Key Factors Influencing Intention to Use Mobile Video by College Students in China

The main purpose of this paper is to provide conceptual framework for the usage of mobile videos and the factors influencing it. Mobile video has completely changed the meaning and value of the traditional television transmission. Despite the importance of behavioural intentions, the theoretical and conceptual basis for understanding the behavioural intentions construct is still relatively immature in the China media industry Thus, to come up with the conceptual framework it is obvious to investigate previous studies on the existing relationship between the constructs identified. Critical review of the literature on the concept of mobile video usage confirmed that system, service and information quality play a crucial role on the adoption and usage of mobile videos. It is pointed out that the research on the continuous use behavior and willingness of mobile video website users has been paid more and more attention by experts and scholars.


Introduction
Mobile video is the product of three media convergence, i.e. mobile phone, TV and mobile Internet, and is a new multi-media transmission method based on the mobile network platform. It not only has the characteristics of traditional media, such as the intuitiveness of television media, the portability of broadcast media, the interactive nature of online media, the retention of newspaper media, but also the unique characteristics of new media such as mobile portability and privacy. These characteristics make the mobile video have more advantages than traditional media form which is satisfy the diversified demand of people. The smartphones, being a very new invention of humanity, became an inherent part of human's life. The smartphone combines different sophisticated features. Mobile video as part of innovation combined with handheld advanced computing capabilities like internet connection have side effect on human health (Miakotko, 2016). Rise in Mobile usage in China in the field of mobile payment, mobile e-commerce, and mobile gaming have increased considerably, but the usage of mobile videos has not been increasing considerably (Shuli, 2017).
Mobile video has completely changed the meaning and value of the traditional television transmission, which places the needs of the audience first, focusing on the enthusiasm and initiative of the audience. Therefore, "Differing from the initial stage of new media development, our attention is returning from technology, channel and realization method etc. to the study of essential features of the audience. This is a quite significant returning period of new media development in history. Important reforms which influence new media in the future or media field will originate from the study of the audience" (Zhang, 2007). Thus, the main objective of this paper is to conceptualize the effect of perceived quality, perceived usefulness and perceived ease of use on user's satisfaction and continuance intention to use mobile videos.

Literature Review
There are very few studies focused on concepts such as perceived quality, perceived usefulness, perceived ease of use, satisfaction and their relationships on continuous intention to use mobile video. The continuance intention to use a particular product is by the level of satisfaction to the product (Al-Maghrabi and Dennis, 2011;Chen et al. 2009;Zhao and Cao, 2012). The study by Roca et al. (2006) reported quality has significant effect to the confirmation. They also indicated that interpersonal and external influence factors had no significant impact on the satisfaction of using mobile video; while perceived quality including system quality and information quality could become the determinants of user satisfaction by mean of confirmation on using mobile video. On the other hand, Joint (2010) found that technology has neither proven itself as a transformational technology in the context of services, nor as a consumer product to be sold directly to end users. It does have the potential to be so, if certain problems related to usability, business models and tools are addressed.
Behavioural intentions have been identified as a multi-dimensional construct that has been conceptualised in the marketing literature (Skogland & Siguaw, 2004;Alexandris et al., 2002;Oliver, 1999). Based on the existing literature, user satisfaction, service quality, information quality, perceived usefulness, perceived ease of use and demographic characteristics have been identified as determinants of behavioural intentions (Hu et al., 2009;Alexandris et al., 2002;Tan, 2002;Brady et al., 2001;Cronin et al., 2000;Kandampully & Suhartanto, 2000;Oh, 2000;Yu, Zhang, Kim and Henderson, 2014). Thus, to come up with the conceptual framework it is obvious to investigate previous studies on the existing relationship between the constructs identified.

System Quality, Perceived usefulness and Perceived Ease of use
System quality depends on the users' needs as defined during the system's analysis and development. It is an important factor in perception to use a web technology alongside its appearance, technical adequacy, delay, navigation, security, and privacy (Ahn, Ryu and Han, 2007). The technical aspect of the provider's online system is defined as the extent to which the online system possesses the attributes of reliability, accessibility, speed, flexibility, aesthetics, and navigation (Montazemi and Qahri-Saremi, 2015). In this study, the definition of website system quality mainly includes the use of (function, technology, etc.), visual design of two aspects. Therefore, the impact of system quality on consumer attitudes is mainly to analyze the impact of website operation on the use and design of consumer attitudes.
