Role of Environmental Sustainability, Psychological and Managerial Supports for Determining Bankers’ Green Banking Usage Behavior: An Integrated Framework

Figures & data

Table 1 The Summary of Relevant Green Banking Literature

SL NO.	Author (s) and Year	Theoretical Basis	Sample Size, Type, and Country, Data Collection Tool, Unit of Analysis)	Outcome Variable and Context	Study Variables	Significant Results
01	Chen et al (2022)^Citation3	Legitimacy theory	322, banking employees of private commercial banks (PCBs), Bangladesh, cross-sectional sample, IBM SPSS (version 22.0) and AMOS (version 23.0)	Bank Environmental Performance (BEP)	Banks Employee Related Practices, Banks Operation Related Practices, Banks Customer Related Practices, Banks Policy Related Practices, Green Financing, Bank Environmental Performance (BEP)	Direct predictors of Green Financing: Banks Employee Related Practices (+), Banks Operation Related Practices (+), Banks Customer Related Practices (-), Banks Policy Related Practices (+) Direct predictors of Bank Environmental Performance (BEP): Green Financing (+), Banks Employee Related Practices (-), Banks Operation Related Practices (+), Banks Customer Related Practices (-), Banks Policy Related Practices (+) Demographics: Female vs males
02	Ding et al (2022)^Citation4	Organizational Learning Theory, Theory of Reasonable Action (TRA), Self-Efficacy Theory	65 teams that belong to green finance industries, China, field survey and online questionnaires, SPSS22.0	Team Effectiveness	Innovative Climate, Knowledge Sharing, Knowledge Heterogeneity, Team Effectiveness	Direct predictors of Knowledge Sharing: Innovative Climate (+) Direct predictors of Team Effectiveness: Knowledge Sharing (+), Innovative Climate (+) Indirect predictors of Team Effectiveness: Innovative Climate through Knowledge Sharing (+) Moderating role of Knowledge Heterogeneity: Between Knowledge Sharing and Team Effectiveness (+) Demographics: Female vs males
03	Desalegn et al (2022)^Citation17		Explanatory research design and a Quantitative research approach, Hungary, voluntary questionnaire survey, purposive sampling techniques, Vector Autoregressive Analysis	Green Finance	Broad money supply, lending Investment rate, Outward foreign direct investment, Inward foreign direct investment, Domestic Investment, Green House Gas	Direct predictors of Green Finance: lending Investment rate (+), Broad money supply (+), Inward foreign direct investment (+), Outward foreign direct investment (+), Domestic Investment (+), Green House Gas (+)
04	Li & Yang (2022)^Citation18		31 provinces of China, Regression	Corporate Technological innovation	Green finance, Corporate Technological innovation, CSR,	Direct predictors of Corporate Technological innovation: Green finance (+), CSR (+) Indirect predictors of Corporate Technological innovation: Green finance Through CSR (+)
05	Fang & Shao et al (2022)^Citation7		re-measurement of the green finance, China, Durbin model	Green Technology Innovation	Command and control environmental regulation, Market incentive environmental regulation, Green finance,	Direct predictors of Green Technology Innovation: Command and control environmental regulation (+), Market incentive environmental regulation (+), Green finance (+), Moderating role of Green finance: Between Command and control environmental regulation and Green Technology Innovation (+); Between Market incentive environmental regulation and Green Technology Innovation (+) Direct predictors of Neighborhood Green Technology Innovation: “Command and control” environmental regulation and “market incentive” environmental regulation (+); Green finance (+)
06	Guang-Wen & Siddik (2022)^Citation13	Legitimacy Theory	388, Bankers of private commercial banks (PCBs), Bangladesh, Non-Probabilistic convenience sampling method, AMOS	Environmental Performance of Bankers	Economic, Social, Environmental, CSR Activities, Environmental Performance	Direct predictors of Environmental Performance: CSR Activities (+), Economic (+), Social (+), Environmental (+) Demographics: Female vs males
07	Yan et al (2022)^Citation12		351 employees of banking institutions, Bangladesh, convenience sampling method, IBM’s SPSS	Sustainability Performance (SP) of employees	Fintech Adoption, Green Finance, Green Innovation	Direct predictors of Sustainability Performance: Fintech Adoption (+), Green Finance (+), Green Innovation (+) Direct predictors of Green Finance: Fintech Adoption (+) Direct predictors of Green Innovation: Fintech Adoption (+) Indirect predictors of Sustainability Performance: Fintech Adoption through Green Finance (+), Fintech Adoption through Green Innovation (+) Demographics: Female vs males
