This contribution aims to investigate the relation between the perceived usefulness of smart working among employees (PUSW) and certain work outcomes, specifically perceived performance (PP) and job satisfaction (JS), hypothesizing techno-stress (TC) as a moderator of the relationship. The spread of increasingly advanced digital technologies supporting remote communication and collaboration has driven organizations to develop smart working (SW) as a new labor model, and the Covid-19 pandemic has greatly accelerated this process. To date, research on SW outcomes shows ambiguous results. Indeed, on the one hand, SW leads to more flexibility, productivity, and a better work-life balance, on the other hand, SW can result in a sense of isolation for workers, difficulties in task management, and worsened performance (e.g., Bednar and Welch, 2019; Carbonara et al., 2022). The development of digital technologies has also caused techno-stress (i.e., a specific form of stress that workers experience when they have difficulties in dealing with new technologies; Dragano and Lunau, 2020). To date, the relationship between SW and TS has been little investigated and a better understanding of it may improve the comprehension of when SW produces positive or negative work-related outcomes. The Job Demand-Resources Model (JDRM; Bakker and Demerouti, 2007) states that, in workplaces, exist job resources that enable job demands to be managed by increasing motivation and improving performance outcomes and job satisfaction. However, the relationship between job resources and work-related outcomes is moderated by the stress that can result from excessive or inadequate job demands on workers. Based on the JDRM we hypothesize that if SW is perceived by employees as useful and appropriate for their tasks it will be a job resource that will improve work-related outcomes (i.e., PP and JS). However, when the TS level of employees is high, the positive relationship between SW and work-related outcomes will be disrupted. To test this hypothesis nearly 500 employees of an Italian municipality are filling out a self-report questionnaire. PUSW is measured with the 13-item scale of Ingusci et al. (2022), and TS with the 11-item scale of Ragu-Nathan et al. (2008). In addition, workers are asked, expressing a percentage from 1 to 100, to rate the level of their PP and JS over the past six months. We are going to conduct a multiple regression analysis where we first are going to test whether PUSW is a significant predictor of PP and JS. Then we are going to verify whether TS significantly moderates the relationship between PUSW and PP/JS. We expect that at low levels of TS, PUSW predicts PP and JS but, at high levels of TC, the relationship between PUSW and PP/JS will no longer be positive in a statistically significant way or even will become negative. The results of the study can contribute to clarifying how SW on work-related outcomes operates and can help practitioners in assessing whether or not, in a given organization, a smart working policy may be effective and efficient.
New Technologies and Work-Related Outcomes: Exploring the Effects of Smart Working and Techno-Stress on Perceived Job Satisfaction and Performance.
Mariani V.;Vacondio M.;Brondino M.;Pasini M.
2024-01-01
Abstract
This contribution aims to investigate the relation between the perceived usefulness of smart working among employees (PUSW) and certain work outcomes, specifically perceived performance (PP) and job satisfaction (JS), hypothesizing techno-stress (TC) as a moderator of the relationship. The spread of increasingly advanced digital technologies supporting remote communication and collaboration has driven organizations to develop smart working (SW) as a new labor model, and the Covid-19 pandemic has greatly accelerated this process. To date, research on SW outcomes shows ambiguous results. Indeed, on the one hand, SW leads to more flexibility, productivity, and a better work-life balance, on the other hand, SW can result in a sense of isolation for workers, difficulties in task management, and worsened performance (e.g., Bednar and Welch, 2019; Carbonara et al., 2022). The development of digital technologies has also caused techno-stress (i.e., a specific form of stress that workers experience when they have difficulties in dealing with new technologies; Dragano and Lunau, 2020). To date, the relationship between SW and TS has been little investigated and a better understanding of it may improve the comprehension of when SW produces positive or negative work-related outcomes. The Job Demand-Resources Model (JDRM; Bakker and Demerouti, 2007) states that, in workplaces, exist job resources that enable job demands to be managed by increasing motivation and improving performance outcomes and job satisfaction. However, the relationship between job resources and work-related outcomes is moderated by the stress that can result from excessive or inadequate job demands on workers. Based on the JDRM we hypothesize that if SW is perceived by employees as useful and appropriate for their tasks it will be a job resource that will improve work-related outcomes (i.e., PP and JS). However, when the TS level of employees is high, the positive relationship between SW and work-related outcomes will be disrupted. To test this hypothesis nearly 500 employees of an Italian municipality are filling out a self-report questionnaire. PUSW is measured with the 13-item scale of Ingusci et al. (2022), and TS with the 11-item scale of Ragu-Nathan et al. (2008). In addition, workers are asked, expressing a percentage from 1 to 100, to rate the level of their PP and JS over the past six months. We are going to conduct a multiple regression analysis where we first are going to test whether PUSW is a significant predictor of PP and JS. Then we are going to verify whether TS significantly moderates the relationship between PUSW and PP/JS. We expect that at low levels of TS, PUSW predicts PP and JS but, at high levels of TC, the relationship between PUSW and PP/JS will no longer be positive in a statistically significant way or even will become negative. The results of the study can contribute to clarifying how SW on work-related outcomes operates and can help practitioners in assessing whether or not, in a given organization, a smart working policy may be effective and efficient.
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
