study of individual's behavioral intention in using m-tix as a

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STUDY OF INDIVIDUAL’S BEHAVIORAL INTENTION IN USING M-TIX AS A DIGITAL PAYMENT METHOD BASED ON INNOVATION DIFFUSION THEORY

Andi Riskyah Rahmadanti Arafah

Faculty of Economics and Business, Universitas Brawijaya [email protected]

Supervisor:

Dr. Zaki Baridwan, Ak., CA., CPA.,CLI., CTA

ABSTRACT

This study aims to examine the consumer intention to use M-Tix services for the purchase of online cinema tickets provided by Cineplex Group based on Innovation of Diffusion Theory.

The data from this research are analyzed using Structural Equation Modeling (SEM) based on Partial Least Squares (PLS). The respondents were 303 active undergraduate students from the Accounting Department in the Faculty of Economics and Business, Universitas Brawijaya. The results of this study indicate that behavioral intention to use M-Tix is significantly and positively influenced by relative advantage, trialability, observability, compatibility, and perceived ease of use. However, complexity has negative influence towards behavioral intention. Thus, it can be concluded that high relative advantage, trialability, observability, compatibility and perceived ease of use will highly affect the intention to use M-Tix.

Keywords: E-money, IDT, Relative Advantage, Complexity, Trialability, Observability, Compatibility, Perceived Ease of Use, Behavioral Intention, M-Tix.

ABSTRAK

Penelitian ini bertujuan untuk menguji minat konsumen pada penggunaan layanan M-Tix untuk pembelian tiket bioskop online yang disediakan oleh Cineplex Group kepada penggunanya berdasarkan Teori Inovasi Difusi (IDT). Data penelitian ini dianalisis dengan menggunakan model persamaan struktural (SEM) berdasarkan Partial Least Squares (PLS). Responden adalah 303 mahasiswa S1 aktif dari jurusan akuntansi Fakultas Ekonomi dan Bisnis, Universitas Brawijaya Hasil penelitian ini menemukan bahwa keuntungan relatif, triabilitas, observabilitas, kompatibilitas dan persepsi kemudahan berpengaruh positif terhadap behavioral intention. Namun kompleksitas berpengaruh negatif terhadap behavioral intention. Dengan demikian, dapat disimpulkan bahwa semakin tinggi keuntungan relatif, triabilitas, observabilitas, kompatibilitas dan persepsi kemudahan semakin tinggi efek terhadap minat untuk menggunakan M-Tix.

Kata kunci: E-Money, IDT, Keuntungan Relatif, Kompleksitas, Trialabilitas, Observabilitas, Kompatibilitas, Persepsi Kemudahan, Behavioral Intention, M-Tix.

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I. Introduction

Technology is changing significantly faster than the media or institution that consumers traditionally rely on to inform and enforce their choices. The pace of technology development is unpredictable (Sunny, Patrick, &

Rob, 2018). Information technology has become an integral part of modern human lives. People use it to facilitate the functioning of nearly all life domains. In line with the rapid developments in informatics and technology, the qualities expected of an individual has also changed.

Today, utilizing the available technologies to get the information that is changing and growing continually is not a privilege, but a must. The individuals are required to know how to access information, how to utilize it for their needs, and to keep up with the developing country (Topaloglu & Tekkanat, 2015).

With the development of e- commerce, there is a continuous transformation of payments from brick-and-mortar retailers to online systems. As a result, a large number of online payment systems (e- payments) have been developed using

debit/credit cards and virtual payment systems or e-wallets (e.g., Paypal) (Casado-Aranda, Liébana-Cabanillas,

& Sánchez-Fernández, 2018).

The increasing quality of national films lately has made people more interested in watching movies of domestic’s production. Head of the Creative Economy Agency, Triawan Munaf said that at the end of 2017, the number of Indonesian film viewers reached 42.7 million viewers, a significant increase from 16 million viewers in 2015. The growth in the number of viewers, he said, made the film industry's revenue also increased by 10.09% from 2016. The growth was the second-highest after the creative economy sub-sector in the television and radio industry (CNBC Indonesia, 2018).

Cineplex 21 Group is one of the cinema companies in Indonesia which has developed an internet-based ticket purchase service and has the most cinema network in Indonesia.

Cineplex 21 Group controls the overall market share of Indonesian cinema viewers by imposing varying ticket prices and types of films shown, according to the location and target theater. Cineplex 21 Group has an

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internet-based ticket purchase service known by consumers as M-Tix. M- Tix has the primary objective of providing convenience and efficiency services to consumers when they want to make a cinema ticket purchase transaction. M-Tix is an online purchase transaction service that offers consumers cinema ticket purchase without coming to the counter, and it can be done everywhere (Kusno, 2013).

