The nexus of digital financial inclusion, digital financial literacy and demographic factors: lesson from Indonesia

Figures & data

Table 1. The instruments.

Variable	Indicators	Scale
Digital Financial Inclusion (Naumenkova et al., 2019)	Used a mobile phone or the internet to access an account Used e-debet, e-credit, mobile/internet banking, e-money, e-wallet and internet to pay bills or make a payment Used e-debet, e-credit, mobile/internet banking, e-money, e-wallet and internet to buy something online Used a debit card to withdraw fund Used fintech to make an investment Used fintech to make an insurance Used an account to receive income/wages/government payments Used an account to pay utility bills Used a mobile phone or the internet to fund transfer	1 = Yes 0 = No
Digital Financial Literacy (Setiawan et al., 2020)	I have a good understanding of digital payment products (such as E-Debit, E-Credit, E-Money, Mobile/Internet banking, E-wallet). I have a good understanding of product digital asset management (such as Tanamduit, Finansialku, Bareksa). I have a good understanding of digital alternatives (such as Investeree, Kreditku, etc.). I have a good understanding of digital insurance (such as W+, Cekpremi, Rajapremi). I have a good understanding of customer rights and protectionas well as the procedure to complain about the service from digital financial providers. I have experience in using the product and service of fintech for digital payment (such as OVO, Gopay, LinkAja). I have experience in using the product and service of fintech for financing (loan) and investment (such as CoinWorks, Investree, Modalku, Amarta). I have experience in using the product and service of fintech for asset management (such as Bareksa, tanamduit and finansialku). I aware about the potential of financial risk in using digital financial provider or fintech, such as the legality of the fintech provider, interest rate and transaction fee. I have a good capability in managing financial activities through a digital platform such as managing the cost of using digital financial transactions. I have a good control on financial activities using digital platforms by evaluating the spending in the platforms.	4 = Strongly Agree 3 = Agree 2 = Disagree 1 = Strongly Disagree

Table 2. The measurement of variables.

Variables	Category	Coding	n
Gender	Male	1	69
	Female	0	91
Age	20- to 29-year old	1	15
	30- to 39-year old	2	25
	40- to 49-year old	3	43
	50- to 59-year old	4	69
	More than 60	5	8
Occupation	Entrepreneur	1	22
	Other occupations	0	138
Marital status	Married	1	24
	Single/divorce	0	136
Income	Less than or equal to 5 million rupiah	1	24
	More than 5 to 10 million rupiah	2	70
	More than 10 to 15 million rupiah	3	28
	More than 15 to 20 million rupiah	4	14
	More than 20 million rupiah	5	24
DFL	High DFL	1 if total score is equal to or more than median	77
	Low DFL	0 if total score is less than median	83
DFI	Digital financial inclusion	1 if total score is equal to or more than median	25
	Digital financial exclusion	0 if total score is less than median	135

Table 3. The value of -2 log likelihood block number = 0.

Iteration	−2 Log likelihood	Coefficient
		Constant
Step 0 1	140.882	1.375
2	138.705	1.658
3	138.688	1.686
4	138.688	1.686

Source: authors analysis.

Table 5. Model summary.

Step	−2 Log likelihood	Cox & Snell R square	Nagelkerke R square
1	104.666	0.192	0.330

Source: authors analysis.

Table 4. Hosmer and Lemeshow test.

	Chi-square	df	Sig	Result
Step 1	9.908	8	0.272	The model is fit

Source: authors analysis.

Table 6. The partial effect of independent variables on DFI.

Step 1	B	SE	Wald	df	Sig	Exp(B)	95% C.I.for EXP(B)
							Lower	Upper
Gender	0.556	0.531	1.096	1	0.295	1.744	0.616	4.939
Age	−1.348	0.383	12.395	1	0.000	0.260	0.123	0.550
Marital status	−0.049	0.977	0.003	1	0.960	0.952	0.140	6.464
Income	0.501	0.235	4.540	1	0.033	1.651	1.041	2.617
Occupation	−1.208	0.677	3.184	1	0.074	0.299	0.079	1.126
DFL	1.051	0.544	3.738	1	0.053	2.861	0.986	8.306
Constant	4.788	1.693	7.994	1	0.005	120.064

Source: authors analysis.

Table 7. Classification matrix.

Step 1	Observed	Predicted
		DFI		Percentage correct
		Digital financial exclusion	Digital financial inclusion
DFI	Digital financial exclusion	5	20	20
	Digital financial inclusion	5	130	96.3
	Overall percentage			84.4

Source: authors analysis.

Naumenkova, S., Mishchenko, S., & Dorofeiev, D. (2019). Digital financial inclusion: Evidence from Ukraine. Investment Management and Financial Innovations, 16(3), 194–205. https://doi.org/10.21511/imfi.16(3).2019.18

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Setiawan, M., Effendi, N., Santoso, T., Dewi, V. I., & Sapulette, M. S. (2020). Digital financial literacy, current behavior of saving and spending and its future foresight. Economics of Innovation and New Technology, 31(4), 320–338. https://doi.org/10.1080/10438599.2020.1799142

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