08	Ye et al (2022)^Citation19		30 provincial administrative regions, China	Green Development	Green Finance Green Technological Innovation, Special Interaction Effect, Green Development	Direct predictors of Green Development: Green Finance (+), Green Technological Innovation (+), Special Interaction Effect (+)
09	Zeng et al (2022)^Citation96		639, Enterprises, China,	Haze Pollution	Green Finance, Haze Pollution, Enterprise Innovation Output, Enterprise Innovation Input,	Direct predictors of Haze Pollution: Green Finance (+) Direct predictors of Enterprise Innovation Output: Green Finance (+) Direct predictors of Enterprise Innovation Input: Green Finance (+) Indirect predictors of Haze Pollution: Green Finance through Enterprise Innovation Output (+), Green Finance through Enterprise Innovation Input (-) Demographics: Enterprises
10	Zhang et al (2022)^Citation6		352, Employee of Private commercial banks, Bangladesh, convenience sampling method, SPSS 22.0 and AMOS 23.0	Bank’s environmental performance of Employee of Private commercial banks	Green banking activities, Sources of green financing, Bank’s environmental performance	Direct predictors of Bank’s environmental performance: Green banking activities (+) Direct predictors of Sources of green financing: Green banking activities (+) Direct predictors of Bank’s environmental performance: Sources of green financing (+) Indirect predictors of Bank’s environmental performance: Green banking activities through Sources of green financing (+) Demographics: Female vs males
11	Wang et al (2021)^Citation97		30 provincial panel, China, Regression	Green development	Green finance pilot Zone, Industrial structural upgrade, Technological innovation ability	Direct predictors of Green development: Green finance pilot Zone (+), Industrial structural upgrade (+) Direct predictors of Industrial structural upgrade: Green finance pilot Zone (+) Direct predictors of Technological innovation ability: Green finance pilot Zone (+), Green development (+)
12	Rehman et al (2021)^Citation1	Socially Responsible Investment (SRI)	200 employees of retail banks at managerial level, Pakistan, Survey questionnaire	Green banking practices of employees of retail banks at managerial level	Policy, Operations, Investments, Green banking practices	Direct predictors of Green banking practices adoption: Bank polices for green environment (+) Direct predictors of bank daily operations: Adoption of green banking practices (+) Direct predictors of Green banking practices: Banks investment decision (+) Demographics: Female vs males
13	Zheng et al (2021a)^Citation98		296, Bankers of Private commercial banks, Bangladesh, Nonprobability sampling method, SPSS 22.0 and AMOS 23.0.	Bankers’ perception of Green Finance	Economic Dimension, Social Dimension, Environmental Dimension, Sources of Group Financing, Bankers’ perception of Green Finance	Direct predictors of Economic Dimension: Bankers’ perception of Green Finance (+) Direct predictors of Social Dimension: Bankers’ perception of Green Finance (+) Direct predictors of Environmental Dimension: Bankers’ perception of Green Finance (+) Direct predictors of Sources of Group Financing: Bankers’ perception of Green Finance (+) Demographics: Female vs males
14	Zheng et al (2021b)^Citation99		302, Bankers, Bangladesh, convenience sampling (non-probabilistic) method, SPSS 22.0 and AMOS 23.0	Sustainability Performance of Bankers	Economic Dimensions, Social Dimensions, Environmental Dimensions, Sustainability Performance	Direct predictors of Social Dimensions: Economic Dimensions (+) Direct predictors of Environmental Dimensions: Economic Dimensions (+), Social Dimensions (+) Direct predictors of Sustainability Performance: Economic Dimensions (+), Social Dimensions (+), Environmental Dimensions (+) Demographics: Female vs males
