Abstract
Libraries are being revolutionized by technological advancements which open up avenues to embed innovative library services. It is imperative for librarians to be in par with new technologies such as social network sites, to prove their worth in this competitive digital world. This study aims to explore factors affecting the acceptance of social network sites by university librarians by applying the technology acceptance model. The findings revealed that perceived usefulness and perceived ease of use were significant predictors of acceptance of social network sites. Trust was found to exert a significant indirect effect on the librarians’ intention to use social network sites. This study contributes to the theoretical novelty of the intersecting field of library science, social network sites and the technology acceptance model, which has received less attention in the literature. Also, this study attempts to fill the gap in the adoption literature, where librarians are rarely acknowledged as users, while supporting the validation of the technology acceptance model in a developing-country context. Overall, the proposed research model explained 58.4% (R 2 = 0.584) of variance in the dependent variable of behavioural intention.
Keywords
Introduction
The proliferation of information and communication technology has enabled libraries to embed blends of innovations for enhancing user services. Social media, including social network sites (SNS), are emerging technologies that have significantly influenced libraries around the globe (Sahoo and Sharma, 2015). SNS are web-based services that allow individuals to (1) construct a public or semi-public profile within a bounded system, (2) articulate a list of other users with whom they share a connection, and (3) view and traverse their list of connections and those made by others within the system. (Boyd and Ellison, 2007: 211)
Despite the various organizational benefits arising from them, SNS remain undervalued by many organizations (Bennett et al., 2010), while some organizations have implemented policies to restrict the use of SNS in the workplace (Brooks, 2013). Regardless of the widespread deployment of SNS, there is a high level of resistance to accepting such technologies in certain countries, specifically in developing countries (Chitumbu, 2015; Fasola, 2015). Yet it is vital that libraries in developing countries fully exploit modern technologies such as SNS in order to gain favourable benefits.
In the information landscape, the value and potential of libraries is constantly being questioned (Mishra, 2008). Libraries and, in particular, university libraries must initiate the use of new social technologies in order to prove themselves equally relevant and worthy as other information providers. University libraries should keep abreast with the dramatic changes in technology, and thus the social presence of libraries via SNS appears to be crucial. At present, the role of the librarian is changing, necessitating a librarian to provide services for end users within the digital environment. SNS provide an innovative approach for libraries to increase their visibility and reach modern tech-savvy users in their preferred environment, breaking down the walls of the traditional library system (Dickson and Holley, 2010; Fasola, 2015).
However, limited research has been conducted on the adoption motives of librarians with regard to SNS. Also, literature on the application of the technology acceptance model (TAM) in the context of developing countries is scarce. Therefore, the main objective of the study is to predict the drivers of librarians’ intentions to accept SNS in the work context. SNS acceptance was assessed by means of an extended TAM, whereby the dimensions of perceived enjoyment, trust and subjective norm were integrated into the classic TAM (Venkatesh and Davis, 1996). This study will shed light on the validity of TAM in a developing-country context and also crystallize the effect of trust, which has received less attention in the adoption literature.
Literature review
TAM was initially formulated to explain the behaviour of computer use. Thus, external factors should be incorporated into TAM to effectively explain user adoption of emerging technologies such as SNS (Ernst et al., 2013; Rauniar et al., 2014; Sledgianowski and Kulviwat, 2009). This extensive literature review aids in identifying appropriate external factors that should be incorporated into the classic TAM to develop the research model of the current study. Moreover, this literature review provides theoretical as well as empirical evidence in support of selecting TAM as the most suitable theoretical framework to serve the purpose of the study.
Researchers have proposed various models and theoretical frameworks to better understand user acceptance of new technologies. These include the theory of reasoned action (Fishbein and Ajzen, 1975), TAM (Davis, 1989; Davis et al., 1989), the theory of planned behaviour (Ajzen, 1991), social cognitive theory (Bandura, 1986), the information systems success model (DeLone and McLean, 1992), the innovation diffusion theory (Rogers, 1995) and TAM 2 (Venkatesh and Davis, 2000). TAM is a well-established model that is extensively and frequently applied in research within the information systems domain (Jeong, 2011). Kim (2006: 1716) asserts that TAM is ‘the most robust, parsimonious, and influential’ model among user-acceptance theories. TAM is popular because of its simplicity and easy applicability in different contexts. Also, TAM offers a quick and cost-effective way of capturing information on user perceptions towards a technology (Han, 2003).
