Abstract - Recent years, mobile technology has become increasingly common in today’s everyday life. However, the data shows that the usage rate of cell phone video call in China is still very low. The conceptual model extend the original TAM by including subjective norm, perceived risk, perceived compatibility and consumer innovativeness, to make it more effective in predicting users’ acceptance of phone video call. The empirical result analyzes the key driver of acceptance of phone video call and provides a theoretic way to raise the usage rate and efficiency of it. This research defined the barriers that obstruct phone video call diffusion in China and then it end up with recommendations for firm’ decision makers, to improve phone video call in their firms, as well as recommendations for future researches with in the same scope of this research. We also hope to do some contributions to the current theoretic frame of consumer innovative actions.
Keywords - phone video call, diffusion of innovation, Technology Acceptance Model, intention to use
I. INTRODUCTION
Driven by the increasing mobility of today’s modern society, the number of mobile phone users has significantly increased in recent years. In particular, as a key increment business of mobile operators, the countries all over the world has a positive forecast for cell video call. Cell phone video call technology has huge development potential. Globally, not only Europe and the United States but also South Korea, cell video call has become increasing popularity. In contrast, since 3G network construction of China starts relatively late, the usage rate of cell phone video call is still in a very low level at present. Just a few number of China mobile consumers are using this service, while huge range of China consumers don’t using it, and others not even heard of it. Thus, the actual market penetration of phone video call services deviates from previous predictions seriously.
Along with the demand for promotion and popularization of 3G technology in China, the issues that consumers how to accept or reject this business has become increasing focused and concerned by academic circles. It is quite deficiency and exigent to use systematic analysis to cell phone video calls for the country's consumer behavior and characteristics of technology adoption. In view of this, using theory and method of innovation diffusion and technology acceptance, this thesis will analyze the question of why consumers have not accept phone video call, and will study the key factors in consumers’ acceptance of phone video call services, offer theory according and meaningful guide for managers how can enhance the number of customers who choose this way of communication as an alternative to more traditional communication mode effectively. For this purpose, the research extended the original TAM by including new constructs and collected 422 usable samples from a representative sample of 500 respondents. Then we used the structural equation modeling software Lisrel8.70 to test a theory-based research model of phone video call acceptance.
The outline of the current article is as follows: First, we extend the original technology acceptance model TAM, to make it more effective in predicting users’ acceptance of technologies, related to mobile services in general, the acceptance of cell video call in particular in China. Based on the literature review and the preliminary study, the researcher extended the original TAM by adding some key constructs (perceived risk, perceived compatibility and consumer innovativeness). Then we present our hypotheses to find the barriers that obstruct the diffusion of phone video call in China and make Chinese customers unwilling to adopt this service, And also; to give imaginations and solutions for solving this problem.
II. LITERATURE REVIEW
In the IT/IS literature, many models have been advanced to predict users’ new technology usage [1]. Among them, the technology acceptance model (TAM), proposed by Davis [2], and has evolved as the most popular. TAM has seen many applications and extensions In the IT/IS field since its development. The benefits of TAM include reliable instruments with empirical soundness, conciseness and excellent measurement properties. TAM is also applied to a wide range of research questions, including attitude toward self-service solutions [3], wireless LAN usage [4], and adoption of internet banking [5].
TAM is predictive model, but in fact it usually does not provide sufficient understanding with the necessary information to create user acceptance for new technology and services, thus; many researchers have extended the original model to make it more affective, such as perceived enjoyment in the internet, perceived critical mass in groupware usage, perceived user resources in a bulletin board system, perceived playfulness in the web context, and compatibility in a virtual store. Moreover, many extended perception variables have been added to TAM in previous studies in specific contexts.
III. HYPOTHESES
The original technology acceptance model (TAM) separated between attitude and intention to use. According to the TAM, attitude towards using a technology has a positive direct effect on intention to use [6] [7]. The implied relationship is reflected by our first hypothesis:
H1: Attitude towards using phone video call has a positive direct effect on the intention to use phone video call.
According to diffusion theory, users are only willing to accept innovations which provide a unique advantage compared to existing solutions [8]. This research adopts the definition perceived usefulness that was given by Davis; “subjective probability that using a specific application or technology will increase his or her job performance within an organization context” [2]. The original technology acceptance model (TAM), suggested that Perceived usefulness can affect users intention to use technology indirectly through its influence on attitude towards use. Hence:
H2: Perceived usefulness of phone video call has a positive direct effect on the attitude towards using phone video call.
