Journal of Indonesian Marketing Association Vol.
No.
April 2024, pp.
103- 113
ISSN : 2963-3710
https://journal-ima.
Mobile Payment Service Adoption: Understanding OVO E-Wallet Customers among GEN Y and GEN Z in Bandung.
West Java Regya Viony 1,a,*.
Arry Widodo 1,b,2 1 Telkom University.
Indonesia.
a regyaviony@student.
b arrywie@telkomuniversity.
*Correspondent Author
ABSTRACT
KEYWORDS
Mobile Wallet
UTAUT
E-Wallet Usage Performance Expectancy Behavioural Intention Social Influence This study aimed to determine the factors that influence the Y and Z generation consumers in using OVO E-wallet in the city of Bandung.
The analysis employed the Unified Theory of Acceptance and Use of Technology (UTAUT) model, namely performance expectancy (PE), social influence (SI), and behavioral intention (BI).
The data analysis was carried out using the structural equation model (SEM-PLS) on the final data collected as many as 400 respondents.
The obtained results indicated that the performance expectancy (PE) and social influence (SI) have a positive and significant effect on the behavioral intention (BI) regarding the use of OVO mobile payment.
In addition, the social influence (SI) moderates the performance expectancy (PE) towards the behavioral intention (BI).
Generations Y and Z have high awareness and strong enthusiasm for adopting OVO mobile payment as long as it provides benefits.
One strategy to encourage the adoption of OVO mobile payments among the Y and Z generations is to facilitate financial transactions in an expeditious manner.
The social influence (SI) is also a factor regarding the adoption of OVO mobile payments.
This suggests that generations Y and Z rely more on advice and recommendations from important people .
uch as family, friends and relative.
in the adoption of OVO mobile wallet.
This is an open-access article under the CCAeBY-SA license.
Introduction It is currently evident that the development of technology is experiencing a significant This increasingly rapid technological progress affects the activities of the Indonesian people in several fields, one of which is in the use of the internet.
According to Dataindonesia.
We Are Social notes that the quantity of web clients in Indonesia has expanded from the earlier year.
In January 2022, 205 million people in Indonesia used the This indicates that 73.
7 percent of Indonesians have used the internet.
OCBC .
reports that the high volume of internet users currently plays a significant role in shaping the purchasing and selling behaviors of Indonesian consumers, including the shift towards digital, non-cash payment methods.
According to Widyanto et al.
Mobile Payment is defined as the use of mobile devices to perform, authorize, and confirm financial transactions to obtain goods and services.
A Kadence International Survey .
on the Digital Payment and Financial Services Usage and Behavior in Indonesia Report with 1,000 http://doi.
org/10.
69477/ima.
ISSN 2963-3710
Journal of Indonesia Marketing Association Vol.
No.
April 2024, pp.
respondents explains that OVO is the most well-known digital wallet .
-walle.
with a brand awareness acquisition rate of 96%.
According to the survey, 31% of respondents who reported being the most active users also indicated that OVO is the brand they use the most frequently.
Fintech.
defines OVO as an application that provides non-cash payment system services, and open access to other digital financial products and services that are presented in collaboration with selected partners.
It is reported by Katadata.
that OVO application has been installed on 115 million devices in total.
Appstore rankings show that OVO is positioned fifth in the finance section, but has a relatively low rating of 3.
9 compared to other digital wallet .
-walle.
The results of user reviews for OVO indicate that a significant number of reviews have rated the application One common reason for this is the difficulty in completing transfers and other The existence of this phenomenon will affect the userAos intention to use OVO application .
ehavioral intentio.
Customers who expect OVO performance to meet their expectations become disappointed when OVO cannot be used .
erformance expectanc.
Customers who intend to recommend to those closest to them become dissatisfied because of bad reviews from other customers .
ocial influenc.
According to the Central Statistics Agency (BPS).
Indonesia will have a population of 275.
million in 2022, making it the fourth largest country in the world.
Generation Z (Gen Z), which makes up 27.
94% of Indonesia's total population, is expected to dominate the country's population in 2020.
This is followed by generation Y or millennials, comprising 25.
87% of the total population of Indonesia .
id, 2.
Of the total groups of generations Y and Z, a significant number reside in West Java, with a population of 11,886,068 in 2021.
