Abstract
Purpose
The purpose of this study is to clarify why business travel has ambivalent effects on occupational well-being. We examine associations between business travel, career satisfaction and turnover intentions, as well as the mediating role of functional and dysfunctional coping strategies.
Design/methodology/approach
We collected four waves of data across three months from 676 employees (n = 147 business travelers who traveled for work at least once during the study period; n = 529 non-travelers) working in various industries and managerial positions.
Findings
Consistent with expectations, the greater the extent of business travel, the higher both career satisfaction (mediated by higher emotional and instrumental support, positive reframing, and substance use, and lower venting and self-distraction, denial and self-blame, and behavioral disengagement) and turnover intentions (mediated by higher active coping and planning, venting and self-distraction, behavioral disengagement, and lower positive reframing).
Practical implications
Findings reveal that business travel presents an ambivalent psychological experience and point to the importance of obtaining and using a coping portfolio in this context.
Originality/value
This study addresses functional and dysfunctional coping as unexplored mediating mechanisms between business travel, career satisfaction, and turnover intentions and provides new insights for research and practice on business travel.
Keywords
Citation
Weiss, M. and Zacher, H. (2025), "Another trip? Functional and dysfunctional coping with business travel", Journal of Managerial Psychology, Vol. 40 No. 1, pp. 1-20. https://doi.org/10.1108/JMP-09-2023-0524
Publisher
:Emerald Publishing Limited
Copyright © 2024, Mona Weiss and Hannes Zacher
License
Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
Despite the increasing use of online communication technology and virtual meetings, many employees frequently go on business trips. Research shows that regularly traveling for work can be challenging for employees as it can hamper their work-life-balance and increase stress (e.g. Espino et al., 2002; Ivancevich et al., 2003). Yet, more recent research has also revealed that business travel can generate positive effects, such as recovery from work or higher work engagement (e.g. Dimitrova et al., 2020). Thus, business travel seems to pose a “double-edged sword”, that is, an ambivalent psychological experience entailing both positive and negative aspects (e.g. Dimitrova, 2020). Although a recent study has addressed some select functional coping strategies in the context of business travel (e.g. preventive coping; Niessen et al., 2018), not much is known about a wider range of coping styles including functional (e.g. active coping, social support) and dysfunctional coping (e.g. substance use, denial) that might explain why business travel can have both positive and negative effects. Moreover, most previous research has studied positive and negative effects of business travel in isolation rather than in concert (e.g. turnover intentions, Dimitrova, 2020; work engagement, Niessen et al., 2018). Yet, a simultaneous consideration of positive and negative effects of business travel as well as an in-depth consideration of coping styles is imperative to enhance our theoretical understanding of the outcomes and mechanisms underlying the recently suggested dual nature of business travel.
Based on conservation of resources (COR) theory (Hobfoll, 1989; Hobfoll et al., 2018), and the dualistic perspective on business travel (e.g. Dimitrova, 2020; Niessen et al., 2018), we argue that business travel simultaneously relates to two key opposing indicators of occupational well-being (i.e. career satisfaction, turnover intentions) through functional (e.g. active coping, emotional support, positive reframing) and dysfunctional (e.g. denial, substance use; see Carver, 1997) coping mechanisms. Using a heterogeneous sample of 676 employees across multiple industries (e.g. healthcare, service industries, public administration, insurances) and adopting a time-lagged design with four measurement waves, we reveal differential pathways between business travel, functional and dysfunctional coping strategies, as well as career satisfaction and turnover intentions.
With our study, we contribute to and extend research on business travel and its psychological consequences for employees. Theoretically, our findings support the idea that business travel is an ambivalent experience entailing both positive and negative effects (e.g. Dimitrova, 2020; Niessen et al., 2018). However, we extend the literature by considering various functional and dysfunctional coping strategies to explain why these opposing effects occur (Carver and Connor-Smith, 2010). In contrast to previous research, we also broaden the concept of business travel and study its intensity (e.g. national vs. international trips, duration of stay) in addition to its mere frequency to more adequately capture the demands and resources associated with this experience. We generate new theoretical insights into how coping styles can explain why business travel can be both detrimental and beneficial for occupational well-being. As such, our findings also hold important practical implications for organizations and human resource management to recognize the dual nature of business travel and to support employees in effectively coping with business travel.
Business travel, career satisfaction, and turnover intentions
To understand how business travel affects occupational well-being via different coping styles, we draw from COR theory, which has been applied to explain a wide range of motivational and work-related outcomes, such as job and career satisfaction, work engagement, and turnover intentions (e.g. Akirmak and Ayla, 2021; Bakker and Xanthopoulou, 2009). COR theory proposes that individuals strive to protect the resources they value and are motivated to seize new resources (Hobfoll, 1989; Hobfoll et al., 2018). Resources are broadly understood as objects, other individuals, conditions, personal characteristics, or mental and physical energies that are individually or socially valued and perceived as instrumental in achieving goals (Halbesleben et al., 2014; Hobfoll, 1989, 2002).
An emerging line of research has conceptualized business travel as an ambivalent experience as it can simultaneously deplete as well as replenish individuals’ resources (e.g. Dimitrova, 2020; Niessen et al., 2018; Ye and Xu, 2020). On the one hand, when individuals are required to travel for work internationally, potentially involving overseas flights, they may experience jetlag and sleep deprivation, flight delays, as well as novel cultural contexts and frequent meetings with clients or business partners (Gustafson, 2014). Business travelers’ work-life balance may also suffer due to frequent time away from home and resulting negative effects on their spouses and family (Espino et al., 2002). On the other hand, it has been shown that taking a work-related trip can support employees in acquiring new knowledge and skills (Oddou et al., 2000) and can increase mental energy through relaxation or a change in demands (Westman et al., 2009). Business travel may also entail a pleasant disruption from daily work routines, which, in turn, may even have benefits for individuals’ private life as the “everyday pressures of the job are presumed to be absent, or at least appreciably diminished” (Eden, 2001, p. 145).
Based on the COR framework and the previously identified opposing effects of business travel, we propose that business travel is positively associated with both career satisfaction and turnover intentions. We focus on career satisfaction and turnover intentions as two complementary indicators of occupational well-being and work-related motivation (Chan and Mai, 2015). Career satisfaction has been described as a key intrinsic career outcome that reflects individuals’ subjective perceptions of their career progress (Ng et al., 2005). Turnover intentions are defined as behavioral intention to leave one’s current employer or organization (Vandenberg and Nelson, 1999). These withdrawal intentions are often accompanied by an active search for alternative employment and positively predict actual turnover (Allen et al., 2005; Cho and Lewis, 2012; Griffeth et al., 2000).
Previous findings suggest that business travel may relate to higher career satisfaction. For example, Dimitrova et al. (2020) investigated how business travel relates to career satisfaction based on a sample of 161 business travelers. Cross-sectional findings revealed that business travel was positively and indirectly related to career satisfaction through adjustment. Further qualitative research by Demel and Mayrhofer (2010) demonstrates that business travelers tend to exhibit specific forms of career aspirations. As stated by a male frequent flyer, “it needs to be something extraordinary, that I am doing, I am not satisfied with average” (Demel and Mayrhofer, 2010, p. 305). Thus, from a COR perspective, a greater extent of traveling for work (vs. a lower extent of or no business travel) might fuel personal resources as the experience of business travel leads to the fulfillment of individually valued career goals and resources (Hobfoll, 1989). Business travel may be perceived as a valuable, exceptional, and stimulating experience that enables business travelers to seize new resources (e.g. networking, personal agency, cultural diversity), which increases satisfaction with one’s career. Importantly, and in contrast to most previous research (e.g. Dimitrova, 2020; Dimitrova et al., 2020; Niessen et al., 2018), we are not just focusing on the frequency of traveling for work but also on its intensity (e.g. national vs. international vs. overseas trips, duration of trip). From a COR perspective (Hobfoll, 1989), capturing the extent of business travel (i.e. frequency and intensity) likely has different implications for the mental, physical, and career-related resources that are fueled by a trip than merely considering how often people travel for work.