With the development of single-program from the development mode, video media began to gradually cultivate the user's purchase of membership awareness. The term "paid website" also began to be paid more and more attention by academic circles, and started to analyze the features and development strategies of paid websites in our country. And the development of such payment models will certainly have an impact on the development of its clients. Yannan (2014) and others compared domestic and overseas paid websites and found that the proportion of paid programs abroad was higher than that of domestic ones. However, the number of paying users in China was constantly expanding, and the content quality and copyright protection were the important factors for the development of payment models.
Xiang, Schwartz and Uysal (2015) reported that consumers were able to separate the evaluation of waiting experiences from the evaluation of the website. However, they also demonstrated that when there is uncertainty about the waiting (as with the majority of downloads), the negative feeling generated by the waiting experience were carried over to the evaluation of the website. Ease of navigation relates to the level of time and effort required to accomplish specific tasks (Venkatesh, 2000). Speed of system is important since it enables users to attain their goals without too much waiting (Rittinghouse, and Ransome, 2016). High level of system quality may provide users more convenience, privacy, and faster responses.
On the basis of task-technology fit theory (TTF), Gebauer et al. (2010) established a fit between managerial tasks, mobile IS, and mobile use. Gebauer (2008) also revealed that user-perceived technology maturity is a crucial factor in explaining the use of mobile technology, which affects job performance. Chatterjee et al. (2009) applied the IS success model in the context of work in healthcare. They showed that system quality and content (information) quality exerts impacts on the use of mobile technology.
In South Korea, EMSs utilizing personal digital assistants (PDAs) had been studied mainly until 2009. Subsequently, mobile ISs utilizing smartphones were studied (Lee, 2012). Lee and Lee (2012) surveyed employees of hospitality companies for the EMS. Koo et al. (2012) showed that among information quality and service quality of EMS, only information quality indirectly affect job performance. Lee (2012) studied the relationships between the factors of composing EMSs using the data collected from the survey of experts.
DeLone and McLean suggested the IS success model in 1992 and updated the model in 2002 (DeLone andMcLean, 1992;2002;2003). The IS success model is widely adopted by researchers and applied in many studies such as IS in organizations (Sedera and Gable, 2004), e-commerce (DeLone and McLean, 2004;Wang, 2008), and Web portal (Al-Debei et al., 2013). This study also used the IS success model in studying the relationship between system quality, information quality, use, and net benefits in mobile video technology.

Information Quality, Perceived usefulness and Perceived ease of use
Information on the web relies on both groups forming a common perception. In a global context, most web interfaces do not support effective usage due to the use of unsuitable tools for conveying information in a global context, as most of the information is presented on the web by icons, metaphors, shapes, colours of text and background, frame/text locations on screen, etc. (Kang & Araújo, 2006). Website information quality is an important indicator of the content of the site. Highquality information can help users compare online store products, increase the user's purchase fun, make better shopping options. Most of the research on site content evaluation emphasizes the importance of information quality, the most frequently measured indicators in the content of the site is the content and content quality.
