Job Satisfaction and the Digital Transformation of the Public Sector: The Mediating Role of Job Autonomy

Abstract

Worldwide, governments have introduced novel information and communication technologies (ICTs) for policy formulation and service delivery, radically changing the working environment of government employees. Following the debate on work stress and particularly on technostress, we argue that the use of ICTs triggers “digital overload” that decreases government employees’ job satisfaction via inhibiting their job autonomy. Contrary to prior research, we consider job autonomy as a consequence rather than a determinant of digital overload, because ICT-use accelerates work routines and interruptions and eventually diminishes employees’ freedom to decide how to work. Based on novel survey data from government employees in Germany, Italy, and Norway, our structural equation modeling (SEM) confirms a significant negative effect of digital overload on job autonomy. More importantly, job autonomy partially mediates the negative relationship between digital overload and job satisfaction, pointing to the importance of studying the micro-foundations of ICT-use in the public sector.

Keywords

digital transformation digital overload job autonomy job satisfaction civil service survey

Introduction

The digital transformation of work radically changes the working environment of private and public sector employees. Similar to the private sector, many governments have adopted ICT tools to support and improve information exchange and communication and to digitize existing procedures for policy formulation and service delivery (Christensen & Lægreid, 2022). In addition to online collaboration tools, social platforms and messenger services have entered the daily routines of government organizations, altering the very context of policy formulation (Fusi & Feeney, 2018b; Fusi & Zhang, 2020; Hwang et al., 2020; Tufts et al., 2015). However, the increasing use of ICTs also creates new demands for government employees’ cognitive resources as work processes and communication accelerate (Karr-Wisniewski & Lu, 2010; Tarafdar et al., 2010). As a result, the same features that turn ICTs into valuable and beneficial tools for government employees to accomplish their tasks may cause detrimental effects for their autonomy and their satisfaction at work.

The scholarly debate on “technostress” discusses these unintended effects of using ICTs at work (Berg-Beckhoff et al., 2017; La Torre et al., 2019; see already Brod, 1984; Weil & Rosen, 1997). Similar to other work stressors, technostress causes harmful psychological, behavioral, and physiological responses (see Lazarus, 1966). Eventually, these stressors and the corresponding response mechanisms are likely to cause negative work-related attitudes and decrease job satisfaction (Baehler & Bryson, 2008; Kim, 2005). Already widely acknowledged for private sector employees, these detrimental effects on job satisfaction have also been confirmed for government employees engaged in service delivery (Ayyagari et al., 2011; Ragu-Nathan et al., 2008; Tarafdar et al., 2010; see also Corbett et al., 1989).

The current scholarly debate on job satisfaction emphasizes the importance of working environments and job characteristics and identifies a positive effect of job autonomy on job satisfaction (Cantarelli et al., 2016). At the same time, scholars interested in the effects of ICT-use at work on job satisfaction show that employees with greater job autonomy are more resilient to technostress (Suh & Lee, 2017). Hence, job autonomy is almost exclusively regarded as a determinant or precondition of potentially detrimental effects of ICT-use at work (Karimikia et al., 2020, cf. Plimmer et al., 2022). In contrast, we follow self-determination theory and argue that the association between ICT-related stress at work and job satisfaction is partly mediated by job autonomy. Accordingly, we regard job autonomy as a consequence of stress triggered by ICT-use, following empirical studies that show how the impact of context features on workplace outcomes is driven by the innate need for autonomy (Deci et al., 1989, 2017; Gagné & Deci, 2005).

We focus on “digital overload” that generates changes in working routines and behavior of employees because they use ICT tools at work themselves (“techno-overload”) and because their work-related third parties use ICTs (“communication overload”).

We fielded a survey of middle-ranked government employees performing managerial and policy functions in three European countries, Germany, Italy, and Norway, which express different administrative traditions and administrative systems. We focus on digital overload to capture the effects of using ICT tools at work and employed structural equation modeling to study how this digital overload shapes job autonomy and eventually job satisfaction. In our empirical analysis, we found a significant negative effect of digital overload on job satisfaction as well as a partial mediation effect by job autonomy, revealing that a reduced job autonomy partially explains the negative relationship between digital overload and job satisfaction. In addition, the analysis showed a significant negative effect of gender on job autonomy and further country-specific variations in job autonomy and job satisfaction. We conclude that the scholarly debate on the digital transformation of the public sector may benefit from a stronger attention for potential negative consequences of ICT-use at the individual level and encourage further cross-country studies on digitalization dynamics in central government organizations.

The remainder of the paper is structured as follows. The following section presents our theoretical argument. Subsequently, we introduce our data and methods, that is, our comparative civil service survey that was fielded in spring 2020. The subsequent section shows our empirical analyses and key findings. In our conclusion, we discuss the implications of our findings for the debate on technostress and the digital transformation of the public sector as well as for scholars interested in the micro-foundation of bureaucratic behavior.