Research conducted by Al- Jabri and Sohail (2012) showed that relative advantage, compatibility, and observability have a positive impact on adoption. Contrary to the findings in the extant literature, trialability and complexity have no significant effect on adoption. Perceived risk has a negative impact on adoption. The findings of this study will have practical implications for the banking industry in Saudi Arabia. Moreover, research by Aisyah (2019) showed that relative advantage, compatibility, trialability, and observability positively affect individual interest in using financial technology services in Yogyakarta district, meanwhile, complexity negatively affects

individual interest in using financial technology services.

Furthermore, research conducted by Al-Rahmi et al. (2019) found that six perceptions of innovation characteristics, in particular, have impacts on students’

e-learning system behavioral intention. The influences of the relative advantages, observability, trialability, perceived compatibility, complexity, and perceived enjoyment on the perceived ease of use is noteworthy.

All variables in the Innovation Diffusion Theory have been discussed in many studies in previous years, regarding their influence on customer behavior in using technology (Al-Jabri and Sohail, 2012; Aisyah, 2019; and Al-Rahmi et al., 2019). The researcher is interested in studying to find out more about the reasons as to why consumers buy cinema tickets on M-Tix. To discuss the phenomena, the researcher used The Innovation of Diffusion Theory as a determinant of consumer interest in using M-Tix to purchase cinema tickets online among consumers who had used the M-Tix.

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II. Literature Reviews 2.1 M-Commerce

According to Alatas (2013), m- commerce is defined as the process of transactions carried out using a mobile device. M-commerce is a subset of e-commerce. M-commerce is the use of mobile devices (handhelds) to communicate and make transactions through public and private networks; there is no concept of formalization of m-commerce today (Peterson and Jarvenpaa, 2002).

2.2 E-Money

E-money is defined as a stored value or prepaid product where a record of funds or benefits available to consumers is stored on consumer electronic devices. According to Soefrianto et al. (2012), e-money is a payment platform issued based on value by the holder to the issuer, the amount of money stored electronically in media such as servers or chips is used as a means of payment to traders who are not electronic money issuers, and e- money value stored and managed by the publisher is not a deposit as stated in the banking constitution.

2.3 M-Tix

According to Kusno (2013), M- Tix is a long-distance ticket purchase

service that offers customers the purchase of cinema tickets without having to queue and can be done anywhere if the need for access to these services were met. According to Augusto et al. (2018), the M-Tix mobile application is an Android- based mobile application launched by Cinema 21 Group since 2015 that offers online cinema ticket booking services. M-Tix is a remote transaction ticket purchase service that is an added value for consumers (Indira and Dirnaeni, 2017).

2.4 Technology Acceptance Model The definition of perceived ease of use is the degree to which a person believes that using a particulars system would be free of physical and mental efforts (Davis, 1989). Ease of use is defined as a level or situation in which a person believes that using a particular system is not required to do anything (free of effort), or in other words, the user can easily understand the technology. Nasution (2004) stated that information technology users believe that information technology is more flexible, easy to understand and easy to operate as a user-friendly characteristic.

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2.5 Innovation Diffusion Theory Innovation Diffusion consists of two- word equivalents, namely diffusion and innovation. Rogers 1995 in Sciffman and Kanuk (2010) the diffusion of innovation is a process of spreading the absorption of ideas or new things in an effort to change a society that occurs continuously from one place to another, from one time to another the following, from a particular field to another field to a group of members of the social system.

2.5.1 Relative Advantage

Relative advantage is the extent of innovation perceived better than before (Rogers, 1983). One of the theoretical models and relevant studies pointed out the positive impact of relative advantage on behavioral intention was conducted by Lee et al. (2011). The first hypothesis is developed in this study as follows:

H1: Relative Advantage has a positive influence on Behavioral Intention to use M-Tix.

2.5.2 Complexity

Complexity is a level the complexity of an innovation to be adopted (Rogers, 1983). Complexity

has a negative relationship when choosing a new system. The lower the level of complexity of an innovation to be understood, the faster the innovation is adopted. Conversely, the more complicated an innovation is to be understood, the longer the innovation is to be adopted (Bauer et al., 2005).

Wulandari et al. (2017) concluded that complexity negatively affected the intention to use Mocash LPG BRI. This is seen in terms of the level of suitability of the product innovation to be applied. Consumers are more willing to adopt an innovation when they feel that it is compatible with their experience and beliefs. The second hypothesis is developed in this study as follows:

H2: Complexity has a negative influence on Behavioral Intention to Use M-Tix.

2.5.3 Triability

The possibility of trialability is the extent to which innovation can be tested before being adopted (Rogers, 1983). The research conducted by Agarwal and Prasad (1997) found that the possibility of a trial affected 6 adopting the current use of information technology.

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A researcher Lee et al. (2011) provided that studies on e-learning have also found that trialability has a positive effect, not only on the perceived ease of use of e-learning, but also on the intention to accept e- learning. The third hypothesis is developed in this study as follows:

H3: Triability has a positive influence on Behavioral Intention to Use M- Tix.