IN the original technology acceptance model (TAM), perceived ease of use is considered as a major influence on attitude towards a technology. This influence appears clearly from the individual’s evaluation of the mental effort involved in using the technology. Consequently, we incorporate perceived ease of use of phone video call in our research model. Also it has been found that perceived ease of use can influence users’ perceived usefulness of the technology [6]. Hence:
H3: Perceived ease of use of phone video call has a positive direct effect on the attitude towards using phone video call.
H4: Perceived ease of use of phone video call has a positive direct effect on perceived usefulness of phone video call.
The original technology acceptance model (TAM), doesn’t include the impact of social influence on the decision of adopting technology. Social information can influence individual innovation decisions over and above the traditional sources of influence such as individual use of the system. Thus, social pressure is also was one of the motivations which can affect technology acceptance. Venkatesh and Davis extend the original TAM by including subjective norm as an additional factor, and the empirical study found that subjective norm not only directly influence consumers’ intention to use, also to consumers’ assessment to it usefulness[6]. Accordingly, we present hypothesis:
H5: Subjective norm has a positive direct effect on the intention to use phone video call.
H6: Subjective norm has a positive direct effect on perceived usefulness of phone video call.
The external variables, which were added to the research model, can also have an impact on consumer’s decision of using phone video call; perceived compatibility was found to have an impact on consumer’s decision to adopt new technology. Tornatzky and Klein find perceived compatibility to be an important innovation characteristic driving consumer acceptance [9]. Extant research shows perceived compatibility both has positive effects on the attitude toward using a technology and perceived usefulness. In view of these findings, we hypothesize the following:
H7: Perceived compatibility of phone video call has a positive direct effect on perceived usefulness of phone video call.
H8: Perceived compatibility of phone video call has a positive direct effect on the attitude towards using phone video call.
We further extend the original technology acceptance model by including the perceived risk of phone video call as an additional factor. Innovations usually come with varieties of risks (such as technical complexity, high prices, and the novelty). Huang and Chuang, based on the theories of planned behavior (TPB), make perceived risk as a new variables influencing innovation adoption, and the results show that the effect is remarkable [10]. Lwin[11], Chen[12], Kim[13] also found the perceived risk of consumers and the attitude towards using unknown technical products has an obvious negative correlation, and proved by empirical evidences. Hence:
H9: Perceived risk of phone video call has a negative direct effect on the attitude towards using phone video call.
Innovation diffusion theory suggests that the early adopters and later adopters are different in personality traits and character. Some studies hold it as a general individual personality, and define this potential tendency to accept new products as consumer innovativeness. Therefore consumer innovativeness will have a strong effect on their adopting to any new technology. Steenkamp[14], Zhang[15] and Chen[16]’s empirical studies found that consumers’ consumer innovativeness have a certain promotion effects on their attitude towards using innovation. Thus, we present hypothesis:
H10: Consumer innovativeness has a positive direct effect on the attitude towards using phone video call.
The consumer acceptancemodel appears in Fig. 1.
Fig. 1. Conceptual model.
IV. SURVEY AND DATA ANALYSIS
A. Survey
The survey was conducted using a standardized questionnaire, and there were a total of 28 measurement items in the questionnaire of the survey. For the research questionnaire, the researcher choose a five-point Likert scale and the codes from 1 (“quite disagree”) to 5 (“quite agree”). Table I provides a list of all measurement items and their sources. To collect the quantitative data for this research, 500 persons were randomly chosen to fill the questionnaire survey. At the end of the data collection period, 422 usable samples were received, with 225 female and 197 male. Of these samples, 43.4% were in their late twenties, 31.8% were 30–39 years old, 16.4% were 40–49, and 8.4% were over 50.
