Individual's Technology Acceptance, Technology Acceptance Model - Literature review Example

Individuals’ technology acceptance literature review In the contemporary world, change is a constant thing and individuals constantly find themselves learning new processes and technologies. such technologies as the one proposed by the ministry of education  is expected to change the way communication between teachers, parents and students communicate in a big way especially as far as provision of learning materials and results is concerned (Jones and Issroff, 2007). As such, there is a growing body of literature attempting to investigate what factors determine the acceptance of certain technologies in the workplace.  According to Venkatesh, etal, (2003) several models investigating individual acceptance technology exist with the most widely known model being the Technology acceptance model (TAM) postulated by Davis (1989).  The model investigates two factors as being behind individual technology acceptance in the workplace. According to Chau & Hu (2001), these factors include the technologies ease of use as well as its perceived usefulness.  According to Ronnie, Christopher and Eugenia, (2011), individuals accept technology based on the degree to which they believe that the new technology will be free of effort as well as the degree to which the individuals believe that the new system will enhance their job performance. Davis (1989) has developed the model below that relates perceived ease of use and perceived usefulness in determining technology acceptance by individuals. Core TAM Rogers (2003) has also investigated technology acceptance by individuals. He classifies the characteristics of technology that enhance its acceptance as its usage characteristics as well as the outcomes of its usage.  According to him, outcomes of usage characteristics would include such factors as image, fun and enjoyment as well as the technology’s relative advantage. According to Chattur (2009), the technology’s perceived ease of use has been widely studied. Silva and Dias (2007) have termed the perceived ease of use as the potential user’s expectation that the technology will be free of effort in its use. Yi, Jackson, Park and  Probst, 2006 states that there is a general acceptance that technology’s acceptance will increase with increases in its perceived ease of use. Both Kholi (2004) and Lucy and Enrico, (2014) have identified different levels of acceptance which include intentional acceptance, attitudinal acceptance and behavioral acceptance (Niehaves and Ralf, 2013, Davis, 1989, Venkatesh & Davis, 2003). Yousuf, Kurnia and Robert (2011) states that perceived usefulness of technology will determine whether or not it is accepted. He defines it as the extent to which the technology will improve performance for its potential adopter. Kate, (2010) views perceived ease of use as of more importance than the technology’s perceived usefulness in determining its acceptance. However, most literature tends to dispute this (Davis, 2011). According to Barbara, (2011) ease of use is a vital determining factor for pre adoption attitude while perceived usefulness is of vital importance for determining post adoption attitudes. As such, individual’s initial decisions to accept the technology will be influenced by its being easy to use while their decision to continue using the technology will be greatly determined by their belief that the technology is useful. The figure below has been used to analyze usage and outcome usage characteristics as the factors influencing acceptance of technology; According to Niehaves, and Ralf, 2013 (2013) the technology’s flexibility will greatly determine its acceptance. If the proposed technology will be easily incorporated in the existing systems in the schools, then it will be easily accepted by the individuals. Rogers (2003), states that if the new technology is deemed as difficult to understand and use or it has a high level of complexity, then it will be hard for it to be accepted.  The same view is held by Chattur (2009), who states that complexity will decrease the possibility of the technology being accepted. To him, the technology’s complexity could also be determined by the adopters’ efficacy or the belief that they are able to use the new technology. The technology’s complexity or the degree to which the individuals view the technology as  being consistent with the existing norms, needs and adopters past experience will also determine its acceptance according to Lucy and  Enrico (2014). According to Silva and Dias, (2007), the technology’s perceived acceptance will have a greater impact on behavioral acceptance as opposed to attitudinal acceptance.  Similar sentiments are held by Barbara, (2011) who states that technologies with longer integration times will hardly be readily accepted. A considerable amount of literature also exists on the role of the technology’s perceived trial-ability in determining its acceptance. The ability to experiment on the new technology on a limited basis will increase its acceptance according to Niehaves and Ralf, 2013 (2001). According to Yousuf, Kurnia and Robert (2012), trial-ability is vital for formation of pre-adoption attitudes as opposed to post adoption attitude among the adopters. The degree to which the new technology’s results are visible to others or its visibility will also determine its acceptance according to Chen, Li and Li, (2011). If individuals easily see the results of the technology, they will easily accept it according to Chattur, (2009).  