Work-related use of information and communication technologies after hours—which refers to the use of portable communication devices to work or contacting work-related people during nonworking hours (Fujimoto et al., 2016)—at any time of the day or night, is anticipated to become a feature of online offices (O’Driscoll et al., 2010). While people enjoy the benefits of W_ICTs (e.g., working from anywhere and at any time), they are already feeling the negative impact of rising W_ICTs requirements (Huang & Liang, 2018). In a Confucian cultural organizational context, where the boundaries between work and home are blurred, many companies do not have specific rules but still expect employees to be available when they receive a work message during nonworking hours. According to a 2018 online survey by the Shanghai Observer in China, during nonworking hours, work instructions have become the norm for WeChat workgroups, and only 19.7% of respondents never receive work instructions (Chu, 2018). W_ICTs may trigger a series of negative effects on work behavior, which include lower work engagement, higher turnover intention, and less proactive behavior (Lanaj et al., 2014).

The hidden or nonobvious requirement of W_ICTs means that employees are unable to leave their work completely during nonworking hours. After-hour tasks can be considered as job demands that reduce employees’ psychology resources. Under the pressure of time-sensitive and complex tasks, it is difficult to avoid error. For example, employees working in the service industry need to respond to customer messages and handle unexpected situations in a timely manner. This creates an unfavorable gap between what is expected and the actual result caused by individuals’ decisions and behaviors, and may have real or potential influence on organizations (Zhao & Olivera, 2006). Employees are often reluctant to report their errors, given the costs and potential negative effects of doing so (Uribe et al., 2002), but the reporting of errors is unclear in the context of W_ICTs. It is important for employees to admit their errors in order to discover problems, improve work, enhance organizational performance, and even promote the safety of society and others (Zhang et al., 2016).

The extant literature has considered the “double-edged sword” effects of W_ICTs (Ohly & Latour, 2014), but few researchers have considered the mechanism of the results and the boundary conditions. In the process of W_ICTs, we suggest that multiple interactions among individuals, teams, and organizations will have a profound impact on employees’ work and life. This study explored the psychological mechanism through which employees’ W_ICTs affect their error admission via emotional state, to enrich the contextual research on W_ICTs based on the person–organization fit perspective.

The Current Study

The job demands–resources (JD–R) model provides a theoretical framework from the perspective of resource gain and loss. According to Demerouti et al. (2001), job demands refer to aspects of the job that require continuous physical or mental effort from employees. Job resources are positive job factors that can reduce the physical and psychological cost related to job demands. The JD–R model postulates that burnout develops in two stages: In the first stage, extreme job demands result in constant overburden and exhaustion. In the second stage, the satisfaction of job demands is complicated by a resource shortage, which results in withdrawal behavior.

W_ICTs are a special form of work demand that consumes individual resources (Ter Hoeven et al., 2016). In this study we refer to Zhang et al.’s (2016) definition of error admission, that is, employees actively report to their leaders and admit their mistakes, and explain that they will try their best to correct those mistakes. Error admission is a proactive behavior (Zhang et al., 2016) and a decision made by an employee based on cost–benefit evaluation (Zhao & Olivera, 2006), which means that the employee has to devote more resources to taking the initiative and dealing with the results of error admission. High demands of W_ICTs drain employees’ psychological resources, which leads to withdrawal from error admission. To avoid further depletion of individual resources, employees are unwilling to admit errors when they are involved in W_ICTs. Therefore, we proposed the following hypothesis:
Hypothesis 1: Work-related use of information and communication technologies after hours will negatively affect employees’ error admission.

Emotional exhaustion is a negative emotional response in which an individual’s resources (e.g., psychological resources) are depleted (Baskerville Watkins et al., 2015). During W_ICTs, employees cannot fully put down portable communication devices after hours because they need to pay attention to their job and be ready to contact work-related people. They invest and waste a lot of their own resources, such as psychological resources, to adjust their emotions. Therefore, we proposed the following hypothesis:
Hypothesis 2: Work-related use of information and communication technologies after hours will increase employees’ emotional exhaustion.