Theory

Digital technologies are often assumed to enable more flexibility in organizing work. Yet, technology-related demands at work may also exceed employees’ response capabilities, who then experience what is often referred to as technostress (cf. Fischer & Riedl, 2017). The existing research on technostress discusses various “technostressors” that are generated by employees’ own ICT-use at work and refer to particular ICT features or the specific set of ICTs used at employees’ workplaces (Karr-Wisniewski & Lu, 2010; Tarafdar et al., 2007). However, research also discusses two rather universal stressors: “Techno-overload” is used in this debate to describe ICT-induced changes in employees’ work routines to accomplish their tasks, including an increased workload and velocity (Tarafdar et al., 2007; see also Ayyagari et al., 2011; Camarena & Fusi, 2022). A different debate discusses primarily stress that is generated by the ICT-use of employees’ work contacts, especially with regards to the communication aspect of ICTs. In this debate, the generic “communication overload” depicts employees’ changes in communication routines that are generated by the ICT-use of their work-related contacts, including employees’ inability to adequately respond to excessive message streams and prioritize incoming messages (Karr-Wisniewski & Lu, 2010; Stadin et al., 2021; see O’Reilly, 1980). These notions of techno- and communication overload are therefore most suitable to comparatively capture the behavioral responses of government employees to the digitalization of their workplaces and the consequences that these aspects may yield for job satisfaction. We regard techno- and communication overload as two dimensions of “digital overload,” defined as a condition of strain emanating from ICT-induced stress and the corresponding alterations of work routines and work behavior (see Figure 1).

Figure 1.

The two-dimensional concept of digital overload.

Digital overload of government employees may reduce their perceived locus of control and thus undermines their job autonomy, that is “the degree to which the job provides substantial freedom, independence, and discretion to the individual in scheduling the work and determining the procedures to be used in carrying it out” (Hackman & Oldham, 1980, p.162). We thus theorize digital overload as an externally imposed pressure and argue that the increased use of ICTs by employees and their work-related contacts shifts response expectations, tightens time schedules, and increases the workload, thus reducing perceptions of self-controlled working practices and time management, that is, independence in deciding how to go about one’s work. After all, the existence of multiple ICT tools that must be served simultaneously is likely to raise disturbance frequency and to force employees to interrupt their workflow (Karr-Wisniewski & Lu, 2010; Tarafdar et al., 2010). Such potential distractions and -redirections occupy cognitive resources, not only to answer the requests made, but also to re-focus on the planned activity and, if necessary, to re-prioritize (un-)scheduled tasks (Jackson et al., 2001), inhibiting the ability to perform a job-related task at an individually chosen time and in a self-determined manner.

In a nutshell, externally imposed constraints at work are likely to trigger perceptions of coercion, pressure, and alienation, threatening employees’ basic needs for autonomy. It follows that digital overload triggered by the use of ICTs at work acts as an externally imposed pressure that forces change in work routines and response mechanisms, diminishing job autonomy.

H1: Digital overload is negatively associated with job autonomy.

In general, employees with greater job autonomy are more satisfied with their jobs (Hackman & Oldham, 1980; Spreitzer, 1995), that is, they enjoy a greater “pleasurable or positive emotional state, resulting from the appraisal of one’s job or job experiences” (Locke, 1976, p. 1304; Wright & Davis, 2003). Studies have shown that employees with high job autonomy feel greater responsibility for the outcomes and quality of their work, enhancing their perceptions of meaningfulness and significance of their tasks and increasing job satisfaction (Hackman & Oldham, 1976). In a nutshell, having a sense of choice and discretion at work is regarded as the basis for growth, motivation, and wellbeing (Deci & Ryan, 2008). Therefore, job autonomy is considered as a major driver of job satisfaction, over time and cross-nationally (Kay et al., 2020; Taylor & Westover, 2011).

In the seminal work by Karasek (1979), job autonomy encompasses decision authority as an individual employee’s control over their work and skill discretion as the variety of work and opportunities to use their skills at work. For government employees engaged in policy formulation, many scholars have focused on authority and have equated job autonomy with employees’ discretion as bureaucratic agents servicing their political masters (Brehm & Gates, 1997; Epstein & O’Halloran, 1999; Huber & Shipan, 2002; Huber et al., 2001). Yet this discretion is predominantly shaped by codified rules and thus may differ from individual job autonomy, oftentimes treated as individual bureaucratic discretion (see Bertelli et al., 2015; Silva & Jalali, 2020). Other scholars have focused on skills and discussed job autonomy as the role and “craft” of government employees (Rhodes, 2016; van Dorp & ’t Hart, 2019). We understand job autonomy of government employees in policy formulation both as an expression of their decision authority and their skill discretion and expect that more autonomous employees experience greater job satisfaction.

H2: Job autonomy is positively associated with job satisfaction.

