Technology acceptance model and social network sites (SNS): a selected review of literature

Sureni Weerasinghe (Main Library, University of Peradeniya, Peradeniya, Sri Lanka)
Menaka Chandanie Bandara Hindagolla (Science Library, University of Peradeniya, Peradeniya, Sri Lanka)

Global Knowledge, Memory and Communication

ISSN: 2514-9342

Publication date: 3 April 2018

Abstract

Purpose

The purpose of this paper is to conduct a systematic review of studies that have used the technology acceptance model (TAM) in the context of social network sites (SNS). It describes various studies undertaken to examine user behaviours and attitudes towards SNS.

Design/methodology/approach

This paper comprehensively reviews the selected literature associated with applications of TAM in the SNS context. Different studies conducted within the SNS context were evaluated for understanding the changes incorporated into the model.

Findings

The findings illustrated that the TAM has been successfully applied via its extension and modification for explaining user adoption and acceptance of SNS.

Originality/value

The study contributes to the theoretical novelty of the body of the existing literature in the domains of TAM and SNS. The study also provides insight on future research directions by helping in identifying gaps in literature in this field.

Keywords

Citation

Weerasinghe, S. and Hindagolla, M. (2018), "Technology acceptance model and social network sites (SNS): a selected review of literature", Global Knowledge, Memory and Communication, Vol. 67 No. 3, pp. 142-153. https://doi.org/10.1108/GKMC-09-2017-0079

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Publisher

:

Emerald Publishing Limited

Copyright © 2018, Emerald Publishing Limited


Introduction

The rapid advancement of information and communication technology (ICT) in recent years has considerably altered the manner in which information is accessed, stored and disseminated. It is inevitable for organizations in the twenty-first century to substantially incorporate blends of innovative technology solutions to achieve competitive advantage and sustainability (Howell, 2016; Kripanont, 2007). Social media is one of the emerging new technologies that have attracted attention of millions of users and keeping accounts in one or more social network sites (SNS) has become one of the highly popular and increasingly growing activities on the internet (Alarcón-del-Amo et al., 2014). Social media is “a group of Internet-based applications that build on the ideological and technological foundations of Web 2.0, and that allow the creation and exchange of user generated content” (Kaplan and Haenlein, 2010, p. 61). According to Kaplan and Haenlein (2010, p. 60), there are six types of social media:

  1. “collaborative projects” (e.g. Wikipedia);

  2. “blogs” (e.g. Open Diary, LiveJournal);

  3. “content communities” (e.g.YouTube);

  4. “social network sites” (e.g. Facebook, Twitter, and LinkedIn);

  5. “virtual game worlds” (e.g. World of Warcraft); and

  6. “virtual social worlds” (Second Life).

SNSs appear to be one of the most popular and rapidly emerging social media technologies embraced by users around the world. There is an exponential increase in employing social technologies for personal as well as professional activities (Nord et al., 2014). The growing ease of using SNSs for personal interactions has led professionals to use these technologies to develop and retain professional relationships that were traditionally conducted in person or through telephones (Willis, 2008). The effective use of SNS is highly beneficial for organizations.

Yet, the acceptance and adoption of these social technologies are influenced by user perceptions, attitudes and beliefs towards the technology. Any information system could offer value to a person, institution or country only if users accept the system (Tibenderana, 2010). Exploration of models and theoretical frameworks, which are capable of explaining and predicting user behavioural tendencies across various contexts, have become an area of research interest in the domain of information systems (IS) and information technology (IT). A range of theoretical frameworks/models have been developed by different researchers to better understand user acceptance of technology, including the theory of reasoned action (TRA) (Fishbein and Ajzen, 1975), the theory of planned behaviour (Ajzen, 1991), social cognitive theory (SCT) (Bandura, 1986), the technology acceptance model (TAM) (Davis, 1989; Davis et al., 1989), the information system (IS) success model (DeLone and McLean, 1992), the innovation diffusion theory (Rogers, 1995), TAM 2 (Venkatesh and Davis, 2000) and the decomposed theory of planned behaviour (DTPB) (Taylor and Todd, 1995). Among these theoretical frameworks, the TAM, a psychology-based research model, is the most extensively used model in explaining user acceptance of IT (Kim, 2006). TAM is very frequently applied by researchers in the IS field (Jeong, 2011) and is a simple model that could be easily adapted into various contexts and hence very popular in the IS and technology acceptance research domain (Han, 2003; Kim, 2006).

