TECHNOLOGY USE AND EMPLOYEE ASSESSMENTS OF WORK EFFECTIVENESS, WORKLOAD, AND PACE OF LIFE

Abstract

This study draws on survey data collected in 2001/2002 from two distinct regional samples of employees (N = 1667 and 547) and uses multivariate analytical techniques to assess ICT user versus non-user perceptions about the role technology plays in enhancing work effectiveness, increasing workloads, and accelerating the pace of life. I also investigate whether different devices or applications, used in different contexts (for work, for personal needs, or both), influence worker assessments of productivity and demands in different ways. I find that: (1) the frequency of computer, email, and cell phone use positively influences assessments that ICT use is connected to greater workplace effectiveness, an increased work load, and an accelerated pace of life; (2) computer and email use is linked more reliably to assessments regarding workplace effectiveness and work load than cell phone use; and (3) while both personal and work-related forms of ICT use influence productivity and pace-of-life assessments, work-related use only appears linked to assessments of increasing work demands. Overall, the findings indicate that perceptions about the social consequences of ICT use depend both on what device or application is used (computers versus cell phones), as well as the context (work versus personal) of this use.

Keywords:

• employment
• ICTs
• mobile technology
• sociology

Notes

Correlations among these variables indicate that computer use and email use are positively and strongly related (r = 0.68 in Careers and 0.79 in Community) while cell phone use is weakly correlated (r's range from 0.12 to 0.25 across variables and samples) with both computer and email use across samples.

Self-employment is also a potentially important covariate. Unfortunately, self-employment was measured only at the time of the initial interview in both samples. I conducted additional analyses (not shown) utilizing the time 1 self-employment measures and found that self-employment was not a significant covariate across models.

In addition to partner status and the number of children, I also examined whether the ages of children or life stage of the respondent (a variable that combines information about respondent age and child's age) were important covariates in the models. These variables were not significant and are not reported in the results.

To assess whether major differences in frequency use within each context influence perceptions about ICT use and job performance, work load, and pace of life, I estimated models that included both frequency, context and frequency × context interaction terms drawing just on samples of technology users. Overall, the results from this sub-analysis suggest that frequency and context are separate effects that do not interact.