If digital overload reduces employees’ job autonomy, and job autonomy, in turn, affects job satisfaction, we expect an indirect relationship between digital overload and job satisfaction, partially mediated by job autonomy (see Figure 2). Our third hypothesis thus rests on two assumptions. On the one hand, empirical evidence points to a direct relationship between work stress and job satisfaction, given that most employees feel negative toward job stress and that job dissatisfaction often results from a misfit between the demands of the working environment and individual resources (Lazarus, 1966). In other words, external expectations of the working environment as stemming from digital overload may exceed individual capacities to meet those demands, causing mental fatigue and frustration. Stress as an unpleasant emotional state may additionally involve tension, concern, nervousness, and irritation, thus triggering feelings of anxiety, anger, or sadness, and even lead to work alienation in that employees distance themselves from work (Millward, 2005). Therefore, digital overload is likely to provoke negative affect and attitudes toward work, reducing job satisfaction in a direct manner.

Figure 2.

Conceptual model.

On the other hand, we argue that the negative impact of digital overload on job satisfaction is partially conveyed through a loss of job autonomy. Following self-determination theory (Gagné & Deci, 2005), the impact of context features on workplace outcomes, such as job satisfaction, is largely mediated by three fundamental psychological needs: self-determination or autonomy, competence, and relatedness (Deci et al., 2017). Autonomy is often regarded as the most essential need (Gagné & Deci, 2005) and social settings that meet the individual demands for autonomy induce motivational regulation styles that are important for enjoyment and satisfaction. Central to self-determination theory is the distinction between different types of motivation, ranging from autonomous to controlled motivation. People who are provided with opportunities for choice and self-initiation (i.e., are autonomously driven) exhibit higher levels of volition and intrinsic motivation because they regulate performing their tasks internally. In contrast, externally imposed constraints are likely to trigger feelings of coercion, pressure, and alienation, thus threatening employees’ basic needs for autonomy and lowering their sense of competence in task accomplishment. Accordingly, in work settings providing greater opportunities for choice and self-initiation—that is greater job autonomy—employees are more content and satisfied, because they enjoy a stronger ability for self-regulated work and work results. To the contrary, if work environments weaken the autonomy at work, employees may show defensive functioning, frustration, and the deterioration of a range of workplace outcomes including job satisfaction (Cantarelli et al., 2016; Judge et al., 2017; Steijn & van der Voet, 2019). Following self-determination theory, we argue that accelerated work routines caused by the individual use of ICTs (i.e., techno-overload) as well as more extensive and faster ICT-based communication by work-related contacts (i.e., communication overload) as caused by using ICTs triggers feelings of reactivity and being constrained by others. These changing work routines lower government employees’ feelings of job autonomy and thus ultimately contribute to reducing their job satisfaction.

H3: Job autonomy partially mediates the negative relationship between digital overload and job satisfaction.

Data and Method

Data

To study the relevance of digital overload for job satisfaction, we employed a survey on digitalization dynamics among middle-ranked government employees in all ministerial departments at the central level of three European countries: Germany, Italy, and Norway. All three countries are characterized by a merit-based ministerial bureaucracy that is primarily concerned with policy formulation, whereas state and local authorities implement government policy. However, they express different administrative traditions, referred to as Germanic, Napoleonic, and Nordic respectively (Pollitt & Bouckaert, 2017). They provide a crucial variation in the working environments of public employees engaged in policy design: Germany is a federal state with a strong legalistic orientation, encompassing highly formalized administrative structures and processes. The Italian national bureaucracy is similarly legalistic but is characterized by centralized administrative structures and weaker local governments. Norway is a unitary state with strong local governments and follows the consensus-based tradition of Nordic countries, entailing more collaborative and flexible administrative decision-making. Both Germany and Italy rely on a “closed” or career-based civil service system, though recruitment practices in Italian ministries rely more on patronage. In contrast, the Nordic tradition is characterized by a rather “open,” that is, position-based system, allowing for more diverse routes to public service (Kickert, 2005; Kuhlmann & Wollmann, 2019).

Our sample included all officeholders below the most senior employees (i.e., subdirectors-generals). These government employees play a crucial role in policymaking by drafting government policy and transmitting bureaucratic expertise to the political leadership as well as communicating political demands to the subordinated bureaucratic workforce. To verify the survey’s feasibility and comprehensibility in a ministerial bureaucracy context, it was piloted as part of a pre-test, which resulted in smaller adaptations of questions. To identify our target population and their email contact information, we used government websites, organizational charts, and social media platforms, and approached 3,353 officeholders. The fielding of the survey took place at the beginning of June in 2020 when civil servants were still adjusting to new work routines as evoked by the Covid-19 crisis (e.g., working from home). We inserted a survey question on the primary office location to acknowledge the circumstances (see Supplemental Material) and extended the response time to October 2020, including three email reminders to increase the response rate. Overall, 679 respondents answered our questionnaire, yielding a response rate of 20.3%, which is similar to other cross-country surveys among public sector managers (see Silva & Jalali, 2020; Steen & Weske, 2016) and we regard as sufficient, particularly given the Covid-19 crisis.¹ The distribution of ranks in our sample echoes the formal hierarchical setting of government organizations: the majority of respondents were department heads or directly subordinated employees (approx. 87.0%), whereas a minority is in the superior rank as heads of sub-directorates. Our sample included respondents from their mid-20s to early 70s with a mean age of 53.3 years. The majority of participants were male; 41.0% female government employees were included in the sample.

