Subscribers’ intention towards using 3G mobile services

: 3G mobile network offers higher data rates than the previous generation networks (1G and 2G). The purpose of this study is to examine the factors influencing subscribers’ intention towards using 3G mobile services with the Technology Acceptance Model (TAM) as the guiding principle. Cross sectional data were collected through a survey and analyzed by means of factor analysis, correlation and regression analysis. Out of 150 questionnaires, only 100 were usable. Findings show that Perceived Usefulness, Perceived Ease of Use and Attitude are jointly responsible in determining the subscribers’ intention to use of 3G mobile services. Perceived Usefulness was found as a key factor influences subscribers’ intention to use 3G mobile services. In addition, implications and direction for future research are discussed.


Introduction
Third Generation (3G) mobile network is the third generation of mobile networks that offer higher data rates than the previous generation networks (1G and 2G). It offers data rates of 144 Kbps for fast-moving mobile users in vehicles, 384 Kbps for slower moving pedestrian users, and 2 Mbps from fixed locations. While 1G as the first generation which emerged in the 1940s offers wide area low bandwidth, just less than 10 kbps. It used analog technology. 1G can only be used for voice service. 2G as the second generation, launched in the 1990s, offers data rates only between 10 and 20 kbps. It can be used for both voice communication and short message service (SMS) (Lehr and McKnight, 2003).
There has been a steady growth in worldwide 3G mobile adoption. However, there also exists a wide range of 3G diffusion levels across countries. For example, the region of Asia trumped all others in 3G adoption with close to 52 percent of the world 3G market share as early as in (International Telecommunication Union, 2006. More recently, Asia-Pacific was home to an estimated 158 million 3G subscribers in 2008 and is expected to reach 564 million subscribers by 2013 (Suppiah, 2009). Historically, Korea, Italy, Japan, Portugal and Hong Kong were the top five 3G mobile economies in terms of 3G mobile penetration rate (International Telecommunication Union, 2006). According to the official International Telecommunication Union report, while the number one 3G nation, Korea, had a penetration rate as high as 25.95 percent, the number five country, Hong Kong, reached only about one third of Korea's rate (8.19 percent). It is evident that there are significant regional differences in the number of 3G subscribers. While close to half of the 3G subscribers are located in the region of Asia, less than thirteen percent of them are in Europe.
Research on 3G technology acceptance, therefore will be extremely worthy in providing useful information, especially at this early stage of 3G mobile Internet development and implementation. It is thus imperative to understand the interplay of factors involved in the adoption of this technology. The purpose of this study is to examine the factors influencing subscribers' intention towards using 3G mobile services with the Technology Acceptance Model (TAM) as the guiding principle. This study will be primarily beneficial to the mobile services provider since they can understand the subscribers' perception of the services. Furthermore, the results of this study may allow them to better segment and target the market.