Substantial empirical evidence supports TAM being parsimonious and robust over a wide range of end-user computing technologies and user populations. This paper attempts to present a critical and comprehensive review of the literature relating to the applications of TAM in the domain of SNSs. This review will help researchers identify potential ways for adapting the model to the world of social networking. The prior TAM-related work of researchers will be critically reviewed and their findings will be comparatively analysed to value the current state of knowledge and recognize the gaps in literature which could be filled by future research conducted in this area. It is expected that this review of literature will help lay the foundation for future studies that attempt to formulate TAMs capable of explaining user acceptance towards the SNS technologies.

Social network sites

Boyd and Ellison (2007, p. 211) define SNSs as a “web-based services that allow individuals to:

  • construct a public or semi-public profile within a bounded system;

  • articulate a list of other users with whom they share a connection with; and

  • view and traverse their list of connections and those made by others within the system.

SNSs are a part of the second-generation internet applications which are generally referred to as Web 2.0 of social web (Constantinides et al., 2013). Users can create personal information profiles on SNSs, invite others to access those profiles and send emails or instant messages between each other (Kaplan and Haenlein, 2010). Furthermore, Durden et al. (2007) assert that social networks are vital for the well-being of humans. SNSs cater to a wide variety of users and these sites vary according to the degree to which they integrate new information and means for communication such as mobile connectivity, blogging, podcasting, e-mail capabilities, video and photo sharing (Boyd and Ellison, 2007; Rosen and Sherman, 2006).

Examples of SNSs include MySpace, Facebook, Cyworld, Bebo, work-related contexts such as LinkedIn, content SNS like Slideshare and Flicker as well as micro SNS such as Twitter (Richter et al., 2009). In addition, ResearchGate, Google Scholar and Academia could be classified as academic SNSs (Palmer and Strickland, 2017). These sites provide an online repository where scholars could upload and share their research output. Moreover, academic SNSs enable the scientific community to develop a professional online presence (Donelan, 2015) as well as interact with peers, find new information and publicize new ideas (Palmer and Strickland, 2017).

Over the past few years, there has been a significant increase in the usage of SNSs for both business and personal purposes (Lane and Coleman, 2012). As a highly popular technology, SNSs open platforms for users to build and share their thoughts and acquire online, social, hedonic-oriented advantages (Hu et al., 2011; Boyd and Ellison, 2007). SNSs are regarded to be important for businesses as well as individuals because these help maintain the already existing social relationships and set up new ties among users (Boyd and Ellison, 2007; Constantinides et al., 2013). In some countries, SNSs are gaining more popularity in comparison to search engines (O’Dell, 2012).

The technology acceptance model

TAM is a theoretical extension of the TRA which explains the determinants of conscious behaviours (Ajzen and Fishbein, 1980; Fishbein and Ajzen, 1975). TRA posits that a person’s intention to perform a given behaviour is a direct determinant of his or her actual behaviour, because of the general tendency of people to behave as they intend to do within the existing time and context (Moon and Kim, 2001). Fred D. Davis adapted the TRA and formulated the TAM in his PhD thesis, in 1986 (Davis, 1989). The TAM was specifically designed for explaining behaviours regarding computer use (Davis et al., 1989).

The TAM provides an influential and sound theoretical basis for explaining a user’s motives towards the use of a technology (Kim, 2006). TAM postulates that two belief variables: Perceived Ease of Use (PEOU) and Perceived Usefulness (PU) are the major determinants of the user’s behavioural intention towards using a technology (Davis, 1989). PU is “the degree to which a person believes that using a particular system would enhance his or her job performance” (Davis, 1989, p. 320), while PEOU is “the degree to which a person believes that using a particular system would be free of effort” (Davis, 1989, p. 320). It is critical to consider user perceptions in the adoption of technology because of their impact on usage behaviours.