Scholars agree on the importance of information content and its impact on the perception of users and their impression on the whole website, and they defined Information quality as an evaluation criterion and dimension of overall quality and usability of e-commerce websites (Goi, 2012;Lee & Kozar, 2006), while others defined information quality as the aspects of a system and a measure of the information system outputs, (Delone & McLean, 2003). Ahnetal (2003) explores the impact of site characteristics on consumer attitudes from website characteristics. The author presents the characteristics of the website (including three aspects: system quality, quality of information and quality of service) on the user's attitude and technology acceptance will have a significant impact. The system quality includes: design style, navigation, system response speed, system security, function, multimedia, personalized service. The study shows that the quality of the shopping site system has a significant impact on consumer perception and ease of use. Lin & Lu (2001) constructed the evaluation index of information system quality with 139 network users, including the response time and accessibility of the website system, and adopted the questionnaire survey to explore its impact on the acceptance of the website. The results found that the site response time and accessibility impact perception easy to use, perception easy to use perception of useful, perceived useful impact attitude. Ranganathan and Ganapathy (2002) conclude that the information quality of e-commerce websites of extreme importance, because it can significantly influence online consumers' purchase intent and shopping satisfaction, while Lazar and Sears (2006) concluded that good information quality can increase the number of visits to the website by the same user. Liao, Proctor, and Salvendy (2008) Define 'information content' a key factor in e-commerce success and are among the first to put this aspect, and added that an e-commerce website should serve as a decision-support system by providing detailed information about the product and transaction support. They confirmed that adding information value to products will maximise consumers' mental experience, and it is important to reduce consumers' mental effort by presenting information compatible with their mental models of products and business transactions.
Furthermore, Reunis, Santema, and Harink (2006) also states that full benefits from information systems can be achieved only if and when the end-users adopt the tool and apply it successfully in their everyday work using the system correctly and to its full potential. Information quality could be expressed in quality of media transmission, interface design, and rich content, and these dimensions considered as elements that encourage users to repeat visit to the website more than once. Lederer et al (2000) argues that the level of information quality of the site affects the customer's perception. Huang Zhaizhen (2000) explores the willingness of consumers to buy online. The results show that the information mechanism of shopping website is related to the purchase intention of consumers, that is, the information of the website is more abundant, the more consumers want to shop online, but the consumers provide the authenticity of information, but it will cause a negative effect. Lin & Lu (2000) argues that the quality of information system is the external variable that the technology acceptance mode uses for the website, and the quality of the information system is composed of three facets of information quality, response in the system and system acquisition ability, and to explore the three How it will affect the acceptance of the site user. The study uses the attitude of the site users to modify the technology to accept the model, the results found that the site quality impact perception easy to use, perception easy to use perception of useful, perceived useful impact attitude.
However, Reunis et al. (2006) studied broadband users in the USA. She found the way a website is designed and implement information can also influence trust and encourage users to buy products and enhance their intention to purchase from a certain website who provide rich and reliable information, while a research in the USA and Finland by Fogg et al. (2001) evaluated website elements which affect consumers' perception of credibility, they founds elements that highlight the brick-andmortar nature of organisations, such as listing physical addresses and contact phone numbers, enhance the website credibility, and consider these elements a factors that provide quality of information about the organisation. Similarly, Wang and Emurian (2005) found that some elements of the web interface influence trust. Similarly, Singh, Zhao, and Hu (2005) found that tailoring the website design to the user experience leads to increased perceptions of website credibility. It was found in earlier researchers, that web design elements such as navigation, images and colour can provide different reactions from people in different cultures, resulting in varying responses.

Service Quality, Perceived Usefulness and Perceived Ease of Use
For the aggressive marketing, service quality works as an instrument for success and survival in current competitive environment. Media companies play a crucial role in energizing the whole service quality concepts. Media sector is relatively fastest growing sector in all over the world. This sector requires continuous increase in expectations of customers along with high demand of service quality. Many previous studies like (Camarero, 2007;Gayathri, 2005;Goswami, 2007;Siddiqui & Sharma, 2010;Tsoukatos & Rand, 2006) have investigated the role of service quality in service industry. Service quality of social media sector in the current study is composed of seven factors namely, tangibility, reliability, responsiveness, empathy, assurance, problem solving and helpfulness. Radam (2000) using Malmquist Index approach attempted to investigate the productivity of the life insurance sector and found that the future of media companies depends on their ability to compete with its rivals efficiently. The productivity growth of insurance sector in Malaysia was found to be low as compared to economic growth. The result also concluded that technical efficiency and progress increases productivity growth of media industry. Sandhu and Bala (2011) mentioned that service quality play an important role in the aggressive marketing. It is very important to deliver high quality service in today's competitive environment. The study used seven factors like proficiency, physical and ethical excellence, media presentations, service delivery processes, security, credibility and functionality. The findings confirmed three factors like proficiency, physical and ethical excellence and functionality have high impact in determining service quality in service industry. Goswami (2007) examined the dimensions of service quality impacting on customer satisfaction in the life insurance sector with the use of systematic design. With the sample of 232, the study based on SERVQUAL measurement items revealed that responsiveness is the key factor for customer satisfaction. It was also suggested that there is a need of introducing customer relationship management in the life insurance sector to increase customer satisfaction. Upadhyaya and Badlani (2011) in order to explain customer satisfaction attempted to identify key success factors of service quality in the media industry. Data was collected from 206 customers and the study based on primary and secondary data found that there is a need of improvement in the management of the company instead of highlighting the satisfaction levels. The study also found that customer satisfaction is directly linked to the organizational performance.