Measures

Job satisfaction

Job satisfaction was assessed via a commonly used single-item measure by Steijn and van der Voet (2019); see Table A1 in Supplemental Material) which asks respondents to indicate their level of agreement with the following statement: “Taking everything into account, I am satisfied with my job.” Single-item measures of job satisfaction were shown to yield high reliability and validity and significantly correlate with multiple-item constructs of job satisfaction, also in the public sector (Dolbier et al., 2005).

Job autonomy

Job autonomy was assessed with a well-established three-item scale by Spreitzer (1995), see Table A1 in Supplemental Material). Cronbach’s alpha for this scale is .85, with the internal consistency being confirmed by a good average variance extracted (AVE = .66).

Digital overload

In line with our theoretical argument, we measured digital overload as a two-factor construct, comprising techno- and communication overload. To measure techno-overload, we relied on a scale introduced by Ragu-Nathan et al. (2008). Sample items include “The ICT-tools force me to work much faster” or “to do more work than I can handle” (see Supplemental Table A1). We provided all respondents a note defining the ICTs with distinct examples, reading as follows: “For example, document transfer management tools, online collaboration tools, data management, analysis or visualization tools, digital integrated management systems as well as social media or messenger services.” In addition, we fielded a scale for communication overload, applying the four-item scale of Karr-Wisniewski and Lu (2010), including items such as “I feel that in a less connected environment, my attention would be less divided allowing me to be more productive at work.” After an exploratory factor analysis indicated a clear two-factor solution, we further investigated the digital overload factor structure by comparing the assumed second-order two-factor model in which techno-overload and communication overload loaded on a second-order factor (i.e., digital overload) with an alternative uncorrelated two-factor model as well as a one-factor model in which all techno- and communication overload items are assumed to measure only one common factor. As anticipated, the higher-order construct provided a better fit to the data (χ² = 49.63, df = 19, CFI = .93, SRMR = .04, and RMSEA = .06) than the uncorrelated two-factor solution (χ² = 111.83, df = 23, CFI = .79, SRMR = .15, and RMSEA = .10) as well as the one factor model (χ2 = 147.72, df = 20, CFI = .70, SRMR = .09, and RMSEA = .12; see supplementary material). Cronbach’s alpha for the digital overload scale is .79 and the average factor loading was .67, with no item loading below .5 and adequate average variance extracted (AVE = .56).

Control variables

As controls, we accounted for individual features discussed in the literature as relevant for job satisfaction and autonomy, such as rank, job tenure, age, and gender. Rank shapes a government official’s work environment and therefore job satisfaction: The higher the formal rank, the more government employees are responsible for managing, supervising, and delegating policy tasks and thus enjoy greater autonomy. Job tenure may affect employees’ responses to workplace practices and was measured in five categories. The importance of age and gender for job satisfaction has been widely confirmed (Perry & Wise, 1990). In addition, older and female employees report greater techno-overload and corresponding techno-stress than their younger and male colleagues (Lee, Son et al., 2016; Marchiori et al., 2019; Yin et al., 2018). Moreover, our research interest in digital overload informed three additional controls: (a) respondents’ attitudes toward ICT-use, (b) their perceptions of organizational support in dealing with changing work processes and (c) their primary work location. Government employees with positive attitudes toward using digital tools at work are likely to cope with digital overload differently than those with negative attitudes. Moreover, Lapuente and Suzuki (Lapuente & Suzuki, 2020) found a significant association between job satisfaction and innovative attitudes among public managers. We based our scale on attitudes toward ICT on previously used items on employees’ openness to try and use new technological applications or services (Wang, 2014); the Cronbach’s alpha is .87 and the three items presented good average variance extracted (AVE = .70). The perception of organizational support was measured with an item assessing the extent to which decision-making processes in the last 2 years have improved, in terms of changing work processes in the respondents’ unit or span of control. Such support in adapting to changing routines may shape both autonomy and satisfaction levels. We controlled for the primary work location to acknowledge that the survey was fielded during the acute management of the Covid-19 pandemic and the fact that government employees who are regularly engaged in telework might experience digital overload differently than those working primarily at the office. Lastly, we controlled for country differences, using Germany as the reference group (see Supplemental Material on measures taken to lower common method variance).