Self-control behavior relies on a common resource that becomes depleted with use (Vohs & Heatherton, 2000). When these resources are depleted, people are more likely to act impulsively, and their ability and willingness to work temporarily declines. Rational decision-making processes can drain resources of self-control (Baumeister et al., 2007). Psychologically, ego depletion reduces employees’ ability to think critically. Individuals who make decisions based on intuition and impulsiveness may engage in short-sighted behaviors such as paying attention to immediate rewards without considering long-term consequences (Jimura et al., 2013). Faced with ego depletion, employees will reduce their work input or output, and be less likely to engage in positive organizational behavior, such as organizational citizenship behavior (Trougakos et al., 2015).

When employees make error-reporting decisions they experience complex psychological processes, including error detection, situation assessment, and behavioral performance (Zhao & Olivera, 2006). In the process of W_ICTs, employees consume psychological resources to deal with tasks in a timely manner, resulting in emotional exhaustion. The available control resources for thinking and decision making are thus reduced, and employees’ impulsive and short-sighted behavior hinders their refined thinking process. Employees’ intuitive defense against errors may cause them to believe that concealing errors means the successful completion of W_ICTs tasks, without full consideration of the resultant effect. Therefore, we proposed the following hypothesis:
Hypothesis 3: Emotional exhaustion will mediate the relationship between work-related use of information and communication technologies after hours, and error admission.

Person–environment fit is defined as the congruence between an employee and their organizational environment (Cable & DeRue, 2002). In the context of an organization, Chatman’s (1989) person–organization fit model emphasizes the importance of values and defines the fit between the members of an organization and the organization’s values and norms.

The matching of individual and environment is a multidimensional, complex, dynamic process because personal and organizational characteristics will change. Individuals and organizations achieve consistent results in the process of mutual response (Su et al., 2015). On the personal front, individuals with higher motivation can remodel their work to match the environment (Bakker et al., 2012). As regards the organizational aspect, organizations choose the right individuals through recruitment, and pass on organizational values to the employees to increase the degree to which they match. According to person–environment fit theory, fit can reduce the conflict of individuals and enhance their positive experience. Specifically, individuals are more active when working within organizations that match their values and skills (Milliman et al., 2017). As a resource for coping with intense work demands (Babakus et al., 2010), person–organization fit predicts higher retention, organizational commitment, job performance, work–family balance, and job satisfaction (Chatman, 1989; Fan, 2018). A better match between employees’ work values and organizational values contributes to better work outcomes, including better work-related attitudes and behaviors (Bao et al., 2012).

In the process of W_ICTs, the success of employee connectivity depends on the consistency of the values of W_ICTs with the organization, that is, the consistency of individual segmentation preference with organization segmentation supply. Individuals with segmentation preferences tend to separate the work–home domain as much as possible by establishing and maintaining psychologically strong boundaries (Zerubavel, 1991). They prefer dealing only with work matters while in the workplace, and focusing on domestic life while at home. Workplaces vary in the extent to which they supply conditions or resources that enable individuals to separate work and family life (Kreiner, 2006). When employees’ preference for personal segmentation (vs. integration) is high, organizations providing a workplace with separate (vs. integrated) work and home environments match employees’ connectivity avoidance (vs. coping) strategies. Matching is a positive experience, and the matching strategy provided can be viewed as the resources of the organization supplementing the personal resources of the employees after emotional exhaustion, to alleviate the loss of personal resources. The self-control resources of employees for error admission are increased. Not limited to short-sighted impulse thinking, employees can consider the long-term personal and organizational loss caused by underreporting, reducing the possibility of concealing errors. Therefore, we proposed the following hypothesis:
Hypothesis 4: The relationship between emotional exhaustion and error admission will be negatively moderated by person–organization fit, that is, the better the person–organization fit, the weaker will be the negative influence of work-related use of information and communication technologies after hours on error admission.

Method

Participants and Procedure

Following the APA requirements regarding treatment and protection of human participants, all respondents provided informed consent for this study. Participants were employees from several companies in Shanghai, Beijing, and Guangzhou, China. We used experience sampling to capture dynamic daily behaviors, by collecting 1,231 questionnaires from 64 employees who had experienced W_ICTs. The formal survey lasted for 10 consecutive working days. Participants were asked to fill out a questionnaire before going to work in the morning and before going to bed at night. We obtained 1,035 valid questionnaires from 55 respondents (response rate = 85.94%).