Literature Review
The number of 3G subscribers increased significantly, thus it represents consumers' willingness to adopt advance wireless technology and engage in activities using systems where 3G can provide more comprehensive contents than other wireless services. Pagani (2004) conducted a study to identify the determinants of adoption of 3G mobile multimedia services and found that perceived usefulness, ease of use, price, and speed of use are the most important determinants of adoption of 3G multimedia mobile services. The importance of determinants differs by age groups or segments.
Furthermore, Performance Expectancy has positive influence towards Behavioral Intention" and "Use behavior". The practicability of system is still the major influential factor that influences the users to use technological service. "Facilitating Conditions" has positive influence towards "Behavioral Intention" and "Use behavior". "Social Influence" of 3G mobile telecommunication services, has positive influence towards "Behavioral Intention" and "Use behavior". "Behavioral Intention" of 3G mobile telecommunication services, has positive influence towards "Use behavior" (Wu, Tao, and Yang, 2008). Providing insight into those factors influencing acceptance of technology in the consumer context, the Technology Acceptance Model (TAM), shown in Figure 1, has been considered the most useful for predicting the usage of such technology. This model, described by Davis, Bagozzi, and Warshaw (1989), is based on construct and relationships in the theory of reasoned action (TRA) (Adams, Nelson, and Todd, 1992;Dishaw and Strong, 1999).
The TAM was mainly derived from the TRA, which posited that an individual's willingness, rational decisionmaking, attitude and Subjective Norm will affect his/her Behavioral Intention. Subjective norm refers to an individual's belief that she/he should perform a certain behavior because this is expected of him/her by others important to the individual (Fishbein and Ajzen, 1975). According to TRA, Attitude and Subjective Norms independently affect intentions, whereas in the TAM, Perceived Usefulness and Perceived Ease of Use are believed to directly affect a person's attitude. Davis et al, (1989) found the Subjective Norm did not significant affect intentions over and above Perceived Usefulness and Perceived Ease of Use and therefore omitted it from the original TAM.  Ortega, Martinez, and Hoyos (2006) have empirically tested the basic constructs to of TAM without any external variables to apply on acceptance of online business management and industry effect. With the help of 3G wireless technology, operators can provide 3G services associated with a variety of entertaining and enjoyable services content (Lehr and McKnight, 2003). Thus, the objective of this study is to provide a theoretically justified research model that extends TAM by proposing the addition of PE to the use of 3G services, and to empirically test factors influencing usage of 3G mobile services.

Perceived Usefulness (PU)
In the investigation of Chau (1996), he hypothesized that behavioral intention to use a particular technology is dependent on the two variables, which are perceived usefulness and perceived ease of use. The empirical findings supported his hypothesized relationships between perceived usefulness and intention to use. Different from motivation theory, Davis et al. (1989) defined PU as 'the prospective user's subjective probability that using a specific application system will increase his or her job performance within an organizational context'. Based on his definition, Adams et al. (1992) and Davis et al. (1989) Subramanian (1994) reaffirmed two belief measurements (PU and PEOU) using a new data set for two different technologies, and found PU, and not PEOU, had a direct effect on usage behavior employing structural equation modelling (SEM). In this study, we define PU as the degree to which an individual believes that use of 3G mobile services will improve his or her communicational performance. Therefore, we posited that:-H1. PU will have a positive effect on BI towards using 3G mobile services.

Perceived Ease of Use (PEOU)
Linkages between PEOU, PU and attitude in TAM theory have been empirically verified in the IT literature. Several studies have employed different usage measures and found them consistent with TAM results, that is, these two beliefs have a close correlation to attitude (Adams et al., 1992;Burton-Jones and Hubona, 2005;Igbaria, Zinatelli, Cragg, and Cavaye, 1997). Perceived ease of use has also been found to influence behavioural intention to use indirectly through perceived usefulness (Norazah, Ramayah & Norbayah, 2008). Many studies have also tested the effects of external variable on PEOU (Hong, Thong, Wong, and Tam, 2002;Igbaria et al., 1997), and found such effect fully independent of PEOU (Compeau, Higgins, and Huff, 1999;Venkaetesh and Davis, 2000). Here, we define ease of use as the extent to which customer' use of 3G mobile services is perceived as easy or effortless. Accordingly, we hypothesize that:-H2. PEOU will have a positive effect on BI towards using 3G mobile services.

Perceived Enjoyment (PE)
If the user can experience enjoyment through the adoption of new technology, attitude toward adoption will be positive. A person will be more motivated to do or repeat an enjoyable activity that is enjoyable more as compared to the same activity which is not enjoyable. A number of studies on PE (Davis, 1992;Igbaria et al., 1997) have indicated that PE significantly affects intention to use computers. Prior studies of the WWW and mobile commerce have empirically added PE to the TAM to predict user acceptance and adoption of a specific source, and found this construct has a positive effect on attitude towards using a specified system (Bruner and Kumar, 2005;Dabholkar, 1996;Moon and Kim, 2001). In this study, we define PE as the degree to which a person believes that use of 3G mobile services will be interesting and associates it with enjoyment. Therefore, we hypothesize that:-H3. PE will be having a positive effect on BI towards using 3G mobile services.