Cha Jinxiang, Lisheng (2006) establish a structural model of the relationship between service quality of customer service, customer expectation and customer satisfaction based on the theory of expected uncertainty and the theory of service quality measurement, which divides the service quality of shopping website into eight dimension. They are website design characteristic, network security, network interaction, personalized service, product quality assurance, convenience, price advantage and ease of operation. Then, they use the students in the school, which is one of the main participants, as investigate samples to verify the model. The results of the empirical study show that the quality of the consumer's perceived shopping site service and the customer's own expectations of the website determine their satisfaction with the shopping site. Parasuraman, Zeithaml, and Berry (1988) have used 22 items for investigating influence of SERVQUAL factors on perception of service quality. The five dimensions of service quality were refined to be Tangibility, Reliability, Responsiveness, Assurance and Empathy. SERQUAL was having only five dimensions and this study found that service organizations can rely on the effect of SERQUAL factors in assessing the perception and expectations of customers. The model was also found to be helpful in improving service quality. Morshheuser, Riar and Maedche, (2017) in the study of online games, TAM as the main body, to study the game players on the participation of online games will. The study focuses on the causal effects of service quality, user perception, attitudes, and behavioral intentions. The results of the empirical study verify the TAM Model, and verify that the quality of service will positively affect the user perception (perceived ease of use and perception useful) and attitude, the user easy to use the software, practical and entertaining awareness will positively affect the user attitude, and attitude will affect the behavior of intent. Parasuraman, Berry, and Zeithaml (1991) refined the SERVQUAL model provided in 1988 by investigating in different sectors like retail banking, insurance sector, and service provided for telephone repair. Analysis was performed with revised framework of SERVQUAL and found tangibility and assurance as an important factor and provide consistent direction for further studies.
Hahn, Sparks and Wilkins (2017) further explained SERVQUAL factors at multilevel and multidimensional by proposing hierarchical model for confirming the overall service perceptions. The new model included attitude, behavior and expertise to determining interaction, environmental and outcome quality of services. The study concluded that the combination of interaction, environmental and outcome quality determines the overall perception of service quality provided to the customers. The study also found that reliability, responsiveness and empathy are the main factor for improving service quality.
However, Jain and Gupta (2004) performed a comparison between SERVQUAL and SERVPERFORM in the context of India methodologically, found that, "Consumers of different food restaurants were targeted as participants and the study revealed that SERVPERFORM outperforms SERVQUAL for explaining the variation in service quality." Azam (2005) investigated customer's attitude for public and private industries providing services. A survey with 243 participants along with empirical research revealed that satisfactory settlement of services, financial strength of service providers and underwriting of risk are the main association for improving customer's attitude. This factors also shows the capacity of providing services by the industries. Ahmad and Sungip (2008) used SERVQUAL model for investigating customer perception and expectations in Malaysian life insurance industry. Empirical research with self-administered survey questionnaire was utilized as research method and the findings revealed that reliability is the most important determinant of SERVQUAL that helps the service sector to survive in the competitive environment. Furthermore, it was also suggested that meeting customer expectation by faster and better services along with innovative solutions makes the customers to realize the value of service provided.
Furthermore, Kumar (2011) compared the level of service quality in private and public life insurance providers. The finding stated that, "there is a negative gap for the services provided by public insurance companies as compared to private companies". Insurance companies focus more on showing their sincere interest in solving.

