Adoption of FinTech and Future Perspective: An Empirical Evidence from Bahrain on Digital Wallets

Relying on the entered data, we analyzed the data included in the questionnaire by using the SPSS program for statistical analysis
• Explanation of the theoretical framework:
The following scheme was relied upon to know the continuity rate of e-wallets in Bahrain, where the questionnaire was divided into two parts, the economic benefit and the perceived risks, each of which depends on a set of factors identified in the appropriate questionnaire.
We analyzed the appropriate data and produced it in an easy-to-read visual way, unlike the entered numerical data, which is usually difficult to understand.
• Data analysis
First, we analyze the statistics to find out the most used electronic wallet:
DigitalWallet
Frequency Percent Valid Percent Cumulative Percent
Valid BenefitPay 342 87.2 87.2 87.2
bWallet 35 8.9 8.9 96.2
MaxWallet 2 .5 .5 96.7
VIVA Cash 13 3.3 3.3 100.0
Total 392 100.0 100.0

We find that the most used digital wallet is BenefitPay
We can also know the time period that customers used and the number of times daily, through the following charts:

Period
Frequency Percent Valid Percent Cumulative Percent
Valid Less than 1 year 223 56.9 56.9 56.9
Between 1 to 2 years 148 37.8 37.8 94.6
Between 2 to 5 years 16 4.1 4.1 98.7
More than 5 years 5 1.3 1.3 100.0
Total 392 100.0 100.0

We find that most users have used wallets for less than a year, and a large part of them have used them for a period between one and two years, and a small number of them have used them during large periods (more than two years)
.
While the average daily use, we find through the following graph:

In the figure below, we analyzed the data based on the electronic wallet, where we find that the period of use for users of the BenefitPay wallet
Likewise for the wallet

We can find the economic benefit based on the following chart:
The percentage of respondents to the first question was as follows:

Where we find a closeness of proportions, but the highest percentage was for those who agree strongly, as well as for those who are neutral.
For a smooth transaction, the following chart shows customers’ answers to the questions asked:
The answers to the above questions were, in order:

The tangible benefit is based on 3 values: economic benefit, convenience, and comfort.
Therefore, we need to find a statistic for the previous three models to find out the tangible benefit.
In the following, a statistical analysis of a questionnaire regarding tangible interest, we find with the shown fees the tangible interest rate
In the order given in the questionnaire (PB1,PB2,PB3,PB4)

Where we find that the tangible benefit depends on several values, and taking into account the analysis of the following statistics and successive statistics, the previous analysis was found

We also find that the perceived risks can be analyzed as follows:

As for demographic statistics and their link to behavioral statistics, we find the following:
Gender * DigitalWallet Crosstabulation
Count
DigitalWallet Total
BenefitPay bWallet MaxWallet VIVA Cash
Gender Male 229 29 2 11 271
Female 113 6 0 2 121
Total 342 35 2 13 392

We sorted digital wallets by user gender, and separated them by nationality, finding:
Nationality * DigitalWallet Crosstabulation
Count
DigitalWallet Total
BenefitPay bWallet MaxWallet VIVA Cash
Nationality Bahraini 333 28 2 11 374
Non-Bahraini 9 7 0 2 18
Total 342 35 2 13 392

Well, does age affect the number of period of use?
Let’s see the stats
Age * Period Crosstabulation
Count
Period Total
Less than 1 year Between 1 to 2 years Between 2 to 5 years More than 5 years
Age 18 – 25 years 56 26 2 0 84
26 – 30 years 51 42 6 1 100
31 – 40 years 68 55 4 2 129
41 – 50 years 45 20 3 2 70
Above 50 years 3 5 1 0 9
Total 223 148 16 5 392

We can see that age does not affect the period of use, so let’s see the types of wallets depending on the degree of education and work for the client:
We combined a number of factors into one table

DigitalWallet * Education * Profession Crosstabulation
Count
Profession Education Total
High school Graduate Postgraduate
Govt Employee DigitalWallet BenefitPay 43 38 81
bWallet 6 7 13
VIVA Cash 4 2 6
Total 53 47 100
Private Employee DigitalWallet BenefitPay 4 91 49 144
bWallet 0 12 4 16
VIVA Cash 0 5 0 5
Total 4 108 53 165
Self Employed DigitalWallet BenefitPay 2 13 7 22
MaxWallet 0 0 2 2
Total 2 13 9 24
Student DigitalWallet BenefitPay 12 6 7 25
bWallet 0 2 0 2
Total 12 8 7 27
Housewife DigitalWallet BenefitPay 2 10 1 13
VIVA Cash 0 0 2 2
Total 2 10 3 15
Unemployed DigitalWallet BenefitPay 1 23 7 31
bWallet 2 0 0 2
Total 3 23 7 33
Retired DigitalWallet BenefitPay 4 5 17 26
bWallet 0 2 0 2
Total 4 7 17 28
Total DigitalWallet BenefitPay 25 191 126 342
bWallet 2 22 11 35
MaxWallet 0 0 2 2
VIVA Cash 0 9 4 13
Total 27 222 143 392

Finally, we can easily find the ratio of males and females:

Where we found from the questionnaire that the ages of the users are different

We find that the percentage of persistence according to the theoretical framework, we find the statistics as follows:
In the order of the questions asked.

Finally, we have completed the data analysis process using the SPSS program