control, and behavioral intention, respectively.

Consistent with our hypotheses, the empirical findings show that attitude, subjective norm, perceived behavioral control, and internal measures are all significantly positively associated with behavioral intention. The hierarchical regression analysis indicates that attitude and perceived behavioral control significantly and positively affect bank employees’ behavioral intentions to implement green finance. This finding supports the view that the theoretical model of planned behavior has the effect of predicting behavioral intention and is consistent with the work of Tsai (2017) and Aziz et al. (2021) [5,6]. This study also finds that after considering the internal measures variable, the model also has the effect of predicting behavioral intention, and may improve the predictive ability. Although the variables of internal measures and subjective norm are not significant, both of them are still positively related to behavioral intention. As for the moderating effect, the empirical result also indicates that the interaction effects of attitude and internal measures on behavioral intention is not significant or positive. Therefore, we do not find any evidence to support the hypothesis that the internal measures of banks have a moderating effect on the relationship between attitude and behavioral intention. Similarly, the interaction effect of subjective norm and internal measures on behavioral intention is not significantly positive. Consequently, we cannot observe any evidence to support the hypothesis that the internal measures of banks have a moderating effect on the relationship between subjective norm and behavioral intention. Also, the interaction effect of perceived behavioral control and internal measures on behavioral intention is still insignificant and positive. This result reveals that the hypothesis that the internal measures of banks have a moderating effect on the relationship between perceived behavioral control and behavioral intention is not supported.

The managerial implications of this study are discussed as follows. In terms of theoretical implications, attitude and perceived behavioral control are significantly and positively related to the behavioral intentions of bank employees to implement green finance. With the rise of green finance, the banking industry should be committed to improving the positive attitudes of employees toward the implementation of green finance, eliminating the pressure that comes from supervisors, peers, and customers, and making employees aware that banks can provide sufficient resources. For female, senior, and new junior employees, as well as older and younger employees, more effort must be made by banks to establish their attitudes, subjective norms, and perceived behavioral control when implementing green finance. In addition, it is recommended that banks should establish ESG executive officers, specify incentive measures, strengthen cross-departmental coordination and cooperation, and enhance ESG education and training for all employees. As for practical implications, like other companies, the operating purpose of the banks is to generate profits. However, banks in Taiwan are chartered businesses, and banking operations are regulated by strict regulations and are usually conservative. Consequently, banks are slow to embrace new changes or new innovation. Previous studies indicate that integrating innovative ideas and products into operations will help improve the company’s economic performance, market position, and financial performance, and even achieve the goal of sustainable development (Alshebami 2023; Asadi et al., 2020; Jiang et al., 2018; Alshebami 2021; Muangmee et al., 2021; Battisti and Perry 2011; Green and Inman 2005; Khan and Johl 2021) [7,8,9,10,11,12,13,14]. From the perspective of banks, how to quickly respond to changes in the external environment, invent innovative green products or green services, provide them to those in need in the market, increase the bank’s profitability, assist enterprises in transformation, and then promote sustainable development policy are very important issues.

The contributions of this study are summarized as follows. First, to our knowledge, this is the first paper to explore, form their perspective, the behavioral intentions of bank employees to implement green finance. The results of this study will help to address the gap in the existing literature. The second contribution is to incorporate the moderating effect of the internal measures of banks into our model. The empirical result of this study will bring constructive value to the banking industry. Finally, the empirical findings of this study are helpful in terms of assisting the banking industry to improve the comprehensive thinking of practitioners in the implementation of green finance behavior intention, and to put forward reasonable suggestions for the banking industry.

The rest of this study is organized follows. In the literature review and hypotheses development section, we review the previous literature and then develop the research hypotheses. In the data collection and methodology section, we describe the data collection process and research methods this study applied, and provide evidence to test our hypotheses through empirical results. Finally, we conclude and discuss the managerial implications of the empirical findings.

2. Literature Review and Hypotheses Development

2.1. Literature Review

In the past, the definition of green finance was inconclusive (Höhne et al., 2012; Zadek and Flynn, 2013; PricewaterhouseCoopers Consultants (PWC), 2013) [15,16,17]. Höhne et al. (2012) [15] indicate that green finance is financial investment that flows into sustainable development projects and initiatives, environmental goods, and policies that promote more sustainable economies. From the viewpoint of Zadek and Flynn (2013) [16], green finance is often used interchangeably with green investment. The implementation of green finance is not only the investment defined by Bloomberg New Energy Finance and others, but also the operating cost of green investment not included under the definition of green investment, which may bring obvious financing challenges. In addition, according to the research report published by PWC (2013) [17], in terms of the banking industry, green finance is defined as financial products and services that consider environmental factors throughout the processes of loan decision making, post-event monitoring, and risk management. In terms of our viewpoint, green finance is any financial activity that can create a positive impact on the environment, whether through personal investment (financing), corporate loans, or the bank issuance of green financial products, etc., investing a large amount of funding in sustainable development projects, and encouraging everyone (including enterprises) to do their best to reduce the negative impacts of their financial operations on the climate or the environment.

