Analyzing Factors Influencing Continuance Intention of E-Payment Adoption Using Modified
UTAUT 2 Model
(A Case Study of Go-Pay from Indonesia)
Indrawati
Faculty Economic & Business, Telkom University Bandung, Indonesia [email protected]
Dianty Anggraini Putri Faculty Economic & Business
Telkom University Bandung, Indonesia [email protected] Abstract— Online business of Indonesia continuous to
grow rapidly. This rapid growth encourages developments for electronic payment systems. Moreover, Bank Indonesia is running a program to increase the awareness of society to become cash-less. One of the e-payment that emerging in Indonesia is Go-Pay, a Go-Jek payment system. Go-Pay successfully becomes one of the fifth largest e-money in Indonesia less than a year of its operation. Therefore, Bank Indonesia awarded Go-Jek as the most active company that increase society’s awareness in conducting non-cash transactions in 2017. The successful of Go-Pay creates opportunities to upgrade the positions of Go-Pay service by knowing factors that influence its customers in continuing using Go-Pay services. This study intended to analyze factors influencing continuance intention of Go-Pay adoption in Indonesia by using a Modified Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) Model with Trust as a new variable. The data were gathered from 507 valid respondents in Indonesia chosen by purposive sampling technique. The result revealed that the factors influence continuance intention adoption of Go-Pay from the highest to the lowest respectively are Habit, Trust, Social Influence, Price Saving Orientation, Hedonic Motivation, and Performance Expectancy. The model can predict strongly the continuance intention of consumers towards Go-Pay services in Indonesia since the R² is 72.8%. This model can be used by Go-Pay management in making decisions to maintain the continuance intention of consumers towards Go-Pay adoption by paying attention to those factors and their indicators.
Keywords—Continuance intention; technology adoption; Go- Pay; modified UTAUT2; Indonesia
I. INTRODUCTION
Indonesian Ministry of Communications and Information released data that there was an increase of online transactions
value in Indonesia. In 2016, the transaction had reached US $ 4.89 billion, this amount is higher compared to 2015 [1].
Online transactions growth has been encouraging the developments of payment system technologies. In line with Bank Indonesia program to increase the non-cash payment system instruments usage which is called as National Non- Cash Movement Program or in Bahasa Indonesia is Gerakan Nasional Non Tunai (GNNT), a non-cash community in conducting transactions on economic activities will emerged [2]. According to the Indonesia Economic Report, non-cash payment instruments usage continues to increase [3]. The non- cash payment system index in 2015 was 249, and it reached 288 in 2016. The e-money usage becomes the largest increase in non-cash payment index. It indicates that e-money has a potential power to grow in Indonesia.
One of the e-money system that is emerging in Indonesia is Go-Pay. Go-Pay is an e-money system inside the Go-Jek application that enables the consumers to conduct financial transactions. Go-Jek is Indonesia on-demand mobile application that provides various services such as transportations, payment, logistics, and food delivery. Go-Pay usage has some benefits compared to cash usage namely the consumers will be able to get discounts, Go-Points Token, and vouchers. The best and the fastest growth of Go-Jek services is Go-Pay [4]. In a short time, Go-Pay successfully become one of the largest e-money in Indonesia according to the number of users, transactions, and usage [5]. Based on the JakPat survey in December 2016, the Go-Pay usage in Indonesia has reached 27.1 percent is ranked fourth. There is Mandiri eMoney in the first rank (43.8%), followed by Flazz (39.1%), Tcash (29.1%), Rekening Ponsel and Line Pay (15,6%) in the fifth rank [6].