The technology’s perceived result demonstrability or the degree to which its benefits and utility will be readily apparent to the adopters will determine whether or not they accept it.  Bouten (2008) believes that the technology’s result demonstrability will greatly determine its acceptance by adopters.  Similar views are held by Barbara, (2011), who states that a technology’s result demonstrability is more vital in formation of pre-adoption attitudes than for post-adoption attitudes. Kate (2010) states that the technology’s perceived voluntariness or the degree to which its use is deemed voluntary will determine its acceptance. Acceptance increases with the technology’s voluntariness and has a bigger impact on the individual’s intention to continue using the technology rather than to adopt it. Rogers (2003) argues that whether the technology will provide benefits to the immediate users will offset its other negative perceptions and is hence critical in determining its acceptance. This is what Lucy and Enrico (2014) refers to as the technology’s relative advantage. The technology’s expectation to improve individual’s performance will influence its acceptance (Moris, 2003, Yousuf, Kurnia, and Robert, 2012). Furthermore, if individuals perceive the technology to be superior to the current way of doing things, they will readily accept it (Chattur, 2009). There is a general agreement that the technology’s added prestige will increase its level of acceptance by individuals (Yi, Jackson, Park and Probst, 2006, Brown, 2005, Venkatesh, 2004). In other words, the technology’s image or its perceived ability of its adoption to bestow its adopters with added prestige in the community will determine whether or not they accept it (Yousuf, Kurnia and Robert, 2012). If the individuals relate the new technology with a negative image, then they will hardly accept it according to Silva and Dias, 2007. If the new technology is expected to result in fun and enjoyment among the adopters, then they will readily accept it (Venkatesh and Davis, 2000). Similarly, the technology’s perceived newness will positively influence its acceptance. However, the technology’s newness and hence its acceptance could be hampered by its complexity according to Chen, Li and Li, 2011. According to Yousuf, Kurnia and Robert (2012), if individuals perceive that by adopting the new technology they will be compromising on their trust and privacy, then they would rather not accept it. As such, individuals acceptance of the new technology will be greatly influenced with the new technology’s perceived value or if its perceived benefits are more than its perceived costs to those expected to use it (Kim, 2001, Yi, Jackson,  Park, and  Probst, 2006, Niehaves and Ralf, 2013). In the words of Kate (2010) the new technology’s perceived value or perceived reward for adopting it is a key drive for the technology’s acceptance.  In addition, if the perceived risks associated with adopting the new technology are too many, then individuals will rarely accept it according Lucy and Enrico (2014). As such, the level of risk decreases the probability of the technology’s acceptance by individuals. In their work, Yousuf, Kurnia and Robert (2012) investigated the role of individual characteristics in persuading or dissuading technology acceptance. He classifies these characteristics into either demographics or psychographics.  The individual’s demographics have been found to greatly influence technology acceptance in a number of studies. These have been classified as education, gender, age and income (David, 1989, Barbara, 2011, Jordan, 2001, Yousuf, Kurnia and Robert, 2012).  In many studies, age has been found to negatively affect acceptance of new technology hence the conclusion by Venkatesh (2005) that increased age decreases acceptance of technology. This is because acceptance of technology by older groups was found to be lower than that of younger group except in technologies involving funds transfer (Chattur, M2009). The individuals’ gender has also been found to affect their acceptance of technology.  Yousuf, Kurnia, and Robert, (2012) state that different gender may have different perception of the technology hence affecting their acceptance of the technology.  While attitude towards using technology was found to be a strong predictor of acceptance of technology in men than in women, Venkatesh (2005) finds that subjective norms including social pressure influence acceptance of new technology among women more than it does for men.  