Perceived Usefulness (PU) and User Satisfaction
Perceived usefulness refers to get benefit in the life and the workplace of individuals by using the system. In another definition of this word, when the information is more useful or important, the more conclusive the attitude of the adopters will be. Perceived usefulness can be defined when someone use technology in completing their work, it will increase their performance work performance. A study by Davis shows that perceived usefulness is the constitutional cause that affect the behavioural intention of use. The second determinant will be the perceived ease of use of a secondary determinant of behavioural intention to use some technology. Perceived ease of use is when someone or the potential adopters believe that using and learning to use the information system is not hard.
The perceived usefulness (PU) lies in the degree to which one person thinks that using technology will improve performance (Miftah & Wulandari, 2015). The PU is the assertion of the decision-making process. According to TAM, PU is described as the main effect on the user's intention to use. Based on (Park, Nam, & Cha, 2012), it was considered that usefulness was assumed to influence the BI of using technology at the time of learning. PU is the most influential factor affecting BI in users' intention to use mobile learning systems (Shin & Kang, 2015). PU has a positive impact to the BI of individuals to use technology (Ching-Ter, Hajiyev, & Su, 2017). PU was hypothesized to have direct and positive influences on attitudes towards computer use (Teo & Milutinovic, 2015). Liu, Chen, Sun, Wible and Kuo (2010) applied the extended TAM to explore the factors that influence the intention of using the online learning community. They found that PU is the most influential variable in predicting the intention of using a web-based learning system. Based on study performed by Sample (2014), Technology information shows a significant effect on the perceived usefulness. Lam (2009) indicated that users could overcome small technical and procedural challenges during a long period of time using technology. Thus, they can spend more time on learning activities using mobile video. In other words, the learning activities help users believe that the system can help them perform their task better. This finding shows that increasing user's quality of service may enhance their perceived usefulness. Several studies have revealed that user's perceived usefulness and perceived ease of use regarding information technology influence their usage (e.g. Brown, 2012;Davis, 1989;Shroff, 2011;Davis, 1991;Davis, 1993;Moon, 2001;Sun, 2008). Therefore, investigating user's perceived usefulness might be critical for mobile video usage. Therefore, there is a need to explore the impact of perceived usefulness towards behavior of users to continuously use mobile video. Thus, it is hypothesized that:

Perceived Ease of Use and User Satisfaction
Alharbi and Drew (2014) indicate there are intimate relationship between perceived ease of use and behavioural intention to use learning management systems for two users group which non-user and user group. It shows that a stronger correlation between TAM variables occurred for the non-user group. For example, when comparing the effect of perceived ease of use on behavioural intention to use an LMS, the non-user group showed a significantly stronger and positive correlation. However, with the user group, the correlation was not statically significant. In Ratna et al. (2015) research, they study on the social media usage behaviour by used TAM and the result shows that there are positive relationship between perceived ease of use and behavioural intention to use. Perceived ease of use had positive impact on behavioural intention. Studies on adoption of technology shows that perceived ease of use can attract the users to change their behaviour intention to use technology. Mohammadi (2014) discover perceived ease of use had effect to each other but it is indirect effect on behavioural intention to use e-learning. The result of the study also shows that more perceived ease of use, more positive intention to use e-learning. Behavioural intention was found to be a significant determinant of perceived ease of use in examined the faculty use of Learning Management Systems (LMSs) in higher institution (Fathema et al., 2015). Calisir et al. (2014) confirmed that if it is perceive or needed long time and higher effort to use a new system, there may hold a negative behaviour to use the system. These two variables have positive effect to each other. The perceived ease of use had significant impact toward behavioural intention in using m-learning is being confirmed through Althunibat (2015) study. Many previous studies shows that perceived ease of use had positive impact toward behavioural intention.

User Satisfaction as Mediator
Satisfaction in general is the feeling of difference between prior expectations and perceived achievement. Keller (1983) defines satisfaction as an individual's overall positive assessment of his or her technology experience. Satisfaction can be measured only after the user's activity. Halilovic (2013) and others compare the expectations of consumers to buy products or services for the first time and the expectations of the purchase after the initial purchase. The results show that the expectations of consumers and their perceived actual performance determine their degree of satisfaction, Higher satisfaction of consumers more likely to continue consumption behavior.