Go-Pay users is estimated 1.5 times more than cash users in Go-Jek users. the Go-Pay growth is described as a Hockey Stick which increasing sharply in a short time [7]. Moreover, Go-Jek has received an award from Bank Indonesia as the most active company in supporting the GNNT Program [8]. In the next short time, Go-Pay service is not only for Go-Jek application payment, but also for various e-commerce 2018 6th International Conference on Information and Communication Technology (ICoICT)
shopping payment [9]. The successful fast growth of Go-Pay still give the opportunity to upgrade the Go-Pay service in order to increase the future positions. Therefore, Go-Pay management needs to always improve the service quality by analyzing factors influencing continuance intention of adopting Go-Pay. Moreover, there was no previous studies which address this phenomenon in Indonesia. Therefore, this study is necessary to be conducted. The aims of the study are to know the factors influencing continuance intention of Go- Pay adoption in Indonesia and to test if there are significant differences of behavior in terms of age and gender.
II. THEORITICAL FRAMEWORK
The authors used a modified Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) Model by Venkatesh, Thong, and Xu (2012) [10]. The reasons of using UTAUT 2 Model is this model is the most updated theory in technology adoption and it has the highest prediction power among others [10]. Compare to UTAUT Model, UTAUT 2 Model is a technology acceptance theory in the consumer context, while UTAUT Model is related to the use of technology in the organizational contexts [10]. Compared to UTAUT Model, this UTAUT2 Model produced an improvement in the explanation of Behavioral Intention (56 percent to 74 percent) also technology use (40 percent to 52 percent) [10]. Lastly, many previous studies also used UTAUT 2 Model in terms of technology adoption, such as [11, 12, 13].
Some modifications have been made in this study with some reasons, first, Behavioral Intention variable was replaced by Continuance Intention and eliminated Use behavior variable since we want to know the continuance intention of Go-Pay consumers in adopting Go-Pay. This is in line with the study of Xu (2014) [13].
The second modification is added Trust as a new variable.
This addition is done due to the fact that Trust has been proven to have a significant influence on mobile payment adoption [11, 14, 15]. The second reasons of adding Trust to the model is the fact that based on the preliminary data gathering, 38 out of 40 respondents believe that Trust becomes the reason of their adoption of Go-Pay.
The third modification is replacing Price Value with Price Saving Orientation. The reason is the usage of Go-Pay does not incur a monetary cost, but enable a lower price. Previous study also has been adapted price value with price saving orientation for some technologies, such as website purchasing which does not create a monetary cost, but enables a lower price (Escobar-Rodríguez, 2014) [16].
The fourth modification is this study did not include Experience as the moderating variable, due to the process of gathering data is not a longitudinal study, but a cross- sectional study. Therefore, including Experience in the model is not applicable. Fig. 1. Shows the modified UTAUT 2 Model to be tested.
Note: Bold Style variable is a new variable proposed in this study
Fig. 1. Modified UTAUT2 Model
There are 9 main variables in the model. The following is the explanation of each variable, which is adopted from the previous published research [10, 16, 17, 21]. Performance Expectancy is the degree to which a person believes that using Go-Pay would provide benefits in conducting Go-Jek services payment. Effort Expectancy is the degree of ease associated with the Go-Pay usage. Next, Social Influence is defined as the extent to which members of social networks, such as family, friends, influence one another’s behavior in using Go- Pay. Facilitating Conditions is the degree to which an individual believes that an organizational and technical infrastructure exists to support the use Go-Pay. Hedonic Motivation is the degree of fun or pleasure derived from using Go-Pay including Go-Pay features such as Discount, Vouchers, and Go-Point. Price Saving Orientation is defined as benefit, such as price reduction in using Go-Pay. This definition was adapted from Jensen (2012) in Escobar- Rodríguez et. al (2014) [16]. Habit is the extent to which people tend to use Go-Pay automatically because of learning.
Trust is the level of consumers can rely on the integrity of the Go-Pay promises in offering the services (Kolsaker & Payne, 2002) [18]. Continuance Intention definition is adapted from the Behavioral Intention definition of Venkatesh et al., (2012) [10]. Therefore, continuance intention is defined as the degree to which a person has formulated plans to continuously perform some specified future behavior. [17] Based on the model, there are 8 main hypotheses and 16 sub-hypotheses.
