Determinants of Trust and it’s Implications on Electronic Money’s Continuance Usage Intention in the Land Transportation Industry in Jakarta


Pdf : 202 Views 506 Download 

Agus Hari Survijanto, Farida Jasfar, Hamdy Hady*

Citation: Agus Hari Survijanto, Farida Jasfar, Hamdy Hady, ”DETERMINANTS OF TRUST AND ITS IMPLICATIONS ON ELECTRONIC MONEY’S CONTINUANCE USAGE INTENTION IN THE LAND TRANSPORTATION INDUSTRY IN JAKARTA”, vol 6, no. 1, 2020, pp. 1-11.

Copyright Amirul Wicaksono , et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Abstract:

The research objective is to identify and analyze the factors of Confirmation, Perceived Value and Customer Satisfaction of Trust, as well as the influence of Trust and other factors on Continuance usage intention, and create a model that conceptualizes these influences on Continuance

Usage Intention
The method used in this study is a quantitative descriptive method that was built using a questionnaire and analyzed using Structural Equation Modelling (SEM) fund analysis techniques based on an evaluation of the interdependence relationship between variables assisted by LISREL software 8.80.

The results showed that the use of electronic money for the transportation industry in Jakarta needs help through increasing the Continuance usage of the intention of users of electronic money services. Continuance usage intention is conceptualized in a proposed model that modified from Expectation-Confirmation Model (ECM) by adding Perceived value dan Trust variables, that involves the role of Confirmation, Perceived value and Customer satisfaction of Trust and its implications for the Continuance usage intention electronic money users in land transportation service users in Jakarta. The results of this study found that (1) The factors that influence Trust of electronic money users in land transportation service users in Jakarta are Confirmation, Perceived value, and Customer satisfaction. (2) Trust has not been proven to affect Continuance usage intention, but Perceived value and customer satisfaction have been proven to influence Continuance usage intention. Perceived value and Customer satisfaction are proven to mediate the influence of Confirmation for the Continuance usage intention. (3) The Perceived value is proven to be the most influential factor towards the Continuance usage intention, and the dimension that most influences the Perceived value is the Perceived emotional value. (4) Perceived value and Customer satisfaction are proven to mediate the influence of Confirmation on Trust. (5) Data security and customer feasibilities on information of historical transaction balance are important in growing Trust that can help increase.

Continuance usage intention sustainably.

These finding has several managerial implications for electronic service provider in carrying out strategic steps in increasing the Continuance
usage intention of users of electronic money for land transportation in Jakarta. Further theoretical implications are research developing a broader
framework of combining the Expectancy-Confirmation Model (ECM) model with Perceived Value and Trust. This is expected to play role in the
progress of science and can provide insights for further research.

Value obtained from this research is the existence of a new model and identification of aspects that affect the Continuance usage intention so that
appropriate steps can be taken in increasing the Continuance usage intention, especially for electronic money users in the land transportation
sector in Jakarta.

Keywords: Confirmation, customer satisfaction, perceived value, customer trust, intention to continue using.




Description:

Introduction

Electronic money is one of the new media for buying and selling transactions. The use of electronic money provides additional benefits for the Government, service providers or users. The government can use electronic money to help people who have not been reached by banking services, and this is realized by the government embarking on the Strategy Nasional Keuangan Inkusif (SNKI) initiative. Electronic money provides added value for service providers because the operating costs of electronic money are cheaper as they can reduce the process chain in providing services. Users
can be facilitated through mobile applications, electronic wallets on their mobile phones or chips as a media to store data and identity. Therefore the opportunity to increase the use of electronic money should be very wide open. However, this is currently not happening and electronic money is not yet the primary choice for people to replace cash. Adoption of electronic money does not necessarily change the procedure for public transactions. Not a few people have tried to use electronic money, but most of them experience obstacles to the Continuance usage intention of electronic money and this needs to be a concern of service providers (Bhattacherjee, 2001; Susanto et.al., 2016; Luqman, 2016; Gong et al., 2018;
Eugene et. al., 2019).

Service providers must understand the key to success in mapping out strategies and steps to stimulate the use of electronic money and increase Continuance usage intention. The cost of acquiring new customers is far more expensive than customer retention, so Continuance usage intention is
something that must be maintained by service providers so that their business continues to grow (Kotler et al., 2017). Research on Continuance usage intention (CUI) is still not as much as research on adoption in terms of electronic money, especially in Jakarta and Indonesia. Two theoretical foundations that are often used for research into the continued use of a technology, Technology Acceptance Model (TAM) and Expectation-Confirmation Model (ECM) (Bhattacherjee, 2001), are often used as a basis for researching Continuance usage intention (Susanto et al. 2016, Luqman et al. 2016 al., 2016, Zhang et al., 2015). TAM is used to predict consumer behavior in accepting a new technology, ECM is used to predict the continued use of a technology through confirmation factors, perceived usefulness and satisfaction (Bhattacherjee, 2001).