Attitude (ATT)
Attitude has long been identified as a cause of intention. In terms of 3G mobile services, their features can be viewed as mere extension of GSM services with major differences in speed and bandwidth to access gain to the wireless network. Most customers today are likely to have been exposed to 3G mobile phones and to have formed an attitude towards using them, ranging from very favorable to very unfavorable. Prior empirical studies have shown the existence of such generalize attitude and its influences on the evaluation of new technology in similar situations (Lederer, Maupin, Sena, and Zhuang, 2000;Moon and Kim, 2001;O'Cass and Fenech, 2003;Vijayasarathy, 2004). In this research, attitude is hypothesized to the influences of the intention towards using 3G mobile services, and is defined as the degree to which an individual's attitude is favorably or unfavorably disposed towards using 3G mobile services. Accordingly, we hypothesized that:-H4. Attitude will have a positive effect on BI towards using 3G mobile services.

Behavioral Intention (BI)
Behavioral Intention to use is a measure of the likelihood that a person will adopt the application, where as the TAM uses actual usage to represent a self-report measure of time or frequency of adopting the application (Davis et al., 1989). However, it is not easy or practical to obtain an objective measurement of an individual's intention to engage in behavior. Several researches have shown that both theoretical and empirical support exists for the powerful correlation between intention to engage in a behavior and actual behavior (Dabholkar and Bagozzi, 2002;Lucas and Spitler, 1999;Vijayasarathy, 2004). To maintain instrument brevity, we adopt behavioral intention as an individual's intention to use 3G mobile services. All things considered, Figure 2 illustrates the theoretical framework of the study.

Methodology
Out of 150 questionnaires, only 100 were usable. The questionnaire consists of two main parts: demographic profile of respondents and perceptions and attitude towards using 3G mobile services. Measurement of items used was adapted from Davis (1992). Cross sectional data were collected through a survey and analyzed by means of factor analysis, correlation and regression analysis via Statistical Package for Social Sciences (SPSS) version 16 computer program. Factor analysis technique used to measure KMO of sampling to confirm the appropriateness of proceeding with analysis to reduce the number of items and identity the dimensions of talent variables. While, correlation and regression used to looking for association between two metric variables and to test any cause and effect between two variables respectively.

Profile of Respondents
A statistical elaboration of the sample took place. The gender distribution of the survey respondents is 40 per cent males and 60 per cent females. The results also indicated that the samples have age predominantly between 25 and 35 years, which is 75 per cent. More than 90 per cent of the respondents are working adults with monthly salary RM2501-3000.

Factor Analysis
The Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy was used to confirming the appropriateness of proceeding with the analysis to reduce the number of items, and identify the dimensions of latent variables. Any item that failed to load on a single factor at 0.5 or less will be dropped but there was none of items were dropped in this analysis. The factor analysis process of dropping an item was repeated until all items loaded at 0.5 or greater on one and only one factor (Lederer et al., 2000;Vijayasarathy, 2004). Results of factor analysis are shown in Table 1.

Perceived Usefulness
The Perceived Usefulness factor comprises five statements with 64.781% of variance and an eigenvalue of 3.239. KMO for this factor is 0.783 and all five statements had factor loading greater than 0.50 without any exception. The most important statements claimed by the respondents was "convenient to use 3G services" (0.874 ), "efficient to use 3G services" (0.845) and " relaxing" (0.811).