15	Taneja & Ali (2020)^Citation22	Theory of Planned Behavior	440 respondents who use at least one of the various digital banking services, India, cross-sectional sample, self-administered questionnaires	Behavioral Intention	Trust, attitude, Perceived Environmental Outcomes, Environmental Consciousness, Perceived Behavioral Control, Subjective Norms, Behavioral Intention	Direct predictors of Behavioral Intention: Attitude (+), Subjective Norms (+), Perceived Behavioral Control (+), Environmental Consciousness (-), Perceived Environmental Outcomes (+), Direct predictors of Attitude: Trust (+), Environmental Consciousness (+) Direct predictors of Perceived Environmental Outcomes: Environmental Consciousness (+) Direct predictors of Trust: Perceived Environmental Outcomes (+) Demographics: Female vs males
16	Burhanudin et al (2020)^Citation21	Self-regulation Theory & Theory of Planned Behavior	313 respondents in commercial banking customers, Indonesia,	Intention to use green Banking Services	Guilt, Attitude towards Green Banking, Perceived Consumer Effectiveness, Negative Word-of-Mouth, Intention to use green Banking Services	Direct predictors of Attitude towards Green Banking: Guilt (-) Direct predictors of Perceived Consumer Effectiveness: Guilt (+) Direct predictors of Perceived Negative Word-of-Mouth: Guilt (+), Perceived Consumer Effectiveness (+) Direct predictors of Attitude towards Green Banking: Perceived Consumer Effectiveness (+) Direct predictors of Intention to use green Banking Services: Attitude towards Green Banking (-), Perceived Consumer Effectiveness (-), Negative Word-of-Mouth (+) Indirect predictors of Intention to use green Banking Services: Perceived Consumer Effectiveness through Attitude towards Green Banking (-); Negative Word-of-Mouth through Perceived Consumer Effectiveness (+) Demographics: Female vs males
17	Sun et al (2020)^Citation11	Theory Of Social Identity	489, 18 years old with a bank account, Pakistan, Multi-stage sampling method, Correlations	Green Customer Loyalty	Corporate Social Responsibility, Green Banking, Co-creation, Green Consumer Loyalty	Direct predictors of Co-creation: Corporate Social Responsibility (+) Direct predictors of Consumer Loyalty: Co-creation (+), Corporate Social Responsibility (+) Indirect predictors of Consumer Loyalty: Corporate Social Responsibility through Co-creation (+) Moderating Role of Green Banking: The indirect relationship of CSR and green consumer loyalty through co-creation (+) Demographics: Female vs males
18	Ibe-enwo et al (2019)^Citation20	Socially Responsible Investment (SRI)	850 customers of the retail banking sector, North Cyprus, Turkey, quantitative survey	Bank Loyalty of customers of the retail banking sector	Green Banking practice, Green Image, Bank Trust, Bank Loyalty	Direct predictors of Green Image: Green Banking practice (+) Direct predictors of Bank Trust: Green Banking practice (+), Green Image (+) Direct predictors of Bank Loyalty: Green Banking practice (+), Green Image 5(+) Bank Trust (-) Indirect predictors of Bank Loyalty: Green Banking practice through Green Image (+); Green Banking practice through Green Trust (-) Demographics: Female vs males
19	Bose et al (2017)^Citation23	Institutional Theory	205 Bank’s Annual Report, Bangladesh,	Green banking disclosure index (GBDI)	Issuance of the central bank’s guidelines, Imitation behavior over the years, Routine process over time, Board size, Independence, Institutional ownership	Direct predictors of Green banking disclosure: Issuance of the central bank’s Guidelines (+), Board size (+), Independence (+), Institutional ownership (+) Direct predictors of Imitation behavior over the years: Green banking disclosure (+) Direct predictors of Routine process over time: Green banking disclosure (+)
20	Xu et al (2020)^Citation100	Neoclassical Theory	62,051, Comprehensive Meta-Analysis Software (CMA) 2.0	Enterprise Green Performance	Green finance, Green credit, Green investment, Green subsidy, Green bond, Environmental Performance, Innovation Performance, Sustainability Performance	Direct predictors of Enterprise Green Performance: Green finance (+), Green credit (+), Green investment (+), Green subsidy (+), Green bond (+) Direct predictors of Environmental Performance: Green finance (+) Direct predictors of Performance Performance: Green finance (+) Direct predictors of Sustainability Performance: Green finance (+) Moderating role of Profitability of enterprise: Between Green Finance and Green Performance (-) Moderating role of type of enterprises: Between Green Finance and Green Performance (+) Moderating role of Region: Between Green Finance and Green Performance (+)