Leong et al. (2018) extended TAM to examine the determinants of students’ behavioural intention to use mobile SNS for their learning purposes. The model was tested using data collected from 600 university students in Malaysia through a structured questionnaire. The findings revealed that perceived task technology was a significant predictor of users’ intention and perceived usefulness (PU). However, the moderating impact of users’ experience on intention was not supported in the study. In a related study, Naqvi et al. (2019) explored the influence of privacy concerns and demographic factors on the intention to use social networking sites by applying TAM. The data was gathered by surveying a convenience sample of 838 university students. The results indicated that perceived privacy, demographic factors and PU significantly influenced user intention. Furthermore, it was revealed that age was not a moderator between perceived ease of use (PEOU) and PU. In another study, Zabadi et al. (2018) investigated the predictors of customers’ intention to purchase online via SNS. A conceptual model was framed using TAM and the theory of reasoned action. The model was empirically tested using graduate and undergraduate students in Jordon. It was found that trust exerted the greatest influence on the students’ behavioural intention, followed by PU.
Rauniar et al. (2014) re-established the original TAM findings in their attempt to examine user adoption of Facebook. The authors used a web-based survey to gather data from 398 Facebook users, and extended TAM by adding the factors of critical mass, perceived playfulness and trustworthiness. In another study, through a survey conducted among 495 university students in the USA, Curran and Lennon (2011) found that the principal TAM components of PU and PEOU were non-significant determinants of user attitudes and intentions towards using social networks. The authors observed that enjoyment was the strongest predictor of attitude. Also, the findings exhibited that social influence exerted a significant impact on attitude and a significant but negative impact on user intention to continue using social networks. Several other researchers have also attempted to study the impact of social influence on SNS acceptance by enhancing TAM, integrating variables such as subjective norm, critical mass (Qin et al., 2011; Sledgianowski and Kulviwat, 2009) and perceived social capital (Choi and Chung, 2012).
Dixit and Prakash (2018) conducted a survey in the context of India and rendered empirical evidence in support of TAM being an effective model to predict users’ intention towards using social networking sites. Various other researchers have also provided empirical evidence in support of TAM being an effective model to predict and explain user acceptance of SNS (Howell, 2016; Lorenzo-Romero et al., 2011; Pinho and Soares, 2011; Shin and Kim, 2008; Taghavinezhad et al., 2015; Willis, 2008). Moreover, Weerasinghe and Hindagolla (2018) conducted a literature review and illustrated that TAM has been successfully applied via its extension and modification to explain user acceptance of SNS.
Few researchers have attempted to study the perspectives of employees towards SNS acceptance (Fasola, 2015; Glass and Li, 2013; Moqbel, 2012). In his attempt to gain insight into the acceptance of SNS by US employees, Moqbel (2012) observed that PEOU and perceived enjoyment were significant determinants of the users’ intention to use SNS. In a similar study, Glass and Li (2013) surveyed 97 Master’s in Business Administration students at a private US university who were also engaged in full-time work. In this study, more than half of the participants indicated that they utilized instant messaging, Facebook or both in the workplace for business-related or personal purposes. Applying TAM 2 as a theoretical framework, Fasola (2015) attempted to understand librarians’ acceptance of Facebook and Twitter in promoting library services. Data was gathered via a survey and interview sessions carried out among 81 librarians who participated in a Nigerian conference. It was found that most of the librarians expressed positive perceptions and high acceptance of using Facebook and Twitter to promote library services.
Research model and hypotheses
TAM (Davis, 1989; Davis et al., 1989) is applied as a theoretical framework because of the importance of having a validated theoretical base to explain the underlying relationships among the relevant factors. TAM is a robust model and validated to be parsimonious with high explanatory power of the variance in users’ technology acceptance in a wide variety of contexts (Park et al., 2009).
In this study, ‘behavioural intention’ is used as an indicator of user acceptance, which is in conformity with many previous studies in the SNS context (Choi and Chung, 2012; Howell, 2016; Moqbel, 2012; Pinho and Soares, 2011; Qin et al., 2011; Shin and Kim, 2008). Figure 1 illustrates the proposed research model.
The proposed research model.
