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For organizations to succeed, knowledge is critical (Garavelli, Gorgoglione & Scozzi 2002; Goh 2002; Karlsen & Gottschalk 2004). However, knowledge transfer can have barriers even if an organization is fully dedicated to managing its knowledge (Szulanski 1996). These barriers include causal ambiguity, arduous rapport between knowledge holder and recipient, or recipient's Absorptive CAPacity (ACAP) (Szulanski 1996). The first two appear to be resolved with horizontal organizational structures (Karlsen & Gottschalk 2004; Tang, Xi & Ma 2006; Uygur 2013). But the third, the recipient's ACAP, stubbornly remains obstructive (Szulanski 1996). ACAP is often construed an dynamic organizational capability to acquire, assimilate, transform and exploit knowledge (Zahra & George 2002). Having said that, from an individual perspective, it remains less researched and understood (Dolmark, Sohaib & Beydoun 2019; Dolmark et al. 2021; Lowik, Kraaijenbrink & Groen 2017; Minbaeva, Mäkelä & Rabbiosi 2012). As individuals are part of organisations (Cohen & Levinthal 1990, p. 131), organisation’s knowledge transfer stems from individuals behaviour (Minbaeva, Mäkelä & Rabbiosi 2012). Understanding how individuals absorb knowledge can help understand the transfer of knowledge within organisations.
In the educational context, technology as an enabler (Lin, Chang & Chang 2004)impacts students beyond their education (Raskind & Scott 1993). The Technology Readiness (TR) dimensions measure individuals’ belief in technology (Lin, Shih & Sher 2007), aligning well with individual ACAP. As behaviour is influenced by beliefs (Ajzen 1991), an individual's belief in technology can be expected to affect their learning behaviours and measured by the Individual Work Performance (IWP)(Koopmans et al. 2013). Universities are an ideal context to examine knowledge transfer and learning behaviour since they pursue the goals of knowledge transfer to individuals. In fact, improving the effectiveness of e-learning and e-learning systems is an essential issue for education and information systems (Ozkan, Koseler & Baykal 2009). When the context of experimentation is conducted in the classroom settings, research yields results that are easier to implement for teachers (Rosenberg & Koehler 2018). Students also benefit from the set of technologies they have learned to use during their education (Raskind & Scott 1993).
As there is already little research into ACAP at the individual level, there is even greater absence of research into bridging technology and individual ACAP. This research aims to examine if there is a causal effect between technology readiness dimensions and individual ACAP towards their learning behaviour. Our research question is “what impacts an individual's technological belief has on their capability to absorb knowledge towards their learning behaviour”. Extending the scope of knowledge using TR would be a valuable benefit rather than taking a shallow view into ACAP. This paper revisits the relation between ACAP at the individual level, technological beliefs, and behaviour to understand said relation better.