TABLE I shows the hypotheses in this study. Those hypotheses will be tested by using one tail test with a confidence level 95%. A confidence level that usually used in business studies are 95% [19].
TABLE I. HYPOTHESES
Hypothesis
H1 Performance Expectancy has a positive and significant influence on Continuance Intention.
H1a The influence of Performance Expectancy on Continuance Intention is moderated by age.
H1b The influence of Performance Expectancy on Continuance Intention is moderated by gender.
H2 Effort Expectancy has a positive and significant influence on Continuance Intention.
H2a The influence of Effort Expectancy on Continuance Intention is moderated by age.
H2b The influence of Effort Expectancy on Continuance Intention is moderated by gender.
H3 Social Influence has a positive and significant influence on Continuance Intention.
H3a The influence of Social Influence on Continuance Intention is moderated by age.
H3b The influence of Social Influence on Continuance Intention is moderated by gender.
H4 Facilitating Conditions has a positive and significant influence on Continuance Intention.
H4a The influence of Facilitating Conditions on Continuance Intention is moderated by age.
H4b The influence of Facilitating Conditions on Continuance Intention is moderated by gender.
H5 Hedonic Motivation has a positive and significant influence on Continuance Intention.
H5a The influence of Hedonic Motivation on Continuance Intention is moderated by age.
H5b The influence of Hedonic Motivation on Continuance Intention is moderated by gender.
H6 Price Saving Orientation has a positive and significant influence on Continuance Intention.
H6a The influence of Price Saving Orientation on Continuance Intention is moderated by age.
H6b The influence of Price Saving Orientation on Continuance Intention is moderated by gender.
H7 Habit has a positive and significant influence on Continuance Intention.
H7a The influence of Habit on Continuance Intention is moderated by age.
H7b The influence of Habit on Continuance Intention is moderated by gender.
H8 Trust has a positive and significant influence on Continuance Intention.
H8a The influence of Trust on Continuance Intention is moderated by age.
H8b The influence of Trust on Continuance Intention is moderated by gender.
III. MEASUREMENT
The data to test the hypotheses in this study were gathered by using questionnaire. There are some steps followed to create good questionnaire items namely conducting a content validity test, expert validity test, readability test, and pilot test.
Firstly, in conducting content validity test, the authors adopted and modified the questionnaire items from previous studies that have been published in reputable journals internationally or nationally. The previous studies are [11, 16, 17, 18, 20, 21, 22, 23]. The authors validate the items to 4 experts in the marketing and digital field by giving some questionnaire improvements. The next step was conducted a readability test.
The result revealed that respondents did not find difficulties in filling out the questionnaire.
The next step is conducting a pilot test to makes sure the items are fulfilled the construct validity and reliability. The pilot test used data from 40 respondents which were processed by using SPSS 23 Software. The criteria of items validity by using the “Corrected Item – Total Correlation” (CITC) score.
According to Friedenberg and Kaplan suggested that correlation coefficient is should be higher 0.3 to be considered valid item [19]. From the validity test result, the overall items
are valid with all CITC score are above 0.3. To test the reliability of the items, Cronbach-Alpha (CA) technique is the most widely used [19]. The instruments which have CA > 0.70 can be stated have a good reliability [19]. The result of SPSS 23 Software revealed that all the items are valid and reliable.
The valid items are shown in TABLE II.
TABLE II. QUESTIONNAIRE ITEMS
Code Item of Performance Expectancy PE1 Using Go-Pay increases my productivity.
PE2 Using Go-Pay helps me accomplish payments more quickly.
PE3 I can save time when I use Go-Pay in the payment process.
PE4 I find Go-Pay useful in my daily life.
Code Item of Effort Expectancy
EE1 Learning how to use Go-Pay is easy for me.
EE2 It does not take long time to learn to use Go-Pay.
EE3 I find Go-Pay easy to use.
EE4 It is easy for me to become skilful at using Go-Pay.
Code Item of Social Influence
SI1 People who are important to me think that I should use Go-Pay.