PU, an extrinsic motivation for a user, is ‘the degree to which a person believes that using a particular technology will enhance their performance’ (Davis, 1989: 320). In the context of SNS, users frequently interact with other users and, across these interactions, will recognize their PU by developing strong interpersonal bonds. Hence, the behavioural intention to use SNS will be increased (Pinho and Soares, 2011). The technology-adoption literature amply demonstrates evidence in support of a direct relationship between PU and intention to use (Alarcón-del-Amo et al., 2012; Ernst et al., 2013; Kuo and Lee, 2009; Lee et al., 2003; Shin and Kim, 2008; Venkatesh, 2000). Thus, the following hypothesis is proposed: Hypothesis 1 (H1): The PU of SNS will have a significant positive effect on the behavioural intention to use them.
PEOU is defined as ‘the degree to which a person believes that using a particular system would be free of effort’ (Davis, 1989: 320). For users to accept SNS, they must feel that these sites are easy to use. A considerable number of prior studies have verified that PEOU is an important predictor of the behavioural intention to use a technology (Alarcón-del-Amo et al., 2014; Choi and Chung, 2012; Davis, 1989; Lorenzo-Romero et al., 2011; Moqbel, 2012; Shin, 2008; Sledgianowski and Kulviwat, 2009; Willis, 2008). Therefore, the following hypothesis is proposed: Hypothesis 2 (H2): The PEOU of SNS will have a significant positive effect on the behavioural intention to use them.
Furthermore, TAM posits that PEOU has an effect on behavioural intention indirectly via PU (Davis, 1989). Venkatesh (2000: 343) indicates that ‘PU will be influenced by PEOU, because the easier a technology is to use, the more useful it can be’. Several studies confirm the causal link between PEOU and PU (Alarcón-del-Amo et al., 2014; Choi and Chung, 2012; Karahanna and Straub, 1999; Pinho and Soares, 2011; Qin et al., 2011; Venkatesh and Davis, 2000). Thus, the following hypothesis is proposed: Hypothesis 3 (H3): The PEOU of SNS will have a significant positive effect on the PU of using them.
Fishbein and Ajzen (1975: 302) define ‘subjective norm’ as a ‘person’s perception that most people who are important to him [stet] think he should or should not perform the behavior in question’. Prior empirical studies have shown that social influence plays a key role in users’ adoption of various technologies, such as blogs (Hsu and Lin, 2008), electronic messaging (Rice et al., 1990), online games (Hsu and Lu, 2004) and instant messaging (Premkumar et al., 2008). Taylor and Todd (1995) found that subjective norm was a strong predictor of user intention. Wirtz and Göttel (2016) clarified that ‘subject norm’ is one of the most predominant TAM constructs in the social media context. Brooks (2013) stressed that any study involving social media use should consider the ‘social aspect’. The subjective norm construct has been taken into consideration by various researchers in the realm of SNS (Choi and Chung, 2012; Glass and Li, 2013; Kim, 2011; Qin et al., 2011; Willis, 2008).
Further, Davis et al. (1989) indicated that social influences can affect behaviour through PU via the theoretical mechanisms of internalization and identification. According to TAM 2 (Venkatesh and Davis, 2000), social influence has a direct impact on PU regardless of the system being voluntary or mandatory. In the current study, the use of SNS in the workplace was voluntary. It can be assumed that subjective norm, which is a variable of social influence, would have a significant direct effect on PU. Qin et al. (2011) also provided evidence to support this notion. Therefore, the following hypotheses are proposed: Hypothesis 4 (H4): Subjective norm will have a significant positive effect on the behavioural intention to use SNS and Hypothesis 5 (H5): Subjective norm will have a significant positive effect on the PU of SNS.
Perceived enjoyment is defined as ‘the extent to which the activity of using the computer is perceived to be enjoyable in its own right, apart from any performance consequences that may be anticipated’ (Davis et al., 1992: 1113). Perceived enjoyment as an intrinsic motivational factor has been recognized as exerting a significant influence on technology acceptance, mainly for hedonic systems (Davis et al., 1992; Koufaris, 2002). Rosen and Sherman (2006) stated that SNS are a form of hedonic technology, and they pointed out that any research model attempting to explain SNS adoption must incorporate the variable of perceived enjoyment.