2.5.4 Observability

(Observability) according to Rogers (1983) is a measure above whether or not an innovation is easy to observe. Various layers of society can accept the faster innovation, the easier the change is to observe the results and vice versa when the community agrees with the old innovation, the results of the innovation will be difficult to follow the results. Bennett and Bennett (2003) defined observability as an easy way to observe, imagine, and describe a technology to users.

Al-Rahmi et al. (2019) provided that observability can affect student's behavioral intention to use the E- Learning system. As for the behavioral intention to use E- Learning, technology and resources

are key issues that need to be taken into consideration. This implies that students should seize the opportunity of having plenty of technological resources due to the fact that this can positively influence their learning performance. The fourth hypothesis is developed in this study as follows:

H4: Observability has a positive influence on Behavioral Intention to use M-Tix.

2.5.5 Compatibility

Conformity is the

compatibility of innovation with values and beliefs of the users with ideas and needs before the introduction of new innovations (Cho, 2006). Hsu (2007) argued that suitability influences the interest in adopting mobile internet. Hung et al.

(2006) stated that there is an influence between conformity with the attitudes of users of e-government services.

This result is consistent with the research of Crespo and Rodriguez (2007) which stated that suitability has a significant influence on the attitude of using shopping services over the internet. Artha’s research (2011) also showed that conformity has a significant effect on the use of e-commerce in students of the

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Accounting and Business Department of Universitas Brawijaya, Malang.

The fifth hypothesis is developed in this study as follows:

H5: Compatibility has a positive influence on Behavioral Intention to Use M-Tix

2.5.6 Perceived Ease of Use Perceived ease of use is the level of measure in which a person believes that the technology system is easy to understand and easy to use without must try hard in its use (Davis, 1989). According to Jogiyanto (2007: 115), perceived ease of use is how far someone believes that the technology system makes it easier for the person to inside use it.

This perceived ease of use is also a belief about the decision making process.

Ease of use is the degree to which individuals believe that the technology adopted is easy to use or free of effort to use it (Govindaraju and Indriany, 2007). Hsu (2007) suggested that ease of use has a positive effect on user adoption of mobile banking. Previous studies conducted by Adiyanti (2015) and Wibowo et al. (2009) concluded that the perceived ease of use has a

significant and positive effect on the intention to use e-money. The sixth hypothesis is developed in this study as follows:

H6: Perceived Ease of Use has a positive influence on Behavioral Intention to use M-Tix.

Figure 2.1 Theoretical Framework

Source: Researcher, 2019 III. Research Methodology

This research is a quantitative study, the data will be collected from the distribution of research instrument called questionnaires, and further, the data collected will be presented in the form of numbers. The study was conducted at Universitas Brawijaya, Faculty of Economics and Business and the research subjects were Undergraduate Accounting Student who has been used or still use M-Tix.

The population used was all Undergraduate Accounting Studentent who has been used or still use M-Tix. This study used a nonprobability i.e convenience

Relative Advantage Complexity

Triability

Observability Compability

Perceived Ease of Use

Behavioral Intention

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sampling design for research sampling. According to Roscoe (1975) in Sekaran (2013: 269). The researcher distributed the online questionnaires directly to the research sample via google form and 303 questionnaires were returned.

The hypothesis developed in this study was tested using Partial Least Square (PLS). According to Barclay et al., (1995) stated that the PLS model is analyzed and interpreted in two steps, first, the assessment of reliability and validity of the measurement model or called as the outer model, which is used to test the validity and reliability of the study variables; second, the assessment of structural models or called as the inner models, which is used to test the hypothesis.

IV. Finding and Discussion 4.1 Data Collection Results 4.1.1 Respondents

Respondents used in This research is Undergraduate Accounting Student of Universitas Brawijaya. The results of data collection through the distribution of online questionnaires received are as follows:

Figure 4.1 Usable Responds

Source: Primary Data (Processed), 2019 4.1.2 Demographic Characteristics

Figure 4.2 Demographic Characteristics 1 Age Respondents Percentage

<18 5 1.65%

18-20 122 40.26%

21-23 164 54.13%

>23 12 3.96%

2 Semester Respondents Percentage

1 5 1.65%

3 48 15.84%

5 63 20.79%

7 85 28.05%

>7 102 33.66%

3 Gender Respondents Percentage

Female 168 55.4%

Male 135 44.6%

4

Duration in Using M-

Tix in a year

Respondents Percentage

<2 Times 46 15.18%

2 - 4 Times 78 25.74%

4 - 6 Times 83 27.39%

>6 Times 96 31.68%

Source: Primary Data (Processed), 2019 4.2 Outer Model

Outer model is used to test the validity and reliability of variables in the study. In testing the validity using SmartPLS consists of two types of testing, namely convergent validity and discriminant validity.