SI2 People who influence my behavior think that I should use Go-Pay.
SI3 People whose opinions that I value prefer that I use Go-Pay.
SI4 Most of people around me are using Go-Pay.
Code Item of Facilitating Conditions FC1 I have the resources necessary to use Go-Pay.
FC2 I have the knowledge necessary to use Go-Pay.
FC3 Go-Pay is compatible with other technologies I use.
FC4 I can get help from others when I have difficulties using Go-Pay.
Code Item of Hedonic Motivation
HM1 It is fun for me to use Go-Pay.
HM2 Features in Go-Pay (Go-Point Token) entertain me.
HM3 Features in Go-Pay (Discounts) entertain me.
HM4 Features in Go-Pay (Vouchers) entertain me.
HM5 Go-Pay is enjoyable.
HM6 I feel excited in using Go-Pay.
Code Item of Price Saving Orientation PSO1 I can save money by using Go-Pay.
PSO2 I like to search for cheap deals in Go-Pay services.
PSO3 Go-Pay offers better value of money.
PSO4 Go-Pay offers valuable promotions for me.
Code Item of Habit
H1 Using Go-Pay has become a habit for me.
H2 Using Go-Pay is something that I do without thinking.
H3 Using Go-Pay is a part of my daily routine.
H4 I am addicted to using Go-Pay.
Code Item of Trust
T1 I believe that Go-Pay is trustworthy.
T2 I trust in Go-Pay.
T3 I do not doubt the honesty of Go-Pay.
T4 Even if not monitored, I would trust Go-Pay to do the job right.
Code Item of Continuance Intention CI1 I intend to continue using Go-Pay.
CI2 I will keep using Go-Pay as regularly as I do now.
CI3 My intention is to continue using Go-Pay than use any alternative means.
CI4 I will strongly recommend that others use Go-Pay.
IV. DATA COLLECTION, ANALYSIS, AND RESULT
To test the 8 main hypotheses and 16 sub hypotheses, the authors distributed the questionnaire through Google Forms to collect the main data. The location of the study is in Indonesia where the cities that Go-Jek services are available. The period of collecting data was from October 27th 2017 - November
20th 2017. The data obtained from 690 respondents with 507 respondents declared to be valid. The valid data means the data that has been filled up by the respondents who meet the characteristics of this study. The respondent characteristics are the Go-Pay consumers for at least three months in order to get more accurate data of the consumer’s assessments and the consumers who are in the age 15 years – 60 year’s old which is divided in to two categories; young age (15-24 years old), and adult age (25-60 years old).
The respondent gender dominance by female with 69.23%.
It is because the Go-Jek application users itself is dominance by female. This result is in line with a research conducted by by Universitas Indonesia which revealed that Go-Jek users came from female with 69% and 31% male [24]. In terms of age, this study dominated by the young category, which in the Diffusion of Innovation Technology Theory included on innovators and early adopter category [25]. Innovators and early adopters has a similarity where these two category are brave and has no worries to take a risk on adopting a new technology, including in Go-Pay Adoption. Therefore, in this study, the respondents are dominated by young category. For the current residence area of respondent, mostly the respondents come from Java Island. It is because the Go-Jek service itself is mostly available in cities in the Java Island which is 30 cities out of 50 cities of Go-Jek operations in Indonesia [26].
After gathering the data, the authors conducted a descriptive analysis to know the assessment of Go-Pay consumers towards the factors inside the modified UTAUT 2 Model. The result revealed that the all the factors are categorized to have very high and high scores. The consumer’s assessment towards factors inside Modified UTAUT 2 Model from the highest to lowest score namely Effort Expectancy, Hedonic Motivation, Price Saving Orientation, Performance Expectancy, Facilitating Conditions, Trust, Continuance Intention, Habit, and Social Influence.
The consumer assessment of the Effort Expectancy factor is categorized as very high. All the items scores are in the very high category. It means that there is a very high level of easiness in using Go-Pay. Most respondents feel that using Go-Pay is very easy. Meanwhile, for the least score comes from item EE1, which is Learning how to use Go-Pay is easy.