The TAM posits that the actual technology usage is shaped by the behavioural intention which is in turn affected by PEOU and PU (Davis et al., 1989). PU exerts a direct impact on the behavioural intention, while PEOU exerts either a direct effect or an indirect effect on the behavioural intention through PU (Davis et al., 1989). PU is further affected by PEOU as, “other things being equal, the easier the system is to use the more useful it can be” (Venkatesh and Davis, 2000, p. 187). The TAM also theorizes that PEOU and PU mediate the influence of external factors on the behavioural intention of technology usage (Venkatesh and Davis, 2000).

TAM has the power of explaining and predicting individual behaviour over a wide variety of end-user computing technologies and user groups while simultaneously being “both parsimonious and theoretically justified” (Davis et al., 1989, p. 985). Moreover, the TAM is capable of explaining approximately 40 per cent of variance in users’ intention towards using a technology (Venkatesh and Bala, 2008).

Technology acceptance model applications in the social network sites context

In the light of the significance of social media among people and the society, this topic has increasingly captured the attention of scholars (Khang et al., 2012). Wirtz and Göttel (2016, p. 98) conducted a literature review of the TAM within the domain of social media and confirmed that “TAM is one of the most prominent models in information technology acceptance research” and “so far the prevailing theoretical approach regarding users’ adoption of social media”. Lane and Coleman (2012) also confirmed the existence of a strong relationship between TAM and social networking media. Likewise, Lorenzo-Romero et al. (2011, p. 172) contended that TAM was suitable for explaining SNS adoption because of its “efficacy to predict the adoption of any technology” and its capability of being extended by the addition of other variables. Many previous studies have used the TAM to examine drivers of users’ acceptance and adoption of SNS.

Lane and Coleman (2012) investigated the user perceptions of usefulness and ease of use towards using social networking media by the US university students. The students’ perspective of the technological complexity of this social technology was also examined. The variable autonomy, relating to a user’s personal trait was incorporated into the proposed model. A survey was performed among a sample of 1,100 business students at a regional US university to collect data. It was found that PEOU was a significant determinant of PU, and PU was a significant determinant of the usage, thus the findings confirmed the established TAM relationships. It was revealed that more autonomous students were the ones who found social networking media more difficult to use and eventually valued this social networking platform as less useful (Lane and Coleman, 2012). Further, autonomy did not have a direct influence on the intensity of social media usage (Lane and Coleman, 2012). In contrast to these results, Hargittai (2007) found that users who were more experienced and had more autonomy were inclined to use SNSs more often via a survey performed among a diversified sample of young adults.

In a related study, Curran and Lennon (2011) examined the factors influencing user attitudes towards social networks and their intended use of social networks. The authors developed a model including five antecedent beliefs: ease of use, usefulness, enjoyment, social influence and drama (Curran and Lennon, 2011). The conceptualized framework was empirical tested using survey data gathered from 495 US university students. Findings indicated enjoyment as the most significant determinant of attitude and it had a “significant direct” influence on “intention to continue using social networks, intention to recommend social networks and intention to join other social networks” (Curran and Lennon, 2011, p. 34). Drama did not exert a direct influence on attitude but it had a “significant negative” effect on the “intention to continue using social networks and intention to recommend social networks” (Curran and Lennon, 2011, p. 34). Also, the findings revealed that social influence was an important determinant of attitude, but it negatively influenced the intention to continue using social networks and this influence was significant (Curran and Lennon, 2011). In this study, the major TAM constructs, PEOU and PU were revealed to have no impact on user attitudes or intentions in the context of social networks, which was inconsistent with the original TAM findings (Curran and Lennon, 2011). The work of Lennon et al. (2012) added to the understanding of the framework developed by Curran and Lennon (2011). The authors investigated how demographic variables were related to the differences in the users’ antecedent beliefs and attitudes towards social networks and the reasons for selecting and using certain social networks. The authors analysed the data collected by Curran and Lennon (2011). It was revealed that the users’ antecedent beliefs and attitudes towards social networks varied according to their gender, age, marital status and parenthood. More positive perceptions towards social networks were found among females in comparison to males, users under 30 years of age compared to those of 30 years and over 30 years of age, singles compared to divorce users and users without children in comparison to parent users (Lennon et al., 2012). Further, the study identified that differences existed among demographic categories in their reasons for selecting and using certain social networks (Lennon et al., 2012).