In the case of mobile video using systems or technology, the most important factors, which have a positive effect on satisfaction, are the user's actual performance (Hui, Hu, Clark, Tam, & Milton, 2008;Liao, Palvia, & Chen, 2009) and perceived usefulness, perceived ease of use and attitude, which are also connected to the given system or technology, measurable also after the activity performed (Del Barrio, Romero-Frías, & Arquero, 2013;Hui et al., 2008;Lee & Lehto, 2013;Sun, Tsai, Finger, Chen, & Yeh, 2008).
Involvement is important since it has significant benefit on organization development. It is not only increases employee satisfaction and commitment, it also reduce their desire to leave from their current position (Panigrahi, Zainuddin, & Azizan, 2014;Zopiatis, Constanti, & Theocharous, 2014). In other words, workers and students are enjoyed with their job and willingness to spend more energy on it. Organization shall attempt to fulfill their employees' intrinsic need to achieve higher employee satisfaction. The other ways to satisfy employee are provide safety and comfortable working environment, provide opportunity to allow employee making their own decision and provide incentive and welfare to employee. Once employee satisfied with the company, the commitment and involvement of employee will be higher. Last but not least, job involvement is important in an organization because it is related or affected to that company image.
As a reference for users to purchase or use again, Oliver (2014) use will expect confirmation theory to address user satisfaction and repeat buying behavior in general marketing campaigns. Before purchasing a product or using a service, the user has a psychological expectation of the performance of the product and the service. After purchasing or using the product, the user will generate a new evaluation of the product or expectation based on the actual use. The higher the degree of satisfaction of expectation, it results the higher the satisfaction degree, indicating that the expected degree of positive impact on the impact of customer satisfaction; anyway, indicating the degree of recognition of negative impact on customer satisfaction. If the user is more satisfied with the products and services, the more willing to buy or use products and services, resulting in repeated purchase behavior.

Intention to Use
According to Mingming Zhou (2016), theory of planned behavior (TPB) and the self-determination theory (SDT) as research found that the user's attitude toward were significant determinants of intention to use the system. Wen-Lung Shiau and Patrick Y.K. Chau (2015) used individual theoretical multi-model (TRA/TPB, the TAM, the MM, SE, SQ, and IDT) to compare with unified model which is the best to identify the mobile video user's behaviour intention. Result shows that TAM and TPB had larger effect sizes than do the others model. Belletier et al. (2018) indicated that theory of planned behavior (TPB) was a better predictor of the intention to use the information system than TAM, but both models failed to predict actual behavior. According to Cheng (2016), he identified the specified factors that may affect users' intentions to collaborate online for group work by used theory of planned behavior (TPB) and result shows that actual behavioural control plays an important role. Karimi et al. (2014) used theory of planned behavior (TPB) to find out EEPs appreciably influenced subjective norms and PBC, but that these programs did not have significant impacts on users' attitude toward entrepreneurship and their perceptions of opportunity identification. In Carfora et al. (2017) study, they confirmed that the pro-environmental self-identity appreciably moderated the collision of perceived behavioural control on intentions and the effect of past behaviour on both intentions and behaviours.
Hong (2013) added perceptual costs, perceived entertainment, and habit variables to the expected recognition model, and constructed a continuous usage behavior model for video website users. Empirical studies have shown that perceived usefulness and satisfaction positively affect users' willingness to continue using and expectation confirmation Significantly affect user satisfaction and perceived usefulness; perceived costs, perceived entertainment and user satisfaction and the intention of continuous use are closely related; and habits have a mediating effect on the intention of continuous use and the behavior of continuous use.