Other factors such as trust in other studies have been shown to influence repurchase intentions or continued use of a technology (Zhou, 2014 and Chen et al., 2015). The use of digital technology such as server-based electronic money has a high risk because it requires sharing customer information, so the trust factor becomes an important thing. Only customers who have confidence in the service and its providers dare to make transactions. If customers do not have trust they are usually reluctant to make transactions (Xin et.al., 2013). This research develops and validates the Continuance usage intention framework by modifying the ECM model that has been applied to various contexts of technology use. (Susanto et al., 2016; Luqman et al., 2016; Zhang et al., 2015; Chen et al., 2008), as well as adding trust factors that affect Continuance usage intention (Zhou, 2014; Chen et al., 2015). This research is more focused on the transportation sector considering that it contributes to the transportation segment in the Gross Domestic Product which is quite large (Bank Indonesia, 2018), and more specifically land transportation which gives the biggest contribution considering the largest contribution of land transportation compared to other modes of transportation, and sectors in the region (Bank Indonesia,
2018), and is geographically restricted in DKI Jakarta.

Literature Review

Expectancy Confirmation Model (ECM) In the development of new technologies, phases of technology adoption are known. This phase introduces the
new technology to customers so customers can try to use the technology. Passing through the adoption phase is not enough because steps are still needed after adoption to ensure the sustainability of the new technology. One model that is often used to evaluate post-adoption steps is the Expectancy Confirmation Model (ECM), which is used to study the continued use of an information system technology. ECM starts with the Confirmation variable that affects perceived usefulness and satisfaction and finally affects Continuance usage intention (Bhattacherjee, 2001).

Continuance usage intention
Continuance usage intention is defined as the will of the user in continuing to use an information system, which is “central to the survival” of online businesses, and is critical for the success of the business (Bhattacherjee, 2001). Factors that determine interest in continuing to use a system
are confirmation of initial expectations about a product or service, perceptions of performance and customer satisfaction. (Bhattacherje, 2001); Customer satisfaction factors for a technology (Bhattacherje, 2001; Chen et al., 2009; Chen et al., 2015; Luqman et al., 2016); is the impact of performance expectations, trust and flow (Zhou, 2014); influenced by technological perception factors and experience flow (Zhou,2013); or the impact of perceived usefulness, enjoyment and social pressure (AlMagrabi et al., 2011). Service providers have invested in large resources and efforts, so if they cannot retain and do not facilitate customers to make sustainable purchases, they will not be able to overcome costs and pursue profit (Zhou, 2013);

Trust

Trust is the foundation of business, business transactions will not occur if each party does not trust each other. Building Trust with customers is an important mission because purchasing decisions are behaviors related to Trust. (Jarvenpaa et al., 2000; McKnight et al., 2002). Goudarzi, et al., (2013) states that Trust has a variety explanation, shows the characteristics of complicated trust concepts. Trust is identified as three dimensions which are
credibility, integrity and benevolence. (Heffernan et al.,2008).

Satisfaction

Kotler, Armstrong, and Opresnik (2017) define marketing as a process that engages customers and manages profitable customer relationships with two main objectives namely getting new customers through superior values, maintaining and growing current customers by providing value and customer satisfaction. Satisfaction occurs when someone evaluates the expectation of “pre-usage” compared to its performance during “actual
usage”. When expectations match their performance, users provide confirmation that they are satisfied, but when performance does not meet expectations, what happens is disconfirmation and dissatisfaction (Bhattacherjee, 2001).


Oliver (2015) argues that the different aspects of satisfaction make it difficult to define it, this is because it relates to the complete consuming experience, namely (1) Satisfaction during the consumption period; (2) Satisfaction is the final result; (3) Satisfaction depends on the level of satisfaction received. In this context Satisfaction is seen as a single event from beginning to end. Satisfaction is the response from the fulfillment of customer needs, which is the customer’s assessment of the level of fulfillment of those needs, namely the fulfillment that is appropriate, less or excess. Customer satisfaction can be defined in to outcome, or as a process (Yi , 1991 in Grigoroudis & Siskos, 2010).

Perceived Value

Cost usually doesn’t valued “accurately” or “objectively” by customer. Value their perceived can tringger them acting and choosing the highest perceived value based on their evaluations between all benefits and all costs of market offerings compared to competitive offers (Kotler et al., 2017)
Perceived value is defined from various points of view with a variety of opinions. One approach that is widely adopted is the Zeithaml (1988) model which divides the dimensions of perceived value into intrinsic attributes, extrinsic attributes, quality, other high level abstractions and sacrifices (monetary and nonmonetary). Sheth (1991) identifies five dimensions of the concept of values (functional), namely functional, social, emotional, epistemic and conditional. Functional value is related to benefits of service. Feelings of experiences is reflection emotional value, acceptance at community and relationships with the social environment is reflected by social value, epistemic value relate by the things that satisfy the desire for knowledge and conditional values relate to situational factors such as illness or certain social situations. Kim et al. (2009) defines several types of values in the form of functional values, emotional values and social values. Functional value is the result obtained by reducing the perceived cost of the product in the short and long term, which is supported by price utility and quality. Emotional value states the benefits as a result of the emotional state of a product. Emotional values include aesthetics and entertainment, and are ‘the benefits of trying new or different things’. Whereas
social value is defined as benefits as a result of the product’s ability to develop social perception.

Sweeny and Soutar (2001) develop the structure of the perceived value dimensions of emotional, social and functional values into four parts. Functional value is built by the attributes of reliability, durability and price, where reliability, durability are quality aspects that have a positive effect, while price is a negative effect, so the function value dimension is split into quality value and price value, so the perceived value dimension becomes quality value, price value, emotional value and social value. This is supported by the opinion of Koller et al. (2011) which also uses four dimensions of perceived value, namely functional value, economic value, emotional value and social value in predicting intention loyalty in the context of green consumption. Peng and Peng and Liang (2013) also use the four dimensions above, namely functional value, price value, emotional value and social value to predict Purchase Intention on e-commerce platforms.

