Need A TurnItIn Report
Technology 0
Age and Technology Innovation in the Workplace
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Age and Technology Innovation in the Workplace
Key findings
After accessing the SAP procurement, it was observed that some employees do not use the system in the right way. A time lag is brought about due to a variation of time between the period when the employees’ report by making use of the SAP procurement system and proper administration of the research’s questionnaire. However, time lag varies depending on each system user hence each individual variable was independently analyzed in order to identify the potential variations. ANOVA test detected significant variations in individual IT acceptance while the Turkey-Student-Newman-Keuls analysis failed to indicate any significant variations over time.
Factor analysis was also performed due to the existence of a correlation between individual-level of IT acceptance and satisfaction during implementation. This factor analysis was performed to establish existence of divergence between the two constructs. The level 2 predictors were used as coefficients in the department-level regression model. They included climate change, age context mean and age context SD. All the parameters showed significant effects on their influence and satisfaction during implementation apart from climate attitude. The age context mean had a positive effect (0.95) while the age context SD had a negative effect (-0.41) on implementation satisfaction with no variation existing with the climate change. Controlling the age context SD results in a greater implementation satisfaction in departments which contain older age contexts as compared to those with young mean ages. This provides an effect on the age context mean. On the other hand, older departments recorded a higher IT implementation satisfaction compared to younger departments in the individual-level findings. These findings alternate the common notions about the reactions of older workers towards implementation of new IT strategies.
The age context mean predicted the slope for level 2 interaction effect within departments. With reference to climatic attitude and age context SD, the older departments varied from younger departments in terms of strength of the slope of level 1 relation between the age of employees and the satisfaction obtained during implementation. Older employees as well as sections with older mean ages recorded more satisfaction on implementation. Control of climatic attitudes and age context SD results in an increase in the age context means which weakens the employee age-implementation satisfaction. Therefore, older workers report more satisfaction in a young department than an older one due to a low age context mean. On the other hand, young employees record more implementation satisfaction when the age aspect of the work environment is older than when it is younger.
Recommendations.
Policy for theory and practice.
To control the time lag effects when performing the study, or any other study of a related case, analysis of data that involve individual IT acceptance should be done twice, the first one using the time lag as the control variable while the second one omitting the time lag to analyze its effects on the model’s results.
This research provided support for cross-level references on employees’ attitude towards IT. Therefore, more research should be done to explore the inner mechanisms in the cross-level relationships by providing a specific attention to the roles played by formal and informal opportunities for IT training together with participation of employees in the process of IT training and implementation. The factors analyzed in the study are among the most frequently reported human obstacles to implementation of IT. More research should also be done in order to understand the role played by employees’ age in the process of IT implementation.
In an applied perspective, organizations should put forward planning efforts prior to their implementation in order to effectively improve their IT initiatives successfully. Workplace interventions should be done to foster a positive IT attitude among employees and help to face out ageist stereotypes in order to build a momentum for the initiative and reduce problems linked to the innovative transitions. Efforts should be made to sensitize employees on the dangers of stereotyping and enlighten them on the realities of cognitive changes over the life course and their effect on the ageist workplace behaviors and attitudes. This can be done through cultivating age-supportive workplace environments prior to the implementation process. The organizations can help both young and old workers to appreciate the benefits each group brings to the work environment while strengthening self-efficiency and retaining the valued knowledge and experience of older workers during IT transitions.
Future research should aim at minimizing biasness by controlling the time lag and technological experience and offering a paper based alternative to web-based mediums. The findings should also be cautiously replicated by employing longitudinal research designs and use multiple methods of data collections.
More attention and resources should be given to the technical aspects of IT innovation as well as the interactions that occur between employees and their contextual influences in the workplace environment that are critical to the success of IT initiatives. Investigations into such relationships will improve the understanding of organizational challenges and solutions towards managing the intersection of workforce aging and workplace IT innovation. These demographic realities of the current workforce will make the matters increasingly worthwhile in future.
ReferencesPosthuma , R., & Campion, M. A. (2009). Age stereotypes in the workplace: common stereotypes, moderators, and future directions. Los Angeles : Elseveir (journal of management).
Rizzuto , T., Mohammed , S., & Vance, R. (2011). Marching in-step: Facilitating technological transitions through climate consensus. Los Angeles: Elsevier (computer in human behavior).
Rizzuto, T. E. (2011). Age and technology innovation in the workplace: Does work context matter? Los Angeles: Elsevier Ltd.