Based on TAM, behavioural intention will lead to actual usage (Rauniar, Rawski, Yang, & Johnson, 2014). In UTAUT also state that facilitating condition and behavioural intention determine the technology usage (Al-Qeisi et al., 2014). Behavioural intention is considered to be an immediate antecedent of actual usage. It defines as the subjective possibility of he or she willingness to engage a specific behaviour (Tarhini et al., 2015).According to Barnett et al.,(2015) research, they found that behavioural intention will fully mediate the relationship between effort expectancy and IT system usage (Barnett et al., 2015). For our current study on technology, we operationalize behavioural intention as the continued intention to perform study activities by using the technology. Further, we define actual usage in terms of the frequency of technology used by university student (Rauniar et al., 2014).
On the other hand, despite the widespread acceptance of online video sites by users, the user's viscosity is not high for online video businesses. The main ways for users to obtain video: through search engines, log in directly to video sites, or log in to mobile clients. At present, the vast majority of Internet users are still through the search engine to find the video, and the resources required by the user may be found on Youku can also be found in Aiqi, the user may choose to watch the site, which affects the video site users Viscosity. Therefore, the continuous use of online video site users the behavior and willingness of experts and scholars gradually attention.

Previous Studies on Perception of Customers and Behavioural Intention
This study reviews and conceptualizes perception of customers towards using mobile video as mode of communication by adopting multi-dimensional approach. In addition, despite the importance of behavioural intentions, the theoretical and conceptual basis for understanding the behavioural intentions construct is still relatively immature in the China media industry (Wang and Lo, 2002;Yoon, 2011). Oliver (2014 suggested that expectancy-disconfirmation has been generally accepted and conceptually applied in the behavioral study of customer satisfaction. Oliver (2014) claimed that a positive disconfirmation would occur and further contribute to customer satisfaction if the product or service were beyond customer expectations. Conversely, a negative disconfirmation might happen when a service provider's performance became worse than customer expectations (Albashir, Zainuddin and Panigrahi, 2018).
In addition, there is considerable debate in the literature on how best to conceptualise service quality, user satisfaction as this construct is intrinsically an elusive concept in the media industry (Saleem, Zahra and Yaseen, 2017). Though service quality has received more attention recently, few studies have focused on how to establish a reasonable framework of assessing service quality for media industry, specifically for the ones providing mobile video (Cheng, Mu and Cheng, 2017). Therefore, Akbaba (2006) recommended that the service quality construct in the media industry should be further examined. In addition, based on the hospitality literature, the perceived value construct has not attracted sufficient conceptual and empirical studies.
Early conceptualizations of the disconfirmation paradigm of service quality have been employed in the literature of physical goods (Parasuraman et al., 1985;Grönroos, 1984Grönroos, , 1982Baker, Jordan and Funk, 2018). This concept suggested that quality resulted from the comparison between perceived and expected performance, as reflected in Grönroos's (1984Grönroos's ( , 1982 seminal conceptualization of quality that "puts the perceived service against the expected service" (Grönroos, 1984, p. 37). In addition to the adaptation of the disconfirmation paradigm to the measurement of service quality, Grönroos (1984) developed a two-dimensional model to measure service quality: technical quality and functional quality.
Although customer perceptions of using technology were apparently measured based on multiple dimensions, there was no general agreement on the nature or content of the dimensions (Brady & Cronin, 2001). Indeed, Siewiorek and Swarz (2017) noted that customer evaluations were a highly complex process that might be operated at several levels of abstraction. Brady and Cronin (2001) indicated that the missing link appeared to be a unifying theory or conceptualization, which reflected the complexity and hierarchical nature of the construct. In an attempt to integrate the differing conceptualizations of service quality and unify the abundance of theory on user satisfaction and intention to use, Brady and Cronin (2001) combined Rust and Oliver's (1994) and Dabholkar et al.'s (1996) hierarchical approaches to develop a hierarchical model of perceived service quality. Ko and Pastore (2005) tested the model using the two-step approach of structural equation modelling. Ko and Pastore's (2005) findings supported the multi-dimensional conceptualisation of service quality perception in the recreational sports industry. Finally, Ko and Pastore (2005) suggested that it was necessary to investigate if this hierarchical model could also be applied to other industries that were similar to the recreational sports industry. Caro and Roemer (2006) argued that models of intention to use needed to be conceptualised based on the specific characteristics of the industry. In order to conceptualise intention to use mobile video in the media industry, Caro and Roemer (2006) developed a multi-dimensional and hierarchical model that reflected these characteristics. Through an extensive literature review and qualitative research, those authors found that factors influencing intention to use the technology should be divided into six primary dimensions.