Probably, in the beginning of Go-Pay usage, the consumers need more time to adapt with Go-Pay.
The assessment of consumers towards Hedonic Motivation factor is very high. It means that there is a very high degree of fun or pleasure derived from using Go-Pay including Go-Pay features such as Discount, Vouchers, and Go-Point. The highest score comes from HM3 which the item is “Features in Go-Pay (Discounts) entertain me.” It means that mostly the respondents were entertained and feel pleasure when they earned discounts. Therefore, it is important for Go-Pay maintain the discounts for the consumers. Meanwhile, the lowest score comes from HM2 item. Although it is the lowest score in this variable, but it still categorized as high. This HM2 item is about features in Go-Pay (Go-Point Token) entertain the consumers.
Based on the descriptive analysis result of Price Saving Orientation, the perception of consumers towards this variable categorized as a very high. The consumers perceived that price reduction or discounts in Go-Pay brings a very high benefit to the them. The highest score comes from PSO2 Item which 86.04% of the respondents perceived that they like to search for cheap deals in Go-Pay services. Meanwhile, the lowest score comes from item PSO4 Go-Pay offers valuable promotions for the respondents.
The consumer assessment of the Performance Expectancy factor is categorized as very high. It implies that Go-Pay brings very high benefits to the consumers. The highest score comes from item PE3 which is using Go-Pay helps consumers accomplish payments more quickly. Meanwhile, the lowest score comes from PE4 which is using Go-Pay increases productivity.
The assessment of consumers towards Facilitating Conditions factor is high. The lowest score is SI4 related with respondents can get help from others when have difficulties using Go-Pay. It implies that this service is still need to be improved in terms of customer service although it is in the high category.
The perception of respondents towards Trust to Go-Pay is high. According to the data, 81,14% respondents perceived that they believe that Go-Pay is trustworthy. Meanwhile, the lowest score is T4 which is “Even if not monitored, I would trust Go-Pay to do the job right.” It revealed that Go-Pay already build trust among the customers, therefore Go-Pay needs always to keep the customer trust in order to always engage the customers.
The consumer assessment of the Continuance Intention factor is categorized as high. It means that there is a high degree to which a person has formulated plans to continuously use Go-Pay perform some specified Go-Pay future behavior.
The opportunity for the consumers to use Go-Pay continuously is High. 77.91% respondents perceived that they intend to continue using Go-Pay.
The assessment of consumers towards Habit factor is high.
All the items are categorized as High. 81.34% respondents perceived that using Go-Pay is something that they do without thinking. It means that most of respondents use Go-Pay automatically because of learning since it is very easy to use Go-Pay. It is supported by the data that 76.77% respondents perceived that using Go-Pay has become a habit for them.
Meanwhile, item H4 becomes the lowest score while it still in a high category, which is about customer’s perception of the Go-Pay addiction.
The assessment of consumers towards Social Influence variable are categorized as high. The least score comes from item SI4, which is “Most of people around me are using Go- Pay.” While the highest score is SI1, which is “People who are important to me think that I should use Go-Pay.”
After knowing the consumer’s assessment towards the factors inside the modified UTAUT2 Model, the authors analyzed the valid data. The 507 valid data were analyzed by using Partial Least Square (PLS) software which is Smart PLS 2.0 M3. There are two steps for processing the data using PLS,
namely assessment of the measurement model (Outer Model) and assessment of the structural model (Inner Model). The first assessment is for making sure that the items are valid and reliable. Cronbach’s Alpha (CA) and Composite Reliability (CR) for evaluating the reliability. Cronbach’s Alpha Coefficient at least 0.7 shows that the questionnaire has a good reliability (Hair et., al 2010; Kaplan and Saccuzzo 1993:126;
Nunnally & Bernstein, 1994; Pedhazur & Pedhazur, 1991) in [27]. A good CR indicates that the construct indicators combine and adequately measure the construct. The value of CR required a minimum CR value of 0.7 [27]. TABLE III shows that all the items of this research have fulfilled the criteria of reliability.