There are initiatives to promote the deepening of green financial products or services in the “Green Finance Action Plan 1.0” promoted by the FSC. Hsu and Li (2022) [18] also argue that under the international wave of ESG, financial institutions have launched financial products linked to ESG in recent years. The “Green Finance Action Plan 2.0” promotes eight specific aspects and measures, including investment, credit granting, talent cultivation, information disclosure, capital market financing, promotion of the development of green financial products or services, prudent supervision, international links, and incentive mechanisms. The “Green Finance Action Plan 3.0” utilizes the five aspects of deployment, funding, data, empowerment, and the ecosystem, hoping to strengthen the role of financial institutions and deepen sustainable development through the power of the financial market. Among them, there are several specific measures for funds, which are to encourage the financial industry to be included in investment and financing decision making, to encourage enterprises to formulate transformation plans, to continue to invest funds (especially bank loan funds) into green and sustainable development, and to promote Taiwan’s green economy sustainable activities and market development. In order to assist the business community and the investing public to pursue carbon reduction and transformation, financial institutions have launched innovative and creative green financial products and services, which can be roughly divided into green stock, green bond index, green funds (including Exchange Traded Fund, ETF), green credit cards, green insurance products, perpetual linked loans, green industry financing, and green deposits (FSC, 2017; 2020; 2022) [2,3,19].

The Asia Pacific Economic Cooperation (APEC, 2010) [20] indicated that green finance is to promote green growth through financial support; the most important work of profit-making institutions is to complete environmental improvement and green growth. The best state of green growth is that it can coexist harmoniously with the environment while growing the economy, and the ultimate goal is to solve the problems of climate change, limited energy reserves, and financial crises that currently threaten the world economy. From a broad perspective, Höhne et al. (2012) [15] discussed that green finance is considered financial investment in sustainable development projects, initiatives, environmental goods, and economic policies that reward sustainable development. Green finance not only refers to climate finance, but also includes mitigation and adaptation finance and other related environmental finance (such as industrial pollution control or biodiversity conservation). PWC (2013) [17] believes that green finance is financial products and services provided under the consideration of environmental factors. In short, green finance hopes to introduce concepts such as energy saving, carbon reduction, and environmental pollution reduction in financial services to do our best for the Earth. It emphasizes the sustainability of long-term development more than ordinary finance. Green finance has become mainstream around the world. Taiwan’s FSC is actively promoting green finance action plans based on the experience of advanced Western countries, and has introduced the Task Force on Climate-Related Financial Disclosures (TCFD) indicators into the domestic banking, insurance, and securities industries. There is no doubt that green finance has become a new financial science.

In the argument of Lee (2019) [1], the rise of green finance is not a moral initiative, but a practical necessity. In the study of banks engaged in green finance, Bose et al. (2021) [21] indicate that green financial performance is positively correlated with the financial performance of banks. Alshebami (2021) [10] also found that there is a significant positive relationship between the implementation of green finance and the bank’s green image. Consequently, the more green finance projects that are implemented, the higher the degree of improvement in the bank’s image. Sharma and Choubey (2022) [22] stated that the banking industry has a very important special position in affecting the country’s economic growth and development, and the banking industry can make good use of improving financial availability to meet the needs of the green economy. Zhang et al. (2022) [23] more clearly indicated that green financial activities have a significant positive impact on banks’ environmental performance and green financing. Green financing also has a significant impact on the environmental performance of banks, and green financing has a moderating effect between green financial activities and the environmental performance of banks.

Sabbir and Taufique (2022) [24] found that in order to maintain employees’ green behavior in the workplace, it is necessary to have a full understanding of the factors that induce green behavior. The environmental protection behaviors performed by employees in their jobs and daily duties are called task-oriented employees’ green behavior. However, both cognitive and non-cognitive factors significantly influence task-oriented employees’ green behavior. In their research on green finance and bank employees, Alshebami (2021) [10] showed that the implementation of green finance policies by banks will directly affect the green behavior of employees. The result suggested that the implementation of green finance by banks can enhance the bank’s green image, and that banks should disseminate green awareness among employees, customers, and other stakeholders. Chen et al. (2022) [25] also found that bank employees and the bank’s policy on the implementation of green finance are positively related to green financing, and the bank’s green financing products have a stronger and more positive impact on the bank’s environmental performance. However, in the study of Zhang et al. (2022), they found that in addition to being constrained by investment costs and technical barriers, green financial products and green financing loan evaluators are also relatively incompetent [23]. Therefore, the difficulty and complexity of green financial project evaluation is the main challenge affecting the development of green finance.

2.2. Hypothesis Development

The TPB is a conceptual model based on the theory of rational action and considers the conceptual model formed by the variable of perceived behavioral control, so it is a continuation of the theory of rational action. Ajzen (1985) [26] argued that many studies on attitude and behavioral orientation have adopted the TPB model, and in the follow-up study of Ajzen and Driver (1992), they used the theoretical model of planned behavior to predict the willingness of college students to engage in beach leisure activities. Their findings showed that accounting for the perceived behavioral control variable improved the explanatory and predictive power of the model [27]. The TPB asserts that people may be influenced by external and irrational factors when they want to engage in a specific behavior. Therefore, in addition to rational attitude and subjective norm, this study also considers the perceived behavioral control variable that directly affects behavioral intention and actual behaviors. Furthermore, based on the foundation of the TPB, this study moderately expands the theory by adding an internal measures variable to the model and predicting the behavioral intentions of bank employees to implement green finance.