Analytical Procedure

Preliminary Analyses

Our empirical analysis consisted of two main steps. First, we employed factor analyses to assess the validity of the latent variable structure as well as its invariance across Germany, Italy, and Norway. Subsequently, we performed SEM to test our hypotheses, using the lavaan-0.6-8 package in R (Rosseel, 2012).

We began by assessing the discriminant validity of the three latent factors that made up our measurement model: (a) digital overload, (b) job autonomy, and (c) attitudes toward ICT-use (see Table 1). The results show that the hypothesized three-factor model provides a very good fit to the data (χ2 = 119.63, df = 73, CFI = .95, SRMR = .04, and RMSEA = .04). The CFA results show also that all scale items have statistically significant factor loadings (p < .01) for their respective latent constructs at the levels at which they were measured (see Supplemental Table A1). We then tested alternative two-factor models, first allowing digital overload and ICT-use attitudes to load on one factor due their significant intercorrelation (see Table 1). In another two-factor solution, we specified digital overload and job autonomy to load on one factor, given that these variables share some common components pertaining to government employees’ job routines. Lastly, we tested a model in which all items were allowed to load on one factor. However, the four-factor model fit the data much better than each of the alternative measurement models, and we concluded the four latent constructs used in this study are theoretically and empirically distinct.

Table 1.

Summary of the Hypothesized and Alternative Measurement Models (N = 420).

	χ²	d.f.	χ²/d.f.	Δd.f.	Δχ²	SRMR	RMSEA	CFI	AIC
Measurement model of digital overload
Hypothesized second-order two-factor model	49.63	19	2.61	—	—	.041	.062	.928	8603.47
Alternative uncorrelated two-factor model	111.83	23	4.86	4.00	62.20	.153	.096	.790	8675.31
Alternative one-factor model	147.72	20	7.39	1.00	98.09	.091	.123	.698	8770.82
Measurement model of the latent study variables
Hypothesized three-factor model	119.63	73.00	1.64	—	—	.043	.039	.948	14209.33
Alternative Model 1: Two-factor model(Digital overload + ICT use attitudes)	188.89	75.00	2.52	2.00	69.26	.117	.060	.872	14307.84
Alternative Model 2: Two-factor model (Digital overload + Job autonomy)	175.47	75.00	2.34	2.00	55.84	.103	.056	.887	14283.88
Alternative Model 3: One-factor-model	1133.59	77.00	14.72	4.00	1013.96	.155	.181	.411	15509.82
Measurement invariance of the latent study variables
Configural invariance	260.52	219.00	1.19	—	—	.061	.037	.945	14008.65
Metric invariance	285.47	239.00	1.19	20.00	24.95	.070	.037	.938	14008.17

Note. The measurement model of digital overload refers to the factor structure of the techno- and communication overload subscales. Chi-square (χ²) values denote Satorra-Bentler adjusted statistics using MLM estimator in order to correct for non-normality. Competing models were compared by drawing on the Satorra-Bentler chi-square difference test as well as the Akaike information criterion (AIC).

Moreover, we undertook checks to ensure the factors and their structural relationships were equivalent across the German, Italian, and Norwegian samples by testing their configural and metric invariance (see Table 1). Configural invariance was tested by investigating a baseline model in which the factor structure was held constant across all three groups, with no further parameter constraints. Because configural invariance was established, we proceeded with testing metric invariance by constraining the factor loadings to be equal across groups and comparing the metric invariance model fit to the configural invariance model fit (see Chen, 2007). The results of the metric model show a good fit (ΔCFI = .007; ΔRMSEA = .000, ΔSRMR = .009), also passing the more restrictive chi-square difference test (Δχ² = 24.95, Δdf = 20; see Cheung & Rensvold, 2002), thus confirming metric invariance and revealing that our pooling of country data was appropriate. We could then establish that the measured constructs had the same meaning to all respondents across the selected countries, and a one-unit change in the latent factor score of one country would lead to the same change in the item-score of another, allowing for meaningful comparison of the SEM results.

The means, standard deviations, and intercorrelations of the study variables are shown in Table 2. As expected, digital overload yields a significant and negative correlation with job autonomy, which is positively correlated with government employees’ job satisfaction. In addition, digital overload shows a negative correlation with job satisfaction and ICT-use attitudes, revealing that higher levels of digital overload are associated with more negative attitudes toward ICT-use. Government employees’ perception of organizational support in dealing with changing work processes is positively associated with job autonomy and job satisfaction and negatively associated with digital overload. The intercorrelations further indicate a negative correlation between age and ICT-use attitudes, corroborating the dominant assumption that older employees exhibit more negative attitudes toward using new technologies at work. Moreover, female respondents report lower levels of job satisfaction and job autonomy. The intercorrelations further indicate that Norwegian respondents show higher levels of job satisfaction and job autonomy, yet lower levels of digital overload and ICT-use attitudes, compared to the German reference group. In contrast, Italian respondents are less satisfied with their job but express more positive attitudes toward ICT-use than the German reference group.