Similar to most of the above studies, Qin et al. (2011) also used university students as their study sample to investigate the factors influencing users to accept online social networks. The researchers specifically focused on the impact of social influence. They enhanced the TAM by integrating subjective norm and critical mass, which were the two variables relating to social influence. To empirically test the proposed research model, a survey was carried out among 269 social network users who were registered in the Management Information Systems (MIS) classes at a US university. It was revealed that subjective norm and critical mass significantly influenced PU, which in turn influenced the usage intention. In addition, PEOU was found to exert an indirect influence on usage intention via PU (Qin et al., 2011). Qin et al. (2011) studied the “user acceptance of online social networks for personal use in a non-organizational setting” (Qin et al., 2011, p. 897). The authors suggested that the adoption of social networks for business use should also be examined in organizational contexts due to the growing popularity of these technologies for professional use. Future research could be conducted in this area, particularly to study user behaviour towards the adoption of SNS in a work context or in other words, within an organization.

In line with the study of Qin et al. (2011) some have also attempted to investigate how social influences affect users’ SNS adoption. For instance, Sledgianowski and Kulviwat (2009) investigated the effect of critical mass, a variable relating to social influence, on user adoption of SNS. In addition to critical mass, the variables of normative pressure, playfulness, trust, PU, PEOU, intention and actual usage were incorporated into the model proposed by the authors. An online survey was conducted to gather data from a convenient sample of 289 US university students. The findings exhibited that the variables PEOU, PU, perceived playfulness, critical mass and trust were significant factors influencing the usage intention. Perceived playfulness and critical mass were found to be the strongest predictors of the usage intention. But, in contrast to the authors’ assumption, normative pressure was revealed to exert a significant but negative effect on the usage intention. In addition, the results demonstrated that intention to use and perceived playfulness significantly influenced the actual usage. In the same way, Rauniar et al. (2014) also incorporated the factors of critical mass and perceived playfulness and also trustworthiness which is equivalent to trust, into the TAM-based model designed in their attempt to understand user attitudes and usage behaviour towards social media sites. The researchers studied the users’ adoption behaviour of the most popular SNS, Facebook. The effects on the intention to use social networking based on the factors of PU, PEOU, critical mass, perceived playfulness, SNS capability and trustworthiness were determined using primary data collected from 398 Facebook users, by means of a web-based survey. It was found that the extended TAM proposed in the study performed well in explaining social media usage behaviour. Besides, the results re-established the causal links among original TAM constructs (Rauniar et al., 2014). In another study, Choi and Chung (2012) focused on studying the underlying factors and causal links influencing user intentions towards the usage of SNSs. The authors extended the TAM by integrating the constructs of subjective norm and perceived social capital, which were associated with social influence. A questionnaire-based survey was used to gather data from 179 graduate students. The relationships among the model constructs were examined via exploratory correlation and path analysis. Findings showed that PU and PEOU had a robust impact on users’ behavioural intention. Also, subjective norm was revealed to be a strong predictor of both PEOU and PU, whereas perceived social capital was an important determinant of SNS acceptance and usage (Choi and Chung, 2012).

Literature revealed some studies, conducted in the South Asian region, focusing on the TAM perspective to understand user behaviour towards social technologies. For example, Shin and Kim (2008) applied an expanded TAM to examine the attitudinal and behavioural patterns when using Cyworld, which was a very popular Korean social network site. They enhanced the TAM by adding the constructs “perceived synchronicity, perceived involvement and user flow experience” (Shin and Kim, 2008, p. 379) to predict the user acceptance of Cyworld. Data were gathered from 352 Cyworld mini-home page owners using a Web-based survey. PU was found to have a significant direct influence on attitude but an insignificant effect on the intention. The findings indicated that perceived enjoyment positively affected the attitude, but it had an insignificant effect on intention. Perceived synchronicity and perceived involvement were found to have no significant relationships. Overall, the findings indicated that the proposed research model showed “good predictive power” and that it explained the behavioural intention to use Cyworld (Shin and Kim, 2008, p. 381). In a different study, El-Haddadeh et al. (2012) explored the adoption of social networking services in corporate communication within the Chinese context. They proposed a conceptual model including the variables of PEOU, PU, loyalty, advertising strategy and trust. A survey was conducted to gather the required data from the Chinese university students who used Facebook and Renren – a very popular social networking site in China. It was revealed that consumers’ higher PEOU towards SNSs led to effective communication with the organization. However, PU was revealed to have no relationship with corporate communication. Also, PU was revealed to have a stronger effect on consumers’ trust and loyalty than PEOU. In addition, findings exhibited that a significant positive causal link existed between advertising strategy and PEOU in social networking services (El-Haddadeh et al., 2012). Yet, there is a lack of such studies in developing countries. Hence, researchers should conduct TAM-based studies in developing countries and test the TAM over cross-cultural contexts.