Individuals who travel for work to a greater extent may also actively seek this opportunity in order to obtain career-related possibilities and resources that – from their perspective – are exceptional resources uniquely associated with the experience of traveling for work (Demel and Mayrhofer, 2010). In contrast, employees who travel less or not at all for work may have a reduced likelihood of obtaining these possibilities and resources. We thus posit that:
A greater extent of business travel (vs. a lower extent of or no business travel) is associated with higher career satisfaction.
Although we propose that individuals who travel for work to a greater extent are likely to be more satisfied with their career, we also suggest that business travel has the potential to result in higher intentions to quit. Previous research has demonstrated that business travel may increase employees’ turnover intentions particularly when work roles and associated tasks are perceived as mundane and repetitive (Dimitrova, 2020). As argued before, traveling for work to a greater extent (vs. traveling to a lower extent or not at all for work) may involve challenging social, physical, and psychological experiences (e.g. Demel and Mayrhofer, 2010; Espino et al., 2002). These experiences can lead to stress when such travel-related stressors exceed individuals’ mental and physical resources (e.g. Ivancevich et al., 2003). Because individuals strive to protect their resources (Hobfoll, 1989), business travelers may be more likely to look for alternative employment when they feel that they cannot meet high travel-related demands. Particularly, when business trips are intense (e.g. long-haul flights, several days or weeks away from home), their demanding aspects may become more salient to individuals, more difficult to manage, and thus, more likely to reinforce turnover intentions. In contrast, employees who travel less or not at all for work are less likely to face these challenging demands. We thus propose:
A greater extent of business travel (vs. a lower extent of or no business travel) is associated with higher turnover intentions.
Functional and dysfunctional coping strategies as mediating mechanisms
To explain why business travel can simultaneously increase career satisfaction and turnover intentions, we draw on the psychological coping literature (Carver and Connor-Smith, 2010; Carver, 2007). Individuals differ in the way in which they cope with challenging situations and these responses have fundamental consequences for their well-being (Carver and Connor-Smith, 2010). We propose that business travelers use functional and dysfunctional coping strategies when engaging in business trips and variation in these coping strategies explains why traveling for work can simultaneously enhance career satisfaction and turnover intentions.
From a COR perspective, it is also relevant to consider how individuals handle—or cope with—potentially challenging demands to protect and acquire mental, physical or social resources. Lazarus and Folkman (1984) define coping as “the efforts to master, reduce, minimize or tolerate the negative consequences of internal or external demands” (p. 141). Such efforts are typically classified into problem-focused (i.e. addressing the problem itself) and emotion-focused coping (i.e. regulating stressful emotions; Folkman et al., 1986). On this basis, more fine-grained taxonomies have been proposed that distinguish between ten or more different coping strategies including, for example, active coping, seeking social support, religion, positive reframing, behavioral disengagement, denial, or substance use (Carver, 1997). Whereas active coping and seeking social support can be subsumed as problem-focused coping, positive reframing and turning to religion are positively related emotion-focused coping strategies. Thus, these two higher-order strategies, whereby individuals actively tackle negative circumstances or emotions have been referred to as active-functional strategies (Jex et al., 2001). In contrast, when individuals try to completely escape from an issue and the associated feelings and emotions, for instance with substance use or denial, this is considered dysfunctional coping (Carver, 1997). Active-functional coping is commonly associated with lower exhaustion and burnout (Wallace et al., 2010), whereas dysfunctional coping is typically associated with more strain and increased work-related exhaustion (Taris et al., 2005).
Qualitative research by Westman (2004) has revealed that business travelers often use a combination of reactive and proactive coping styles to prevent resource loss. For example, many interviewees indicated that organizing additional social support (e.g. a babysitter) or having pre-packed luggage helped them minimize resource loss. The importance of preventive coping strategies has also been demonstrated in a study by Niessen et al. (2018), which showed that business travelers who were more likely to plan for future eventualities were less likely to experience decreases in work-life-balance and, consequently, reported lower emotional exhaustion and more work engagement. Together, these previous studies suggest the importance of active-functional coping strategies that business travelers use to react to high travel demands in order to counteract or prevent resource loss.
So far, we proposed – based on COR theory – that a greater extent of business travel relates positively to career satisfaction due to the possibility of augmenting specific and possibly unique career-related resources and this relationship has also been established cross-sectionally (Dimitrova et al., 2020). We argue that one potential reason for this relationship may be that employees with a greater extent of business travel (vs. employees who travel less or not at all for work) engage in a variety of functional coping strategies that help them to minimize resource loss and gain individually valued resources during a business trip (Carver and Connor-Smith, 2010). For example, business travelers may engage in coping strategies that allow them to proactively deal with challenging circumstances when traveling for work. Even when trips involve long distance travel and a longer absence from home, functional coping strategies such as positive reinterpretation (e.g. reframing an overseas trip as an opportunity to experience a different country), acceptance (e.g. accepting that traveling for work is part of one’s job), or turning to religion (e.g. finding balance and mental clarity) can help them to maintain a positive mindset (Carver, 1997; Stoeber and Janssen, 2011). Moreover, the positive relationship between business travel and career satisfaction may also be explained by the fact that business travelers are likely to seek social support before or during the trip (e.g. connecting with friends and family virtually or meeting colleagues) and by actively tackling potential issues associated with the business trip in advance (e.g. managing the time away from home; Niessen et al., 2018).
By engaging in these functional coping strategies, they may not only prevent resource loss but may also be able to acquire new resources during the trip, such as new skills and rewarding experiences (Oddou et al., 2000). This likely explains why taking work-related trips can increase career satisfaction as an important work-related resource (Hobfoll, 1989). We thus hypothesize:
The positive association between the extent of business travel and career satisfaction is mediated by (a) active coping/planning, (b) social and instrumental support, (c) positive reframing, (d) religion, and (e) acceptance.
On the other hand, coping styles may also explain why a greater extent of business travel relates not only positively to career satisfaction but also positively to turnover intentions. Specifically, we argue that because individuals use functional as well as dysfunctional coping when faced with challenges (Carver and Connor-Smith, 2010), business travelers are likely to engage in dysfunctional coping as well. In general, individuals are motivated to prevent resource loss when facing stressors (Hobfoll, 1989). Thus, business travelers are likely to also engage in dysfunctional coping as it may prove beneficial in dealing with travel demands. Specifically, we propose that a greater extent of business travel (vs. a lower extent of business travel or no work-related travel at all) can also increase the use of dysfunctional coping strategies. These strategies may at least in the short-term support employees in counteracting various negative effects of business travel (e.g. absence from home, long-haul flights, jetlag). However, it is likely that an increased use of dysfunctional coping strategies, such as substance use, behavioral disengagement, or humor (i.e. sarcasm), can increase travelers’ turnover intentions. Surprisingly, even though business travel can be demanding and stressful (e.g. Demel and Mayrhofer, 2010; Ivancevich et al., 2003), empirical evidence for dysfunctional coping in relationship with business travel is scarce. One correlational study showed that frequent business travelers (>21 nights per month) were significantly more likely to smoke and to score above clinical thresholds for alcohol dependency than those who only traveled for one to six nights per month (Rundle et al., 2018). We propose that engaging in such and other dysfunctional coping strategies may increase business travelers’ turnover intentions. Although using substances such as alcohol and drugs may seem adaptive to counteract immediate demands associated with traveling (e.g. adapting to a new circadian rhythm or coping with loneliness), they are likely to cause substantial health-related and psychological issues over time, which will make them more likely to search for less demanding jobs.
Another dysfunctional coping strategy is the use of humor. Whereas humor in itself may not be necessarily dysfunctional, it is considered an avoidant coping style when a situation is not taken seriously and its potentially significant implications are completely ignored (Carver, 1997). By using humor in such a maladaptive way, business travelers may become increasingly sarcastic and disengaged from their jobs. Using behavioral disengagement or denial as strategies to cope with traveling for work may also be dysfunctional because both strategies suppress negative emotions and prevent individuals to actively tackle the causes of dissatisfaction and stress associated with traveling for work. Disregarding the existence of demands, even when they are clearly present, does little to facilitate an individual’s adaptation to these demands. Moreover, relying on denial and avoidance as coping mechanisms has been linked to adverse consequences (Carver et al., 1989; Yagil et al., 2011).