Confirmation
Bhattacherjee (2001) defines confirmation as the customer’s perception of the level of conformity between expectations in an information system and actual experience, and if the performance exceeds performance expectations before making a purchase, then what happens is the customer feels satisfied and there is confirmation. Customers will re-evaluate their acceptance during the last confirmation period and decide to continue using the service or stop it (AlMaghrabi, 2011).

Confirmation also has a positive relationship with customer satisfaction because it realizes the expected benefits. When post-consuming a confirmation service is positively related to satisfaction and perceived usefulness. (Bhattacherjee, 2001; Chen et al., 2008; Larsen et al., 2009; Susanto et al., 2016). Confirmation as post consumption perception plays an important role to direct user perception such as usability perception and security / privacy perception in using services (Chen, 2012; Susanto, 2016)

Electronic Money in Indonesia
Electronic money is money that is not in the form of physical money and can replace cash for cashless money transactions (Bank Indonesia, 2018), which consists of chip based / prepaid cards or often also referred to as electronic purses and server based or prepaid software or often called digital cash. Based on data from Bank Indonesia (2019), until the end of October 2019, the number of electronic money players in Indonesia currently are the 39 electronic money providers that have received training from Bank Indonesia. Of the many electronic money licenses, only a few have begun to be widely used by the general public. The market share for chip-based electronic money is still dominated by four major book 4 banks, namely Bank Mandiri (e-money), Bank Central Asia (Flazz), Bank Rakyat Indonesia (Brizzi) and Bank Negara Indonesia (Tap Cash). Whereas server-based electronic money is controlled by Go-pay, Ovo and Link Aja.

Land Transportation in DKI Jakarta

Transportation is one of the most important sectors and this sector accounts for Rp615.51 T (4.52%) of the National Gross Domestic Product (GDP). Land transportation which consists of buses, trains, taxis, city transportation, and ojek contribution of Rp318 T or 53.28% of the industry (Bank Indonesia, 2018). Jakarta as the capital of the Republic of Indonesia, contributed 23.75% of the total national GDP, which is dominated by the city of Central Jakarta and the city of South Jakarta, with the provincial economic growth rate of 6.17% in 2018. (BPTJ, 2019). The availability of safe and comfortable public transportation is a serious concern of the Provincial Government of Jakarta, especially to overcome traffic jams in the capital. Since 2004 Jakarta residents have been able to enjoy mass transportation of Transjakarta buses. To increase the use of Transjakarta buses, the number of corridors and buses continues to be increased. In addition, to improve time and ease of use for Transjakarta bus transportation service users, an electronic payment system for Transjakarta bus users began to be launched on 22 January 2013, and this system has been implemented in all Transjakarta corridors since 21 February 2016.

Railways as a means of transportation are generally chosen because not only an alternative to cheap public transportation options, but also free from congestion on the capital’s highways. The number of train passengers during 2013-2017 continues to increase with an average growth rate of 13.48 percent per year. The biggest growth occurred in train passengers outside the city, which amounted to 26.04 percent per year. Likewise, the growth of train passengers to Jabodetabek also increased by 18.82 percent per year. (BPS Provinsi DKI Jakarta, 2018). Application-based transportation in DKI Jakarta is currently increasingly popular with the presence of online motorcycle taxis, online taxis or online rental cars, even online bajaj. Ordering transport using a smartphone or smartphone by installing an application that can be downloaded for free, each user can order this service from anywhere. The pioneer of online motorcycle taxi technology company that provides applications to connect transportation users with motorcycle taxi drivers is Gojek, which began to be widely known by the people of Jakarta in early 2015. Similar businesses include Grabbike launched in May 2015, and developed through Grabcar which was first launched on 9 August 2015 using the payment method at that time using cash and as the journey
turned into electronic money. With Grabcar, Gojek also reacted by adding Gocar services to compete with Grab in the application-based public transportation industry in DKI Jakarta. Until now Gojek and Grab are still competing with each other over a fairly large market share.

Theoretical Model

This study combines the ECM model that examines the relationship of Confirmation, Percevied Usefulness, Satisfaction and Continuance usage intention (Bhattacherjee, 2001). Furthermore, the confirmation relationship with trust was developed (Susanto et al., 2016), Confirmation with
perceived easy of use (Hong et al., 2005), and added the Trust variable and the effect of satisfaction on trust (Gong et al.,2018), and Perceived Value of Continuance usage intention



(Prodanova et al., 2019), so a research model is proposed as follows:

Research Hypothesis
The Relationship between Confirmation and Perceived Value, Customer Trust and Customer Satisfaction In the ECM model developed by Bhattacherjee (2001), confirmation is the answer to whether one’s expectations after the use of a technology are fulfilled. Someone will feel the benefits of the use of technology if the expectations after the use of the technology are met, and vice versa will not be useful if expectations are not met (Oliver, 1980). Several empirical studies have shown that confirmation positively influences perceived value and customer satisfaction. (Bhattacherjee, 2001; Susanto et al., 2016; Luqman et al., 2016; Zhang et al., 2015). Confirmation also has a positive relationship with customer satisfaction because it realizes the expected benefits. (Bhattacherjee, 2001). Confirmation experience is positively related to satisfaction levels and further influences the interest in continuing to use Rafio Frequency Identification Device / RFID technology (Chen et al., 2008).