This research can be explained by a model of user behavior towards information technology called UTAUT (Unified Theory of Acceptance and Use of Technolog.
which is one of the acceptance of technology that uses the elements in eight existing models of technology acceptance, namely theory of reasoned (TRA), technology acceptance model (TAM), motivation model (MM), theory of planned behavior (TPB), combined TAM and TPB, model of PC utilization (MPTU), innovation diffusion theory (IDT), and social cognitive theory (SCT) to obtain an unified view of acceptance of the latest technology (Venkatesh et al, 2.
Gupta & AroraAos .
research on performance expectancy reveals that the performance expectancy significantly impacts the consumersAo behavioral intention to use e-wallets due to the time-saving and effectiveness of utilizing e-wallets for transactions .
-value 2.
p-value < 0.
The research on social influence conducted by Esawe .
shows that the social influence significantly influences the consumer behavioral intentions towards using e-wallets .
-value 4.
p-value < 0.
In other words, one of the factors driving the behavioral intention to use e-wallets is the social influence of important people, such as family, relatives and friends.
Based on the description of the gap phenomenon supported by the data, theory, and research gaps from the results of previous research, it is necessary for the researchers to conduct a research related to performance expectancy, social influence, and behavioral Literature Review Unified Theory of Acceptance and Use of Technology (UTAUT) This study uses the theory put forward by Venkatesh et al.
namely Unified Theory of Acceptance and Use of Technology (UTAUT).
This theory is the theory of acceptance and use of the latest integrated technology which is considered the most appropriate model.
UTAUT
combines eight models, namely Theory Reasoned Action (TRA).
Technology Acceptance Model (TAM).
Motivational Model (MM).
Theory of Planned Behavior (TPB).
Combined TAM and TPB Regya Viony et.
al(Mobile Payment Service Adoption.
Journal of Indonesia Marketing Association Vol.
No.
April 2022, pp.
ISSN 2963-3710
(C-TAM-TPB).
Model of PC Utilization (MPCU).
Innovation Diffusion Theory (IDT), and Social Cognitive Theory (SCT).
Compared to the eight models.
UTAUT has proven successful in explaining up to 70% of behavioral intention variants.
Venkatesh et al.
found, through their analysis of several influential constructs directly and significantly impacting intention and use, that there are four constructs that play a crucial role as direct determinants of user acceptance and usage behavior in the Unified Theory of Acceptance and Use of Technology (UTAUT).
The four constructs are performance expectancy, effort expectancy, social influence, and facilitating conditions.
This theory has several moderators, namely gender, age, voluntariness of use, and experience.
The following is the model of UTAUT:
Figure 1.
Unified Theory of Acceptance and Use of Technology (UTAUT) Unified Theory of Acceptance and Use of Technology Model (UTAUT) has an important role as a direct determinant of behavioral intention and use behavior, namely performance expectancy, effort expectancy, social influence, and facilitating conditions.
Performance Expectancy Performance expectancy is defined as the extent to which an individual believes that using a system will improve their performance at work.
Effort Expectancy Effort expectancy reflects the extent to which users perceive technology as easy to use, which can result in a reduction of the effort and time required to complete work tasks.
Social Influence Social influence refers to the extent to which a consumerAos decision to use a product or service is influenced by the opinions of their family, relatives or friends.
The indicators used are based on what other people think, should, and usually do to help use mobile Facilitating Conditions Facilitating conditions can be interpreted as the level of confidence that users can implement innovations with suggestions that support the use of new technology.
Behavioral Intention Behavioral intention is a personAos desire to use information technology for the purposes he/she wants.
Electronic Wallet (E-Walle.
Referring to the 2016 Bank Indonesia Regulation number 18/40/PBI/2016, e-wallet is an Regya Viony et.
al(Mobile Payment Service Adoption.
ISSN 2963-3710
Journal of Indonesia Marketing Association Vol.
No.
April 2024, pp.
electronic service for storing payment instrument data, including payment instruments using cards and/or electronic money, which can also accommodate funds for making payments.
Ramli and Hamzah .
define an e-wallet as a mobile device-based platform that facilitates payment of cashless sales transactions Ae both in person and remotely, between consumers and merchants or service providers.
Its several advantages lead to consumer acceptance of e-wallet.
To attract the attention of consumers, service providers often offer a variety of incentives as rewards for using their For example, they offer cashback, bonus points, good offers or discounts.
Utilizing ewallet services enables consumers to efficiently transfer money to third party accounts.
addition, e-wallet users can pay the same amount separate receipts to separate invoices.
Several e-wallet providers offer this feature to consumers to save costs for related services (Ramli & Hamza, 2.