By denying the fact that business travel can be demanding and finding ways to cope with these demands, individuals likely become less engaged with and more alienated from their job. Over time, this may increase their intentions to leave their current employer and to look for an alternative job. We thus propose:
The positive association between the extent of business travel and turnover intentions is mediated by (a) substance use, (b) humor, (c) behavioral disengagement, (d) denial/self-blame, and (e) venting/self-distraction.
Method
Study design, participants, and procedure
The data used in this study were collected as part of a larger longitudinal data collection effort and, so far, four other papers based on the same dataset, but with completely different research questions and completely different, non-overlapping substantive variables, have been published (Kleine et al., 2022; Weiss and Zacher, 2022; Zacher and Rudolph, 2022; Zacher and von Hippel, 2022).
We conducted a time-lagged study with a baseline survey (Time [T] 0, July 2018) and 3 subsequent monthly measurement waves (T1 = August 2018, T2 = September 2018, T3 = October 2018). Demographic and employment characteristics (i.e. control variables) were assessed in the baseline survey. Business travel was assessed at T1, coping strategies at T2, and career satisfaction and turnover intentions at T3. Because we were interested in the immediate impact of a business trip on individuals’ coping styles and work outcomes, we used relatively short lags (i.e. four weeks) between two respective measurement waves (Dormann and Griffin, 2015).
We commissioned a professional and ISO 26362 certified panel company to recruit participants from a nationally representative online panel. To be eligible to participate, participants had to be at least 18 years old and be working full-time. Approximately 3,500 employees were initially contacted with a request to participate in the first measurement wave (T1). Of these, n = 1,525 individuals initiated the survey and n = 676 provided complete data regarding our focal measures (final response rate: 19.31%). Participants were compensated by the panel company for their time. According to the demographic characteristics collected at T0, participants’ mean age was 44.12 years (SD = 10.41, range = 21–68) and 42.5% were women. Occupational tenure ranged from a few months to 51 years (M = 15.24, SD = 11.37). Regarding job level, on a scale from 1 (entry level position) to 7 (executive position), the mean score was 4.13 (SD = 1.45). Participants worked across a wide range of industries, with manufacturing (12.6%), public administration (11.7%), and healthcare and social work (10.2%) most often represented. All data and code reported in this paper are available at the Open Science Framework: https://osf.io/j84qe/?view_only=53d27d2ff2144fb6982163d0f879e9fc.
Measures
Business travel. The extent of business travel, ranging from no work-related travel at all to extensive travel, was assessed at T1 using six questions based on previous research, but using multiple items instead of single items (Niessen et al., 2018). Participants were instructed to enter “0” if they did not go on business trips in the last month. First, participants were asked to indicate the total number of business trips in the last month (descriptive statistics for all 676 participants: M = 0.75, SD = 3.27, median = 0, range = 0–45). Second, participants reported the total number of days in the last month spent with business travel (M = 0.76, SD = 0.2.71, median = 0, range = 0–40). Third, participants provided the average number of overnight stays during their business travel in the last month (M = 0.46, SD = 1.49, median = 0, range = 0–20). The fourth, fifth, and sixth questions asked about the number of national (i.e. within Germany; M = 0.66, SD = 3.13, median = 0, range = 0–45), European (M = 0.11, SD = 0.60, median = 0, range = 0–10), and international (i.e. outside of Europe; M = 0.05, SD = 0.35, median = 0, range = 0–4) business trips, respectively.
Given the relatively large number of individuals who reported that they did not travel for work at all (n = 529), all responses greater than “1” for each business travel item among the remaining n = 147 employees can be considered extreme outliers from a statistical perspective. Because it was not an option to exclude these outliers given the focus our study, we decided to set extreme outliers equal to the less extreme value of “1.” Specifically, we winsorized the data by assigning a value of “1” to extreme responses and created a business travel index by averaging the scores across the six dichotomous business travel items. We created this index of business travel because we aimed to assess not just the mere frequency of traveling for work but also its associated demands. For example, traveling overseas and experiencing a long-haul flight and jetlag once a month likely consumes more resources and thus requires different coping strategies than taking multiple national shorter trips. An overall score of “0” on the index accordingly represents no business travel, whereas higher values represent a greater extent of business travel (M = 0.14, SD = 0.28, median = 0, range = 0–1). Winsorizing the data allows for a more accurate representation of the mean and the standard deviation in the data set (Lusk et al., 2011). The reliability of the 6-item index was very good (α = 0.90).
Coping strategies. Ten functional and dysfunctional coping strategies were assessed at T2 using 28 items of the German version of the brief COPE inventory (Knoll et al., 2005). Based on findings of and recommendations based on the validation study (Carver, 1997), four scales were created by combining two closely related facets of the COPE inventory each. Specifically, the four dimensions active coping and planning (“I’ve been concentrating my efforts on doing something about the situation I’m in”; α = 0.91), using emotional and instrumental support (“I’ve been getting emotional support from others”; α = 0.88), venting and self-distraction (“I’ve been turning to work or other activities to take my mind off things”; α = 0.82), and denial and self-blame (“I’ve been criticizing myself”; α = 0.87) were measured with four items each. The other 6 dimensions behavioral disengagement (“I’ve been giving up trying to deal with it”; α = 0.79), positive reframing (“I’ve been looking for something good in what is happening”; α = 0.92), humor (“I’ve been making fun of the situation”; α = 0.82), substance use (“I’ve been using alcohol and drugs to make myself feel better”; α = 0.94), acceptance (“I’ve been learning to live with it”; α = 0.88), and religion (“I’ve been praying or meditating”; α = 0.92) were measured with two items each. The instructions read, “Please indicate to what extent you have shown the following ways of thinking and acting in unpleasant or difficult situations in the work context in the last month.” Responses were provided on a 5-point scale ranging from 1 = never to 5 = all of the time.
Career satisfaction. Career satisfaction was assessed with a single item: “All in all, how satisfied were you with your career in the last month?” Participants provided their responses on a 5-point scale ranging from 1 = very dissatisfied to 5 = very satisfied. Research suggests that single-item measures of work-related satisfaction are reliable and valid (Nagy, 2002; Wanous et al., 1997)
Turnover intentions. Turnover intentions were measured with a 3-item scale (Adams and Beehr, 1998). The items were answered on 5-point response scales ranging from 1 (strongly disagree) to 5 (strongly agree, e.g. “In the last month I often thought of quitting my job and finding another”).
Control variables. We controlled for a number of employee characteristics that have been shown to be associated with business travel, career satisfaction, and turnover intentions, including age (measured in years since birth), sex (1 = male, 2 = female), occupational tenure (in years), job level (1 = entry level, 7 = executive level), partnership status (1 = not married or not in a long-term relationship, 2 = married or in a long-term relationship), and number of children living in the household, which were assessed in the baseline survey (T0).
Results
Descriptive statistics and correlations among the study variables are shown in Table 1. A number of interesting bivariate associations emerged between business travel at T1 and the other variables. For instance, older employees, women, and employees with longer tenure reported a lower extent of business travel, whereas employees with a higher job level and a higher number of children living in the household reported more business travel. Furthermore, business travel was positively associated with all coping strategies at T2, except for acceptance. Finally, providing preliminary support for Hypotheses 1 and 2, business travel was positively related to both career satisfaction and turnover intentions at T3 (see Table 1).
Confirmatory factor analysis
To examine the quality of our measurement model, we compared the results of three confirmatory factor analyses using the items from the multi-item scales included in the study (i.e. business travel, 10 coping strategies, turnover intentions, but not the single career satisfaction item). The first 12-factor model, in which all items were specified to load on their designated latent factors, had an acceptable fit to the data given the relatively high number of 2-item coping factors (χ2[df = 563] = 1180.28, p < 0.001; comparative fit index [CFI] = 0.89; root mean square error of approximation [RMSEA] = 0.04). In contrast, a 3-factor model in which all coping items were specified to load on a single factor, had a significantly worse fit (χ2[df = 626] = 2435.78, p < 0.001; CFI = 0.67; RMSEA = 0.07; Δχ2[Δdf = 63] = 1255.50, p < 0.001). Finally, a single-factor model also had a worse fit to the data than the initial model (χ2[df = 631] = 11091.25, p < 0.001; CFI = 0.00; RMSEA = 0.16; Δχ2[Δdf = 68] = 9910.97, p < 0.001). These findings suggest that participants distinguished between the different measures employed.