Description Questionnaire Questionnaires are distributed 350 Questionnaires are not returned 24 Questionnaires are returned 326 Questionnaires that are unusable 23 Questionnaires which are usable 303

Response Rate 93%

Usable Response Rate 87%

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4.2.1 Convergent Validity Test According to Hartono (2015:

195), the rule of thumb for convergent validity loading factor (outer loading) should be valued greater than 0.70 (>

0.70). Based on Table 4.1, it is known that the loading factor (outer loading) of all indicators has a value greater than 0.70 (> 0.70) in the original sample (O) column, and the statistical value of each construct is greater than 1.64. So it can be concluded that the constructs and indicators used in this study are valid.

Table 4.1 Outer Loadings

RA CX TR OB CT EOU BI

RA1 0.8777 RA2 0.7788 RA3 0.7257 RA4 0.7901 RA5 0.8698

CX1 0.8833

CX2 0.8874

CX3 0.8394

CX4 0.7927

CX5 0.7598

TR1 0.8423

TR2 0.8930

TR3 0.9054

OB1 0.8389

OB2 0.7388

OB3 0.8898

OB4 0.8842

CT1 0.8664

CT2 0.8111

CT3 0.9044

CT4 0.8762

EOU1 0.9122

EOU2 0.9255

EOU3 0.9397

EOU4 0.9385

BI1 0.9345

BI2 0.9506

BI3 0.9564

Source: Primary Data (Processed), 2019 Description:

RA: Relative Advantage; CX: Complexity;

TR: Triability; OB: Observability ; CT:

Compatibility; EOU: Perceive Ease of Use;

BI: Behavioral intention.

Table 4.2

AVE and Communality Results

Source: Primary Data (Processed), 2019

The rule of thumb for convergent validity Average Variance Extracted (AVE) shoule be valued greater than 0.50 (> 0.50), and the communality is greater than 0.50 (> 0.50). Based on Table 4.2, it is known that the AVE value of all indicators has a value greater than 0.50 (> 0.50), and the Communality value of each indicator is greater than 0.50 (> 0.50).

Therefore, it can be concluded that the indicators used in this study are valid.

4.2.2 Discriminant Validity Test Based on Table 4.3, it is known that all indicators that compile each variables in this study (valued in bold) have fulfilled the rule of thumb value which is greater than 0.70 (>

0.70). Thus, all indicators of each variable in this study have met discriminant validity.

AVE Communality RA 0.656848 0.656848 CX 0.695603 0.695603 TR 0.775574 0.775574 OB 0.705725 0.705725 CT 0.748565 0.748565 EOU 0.863122 0.863122 BI 0.897265 0.897265

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Table 4.3 Cross Loadings

RA CX TR OB CT EOU BI

RA1 0.878 -0.498 0.582 0.564 0.603 0.612 0.640 RA2 0.779 -0.323 0.644 0.563 0.552 0.442 0.550 RA3 0.726 -0.385 0.546 0.499 0.454 0.494 0.407 RA4 0.790 -0.461 0.457 0.472 0.450 0.570 0.574 RA5 0.870 -0.506 0.635 0.635 0.583 0.658 0.641 CX1 -0.503 0.883 -0.466 -0.487 -0.505 -0.549 -0.567 CX2 -0.491 0.887 -0.456 -0.471 -0.447 -0.564 -0.551 CX3 -0.459 0.839 -0.440 -0.394 -0.416 -0.482 -0.439 CX4 -0.357 0.793 -0.394 -0.363 -0.421 -0.428 -0.405 CX5 -0.424 0.760 -0.326 -0.348 -0.335 -0.439 -0.492 TR1 0.551 -0.429 0.842 0.588 0.558 0.473 0.485 TR2 0.646 -0.497 0.893 0.645 0.618 0.608 0.678 TR3 0.653 -0.394 0.905 0.659 0.673 0.575 0.614 OB1 0.532 -0.375 0.625 0.839 0.637 0.525 0.551 OB2 0.580 -0.507 0.543 0.739 0.608 0.713 0.530 OB3 0.584 -0.393 0.639 0.890 0.648 0.591 0.634 OB4 0.576 -0.417 0.604 0.884 0.628 0.569 0.621 CT1 0.517 -0.462 0.567 0.610 0.866 0.581 0.578 CT2 0.449 -0.415 0.494 0.590 0.811 0.586 0.518 CT3 0.636 -0.477 0.683 0.711 0.904 0.676 0.665 CT4 0.645 -0.417 0.667 0.672 0.876 0.642 0.631 EOU1 0.628 -0.560 0.546 0.633 0.642 0.912 0.625 EOU2 0.650 -0.547 0.604 0.661 0.674 0.926 0.684 EOU3 0.647 -0.543 0.611 0.650 0.663 0.940 0.683 EOU4 0.639 -0.564 0.590 0.692 0.696 0.939 0.665 BI1 0.664 -0.590 0.638 0.655 0.674 0.707 0.935 BI2 0.663 -0.537 0.684 0.665 0.658 0.662 0.951 BI3 0.674 -0.566 0.618 0.662 0.643 0.664 0.956

4.2.3 Reliability Test

Based on Table 4.4, the values of Cronbach's alpha and Composite reliability shown an amount greater than the rule of thumb (> 0.70). So, it can be concluded that all constructs or variables used in this study are reliable.