Ajzen and Fishbein (1980) [28] argued that attitude is composed of cognition and emotion. The so-called cognition refers to someone’s opinion on someone and something, while emotion refers to the evaluation of its trigger. Attitude is the actor’s evaluation or emotion towards a certain behavior, and the more positive the actor’s attitude towards the behavior, the higher the behavioral intention (Ajzen, 1991, 2001) [29,30]. Ajzen (1991) [29] indicates that the TPB has been fully supported by empirical evidence. Through attitude, subjective norm, and perceived behavioral control, the TPB predicts intentions for different types of behavior with high precision, and these intentions, together with perceptions of behavioral control, explain large differences in actual behavior. Ajzen (1991) [29] found that attitude, subjective norm, and perceived behavioral control significantly affect behavior, norms, and control beliefs. Raza et al. (2019) [31] pointed out that the variables of attitude, subjective norm, and perceived behavioral control have a positive impact on the intentions of Islamic bank employees and customers to purchase Islamic insurance. Aziz et al. (2021) [6] also found that attitude and perceived behavioral control will significantly affect employees’ intention to approach the environment behavior. Similarly, the finding of Tsai (2017) also showed that employees’ attitudes toward participating in public welfare activities will positively affect their behavioral intentions [5]. Thus, we developed our first hypothesis:

Hypothesis 1 (H1).

Attitude is significantly and positively related to the behavioral intentions of bank employees to implement green finance.

Ajzen (1991) [29] argued that subjective norm is the pressure that the actor feels and endures when engaging in a specific behavior. The source of this pressure may come from influential people such as supervisors, peers, customers, or external information and interpersonal relationships (Bhattacherjee, 2000) [32]. In the research on employees’ subjective norms, Bouarar et al. (2021) [33] found that attitude and subjective norm have a significantly positive impact on employees’ behavioral intentions in terms of green implementation. Khalid et al. (2022) [34] also found evidence that employees’ green attitudes, green subjective norms, and green perceived behavioral control have positive effects on employees’ green behavior intentions. In addition, organizational support further enhances the positive impact on employees’ green behavior intentions. Luo (2014) [35] also found that employee participation in corporate social responsibility (CSR) attitudes, subjective norm, and perceived behavioral control are significantly and positively related to behavioral intention to participate in CSR activities. In addition, the empirical findings of Gamel et al. (2022) [36] show that subjective norm, perceived behavioral control, consumption status, and investor experience have statistically significant effects on wind energy investment intentions. Accordingly, we propose the following hypothesis:

Hypothesis 2 (H2).

Subjective norm is significantly and positively related to the behavioral intentions of bank employees to implement green finance.

Perceived behavioral control is the actor’s cognition of whether it is difficult or easy to engage in a specific behavior when engaging in it (Ajzen, 2001) [30]. Controlling belief indicates the degree of cognition of how many resources or how many obstacles a person encounters when engaging in a certain behavior. Compared with controlling belief, the perception-facilitating condition is the extent to which this behavior is affected by these resources or obstacles. When the perceived behavior is properly controlled, more resources and opportunities become available and the expected obstacles reduce. Aziz et al. (2021) [6] found that attitude and perceived behavioral control are positively correlated to employees’ intentions to approach the environment behavior. The empirical finding of Katz et al. (2022) [37] also indicates that employees’ environmental attitudes, subjective norms, and perceived behavioral control have positive impacts on their environmental behavior intentions. Similarly, in the study of Chen and Hung (2016) [38], they found that consumers’ attitudes, perceived behavioral control, environmental awareness, and environmental ethics and beliefs are significantly positively correlated with their willingness to use green products. Zhang et al. (2019) [39] also extended the TPB structure and incorporated a cognitive construct, namely, environmental concern, to explore purchase intentions for different kinds of green products. Their findings indicated that attitude, perceived behavioral control, and environmental concern have a significant and positive impact on the purchase intention of both utilitarian green products and hedonic green products. However, subjective norm only has a significant and positive impact on the purchase intention of utilitarian green products. In the light of the importance of perceived behavioral control, we construct the third hypothesis, as follows:

Hypothesis 3 (H3).

Perceived behavioral control is significantly positively related to the behavioral intentions of bank employees to implement green finance.

Internal measures are an important mechanism for bank operations because they help ensure employee compliance, effectively keep compliance programs running as usual, and enhance customer loyalty to the bank. The internal measures cover a wide range, such as organizational structure adjustment, staffing, reward and punishment systems, and the intensity of on-the-job training. The Central Bank of the Republic of China (Taiwan) (CBRC (Taiwan)) (2021) [40] also pointed out that in the process of promoting sustainable financial business, financial institutions will encounter obstacles that require high investment, such as internal communication, organizational transformation, and education and training. However, internal communication and organizational transformation take a long time, and it is rather difficult to cultivate sustainable financial talent, education, and training. Moreover, in order to promote the development of sustainable finance, it is also necessary to negotiate with stakeholders. From the viewpoint of Clark (2022) [4], in the process of implementing ESG and a sustainable financial framework, employees, customers, and investors need to fully understand the potential benefits and the competitive advantages they can bring to the bank. Of course, banks must also keep their employees informed about what the bank is doing and how far it is going. It can be seen that good internal measures help to strengthen the behavioral intention of bank employees to implement green finance, and then positively affect the intention to engage in green finance.