Figure 1 The conceptual framework.

Table 2 Demographic Profile of the Respondents

Variables	Number	Percentage
Gender
Male	223	0.609
Female	143	0.391
Age
18–25	88	0.240
25–40	143	0.391
40–55	40	0.109
Above 55	95	0.260
Working place
State-owned commercial banks (SOCBs)	117	0.320
Specialized development banks (SDBs)	120	0.328
Private commercial banks (PCBs)	70	0.191
Financial institutions (FIs)	59	0.161
Designation
Branch Manager	81	0.221
Senior Officer	121	0.331
Junior Officers	120	0.328
Other	44	0.120
Geographical Region (Working Area)
Capital City	187	0.511
Divisional Level	66	0.180
District Level	62	0.169
Upozilla	51	0.139

Table 3 Construct Reliability (roh_A, CR, and Cronbach Alpha), AVE, and Cross Loading

Constructs	Items	Loadings	Cranach’s Alpha	ro_A	CR	AVE
Subjective Norms (SN)	SN1	0.701	0.772	0.801	0.867	0.622
	SN2	0.782
	SN3	0.801
	SN4	0.862
Perceived Cognitive Efforts (PCE)	PCE1	0.783	0.809	0.882	0.870	0.626
	PCE2	0.819
	PCE3	0.798
	PCE4	0.763
Environmental Sustainability (ES)	ES1	0.750	0.736	0.787	0.846	0.580
	ES2	0.735
	ES3	0.816
	ES4	0.742
Management Supports (MS)	MS1	0.700	0.764	0.821	0.836	0.505
	MS2	0.701
	MS3	0.729
	MS4	0.716
	MS5	0.708
Attitudes toward Green Banking (ATT)	ATT1	0.813	0.768	0.865	0.806	0.581
	ATT2	0.743
	ATT3	0.729
Green Banking Use Behavior (GBUB)	CB1	0.793	0.793	0.850	0.882	0.651
	CB2	0.774
	CB3	0.834
	CB4	0.825

Table 4 Fornell and Lacker Criteria

	SN	PCE	ES	MS	ATT	GBUB
SN	0.789
PCE	0.062	0.791
ES	0.162	0.601	0.762
MS	0.332	0.172	0.352	0.710
ATT	0.101	0.196	0.408	0.046	0.762
GBUB	0.502	0.301	0.288	0.095	0.357	0.807
Eigenvalues	8.35	5.29	4.05	2.87	2.29	1.63
% of Variance	28.56%	18.12%	13.87%	9.81%	7.85%	5.59%
Cumulative %	28.56%	46.68%	60.55%	70.36%	78.21%	83.80%

Note: The italic bold value in the diagonal elements stands for square root of AVE.

Table 5 Heterotrait-Monotrait Ratio (HTMT)

	SN	PCE	ES	MS	ATT	GBUB
SN	–
PCE	0.275	–
ES	0.331	0.234	–
MS	0.234	0.192	0.239	–
ATT	0.531	0.350	0.330	0.107	–
GBUB	0.403	0.192	0.307	0.270	0.246	–

Table 6 Path Coefficient and Hypotheses Test Results

Hypotheses		Path Coefficient	Standard Deviation	t-Statistics	P values	VIF	f^2	Remarks
H1a	SN -> ATT	0.309	0.071	4.352	0.000	2.273	2.001	supported
H1b	SN -> GBUB	0.281	0.061	4.607	0.000	1.238	0.208	supported
H2a	PCE -> ATT	0.401	0.113	3.549	0.000	1.301	0.403	Supported
H2b	PCE -> GBUB	0.103	0.051	2.020	0.002	1.002	0.231	Supported
H3a	ES -> ATT	0.278	0.101	2.752	0.001	1.872	0.087	supported
H3b	ES -> GBUB	0.503	0.135	3.726	0.001	2.091	0.119	supported
H4a	MS -> ATT	0.291	0.067	4.343	0.000	2.201	0.205	supported
H4b	MS -> GBUB	0.231	0.162	1.426	0.071	1.761	0.001	Not supported
H5	ATT-> GBUB	0.602	0.109	5.523	0.015	1.871	0.430	supported

Notes: N.B. Coefficient of determinations (R²), ATT = 0.709, GBUB = 0.761; Blindfolding-Based Cross-Validated Redundancy (Q2), ATT = 0.504, GBUB = 0.602.

Figure 2 Structural Model of the Study.

Table 7 Mediated Model

Indirect Relationship		b	Standard Error	t Statistic	Sobel Test (Z Value)	CI (95%)	P values	Remarks
H6a	SN->ATT-> GBUB	0.186	0.045	4.133	3.418	(0.028, 0.036)	0.000	Significant
H6b	PCE-> ATT-> GBUB	0.241	0.091	2.648	2.985	(0.038, 0.022)	0.002	Significant
H6c	ES -> ATT-> GBUB	0.167	0.103	1.621	1.555	(0.043, 0.042)	0.119	Insignificant
H6d	MS -> ATT-> GBUB	0.175	0.073	2.397	3.414	(0.019, 0.021)	0.000	Significant

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