Confirmation increases user satisfaction and increases their level of trust in service. Confirmation as post consumption perception plays an important role in directing user perception such as perceived value, especially perceived usefulness, perceived ease of use, and perceived security / privacy in using services in general and smartphone banking services in particular (Hong et al., 2005; Santosa et al., 2016).In the model of Susanto et al. (2016) proven confirmation factors influence customer trust (Trust), perceived security and privacy, perceived usefulness, and satisfaction.
Based on this study several hypotheses related to confirmation were developed:

H1: Confirmation has a positive and significant effect on Customer Satisfaction in electronic money services in Jakarta.
H2: Confirmation has a positive and significant influence on Perceived Value in electronic money services in Jakarta.
H3: Confirmation has a positive and significant influence on Trust in electronic money services in Jakarta.

The Relationship between Perceived Value and Satisfaction with Trust

Perceived value is the customer’s evaluation of the benefits of a product or service, based on the differences between the customer’s understanding and what they receive, and between what they give (effort) and they get (Zeithaml, 1988; Oliver, 2015). From the definition, it is known that the perception of usefulness is a belief about the decision making process. If someone feels that the system is useful, customers will get satisfaction, but if it is not useful, they will not use it (Bhattacherjee, 2001; Susanto et al., 2016; Luqman et al.,2016; Zhang et al., 2015).

This statement was supported by several studies conducted by Ha et al., (2019) who examined channel relationships in the electronics industry as research subjects, and Berraies et al., (2017) who tested the effect of e-satisfaction among baby boomers, generations X and generation Y, and research Gil- Saura et al., (2009) in the context of Business-to-business (B2B) in Spain. The three studies above show that Perceived
Value has a significant (positive) effect on Trust. As for the relationship between the variable Customer Satisfaction (Satisfaction) to Trust (Trust), Gong et al. (2018) proves that satisfaction is the antecedent of trust. Furthermore, from the differences in the results of the study, the researcher proposes a hypothesis:

H4: Customer Satisfaction has a positive and significant influence on Trust in electronic money services in Jakarta.
H5: Perceived Value has a positive and significant influence on Trust in electronic money services in Jakarta.
The Relationship between Satisfaction, Trust and Perceived Value with Continuance usage intention Customer Satisfaction and Trust is a matter that contributes to the relationship between buyers and sellers or users with providers of a service (Lee, 2017). While researching social network services (SNS), Lee (2017) grouped Trust and Satisfaction into a Relationsip Quality variable, and the variable proved to have a significant effect on Continuance usage intention and Trust’s influence was slightly stronger than Satisfaction.

Customers after assessing their level of satisfaction during and after using the service will use this information to update their perceptions and evaluate service performance by comparing with their expectations. Therefore customer satisfaction can prevent customer movement to competitors, reduce customer sensitivity to prices, reduce customer acquisition costs, keep customers loyal for longer periods of time, even encourage customers to repurchase (Oliver RL, 2015, Zeithaml et. al., 2017; Kotler et al., 2017).

This opinion is supported by almost all the results of research on the interest in continuing to use which shows that customer Satisfaction is a construct that has the greatest influence on the interest in continuing to use a service (Bhattacherjee, 2001, Susanto et al., 2016; Luqman et al., 2016 ; Zhang et al., 2015; Chen et al., 2015; Chen et al., 2012; and Chen et al., 2009), therefore a hypothesis is proposed as follows:

H6: Customer Satisfaction has a positive and significant influence on the interest in Continuing Usage Intention of electronic money services in Jakarta.
Trust is a definition that further emphasizes social and economic interactions that have uncertainty. Practically, all interactions require an element of trust, especially in the application of new technology. Trust creates a positive attitude towards individuals in technology acceptance. Therefore,
through attitude, Trust impacts on the intention to use technology and indeed trust is identified as an important factor in the adoption and use of individuals (Cheng et al., 2014; Lin et al., 2018).

Zhou (2014) concluded that Trust together with Performance expectancy, and Flow affected Continuance usage intention of mobile payment customers in China. Mittendorf (2017) in a study of ride sharing platforms, Trust on the driver has a significant effect on Continuance usage intention. This is
supported by research Shao et al. (2019) recently conducted a study of ride sharing platforms which resulted in Trust in the Platform and Trust in the driver having a significant effect on Continuance usage intention. Research Ofori et al. (2017) also supports this theory, his research proving the Trust’s direct influence on Continuance usage intention and the indirect effect mediated by Satisfaction.

H7: Trust has a positive and significant influence on the Continuation of Usage Intention of electronic money services in Jakarta.

Prodanova et al. (2019) states that Perceived Value influences Continuance usage intention in m-banking research in Macedonia. This finding shows that bank entities can increase customer interest in continuing to use M-banking (Continuance usage intention) by providing enriched values of
banking services, precisely emphasizing driving the perceived value associated with utilitarian value (ubiquity) and epistemic value (new search). The hypothesis that can be summarized based on this theory is:

H8: Perceived Value has a positive and significant effect on the Continuance usage intention of electronic money services in Jakarta.