In the recent past, Taghavinezhad et al. (2015) carried out a study in Iran to examine factors influencing social network acceptance among graduate students. The survey strategy was used for collecting data from 360 graduate students at an Iranian university. It was revealed that PU, PEOU, external variables, attitudes and intention to use were significant determinants of the usage of social networks (Taghavinezhad et al., 2015). Yet, in this study, the authors had not specified the external variables. In another previous study, Willis (2008) confirmed that the TAM was capable of explaining and predicting SNS acceptance and use. He tested two models of technology acceptance: model A used the variables PU, PEOU, subjective norm and intention, while model B used the aforesaid variables and experience. An online survey was performed among 500 students of a US university and their experiences and beliefs of social networking systems were inquired via a questionnaire. Findings indicated that the TAM could reasonably predict the acceptance of online SNSs, but subjective norm was not predictive of this acceptance. Pinho and Soares (2011) corroborated the findings of Willis (2008) by showing that the TAM was an effective model to predict the SNS acceptance. This study was conducted in the Portuguese context. To collect data, a non-probability sample of 150 university students was surveyed. According to the results, majority of the respondents found social networks were “relatively easy to use, they become quickly skilful at using these technologies and found these quite flexible to interact with” (Pinho and Soares, 2011, p. 126). In addition, PU was revealed to be a stronger predictor of attitude than PEOU. Also, the respondents found that social networks were “quite fun and enjoyable to use” (Pinho and Soares, 2011, p. 126). Further, the findings supported the significant positive relationships between PU and attitude, PEOU and attitude and also attitude and behavioural intention of usage of social networks. Thus, this study confirmed that the TAM could potentially explain the adoption of social networks while contributing to the “validation of the model outside the Anglo-Saxon context” (Pinho and Soares, 2011, p. 125).

In a similar study, Teo (2016) attempted to investigate the determinants influencing Facebook use among university students. The author extended the TAM by adding an external variable named “Emotional Attachment (EA)”. The required data were gathered by performing a survey among 498 Thailand (public-funded) university students. It was revealed that PU, attitude and EA exerted significant direct effects on the actual usage. On the other hand, PEOU indirectly affected Facebook usage of students (Teo, 2016). Further, EA was found to have a significant direct effect on all major TAM variables: PU, PEOU, attitude and actual use (Teo, 2016). In another study, Ernst et al. (2013) focused on studying the impact of hedonic and utilitarian motivations on the users’ SNS acceptance. They proposed a model including the variables, PEOU, PU, perceived enjoyment and behavioural intention to use and tested it using survey data gathered from 415 students of a German university. The findings revealed that both PU and perceived enjoyment were significant predicators of the behavioural intention, whereas PEOU had no significant impact on the behavioural intention of using SNS. The authors concluded that hedonic as well as utilitarian motivations were drivers of SNS adoption, and hence SNS was a blend of dual information technologies (Ernst et al., 2013).

It could be seen that most of the above-discussed studies have used university students as their research subjects. This creates a gap in literature where only few studies have used professionals or employees as the subject of their research. Behaviour towards social technologies could vary depending on various professions, and the attitudes of students and employees towards these new technologies may also be different. It would be interesting to carry out future TAM-based research in the SNS context using employees/professionals as research subjects. Further, studies could be done to identify their behaviours towards SNS for personal as well as professional use.