Hypotheses testing
Table 2 shows the results of multiple regression analyses used to test the hypotheses. According to Hypothesis 1, the extent of business travel at T1 is positively related to career satisfaction at T3. As shown in Table 2, business travel (T1) positively predicted career satisfaction (T3) after accounting for the control variables (β = 0.12, p < 0.01), therefore Hypothesis 1 was supported. In an additional, exploratory analysis, we added a squared business travel term to the regression equation. The squared term did not significantly explain incremental variance in career satisfaction (ΔR2 = 0.004, p = 0.085), suggesting that the effect of business travel on career satisfaction is linear.
Hypothesis 2 was also supported by a positive effect of business travel (T1) on turnover intentions at T3 (β = 0.12, p < 0.01). Again, a squared business travel term did not significantly explain incremental variance in turnover intentions (ΔR2 = 0.004, p = 0.094), suggesting that the effect of business travel on turnover intentions is also linear. Table 2 further shows that, after accounting for the control variables, business travel (T1) predicted all of the coping strategies at T2 except for acceptance, with estimates ranging from β = 0.08 (p < 0.01) for using emotional and instrumental support and behavioral disengagement to β = 0.16 (p < 0.01) for venting and self-distraction. Overall, these findings suggest that employees who engage in business travel to a greater extent generally use more functional and dysfunctional coping strategies than less extensive or non-business travelers.
According to Hypotheses 3a-e and 4a-e, functional and dysfunctional coping strategies mediate the effects of business travel on career satisfaction and turnover intentions, respectively. Table 3 shows the effects of all coping strategies at T2 on career satisfaction and turnover intentions at T3, after accounting for the control variables and business travel. Career satisfaction at T3 was positively predicted by using emotional and instrumental support at T2 (β = 0.18, p < 0.01) and positive reframing (β = 0.14, p < 0.01). Contrary to expectations, career satisfaction at T3 was also positively predicted by substance use at T2 (β = 0.11, p < 0.05), and negatively predicted by venting and self-distraction (β = −0.13, p < 0.05), denial and self-blame (β = −0.18, p < 0.01), and behavioral disengagement (β = −0.17, p < 0.01), all at T2. We found no significant relationships between active coping/planning, humor, acceptance, and religion at T2 and career satisfaction at T3.
Turnover intentions at T3 were positively predicted by active coping and planning (β = 0.12, p < 0.05), venting and self-distraction (β = 0.13, p < 0.05), behavioral disengagement (β = 0.29, p < 0.01), and negatively predicted by positive reframing (β = −0.15, p < 0.01), all at T2. We found no significant relationships between using emotional/instrumental support, denial/self-blame, humor, substance use, acceptance, and religion at T2 and turnover intentions at T3.
Table 4 shows the results of indirect effect analyses using bootstrapped confidence intervals (95%). The findings suggest that business travel at T1 had positive indirect effects on career satisfaction at T3 via using emotional and instrumental support, positive reframing, and substance use, and a negative indirect effect via denial and self-blame at T2. Furthermore, business travel at T1 had positive indirect effects on turnover intentions at T3 via active coping and planning, venting and self-distraction, and behavioral disengagement, and a negative indirect effect via positive reframing at T2 (see Figure 1 for a summary of findings). Overall, these findings support Hypotheses 3b and 3c as well as Hypotheses 4c and 4e.
Supplemental analyses
Given the relatively large number of non-business travelers in our employee sample (n = 529), we re-ran all analyses with the subset of n = 147 participants who reported at least one business trip over the course of the study. The extent of business travel was not significantly associated career satisfaction and turnover intentions above and beyond the control variables in these analyses. However, business travel also positively and significantly predicted the various coping strategies (with estimates ranging from β = 0.19, p < 0.05, for behavioral disengagement to β = 0.30, p < 0.01, for positive reframing and denial and self-blame), except for humor, substance use, and acceptance. Using emotional and instrumental support (β = 0.34, p < 0.05) positively, and denial and self-blame (β = −0.40, p < 0.01) negatively, predicted career satisfaction in this subsample. Moreover, using emotional and instrumental support (β = 0.39, p < 0.01) negatively, and venting and self-distraction (β = 0.37, p < 0.01) and denial and self-blame (β = 0.39, p < 0.01) positively, predicted turnover intentions in this subsample. Consistently, mediation analyses showed that the extent of business travel had a positive indirect effect on career satisfaction via using emotional and instrumental support (B = 0.36, 95% CI [0.02, 0.84]), and a negative indirect effect via denial and self-blame (B = −0.58, 95% CI [−1.19, −0.12]). Finally, business travel had positive indirect effects on turnover intentions via venting and self-distraction (B = 0.51, 95% CI [0.04, 1.16]) and via denial and self-blame (B = 0.75, 95% CI [0.20, 1.46]) in this subsample.
Discussion
The goal of this research was to examine why a greater extent of business travel may be related to both higher career satisfaction and turnover intentions. We examined functional and dysfunctional coping strategies as mediators of these countervailing effects using a time-lagged study with four measurement waves and a large and heterogeneous employee sample including both business travelers and non-travelers. Consistent with our hypotheses, we found that the greater the extent of business travel, the higher both career satisfaction and turnover intentions. In contrast, support for our hypotheses on the mediating role of coping strategies was mixed. Both functional and dysfunctional coping strategies mediated the association between business travel and career satisfaction and turnover intentions, respectively. The positive association between business travel and career satisfaction was mediated by higher levels of using emotional and instrumental support, positive reframing, and lower levels of venting and self-distraction, denial and self-blame, and behavioral disengagement. An unexpected finding was that the relationship between business travel and career satisfaction was mediated by more substance use. In addition, and also contrary to expectations, the association between business travel and career satisfaction was not significantly mediated by the functional coping strategies of active coping and planning, and surprisingly, the positive association between business travel and turnover intentions was mediated by higher active coping and planning, venting and self-distraction, behavioral disengagement, and lower positive reframing. This suggests that frequent business travelers may be more likely to actively seek a “way out” of a demanding work role or are more likely to receive alternative job offers as we will discuss further below. Additional analyses revealed that the pattern of relationships slightly differed in the subsample of those individuals who indicated that they had traveled recently (i.e. in the past month). Findings revealed indirect relationships between business travel and higher career satisfaction via functional coping (i.e. using emotional and instrumental support) and between business travel and higher turnover intentions via dysfunctional coping (i.e. venting, self-distraction, denial, and self-blame).
Theoretical and practical implications
Our findings confirm prior theorizing on business travel as a dualistic experience with positive and negative outcomes for occupational well-being (Dimitrova, 2020; Niessen et al., 2018). However, we also broaden this line of research in two important ways: First, we simultaneously consider positive and negative effects of business travel on key indicators of occupational well-being (turnover intentions, career satisfaction). From a COR perspective, business travel can thus similarly lead to the acquisition and loss of mental, physical, or social resources and this is evidenced in both higher career satisfaction and turnover intentions.
Second, our findings highlight how functional and dysfunctional coping styles can explain these opposing effects of business travel. Thus far, scholars have only examined select coping strategies but not a comprehensive set of functional and dysfunctional strategies in the context of business travel. In line with the commonly proposed theoretical differentiation of active-functional and dysfunctional coping Carver and Connor-Smith (2010), our findings suggest that business travelers use a coping portfolio consisting of a variety of functional and dysfunctional coping strategies ranging from positive reframing, self-distraction, active coping, humor, denial, religion, to garnering social support and engaging in substance use. In combination, these coping strategies exert differential effects on business travelers’ occupational well-being (career satisfaction and turnover intentions). When looking at their combined effects and when controlling for important demographic variables, functional and dysfunctional coping more frequently relate to individuals’ career satisfaction (6 significant pathways) than to their turnover intentions (4 significant pathways). Thus, the various coping styles that individuals have at their disposal are one reason why traveling for work relates to higher career satisfaction. As trip frequency and intensity increases, business travelers may nevertheless be more inclined to quit their jobs and this is because they are more likely to engage in dysfunctional coping such as venting and disengagement.
