Influential Factors and User Behavior of Mobile Reading

2.1 User Behavior in Mobile Internet

According to Kaasinen [13], the user must first accept the service before the use intention is obtained. The user should get available service information and be able to install and start to use the service. At the same time, the actual value of the service should be emphasized, and the user can use the service freely. Aside from factors that influence perceived ease of use and perceived value, the research also introduced the variable “trust” to analyze the user’s dependence on overall services under the framework of TAM. Based on this, Kim and Kim [15] proposed a mobile Internet adoption model consisting of seven critical factors including usefulness, usability, social influence, and compatibility. Their study had several interesting theoretical and practical implications from the individual perspective to view post-adoption behaviors and suggest a model-based comparison method.

2.2 User Behavior in Mobile Commerce Services

Currently, many researchers are performing empirical studies regarding mobile commerce as well as mobile Internet. As an example, researchers discussed factors affecting mobile commerce, focusing on consumer behavior from the subjective aspect. In mobile network environment, consumers are willing to accept mobile application programs (apps) actively, while affording the working cost of using new apps [34]. These new apps not only increase the efficiency and entertainment of work and living, but also achieve social consistency. Based on TAM, variables such as perceived usefulness, perceived entertainment, and perceived price were put forward to analyze user attitude and behavioral intention about mobile commerce service [34]. Jayasingh and Eze [12] integrated social influence, compatibility, perceived credibility, and coupon proneness to construct a new TAM-based model to analyze the adoption behavior of mobile coupon. Their study strongly supports the appropriateness of using the extended TAM model to understand the acceptance of user behavior on mobile coupons. To assess the likelihood of acceptance in mobile learning, a modified acceptance framework based on UTAUT was adopted to determine factors that influence students’ intention to use mobile learning, and factors including social influence, behavioral attitude, and behavioral intention are identified [11]. In addition, research about mobile payment, social group purchase, hybrid media apps, and mobile services is becoming increasingly popular.

Mobile reading is a new topic in mobile commerce, whereas user behavior-related literature is still relatively rare. A study on paid mobile phone apps shows that although more people are becoming mobile readers, only 8% of the customers are willing to pay. Therefore, research about the acceptance of mobile reader has become an urgent issue. Some researchers put forward an influential model for mobile reading, in which variants such as perceived behavioral control, perceived payment, perceived entertainment, and user attitude are included [8]. Combining the theory of reasoned action with planned behavior and perceived entertainment, Ding [8] extended the TAM model to study behavior of mobile reading consumers. Mobile reading has itself the function of information dissemination, entertainment, and leisure. The payment willingness of mobile reading consumers is low, which undoubtedly will affect the profit mode; thus, it is essential to take the factor “cost” into consideration of whether mobile reading is being used in the decision-making process.

In summary, studies on mobile reading are in their early stages. Literature [8] is primarily only aimed at consumers who have reading experience instead of bringing the corresponding variables into the research model. It does not emphasize whether people have a reading experience. With the popularity of free-of-charge culture, perceived payment may not work in mobile reading. This requires further research in the future.

3.1 Perceived Usefulness

Perceived usefulness (PU) means promotion degree of work performance that user subjectively thinks a particular system can bring when it is being used.

Davis [7] found perceived usefulness was the primary determinant influencing users’ attitude. It is vital that users perceive mobile commerce as useful to them, as it encourages them to use mobile service and reuse behavior [34]. Lee et al. [17] gave four assessment factors about perceived usefulness in a research of mobile commerce adoption behavior: money-saving, time-saving, wide variety of product or service, and overall perceived usefulness. People tend to make the choice to use a mobile service based on whether it beneficially affects their abilities to perform their jobs [6]. Following this argument, the following hypothesis can be introduced:

Hypothesis H_1a:Users’ perceived usefulness will have a positive effect on their attitudes toward using mobile reading.

Users will have behavioral intention after consideration of a useful particular tool or system and high performance price ratio [34]. Individuals evaluate the consequences and choices of their behavior in terms of perceived usefulness and desirability [20], and more than 73% of researchers hold the same point that perceived usefulness has a direct impact on behavioral intention [18]. Nowadays, people make good use of mobile reading to search a vast amount of required knowledge, keep them informed, kill time, relax, and entertain. They prefer helpful information technology. Therefore, we give the following hypothesis:

HypothesisH_1b:Users’ perceived usefulness will have a positive effect on their behavioral intention of using mobile reading.