However, Moqbel (2012) identified a dearth of research on user acceptance of social networking focused on the employee perspectives. He attempted to fill this research gap by conducting a study to explain the acceptance of SNSs by employees. Data were collected from 193 US employees using offline means as well as a web-based survey. He proposed a TAM-based model which included the constructs of usefulness, enjoyment and ease of use and intention to use (Moqbel, 2012). It was revealed that PEOU, perceived enjoyment and PU, “when accounting for control variables, explained 72 per cent” of the variance in the behavioural intention (Moqbel, 2012, p. 115). In accordance with prior studies, the results indicated that PEOU and perceived enjoyment were important predictors of employees’ behavioural intention towards the use of social networking. But it was observed that PU had a non-significant effect on the behavioural intention. Further, the results indicated that “the explanatory effect of perceived enjoyment on behavioural intention was much higher than that of perceived ease of use and perceived usefulness” (Moqbel, 2012, p. 115). In a similar attempt, Glass and Li (2013) incorporated social influence factors (subjective norm and critical mass) and demographic factors (gender and age) into the TAM to develop a model that could explain user adoption of social network technologies in the workplace. The subjects of the study were 97 MBA students at a private university in the USA, who were also engaged in working full time. More than half of the surveyed participants claimed that they used instant messaging, Facebook or both of these social technologies in the workplace for business-related or personal purposes (Glass and Li, 2013). A discriminant analysis revealed that “PEOU, PU and subjective norm (collapsed into one construct), critical mass and gender” were important factors in making distinctions between “adopters and non-adopters” of the social technologies (Glass and Li, 2013, p. 1087). In comparison to non-adopters, adopters believed that social networking technologies were more “useful, easier to use and more influenced” by others (Glass and Li, 2013, p. 1087). The results also showed that females were more inclined than males to adopt these social technologies in the workplace. This study will likely contribute to fill the gap in literature where there is no sufficient research exploring an individual’s beliefs and use of social networking technologies for business-related purposes within the work environment (Glass and Li, 2013).

On the other hand, Fasola (2015) investigated librarians’ perceptions and acceptance of Facebook and Twitter to promote library services by employing TAM 2 as a theoretical base. Data were collected through a survey of 81 registered librarians who attended the 2013 annual conference of the Nigerian Library Association. Interview sessions were also held to complement the survey data. The results revealed that majority of the librarians had positive beliefs and high acceptance of Facebook and Twitter usage to promote library services. Gender was found to have no influence on the librarians’ social media acceptance. Age and the type of library were revealed to be significant factors influencing the attitudes of librarians towards accepting Facebook and Twitter to enhance library services (Fasola, 2015). In the existing literatures, there is a dearth of studies examining Library and Information Science (LIS) professionals’ perception towards SNS from the TAM perspective. This would be an interesting area for future research where TAMs could be developed in the SNS context to identify the determinants behind the acceptance of SNS by LIS professionals.