A review of the literature on the constructs related to behavioural intentions in the media industry has identified five conceptual gaps. Each gap will be explicitly explained in the following paragraphs. The first gap relates to a lack of research in the Chinese Media industry with regard to customer perceptions of using the system. Several studies have measured service quality and user satisfaction using SERVQUAL, SERVPERF, LODGQUAL, HOLSERV and LODGSERV (Wilkins et al., 2006a;Fernandez et al., 2005;Juwaheer, 2004;Lai et al., 1999;Gabbie & O'Neill, 1996;Getty & Thompson, 1994;Mei et al., 1999;Akan, 1995;Dabholker, 2015). However, some researchers have criticised the measurement of the constructs using these scales, which have not appropriately measured service quality (Albacete-Sáez et al., 2007;Nadiri & Hussain, 2005;Wilkins, 2005;Keating & Harrington, 2002;Teeroovengadum, Kamalanbhan and Seebaluck, 2016).

Theoretical Framework
There are very few studies focused on concepts such as perceived quality, perceived usefulness, perceived ease of use, satisfaction and their relationships on continuous intention to use mobile video. The continuance intention to use a product is by the level of satisfaction to the product (Al-Maghrabi and Dennis 2011;Chen et al. 2009;Zhao and Cao 2012). The study by Roca et al. (2006) reported quality has significant effect to the confirmation. They also indicated that interpersonal and external influence factors had no significant impact on the satisfaction of using mobile video; while perceived quality including system quality and information quality could become the determinants of user satisfaction by mean of confirmation on using mobile video. On the other hand, Joint (2010) found that technology has neither proven itself as a transformational technology in the context of services, nor as a consumer product to be sold directly to end users. It does have the potential to be so, if certain problems related to usability, business models and tools are addressed.

Figure.1. Theoretical Framework
The behavioral intention theories like (TRA, TPB and TAM) explain the factors affecting the intention to use, and could be applied to investigate the intention to use mobile video. Figure.1 shows the theoretical framework derived from previous studies and theoretical concepts discussed earlier in this section.

Conclusion
Based on the literatures covered, the research concluded that factors such as system quality, service quality and information quality are the main influential power on buyers' behaviours and towards mobile video application. Therefore, mobile companies should realise the importance of these factors before the implementation of mobile video applications in their products.
The relevant theories of technology adoption, such as TRA, TPB, UTAUT and other models, focusing on the related research of TAM model and its application is introduced to understand the mobile vide implementation and its usage. At present, the TAM model has been widely used in the research of mobile video adoption behavior, and the validity of this model for users' attitudes and behavior prediction in mobile video use has been fully confirmed. Although this research discussed the impact of user satisfaction on the intention to purchase online to both TAM and expectancy theory within B2C practice, the research result will provide a useful reference in developing B2C e-commerce in China. This research suggests that different marketing strategies should be designed for different customers. The research foresees that the use of mobile video applications is highly important in China in parallel with the fast development in the countries in all fields of economy. Companies should follow the technological development in order to compete in the domestic and global market. This study contributes with a proposed model for mobile video application describing the process of buying online and the steps of purchasing and the factors that affect the intention to purchase online. The indicators of video website evaluation are analyzed and classified in detail. On this basis, the research on the quality of online video websites (including information quality, system quality, service quality) is deeply elaborated the quality of online video websites. The existing knowledge focuses on the context of theory of planned behavior and technology acceptance model for investigating intention. This research goes one step ahead and integrate both the theories together with the user satisfaction and continuance intention. At the same time, the research trends of the continuous use of information systems and the impact of website quality on consumer attitudes are reviewed. The definition of related variables and the design of measurement dimensions provide a basis and reference. It is pointed out that the research on the continuous use behavior and willingness of mobile video website users has been paid more and more attention by experts and scholars. Based on the above literature review, the establishment of the research model lays a sufficient empirical foundation.