Framework In this study, the researchers conducted a research on the factors that influence the Y and Z generation consumers who use mobile payments on OVO e-wallet in the city of Bandung.
This research used the Unified Theory of Acceptance and Use of Technology (UTAUT) theory by using performance expectancy and behavioral intention variables as well as social influence variable as a moderating variable.
For this reason, a framework is needed as a basis for developing According to the research conducted by Puspa .
, performance expectancy has a significant influence on behavioral intention.
This means that the greater the consumerAos expectations, the stronger their desire to use the system.
Furthermore, the other study conducted by Rahi et al.
also stated that social influence positively influences the consumer intentions in using mobile banking.
Based on this description, the framework of the research is described as follows:
Figure 2Research Model Regya Viony et.
al(Mobile Payment Service Adoption.
Journal of Indonesia Marketing Association Vol.
No.
April 2022, pp.
ISSN 2963-3710
Relations among Variables Relationship between Performance Expectancy and Social Influence In their study.
Venkatesh et al.
explained that performance expectancy and social influence are closely related and complement each other in regards to behavioral intention.
Furthermore.
Hidayatullah et al.
explained that consumer behavior towards performance expectancy always meets the expectations of users and consumers in making purchasing decisions, and this holds true for all behaviors.
Additionally, social influence also provides a positive stimulus to behavioral intention.
Therefore, the performance expectancy and the social influence together provide a clear picture of the current consumer behavior.
In this study, we aimed to understand the relationship between the performance expectancy and social influence, particularly in the digital age where consumer behaviors and geographical conditions can vary.
Relationship between Performance Expectancy and Behavioral Intention Hutabarat et al.
found that Performance Expectancy has a significant impact on Continuance Intention based on their research.
This means that if a system helps to achieve benefits or optimal performance, it will increase a personAos desire to use it.
This supports the results of the research conducted by Kelvin .
stating that the performance expectancy variable has an influence on the intention to use electronic payment systems in e-money.
Relationship between Social Influence and Behavioral Intention According to the research conducted by Achiriani .
, social influence variable has a significant influence on behavioral intention variable.
This suggests that the recommendation, usage, and support of OVO e-wallet provided by close individuals, such as family, relatives, or friends, has an influence on the behavioral intention to use the system.
This aligns with the findings of research conducted by Kelvin .
, which found that social influence variable has an impact on the intention to use electronic payment systems through e-money.
Hypothesis Development According to Sugiyono .
9: .
, a hypothesis is a temporary answer to a formulation of research problem, where the formulation of the problem has been stated in the form of a It is said temporarily because its new answer is based on relevant theories, not based on the results of facts that have been obtained from data collection.
The following are hypotheses in this study:
H1: Performance expectancy has an effect on behavioral intention among OVO e-wallet users.
H0: Performance expectancy has no effect on behavioral intention among OVO e-wallet users.
H2: Performance expectancy has an influence on social influence among OVO e-wallet users.
H0: Performance expectancy has no influence on social influence among OVO e-wallet users.
H3: Social influence has an effect on behavioral intention among OVO e-wallet users.
H0: Social influence has no effect on behavioral intention among OVO e-wallet users.
H4: Performance expectancy has an effect on behavioral intention, with social influence as a moderating variable among OVO e-wallet users.
H0: Performance expectancy has an effect on behavioral intention, with social influence as a moderating variable among OVO e-wallet users.
Methodology Research Population and Sample Population in a study must be stated explicitly, including a size of population members and Regya Viony et.
al(Mobile Payment Service Adoption.
ISSN 2963-3710
Journal of Indonesia Marketing Association Vol.
No.
April 2024, pp.
the research area covered.
The population is a key part of all aspects of the study (Widodo and Yusiana, 2021: .
In this study, the population consists of OVO digital wallet users in Bandung, who are unknown in terms of their exact number.
The research location was chosen because Bandung is one of the largest cities in Indonesia.
In addition, according to KadenceAos 2021 survey AuDigital Payment and Financial Services Usage and Behavior in Indonesia,Ay OVO is the most widely used digital wallet in the city of Bandung, at 33%.
In this study, the following sample selection criteria were used:
Domiciled in the city of Bandung Using OVO mobile wallet application In this study, the nonprobability sampling technique with purposive sampling was used.
Nonprobability sampling is defined by Sugiyono .
as a technique that does not provide equal opportunities for every member of a population to be selected.