Although applying the TPB to predict behavioral intention is a fairly mature research model, many scholars have suggested that additional variables should be considered in the model to improve its explanatory ability. Ajzen (1991) and Hagger et al. (2002) also suggested that follow-up researchers should consider other factors to improve the explanatory ability of behavioral intention [29,41]. In view of this, this study is based on scholars’ discussions and the practices of financial institutions in the process of promoting green financial business, constructing an internal measures variable, and putting forward the following hypothesis:

Hypothesis 4 (H4).

Internal measures of banks have a significant and positive impact on bank employees’ behavioral intentions to implement green finance.

In addition, this study also attempts to understand whether the internal measures of banks may have a moderating effect among the variables now that the wave of green finance is rising. Consequently, this study uses internal measures as a moderating variable to explore their moderating effects, and proposes the following three hypotheses:

Hypothesis 5 (H5).

The internal measures of banks have a moderating effect on the relationship between attitude and behavioral intention.

Hypothesis 6 (H6).

The internal measures of banks can moderate the relationship between subjective norm and behavioral intention.

Hypothesis 7 (H7).

The internal measures of banks can moderate the relationship between perceived behavioral control and behavioral intention.

Consequently, this study applies the TPB proposed by Ajzen and Driver (1992) [27] and expands it to consider attitude, subjective norm, perceived behavioral control, and internal measures in the model, and explores the behavioral intentions of bank employees to implement green finance. The structure of this study is organized as shown in Figure 1.

According to the research framework, the definitions of the research variables in this study including attitude, subjective norm, perceived behavioral control, internal measures, and behavioral intention are summarized in

Table 1. Definitions of research variables in all constructs.

Construct	Definition	Question	Reference
Attitude	The attitude of bank employees towards the implementation of green finance is positive or negative.	I feel happy to be able to promote green finance business at work. I think it is valuable to be able to promote green finance business in my work. I think being able to promote green finance business at work is helpful to society. I think it is in line with the trend of the times to be able to promote green finance business at work.	Ajzen (1991, 2001) [29,30] Aziz et al. (2021) [6]
Subjective Norm	Bank employees feel the influence of key stakeholders when implementing green finance.	I think my supervisor will agree with me in promoting green finance business at work. I feel that my colleagues will agree with me in promoting green finance business at work. I think customers will agree that I promote green finance business in my work. I feel that the supervisor will recognize that I actively assist customers to obtain green financial services in my work. I feel that my colleagues will recognize that I actively assist customers to obtain green financial services in my work.	Ajzen (1991) [29] Bhattacherjee (2000) [32]
Perceived Behavioral Control	The degree of difficulty for bank employees to implement green finance	I think it is easy for me to promote green finance business in my work. I believe I have sufficient knowledge and ability to promote green finance business. I know how to assist customers to obtain green financial services. I firmly believe that the green finance services I provided are beneficial to both banks and customers.	Ajzen (2001) [30] Katz et al. (2022) [37]
Internal Measures	In the process of promoting green finance business, banks need to take measures including cross-departmental consultation, education and training, and letting stakeholders fully understand the potential benefits.	The establishment of ESG executive officers by banks can effectively enable bank employees to promote green finance business in their work. Banks’ explicit incentive measures can effectively enable bank employees to promote green finance business at work. Banks strengthen cross-departmental coordination and cooperation can effectively enable bank employees to promote green finance services at work. Banks strengthen ESG education and training for all employees, which can effectively enable bank employees to promote green finance business at work.	CBRC (Taiwan) (2021) [40] Clark (2022) [4]
Behavioral Intention	The subjective probability that bank employees engage in the implementation of green finance	I would like to try to share my green finance knowledge with colleagues in the bank. I would like to try to share my green finance knowledge with customers. I would like to try to promote green finance business at work. I would like to try my best to help customers obtain green financial services.	Ajzen (2001) [30]

.

3. Data Collection and Methodology

3.1. Data Collection

This study employed the TPB as the framework for the questionnaire design. We mainly conducted surveys on current bank employees, and collected primary data by means of questionnaires. In order to make the design of the questionnaire conform to the theory validity and content validity, before designing the questionnaire, we interviewed six bank employees in an attempt to understand the thoughts and behavior patterns of current bank employees on the implementation of green finance. Accordingly, this provided us with an important reference for designing the questionnaire. After pre-testing and confirming that each measurement reached an acceptable level, we designed a questionnaire using Google Forms, and sent a link with the URL of the questionnaire to the bank employees familiar with the researcher through the LINE. In addition, the bank employees who completed the questionnaire were asked to forward the link to other colleagues and friends serving in the bank. The researchers also publicized the questionnaire URLs through the two fan pages of the bank on Facebook, asking current bank employees to fill in the answers. The questionnaire was open for answering from 18 September 2022 to 18 October 2022. The survey period lasted for one month, and a total of 123 questionnaires were collected. Since each question item was set as mandatory, there were no invalid questionnaires.