However, because we found an association between two functional coping strategies and turnover intentions, namely active planning and coping, it is also possible that higher turnover intentions may not necessarily reflect lowered occupational well-being but instead having alternative career options that are more attractive than one’s current job. Research has shown that having desirable job alternatives promotes voluntary turnover (Swider et al., 2011). Traveling for work may provide individuals with a broader array of alternative career opportunities and job offers, for example, through access to broad business networks and face-to-face contacts with clients (Demel and Mayrhofer, 2010). Business travelers may thus actively plan to search for alternative employment or to consider alternative job offers if their current job does not align with their career goals.
As such, our work also has implications for the coping literature (Carver and Connor-Smith, 2010). This literature typically defines coping styles in distinct functional or dysfunctional terms (Biggs et al., 2017). In line with this theorizing, our results confirm that most functional strategies are related to higher career satisfaction as a positive outcome and that most of the investigated dysfunctional coping styles were associated with higher intentions to quit as a negative outcome. At the same time, and counter to the common distinction of functional and dysfunctional coping, we found that both functional and dysfunctional coping mediated the effect between business travel and the two negatively correlated outcomes. This suggests that coping styles that are commonly denoted as dysfunctional may nevertheless prove functional in achieving a desired outcome and vice versa. Thus, the positive relationship between dysfunctional coping strategies and positive outcomes, especially the link between substance use and higher career satisfaction warrants discussion. Research has shown that, in moderation, drinking alcohol has been shown to reduce work stress and improve mental health (Marchand et al., 2003). Another possibility is that business travel may be related to a higher availability of alcohol, for example, alcohol may be provided at business lunches, dinners, events, other work functions that take place during a business trip. Previous research has shown that contextual drinking norms can affect the acceptance of drinking alcohol among employees (Klotz and da Motta Veiga, 2018) and as such, business travel may be a context, in which individuals are more likely to consider drinking alcohol as appropriate.
However, it is noteworthy that our data only covered a few months in which business travelers’ coping mechanisms were investigated and, thus, it is not clear how dysfunctional coping (i.e. especially substance use) may affect individuals in the long run. Overall, however, our findings imply that functional and dysfunctional coping do not automatically relate to positive and negative effects, respectively, but that individuals use a portfolio of coping strategies to cope with business travel (Becker et al., 2022).
Regarding practical implications, organizations should design interventions that enhance functional coping with business travel, and monitor the extent to which employees use dysfunctional strategies. Research has found that organizational and individual travel stress interventions may support travelers in coping with travel-related stressors (DeFrank et al., 2000). For example, organizational interventions may include training sessions in which employees who are about to travel receive relevant information associated with the trip (e.g. vaccinations needed, what to wear, accommodations, and cultural customs). Moreover, organizations should evaluate and potentially re-design time schedules for frequent travelers to allot sufficient time for after-travel recovery (e.g. due to jet lag and time differences). Frequent breaks in between assigned tasks and meetings during the trip as well on-site sports and recreation opportunities can also aid employees in engaging in functional instead of dysfunctional coping. Importantly, organizations should provide as much support as possible to minimize travel demands and promote travelers’ adjustment (e.g. planning and organizing flights, hotels, and providing on-site assistance). Moreover, in times of virtual communication technology, organizations should also assess whether and when a business trip is necessary.
Travelers themselves can also use certain strategies that support them in active-functional coping (De Frank et al., 2000). For example, business travelers can alleviate the impact of jetlag by consuming enough fluids, eating a healthy diet, and avoiding alcohol. This also includes a mindful consumption of alcoholic drinks in the context of business-related meetings. Exercising regularly before and during the trip can also promote better adjustment to long distance traveling and promote post-travel recovery.
Limitations and future research
Despite the strengths of this research that include a large and heterogenous sample of employees and a multi-wave design across several months, there are some limitations. First, all constructs were assessed using self-report questionnaires, which may raise concerns about self-report bias and common method variance. Following current recommendations to control common method variance, we have used time-lagged assessments to separate our predictor and outcome measures and different scale formats to assess them (Podsakoff et al., 2003). Nevertheless, future research should also collect objective measures (e.g. career performance indicators) and/or second sources (e.g. coworker or supervisor assessments). Other alternative study designs include diary studies during business trips as well experimental studies where different trip scenarios and possible coping strategies can be manipulated.
A second concern may be related to the construct validity of a single-item career satisfaction measure. Similar to one-item job satisfaction measures, single item assessments of career satisfaction are common (Verbruggen and Van Emmerik, 2020) and the moderate negative correlations with turnover intentions further validate this measure in our sample. Multi-item measures may provide more insight into specific career-related aspects (e.g. promotion opportunities, salary, skill enhancement) that could potentially relate differently to business travel.
Third, despite using a time-lagged design, we did not include baseline measures of our focal constructs, and thus, are unable to investigate potential change in these measures over time. However, it is unlikely that the use of coping strategies and the two outcomes change much across one or two months, so we focus on interindividual variability, not on within-person change in this study. We encourage the use of longitudinal studies with longer lags to separate within-from between-person variability across time. This would also provide more insight into possible individual difference in adopting functional and dysfunctional coping strategies.
Fourth, it remains noteworthy that we had to winsorize our data to account for the highly skewed distribution of business travel. This approach is superior to using a single item assessment as it allows for including a broad sample of business travelers as well employees who do not travel for work.
Fifth, even though we included control variables (e.g. age, sex, tenure, number of children) that have previously been denoted as relevant in the context of business travel, future research should examine additional individual characteristics, such as personality, work- and trip-related attitudes as well as contextual factors, such as specific family demands and resources which may enact additional influence on the relationship between business travel, coping, and occupational well-being. Also, although career satisfaction and turnover intentions are rather representative for positive and negative well-being outcomes in the work context, future research could explore additional outcomes, such as job engagement and work performance (potentially assessed through second sources). Relatedly, future research may explore if business travel has different implications across different industries. Although our sample included employees from different industries (e.g. public administration, manufacturing, healthcare), future research may the effects of business travel on occupational well-being by looking at specific types of organizations and industries in which traveling for work may be particularly common and demanding (e.g. consulting).
Conclusion
Business travel is an important work-related experience, but the psychological pathways through which it affects both positive and negative work outcomes have not yet received much attention. Results based on four waves of monthly data collected from 676 employees showed that the extent of business travel predicted both higher career satisfaction and turnover intentions. Further, both functional (e.g. active coping, social support) and dysfunctional coping (e.g. substance use, denial) strategies can explain the occupational well-being consequences of business travel. Our findings provide new insights into the work-related and psychological implications of business travel.