TABLE III. THECA,CRANDAVESCORES
Variable CA CR AVE
PE 0.86 0.91 0.71
EE 0.93 0.95 0.83
SI 0.87 0.92 0.74
FC 0.80 0.87 0.63
HM 0.91 0.93 0.70
PSO 0.87 0.91 0.73
H 0.91 0.93 0.78
T 0.94 0.96 0.84
In terms of convergent validity, the test was conducted by calculating the Average Variance Extracted (AVE) Indicators.
The AVE score which is more than 0.50 shows that the items of a variable has an enough convergent validity (Hair et., al 2010; Ghozali, 2008) in [27]. TABLE III shows that the constructs used in this study have AVE values above 0.5.
Therefore, each construct meets the requirement of convergent validity test.
The assessment of structural model in PLS which is done first to know the influence of the latent variables towards other latent variables by using bootstrapping procedure. The criteria used is the t-value of path coefficient from one latent variable to another variable should be at least 1.65 to be considered significant at 95% confidence level one tail test. Table IV shows the path coefficient and t-value of each latent variable.
TABLE IV. THE PATH COEFFICIENT AND T-VALUE
Correlation of Variables Path Coefficient t-value Status
PE→CI 0.07 1.71 H1 accepted
EE→CI -0.06 1.46 H1 rejected
SI→CI 0.09 2.71 H1 accepted
FC→CI 0.02 0.6 H1 rejected
HM→CI 0.09 1.74 H1 accepted
PSO-> CI 0.067 1.81 H1 accepted
H→CI 0.48 10 H1 accepted
T→CI 0.24 4.93 H1 accepted
Based on the results shown in Table IV, the independent variables which have positive and significant influence on CI, respectively from the highest to the lowest are H, T, SI, PSO, HM, PE. Two variables namely EE and FC have no significant influence on CI.
EE has no significant influence on Continuance Intention.
According to the respondent profile, 86.19% respondents of this research are coming from young age category, who are
brave and has no worries to take a risk in adopting a new technology, including in Go-Pay Adoption. Therefore, the level of easiness does not become a consideration for them to adopt Go-Pay. This result confirmed the research conducted by [12].
In this study, FC has a positive but no significant influence on Continuance Intention. It may cause by the consumers who already have necessary devices to use Go-Pay. This is in line with a study by [12].
The second objective of structural assessment model is prediction power of the model which is indicated by for dependent latent variable. The result 0.67; 0.33; and 0.19 indicate that the model is “Good”, “Moderate”, and “Weak”
[27]. The result of bootstrapping shows that the of this study is 72.8%. Therefore, this study confirmed that the model has a strong predictive power. To test the sub hypotheses, this study uses group comparison by using Chin Formula that will result a t-value for comparing paths of each group [27].
TABLE V. THE RESULT OF MODERATION EFFECT Paths T-value for moderating variable
Age Gender
H -> CI 0.02 0.01
HM -> CI 0.06 0.05
PE -> CI 0.05 0.00
PSO -> CI 0.03 0.05
SI -> CI 0.05 0.02
T -> CI 0.01 0.02
The TABLE V shows that Young and Adult category also Age and Gender differences do not affect the influence of the modified UTAUT2 Model factors on continuance intention of consumers in the context of Go-Pay services in Indonesia. All the t-values of comparing paths are below 1.96. It reveals that there is no difference perception of respondents in terms of age and gender. This result is in line with the research result of Indrawati & Mansur (2015) in [27]. Fig.2. shows the tested model for continuance intention to adopt Go-Pay in Indonesia.
Fig. 2. Tested Model for Continuance Intention to Adopt Go-Pay in Indonesia
As shown in Fig 2, this study can conclude that the data in this study support that Trust has a positive and significant influence on continuance intention along with five other variables from original UTAUT2 Model (PE, SI, HM, PSO, H, T).