Table 2.

Descriptive Statistics and Intercorrelations of the Study Variables (N = 420).

		M	SD	Min	Max	1	2	3	4	5	6	7	8	9	10	11
1	Job satisfaction	4.06	0.76	1.00	5.00
2	Digital overload	2.87	0.63	1.00	4.50	−.19***	(.79)
3	Job autonomy	3.75	0.74	1.00	5.00	.32***	−.11*	(.85)
4	Rank	0.81	0.39	0.00	1.00	.07	.09	.11*
5	Job tenure	3.04	1.38	1.00	5.00	−.08	−.03	.01	.17***
6	Age	53.28	8.12	25.00	71.00	.04	.09	.16**	.37***	.41***
7	Gender (1 = female)	0.41	0.49	0.00	1.00	−.13**	−.03	−.16***	−.09	−.09	−.19***
8	ICT use attitudes	3.39	0.91	1.00	5.00	−.05	−.24***	–.03	−.13**	–.02	−.17***	−.03	(.87)
9	Primary work location	0.43	0.50	0.00	1.00	−.03	−.05	−.04	−.15**	.05	−.12*	.13**	.02
10	Organizational support	3.53	0.91	1.00	5.00	.24***	−.14**	.19***	.12*	.01	.03	−.03	.04	.02
11	Norway	0.15	0.36	0.00	1.00	.15**	−.12*	.10*	−.02	.06	.07	−.03	−.19***	−.06	–.06
12	Italy	0.27	0.44	0.00	1.00	−.15**	−.03	−.05	.02	.16**	.10*	.02	.21***	−.10*	.23***	–.26***

Note. Responses on the latent variables were provided on a five-point Likert scale (1 = strongly disagree; 5 = strongly agree).

Values in parentheses are alpha coefficients. Germany serves as a reference category for Norway and Italy.

p < .05. **p < .01. ***p < .001.

On average, participants are satisfied with their jobs (M = 4.06), agree to have some job autonomy (M = 3.75) and exhibit an intermediate level of digital overload (M = 2.87). A closer look at the two stressors reveals that respondents across all countries report higher techno-overload than communication overload (see Figure 3). Norwegian respondents show the lowest level of techno- and communication overload,² and both stressors are closer together than in Italy and Germany: In these countries, techno-overload is reported to be higher than communication overload, that is, government employees experience higher stress levels related to their own use of ICTs than generated by their work-related contacts using them. This gap is slightly larger for Italian than for German employees. However, German respondents agree more strongly, that is, they vary less in their respective stressor assessments.

Figure 3.

Digital overload by country.

The highest level of agreement on techno-overload is that ICT-use requires an adaptation of work habits (M = 3.44), followed by ICT-use causing tighter time schedules (M = 3.38) and faster workflows (M = 3.12) (see Table A1 in Supplemental Material). Larger workloads are perceived to be less of a consequence of ICT-use (M = 2.66). Similarly, communication overload assessments show higher levels of agreement for electronic communication as a source of time wasted (M = 2.91) as well as for ICT dividing government employees’ attention at work (M = 2.70).

With a mean of M = 3.39, government officials indicate rather positive ICT-use attitudes. The respective item scores show that they generally like to try out new ICT-tools (M = 3.76) but are less eager to experiment with them (M = 3.43), especially when asked to compare themselves to colleagues (M = 2.97).

Main Analyses and Results

We tested our hypotheses by employing SEM, using maximum-likelihood (ML) estimation. Our structural model included paths from digital overload as well as the control variables to both the mediator and dependent variable. The controls were also allowed to correlate with each other, and our model fitted the data well (χ² = 445.34, df = 182, CFI = .905, SRMR = .050, and RMSEA = .059, AIC = 22806.60). Hypothesis 1 predicted that digital overload negatively affects government employees’ job autonomy, which is supported by our structural model (β = −.23, p < .05). Moreover, and in line with prior research, job autonomy yields a significant and positive effect on job satisfaction (β = .24, p < .001), supporting hypothesis 2. Our structural equation model also indicates a significant indirect effect of digital overload on job satisfaction via reducing job autonomy (β = −.06, p < .05). Hence, hypothesis 3 also gains support from our analysis. As the direct path from digital overload to job satisfaction remains significant (β = .35, p < .01) and an “indirect effects only” model fits the data worse than the partial mediation model (χ² = 451.06, df = 183, CFI = 0.903, SRMR = .055, and RMSEA = .059, AIC = 23077.00), we find that job autonomy partially mediates the negative association between digital overload and job satisfaction. A closer look at the two digital overload dimensions indicates that the correlation between techno-overload and job autonomy (r = −.15) as well job satisfaction (r = −.23) is somewhat weaker than the association between communication overload and its downstream variables (r = −.19 and r = −.29, respectively), suggesting that accelerated communication and frequent interruptions cause a greater share of detrimental effects (Table 3).

Table 3.