Table 4.4 Cronbach’s Alpha and Composite Reliability Results Independent

Variable

Composite Reliability

Cronbach’s Alpha

RA 0.905 0.869

CX 0.919 0.890

TR 0.912 0.857

OB 0.905 0.859

CT 0.922 0.888

EOU 0.962 0.947

BI 0.963 0.943

4.3 Inner Model

The inner model or structural model in SmartPLS is evaluated using R² for the dependent construct and path coefficient values.

Table 4. 5 R² Result Variable R² (R Square)

BI 0.6653

Table 4.5 shows the R-square value for the BI variable obtained at 0.6653. This value indicates that 66.53% of the Behavioral Intention (BI) Variable can be influenced by the Relative Advantage, Complexity, Triability, Observability, Compatibility, and Perceived Ease of Use variables. While the remaining

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33.47% is influenced by other variables outside the study.

4.3.1 Hypothesis Testing

Path coefficient in table 4.6 shows a significant level on hypothesis testing. The hypothesis used in this study is a one-tailed hypothesis with a T-statistic value greater than 1.64 for the hypothesis acceptance.

Table 4.6 Path Coefficient Original T Statistics

Hypothesis Sample (O) (|O/STERR|)

RA -

> BI 0,1375 2.769 Supported CX -

> BI -0.161 2.344 Supported TR -

> BI 0,098611111 2.101 Supported OB -

> BI 0,964583333 2.197 Supported CT -

> BI 0,963888889 2.080 Supported EOU

-> BI 0,135416667 2.810 Supported Source: Primary Data (Processed), 2019

Description:

4.4 Discussion and Results Based on hypothesis testing that has been done, researchers able to prove that the constructs of relative advantage, triability, observability, compatibility and perceived ease of use have a significant positive effect on the intention to use M-Tix.

However, complexity has significant negative effect on the intention use M-Tix.

4.4.1 Relative Advantage on Behavioral Intention

Based on Table 4.6, shows the T-statistic value of 2.769, which is more than 1.64, so it can be concluded in this study H1 is supported. Thus, hypothesis 1 (H1) states that the relative advantage has positive and significant effect on the intention use M-Tix.

This result is consistent with research conducted by Al-Jabri et al., (2012) conducted research to examine a number of factors affecting mobile banking adoption in Saudi. It implies that those customers who find mobile banking a useful and convenient way of managing their finances efficiently and effectively will tend to adopt it.

This result also supported by Indriyati and Aisyah (2019) to determine factors which influence individual interest in using financial technology services by Innovation Diffusion Theory (IDT) framework in Yogyakarta. Thus, financial technology has been considered fully superior to facilitate individuals in making transactions because it can increase individual effectiveness in

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transactions and foster confidence in individuals because they feel more modern and create comfort and satisfaction for individuals who use financial technology services. This results are also supported by Wulandari et al., (2018) in Bandar Lampung and Sholahuddin (2017) investigated the influence of innovation characteristic to an intention to adopt Solopos e-paper

The results of this research indicate that students feel like using M-Tix as a means of payment is better and also faster than using cash as a means of payment. The students also experience the real benefit by M-Tix as a means of payment. The more people can benefit relative to M-Tix, the faster the M-Tix is adopted.

4.4.2 Complexity on Behavioral Intention

Based on Table 4.6, shows the T-statistic value of 2.344, which is more than 1.64, so it can be concluded in this study H2 is supported. Thus, hypothesis 2 (H2) states that the complexity has negative and significant effect on the intention use M-Tix.

This result consistent with research conducted by Pu’o et al., (2018) to examine the factors

affecting the interest of taxpayers in using the e-Filling facility that are listed in Poso, Tax Office. The result shows that complexity affects negatively the intention to use e- Filling. This result also supported by Kurniawati (2018) to determine the complexity of using e-filling in KPP Pratama Sukoharjo. Taxpayers are able to use information technology, easy to understand the complexity of the presentation in the e-filling system, and taxpayers are able to interpret the e-filling system, taxpayers decide to always use the e- filling system so on in reporting tax returns. This result is also supported by Wulandari et al., (2018) in Bandar Lampung.

The results of the study showed that the student had no difficulty in using M-Tix. The student also has no difficulty in understanding the features found in M-Tix. These results can be caused because the respondents in this research were mostly people with the age range of 17-25 years old. People with this age range tend to be more open to innovations. Also, most respondents tend to be familiar with technology,

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so there is no difficulty in using M- Tix.

4.4.3 Triability on Behavioral Intention

Based on Table 4.6, shows the T-statistic value of 2.101, which is more than 1.64, so it can be concluded in this study H3 is supported. Thus, hypothesis 3 (H3) states that the triability has positive and significant effect on the intention use M-Tix.