Research Method

This study uses a multivariate data analysis method using SEM (Structural Equation Modeling). The population of this research is the community of land transportation users in DKI Jakarta. The sample of this study is land transportation users in DKI Jakarta and mobile payment customers. The research data consisted of secondary data collected through literature studies and primary data collected through questionnaires to
621 respondents.

Profile of Respondents

The following table shows 621 questionnaires from four land transportation operators who sent the questionnaires back for processing.




Analysis and discussion

Measurement model

This study uses SPSS 21 to carry out descriptive statistical analysis and Lisrel 8.80 to analyze structural equation models. To build the reliability and validity of the measurement model, a construct reliability and validity test is performed. The construct validity is tested by using a measure of the size of the loading factor (path coefficient) of each indicator and dimension. Construct Validity testing is performed using Confirmatory Model Analysis (CFA) with the Convergent Validity criteria (Hair et al., 2014). The construct reliability test uses composite reliability (CR) and average variance extracted (AVE). If CR> 0.70 and AVE> 0.50 then the construct is reliable. (Fornell C. and Larcker, D., 1981)

Table 2 shows the mean scores of each variable in the range 3.97 - 4.08, meaning that respondents gave an assessment with the agreed category on each statement for the variable. Value of α (Cronbach-Alpha) in the range 0.813 - 0.925; CR> 0.70 and AVE> 0.50.

Structural model

Analysis of the results of data processing at the full SEM model stage is carried out by conducting a model suitability test and a statistical test. After obtaining an acceptable model, which has a good fit of model data, validity and reliability with



CFA, a SEM analysis is performed. To test the hypothesis, the research is carried out using Structural Equations. Table 3 shows that every model compatibility parameter fulfills goodness of fit requirements except for Chi-Square.

The results of the hypotheses test that of the eight hypotheses tested, only one hypothesis was not accepted, namely H7: Customer Trust does not significantly affect the Continuance usage intention with β= - 0.88 ; |t-value|= 1.66< 1,97. Confirmation, Customer Satisfaction and Perceived Value variables have the contribution to explain the Customer Trust variability by 99%. Meanwhile, the Confirmation, Customer Satisfaction, Perceived Value, and Customer Trust variables explains the variability of Continuance usage intention by 70%.

The effect of Confirmation variable on Customer Satisfaction is positive and significant (γ=0.88 ; t-value = 14.61 > 1,97). Confirmation on Perceived Value is positive and significant (γ=0.89 ; t-value = 14.83 > 1,97). Confirmation on Customer Trust is positive and significant (γ=0.53 ; t-value = 3.71 > 1,97). Customer Satisfaction on Customer Trust is positive and significant (γ=0.21 ; t-value = 2.30 > 1,97). Perceived Value on




Customer Trust is positive and significant (γ = 0.29; t-value =3.23 > 1,97). Customer Satisfaction on Contiunance Intention to Use is positive and significant (γ=0.84 ; t-value = 2.68 > 1,97). Perceived Value on Contiunance Intention to Use is positive and significant (γ=0.94 ; t-value = 3.18 > 1,97).

Implications

Managerial Implications

The first is that the Trust’s direct influence on Continuance usage intention has not been proven. This implies that Trust is not mediate effect of Confirmation, Satisfaction and Perceived value on Continuance usage intention. Second, Customer Satisfaction and Perceived Value are full
mediators of the influence of Confirmation on Continuance usage intention. Whereas Perceived value and satisfaction have a positive and significant effect on Continuance usage intention, and Perceived value is the most dominant influence Continuance usage intention. Therefore, when banks, payment infrastructure providers, telecommunications operators, e-wallets and payment gateways develop strategies for increasing the level of sustainable use of electronic money, they must take into account these determinants especially on Perceived emotional value. Satisfaction also has a direct and significant effect on Continuance Usage Intention will encourage service providers to always increase user satisfaction.

Third, the effect of Confirmation on Continuous Usage Intention can be mediated by Satisfaction and Perceived value. The path mediated by Perceived value is more dominant than the path mediated by Satisfaction. Fourth, Confirmation directly affects Satisfaction, Perceived Value and Trust. It encourages providers to increase user satisfaction, perceived value and trust by meeting user needs and requirements through efficient and effective responses.

Theoretical Implications

This study is a refinement of the the Expectancy Confirmation Model / ECM model (Bhattacherjee., 2001) by integrating factors that are important for Continuance usage intention of mobile interest / e-money services, which are Confirmation, Customer Satisfaction, Perceived Value and Customer Trust. This model is used to study the continued use of a new technology after adoption. The decision to continue using is the same as the decision to repurchase in ECT because both decisions follow the initial decision, are influenced by the initial use, and have the potential to obtain the opposite
conditions from the initial decision. (Bhattacherjee, 2001). This model was modified from the Expectancy Confirmation Model (ECM) model by eliminating the perceived ease of use variable because the impact was not too significant and the user was already familiar with IT, replaced with a perceived value variable that proved to have a significant impact on Continuance usage intention and added by Trust variable (Susanto et al., 2016)
By doing that, this research model augments existing knowledge in electronic money areas. In line with the wisdom of the accumulative knowledge tradition, this research has strengthened existing understanding of the use of e-banking technology. Specifically, we confirm the role of Customer Satisfaction and Perceived Value as important variables in Continuance usage intention mobile payment /e-money services. Whereas Customer Trust is not the case.