3.2 Perceived Ease of Use

Perceived ease of use (PEOU) is the extent to which a person accepts as true that using an exacting method would be simple and easy.

According to Chau [20], perceived ease of use played an important role, and it was a key factor to determine user’s behavior when exploring technology usage. Perceived ease of use is a crucial determinant of mobile services adoption [23]. As mobile reading services develop rapidly, users feel that mobile reading products should be easy to obtain as well as simple to operate [8]. Here is the hypothesis:

HypothesisH_2a:Users’ perceived ease of use will have a positive effect on their attitudes toward using mobile reading.

People tend to use application programs that can beneficially affect their work and life performances. However, potential users might decide that a system is too difficult to use, even if they believe the given application program is useful [6]. Users would increase their intention of using mobile reading if they felt that mobile reading could make their daily work and study interesting and easy. To consumers, the greater the perceived ease of use, the more useful they will believe mobile reading to be [8].

Hypothesis H_2b:Users’ perceived ease of use will have a significant positive effect on their perceived usefulness.

3.3 Perceived Payment

Perceived payment (PP) is the cost that users feel a product or service will have with continuous use.

Cost in information system adoption behavior was an important influence factor. Consumers must deal with non-negligible costs in switching between different brands of products or relative services [26]. In a study on user behavior of mobile video adoption, researchers found that an individual perceives that mobile video in a 3G network would be a costly technology to adopt, and more costly technologies had a lesser likelihood of being adopted [10]. In mobile reading industry, cost is important to take into consideration in mobile reading behavior decision making [8].

Hypothesis H₃:Users’ perceived payment will have a negative effect on their attitude toward using mobile reading.

3.4 Social Influence

Social influence (SI) refers to the degree to which users believe those in their social circle (friends, colleagues, etc.) will agree and support to use information technology.

According to the conformity theory of social psychology, group members have a tendency to follow current social norms that can affect their cognition and behavior [16]. A number of researchers believe that external influence directly affects the subjective norms of an individual and can impact their behavioral intention [3, 27]. Researchers found external influence had a large effect on potential adopters through an e-government adoption behavior research [9]. They also found that adoption of mobile services influenced by the social environment can be regarded as a theory of fashion [23]. Mobile users are usually in a social situation, and young people like to show smartphones as new fashion goods at public occasions [20]. Adding social influence into the research model, we have the following hypothesis:

Hypothesis H₄:Social influence will have a positive effect on users’ attitude toward using mobile reading.

3.5 Attitude

Attitude is the positive or negative attitude showed by users to reflect one’s perception of using some new technologies.

Based on TAM, many research reports demonstrate that one’s attitude decides behavioral intention. In the field of mobile marketing, researchers found that attitude toward mobile marketing strongly determine behavioral intention in mobile marketing services [2]. Researchers have confirmed that a more positive consumer attitude toward using mobile reading would make a stronger behavioral intention [8]. Respondents who were willing to receive mobile ads tended to seek full messages and read them immediately, but those who were not willing to receive mobile ads would ignore such messages [14].

Hypothesis H₅:Users’ attitude toward using mobile reading will have a positive effect on their behavioral intention.

3.6 Living Habits

Personal experience would influence the effects of perceived usefulness and perceived ease of use on attitude toward using new technologies [30]. Some researchers put forward that mobile learning experience was also an important influential factor, and a model to investigate if prior experience of mobile devices affected the acceptance of m-learning was executed [1]. Mobile reading shares many similar features with mobile learning.

Hypothesis H_6a:It is controlled by living habit when perceived usefulness influences attitude toward using mobile reading.

As Ouellette and Wood [22] noted, once a behavior has become a habit or well-practiced behavior, it is automatic and carried out without conscious decision. Lin and Wang [19] found that the force of habit affects behavioral intention once people have gained experience, and habitual behavior leads to the continuation of the same type of behavior. Ajzen and Fishbein [30] noted that feedback from previous experiences would influence beliefs and, consequently, future behavioral performance.

Hypothesis H_6b:It is controlled by living habit when perceived usefulness influences behavioral intention of mobile reading.