This result is consistent with research conducted by Al-Rahmi et al. (2019) to explore and investigate the potential factors influencing students’ behavioral intentions to use the e-learning system in Malaysia.

The study stated that trialability has in turn affect students’ behavioral intention to use the E-Learning system. This study also supported by Eric Osei-Assibey (2014) to investigates factors that determine one’s intention to adopt the MM space as saving channel in Ghana, West Africa The study found that trialability to be statistically significant in influencing one’s behavioral intention to accept MM.

this result is also supported by Shiau et al. (2016) in Taiwan.

The results of the study showed that students use M-Tix as they want to test the features that are available on M-Tix and when deciding to use M-Tix, students believe they have nothing to lose.

4.4.4 Observability on Behavioral Intention

Based on Table 4.6, shows the T-statistic value of 2.197, which is more than 1.64, so it can be concluded in this study H4 is supported. Thus, hypothesis 4 (H4) states that the observability has positive and significant effect on the intention use M-Tix.

This result is consistent with research conducted by Al Jabri et al.

(2012) to examines a number of factors affecting mobile banking adoption in Saudi. It implies that mobile banking service fits well in the manner customers manage their finances, is suitable for their working and lifestyle, therefore, they like to adopt new innovations. This study is also supported by Kim et al. (2018) to determine factors that influence their decision to adopt mobile learning in South Korean undergraduate students. Indicating that mobile learning is more readily adopted when it is consistent with conventional

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learning methods or individuals’

values. This results are also supported by Septiani et al. (2017) in Indonesia and Ugur et al. (2016) at Sakarya University.

The result of the study showed that M-Tix is suitable for student’s lifestyles and ideal for transaction activities in purchasing e-ticket movies.

4.4.5 Compatibility on Behavioral Intention

Based on Table 4.6, shows the T-statistic value of 2.080, which is more than 1.64, so it can be concluded in this study H5 is supported. Thus, hypothesis 5 (H5) states that the compatibility has positive and significant effect on the intention use M-Tix.

This result is consistent with research conducted by Septiani et al.

(2017) investigated factors that affect the user’s behavioral intention on one of the online transportation services in Indonesia: GO-JEK The result also stated that compatibility positively affects behavioral intention on the use of GO-JEK. This study also supported by Ugur et al. (2016) to predict their acceptance attributes based upon diffusion of innovation (DOI)

framework towards the usage of m- learning. The objectives of the research are to determine the usage level of mobile learning and to identify the factors that the learners’

intentions to adopt are a relative advantage, compatibility, complexity, observability, and trialability in School of Management at Sakarya University. This research shows that compatibility with the university technological infrastructure and value system further strengthens the students’ intention of m-learning adoption. This result is also supported by Al-Jabri et al., (2012).

The result of the study showed that M-Tix is suitable for student’s lifestyles and ideal for transaction activities in purchasing e-ticket movies.

4.4.6 Perceived Ease of Use on Behavioral Intention

Based on Table 4.6, shows the T-statistic value of 2.810, which is more than 1.64, so it can be concluded in this study H6 is supported. Thus, hypothesis 6 (H6) states that the Perceived Ease of Use has positive and significant effect on the intention use M-Tix.

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This result is consistent with research conducted by Pratama (2019) to find out perceived usefulness, perceived ease of use, and trust in the interest to use e-money in the Faculty of Economics and Business, Universitas Udayana. The research found that perceived ease of use has a positive influence on the intention to use e-money. This study also supported by Syahril and Rikumahu (2019) developed research by using Technology Acceptance Model (TAM) to test the effect of perceived usefulness, perceived ease of use, and perceived risk on student intention to use e-money in Universitas Telkom. The result stated that perceived ease of use has a positive influence on the intention to use e-money. This result of study is also supported by Ismail (2016) in Semarang.

The result of the study showed that the students perceive M-Tix as a technology that will be beneficial to them. Using M-Tix is also helpful, saving times and less costly.

V. Conclusion and Recommendation 5.1 Conclusions

This research aims to investigate the influence of relative advantage,

complexity, trialability, observability, compatibility, and perceived ease of use towards the behavioral intention of undergraduate accounting students at Faculty of Economics and Business, Universitas Brawijaya in using M-Tix. This research tests the construction of Innovation Diffusion Theory (IDT) where relative advantage, triability, observability, compatibility have positive and significant toward the intention to use M-Tix. However, complexity has negative and significant effect towards the intention to use M-Tix.

5.2 Research Implications

According to the result of this research, people, especially students, feel M-Tix is beneficial for them, so Cineplex 21 Group or other third- parties in order to attract more customers are expected to always innovate on M-Tix. Cineplex 21 Group or other third-parties must develop M-Tix while maintaining to reduce the level difficulty of the application that can occur, so customers feel that M-Tix is beneficial, useful, and easy to use.

5.3 Research Limitation

There are also drawbacks in the use of convenience sampling,

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including lower generalization rates than other sampling procedures.