However, the results of the study revealed that Confirmation, Customer Satisfaction and Perceived Value are important variables in Customer Trust. We also examined how Customer Satisfaction, Perceived Value and Customer Trust affect Continuance usage intention mobile payment / e-money services. Therefore, the researcher analyzes how Customer Satisfaction and Perceived Value play an important role for Confirmation to affect Customer Trust. It also confirms the important role of Customer Satisfaction and Perceived Value for Confirmation affecting Continuance usage intention mobile payment / e-money services. Then, because banking is related to sensitive financial problems, consumers need to have confidence in new banking services before using it.


References

1. AlMaghrabi, T., dan Dennis, C. (2011). What drives consumers’ continuance intention to e-shopping Conceptual framework and managerial implications in the case of Saudi Arabia. International Journal of Retail & Distribution Management, Vol. 39 Iss 12 pp. 899 – 926.

2. Bank Indonesia. (2015). Digital Financial Inclusion in Indonesia. Financial Inclusion and Electronification Task Force Bank Indonesia Transformation
Office, Jakarta.

3. Bank Indonesia. (2018). Program Elektronifikasi Sistem Pembayaran Retail. Departemen Elektronifikasi & Gerbang Pembayaran Nasional,
Jakarta.

4. Bank Indonesia. (2019). Daftar Penyelenggara Uang Elektronik yang Telah Memperoleh Izin dari Bank Indonesia. Bank Sentral Republik of
Indonesia, Jakarta.

5. Berraies, S., Yahia, K.B., dan Hannachi, M .(2017). Identifying the effects of perceived values of mobile banking applications on customers: Comparative study between baby boomers, generation X and generation Y. International Journal of Bank Marketing, Vol. 35 No. 6 pp. 1018-1038

6. Bhattacherjee, A. (2001). Understanding Information Systems Continuance: An Expectation-Confirmation Model. MIS Quarterly, Vol.
25, Iss. 3 pp. 351-370.

7. BPS Provinsi DKI Jakarta. (2018). Statistik Transportasi Jakarta 2018, BPS Provinsi DKI Jakarta, Jakarta.

8. BPTJ (2019), Strategi Implementasi Integrasi Antar Moda Transportasi di Jabodetabek, Badan Pengelola Transportasi Jabodetabek, Jakarta.

9. Chen, C.C., Wu, J., Su, Y.S., dan Yang, S.C. (2008). Key drivers for the continued use of RFID technology in the emergency room. Management
Research News, Vol. 31 Iss 4 pp. 273 – 288.

10. Chen, M., dan Qi, X. (2015). Members satisfaction and continuance intention: a sociotechnical perspective. Industrial Management & Data
Systems, Vol. 115 Iss 6 pp. 1132 – 1150.

11. Chen, S.C., Chen, H.H., dan Chen, M.F. (2009). Determinants of satisfaction and continuance intention towards self-service technologies.
Industrial Management & Data Systems, Vol. 109 Iss 9 pp. 1248 – 1263.