A series of TAM-based studies which aimed to explain users’ SNS adoption have been conducted in several developed countries using panels of SNS users. Following the study of Willis (2008), Lorenzo-Romero et al. (2011) conducted a study in The Netherlands to gain more insight into the capability of TAM in predicting SNS adoption. To examine the factors influencing users to accept and use SNSs, the researchers used an extended TAM which included the variables of PU, PEOU, perceived risk, trust, attitude, intention to use and use. The proposed theoretical framework was tested with data collected from a panel of 400 Dutch users by means of an online national survey. Findings demonstrated that trust was a direct determinant of the attitude and that it had an important positive influence on each of PU and PEOU. Furthermore, perceived risk exerted a significant negative influence on use intention, while PEOU had a significant negative effect on perceived risk (Lorenzo-Romero et al., 2011). Yet, perceived risk was found to be a non-significant determinant of PU (Lorenzo-Romero et al., 2011). Moreover, the results provided empirical evidence supporting the causal links postulated by the original TAM. In the same way, Alarcón-del-Amo et al. (2014) added the variables trust and perceived risk in the TAM to conceptualize a framework that could explain the adoption of SNSs by Italian users. Online survey data were gathered from 675 Italian users of age between 16 and 74 years. The findings empirically justified the original TAM relationships. Corroborating the findings of Lorenzo-Romero et al. (2011), perceived risk was revealed to have no significant impact on PU. In addition, trust was revealed to exert a positive effect on each of the variables, attitude, PU and PEOU. Relating to the above studies, Alarcón-del-Amo et al. (2012) and Constantinides et al. (2013) used the initial TAM (Davis et al., 1989) as a theoretical basis to explore the determinants of the users’ acceptance of SNSs. In both studies, online surveys were used to collect data from SNS users aged 16-74 years old. The former study was conducted in Spain, while the latter was conducted in the context of The Netherlands. The findings of the study of Alarcón-del-Amo et al. (2012) supported most of the postulated causal links, but PEOU was revealed to exert a non-significant positive influence on the intention. The results of Constantinides et al. (2013) study supported all proposed research hypotheses. This study empirically demonstrated that the TAM performed well in explaining and predicting the acceptance of SNSs and complemented the study of Willis (2008). Along similar lines with the above studies, Howell (2016) used a quantitative approach and a non-experimental research design to test the TAM in the context of social media sites, using the constructs PU, PEOU, attitude, trust and behavioural intention while controlling for a positive mood of users. For the empirical validation of the proposed research model, data were gathered from US social media sites users of age 16-74 years. The author used a probability sample in his study, while many related studies have used non-probability samples to test their models. The results demonstrated highly significant positive correlations between the constructs PU and attitude, attitude and behavioural intention, trust and attitude and PEOU and PU. The findings corroborated as well as extended prior research findings (Willis, 2008; Pinho and Soares, 2011; Lorenzo-Romero et al., 2011) in the context of TAM and SNSs. Implications of the research included formation of positive user attitudes towards technology via education, training and technology exposure (Howell, 2016).

Almost all of the above studies have used the purely quantitative survey research strategy to gather the required data. In future, researchers who are interested in conducting TAM-based research in the SNS context could attempt to use qualitative data collection techniques such as semi-structured or focus group interviews to complement their survey data. This may improve the understanding of user adoption towards SNS.

Conclusion

The TAM has evolved as a major theoretical framework in explaining the predictors of user behaviours towards technology acceptance and the power of this model is exhibited through various studies which highlight its wide applicability across different technologies and contexts. This study presented a comprehensive review of TAM-related prior studies in the context of SNS. This literature review demonstrates that the TAM is a robust model having many successful applications in the prediction of user acceptance and adoption of SNS technologies across diverse research contexts. It is indicated by this review that there is a consistent progress in identifying new factors that exert significant effects on the major TAM variables within the context of SNS. The study also attempted to gain insight on various changes incorporated into the model by different researchers in the area of SNS. In most of the TAM-related studies in the SNS context, the major TAM variables (PEOU and PU) were revealed to be significant determinants of SNS adoption by users. Besides, constructs such as enjoyment/playfulness, social influence and trust, users’ personal traits such as autonomy, demographic variables including age and gender as well as moderators like experience were found to play an important role in the determination of user behaviours towards SNS adoption and acceptance. The various factors identified through this literature review along with the principal TAM components of PU and PEOU could be used in developing such models in the SNS context. Therefore, this review will help establish a sound basis to formulate research models with the capability of explaining user technology acceptance for future studies in the SNS context.

This literature review attempts to survey the literature and identify research gaps, thus highlighting areas that require future research. Future studies could be carried out to understand user SNS adoption in work contexts and using professionals/employees as research subjects. Specifically, less research has been carried out in the intersecting field of LIS, TAM and SNS; in other words, less TAM research focused on LIS professionals’ perspectives is available and hence could be studied in future. In addition, prospective studies could be done in the context of developing countries, leading to the validation of the TAM over cross-cultural settings. Furthermore, qualitative methods could be integrated into the research strategies associated with TAM-based studies to complement the quantitative survey data.

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Further reading

Sahoo, D.R. and Sharma, D. (2015), “Social networking tools for library services”, International Journal of Innovative Science, Engineering and Technology, Vol. 2 No. 3, pp. 69-71.

Supplementary materials

GKMC_67_3.pdf (11.4 MB)

Corresponding author

Sureni Weerasinghe can be contacted at: sureniw1@yahoo.com