In the context of SNS, several researchers have tested the influence of enjoyment on SNS adoption (Curran and Lennon, 2011; Ernst et al., 2013; Hu et al., 2011; Kim, 2011; Moqbel, 2012; Shin and Kim, 2008). Furthermore, a number of previous studies have demonstrated that PEOU has a significant positive effect on perceived enjoyment (Davis et al., 1992; Ernst et al., 2013; Gu et al., 2010; Hu et al., 2011; Moqbel, 2012; Teo et al., 1999; Van der Heijden, 2004). Based on the evidence, the following hypotheses are proposed: Hypothesis 6 (H6): Perceived enjoyment will have a significant positive effect on the behavioural intention to use SNS and Hypothesis 7 (H7): The PEOU of SNS will have a significant positive effect on the perceived enjoyment of using them.
Trust is an effective tool; it reduces uncertainty and risks while producing a sense of safety (Lin, 2011). User trust in Internet-based technologies is perceived to play an important role in users’ intention to accept technology (Gao and Bai, 2014). According to Gefen et al. (2003: 308): ‘trust is the expectation that other individuals or companies with whom one interacts will not take undue advantage of a dependence upon them’. Even though users believe that a new technology is easy to use and useful, if they have low trust towards that technology, it may slow or prevent the adoption of the new technology (Howell, 2016). Several researchers have integrated the construct of ‘trust’ into their investigations on user acceptance of electronic services (Alsajjan and Dennis, 2010; Gefen et al., 2003; McKnight et al., 2002; Pavlou, 2003; Suh and Han, 2003).
Also, in an online environment, trust is a predictor of PU because it guarantees that users will get their anticipated utility from the interface of the Web, depending on the site and the users behind the site (Gefen et al., 2003). The effect of trust has been examined by researchers who have concluded that trust influences PU (Gao and Bai, 2014; Ha and Stoel, 2009; Pavlou, 2003; Shin, 2008) as well as PEOU (Gefen et al., 2003; Pavlou, 2003; Shin, 2008). In the SNS context, Lorenzo-Romero et al. (2011) and Alarcón-del-Amo et al. (2014) have identified that trust is an important predictor of both the PU and PEOU belief variables. In line with the aforementioned evidence, the following hypotheses are proposed: Hypothesis 8 (H8): Trust will have a significant positive effect on the behavioural intention to use SNS; Hypothesis 9 (H9): Trust towards SNS will have a significant positive effect on the PU of SNS; and Hypothesis 10 (H10): Trust towards SNS will have a significant positive effect on the PEOU of SNS.
Methodology
The study followed a quantitative approach using a survey strategy. The study population comprised of all university librarians – including librarians, deputy librarians, senior assistant librarians and assistant librarians – employed in the 15 state universities accredited with the University Grants Commission in Sri Lanka. The size of this population was 124. Sampling techniques were not applied since the entire study population was used in the study.
The main research tool of this study was a self-designed questionnaire, prepared in English, which consisted of two parts. The first part was structured in nominal/ordinal scales to obtain the demographic characteristics of the subjects. The second section related to the measurement of factors which captured the feelings and intentions of the respondents towards SNS use in the workplace. This part was structured using theoretical constructs that have been previously validated in TAM-based studies (Table 1). Table 1 shows the measurement items that were adapted for each construct in the model. A multiple-item seven-point Likert scale was used to measure the constructs.
Measurement items for the major constructs in the model.
A pilot survey was conducted among a random sample (n = 40) of university librarians to ensure the reliability and validity of the measurement items. Refinements were made based on the feedback from the pilot survey. Some items (namely, SN1 and TR5) were found to have low loading values on their appropriate factors and hence were dropped from the instrument.
The finalized questionnaire was administered to the study population over a two-month (April–May 2017) period using both offline and online means, including a web survey, posted questionnaires and personally administered questionnaires. The data analysis was carried out using the Statistical Package for the Social Sciences (SPSS), version 23. The model was tested using path analysis, whereas factor analysis was performed through the principal component method.
Results
Demographic characteristics
One hundred and sixteen questionnaires were returned, producing a response rate of 93%. Of these respondents, 60% were female and 40% were male. More than 70% of the population belonged in the 31–50 age category. With respect to their current academic position, the highest percentage (40%) of respondents held a Grade 2 senior assistant librarian designation. Further, the majority of the respondents (74%) had graduated at the Master’s level. Regarding the respondents’ work experience as a university librarian, 33% reported that they had more than 15 years of experience, while 27% had 6–10 years of experience. Table 2 shows the university librarians’ experience in using SNS in the workplace, indicating that the respondents who had used SNS in the workplace for 1–5 years were in the majority (44.8%).