12. Chen, Y.T dan Chou, T.Y. (2012). Exploring the continuance intentions
of consumers for B2C online shopping Perspectives of fairness and trust.
Online Information Review, Vol. 36 Iss 1 pp. 104-125
13. Cheng, Y.M. (2014). Extending the expectation-confirmation model with
quality and flow to explore nurses’ continued blended e-learning intention.
Information Technology & People. Vol. 27 No. 3, 2014 pp. 230-258.
14. Coulter, K. S. dan Coulter, R. A. (2002). Determinants of Trust in a Service
Provider: the Moderating Role of Length of Relationship. Journal of
Services Marketing, Vol. 16 No. 1, pp 35-50.
15. Ding, Y. dan Chai, K.H. (2015). Emotions and continued usage of mobile
applications. Industrial Management & Data Systems, Vol. 115 No. 5, pp.
833-852.
16. Dutka, A. (1993). AMA Handbook for Customer Satisfaction: A Complete
Guide to Research, Planning, and Implementation. (International ed.).
Illinois: NTC Business Books.
17. Eugene C.A., Basha N.K., Siew I. N. dan Sambasivan, M. (2019). To
grab or not to grab? The role of trust and perceived value in on-demand
ridesharing services. Asia Pacific Journal of Marketing and Logistics, Vol.
31 No. 5, pp. 1442-1465.
18. Ferdinand, A. 2006. Metode Penelitian Manajemen: Pedoman Penelitian
untuk Penulisan Skripsi, Tesis, dan Disertasi Ilmu Manajemen. Badan
Penerbit Universitas Diponegoro, Semarang.
19. Fitriani, F.F. (2018, May 22). Presiden Go-Jek: Ada 22 Juta Pengguna
Aktif, 30%-40% di Jakarta, Bisnis.com, Jakarta.
20. Fornell, C., and Larcker, D. F. (1981). Evaluating Structural Equation
Models with Unobservable Variables and Measurement Error. Journal of
Marketing Research, Vol.18 Iss1 pp. 39-50.
21. Ghozali, I. dan Latan, H. (2012). Partial Least Square: Teknik dan
Applikasi SmartPLS 2.0M3. Badan Penerbit Universitas Diponegoro,
Semarang.
22. Gil-Saura, I., Frasquet-Deltoro, I., dan Cervera-Taulet, A. (2009), The
value of B2B relationships. Industrial Management & Data Systems, Vol.
109 No. 5, 2009 pp. 593-609
23. Gong, X., Liu, Z. dan Zheng, X. (2018). Why are experienced users
of WeChat likely to continue using the app?. Asia Pacific Journal of
Marketing and Logistics, Vol. 30 No. 4 pp. 1013-1039.
24. Goudarzi, S., Ahmad, M. N., Soleymani, S.A., dan Mohammadhosseini,
N. (2013). Impact of Trust on Internet Banking Adoption: A Literature
Review. Australian Journal of Basic and Applied Sciences, Vol 7 (7) pp.
334-347.
25. Grigoroudis, E., Siskos Y. (2010). Customer Satisfaction Evaluation:
Methods for Measuring and Implementing Service Quality. Springer,
Technical University of Crete, Chania, Greece.
26. Ha, Y.W. dan Park, M.C. (2013). Antecedents of customer satisfaction and
customer loyalty for emerging devices in the initial market of Korea: an
equity framework. Psychology & Marketing, Vol. 30 No. 8, pp. 676-689.
27. Hair, J.F., Black, W.C., Babin, B.J., dan Anderson, R.E. (2014).
Multivariate Data Analysis, Pearson International, 7th edition. Pearson
Education Limites, London.
28. Hair, J.F., Bush, R.P., dan Ortinau, D.J. (2002). Marketing Research:
Within a Changing Information Environment. McGraw-Hill Education,
New York.
29. Heffernan, T., O’Neill, G., Travaglione, T., dan Droulers, M. (2008),
Relationship marketing: The impact of emotional intelligence and trust on
bank performance. International Journal of Bank Marketing, Vol. 26 No.
3, 2008 pp. 183-199
30. Hong, S.J., Thong, J.Y.L. dan Tam, K.Y. (2005). Understanding Continued
IT Usage: An Extension to the Expectation-Confirmation Model in IT
Domain. Pacific Asia Conference on Information Systems (PACIS) 2005
Proceedings, 105. pp 1267-1280
31. Hu, H.H., Kandampully, J., & Juwaheer, T. D. (2009). Relationships and
impacts of service quality, perceived value, customer satisfaction, and
image: an empirical study. The Service Industries Journal, 29(2), 111-125.
32. Jarvenpaa, S.L., Tractinsky, N. dan Vitale, M. (2000). Consumer trust in
an Internet store. Information Technology & Management, Vol 7 (1-2) pp.
45-71.
33. Khan, A., Gandhi, M., Jain, A., Khacolia, N. (2016). Emerging Markets
Driving the payments transformation. Price Waterhouse Cooper, UK
London.
34. Khan, N. (2010). Functional and relational value influence on commitment
and future intention: The case of banking industry. The Journal of
International Social Research, 3(10), 377-391.
35. Kim, D. J., Ferrin, D. L., dan Rao, H. R. (2003). Antecedents of Consumer
Trust in B-to-C Electronic Commerce. (2003). Proceedings of the
Americas’ Conference on Information Systems. 2013 pp. 157-167.
36. Kim, H,W., Koh, J., dan Lee, H.L. (2009). Investgating the Intention
of Purchasing Digital Items in Virtual Communities. Pasific Asian
Conference on information Systems (PACIS), 18
37. Koller, M., Floh, A., Zauner, A. (2011). Further insights into perceived
value and consumer loyalty: A ‘Green’ perspective. Psychology &
Marketing, 28(12), 1154-1176.
38. Kotler, P., Armstrong, G. dan Opresnik, M.O. (2017). Principles of
marketing, Pearson, Edisi Global ke 17, Harlow England.
39. Larsen, T.J., Sorebo, A.M., dan Sorebo, O. (2009). The role of tasktechnology
fit as users’ motivation to continue information system use,
Computers in Human Behavior, Vol 25 pp. 778–784.
40. Lee, S., Kim, B.G. (2017). The impact of qualities of social network
service on the continuance usage intention, Management Decision, Vol.
55 Issue: 4, pp.701-729.
41. Lin, J., Li, L. Yan, Y., dan Turel, O. (2018). Understanding Chinese
consumer engagement in social commerce: The roles of social support and
swift guanxi. Internet Research. Vol. 28 No. 1, pp. 2-22
42. Luqman, A., Razak, R.C., Ismail, M., dan Alwi, M.A.M. (2016).
Continuance Intention of Mobile Commerce Usage Activities: Does
Personal Innovativeness Matter?. The Social Sciences, Vol 11 pp. 2817-
2827.
43. Mayer, R.C., Davis, J.H., dan Schoorman, F.D. (1995). An Integrative
Model of Organizational Trust. Academy of Management Review, 20 (3),
709-734.
44. McKnight, D.H., Choudhury, V. dan Kacmar, C. (2002). Developing
and validating trust measures for e-commerce: An integrative typology.
Information Systems Research, 13 (3), pp.334-359.
45. Mittendorf, C. (2017). The Implications of Trust in the Sharing Economy
– An Empirical Analysis of Uber. Proceedings of the 50th Hawaii
International Conference on System Sciences, pp 5837- 5846
46. Morar, D.D. (2013). An overview of the consumer value literature
perceived value. International Conference. Marketing from Information to
Decision, 6th ed. p169-186.
47. Ofori, K.S., Boateng, H., Okoe, A.F., dan Gvozdanovic, I. (2017).
Examining customers’continuance intentions towards internet banking
usage. Marketing Intelligence & Planning, Vol. 35 No. 6 pp. 756-773
48. Oliver, R. L. (1980). A cognitive model of the antecedents and consequences
of satisfaction decisions. Journal of marketing research, 460-469.
49. Oliver, R.L. (2015). Satisfaction: A behavioral perspective on the customer.
Routledge, edisi ke 2, New York.
50. Peng, L., dan Liang S. (2013). The effects of consumer perceived value
on purchase intention in e-commerce platform: A time-limited promotion
perspective. Proceedings of the Thirteen International Conference on
Electronic Business, December, 1-4. p56.