Perceived Usefulness
Perceived Ease of Use Perceived Enjoyment Behavioral Intention towards using 3G Mobile Services Attitude

Perceived Ease of Use
The second factor, Perceived Ease of Use, was accounted for 75.509% of variance and an eigenvalue of 3.020. The KMO result for this factor is 0.834 and none of four statements were dropped from the analysis since the factor loading greater than 0.50. All four Perceived Ease of Use statements which were rated positively includes "3G services are understandable and clear" (0.911) "I learned to use 3G services quickly" (0.862) "it is easy to use 3G services" (0.857) and "it is simple to use 3G services" (0.844).

Behavior Intention
There were three statements loaded in Behavior Intention factor, which relates to intention toward using 3G mobile services. Table 1 stated that the most important statement in this factor was "willing to use 3G services in future" (with the highest loading of 0.926), followed by "willing to use 3G services" (0.908) and "recommend someone to use 3G services (0.863). 80.887% of variance and 2.427 of eigenvalue was accounted for this factor with KMO 0.720.

Perceived Enjoyment
The Perceived Enjoyment factor comprises six statements with 58.077% of variance and an eigenvalue of 3.485. All statements had factor loading greater than 0.50, with the exception of "using the 3G services guide me to explore novelty" and a "great diversity of 3G services can excite me with more imagination space" which was dropped from the analysis. The most important statements claimed by the respondents was "interesting to use 3G services" (0.832), "enjoyable to use 3G services" (0.818) and "delightful using the 3G services" (0.812). KMO for this factor is 0.866.

Attitude
The final factor grouped dimensions related to Attitude factor which accounted for 58.143% of the variance with eigenvalues of 2.326 and KMO is 0.662. The most important variable, as affirmed in Table 1, was that they "using the 3G services is good attitude" (0.860) followed by "using 3G services is good idea" (0.815).

Reliability Analysis
The reliability of scale indicates that the study is free from random error. Internal consistency is measured in this research using Cronbach's coefficient alpha, ( ). The statistic provides an indication of the average correlation among all of the items that make up the scale. Values range from 0 to 1 with higher values indication greater reliability. Table 2 indicates the result of analysis of the Cronbach's alpha scale for Perceived Usefulness, Perceived Ease of Use, Behavior Intention, Perceived Enjoyment, and Attitude where its value is more than 0.7. This indicates that the survey instrument (questionnaire) can be a reliable tool to measure all constructs consistently. Moreover, all of the measures of constructs had been used in past studies, and have thus been validated.

Correlation Analysis of Variables
Pearson correlations were calculated to identify the correlations between the variables and to describe the relationship of the dependent variable and the outcome. All the major variables were correlated together using the correlation test. The average score of the multi-items for a construct was computed since a single construct in the questionnaire was measured by multiple items, and the score was used in further analysis such as correlation analysis and regression analysis (Wang and Benbasat, 2007). As cited in Wong and Hiew (2005) the correlation coefficient value (r) range from 0.10 to 0.29 is considered weak, from 0.30 to 0.49 is considered medium and from 0.50 to 1.0 is considered strong. However, according to Field (2005), correlation coefficient should not go beyond 0.8 to avoid multicollinearity. Since the highest correlation coefficient is 0.524 which is less than 0.8, there is no multicollinearity problem in this research (Table 3).

