TRAM Model for Performance

Two of the most often used theoretical frameworks in IT studies are the Technology Readiness Assessment (TRA) model and the Technology Acceptance Model (TAM) (Granić & Marangunić, 2019). The TRAM model is a combination of the two frameworks; it utilizes both insights to explain the correlation between hybrid workplace performance, technical preparedness, and acceptance.

TRAM Model

As a unified theoretical framework, the TRAM model integrates the TRA model’s four pillars with the TAM model’s two pillars. The two components of the TAM model are perceived usefulness and perceived ease of use, whereas the four components of the TRA model are optimism, innovation, discomfort, and insecurity. The TRAM model suggests that these factors collaborate to affect tech adoption and, by extension, productivity in the workplace. The TAM model’s component of perceived usefulness is related to the TRA model’s optimism and creativity, increasing technological adoption.

However, the TAM model’s perceived ease of use component relates to reduced TRA model discomfort and insecurity and higher technical acceptability (Fu et al., 2022). When people are more open to using new technologies at work, they tend to be more productive in a hybrid setting. Personal and environmental influences on workers’ perspectives on adopting and using new technologies are highlighted by the TRAM model. It acknowledges that workers’ varying comfort and familiarity with new technologies may impact their productivity in a blended workplace. Positive and creative workers may be more open to adopting new technology, whereas those who are less confident may be less receptive to changes in the workplace.

(Fig 1. https://www.google.com/url?sa=i&url=https%3A%2F%2Fwww.researchgate.net%2Ffigure%2FTheoretical-model-based-on-TRAM-Lin-et-al-2007)

Benefits of using the TRAM Model

Organizations may improve the performance and productivity of their employees by utilizing the TRAM model to create and deploy technological interventions. The model offers a holistic and integrative framework for analyzing how technological preparedness, acceptability, and performance in a blended workplace are related (Geng, Law & Niu, 2019). It aids businesses in pinpointing the characteristics that determine whether or not their employees will embrace new technologies and crafting plans to increase employee enthusiasm for technological advancements.

A business can utilize the TRAM model, for instance, to evaluate the level of technical preparation of its employees and to identify any areas of weakness that need more education or reinforcement. After that, the corporation could provide specific training and development programs for its employees to improve their familiarity with and ability to use technology (Granić & Marangunić, 2019). It is possible that highlighting the usefulness and comfort offered by cutting-edge technologies may also stimulate their broad adoption. If people in a diverse workplace were more willing to try out new technologies and were more at ease using them, they would have higher levels of performance and productivity.

In conclusion, the TRAM model provides a helpful framework for analyzing how familiarity with new technologies affects productivity in a blended workplace. It acknowledges that individual and organizational variables influence workers’ perspectives on technology adoption and usage and that encouraging constructive perspectives on technology’s role in enhancing performance and productivity is essential. Organizations may improve the performance and productivity of their employees by utilizing the TRAM model to create and deploy technological interventions. They will be able to figure out what makes people open to new technologies and how to get them excited about using them. In a hybrid workplace, this contributes to better efficiency and output from staff.

References

Fu, H., Mensah, I. K., Wang, R., Gui, L., Wang, J., & Xiao, Z. (2022). The predictors of mobile government services adoption through social media: A case of Chinese citizens. Information Development, 02666669221114649.

Geng, S., Law, K. M., & Niu, B. (2019). Investigating self-directed learning and technology readiness in blending learning environment. International Journal of Educational Technology in Higher Education, 16(1), 1-22.

Granić, A., & Marangunić, N. (2019). Technology acceptance model in an educational context: A systematic literature review. British Journal of Educational Technology, 50(5), 2572-2593.