Role of Age in Technology Adoption Decisions in Organizations Aashish Jagini
University of Missouri
Technology has become a vital and integral part of every organization. From multi-national corporations who maintain mainframe systems and databases to small businesses that own a single computer, technology plays a role. Technology has become indispensable because it has made its way into all the areas of an organization. Adoption of technology in an organization may influence performance and growth through improvement in productivity, competitiveness, efficiency, and effectiveness. Technology helps an organization to re-engineer work practices, improve speed, maintain consistency and accuracy and increase reliability. In the past two decades, research has focused on the notion of technology adoption. Studies have examined various aspects of technology adoption at an individual and organizational level and in this paper will analyze if age can be a differentiating factor in adoption of technology in the workplace. Research examining age differences in technology adoption decisions
A research study was conducted by Micheal G.Morris and Viswanath Venkatesh in the year 2000 to investigate age differences in individual adoption and sustained usage of technology in the workplace using the theory of planned behavior. The theory of planned behavior is a theory which links beliefs and behavior. The study was done over a period of 5 months among 118 workers. User reactions and technology usage behavior were studied majorly in this experiment by introducing a new software system to the workers.
The setting for the research done by Morris and Venkatesh was a medium-size financial accounting firm in a large mid-western city with approximately 300 employees. The firm was well established and had been in business for about 15 years. A total of 130 customer account representatives who were in the process of implementing a new technology participated in the study out of which 118 usable responses were obtained at all points of measurement. The new software being introduces was an organization-wide system for data and information retrieval. Usage of the new system was voluntary because the participants could use either the new system or the existing system. None of the participants had any prior knowledge about the new technology being introduced. All participants received a 2-day training session on the system which was a combination of training, interactive lecture, and hands-on use. Potential Confounding factors:
Three potential confounds associated with age include income, occupation, and education. Specifically, older individuals are overrepresented in categories of higher income, higher occupational positions, and higher educational qualification. Thus, in the research done by Morris and Venkatesh, it was deemed important to initially evaluate the effects of income level, occupation level, and education level. Key Determinants in the theoretical model:
1. Attitude towards behavior (A): Refers to the degree to which a person has a favorable or unfavorable evaluation or appraisal of the behavior in question (Ajzen, 1991, p.188) 2. Subjective norm (SN): Refers to the perceived social pressure to perform or not to perform the behavior (Ajzen, 1991, p.188) 3. Perceived behavioral control (PBC): Defined as people’s perception of the ease or difficulty of performing the behavior of interest (Ajzen, 1991, p.183) Procedure and Measurement:
Employees’ reactions to the technology were gathered at two points in time: immediately after the initial training (t1) and after 3 months of experience (t2). Actual usage behavior (USE) was measured over a 5 month period from the time of the introduction of the technology. For purposes of this research, t1 represented the measurement point to study short-term effects (initial user reactions), and t2 represented measurements to study long-term...
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