A Study on the Adoption Factors of Cell Phone Video Call Technology Bo Zhang, Hao Jin School of Management, Hebei University of Technology, Tianjin, China ([email protected], [email protected] ) 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 . Among them, the technology acceptance model (TAM), proposed by Davis , 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 , wireless LAN usage , and adoption of internet banking . 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   . 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 . 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” . 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 . 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. 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 . 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 . Lwin, Chen, Kim 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, Zhang and Chen’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 acceptance model 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 Intention to use Davis (1989) Venkatesh and Davis (2000) Attitude towards use Van der Heijden (2003) Yang and Yoo (2004) Perceived usefulness Van der Heijden (2003)  Perceived ease of use Venkatesh and Davis (2000) Subjective norm Venkatesh and Davis (2000) Perceived compatibility Plouffe et al. (2001)  Perceived risk Luarn and Lin (2005)  Consumer innovativeness Dr Niki Hynes（2006） Items 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. Using phone video call is a good idea. Using phone video call is a wise choice. In general, using phone video call is beneficial. 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. 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. 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. 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. 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. 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 Intention to use Attitude towards use Perceived usefulness Perceived ease of use Subjective norm Perceived compatibility Perceived risk Consumer innovativene ss Items IN1 IN2 IN3 AT1 AT2 AT3 PU1 PU2 PU3 PU4 PE1 PE2 PE3 PE4 SN1 SN2 SN3 PC1 PC2 PC3 PR1 PR2 PR3 PR4 CI1 CI2 CI3 CI4 Cronbach alpha 0.784 0.825 0.839 0.888 0.689 0.797 0.864 0.839 Loadings T-value 0.74 0.83 0.66 0.80 0.74 0.81 0.68 0.67 0.76 0.91 0.78 0.78 0.79 0.91 0.54 0.52 0.65 0.57 0.71 0.68 0.79 0.77 0.81 0.77 0.76 0.62 0.89 0.75 13.65 16.10 11.81 15.35 13.91 15.74 12.47 12.08 14.44 18.62 15.26 15.23 15.45 19.15 7.85 7.58 9.34 8.92 11.08 10.57 15.05 14.69 15.61 14.65 14.27 10.89 17.77 14.08 C. Structural equation model analysis Fig. 2. Results of model estimation. Previous table illustrates that the tolerance values for all dimensions were accepted, the next step was to examine the structural model. The overall fit indices of the structural model were within the range that scholars generally recommend. The ratio of chi-square to degrees of freedom was 1.632, which met the recommended criteria of less than 3. The goodness of fit index (GFI) and adjusted goodness of fit index (AGFI) were 0.90 and 0.88, respectively. The normed fit index (NFI) and comparative fit index (CFI) were 0.93 and 0.98, respectively. The standard root mean square residual (SRMR) and root mean square error of approximation (RMSEA) was 0.43 and 0.36. A comparison of these values against those recommended in the literature suggests that the model estimation result is quite satisfactory. Fig. 2 summarizes the estimation results and shows the relationships among constructs that are statistically significant. V. RESULTS We found support for H1, attitude has a significant and positive relationship with the intention to use phone video call (b = 0.71; p≤0.001). Moreover, the path coefficient of 0.14, significant at a 1% level, points to perceived usefulness has a strong positive relationship with the attitude towards using phone video call, as proposed in H2. Further, structural links from perceived ease of use to the attitude (b = 0.03; p >0 .05) and from perceived ease of use to the perceived usefulness (b = 0.10; p>0.05) are not significant. Thus, H3 and H4 were rejected. In addition, the relationship proposed in H5 and H6 are confirmed; that is, subjective norm has positive effects to the intention to use phone video call (b = 0.21; p≤0.001) and the perceived usefulness (b = 0.16; p≤0.01). The results also provide strong evidence for the effects of perceived compatibility on the attitude (b =0.26; p≤0.001) and the perceived usefulness (b = 0.20; p≤0.001), in support of H7 and H8. Regarding the perceived risk factor, we found a significant link with the attitude (b = -0.32; p≤0.001), implying that the perceived risk has a strong negative effect on attitude towards using phone video call. Therefore, H9 is confirmed. In the end, the construct of consumer innovativeness has a significant relationship with the constructs of attitude (b = 0.12; p≤0.05). Thus, H10 is supported. In the entire model for all predictors, R2 explains 68.2% of the variance related to intention to use phone video call, indicating that the model highlights a comprehensive set of important factors that are associated with consumer acceptance. In order to examine the total effects and establish a ranking among the drivers of phone video call acceptance, we multiply the coefficients along the paths. (Table IV)  . For example, the total effect of compatibility on intention to use equals the indirect effect via perceived usefulness plus the indirect effect via attitude towards use (0.20*0.14*0.71 + 0.26*0.71 = 0.20). TABLE III TOTAL EFFECT ON INTENTION TO USE Factor Total effect son intention to use. Subjective norm 0.23 Perceived -0.23 risk Perceived compatibility Perceived usefulness Consumer innovativeness Perceived ease of use 0.20 0.10 0.08 0 VI. DISCUSSION The research presents a powerful model to predict technology acceptance and recognizes that there are many factors that could affect the success and effectiveness of phone video call in developing countries. The empirical study found that subjective norm and perceived risk have the greatest impact on the intention to use phone video call. It is important since both perceived risk and subjective norm are not part of the original technology acceptance model and thus are often not considered by researchers. The same is true for the factor perceived compatibility. The six factors summarized in Table IV can serve as a guideline for increasing further market penetration of phone video call services. The impact of subjective norm was found to be very important in the research model. It can be implied that firms need to identify early adopters and stimulate their usage of phone video call services, so that they can serve as a reference facilitating broad diffusion in the future. Perceived risk is another key factor of the consumer acceptance of phone video call. Thus, firms need to increase the security of using phone video call by using the most developed technology in this field ， besides improving this services focused on charges, communication performance and privacy protection when promoting it. The research which was conducted by supports in explaining a part of the rest whereas it explains 20% of the variance of consumers’ perceived compatibility of using phone video call in developing countries. Thus, firms should develop phone video call technology and solutions that make consumers regard it as well-suited to their individual behavioral patterns. Similarly, perceived usefulness and consumer innovativeness also of “some concern” for affects effects on access of using phone video call, so firms can use the way of advertise to make users know more about the benefits and joy of this service, thereby increasing consumers’ cognitive of usefulness and Cause interests of potential consumers. REFERENCES  Venkatesh, V., Davis, F.D, “A theoretical extension of the technology acceptance model: Four longitudinal field study,” Management Science, vol. 46, no. 2, pp. 186-204, 2000.  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