Do financial consultants exert a moderating effect on savings behavior?A study on the Indian rural population

Figures & data

Figure 1. The research framework.

Source: Author’s own, Note: SPO: Small Savings Scheme; FLB: Financial Literacy and Behavior; FC: Financial Consultant

Table 1. Support for scale items and theoretical background

Item code and Description of item	Theoretical background and Support
Construct: Savings/Investment Habit (SH) S1: Social security and social relaxation intention persuade savings habit. S2: Economic benefit fulfillment behavior motivates savings habit. S3: Other need fulfillment behavior encourages savings habits.	Wang et al., 2021; Chawla & Joshi, 2021; Ganapathi, 2010; García-Santillán et al. (2021);
Financial Literacy and Behavior (FLB) F1: Financial literacy and family financial behavior F2: Financial literacy and financial behavior of peer groups. F3: Family financial socialization and financial behavior of people in the financial institutions.	Steinhart & Jiang, 2019; Roa et al., 2019;
Construct: Financial consultant (FC) C1: Postal agents influence savings habits. C2: Postal employees guide savings habits. C3: Social relations persuade savings habits.	Lewellen et al., 1977; Fromlet, 2001; Shiller Robert, 2000; Shiller, 2014
Construct: Small Savings Scheme (SPO) P1: Secured and better return traits of postal savings scheme motivate me to save. P2: Simplified procedure and reliability of the scheme attract me to save. P3: The structure of the postal industry motivates my purchase decision. P4: The maturity period of the scheme motivates my purchase decision.	Gavini & Athma, 1999; Singh, 2002; NCAER, (2017-18) Prajapati et al., 2021; Chopra et al., 2021

Source: Authors’ own

Table 2. Factor loadings

Factor loadings
Items loaded	1	2	3	4
S1 S2 S3	0.788 0.827 0.641	0.732 0.781 0.685
F1 F2 F3
C1 C2 C3			0.688 0.686 0.721
P1 P2 P3 P4				0.788 0.817 0.795 0.751

Source: Authors’ Own

Figure 2. Measurement model.

Source: Authors’ own

Table 3. Measurement model fit indices

Index name	Index value of MM*	Acceptable values for good model fit **
X^2/df	2.169	< 5.00
GIF	0. 931	> 0.90
NFI	0. 928	> 0.90
CFI	0. 959	> 0.90
TLI	0. 942	> 0.90
AGFI	0. 901	> 0.90
RMSEA	0. 071	< 0.08
Model-fit	Good

Source: Authors’ own

Notes: (a) * Measurement model, (b) **Hair et al., 2010

Table 4. Test of convergent validity of measurement model

Factor and items	Standardized factor loadings*	Cronbach’s α	AVE	CR
Construct: Savings/Investment Habit (SH)
S1: Social security and social relaxation intention persuade my savings habit.	0.723	0.835	0.678	0.862
S2: Economic benefit fulfillment behavior motivates my savings habit.	0.775
S3: Other need fulfillment behavior encourages my savings habit.	0.924
Financial Literacy and Behavior (FLB)
F1: Financial literacy and family financial behavior	0.809	0.711	0.605	0.821
F2: Financial literacy and financial behavior of peer groups.	0.725
F3: Family financial socialization and financial behavior of people in the financial institutions.	0.797
Construct: Financial Consultant (FC)
C1: Postal agents influence savings habits.	0.739	0.778	0.644	0.844
C2: Postal employees guide savings habits.	0.821
C3: Social relations persuade savings habits.	0.843
Construct: Small Savings Scheme (SPO)
P1: Secured and better return traits of postal savings scheme motivate me to save.	0.771
P2: Simplified procedure and reliability of the scheme attract me to save.	0.813	0.815	0.639	0.876
P3: The structure of the postal industry motivates my purchase decision.	0.829
P4: The maturity period of the scheme motivates my purchase decision.	0.784

Source: Authors’ own

Table 5. Discriminant validity test of measurement model

Construct	SH	FLB	FC	SPO
SH	0.823408
FLB	0.729	0.777817
FC	0.708	0.718	0.802496
SPO	0.698	0.711	0.664	0.799375

Source: Authors’ own

Figure 3. Structural model.

Source: Authors’ own

Table 6. Structural Model Fit Indices

Index name	Index value	Acceptable values for good model fit *
X^2/df	1.631	< 5.00
GFI	0. 998	> 0.90
NFI	0. 997	> 0.90
CFI	0. 999	> 0.90
TLI	0. 989	> 0.90
AGFI	0. 949	> 0.90
RMSEA	0. 052	< 0.08
Model-fit	Good

Note: (a) *Hair et al. (2010)

Source: Authors’ own

Table 7. Path details of the structural model

	Estimate	S.E.	P-value	Observation/Effect	Effect Size	Remarks
SH←SPO	0.513	0.243	0.001*	Effect exist	Small (0.0761)**	Support: H1 & H2
SH←FC	0.736	0.090	0.001*	Effect exist	Medium (0.1714) **
SH←FLB	0.695	0.085	0.001*	Moderation Effect exist	Small (0.0224) **
SH←SPO_FC	0.283	0. 064	0.001*	Moderation Effect exist	Medium (0.2934) **	Support: H3
SH←FLB_FC	0.667	0.075	0.001*	Moderation Effect exist	Medium (0.2975) **

Source: Authors’ own

Note: (a)*p < 0.05,

(b) SPO = Small Savings Scheme, FC = Financial Consultants, SH = Savings Habit, and Financial Consultant = FC

(c) **Aiken, L. S., & West, S. G. (1991)

Table A1. Total Variance Explained

Component	Initial Eigenvalues			Extraction Sums of Squared Loadings
	Total	% of Variance	Cumulative %	Total	% of Variance	Cumulative %
1	5.378	41.369	41.369	5.378	41.369	41.369
2	1.483	11.406	52.776
3	1.104	8.495	61.271
4	.978	7.527	68.798
5	.833	6.407	75.205
6	.672	5.166	80.371
7	.576	4.435	84.806
8	.506	3.894	88.700
9	.395	3.039	91.739
10	.341	2.621	94.360
11	.286	2.200	96.560
12	.260	2.003	98.563
13	.187	1.437	100.000

Extraction Method: Principal Component Analysis

Source: Author’s Own

Table A2. KMO and Bartlett’s Test

Kaiser–Meyer–Olkin Measure of Sampling Adequacy.		.872
Bartlett’s Test of Sphericity	Approx. Chi-Square	1618.925
	df	78
	Sig.	.000

Source: Author’s Own

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