51. Prodanova, J., Shuleska, A.C., dan Sterjadovska, N.P. (2019). Enriching
m-banking perceived value to achieve reuse intention. Marketing
Intelligence & Planning Vol. 37 No. 6, pp. 617-630.
52. Robson, B. (2017). Retail payments in Indonesia: Who will drive the
cashless revolution?. KPMG Siddharta Advisory, Jakarta.
53. Roy, S.K., dan Shekhar, V. (2010). Dimensional hierarchy of
trustworthiness offinancial service providers. International Journal of
Bank Marketing, Vol. 28 No. 1, 2010 pp. 47-64.
54. Sekaran, U., dan Bougie, R. (2016). Research Method for Business : A
Skill-Building Approach. John Wiley & Sons Ltd, West Sussex UK.
55. Sekretariat Kabinet RI. (2016). Peraturan Presiden RI No. 82 Tahun 2016
Tentang Strategi Nasional Keuangan Inkusif, Lembaran Negara Republik
Indonesia Tahun 2016 Nomor 185, Sekretariat Kabinet RI, Jakarta.
56. Setyowati, D. (2019, September 10). Babak Baru Pertarungan Gojek dan
Grab di Tiga Layanan. Katadata.co.id, Jakarta.
57. Shao, Z., dan Yin, H. (2019). Building customers’ trust in the ridesharing
platform with institutional mechanisms: An empirical study in China.
Internet Research Emerald Publishing Limited, pp. 1066-2243.
58. Sheth, J.N., Newman, B.I. dan Gross, B.L. (1991). Why we buy what we
buy: a theory of consumption values. Journal of Business Research, 22(2):
159-170.
59. Singh, H. (2006). The Importance of Customer Satisfaction in Relation
to Customer Loyalty and Retention. Asia Pacific University College of
Technology & Innovation Technology Park Malaysia, UCTI Working
Paper, pp. 1-6.
60. Stauss, B., dan Seidel, W. (2019). E¬fective Complaint Management, The
Business Case for Customer Satisfaction. Springer, Edisi ke 2, Cham-
Switzerland.
61. Suh, B. dan Han, I. (2002). Effect of trust on customer acceptance of
Internet banking. Electronic Commerce Research and Applications
Volume 1, Issues 3–4, Autumn–Winter 2002, Pages 247-263.
62. Susanto, A., Chang, L.Y. dan Ha, Y. (2016). Determinants of continuance
intention to use the smartphone banking services. Industrial Management
& Data Systems, Vol. 116 Iss 3 pp. 508 - 525.
63. Sweeney, J.C. dan Soutar, G.N. (2001). Consumer perceived value: the
development of a multiple item scale. Journal of Retailing, Vol. 77 No. 2,
pp. 203-220.
64. Taylor, E. (2016). Mobile payment technologies in retail: a review of
potential benefits and risks. International Journal of Retail & Distribution
Management, Vol. 44 Iss 2 pp. 159 – 177.
65. Widarjono, A. (2007). Ekonometrika: Teori dan aplikasi untuk ekonomi
dan bisnis. Ekonisia FE UII, Yogyakarta.
66. Xin, H., Techatassanasoontorn, A. A., dan Tan, F.B. (2013). Exploring the
Influence of Trust on Mobile Payment Adoption. PACIS 2013 Proceedings.
Paper 143.
67. Yu, P.L., Balaji, M.S., Khong, K.W. (2015). Building trust in internet
banking: a trustworthiness perspective. Industrial Management & Data
Systems, Vol. 115 Issue: 2, pp.235-252.
68. Zeithaml, V.A. (1988). Consumer perceptions of price, quality and value:
A means-end model and synthesis of evidence. Journal of Marketing, 52,
2-22.
69. Zeithaml, V.A., Bitner, M.J., dan Gremler, D.D. (2017). Services
Marketing: Integrating Customer Focus Across the Firm. McGraw-Hill
Education, Edisi ke 7, New York.
70. Zhang H., Lu Y., Gupta S., dan Gao P. (2015). Understanding groupbuying
websites continuance An extension of expectation confirmation
model, Internet Research, Vol. 25 Iss 5 pp. 767 – 793.
71. Zhou, T. (2013). Understanding continuance usage of mobile sites.
Industrial Management & Data Systems, Vol. 113 Iss 9 pp. 1286 – 1299.
72. Zhou, T. (2014). Understanding the determinants of mobile payment
continuance usage. Industrial Management & Data Systems, Vol. 114 Iss
6 pp. 936 – 948.

ARJ @ SOCIAL

openaccess

Testimonials

Indexing

Indexing