Experience of university librarians in using SNS in the workplace.
Reliability and validity assessment
Table 3 presents the reliability of the constructs. All the Cronbach’s α values of the construct items exceeded the acceptable level of .7 (Peter, 1979; Sekaran, 2000), demonstrating the high internal consistency of the measures (Table 3). The results indicated that all the item-to-total correlation values exceeded .5 and all the inter-item correlation values exceeded .3, agreeing with the recommendations made by Robinson et al. (1991), and thus verifying that the questionnaire was a reliable measurement tool.
Summary of Cronbach’s α, inter-item correlation and item-to-total correlation values.
The convergent validity of the measures was assessed by performing factor analysis employing the principal component method with varimax rotation using SPSS (version 23). As shown in Table 4, for all of the constructs in the proposed model, the items measuring the same construct loaded onto a single factor. The total loading of variance explained by the six variables was approximately 83%. The factor loading values of most of the construct items exceeded .6, complying with the recommendations of Dillon and Goldstein (1985). Yet all the factor loadings of the survey items exceeded the acceptable level of .5, as recommended by Hair et al. (1995). These results demonstrate the convergent validity of the survey instrument. Overall, the reliability and validity assessment indicated that the survey instrument was a reliable and valid measurement tool.
Factor loadings of the survey items.a
Extraction method: principal component analysis.
Rotation method: varimax with Kaiser normalization.
a Rotation converged in six iterations.
Results of the causal model
A path analysis, based on a series of multiple regression analyses with the ordinary least squares method in SPSS, was used to test the hypothesized relationships among the variables in the proposed research model. The results of the hypothesis testing are shown in Table 5.
It was evident from the results that the paths for Hypotheses 1 and 2 were significant (Hypothesis 1: β = .368, t = 4.487, p < .05; Hypothesis 2: β = .421, t = 5.674, p < .05). This verifies that there exist significant causal links between PU and behavioural intention, as well as between PEOU and behavioural intention, agreeing with many prior TAM-related studies. Further, it was revealed that PEOU (β = .421) exerted a stronger effect on behavioural intention than PU (β = .368). The path from PEOU to PU was also significant (β = .298, t = 3.881, p < .05), supporting Hypothesis 3.
Results of hypothesis testing.
Hypothesis 4 assumed that subjective norm would be a direct determinant of behavioural intention. Yet the results indicated that the path for Hypothesis 4 was not significant (β = .036, t = 0.485, p > .05). Hypothesis 5 proposed that subjective norm would have a positive effect on PU. Yet, contradicting this assumption, it was revealed that the proposed path was not significant (β = .145, t = 1.748, p > .05). Hypothesis 6 tested the effect of perceived enjoyment on behavioural intention. Contrary to expectations, it was found that the path for Hypothesis 6 was not significant (β = .129, t = 1.651, p > .05). However, Hypothesis 7, which assumed that PEOU would be a positive predictor of perceived enjoyment, was supported (β = .492, t = 6.028, p < .05).
Hypotheses 8 to 10 tested the effects of trust. Hypothesis 8 proposed that trust would have a significant positive effect on behavioural intention. The path for Hypothesis 8 was not significant (β = −.13, t = −0.155, p > .05), contrary to expectations. In addition, the hypotheses about trust assumed that the variable would be a positive predictor of PU (Hypothesis 9) and PEOU (Hypothesis 10). Both the proposed paths were significant in the hypothesized direction (Hypothesis 9: β = .393, t = 4.551, p < .05; Hypothesis 10: β = .349, t = 3.980, p < .05), supporting Hypotheses 9 and 10.
Further, the indirect effects of trust were examined. The total indirect effect of trust (mediated by PEOU = β = .349*.421 = .147, p < .05 + mediated by PU = β = .393*.368 = .145, p < .05 + mediated by both PU and PEOU = β = .349*.298*.368 = .038, p < .05) on behavioural intention was significant (β = .330, p < .05). These results implied that even though trust did not directly influence behavioural intention, it exerted a significant indirect effect on behavioural intention via PEOU and PU.
It was also found that R 2 = 0.584, which suggests that all five predictors (PU, PEOU, perceived enjoyment, subjective norm and trust) in the model together explained the 58.4% of variance in the users’ behavioural intention (dependent variable) to use SNS. Figure 2 displays the final validated research model of the study.
Validated research model (*p < .05).