V. CONCLUSION AND SUGGESTIONS
Based on the results and analysis of this research, the author draws some conclusions.
A. Conclusion
There are 6 variables in this study that were proven to have a positive and significant influence on the consumer’s continuance intention of Indonesia Go-pay adoption. The variables were ordered from the highest to lowest affect respectively as follows: Habit, Trust, Social Influence, Price Saving Orientation, Hedonic Motivation, and Performance Expectancy. There is no difference perception of respondents in terms of age and gender.
The proposed model of this research had an R-Square value of 72.8% which means this model has a good predicting power to predict customer’s continuance intention towards Go-Pay adoption. Therefore, this proposed model can be used to be implemented in deciding Go-Pay management marketing program to increase customer continuance intention on Go- Pay adoption.
From the results of this research, Go-Pay management is expected to be able to point out and identify factors inside the modified UTAUT2 Model influencing consumer’s continuance intention of Go-Pay adoption. Go-Pay management could make a priority which factors needed to be concerned for the further Go-Pay business strategy developments. Therefore, Go-Pay management will understand more what user’s preferences are. Below are the suggestions for the Go-Pay management based on the factors that has a significant influence towards the consumer’s continuous intention in adopting Go-Pay:
B. Suggestions
This study has found that the most significant factor from the modified UTAUT2 Model that influence the Continuance Intention to use Go-Pay is Habit. The lowest item score of descriptive analysis in this factor is related with the addiction in using Go-Pay. Therefore, in order to make the consumers become addicted to use Go-Pay, the authors suggest to create a Go-Pay reward name for several levels. Once consumers unlock a higher level, there will be higher amount of discounts and Go-Points and it will increase the customer addiction.
The second factor that significantly influence the continuance intention to use Go-Pay is Trust. Regarding the lowest item score in this variable, it was about the consumer’s trust to Go-Pay in doing the right jobs even not monitored. It would be better if Go-Pay management to always increase the consumer’s trust by minimizing errors that may happen in Go- Pay. Go-Pay management may improve and always upgrade the system and security routinely. As a result, the errors would be minimized and could result an increase in Go-Pay consumer’s trust. Just in case some errors come, Go-Pay needs to be always ready and when the consumer’s need help to overcome the problems.
The third factor that significantly influence the continuance intention to use Go-Pay is Social Influence. According to the descriptive analysis result, most consumers do not think that
most of people around them are using Go-Pay. Therefore, Go- Pay management would be better to have more interactions with some communities or with the one who are important or key player inside the communities.
The fourth factor that influence the continuance intention in using Go-Pay services is Price Saving Orientation. According to the score from the descriptive analysis result, the lowest item score was related with Go-Pay offers valuable promotion for the consumers. The suggestion is Go-Pay management could widen the corporations with merchants that is more popular with attractive promotions, so then, people willing to redeem the Go-Points with more beneficial vouchers. If there are many attractive promotions regarding the vouchers also various merchants, people would like to collect the Go-Point as much as possible to experience the benefits of the valuable promotions then, Go-Pay usage will increase.
The fifth factor that significantly influence the Continuance Intention to use Go-Pay is Hedonic Motivation. The lowest item score was about Go-Pay Features (Go-Point) entertain the consumers. Therefore, a suggestion related the Go-points improvements had been formulated. To make the Go-Points Token more entertaining, Go-Pay management could improve the gifts inside the Token by adding doubled points, triple points, so then the Token will become more interesting.
Performance Expectancy becomes one factors significantly influence consumers in using Go-Pay. Since Performance Expectancy has the least significant score, Go-Pay management just need to maintain the quality of service for Go-Pay. Go-Pay management also need to conduct a competitor analysis and ensure that the service is still the best.
For further research, since this modified UTAUT2 Model has a strong explanatory power which is 72.8%, further research is expected to do a research in the field of e-payment but with a different research object.
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