Results of the Structural Model (N = 420).

	Mediator variable model			Dependent variable model
	Job autonomy			Job satisfaction
	Effect (SE)	95% CI		Effect (SE)	95% CI
	Effect (SE)	Lower	Upper	Effect (SE)	Lower	Upper
Digital overload	−0.23* (0.11)	−0.44	−0.02	−0.35** (0.10)	−0.54	−0.15
Job autonomy				0.24*** (0.05)	0.14	0.34
Rank	0.10 (0.10)	−.11	0.30	0.04 (0.09)	−0.14	0.22
Job tenure	−0.05 (0.03)	−0.11	0.01	−0.05 (0.03)	−0.10	0.00
Age	0.02* (0.01)	.01	0.03	0.00 (0.01)	−0.01	0.01
Gender	−0.22** (0.08)	−.37	−0.07	−0.12 (0.07)	−0.26	0.01
Primary work location	0.02 (0.08)	−.13	0.17	−0.04 (0.07)	−0.17	0.10
Organizational support	0.16*** (0.04)	.08	0.24	0.17*** (0.04)	0.10	0.25
ICT use attitudes	−0.03 (0.06)	−.14	0.07	−0.08 (0.05)	−0.17	0.02
Norway (0 = Germany)	0.20 (0.11)	−.02	0.41	0.12 (.10)	−0.07	0.31
Italy (0 = Germany)	−0.08 (0.09)	−.26	0.10	−0.26* (.08)	−0.42	−0.10
					95% CI
Direct effects				Effect (SE)	Lower	Upper
Digital overload → Job satisfaction				−0.35** (0.10)	−0.54	−0.15
					95% CI
Indirect effect				Effect (SE)	Lower	Upper
Digital overload → autonomy → Job satisfaction				−0.06* (0.03)	−0.11	−0.00
					95% CI
Total effect				Effect (SE)	Lower	Upper
				−0.40*** (0.10)	−0.60	−0.20

p < .05. **p < .01. ***p < .001.

Most of our controls show no significant effects. As an exception, gender yields significant negative effects on job autonomy, indicating that women self-reported to be less autonomous than their male counterparts. These findings confirm previous studies in which female public mangers reported significantly lower decision latitude than male public managers (Furunes et al., 2011; Sturm et al., 2014). The control variables further yield a positive effect of organizational support on job autonomy and satisfaction and indicate that Italian government employees are significantly less satisfied with their jobs than the German reference group. This may be related to the strong formalism and juridification of the Italian civil service, which offers secure career tracks but comparatively less power and status (Kickert, 2005). Lastly, the Norwegian participants’ positive association with job autonomy, though not significant, is likely to reflect the high level of shared norms and values among political and administrative actors (Christensen & Lægreid, 2005) (Table 3).

To check the robustness of our findings, we compared our structural model to several alternative solutions. First, we reran our analysis without including any control variables and all our parameter estimates remained (see Table 4). Second, we tested an alternative mediation model in which job autonomy served as an independent, and digital overload as a mediating variable, following the existing literature that treats job autonomy most often as an important antecedent of work outcomes. However, such an alternative mediation model fitted the data significantly worse than our hypothesized model. Third, we examined an alternative moderation model in which the relationship between digital overload and job satisfaction is conditional on government employees’ job autonomy because the latter is often considered as a contextual variable reducing the harmful effects of various stressors. However, the moderation model yielded a significantly worse fit as well. Lastly, we tested an inverted structural model in which all the hypothesized paths were specified to point into the opposite direction. Again, the model performed worse than our hypothesized model, further strengthening our confidence in this study’s findings (Table 5).

Table 4.

Results of the Alternative No-controls Structural Model (N = 420).

	Mediator variable model			Dependent variable model
	Job autonomy			Job satisfaction
	Effect (SE)	95% CI		Effect (SE)	95% CI
	Effect (SE)	Lower	Upper	Effect (SE)	Lower	Upper
Digital overload	−0.24* (0.10)	−0.44	−0.04	−0.33*** (0.09)	−0.51	−0.14
Job autonomy				0.32*** (0.05)	0.22	0.42
					95% CI
Indirect effect				Effect (SE)	Lower	Upper
Digital overload → autonomy → Job satisfaction				−0.08* (0.03)	−0.14	−0.01
Total effects
				−0.41*** (0.10)	−0.60	−0.21

p < .05. **p < .01. ***p < .001.

Table 5.

Summary of the Hypothesized and Alternative Structural Models (N = 420).