Discussion
In accordance with the original TAM, it was found that PEOU and PU were salient predictors of users’ intention to use SNS in the workplace context. These results indicate that university librarians formed intentions to use SNS in the workplace because they believed that SNS were useful for them and these sites were easy to use. Furthermore, PEOU was revealed to be a stronger predictor of behavioural intention than PU. The explanation for this finding could be attributed to the fact that ‘easy to use technologies are more likely to be used than those that are difficult to use, regardless of how useful they are perceived to be’ (Willis, 2008: 16). Moreover, users will not acknowledge the use of websites where a lot of effort is required to locate their features and navigate through the sites (Pillai and Mukherjee, 2011).
It was also revealed that PEOU was positively associated with the PU of SNS, suggesting that ‘increased ease of use is likely to improve user perceptions of usefulness’ (Kim, 2006: 1716). Furthermore, when a system is easy to use, less effort will be required to use it, and the effort saved could be allocated to achieve other tasks, contributing to better performance (Davis, 1989). The established causal links between PEOU, PU and behavioural intention in TAM were verified in this study.
It was expected that subjective norm would play a vital role in the determination of SNS acceptance due to the social nature of SNS. Yet, contrary to expectations, it was revealed that subjective norm was not a significant determinant of SNS acceptance. This result contradicts the results of several prior studies which found subjective norm to be a significant determinant of intention (Glass and Li, 2013; Hsu and Lin, 2008; Hsu and Lu, 2004; Premkumar et al., 2008; Rice et al., 1990). In the SNS context, Qin et al. (2011) also found that subjective norm significantly influenced PU, which in turn had an effect on user intentions. But Qin et al. (2011) studied user acceptance of SNS for personal use in a non-organizational setting. This differs from the current research context, in which SNS usage in an organizational setting was examined. Therefore, results may depend on the research setting. The results imply that university librarians will not be influenced to use SNS in the workplace through social pressure from peers or people important to them. Also, the majority of the participants in the current study had experience in using SNS, and users with experience in using a system are less likely to be influenced by social pressure (Venkatesh and Davis, 2000; Willis, 2008).
Even though SNS are more associated with hedonic aspects, providing more fun and enjoyment for users, the component of perceived enjoyment was found to be a non-significant predictor of SNS acceptance, corroborating the results of Shin and Kim (2008). Yet several other researchers have observed perceived enjoyment to be a strong predictor of intention to use SNS (Kim, 2011; Moqbel, 2012). The current study was conducted in a workplace context. The respondents may therefore have considered SNS as a utilitarian (productivity-oriented) system rather than showing concern for their hedonic nature. A utilitarian system has more utility value and increases a ‘user’s task performance while encouraging efficiency’ (Van der Heijden, 2004: 696). It appears that the university librarians believed that SNS would help them to achieve expected tasks by increasing their work productivity and performance. Hence, in the workplace context, it is evident that perceived enjoyment loses its power to PU in the adoption of SNS.
However, PEOU was found to exert a significant positive influence on perceived enjoyment, conforming several prior studies (Davis et al., 1992; Hu et al., 2011; Moqbel, 2012). This suggests that easy-to-use systems are more likely to be perceived as enjoyable. PEOU is inversely associated with the perceived complexity of SNS use, so it could have an impact on perceived enjoyment, since technologies that are difficult to use are less likely to be perceived as enjoyable (Teo et al., 1999).
Trust was revealed to have no direct impact on behavioural intention. Similarly, Howell (2016) found that there was a negative and insignificant correlation between trust and behavioural intention. However, Slegianowski and Kulviwat (2009) obtained different results in their study, in which trust was identified as having a significant positive effect on the intention to use SNS. Trust in a website is built through users’ belief that proper safety mechanisms are included in the site (Gefen et al., 2003). In this study, trust was not a direct determinant of users’ intention, and the reason may be that university librarians tend to think that using SNS – specifically Facebook – entails risks and no proper safety measures are incorporated within these sites.
However, trust was revealed to exert a significant positive effect on both PU and PEOU, agreeing with the studies of Lorenzo-Romero et al. (2011) and Alarcón-del-Amo et al. (2014). The results imply that the more users trust SNS, the greater will be the belief in the ease of use and usefulness of the sites. The more a person trusts a site, the less time and effort will be allocated to browsing and understanding the privacy settings, policies or terms of the site, and consequently the person will perceive that the site is easy to use (Shin, 2008). On the other hand, trust assures that a user will gain the expected utility from SNS; hence, trust is a predictor of the PU of SNS (Gefen et al., 2003).