The demographic variables collected by this study include gender, age, education, education major, years of service in the bank, service department, and type of bank service. According to the data from the returned questionnaires, males accounted for 56.9% of the overall sample. The participants were mainly aged between 46 and 55 years old. Most of the respondents had a university degree or above, and most of them majored in finance, economics, and business management. It is obvious that most of the respondents are high-level intellectuals. As for the years of service, most of the respondents had worked at their bank for over 21 years, and the most common service department was the credit department. The types of banks that the respondents worked for were mainly domestic private banks.

3.2. Methodology

Hierarchical regression is mainly used to test the influence of the relationship between two or more independent variables on the dependent variable. If the influence of the relationship between one independent variable on the dependent variable is greater than the influence of the relationship between another independent variable on the dependent variable, it is necessary to consider the importance of this variable. When performing regression analysis, this is determined by observing whether the increase in the R-square of the regression model is significant at the statistical level by adding a newly independent variable. Because of the abovementioned properties, this study will employ hierarchical regression to investigate whether rational behavior theory, planned behavior theory, and the research framework of this study have different explanatory abilities in predicting the behavioral intentions of bank employees to implement green finance.

Generally speaking, if there is a serious multicollinearity problem in the multiple regression model, the regression coefficient will be biased, causing the sign of the regression coefficient to be contrary to the expectation, and even the significance of the variables will be changed, leading to incorrect inferences in the study. Accordingly, this study applies the variance inflation factor (VIF) to detect the multicollinearity problem of the hierarchical regression model. If the VIF is greater than 10, it shows that the hierarchical model has serious multicollinearity problems, and the regression model needs to be corrected.

4. Empirical Result

Reliability analysis is used to test the stability and reliability, that is, the consistency and stability of the respondents’ answers in each construct. The coefficient of Cronbach’s α is usually used as an indicator to detect the reliability of the research, and confirms the internal consistency and correlation of each construct. Nunnally (1978) [42] suggested that the coefficient of Cronbach’s α must exceed 0.7 to correspond to the standard of reliability. The reliability of all constructs in this study is reported in

Table 2. Reliability analysis of all constructs.

Constructs	Number of Items	Cronbach’s α
All	21	0.979
Attitude	4	0.959
Subjective Norm	5	0.955
Perceived Behavioral Control	4	0.890
Internal Measures	4	0.948
Behavioral Intention	4	0.970

. The finding in Table 2 reveals that the Cronbach’s α in this research is as high as 0.979, and the Cronbach’s α value of each construct is above 0.9, except for perceived behavioral control, which is 0.890. In the unreported result, factor analysis shows that the coefficient of KMO of the questionnaire is 0.938, and the result of Bartlett’s test of sphericity is also significant (x² = 3605.154, df = 210, p < 0.001). The coefficients of factor loadings are all above 0.7, and the cumulative total explained variance is 81.717%. It can be seen that the measurement of each variable in this study has sufficient consistency and has acceptable reliability and validity.

This study uses one-way ANOVA analysis to examine whether there are differences between groups in the constructs of attitude, subjective norm, perceived behavioral control, internal measures, and behavioral intention among the demographic data. The one-way ANOVA analysis result is reported in

Table 3. ANOVA results for research variables.

	Attitude	Subjective Norm	Perceived Behavioral Control	Internal Measures	Behavioral Intentions
Years of Service in the Bank	*	*	*	*	*
Service Department
Education
Education Major
Age	*		*		*
Gender					*
Type of Bank Service

* Present significant difference.

. We find that years of service in the bank, age, and gender have group differences in one or more constructs. It can be seen that there are significant differences among the years of service in the bank in terms of attitude, subjective norm, perceived behavioral control, internal measures, and behavioral intention. In the unreported table, Scheffe and Tukey’s post hoc test results show that there are group differences between the junior and senior groups, and between the young and old groups. In addition, the behavioral intentions of male bank employees in terms of implementing green finance are significantly higher than those of female employees.

This study uses Pearson correlation analysis to examine whether there is a significant positive correlation between bank employees’ attitudes, subjective norm, perceived behavioral control, internal measures, and behavioral intentions. In

Table 4. Pearson correlation coefficient analysis.

	Attitude	Subjective Norm	Perceived Behavioral Control	Internal Measures	Behavioral Intention
Mean	3.9126	3.6081	3.3882	3.6870	3.7703
Standard Deviation	0.9954	0.9473	0.8941	1.0527	0.9125
Attitude	1.00
Subjective Norm	0.807 ***
Perceived Behavioral Control	0.694 ***	0.770 ***
Internal Measures	0.754 ***	0.833 ***	0.727 ***
Behavioral Intention	0.845 ***	0.797 ***	0.810 ***	0.771 ***	1.00

*** Present significant at 1%; the parameter of parentheses is t-value.

, this study finds that attitude, subjective norm, perceived behavioral control, internal measures, and behavioral intention all have significant and positive correlations between the two variables. The correlation between attitude and behavioral intention is the highest, and the correlation coefficient is 0.845. The correlation between perceived behavioral control and behavioral intention is second, and the correlation coefficient is 0.810. The correlation between internal measures and behavioral intention is the lowest, and its correlation coefficient is 0.771. The Pearson correlation analysis result shows that the higher the attitude and perceived behavioral control, the stronger the behavioral intention. In addition, the behavioral intention of implementing green finance is mostly positive, and the average is 3.7703, which is only slightly higher than the median. The implication of this result is that about half of the respondents still have negative or uncertain views. It is worth noting that we cannot conclude that a higher correlation coefficient between two independent variables will result in the multicollinearity of the regression model (the serious multicollinearity problem is caused by the high degree of linear dependence among multiple explanatory variables (Myers, 1990) [43]). The multicollinearity should be tested by VIF in the following hierarchical regression model.