Nonetheless, the method of convenience sampling is chosen, as the researcher has no data on the number of students in Universitas Brawijaya's Faculty of Economics and Business who have ever used M- Tix or still using it.

5.4 Recommendation

Suggestions that can be given for further research is extending the time used to wait for respondents to fill out and return the questionnaire, so that the number of questionnaires returned can be more. The researcher should be able to find information about the population to be studied.

This is intended in order to facilitate researchers in determining the number of samples to be studied, so that the result of the sample can be more representative for the entire population in the study.

References

A Kurniawati. (2018). Analisis Faktor-faktor Minat Perilaku

Wajib Pajak untuk

Menggunakan. E-filing (Studi Empiris di KPP Pratama Sukoharjo). Prosiding Seminar Nasional Akuntansi, Manajemen, dan Keuangan ke III, 2018.

Adiyanti, Arsita Ika. 2015. Pengaruh Pendapatan, Manfaat, Kemudahan Penggunaan, Daya Tarik Promosi, dan Kepercayaan terhadap Minat menggunakan layanan E-money. Jurnal Ilmu Ekonomi Univeristas Brawijaya.

Agarwal, R. & Prasad, J. (I997). The Role of Innovation

Characteristics and Perceived Voluntariness in the Acceptance of Information Technologies.

Decision Sciences, 28 (3), I997, 557-582

Alatas, Z., & Achmad. (2013).

Rancang Bangun dan Implementasi Aplikasi Mobile Commerce Berbasis Android di Toko Batik Qonita Pekalongan.

Al-Jabri, I. M., & Sohail, M. S.

(2012). Mobile Banking Adoption : Application of diffusion of innovation theory.

Journal of Electronic Commerce research, 13.

Al-Rahmi, Yahaya, Aldraiweesh, Alamri, Aljarboa, Alturki, and Aljeraiwi. (2019). Integrating Technology Acceptance Model With Innovation Diffusion Theory: An Empirical Investigation on Students’

Intention to Use E-Learning Systems. Open Journal Volume 7 Augusto, Y., Rachmadi, A., &

Herlambang, A. Analisis Kesuksesan Aplikasi Mobile Pemesanan Tiket Bioskop M-Tix Cinema 21 Berdasarkan Perspektif Pengguna di Kota

Malang Menggunakan

Pendekatan Delone and McLean Success Model. Jurnal Pengembangan Teknologi

(17)

Informasi dan Ilmu Komputer, vol. 3, no. 1, p. 07-12, agu. 2018.

ISSN 2548-964X

BEKRAF. Ekonomi Kreatif Mesin Baru Kemakmuran Ekonomi.

Retrieved 16 Agustus 2018, from https://www.cnbcindonesia.com/

lifestyle/20180227195654-33- 5686/penonton-film-nasional- capai-427-juta-penonton-di-2017 Bennett, J. and Bennett, L. (2003), “A

review of factors that influence the diffusion of innovation when structuring a faculty training program”, The Internet and Higher Education, Vol. 6, pp. 53- 63.

Bougie, R., & Sekaran, U. (2013).

Research methods for business (6th edition). John Wiley & Sons Ltd

Casado-Aranda, L. A., Liébana- Cabanillas, F., & Sánchez- Fernández, J. (2018). A Neuropsychological Study on How Consumers Process Risky and Secure E-payments. Journal of Interactive Marketing, 43, 151–164.

https://doi.org/10.1016/j.intmar.

2018.03.001

Cho, V. 2006. a study of the roles of trust and risks in informaton- oriented online legal services using an integrated model.

Information and Management.

Vol. 43 502 – 520

CNBC Indonesia. Penonton Film Nasional Capai 427 Juta Penonton di 2017. Retrieved 16

Agustus 2018 from

https://www.cnbcindonesia.com/

lifestyle/20180227195654-33-

5686/penonton-film-nasional- capai-427-juta-penonton-di-2017 Crespo, A.H., & Rodr•´guez, I.A.

Del. (2007). Explaining B2C e- commerce acceptance: An integrative model based on the framework by Gatignon and Robertson. Interacting with Computers, 20, 212–224

Davis, F. (1989). Perceived Usefulness, Perceived Ease Of Use, And User Acceptance of Information Technology. MIS Quarterly, 319.

Eric Osei-Assibey. (2014). What drives behavioral intention of mobile money adoption? The case of ancient susu saving operations in Ghana.

International Journal of Social Economics Vol. 42 No. 11, 2015.

Govindaraju, R., dan Indriany, N.

(2007). Studi Mengenai Penerimaan Sistem ERP:

Enhancement terhadap Model Penerimaan Sistem ERP Berbasis TAM. National Industrial Engineering Conference No.4 Hsu, C. L., Lu, H. P., & Hsu, H. H.

(2007). Adoption of the Mobile Internet: An Empirical Study of Multimedia Message Service (MMS). International Journal of Management Science.