Samples for this study were collected through an online survey conducted in Bandung in November 2022.
The research was conducted for approximately two weeks using Google Forms, which were shared on social media platforms such as Instagram and WhatsApp.
The researchers were able to collect 400 responses that met the predetermined criteria.
Results In this study, the characteristics of the respondents were divided into three categories: age, occupation, and monthly income.
The following table presents a summary of the characteristics of the respondents:
Table 1.
Profile of the respondents Categories Description No.
Respondents >35 Student
Employee < IDR 1,000,000 IDR 1,000,000 Ae IDR
5,000,000
IDR 5,000,000 Ae IDR
10,000,000
> IDR 10,000,000
Occupation Level of Income .
onthly This study employed the SEM-PLS technique.
According to Hair et al.
SEM-PLS
consists of two stages: the first stage, known as the outer model .
easurement mode.
, assesses reliability and validity, while the second stage, known as the inner model .
tructural mode.
, tests the strength of the relationship between constructs.
Discriminant and convergent validity is seen through the measurement of cross loading factor with a comparison of AVE and correlation between variables in a study.
If the data shows that the construct correlation of each indicator has a value greater than the other construct values, then this variable has a high cross loading factor (Hair et al.
, 2.
In addition, there are other approaches to determine the amount of discriminant validity, namely using the heterotrait-monotrait ratio and the Fornell-Larcker Criterion.
In the heterotrait-monotrait .
r HTMT) approach, the ratio value for HTMT in a study may not exceed 0.
9 (Henseler et al.
Regya Viony et.
al(Mobile Payment Service Adoption.
Journal of Indonesia Marketing Association Vol.
No.
April 2022, pp.
ISSN 2963-3710
Furthermore, the reliability test on partial least squares is carried out using two methods, namely CronbachAos Alpha which must have a value of > 0.
60 and Composite Reliability which must have a value of > 0.
70 (Ghozali, 2.
Table 2.
Measurement Model Assessment1 Latent Variables Items Indicator Reliability Load Factor (>0.
Convergent Validity AVE (>0.
Performance Expectancy PE1
PE2
PE3
PE5
PE6
PE7
PE8
PE9
PE10
PE11
PE12
PE13
PE14
PE15
PE16
BI1
BI2
BI3
BI4
BI5
BI6
BI7
BI8
SI1
SI2
SI3
SI4
SI5
SI6
SI7
SI8
Behavioral Intention Social Influence Internal Consistency Reliability Composite CronbachAos Reliability Alpha (>0.
(>0.
Table 3.
Heterotrait-monotrait ratio (HTMT) Behavioral Intention Performance Expectancy Social Influence Regya Viony et.
al(Mobile Payment Service Adoption.
ISSN 2963-3710
Journal of Indonesia Marketing Association Vol.
No.
April 2024, pp.
Furthermore, the measurement of the structural model (Inner Mode.
aimed to test the effect of other latent variables.
The test was carried out based on the path value to see whether or not the influence that can be displayed from the t value is significant.
The t value can be obtained by bootstrapping.
The R-square value is the coefficient of determination in the endogenous construct.
A higher R-square value indicates a better prediction of the proposed research model.
Table 4.
R-Square Variable R-Square Behavioral Intention (Y) Social Influence (Z) Based on table 4, it can be seen that the R-Square value on behavioral intention resulted in an R-Square value of 0.
This means that performance expectancy has an influence of 61.
and the remaining 38.
4% is influenced by other variables outside the research.
the R-Square value for social influence is 0.
324, meaning that the effect of performance expectancy on social influence is 32.
4% and the remaining 67.
6% is influenced by other variables outside this study.
Q-square indicates the independent-test predictive power or predictive significance of the A Q2 value greater than 0 indicates that the model has predictive value for certain endogenous constructs.
Conversely, values of 0 and below indicate a lack of predictive As a relative measure of predictive importance, values of 0.
02, 0.
15, and 0.
indicate that exogenous constructs have low, medium, and high predictive significance, respectively, for certain endogenous constructs (Hair et al.
, 2.
The following is a Q-Square calculation using SmartPLS:
Table 5.
Q-Square Behavioral Intention (Y) Social Influence (Z) (Q.
Based on table 5 above, it can be seen that the Q2 value for the social influence variable is Because Q2 = 0.
159 > 0, it is concluded that the performance expectancy variable has predictive relevance for the social influence variable.
It is known that the value of Q2 = 0.
which is greater than 0.
