THE ROLE OF HIGHER EDUCATION IN MOULDING THE FUTURE WORKFORCE AND THE SIGNIFICANCE OF TECHNOLOGICAL ADAPTATION TO THE SERVICE SECTOR'S GROWTH

Abstract

"Let's face it: in the age of Google and Wikipedia, the university and, most likely, secondary school business models will have to alter. We cannot make a life selling truth anymore. They are instantly accessible with the click of a mouse" (Firenstein, 2013). Despite information technology's long history as a major field of study, the last decade has seen a dramatic shift in the field's focus due to the rise of the Internet. To account for the dramatic developments across both technologies and their settings, many researchers have investigated and presented models and theories of technology adoption to anticipate and explicate user behaviour with technology. Most of these theories and models were created in the United States, and each one proposes a unique collection of determinants and moderators. Thus, it is questioned if the models and theories of technology acceptance developed, adapted, and extended in the United States are applicable in other nations, particularly India. Additionally, it is speculated that other potential determinants and moderators may also play significant roles in this setting. This paper (1) reviewed literature in regards to prominent theories and models; (2) reviewed previous literature about IT acceptance and usage within four contexts of study; and (3) concluded that using the Internet helps in improving academics' professional practices. In the research model, there are five main factors that influence usage and up to nine others that moderate important associations. Perceived utility, perceived ease of use, and self-efficacy were found to be the most important factors in determining usage behaviour in the classroom. Usefulness and self-efficacy were two primary characteristics that strongly predicted usage behaviour across different activities. In conclusion, usage patterns were a major factor in shaping future behaviour. Key drivers of using behaviour were also moderated by three factors: age, e-university plan, and reading and writing proficiency. There were just two moderators that affected the impact of usage behaviour on behaviour intention, and those were age and intended university research. Gender, degree of education, academic rank, years of experience, and fluency in India had no effect on the impact of the major determinants on usage behaviour, and usage behaviour had no effect on the impact of the intention to change. Practitioners may benefit from a deeper familiarity with the model in order to better understand the factors contributing to users' reluctance to adopt the technology and to develop more effective strategies for boosting its widespread adoption and use.