Among the 55 participants, 25 (45.5%) were men and 30 (54.5%) were women. In terms of age, 34.5% were aged 25 years or younger, 10.9% between 26 and 30 years, 25.4% between 31 and 40 years, and 29.2% over 40 years. The organizational positions of participants were 45.7% junior managers, 23.2% middle managers, 19.3% staff, and 11.8% senior managers. Their education level was 7.3% high school and below, 72.7% college or undergraduate, 18.2% master’s degree, and 1.8% doctoral degree and above. Participants’ team working tenure was 17% working for 0.5 to 1 year, 36.2% for 1 to 3 years, 8.5% for 3 to 5 years, and 38.3% for 5 years and over.

We measured within-person variance once (N = 1,035, Level 1), including individual segmentation preference and organization segmentation supply. We measured between-person variance repeatedly (N = 55, Level 2), including W_ICTs, emotional exhaustion, and error admission. The participants’ gender, age, position, education level, and team working time were controlled for.

Measures

We adopted all constructs from existing studies. Participants rated the items on a 5-point Likert scale ranging from 1 = strongly disagree to 5 = strongly agree, except for W_ICTs, which were measured on a 5-point scale ranging from 1 = never to 5 = very often.

Independent Variable
We used a three-item W_ICTs scale from Ma et al.’s (2016) study. An example item is “How often do I check all kinds of work-related messages?” Cronbach’s alpha in this study was .91.

Mediating Variable
We used the three-item Emotional Exhaustion Scale from Watkins et al. (2015). A sample item is “I feel mentally drained by work.” Cronbach’s alpha in this study was .94.

Dependent Variable
We used the six-item feedback mitigation strategy scale from Moss et al. (2003). A scene description of W_ICTs was added to each question. A typical item is “If something goes wrong at work outside of work hours, I will immediately report my poor performance to my supervisor.” Cronbach’s alpha in this study was .84.

Moderating Variable
Person–organization fit was measured with four items by Kreiner (2006). Individual segmentation preferences included items such as “I don’t like to think about work when I’m at home.” Cronbach’s alpha in this study was .72. Organizational segmentation included items such as “My team makes people forget to work at home.” Cronbach’s alpha in this study was .72. In accordance with Kreiner (2006), person–organization fit was calculated by 1 minus the absolute value of the difference between organizational segmentation supply and individual segmentation preference.

The intraclass correlation coefficient (ICC1) of error admission was .64. Values below .06 are considered to indicate a weak correlation and those above .12 indicate a strong correlation (Cohen, 1988). This indicates that error admission had a significant difference at the between-subjects level, which warrants the use of multilevel modeling.

Results

Measurement Model

Means, standard deviations, and correlation values are presented in Table 1. Correlations below the diagonal, calculated by variables that were measured once at the person level, represent the between-subjects level. Correlations above the diagonal, calculated by variables that were measured on the day level, represent the within-subjects level. At the within-subjects level, W_ICTs were positively correlated with emotional exhaustion and error admission. Emotional exhaustion was positively correlated with error admission.

We used Mplus to conduct a cross-layer confirmatory factor analysis (CFA) of the key variables. As shown in Table 2, the five-factor model offered the best fit to the data. The measurement of five variables represented five different conformations and had good discriminant validity.

Structural Equation Modeling

As shown in Table 3, daily W_ICTs significantly and negatively affected error admission, daily emotional exhaustion significantly and negatively affected error admission, and W_ICTs significantly and positively affected emotional exhaustion. Thus, Hypotheses 1 to 3 were supported.

We used bootstrapping analysis to test the mediating effect of emotional exhaustion in the relationship between W_ICTs and error admission. The mediating effect was significant, 95% confidence interval [0.01, 0.02]. Further, as shown in Table 4, the square of the difference significantly and positively moderated the effect of emotional exhaustion on error admission. Thus, Hypothesis 4 was supported.