Table 5. Univariate regression analysis of behavioral intention.

Independent Variable	Coefficient	R Squared
Attitude	0.845 *** (17.36)	0.713
Subjective Norm	0.797 *** (14.53)	0.636
Perceived Behavioral Control	0.810 *** (15.18)	0.656
Internal Measures	0.771 *** (13.34)	0.595

*** Present significant at 1%; the parameter of parentheses is t-value.

reports the univariate regression results for behavioral intention. The empirical finding shows that attitude, subjective norm, perceived behavioral control, and internal measures are significantly and positively related to behavioral intention, respectively. This evidence supports Hypotheses H1 to H4.

This study uses hierarchical regression to analyze the predictive ability of each variable in the theoretical model on the behavioral intention of bank employees to implement green finance. In model 1 of

Table 6. Hierarchical regression results for behavioral intention.

Model	Independent Variable	Coefficient	T-Statistic	p-Value	R2
Model 1	Attitude	0.529 **	7.492	0.000	0.748
	Subjective Norm	0.319 **	4.307	0.000
Model 2	Attitude	0.455 **	7.243	0.000	0.808
	Subjective Norm	0.090	1.213	0.227
	Perceived Behavioral Control	0.401 **	6.199	0.000
Model 3	Attitude	0.433 **	6.774	0.000	0.810
	Subjective Norm	0.028	0.334	0.739
	Perceived Behavioral Control	0.380 **	5.786	0.000
	Internal Measures	0.104	1.602	0.112

** Present significant at 5%.

, which is adopted to verify rational behavior theory, we use attitude and subjective norm as independent variables to predict the behavioral intention of bank employees to implement green finance. In addition to attitude and subjective norm, behavioral control is also taken into account in model 2, which is verification of the theory of planned behavior. This study also proposes model 3 by adding internal measures in model 2 to verify the additional model.

In the rational behavior theory of model 1, the coefficients of attitude and subjective norm are 0.529 and 0.319, respectively, and are significantly positively associated with behavioral intention. The finding that the magnitude of the coefficient is larger in attitude rather than subjective norm indicates that attitude has a greater influence on behavioral intention than subjective norm. The coefficient of ΔR² in model 1 shows that the prediction ability in model 1 is 74.8%.

Compared with rational behavior theory in model 1, the predicting ability of the TPB is 80.8%, and it explains more than 6% of the variation in model 1. Consequently, we conclude that the TPB should be superior to the theory of rational behavior in predicting behavioral intention. Except for subjective norm, we can observe that attitude and perceived control are significantly and positively associated with behavioral intention, and attitude still has a larger impact in this model.

When the internal measures are added, the prediction ability in model 3 increases about 0.2% compared with model 2. In spite of the predicting ability in model 3 being slightly higher than in model 2, and it may be constrained by the sampling not being wide enough, it cannot be inferred that this model is better than the TPB in predicting behavioral intention. Similar to model 2, both attitude and perceived behavioral control are significantly positively associated with behavioral intention, and attitude also still has a larger impact.

In terms of the appropriateness analysis of behavioral intention, the empirical results of this study support the view that the theoretical model of planned behavior has the effect of predicting behavioral intention. Although the subjective norm variable is not as good as we expected, attitude and perceived behavioral control are significantly and positively related to the behavioral intention of bank employees in terms of implementing green finance. This result is consistent with the findings of Tsai (2017) and Aziz et al. (2021) [5,6].

After adding the variable of internal measures, the model also has the effect of predicting behavioral intention and improving the predictive ability, although subjective norm and internal measures are not significantly positively associated with behavioral intention.

Baron and Kenny (1986) [44] found that when using hierarchical regression analysis to examine the moderating effect, in order to avoid the problem of multicollinearity, it is necessary to standardize the independent variable and the adjustment, that is, the technique of mean centering. In light of this, this study adopts hierarchical regression and constructs three models to investigate whether the internal measures have a moderating effect on attitude, subjective norm, and perceived behavioral control toward behavioral intention. These models are established as follows. The first one uses attitude, subjective norm, or perceived behavioral control as independent variables, and the second is used to emphasize the examination of the impact of attitude, subjective norm, or perceived behavioral control and internal measures on behavioral intention. Finally, the interaction term of attitude, subjective norm, or perceived behavioral control and internal measures on behavioral intention is used to capture its relative influence.

The empirical finding in model 2 of

Table 7. Moderating effect of internal measures on the relationship between attitude and behavioral intention.