Furthermore, trust exerted a significant indirect influence on behavioural intention through PEOU and PU. This indicates that trust is also an important factor in determining user acceptance of SNS use. Forming perceptions of trust about SNS in librarians will improve their perceptions of the ease of use and usefulness of SNS, which in turn will positively affect their intention to use SNS.
The five determinants of the proposed model accounted for 58.4% of variance in the dependent variable (R 2 = 0.584) of behavioural intention to use SNS. This demonstrates that the proposed model provides a good explanation for the acceptance of SNS in the workplace by Sri Lankan university librarians. The overall findings demonstrate the appropriateness of using TAM to explain the behavioural intention of Sri Lankan university librarians to use SNS in the workplace.
Conclusion
The findings indicate that PU and PEOU were the most influential factors in the acceptance of SNS by Sri Lankan university librarians. Also, it was seen that, in the workplace context, perceived enjoyment lost its power to PU in SNS adoption. Trust was a strong factor in determining SNS acceptance. Based on the results, it is recommended that the motivational factors of PU, PEOU and trust should be taken into account by library management and practitioners, as well as SNS developers, in designing interventions to implement and enhance the effective use of SNS in the workplace by university librarians.
The study provides empirical evidence to support TAM’s already established relationships between the constructs of PU, PEOU and behavioural intention. These findings are consistent with those of a considerable number of prior studies in the TAM literature. It was also revealed that trust significantly influenced intention indirectly via PEOU and PU. The component of trust has received less attention in the user-acceptance literature in comparison to the components of PU and PEOU. However, this study supports the idea that trust plays a crucial role in the formation of user intentions to use SNS. This study provides insights into the applicability of TAM in a developing-country context, as well as providing empirical evidence to support the validity of TAM across different cultural contexts.
This study will aid university librarians to assess their level of SNS acceptance, identify factors that cause them to lag behind in the use of SNS, and take measures to increase the effective use of SNS in the workplace. This will lead to librarians increasing their work productivity and their contribution to fulfilling the goals of their library.
According to the findings of the study, the motivational factors of PU, PEOU and trust were the key drivers of SNS acceptance. Library management and practitioners should take into account these drivers when designing interventions, including training and marketing to enhance and implement SNS in university libraries effectively and efficiently. The findings of this study could be used by top library management to motivate targeted user groups who are less inclined to use SNS in their work. Awareness programmes must be conducted to educate librarians, elaborating the usefulness and ease of use of SNS, and outlining the simplicity and user-friendliness of these technologies, as well as the productive benefits offered by SNS to libraries. It is vital for university libraries to grasp the potential of the concept of SNS in order to remain competitive among information providers in this digital era.
Furthermore, in an online environment, safety and privacy issues are of vital concern (Alarcón-del-Amo et al., 2014); hence, trust plays an imperative role in influencing university librarians to use SNS in the workplace. Library management should implement well-planned and well-administered strategies and policies for the use of SNS in the workplace in order to ensure a safe online environment for users. It is hoped that the major findings of this study will help university librarians to gain more knowledge about the experiences of using SNS in the workplace, which will aid in preparing them to be in par with changes in their profession.
This study was limited to a single country (Sri Lanka) and restricted to university-sector libraries. Also, the study employed a cross-sectional survey strategy for data collection. Thus, changes in user beliefs over time were not acquired via the study. Furthermore, this study used self-reported data to measure acceptance. Lee et al. (2003) highlighted that the use of self-reported usage is a limitation of TAM-based studies, where these studies rely heavily on a subjective measure of usage instead of measuring the actual usage.
This study could be replicated by taking into account a wider sample, spanning all universities (including those in the private sector) and higher education institutions in Sri Lanka. As a future research direction, this study could be repeated using samples from other countries and performing cross-cultural comparative analysis associated with SNS acceptance. Also, a similar type of study could be performed by applying a longitudinal approach for data collection in order to capture the changes in user intentions over time. In future research, it could be possible to improve the results by extending the model in this study to form a more complex model by incorporating other factors, as well as moderators (e.g. age, gender), in order to better understand user acceptance of SNS.
Footnotes
Declaration of conflicting interests
The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.
Funding
The authors received no financial support for the research, authorship and/or publication of this article.