Figures
Figure 1
Indirect effects of time 1 business travel on time 3 career satisfaction and turnover intentions through time 2 coping strategies
Descriptive statistics and correlations
| Variables | M | SD | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Time 0 (Baseline) Variables | |||||||||||||||||||||
| 1. Age | 44.12 | 10.41 | – | ||||||||||||||||||
| 2. Sexa | 1.42 | 0.49 | −0.01 | – | |||||||||||||||||
| 3. Occupational tenure | 15.24 | 11.37 | 0.61** | −0.01 | – | ||||||||||||||||
| 4. Job level | 4.13 | 1.45 | 0.20** | −0.05 | 0.19** | – | |||||||||||||||
| 5. Partnershipb | 1.62 | 0.49 | 0.04 | −0.08* | 0.04 | 0.08* | – | ||||||||||||||
| 6. Children | 0.57 | 0.86 | −0.07 | −0.10** | −0.06 | 0.11** | 0.30** | – | |||||||||||||
| Time 1 Variable (Predictor) | |||||||||||||||||||||
| 7. Business travel | 0.14 | 0.28 | −0.14** | −0.09* | −0.13** | 0.18** | 0.03 | 0.12** | (0.90) | ||||||||||||
| Time 2 Variables (Mediators) | |||||||||||||||||||||
| 8. Active coping/planning | 2.63 | 1.07 | −0.07 | 0.04 | −0.06 | 0.09* | 0.01 | 0.06 | 0.15** | (0.91) | |||||||||||
| 9. Using emotional/instrumental support | 2.28 | 0.96 | −0.20** | 0.10** | −0.10* | −0.01 | 0.08 | 0.12** | 0.11** | 0.69** | (0.88) | ||||||||||
| 10. Venting/self-distraction | 2.13 | 0.84 | −0.22** | 0.04 | −0.12** | −0.01 | 0.04 | 0.13** | 0.19** | 0.58** | 0.65** | (0.82) | |||||||||
| 11. Denial/self-blame | 1.87 | 0.88 | −0.22** | 0.01 | −0.11** | −0.03 | 0.07 | 0.08* | 0.17** | 0.50** | 0.58** | 0.70** | (0.87) | ||||||||
| 12. Behavioral disengagement | 2.00 | 1.02 | −0.11** | 0.03 | −0.02 | −0.04 | −0.03 | 0.06 | 0.09* | 0.34** | 0.38** | 0.55** | 0.60** | (0.79) | |||||||
| 13. Positive reframing | 2.76 | 1.22 | 0.00 | 0.04 | 0.00 | 0.01 | 0.03 | −0.01 | 0.12** | 0.67** | 0.58** | 0.42** | 0.35** | 0.27** | (0.92) | ||||||
| 14. Humor | 2.44 | 1.10 | −0.11** | −0.05 | −0.04 | 0.00 | 0.04 | 0.05 | 0.15** | 0.53** | 0.47** | 0.41** | 0.38** | 0.32** | 0.55** | (0.82) | |||||
| 15. Substance use | 1.48 | 0.88 | −0.26** | −0.06 | −0.14** | −0.02 | 0.02 | 0.13** | 0.14** | 0.23** | 0.38** | 0.50** | 0.59** | 0.46** | 0.17** | 0.25** | (0.94) | ||||
| 16. Acceptance | 2.46 | 1.15 | −0.03 | 0.01 | 0.03 | −0.02 | 0.05 | 0.03 | 0.05 | 0.50** | 0.41** | 0.46** | 0.46** | 0.50** | 0.46** | 0.44** | 0.27** | (0.88) | |||
| 17. Religion | 1.65 | 1.04 | −0.14** | −0.02 | −0.09* | −0.04 | 0.03 | 0.15** | 0.17** | 0.31** | 0.44** | 0.45** | 0.53** | 0.36** | 0.28** | 0.30** | 0.48** | 0.25** | (0.92) | ||
| Time 3 Variables (Outcomes) | |||||||||||||||||||||
| 18. Career satisfaction | 3.32 | 1.01 | 0.15** | 0.07 | 0.09* | 0.19** | 0.06 | 0.03 | 0.12** | 0.06 | 0.08* | −0.09* | −0.13** | −0.17** | 0.14** | 0.04 | −0.04 | −0.04 | 0.01 | – | |
| 19. Turnover intentions | 1.94 | 1.19 | −0.30** | −0.01 | −0.21** | −0.09* | −0.06 | 0.02 | 0.14** | 0.19** | 0.21** | 0.36** | 0.37** | 0.41** | 0.04 | 0.12** | 0.33** | 0.19** | 0.22** | −0.42** | (0.94) |
Note(s): N = 676. aSex (1 = male, 2 = female), bPartnership (1 = not married or in a long-term relationship, 2 = married or in a long-term relationship). *p < 0.05, **p < 0.01
Source(s): Created by authors
Results of regression analyses predicting time 3 career satisfaction and turnover intentions and time 2 coping strategies
| Predictors | B | SE | β | B | SE | β | B | SE | β | B | SE | β | B | SE | β | B | SE | β |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| T3 Career satisfaction | T3 Turnover intentions | T2 Active coping/planning | T2 Using emotional/instrumental support | T2 Venting/self-distraction | T2 Denial/self-blame | |||||||||||||
| Intercept | 1.85 | 0.26 | 3.57 | 0.30 | 2.42 | 0.28 | 2.44 | 0.24 | 2.55 | 0.21 | 2.41 | 0.22 | ||||||
| T0 Age | 0.01 | 0.01 | 0.14** | −0.03 | 0.01 | −0.25** | −0.01 | 0.01 | −0.06 | −0.02 | 0.00 | −0.22** | −0.02 | 0.00 | −0.22** | −0.02 | 0.00 | −0.23** |
| T0 Sexa | 0.18 | 0.08 | 0.09* | −0.02 | 0.09 | −0.01 | 0.13 | 0.08 | 0.06 | 0.24 | 0.07 | 0.12** | 0.12 | 0.06 | 0.07 | 0.05 | 0.07 | 0.03 |
| T0 Occ. tenure | −0.00 | 0.00 | −0.01 | −0.00 | 0.01 | −0.03 | −0.00 | 0.01 | −0.02 | 0.00 | 0.00 | 0.05 | 0.00 | 0.00 | 0.05 | 0.01 | 0.00 | 0.06 |
| T0 Job level | 0.10 | 0.03 | 0.14** | −0.05 | 0.03 | −0.06 | 0.06 | 0.03 | 0.08* | 0.00 | 0.03 | 0.01 | −0.01 | 0.02 | −0.01 | −0.02 | 0.02 | −0.03 |
| T0 Partnership | 0.10 | 0.08 | 0.05 | −0.12 | 0.10 | −0.05 | −0.02 | 0.09 | −0.01 | 0.13 | 0.08 | 0.06 | 0.04 | 0.07 | 0.02 | 0.11 | 0.07 | 0.06 |
| T0 Children | 0.01 | 0.05 | 0.01 | 0.01 | 0.05 | 0.01 | 0.04 | 0.05 | 0.04 | 0.10 | 0.04 | 0.09* | 0.10 | 0.04 | 0.10 | 0.04 | 0.04 | 0.04 |
| T1 Business travel | 0.45 | 0.14 | 0.12** | 0.50 | 0.16 | 0.12** | 0.50 | 0.15 | 0.13** | 0.29 | 0.13 | 0.08* | 0.48 | 0.12 | 0.16** | 0.48 | 0.12 | 0.15** |
| R2 | 0.07 | 0.11 | 0.04 | 0.08 | 0.09 | 0.08 | ||||||||||||
| F | 7.26** | 11.21** | 3.69** | 7.74** | 9.62** | 8.23** | ||||||||||||
| T2 Behavioral disengagement | T2 Positive reframing | T2 Humor | T2 Substance use | T2 Acceptance | T2 Religion | |||||||||||||
| Intercept | 2.58 | 0.27 | 2.35 | 0.32 | 2.90 | 0.29 | 2.43 | 0.22 | 2.46 | 0.30 | 2.11 | 0.27 | ||||||
| T0 Age | −0.01 | 0.01 | −0.15** | 0.00 | 0.01 | 0.01 | −0.01 | 0.01 | −0.12* | −0.02 | 0.00 | −0.26** | −0.01 | 0.01 | −0.07 | −0.01 | 0.01 | −0.10* |
| T0 Sexa | 0.08 | 0.08 | 0.04 | 0.13 | 0.10 | 0.05 | −0.08 | 0.09 | −0.04 | −0.08 | 0.07 | −0.05 | 0.05 | 0.09 | 0.02 | 0.01 | 0.08 | 0.01 |
| T0 Occ. tenure | 0.01 | 0.00 | 0.10 | 0.00 | 0.01 | 0.01 | 0.01 | 0.01 | 0.05 | 0.00 | 0.00 | 0.03 | 0.01 | 0.01 | 0.09 | 0.00 | 0.00 | 0.01 |
| T0 Job level | −0.03 | 0.03 | −0.05 | −0.01 | 0.03 | −0.02 | −0.01 | 0.03 | −0.02 | 0.00 | 0.02 | 0.01 | −0.03 | 0.03 | −0.03 | −0.05 | 0.03 | −0.06 |
| T0 Partnership | −0.09 | 0.09 | −0.05 | 0.09 | 0.03 | 0.07 | 0.09 | 0.03 | −0.01 | 0.07 | −0.01 | 0.12 | 0.10 | 0.05 | −0.02 | 0.09 | −0.01 | |
| T0 Children | 0.08 | 0.05 | 0.07 | −0.04 | −0.03 | 0.02 | 0.05 | 0.02 | 0.11 | 0.04 | 0.10** | 0.01 | 0.06 | 0.01 | 0.16 | 0.05 | 0.13** | |
| T1 Business travel | 0.31 | 0.15 | 0.08* | 0.60 | 0.17 | 0.14** | 0.55 | 0.16 | 0.14** | 0.29 | 0.12 | 0.09* | 0.25 | 0.17 | 0.06 | 0.57 | 0.15 | 0.15** |
