My Two Key Take-ons that Promote the Acceptance and Adoption of New Technology

In my previous blog, I established myself as an adult learner. Along this process of adult learning, I aspire towards building connections, increasing my critical consciousness, making contributions, co-constructing, and attaining mastery. Such hopes are subject to social realties of the time. We live in an era of digital technology hastily and aggressively integrating all facets of our lives. We can be inactive and get submerged and swept away in technologies’ waves of changes or we can act, through anchoring and adjusting ourselves to our digital-era’s realities with critical consciousness. I choose to adopt new technologies (act & reflect). But what drives this action and how is it that some may be more inclined to accept technology than others. In exploring my acceptance of technology as an adult learner, I will ground my discussion on the Technology Acceptance Model (TAM) developed by F. D. Davis (Davis, 1989) and the Technology Readiness Index (Tri) introduced by A. Parasuraman (Parasuraman, 2000).

Davis (1985) investigated three research questions (figure 1) which supported the construction of TAM. I believe these questions align to my exploration of adopting and accepting technology. However, the theoretical concepts established in TAM 3 (Venkatesh & Bala, 2008) through the advancement of the model over the years from TAM 1 (Davis, 1989), TAM 2 (Venkatesh & Davis, 2000) and eventually, TAM 3 (Venkatesh & Bala, 2008), serves as the main theoretical framework for my post.  

Figure 1

Research question proposed by F. D. Davis (Davis, 1985)

        Davis (1985) suggested two constructs of TAM, perceived usefulness (PU) and perceived ease of use (PEOU) that affect a participants’ decision making in using technology. These constructs establish a participant’s intention to use technology. Hence, the intention to use technology is caused by PU and/or PEOU, which influences a participant actually using technology (Davis, 1985). A participant’s PU and PEOU are brought on by “determinants” (Venkatesh & Davis, 2000; Venkatesh & Bala, 2008). Venkatesh and Bala (2008) classify  determinants into “individual differences, system characteristics, social influences, and facilitating conditions” (p. 276). Relevant to my experiences, I regard individual differences and systems characteristics as chief areas that influence my adopting of new technologies.

        Parasuraman (2000), pioneered the construct of technology-readiness. He explains technology-readiness as an individual’s predisposition to accept and use technology. It is a “state of mind” formed by a combination of “mental enablers and inhibitors” (Parasuraman, 2000, p. 308). He posits that in our repertoire of feelings towards technology, cohabiting are feelings of favorability and unfavorability. Our stance, on whether we embrace, or use technology can be predicted from where we place ourselves on this range of feelings about technology (Parasuraman, 2000). From his studies, he established four measurable personal characteristics that affects technology readiness. “Optimism and innovativeness” as the mental enablers and “discomfort and insecurity” as mental inhibitors (Parasuraman, 2000, p. 311).

         At times feelings of doubt, wariness, and agitation creeps in, but my resolve to grow, develop, and transform my knowledge, skills, and attitudes stifle these inhibiting emotions. These prevailing enablers, optimism and innovativeness indicate my technology readiness (Parasuraman, 2000) and is closely tied to my beliefs of the ability and distinctive aspects of technology or as Venkatesh and Bala (2008) designate, “system characteristics” (p. 276). Technology as a tool may help to problem solve and reduce the wastage of time, resources, movement, energy spent on repetitive and redundant tasks. A contributor to my efficacy, enhancing my desire to create and adopt new, more efficient designs, processes, and products of learning. 

         (Davis, 1989) through TAM underscores the significance of PEOU in its causal relationship with behavioral intentions to use technology. Moreover, he establishes behavioral intent as a mediator between PEOU, and the behavioral use of technology. Thus, behavioural intent is caused by PEOU and influences behavior use or the adopting and accepting of new technologies. Figure 2 highlights two determinants affecting perceptions of technologies ease of use (Parasuraman, 2000; Venkatesh & Davis, 2000; Venkatesh & Bala, 2008). Furthermore, it emphasises some initiatives that we as learners may perform to help support our behavioural use of technology.

Figure 2

Reinforcing perceptions of PEOU to promote adult learner taking on 

and using new technology

References

Davis, F. D. (1985). A technology acceptance model for empirically testing new end-user information systems: Theory and results. [Unpublished doctoral dissertation]. MIT Sloan School of Management,Cambridge, MA. https://dspace.mit.edu/handle/1721.1/15192Links to an external site.

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology.  MIS Quarterly, 13(3), 319-340. 

Parasuraman, A. (2000). Technology readiness index (TRI): A multiple-item scale to measure readiness to embrace new technologies. Journal of Service Research: JSR, 2(4), 307–320. https://doi.org/10.1177/109467050024001

Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273–315. https://doi-org.er.lib.k-state.edu/10.1111/j.1540-5915.2008.00192.xLinks to an external site..

Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46, 186–204.https://k-state.primo.exlibrisgroup.com/permalink/01KSU_INST/1260r8r/cdi_gale_infotracacademiconefile_A62347235Links to an external site.