Multiple Regression Analysis
Multiple Regression analysis was performed to test the hypothesis relationship between independent and dependent variables. Four hypotheses were proposed and results were enumerated in Table 4. The Fstatistics produced (F = 19.175) was significant at 1 per cent level (Sig. F<0.01), thus confirming the fitness for the model. Therefore, there is a statistically significant relationship between the four factors (Perceived Usefulness, Perceived Ease of Use, Perceived Enjoyment, and Attitude) and Behavior Intention towards using 3G mobile services. The coefficient of determination R 2 was 44.7 per cent. Thus, the four factors can significantly account for 44.7 per cent in the subscriber's intention towards using 3G mobile services.  Adams et al. (1992) and Davis et al. (1989) stating that Perceived Usefulness is a major determinant of usage behavior and intention. When it is being used frequently, people will find it generally good and perceive it as something useful.
Further investigation of study was performed on second proposed hypothesis on whether there is significant relationship between Perceived Ease of Use and Behavior Intention towards 3G mobile service. Findings in Table 4 confirmed that Perceived Ease of Use ( = 0.224; t = 2.372; p = 0.020) is significantly related to Behavior Intention towards 3G mobile service. Hence, H2 is verified. The positive intention to use 3G mobile services is due to the reasons that subscriber's learned to use 3G services quickly and unearth that it is easy to use it. It has been suggested that as systems become easier to use and users become more skilled, the variation in the ease of use construct is reduced, especially for the current Internet and e-commerce environment. This corroborates the finding by Davis et al. (1989). Next, H3 exhibited a significant relationship between Perceived Enjoyment and Behavior Intention towards using 3G mobile services ( = -0.013; t =-0.156). Its p-value is > 0.05, posited that H3 is not supported by the data. Great diversity of 3G services can excite subscribers' with more imagination space that lead them to experience enjoyable towards using 3G mobile services. Enjoyment and well-designed interface of the 3G mobile services able to give user positive experience and therefore repeat usage. However, results does not substantiate studies on Perceived Enjoyment by Davis (1992), Igbaria et al. (1997) who have indicated that Perceived Enjoyment significantly affects intention to use computers.
The final hypothesis, H4 proposed that Attitude will have a positive effect on Behavior Intention towards using 3G mobile services. Attitude exhibited a significant relationship with Behavior Intention towards using 3G mobile services ( = -0.316; t = -3.762). Its p-value is < 0.05, posited that H4 is strongly supported. Using the 3G services is good attitude and a good idea. Thus, the significant role of Attitudes in shaping Behavioral Intention has been visible when a relationship between the Attitude and Behavioral Intention has been studied. The assumption that Attitudes have a strong, positive direct influence on intention to use mobile devices/services is reinforced when the coefficients of the Attitude is examined (refer Table 4).

Conclusion and Recommendations
This paper has examined the factors influencing subscribers' intention towards using 3G mobile service with the Technology Acceptance Model (TAM) as the guiding principle. Results showed that subscribers' intention to use 3G mobile services is determined by their perception on its usefulness and how convenient it is to use and access 3G mobile services' functions. Further, the results highlighted the importance of perceived ease of use towards 3G mobile services' in terms of how easy or effortless it is to communicate with each other. 3G offers a vertically integrated, top-down, services provider approach to delivering wireless Internet access. For practitioners and stakeholders of 3G deployment, these are the two most important factors to keep in mind when offering 3G services. The 3G standard is able to support broadband services include: voice, audio, text, still image, dynamic video; interactive services such as conversations, messages, and restore and storage; distribution services such as point-to-multipoint broadcasts; location-based mobile information services; data services that are dependent on the radio connection; fixed wireless access for broadband connections; wireless packet service for Internet access; and wireless circuit service for voice and low-speed data connections since its data transmission rates are about 2Mbps in indoor communications and less than 1Mbps in outdoor communication.
Among the four factors, only Perceived Enjoyment was proven to be insignificantly influencing the Behavioral Intention towards using 3G mobile services. Perceived Enjoyment may be a necessary condition, but not the sufficient criterion to lift consumers' intention to adopt 3G mobile services. This is unusual exception to general technology acceptance situations and thus it is worthy of the consideration of the 3G mobile telecommunication companies. All things considered, the current findings significantly enhance understanding of user acceptance of mobile communication services. This study can act as a reference for those researchers that are interested in this field of Information Systems. Results suggest users' of 3G mobile services need to be provided with more diverse and entertaining ways of communicating, which are at the same time easily accessible and convenient to use. Future research can extend the study to different samples and extended the proposed model to include other technology adoption factors. The model could also be used to study the adoption of other technologies apart from 3G.