	χ²	df	χ²/df	Δdf	Δχ²	SRMR	RMSEA	CFI	AIC
Structural model
Hypothesized structural model	445.34	182.00	2.45	—	—	.050	.059	.905	22806.60
Alternative mediation model	471.82	182.00	2.59	0.00	26.48	.054	.062	.895	22833.08
Alternative moderation model	515.60	212.00	2.43	30.00	70.26	.059	.058	.891	22833.96
Alternative inverted structural model	489.21	183.00	2.67	1.00	43.87	.051	.063	.889	21888.46

Conclusion

In this paper, we studied how the increasing use of ICT tools at work may inhibit stressors of digital overload for government employees, which shape their job satisfaction. We show that digital overload has significant negative effects on job autonomy and on job satisfaction, whereby job autonomy partially mediates the negative relationship between digital overload and job satisfaction. Although we focused on government employees engaged in policy formulation, we expect these individual-level mechanisms to be generalizable for public employees involved in service delivery as well as for private sector employees. Nevertheless, such other employees may use more or different ICTs at work and are arguably exposed to additional stressors. Considering that behavioral digitalization dynamics in policymaking inside ministerial bureaucracies is an understudied research area in comparison to public sector employees involved in service delivery (Camarena & Fusi, 2022; Fusi & Feeney, 2018a), our findings provide valuable first insights into the nature and consequences of digital overload among policy officials.

Moreover, this study and its findings extend our current knowledge in several ways. Firstly, considering digital overload as a determinant of job autonomy, that is, an externally imposed pressure that reduces choice and self-initiation at work, challenges the current scholarly view of job autonomy as a condition of ICT-induced work stress. If digital overload and the responding changing work routines reduce perceptions of job autonomy in an environment already known to leave less room for individual discretion, the practical implications for government employees may be much different than merely considering job autonomy as antecedent or moderating variable. For example, government organizations may have to invest in training measures to strengthen employees’ digital resilience (e.g., in terms of e-skills, self-care as well as remote social and remote emotional skills, see Tramontano et al., 2021), thus encouraging ICT-use in a self-paced and self-determined manner and mitigate negative effects on job satisfaction. However, while our SEM results support the assumed negative impact of digital overload on job satisfaction via impairing job autonomy, the analytical procedures do not allow for conclusions about causality. Future research may employ longitudinal or experimental designs to investigate the causal relationship between digital overload and job satisfaction in the policy formulation context further and confirm the observed effects across different institutional contexts and administrative traditions.

Secondly, job autonomy partially mediates the effects of digital overload on job satisfaction, which is crucial for the scholarly debate on the digital transformation of the public sector. Our current knowledge on the use of ICTs in the public sector oftentimes discusses the virtues and pitfalls of ICT tools in policy design and service delivery, thus taking an output-oriented perspective and widely diminishing individual consequences (Cordella & Tempini, 2015; Höchtl et al., 2016; Janowski, 2015). If the debate discusses individual level effects, they are mostly considered as the changing prerogatives of bureaucrats’ discretion, also to study how digital tools may allow for reducing human error and malevolent bureaucratic behavior (Busch et al., 2018). Yet our study sheds light to a crucial unintended consequence of the digital transformation of the public sector. In line with other recent studies on the relevance of ICT for shifting control over bureaucratic behavior (Charbonneau & Doberstein, 2020), we show that digital overload exists, that is, government employees respond in their work routines to the ICT-use at work. Considering the crucial importance of job satisfaction for phenomena such as organizational and task performance, the negative effects of digital overload deserve further attention for those government employees engaged in policy design, including potential performance effects in terms of the very substance of government policies.

Lastly, the use of ICTs in service delivery is a common theme of empirical research, including also raising concerns over the “digital monitoring” of employees (Fusi & Feeney, 2018a), whereas the “creeping” digital transformation in policy formulation is often neglected. Our current knowledge on the causes and consequences of using ICTs in these processes of government policymaking is best in discussing big data (Kettl, 2016), assessing the role of actors promoting digitalization across governments (Clarke, 2020; Mergel, 2019), or discussing the effects of digital means for government coordination (Christensen & Lægreid, 2022). Hence, this study adds that the accelerated use of ICTs in policy formulation yields considerable effects for the micro-foundation of bureaucratic behavior, as we exemplified for job satisfaction.

Supplemental Material

sj-docx-1-rop-10.1177_0734371X221148403 – Supplemental material for Job Satisfaction and the Digital Transformation of the Public Sector: The Mediating Role of Job Autonomy

Supplemental material, sj-docx-1-rop-10.1177_0734371X221148403 for Job Satisfaction and the Digital Transformation of the Public Sector: The Mediating Role of Job Autonomy by Julia Fleischer and Camilla Wanckel in Review of Public Personnel Administration

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 726840.

ORCID iD

Julia Fleischer

Supplemental Material

Supplemental material for this article is available online.

Notes

Author Biographies

Julia Fleischer is Professor and Chair in German Politics and Government at the University of Potsdam. Her research addresses comparative public administration and governance, she is particularly interested in the transformation of organizational and individual behavior.

Camilla Wanckel is research fellow and doctoral student at the Chair for German Politics and Government at the University of Potsdam. She studies the behavioral foundations and effect of information and communication technologies (ICT) on policy-making processes inside governments.

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