Discussion

Theoretical Implications

Most studies on the negative effects of W_ICTs have focused on family-related fields, such as reduced well-being and work–family conflict (Ohly & Latour, 2014; Schieman & Young, 2013; Schlachter et al., 2018); thus, the impact on specific work behavior remains to be examined. Through a new perspective of the JD–R model, we constructed a theoretical model of the effect of W_ICTs on employee error admission, in which we explored the antecedents of employee error admission. Our results enrich contextual research on W_ICTs.

The motivation of employee error admission is complex, and there are many influencing factors. Existing research has mainly focused on the environmental and personal perspectives (Hofmann & Mark, 2006; Russo et al., 2015), and the antecedents of error admission from the perspective of rational decision making, such as profit and loss analysis (Zhao & Olivera, 2006). We explored the psychological mechanism by which employees’ W_ICTs via emotional state affect their error admission.

When considering the situational factors of the process of W_ICTs, previous research has usually begun from a single perspective, ignoring the interaction of individual and environmental factors (Olson-Buchanan & Boswell, 2006; Park et al., 2011). However, we found that person–organization fit mitigated the strength of the relationship between emotional exhaustion and error admission.

Practical Implications

Errors in work cannot be eliminated, and those responsible for errors often choose to conceal or omit admitting their mistakes, which is contrary to organizations’ requirement for the timely reporting of errors. Frequent W_ICTs make employees more likely to hide errors during nonworking hours. At present, most organizations regard W_ICTs as an implicit requirement for their employees, and do not explicitly advise employees on whether to separate or integrate work and family. Employees use their perception of the W_ICTs atmosphere in their environment to understand the organization’s value orientation on whether nonworking hours should be worked. Because most organizations do not clearly define or emphasize the work norms and requirements regarding W_ICTs, the perceived organizational requirements of employees are the completion of tasks, and their negative emotional state promotes negative coping with errors that occur.

Therefore, enterprises should accurately communicate the organization’s W_ICTs norms to employees to offer more accurate psychological expectations. Enterprises should do so in a way that rewards rather than punishes, to encourage employees’ error admission and create a good error-management atmosphere both within and outside working hours. Second, the organization should attach importance to the matching of employees’ W_ICTs preference. Organizations can hire people who fit the company’s W_ICTs norms, and can influence their employees’ segmentation preferences by adopting policies, such as requiring that important tasks be done as often as possible during working hours, and let employees choose whether to work during nonwork time.

Limitations and Future Research Directions

Our study considered the fit of individual and organization on work–family boundary management preferences. Other factors can also be considered in future, such as employees’ match with their team, leadership, and colleagues. When the social exchange relationship between employees and their organization is harmful, employees adjust their work attitudes negatively in response to unfavorable treatment (Parzefall & Salin, 2010). In the context of W_ICTs, employees are often unpaid for extra work. Faced with this unequal reciprocity, they may feel justified in not reporting errors. Future research could further examine the relationship between error admission and W_ICTs based on different perspectives.

Conclusion

We explored the mechanism of the impact of W_ICTs on employees’ nonwork time error admission. In addition, we employed experience sampling to assess the dynamic variation in the variables. We found that employees’ daily W_ICTs had significant negative effects on error admission, that emotional exhaustion mediated the relationship between W_ICTs and error admission, and that person–organization fit negatively moderated the relationship between emotional exhaustion and error admission. We suggest that organizations should attach importance to the matching of employees’ W_ICTs preference.

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This study was supported by the Shandong Provincial Education Department Research Project

The study of industry-education integrated enterprises (GD46)

the National Natural Science Foundation of China (72072110)

and the Shanghai Philosophy and Social Science Planning Project (2019BGL001).

Yiyun Sheng, SHU-UTS SILC Business School, Shanghai University, #20, Chengzhong Road, Jiading District, Shanghai, People’s Republic of China. Email: [email protected], or Weiwei Huo, SHU-UTS SILC Business School, Shanghai University, #20, Chengzhong Road, Jiading District, Shanghai, People’s Republic of China. Email: [email protected]