Independent Variable	Model 1	Model 2	Model 3
Attitude	0.845 *** (17.36)	0.610 *** (8.86)	0.559 *** (7.21)
Internal Measures		0.312 ***	0.306 ***
Attitude × Internal Measures			−0.083
R2	0.713	0.755	0.759
ΔR2	0.713	0.042	0.004
F	301.302	185.182	125.080
ΔF			1.948
VIF		2.321	1.754

*** Present significant at 1%; the parameter of parentheses is t-value.

shows that both attitude and internal measures have direct effects on behavioral intention. Regarding the moderating effect of internal measures on the relationship between attitude and behavioral intention, we find the change of R² is 0.004, and value of ΔF is not significant. This result indicates that the moderating effect does not exist; thus, we find no evidence to support Hypothesis 5. It is worthy of note that the coefficients of the VIF in model 2 and model 3 in Table 7 are both below 10, indicating that there is no multicollinearity problem in the hierarchical regression model.

In contrast to the result of Table 7,

Table 8. Moderating effect of internal measures on the relationship between subjective norm and behavioral intention.

Independent Variable	Model 1	Model 2	Model 3
Subjective Norm	0.797 *** (14.53)	0.505 *** (5.36)	0.500 *** (5.30)
Internal Measures		0.350 *** (3.71)	0.313 *** (3.16)
Subjective Norm × Internal Measures			−0.076 (−1.22)
R2	0.636	0.673	0.677
ΔR2	0.636	0.038	0.004
F	211.202	123.657	83.265
ΔF			1.484
VIF		3.27	1.437

*** Present significant at 1%; the parameter of parentheses is t-value.

reports the moderating effect of the internal measures on the relationship between subjective norm and behavioral intention. The finding in model 2 indicates that both subjective norm and internal measures have direct impacts on behavioral intention. Similar to Table 7, the result in model 3 also shows that the moderating effect does not exist. The insignificantly positive result of the interaction effect of subjective norm and internal measures on behavioral intention does not support Hypothesis 6. Again, all of the coefficients of the VIF in Table 8 are smaller than 10. Therefore, there is no multicollinearity problem in the research model.

The moderating effect of internal measures on the relationship between subjective norm and behavioral intention is reported in

Table 9. Moderating effect of internal measures on the relationship between perceived behavioral control and behavioral intention.

Independent Variable	Model 1	Model 2	Model 3
Perceived Behavioral Control	0.810 *** (15.18)	0.528 *** (7.60)	0.519 *** (7.52)
Internal Measures		0.388 ** (5.58)	0.343 *** (4.68)
Perceived Behavioral Control × Internal Measures			−0.098 (−1.76)
R2	0.656	0.727	0.734
ΔR2	0.656	0.071	0.007
F	230.403	159.512	109.223
ΔF			3.090
VIF		2.119	1.378

*** Present significant at 1%; ** Present significant at 5%; the parameter of parentheses is t-value.

. The finding of model 2 reveals that both perceived behavioral control and internal measures have direct effects on behavioral intention. Again, we find no evidence to support that perceived behavioral control and internal measures have moderating effects. Accordingly, our result does not support Hypothesis 7. Similar to the results of Table 7 and Table 8, we also find that no multicollinearity problem exists in the regression model in Table 9 due to the smaller VIF coefficients. In addition, the main findings of this study are illustrated in Figure 2.

5. Discussion

Green finance is one of the most important issues that has been widely discussed in recent years. As aforementioned in this study, research on green finance can be roughly divided into research on the relationship between bank employees and green finance and research on the behavioral intention of bank employees to implement green finance by applying the TBP. In the research on the relationship between bank employees and green finance, previous studies have found that employees’ cognitive and non-cognitive factors affect employees’ green behaviors; moreover, the implementation of bank green finance policies will not only affect employees’ green behaviors, but also green financing (Sabbir and Taufique, 2022; Alshebami 2021; Chen et al. 2022) [10,24,25]. As for the research on the TPB and its application, the model is widely used in research in various fields, and empirical evidence has found that attitude, subjective norm, and perceived behavioral control have a positive impact on behavioral intention (Ajzen and Fishbein 1980; Ajzen 1991; Raza et al. 2019; Aziz et al. 2021; Bouarar et al. 2021; Khalid et al. 2022; Katz et al. 2022) [6,28,29,31,33,34,37]. In particular, in the related studies on behavioral intention and finance, Raza et al. (2019) [31] found that attitude, subjective norm, and perceived behavioral control significantly affect customers’ intention to purchase insurance. Similarly, Khalid et al. (2022) [34] also found that employees’ green attitude, green subjective norm, and green perceived behavioral control have a positive impact on employees’ green behavior intention.

This study also involves the issue of green finance, and explores the behavioral intention of bank employees to implement green finance. Different from the above studies, this study extends the argument of Clark (2022) [4], arguing that internal measures play a decisive role in the process of banks implementing green finance. Moreover, this study incorporates internal measures into the theoretical framework of the TPB to examine the behavioral intention of bank employees to implement green finance. Compared with the previous literature, the originality of this study lies in the integration of internal measures into the TPB model.

Consistent with the empirical findings of Raza et al. (2019) and Khalid et al. (2022) [31,34], this study finds that both attitude and perceived behavioral control significantly and positively affect the behavioral intention of bank employees to implement green finance. However, subjective norm and internal measures have no significant or positive impact on the behavioral intention of bank employees when implementing green finance. The coefficient of the internal measures is positive, while its p-value is 0.112. This weak evidence suggests that we do not have enough evidence to support the claim that internal measures influence behavioral intention. However, the results of this study are still of great value and can be used as academic and practical references.