Hung, S., Chang, C., and Yu., (2006).

Determinants of user acceptance of the eGovernment services:

The case of online tax filing and payment system. Government Information Quarterly. Vol.23.

pp.97 – 122.

(18)

Indira dan dirnaeni. (2017). Pengaruh Pemanfaatan M-TIX Terhadap Minat Pembelian Tiket Bioskop Online di XXI Mall Metropolitan Bekasi. Universitas Gunadarma Junral Volume 11 No. 12.

Indriyati and Aisyah. (2019).

Determinan Minat Individu Menggunakan Layanan Financial Technology dengan Kerangka Innovation Diffusion Theory.

Jurnal Nominal Volume VII No.

2.

Ismail, Harries Arizona. (2016).

Intention to Use Smartphone through Perceived Compatibility, Perceived Usefulness, and Perceived Ease of Use. Jurnal Dinamika Manajemen, 7 (1) 2016, 1-10

Jogiyanto, H.M., 2005, Analisa dan Desain Sistem Informasi:

Pendekatan Terstruktur Teori dan Praktik Aplikasi Bisnis, ANDI, Yogyakarta

Kusno. (2013). Analisis Faktor- Faktor yang Mempengaruhi Intensi Penggunaan M-Tix Sebagai Layanan Pembelian Tiket Menonton Film Bioskop Jaringan Cinema XXI Indonesia:

Pendekatan Technology Acceptance Model (TAM).

Skripsi. Yogyakarta: Universitas Gadjah Mada.

Kim and Jong-Youn. (2018).

Predicting the Drivers of the Intention to Use Mobile Learning in South Korea. http://www.i- jim.org.

Lee, Y.-H., Hsieh, Y.-C., & Hsu, C.- N. (2011). Adding Innovation Diffusion Theory to the Technology Acceptance Model:

Supporting Employees' Intentions to use E-Learning Systems. Educational Technology & Society, 14 (4), 124–137.

Peterson, A., Robert, Jarvenpaa, L., &

Sirkka. (2002). Exploring the Implications of M-Commerce for Markets and Marketing. 348- 361.

Pratama and Suputra. (2019).

Pengaruh Persepsi Manfaat,

Persepsi Kemudahan

Penggunaan, dan Tingkat Kepercayaan Pada Minat Menggunakan Uang Elektronik.

E-Jurnal Akuntansi Universitas Udayana Vol.27.2.

Pu’o, Sondakh, Budiarso. (2018).

Analisis Faktor-Faktor yang Mempengarhui Minat Wajib Pajak Orang Pribadi dalam Menggunakan E-Filling Sebagai Sarana Pelaporan SPT pada KPP Pratama Poso. Jurnal Riset Akuntansi Going Concer 13(3).

Rogers, E. M. 1983. Diffusion of Innovations. Third Edition. New York: The Free Press.

Septiani, Handayani and Azzahro.

(2017). Factors that Affecting Behavioral Intention in Online Transportation Service: Case study of GO-JEK. 4th

Information Systems

International Conference 2017, ISICO 2017, 6-8 November 2017, Bali, Indonesia

(19)

Sholahuddin. (2017). pasca pengaruh karakteristik inovasi terhadap niat mengadopsi solopos epaper.

tesis. surakarta: universitas Surakarta

Sunny, S., Patrick, L., & Rob, L.

(2018). Impact of cultural values on technology acceptance and technology readiness.

International Journal of Hospitality Management, (June).

https://doi.org/10.1016/j.ijhm.20 18.06.017

Syahril and Rikumahu. (2019).

Penggunaan Technology Acceptance Model (TAM) dalam Analisis Minat Perilaku Penggunaan E-Money pada Mahasiswa Universitas Telkom.

Jurnal Mitra Manajemen Vol. 3 No. 2

Topaloglu, M., & Tekkanat, E.

(2015). Identifying the Usage of Information Technologies and Literacy Levels. Procedia - Social and Behavioral Sciences,

182, 574–583.

https://doi.org/10.1016/j.sbspro.

2015.04.784

Ugur and Tugba. (2016). Diffsuion of M-Learning: Sakarya University Case. Education Research Highlights in Mathematics, Science and Technology 2016.

Wibowo, Setyo F., Dede R., Usep S.

(2015). Pengaruh Persepsi Manfaat, Persepsi Kemudahan, Fitur Layanan, dan Kepercayaan Terhadap Minay Menggunakan E-Money Card (Studi Pada Pengguna Jasa Commuterline di Jakarta). Jurnal Riset Manajemen Sains Indonesia (JRMSI) | Vol. 6, No. 1.

Wulandari, bangsawan, bursan.

(2017). Pengaruh Inovasi Produk (Keuntungan Relatif,

Kompatibilitas dan

Kompleksitas) Terhadap Niat Penggunaan Mobile Banking BRI (Studi pada Agen LPG 3 Kg di Bandar Lampung). Jurnal bisnis dan manajemen volume 13 No. 3.