Niehaves and Ralf (2013) studied the role of education in influencing technology acceptance. They conclude that the individuals’ level of education will positively affect their level of acceptance. This is because education influences the perceived ease of use meaning individuals who are highly educated would perceive the new technology easier to use and hence accept it according to Silva and Dias, (2007). Although income may not be a predictor of acceptance of the technology being introduced in schools, Venkatesh and Davis (2000) have found it to influence acceptance of technology. This is because individuals with higher incomes will have more money to invest in technology than those with less income. Among the physiological factors influencing technology acceptance is technology readiness. Lucy and Enrico (2014) see technology readiness as people’s propensity to embrace and use new technologies in accomplishing goals especially at work.  According to him, if people perceive the technology as offering them increased control, efficiency and flexibility in life as well as increased security and trust, then they will readily accept it.  In the words of Kate, (2010), technology readiness among individuals will positively influence their acceptance of the technology.  Personal innovativeness or individuals’ tendency to try new things has also been found to positively influence their acceptance of new technology. According to Chattur, (2009), there is a positive correlation between personal innovativeness and their acceptance of technology. Trust and privacy concerns are another psychological factor influencing individual’s acceptance of technology according to Bouten, (2008). Although they have never used the technology and hence they may have suspicions about its usefulness, individuals trust in the provider of the technology will help ease their anxiety and hence positively influence their acceptance.  According to Niehaves and Ralf (20013), individuals’ intentions to accept the technology will be influenced by the trust they have in the provider of the technology. In this case, this is the government. Silva and Dias (2007) view technophobia or dislike of new technologies as a negative predictor of technology acceptance. in this regard, technophobia will be assessed through such factors as cognitions, anxiety and individual attitude towards technology. Finally, individual’s self efficacy or their judgment on their ability to use the technology in accomplishing their particular job related tasks will influence their level of acceptance of the technology according to Davis (2003). In this regard, self efficacy has been found to positively influence technology acceptance Several literature has been found to exist regarding factors that influence individual’s acceptance of technology. These factors rage from those that are related to the technology itself to those factors that are related to the individuals to whom the new technology is being introduced Silva and Dias, (2007). As such, there is need for increased research on all the above factors especially with regard to the implementation of this project. This is important in a bid to ensure that there are no factors militating against the project’s implementation. Where there are gaps, the government should put strategies in place to fill them in a bid to enhance acceptance of the new technology. Technology acceptance in schools has limited literature although Silva and Dias state that governments in their bid to ease learning and operations in schools ought to introduce technology that will be deemed easy to use especially by teachers and schools administrators since they are the min drivers of technology acceptance in a learning environment. Similar views are held by Kholi (2004) although he states that technology acceptance in government institutions will be greatly influenced by government policy on the new technology although  he is of the idea that the new technology should be less complex when compared with the paper based system. Other factors that he considers as important in driving technology acceptance in schools include its visibility, result demonstrableness and voluntariness. As far as the  technology's outcome of usage, Davis states that a technology such as the one the government intends to introduce will almost be readily accepted based on its relative advantage in comparison with the paper based system. Such a system would be deemed as boosting the image of all the concerned parties while students being able to download their results from the internet will be deemed prestigious (Lucy and Enrico, 2014) elimination of the tediousness associated with the paper based system as well as the privacy and efficiency that comes with the new system will greatly boost acceptance of the electronic based systems in schools. Niehaves and Ralf (2013) have briefly analyzed the role of individual characteristics in boosting technology acceptance in schools. They are of the view that individual income levels may not have a great role to play in schools acceptance of electronic based systems since in most cases, the government would provide funds to boost its new technology policy. However, there is a general agreement that age and education would play a great role in determining technology acceptance from paper based system to electronic based system (Yousuf, Kurnia, and Robert, (2012). In this case, student and teachers are deemed to  readily accept the new technology wile parent especially the old and the less educated would have some difficuties in