B. Reliability and validity analysis
After survey we used Crobach alpha with SPSS18.0 software to make reliability analysis. In this research the reliability test was used to examine the consistency with which individuals respond to the test in diverse occasions. We first conducted analyses separately for each factor and calculated coefficient alphas, composite reliabilities, and corrected Item—total correlation (CITC). Table II provides the detailed description of the scales used to measure each of the variables. Crobach alpha for all research variables are greater than 0.6; composite reliabilities are exceed the recommended threshold of 0.7; and corrected Item—total correlation values ranged from 0.464 to 0.823. From these results it is conclude that the scales have high levels of internal consistency, and are considered to be suitably reliable,
In addition, we assess measurement validity through the content validity and structural validity. The whole scale is developed based on the mature scale of prior studies, so it has already had good content validity itself. We conducted a confirmatory factor analysis (CFA) using Lisrel8.70 to assess structural validity of the measurement. All the constructs were measured with multiple indicators. If a factor’s loading is lower than 0.4 or its T value is lower than 1.95, the factor will be eliminated. The results showed that the size of each factor loading ranged from 0.52 to 0.91 and the T values for those indicators ranged from 7.58 to 19.15. Table II shows the results of the test and factor loading items of all the variables. Overall, we conclude that all the items of the questionnaire are accepted in the final study.
TABLE I
MEASUREMENT ITEMS
Construct / References / ItemsIntention to use / Davis (1989)
Venkatesh and Davis (2000) / I'm using or planning to use phone video call recently.
Given the opportunity, I will use phone video call.
In the near future, I am willing to more use phone video call.
Attitude towards use / Van der Heijden (2003)
Yang and Yoo (2004) / Using phone video call is a good idea.
Using phone video call is a wise choice.
In general, using phone video call is beneficial.
Perceived usefulness / Van der Heijden (2003) [17] / Using phone video call can shorten the distance between I and others.
Using phone video call makes my communication become easier.
Using phone video call makes my communication become more fun.
In general, phone video call is a useful communication technology.
Perceived ease of use / Venkatesh and Davis (2000) / It is easy to become skillful at using phone video call.
The interaction with phone video call is clear and understandable.
It is easy to perform the steps required to use phone video call.
In general, phone video call is a technology that easy to master.
Subjective norm / Venkatesh and Davis (2000) / People who are important to me would recommend using phone video call.
People who are important to me would find using phone video call beneficial.
People who are important to me would find using phone video call a good idea.
Perceived compatibility / Plouffe et al. (2001) [18] / Using phone video call fits well with my lifestyle.
Using phone video call fits well with my past experience.
In general, phone video call fits well with my current need of communication.
Perceived risk / Luarn and Lin (2005) [19] / I worry about that using phone video call may leak my privacy.
I worry about that using phone video call may lead to high costs.
I worry about that the network is instability, may be disrupted when communication.
Using phone video call leads me to some degree of tension and worry.
Consumer innovativeness / Dr Niki Hynes（2006）[20] / I am willing to try new things in life.
I like to accept challenges from new things; even it would worth my time and effort.
I think new lifestyle and ways of consumption is a progress to the past.
When the new product or technology appearance, I usually to be the earlier adopter.
TABLE II
RELIABILITY AND VALIDITY ANALYSIS
Construct / Items / Cronbach alpha / Loadings / T-valueIntention to use / IN1
IN2
IN3 / 0.784 / 0.74
0.83
0.66 / 13.65
16.10
11.81
Attitude towards use / AT1
AT2
AT3 / 0.825 / 0.80
0.74
0.81 / 15.35
13.91
15.74
Perceived usefulness / PU1
PU2
PU3
PU4 / 0.839 / 0.68
0.67
0.76
0.91 / 12.47
12.08
14.44
18.62
Perceived ease of use / PE1
PE2
PE3
PE4 / 0.888 / 0.78
0.78
0.79
0.91 / 15.26
15.23
15.45
19.15
Subjective norm / SN1
SN2
SN3 / 0.689 / 0.54
0.52
0.65 / 7.85
7.58
9.34
Perceived compatibility / PC1
PC2
PC3 / 0.797 / 0.57
0.71
0.68 / 8.92
11.08
10.57
Perceived risk / PR1
PR2
PR3
PR4 / 0.864 / 0.79
0.77
0.81
0.77 / 15.05
14.69
15.61
14.65
Consumer innovativeness / CI1
CI2
CI3
CI4 / 0.839 / 0.76
0.62
0.89
0.75 / 14.27
10.89
17.77
14.08
C. Structural equation model analysis