With the strength of user skills and experience, perceived ease of use was not an important index to influence user adoption anymore [4]. In mobile domain, researchers found that students with prior experience of using mobile devices perceived mobile learning as easy to use [21]. Here is the final hypothesis:

Hypothesis H_6c:It is controlled by living habit when perceived ease of use influences attitude toward using mobile reading.

4.1 Questionnaire Design and Data Collection

The questionnaire invoked in this article is divided into three parts. Part 1 is about basic information, including gender, age, education level, job, and monthly consumption. Part 2 aims to get information about knowing and using mobile reading. Part 3 is the main part of the questionnaire, investigating perceived usefulness, perceived ease of use, perceived payment, attitude, behavioral intention, living habit, and social influence of mobile reading.

There were 240 people involved in the questionnaire, with 111 men (46.25%) and 129 women (53.75%); 73.33% were 18–25 years old, showing that mobile reading service is most widely spread among young people, especially in colleges and universities.

The main part uses Likert scale to carry on the measure to every question, requesting an appraisal in 1–5 scores in view of all questions, with 1 representing “does not agree” and 5 representing “completely agree”, and deep analysis is processed by SPSS and Amos.

4.2 Reliability and Validity Analysis

5.1 Model Fitting

The structural equation model (SEM) is adopted to analyze the conceptual model, and Amos 17.0 is used to measure model fitting and model hypothesis testing with χ²/degrees of freedom, goodness-of-fit index (GFI), root mean square error of approximation (RMSEA), normed fit index (NFI), and comparative fit index (CFI).

The initial fitting result of this study shows that χ²/degrees of freedom is 3.606, GFI value is 0.876, RMSEA value is 0.104, NFI value is 0.837, and CFI value is 0.876. Usually, if χ²/degrees of freedom is <3.0, the GFI value is higher than 0.9, RMSEA is <0.1, NFI and CFI are closer to 1, the model fitting is fairly qualified. However, the former three indices’ results do not meet the standards, indicating the fitting degree of model is relatively low. In this case, a revision is needed to make it more appropriate. The adjustments were conducted through modification indices to reduce the χ² value and increase the p value to optimize the model fitting. After adjusting the model, as depicted in Table 3, all other indices meet the standards except the GFI value, which is somewhat off the standard. But in social science and psychology domains, GFI>0.8 is acceptable since the complexity of the aimed subjects. These indicate that the overall model fitness is qualified.

5.2 Path Analysis and Hypotheses Testing

Based on UTAUT and TAM theories, this article adopts SEM to study the relationship between variables by processing and calculating the standardized regression coefficient (path coefficient) and the significance of each path in the model. A higher coefficient correlates with a greater strength of the casual relationship.

The path diagram of mobile reading acceptance behavior model is obtained according to SEM processing (Figure 2.). Since the path coefficient of how perceived payment influences attitude is low and non-significant, Hypothesis H₃ cannot be supported. However, other path coefficients are significant and get different levels of support.

Figure 2

Path Coefficients in Mobile Reading.

When the non-significant variable “perceived payment” and its correlativity ties are removed, path analysis is conducted with the readjusted model and gains the following results. The influence coefficient of perceived usefulness on attitude and behavioral intention are 0.647*** and 0.163**, respectively. The influence coefficient of perceived ease of use on perceived usefulness is 0.722***, whereas the influence coefficient of social influence on attitude is 0.385***. The influence coefficient of attitude on behavioral intention is 0.709***, but the influence of perceived ease of use on attitude is non-significant (0.180). Data show that all the paths are supported except for Hypothesis H_2a, with an influence coefficient of 0.180. Thus, the tie between perceived ease of use and attitude is deleted, and we get the final model and path coefficient after adjusting and analyzing.

The remaining hypotheses are supported by different degrees according to the path coefficients of the modified model without taking the control variable into account (Figure 3). The final path coefficients of Hypotheses H_1a and H₄ are 0.860*** and 0.341***, respectively. This indicates that both have significant positive influences on attitude. In contrast, perceived ease of use and perceived payment have non-significant impacts on attitude, as indicated by the non-significant path coefficients of H_2a and H₃. Analysis results show that H_1b and H₅ are supported, meaning that perceived usefulness and attitude have positive influences on behavioral intention. Hypothesis H_2b is supported as well, with a path coefficient of 0.841***.

Figure 3

Path Coefficients After Modification.