| R2 | 0.03 | 0.02 | 0.04 | 0.09 | 0.01 | 0.06 | ||||||||||||
| F | 3.05** | 1.96 | 3.52** | 9.65** | 1.11 | 6.03** | ||||||||||||
Note(s): N = 676. T = Time. Occ. = Occupational. aSex (1 = male, 2 = female), bPartnership status (1 = not married or in a long-term relationship, 2 = married or in a long-term relationship). *p < 0.05, **p < 0.01
Source(s): Created by authors
Results of regression analyses predicting time 3 career satisfaction and turnover intentions
| T3 career satisfaction | T3 turnover intentions | |||||
|---|---|---|---|---|---|---|
| Predictors | B | SE | β | B | SE | β |
| Intercept | 1.98 | 0.28 | 2.15 | 0.31 | ||
| T0 Age | 0.01 | 0.01 | 0.12* | −0.02 | 0.01 | −0.15** |
| T0 Sexa | 0.18 | 0.08 | 0.09* | −0.05 | 0.08 | −0.02 |
| T0 Occupational tenure | 0.00 | 0.00 | 0.01 | −0.01 | 0.00 | −0.06 |
| T0 Job level | 0.09 | 0.03 | 0.13** | −0.04 | 0.03 | −0.05 |
| T0 Partnership | 0.08 | 0.08 | 0.04 | −0.0.07 | 0.09 | −0.03 |
| T0 Children | 0.01 | 0.05 | 0.01 | −0.05 | 0.05 | −0.04 |
| T1 Business travel | 0.48 | 0.14 | 0.13** | 0.31 | 0.15 | 0.07* |
| T2 Active coping/planning | −0.02 | 0.06 | −0.02 | 0.13 | 0.06 | 0.12* |
| T2 Using emotional/instrumental support | 0.19 | 0.06 | 0.18** | −0.06 | 0.07 | −0.05 |
| T2 Venting/self-distraction | −0.15 | 0.07 | −0.13* | 0.18 | 0.08 | 0.13* |
| T2 Denial/self-blame | −0.20 | 0.07 | −0.18** | 0.08 | 0.08 | 0.06 |
| T2 Behavioral disengagement | −0.17 | 0.05 | −0.17** | 0.34 | 0.05 | 0.29** |
| T2 Positive reframing | 0.12 | 0.04 | 0.14** | −0.15 | 0.05 | −0.15** |
| T2 Humor | 0.02 | 0.04 | 0.02 | −0.05 | 0.05 | −0.04 |
| T2 Substance use | 0.13 | 0.06 | 0.11* | 0.10 | 0.06 | 0.07 |
| T2 Acceptance | 0.00 | 0.04 | 0.00 | −0.02 | 0.05 | −0.02 |
| T2 Religion | 0.04 | 0.04 | 0.05 | 0.01 | 0.05 | 0.00 |
| R2 | 0.16 | 0.29 | ||||
| F | 7.38** | 15.48** | ||||
Note(s): N = 676. aSex (1 = male, 2 = female), bPartnership status (1 = not married or in a long-term relationship, 2 = married or in a long-term relationship)
*p < 0.05, **p < 0.01
Source(s): Created by authors
Indirect effects of time 1 business travel on time 3 career satisfaction and turnover intentions through time 2 coping strategies
| T3 career satisfaction | T3 turnover intentions | |||||||
|---|---|---|---|---|---|---|---|---|
| Mediator | B | SE | LLCI | ULCI | B | SE | LLCI | ULCI |
| T2 Active coping/planning | −0.01 | 0.03 | −0.08 | 0.05 | 0.07 | 0.04 | 0.00 | 0.15 |
| T2 Using emotional/instrumental support | 0.05 | 0.03 | 0.00 | 0.13 | −0.02 | 0.02 | −0.07 | 0.02 |
| T2 Venting/self-distraction | −0.07 | 0.04 | −0.16 | 0.00 | 0.09 | 0.04 | 0.01 | 0.18 |
| T2 Denial/self-blame | −0.10 | 0.05 | −0.21 | −0.02 | 0.04 | 0.05 | −0.04 | 0.14 |
| T2 Behavioral disengagement | −0.05 | 0.03 | −0.12 | 0.00 | 0.11 | 0.05 | 0.00 | 0.22 |
| T2 Positive reframing | 0.07 | 0.04 | 0.01 | 0.15 | −0.09 | 0.04 | −0.18 | −0.02 |
| T2 Humor | 0.01 | 0.03 | −0.04 | 0.06 | −0.03 | 0.03 | −0.08 | 0.03 |
| T2 Substance use | 0.04 | 0.02 | 0.00 | 0.09 | 0.03 | 0.02 | −0.01 | 0.09 |
| T2 Acceptance | 0.00 | 0.01 | −0.03 | 0.03 | −0.01 | 0.01 | −0.04 | 0.02 |
| T2 Religion | 0.02 | 0.03 | −0.03 | 0.09 | 0.00 | 0.03 | −0.06 | 0.07 |
Note(s): T = time. Standard errors (SE), lower level 95% confidence intervals (LLCI), and upper level 95% confidence intervals (ULCI) are based on 5,000 bootstraps
Source(s): Created by authors
Conflict of interest: The authors declare that they have no conflict of interest.
References
Adams, G.A. and Beehr, T.A. (1998), “Turnover and retirement: a comparison of their similarities and differences”, Personnel Psychology, Vol. 51 No. 3, pp. 643-665, doi: 10.1111/j.1744-6570.1998.tb00255.x.
Akirmak, U. and Ayla, P. (2021), “How is time perspective related to burnout and job satisfaction? A conservation of resources perspective”, Personality and Individual Differences, Vol. 181, 109667, doi: 10.1016/j.paid.2019.109667.
Allen, D.G., Weeks, K.P. and Moffitt, K.R. (2005), “Turnover intentions and voluntary turnover: the moderating roles of self-monitoring, locus of control, proactive personality, and risk aversion”, Journal of Applied Psychology, Vol. 90 No. 5, pp. 980-990, doi: 10.1037/0021-9010.90.5.980.
Bakker, A.B. and Xanthopoulou, D. (2009), “The crossover of daily work engagement: test of an actor–partner interdependence model”, Journal of Applied Psychology, Vol. 94 No. 6, pp. 1562-1571, doi: 10.1037/a0017525.
Becker, J., Derra, N.D., Regal, C. and Kühlmann, T.M. (2022), “Mitigating the negative consequences of ICT use: the moderating effect of active-functional and dysfunctional coping”, Journal of Decision Systems, Vol. 31 No. 4, pp. 374-406, doi: 10.1080/12460125.2021.1901337.
Biggs, A., Brough, P. and Drummong, S. (2017), “Lazarus and Folkman’s psychological stress and coping theory”, in Cooper, C.L. and Quick, J.C. (Eds), The Handbook of Stress and Health: A Guide to Research and Practice, Wiley, Chichester, pp. 349-364.
Carver, C.S. (1997), “You want to measure coping but your protocol’ too long: consider the brief cope”, International Journal of Behavioral Medicine, Vol. 4 No. 1, pp. 92-100, doi: 10.1207/s15327558ijbm0401_6.
Carver, C.S. and Connor-Smith, J. (2010), “Personality and coping”, Annual Review of Psychology, Vol. 61 No. 1, pp. 679-704, doi: 10.1146/annurev.psych.093008.100352.
Carver, C.S. (2007), “Stress, coping, and health”, in Friedman, H.S. and Silver, R.C. (Eds), Foundations of Health Psychology, Oxford University Press, pp. 117-144.
Carver, C.S., Scheier, M.F. and Weintraub, J.K. (1989), “Assessing coping strategies: a theoretically based approach”, Journal of Personality and Social Psychology, Vol. 56 No. 2, pp. 267-283, doi: 10.1037/0022-3514.56.2.267.
Chan, S.H.J. and Mai, X. (2015), “The relation of career adaptability to satisfaction and turnover intentions”, Journal of Vocational Behavior, Vol. 89, pp. 130-139, doi: 10.1016/j.jvb.2015.05.005.
Cho, Y.J. and Lewis, G.B. (2012), “Turnover intention and turnover behavior implications for retaining federal employees”, Review of Public Personnel Administration, Vol. 32 No. 1, pp. 4-23, doi: 10.1177/0734371x11408701.