15, then it is concluded that the relevance of the prediction is medium.
Furthermore, the Q2 value for the behavioral intention variable is 0.
Because Q2 = 0.
> 0, it can be concluded that the performance expectancy variable has predictive relevance for the behavioral intention variable.
It is known that the value of Q2 = 0.
325, which is greater than 15, it can be concluded that the relevance of the prediction is medium.
Based on the results of the SEM analysis that was carried out, it can be seen from the results of the hypothesis test that the performance expectancy has a significant and positive effect on the behavioral intention to use OVO e-wallet .
-statistic 2,676.
p-value 0.
007 < 0.
This is in line with the research conducted by Esawe .
which states that the performance expectancy influences consumer the behavioral intention to use e-wallets because using ewallets can save time and make transactions more effective.
Furthermore, the results of the hypothesis test show that the performance expectancy has a significant and positive effect on the social influence on the use of OVO e-wallet .
-value p-value 0.
000 < 0.
This finding is consistent with the research conducted by Hidayatullah et al.
, which found that consumer behavior in terms of intention on performance expectancy (PE) always meets the expectations of users and consumers in making purchase decisions, including their behavior.
Moreover, the social influence (SI) also provides Regya Viony et.
al(Mobile Payment Service Adoption.
Journal of Indonesia Marketing Association Vol.
No.
April 2022, pp.
ISSN 2963-3710
a positive stimulus to the behavioral intention.
The social influence has a significant and positive effect on the behavioral intention in using OVO e-wallet .
-value 20.
p-value 0.
000 <0.
In other words, one of the drivers of the behavioral intention to use OVO e-wallet is the social influence of important people, such as family, relatives and friends.
These results are supported by previous research by Esawe .
and Abdullah et al.
In addition, the performance expectancy has a significant and positive effect on the behavioral intention through the social influence .
-value 14.
p-value 0.
000 < 0.
This can be explained by the fact that the social influence from family, relatives, and friends influences consumer performance expectations and the behavioral intention in using OVO ewallet.
For more details, refer to the following table:
Table 6.
Path Coefficient PE -> BI
PE -> SI
SI -> BI
PE -> SI -> BI
Original Sample (O) Sample Means (M) Standard
Deviation (STDEV) T Statistics (|O/STDEV|) P Values 2,676 20,897 20,377 14,569 Based on the results of this research, the following conclusions can be drawn regarding the Table 7Summary of Hypothesis Test Results Hypotheses Description Relations between Variables Results Performance expectancy on behavioral PE -> BI
Performance expectancy on social
PE -> SI
Social influence on behavioral intention SI -> BI
H0 is H1 is H0 is H2 accepted H0 is H3 is Performance expectancy on behavioral intention moderated by social influence DIRECT EFFECT
INDIRECT EFFECT
PE -> SI -> BI
H0 is H4 is Conclusion The results of this study show that the majority of respondents in generations Y and Z in Bandung City.
West Java have a positive attitude towards using OVO e-wallet.
Based on the results of the SEM analysis that was carried out, it can be seen from the results of the hypothesis test that the performance expectancy (PE) has a significant and positive effect on the behavioral intention (BI) regarding the use of OVO e-wallet .
-statistic 2,676.
p-value 0.
007 < 0.
The Regya Viony et.
al(Mobile Payment Service Adoption.
ISSN 2963-3710
Journal of Indonesia Marketing Association Vol.
No.
April 2024, pp.
performance expectancy (PE) also has a significant and positive effect on the social influence (SI) regarding the use of OVO e-wallet .
-value 20.
p-value 0.
000 < 0.
The social influence (SI) also has a significant and positive effect on the behavioral intention (BI) in using OVO e-wallet .
-value 20.
p-value 0.
000 < 0.
The performance expectancy (PE) has a significant and positive effect on the behavioral intention through the social influence (SI) as well .
-value 14.
p-value 0.
000 <0.
The results of hypothesis test indicate that the PE.
BI and SI variables are factors that influence the intention to adopt OVO mobile payment.
The Y and Z generations have high awareness and strong enthusiasm for adopting OVO mobile payment as long as it provides Making financial transactions effortlessly and swiftly is a way to attract the Y and Z generations to use OVO mobile payment.
The social influence (SI) is also a factor in the use of OVO mobile payment.
This suggests that generations Y and Z rely more on advice and recommendations from important people .
uch as family, friends, and relative.
when using OVO mobile wallet.
Reference