6. Managerial Implications

6.1. Theoretical Implications

In the past, most of the research has highlighted the discussion of the TPB, but there have been no examples of applying it to the emerging green finance implementation field. By applying and extending the TPB, this study not only takes the original model into account, but also incorporates internal measures into the research model. In addition, the interaction effect is further explored using internal measures as an intermediary variable. Because the items of this research questionnaire were designed by interviewing current bank employees and combining theoretical foundations, the implications of the empirical analysis results are both theoretical and practical. The empirical results of this study can provide the banking industry with a reference to help improve the comprehensive thinking about employees’ behavioral intentions in terms of the implementation of green finance.

As mentioned, Alshebami (2021) [10] found that the bank’s policy of implementing green finance will directly affect the green behavior of its employees, and because banks can enhance their green image when implementing green finance, banks should spread green awareness among employees, customers, and other stakeholders. In addition, the CBRC (Taiwan) (2021) [40] also indicated that in the process of promoting sustainable financial business, financial institutions will encounter obstacles from internal measures such as internal communication, organizational transformation, and education and training. Accordingly, this study proposes the following recommendations for management.

(i)

Attitude and perceived behavioral control are significantly and positively related to the behavioral intention of bank employees to implement green finance. With the rise in green finance, the banking industry should be committed to improving the positive attitudes of employees toward the implementation of green finance, eliminating the pressure that comes from supervisors, peers, and customers, and making employees aware that banks can provide sufficient resources. This can help all stakeholders to implement green finance and further help to reduce the obstacles expected by employees. In addition, for female, senior, and new junior employees, as well as older and younger employees, banks should make more effort to establish their attitudes, subjective norms, and perceived behavioral control when implementing green finance.

(ii)

It is recommended that banks should establish ESG executive officers, specify incentive measures, strengthen cross-departmental coordination and cooperation, and enhance ESG education and training for all employees. In addition, in terms of relevant internal measures, the banking industry must still consider the strength of the implementation and establish the psychological boundaries of its employees.

6.2. Practical Implications

Like other companies, the purpose of operating banks is to generate profits. However, banks in Taiwan are chartered businesses, and banking operations are regulated by strict regulations and are usually conservative. Consequently, banks are slow to embrace new changes or new innovation. Previous studies indicate that integrating innovative ideas and products into operations will help improve the company’s economic performance, market position, and financial performance, and even achieve the goal of sustainable development (Alshebami 2023; Asadi et al., 2020; Jiang et al., 2018; Alshebami 2021; Muangmee et al., 2021; Battisti and Perry 2011; Green and Inman 2005; Khan and Johl 2021) [7,8,9,10,11,12,13,14]. In short, from the perspective of banks, how to quickly respond to changes in the external environment, invent innovative green products or green services and provide them to those in need in the market, increase the bank’s profitability, assist enterprises in transformation, and then promote sustainable development policy are very important issues.

7. Conclusions and Research Limitations

7.1. Conclusions

Green finance helps promote a country’s sustainable development policy. In view of the importance of green finance, the aim of this study was to discuss the impact of attitude, subjective norm, and perceived behavioral control on the behavioral intentions of bank employees to implement green finance. In particular, different from previous studies, the originality of this study lies in the integration of internal measures into the TPB model to explore whether internal measures have moderating effects on bank employees’ behavioral intentions when they implement green finance.

According to the reliability analysis results, the Cronbach’s α of all constructs of the questionnaire designed in this study was as high as 0.979 and the Cronbach’s α of each construct exceeded 0.90, except for perceived behavioral control (0.890). This result indicates that the questionnaire designed in this study had quite good reliability. Supporting Hypothesis 1 to Hypothesis 4, this study found that attitude, subjective norm, perceived behavioral control, and internal measures have significant and positive impacts on the behavioral intention of bank employees when implementing green finance.

This study also found that the theoretical model of planned behavior has the effect of predicting behavioral intention. In addition to subjective norm, attitude and perceived behavioral control are significantly and positively related to behavioral intention. Accordingly, more attention should be paid to the attitude and perceived behavioral control of bank employees when implementing green finance. Similarly, after considering internal measures within the TPB, this study also found that even though subjective norm and internal measures were not significantly positive, the TPB also had the effect of predicting behavioral intention, and can slightly improve the predictive ability.

In terms of the moderating effect of internal measures, this study found that the moderating effects of attitude and internal measures, the moderating effects of subjective norm and internal measures, and the moderating effects of perceived behavioral control and internal measures did not exist. Therefore, this study found no evidence to support Hypotheses 5 to 7; that is, the interaction effects of internal measures and attitude, subjective norm, and perceived behavior as a control do not have positive moderating effects on behavioral intention.

7.2. Research Limitations

Because of the limitations of time, manpower, and funds, this study was unable to conduct large-scale and in-depth research, which led to the following three limitations of this study. First of all, the objects of this study were current bank employees, which meant that the data sampling was not wide enough. Therefore, it is necessary to be careful when making inferences from this study. Second, the factors that affect bank employees to implement green finance are very complex and diverse. This study only relied on the theoretical basis and on collecting research data through the use of questionnaires, ignoring and failing to discuss other possible influencing factors. Finally, this study used questionnaires to collect the primary data. However, factors such as the subjects’ understanding of the items, subjective opinions, or self-reservation may have caused research measurement errors.