accepting the new technology (Chattur, M2009). According to Lucy and Enrico (2014), the stakeholders propensity to embrace and use technology in accomplishing goals will be a great determinant of acceptance to move from paper based system to electronic based system in schools. According to them, this propensity will be highest among teachers who will deem the new technology as offering them  much efficiency and flexibility. Niehaves and Ralf (20013)  have studied the role of self efficacy in determining acceptance of change in technology in learning institutions from a paper based system to an electronic based one. They seem to suggest that self efficacy will be a great determining factor in technology acceptance among student and teachers while it will be lowest among parents especially those who have never dealt with such a technology before. It should however be noted that there is very little literature  regarding  about moving from paper based system to electronic system. As such there is need for more research on this topic. Future research should be geared towards the role of knowledge management in  moving from paper based system to electronic system.             References: Venkatesh, V, Morris, M, Davis, F&, Davis, F2003, User Acceptance of Information  Technology:  Toward a Unified View,” MIS Quarterly, 27, 2003, 425-478 http://www.vvenkatesh.com/it/organizations/theoretical_models.asp Ronnie, H, Christopher, C&, Eugenia, M2011, Analysis of the technology acceptance model  in examining student’s behavioral intention to use an e-portfolio system, Australian  Journal of Education technology, vol. 27, no. 4, pp. 600-618.  http://www.ascilite.org.au/ajet/ajet27/shroff.pdf  Chattur, M2009, Overview of the technology acceptance model: Origins, development and  future directions, Indiana University, USA, Sprouts: Working papers on information  systems, vol. 9 no. 37 http://sprouts.aisnet.org/785/1/TAMReview.pdf Silva, P&, Dias, G2007, Theories about technology acceptance: Why the users accept or reject the  information technology, Brazilian Journal of Information Science, vol. 1, no. 2, pp. 69-86. http://www2.marilia.unesp.br/revistas/index.php/bjis/article/viewFile/35/59 Niehaves, B& Ralf, P2013, Internet adoption by the elderly: Employing IS technology acceptance theories  for understanding age related digital divide, European Journal of Information Systems http://www.palgrave-journals.com/ejis/journal/vaop/ncurrent/full/ejis201319a.html Chen, S, Li, S& Li, C2011, Recent related research in technology acceptance model: A literature review,  Australian Journal of Business and Management Research, vol. 1, no. 9, pp. 124-127. http://www.ajbmr.com/articlepdf/AJBMR_19_04i1n9a14.pdf Bouten, M2008, Compatibility and technology acceptance, Retrieved on 30th April, 2014, from; http://arno.unimaas.nl/show.cgi?fid=11436  Barbara, L2011, Understanding the influence of the technology acceptance model for online adult  education, Retrieved on 30th April, 2014, from; http://www.wordsinmyear.com/Barbara_2012/Documents/TAM_11113_Lauridsen_2011.pdf Kate, s2010, Social network influences on technology acceptance: A matter of tie strength, centrality  and density, Retrieved on 30th April, 2014, from; https://domino.fov.unimb.si/proceedings.nsf/0/eaa5e9b00ca2dd37c12577570035e643/$FILE/0 2_tenKate.pdf Lucy, D&, Enrico, F2014, When technology meets the mind,: A comparative study of the technology  acceptance model, Retrieved on 30th April 2014, from; http://www.enricoferro.com/OFFICE/RESEARCH/TAM.pdf Yousuf, A, Kurnia, S&, Robert, B2012, Adoption of mobile commerce services by individuals: Ameta  analysis of the literature, Retrieved on 30th April 2014, from; http://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=3&cad=rja&uact=8&ved=0CEQQFjAC&url=http%3A%2F%2Ftucs.fi%2Fpublications%2Fattachment.php%3Ffname%3DTR540.pdf&ei=2lZkU5aEAsOKOIfTgIAB&usg=AFQjCNE3aqKMPLQ-rj07OHAct2TlDl4Y_Q&sig2=iqFbJZp6nkwIeTA68qG8Kg&bvm=bv.65788261,d.ZWU Yi, M, Jackson, J, Park, J&, Probst, J2006, Understanding information technology acceptance by  individual professionals: Toward an integrative view, Information & Management, vol.43, pp.  350–363 Venkatesh, V&, Davis, F2000, A theoretical extension of the Technology Acceptance Model: Four  longitudinal field studies, Management Science, Vol 46, No2, pp 186-204 Rogers, E2003, Diffusion of Innovations, Free Press, New York.  Miller, K2005, Communications theories: perspectives, processes, and contexts. New York: McGraw- Hill. Jordan, P2001, Designing Pleasurable Products: An Introduction to the New Human Factors, Taylor  & Francis, London Jones, A &, Issroff, K2007, ‘Motivation and mobile devices: exploring the role of appropriation and  coping strategies’, ALT-J: Research in Learning Technology, Vol.15, 3, pp247-258 Davis, F1989, "Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information  Technology," MIS Quarteriy (13:3), pp. 319-339. Chau, P& Hu., P2001, "Information Technology Acceptance by Individual Conole, G2006, ‘JISC LXP:  Student experiences of technologies’, Final report of the JISC-funded LXP  project, Southampton:  University of Southampton, available online at  www.jisc.ac.uk/elp_learneroutcomes.html           Read More