DeFrank, R.S., Konopaske, R. and Ivancevich, J.M. (2000), “Executive travel stress: perils of the road warrior”, Academy of Management Perspectives, Vol. 14 No. 2, pp. 58-71, doi: 10.5465/ame.2000.3819306.
Demel, B. and Mayrhofer, W. (2010), “Frequent business travelers across Europe: career aspirations and implications”, Thunderbird International Business Review, Vol. 52 No. 4, pp. 301-311, doi: 10.1002/tie.20352.
Dimitrova, M. (2020), “Of discovery and dread: the importance of work challenges for international business travelers' thriving and global role turnover intentions”, Journal of Organizational Behavior, Vol. 41 No. 4, pp. 369-383, doi: 10.1002/job.2430.
Dimitrova, M., Chia, S.I., Shaffer, M.A. and Tay-Lee, C. (2020), “Forgotten travelers: adjustment and career implications of international business travel for expatriates”, Journal of International Management, Vol. 26 No. 1, 100707, doi: 10.1016/j.intman.2019.100707.
Dormann, C. and Griffin, M.A. (2015), “Optimal time lags in panel studies”, Psychological Methods, Vol. 20 No. 4, pp. 489-505, doi: 10.1037/met0000041.
Eden, D. (2001), “Job stress and respite relief: overcoming high-tech tethers”, Exploring Theoretical Mechanisms and Perspectives, Vol. 1, pp. 143-194, doi: 10.1016/S1479-3555(01)01012-5.
Espino, C.M., Sundstrom, S.M., Frick, H.L., Jacobs, M. and Peters, M. (2002), “International business travel: impact on families and travellers”, Occupational and Environmental Medicine, Vol. 59 No. 5, pp. 309-322, doi: 10.1136/oem.59.5.309.
Folkman, S., Lazarus, R.S., Gruen, R.J. and DeLongis, A. (1986), “Appraisal, coping, health status, and psychological symptoms”, Journal of Personality and Social Psychology, Vol. 50 No. 3, pp. 571-579.
Griffeth, R.W., Hom, P.W. and Gaertner, S. (2000), “A meta-analysis of antecedents and corre- lates of employee turnover: update, moderator tests, and research implications for the next millennium”, Journal of Management, Vol. 26 No. 3, pp. 463-488, doi: 10.1177/014920630002600305.
Gustafson, P. (2014), “Business travel from the traveller's perspective: stress, stimulation and normalization”, Mobilities, Vol. 9 No. 1, pp. 63-83, doi: 10.1080/17450101.2013.784539.
Halbesleben, J.R., Neveu, J.P., Paustian-Underdahl, S.C. and Westman, M. (2014), “Getting to the “COR” understanding the role of resources in conservation of resources theory”, Journal of Management, Vol. 40 No. 5, pp. 1334-1364, doi: 10.1177/0149206314527130.
Hobfoll, S.E. (1989), “Conservation of resources: a new attempt at conceptualizing stress”, American Psychologist, Vol. 44 No. 3, pp. 513-524, doi: 10.1037//0003-066x.44.3.513.
Hobfoll, S.E. (2002), “Social and psychological resources and adaptation”, Review of General Psychology, Vol. 6 No. 4, pp. 307-324, doi: 10.1037/1089-2680.6.4.307.
Hobfoll, S.E., Halbesleben, J., Neveu, J.P. and Westman, M. (2018), “Conservation of resources in the organizational context: the reality of resources and their consequences”, Annual Review of Organizational Psychology and Organizational Behavior, Vol. 5 No. 1, pp. 103-128, doi: 10.1146/annurev-orgpsych-032117-104640.
Ivancevich, J.M., Konopaske, R. and Defrank, R.S. (2003), “Business travel stress: a model, propositions and managerial implications”, Work and Stress, Vol. 17 No. 2, pp. 138-157, doi: 10.1080/0267837031000153572.
Jex, S.M., Bliese, P.D., Buzzell, S. and Primeau, J. (2001), “The impact of self-efficacy on stressor–strain relations: coping style as an explanatory mechanism”, Journal of Applied Psychology, Vol. 86 No. 3, pp. 401-409, doi: 10.1037/0021-9010.86.3.401.
Kleine, A.-K., Rudolph, C.W., Schmitt, A. and Zacher, H. (2022), “Thriving at work: An investigation of the independent and joint effects of vitality and learning on employee health”, European Journal of Work and Organizational Psychology, Vol. 32 No. 1, pp. 95-106.
Klotz, A.C. and da Motta Veiga, S.P. (2018), “Recruiting under the influence: new labor market entrants' reactions to workplace drinking norms”, Human Resource Management, Vol. 57 No. 5, pp. 1303-1316, doi: 10.1002/hrm.21906.
Knoll, N., Rieckmann, N. and Schwarzer, R. (2005), “Coping as a mediator between personality and stress outcomes: a longitudinal study with cataract surgery patients”, European Journal of Personality, Vol. 19 No. 3, pp. 229-247, doi: 10.1002/per.546.
Lazarus, R.S. and Folkman, S. (1984), Stress, Appraisal, and Coping, Springer Publishing Company, New York, NY.
Lusk, E.J., Halperin, M. and Heilig, F. (2011), “A note on power differentials in data preparation between trimming and winsorizing”, Business Management Dynamics, Vol. 1 No. 2, pp. 23-31.
Marchand, A., Demers, A., Durand, P. and Simard, M. (2003), “The moderating effect of alcohol intake on the relationship between work strains and psychological distress”, Journal of Studies on Alcohol, Vol. 64 No. 3, pp. 419-427.
Nagy, M.S. (2002), “Using a single‐item approach to measure facet job satisfaction”, Journal of Occupational and Organizational Psychology, Vol. 75 No. 1, pp. 77-86, doi: 10.1348/096317902167658.
Ng, T.W., Eby, L.T., Sorensen, K.L. and Feldman, D.C. (2005), “Predictors of objective and subjective career success: a meta-analysis”, Personnel Psychology, Vol. 58 No. 2, pp. 367-408, doi: 10.1111/j.1744-6570.2005.00515.x.
Niessen, C., Müller, T., Hommelhoff, S. and Westman, M. (2018), “The impact of preventive coping on business travelers' work and private life”, Journal of Organizational Behavior, Vol. 39 No. 1, pp. 113-127, doi: 10.1002/job.2215.
Oddou, G., Mendenhall, M.E. and Ritchie, J.B. (2000), “Leveraging travel as a tool for global leadership development”, Human Resource Management, Vol. 39 Nos 2-3, pp. 159-172, doi: 10.1002/1099-050X(200022/23)39:2/3%3C159::AID-HRM6%3E3.0.CO;2-J.
Podsakoff, P.M., MacKenzie, S.B., Lee, J.Y. and Podsakoff, N.P. (2003), “Common method biases in behavioral research: a critical review of the literature and recommended remedies”, Journal of Applied Psychology, Vol. 88 No. 5, pp. 879-903, doi: 10.1037/0021-9010.88.5.879.
Rundle, A.G., Revenson, T.A. and Friedman, M. (2018), “Business travel and behavioral and mental health”, Journal of Occupational and Environmental Medicine, Vol. 60 No. 7, pp. 612-616, doi: 10.1097/JOM.0000000000001262.
Stoeber, J. and Janssen, D.P. (2011), “Perfectionism and coping with daily failures: positive reframing helps achieve satisfaction at the end of the day”, Anxiety, Stress and Coping, Vol. 24 No. 5, pp. 477-497, doi: 10.1080/10615806.2011.562977.
Swider, B.W., Boswell, W.R. and Zimmerman, R.D. (2011), “Examining the job search–turnover relationship: the role of embeddedness, job satisfaction, and available alternatives”, Journal of Applied Psychology, Vol. 96 No. 2, pp. 432-441, doi: 10.1037/a0021676.
Taris, T.W., Le Blanc, P.M., Schaufeli, W.B. and Schreurs, P.J. (2005), “Are there causal relationships between the dimensions of the Maslach Burnout Inventory? A review and two longitudinal tests”, Work and Stress, Vol. 19 No. 3, pp. 238-255, doi: 10.1080/02678370500270453.
Vandenberg, R.J. and Nelson, J.B. (1999), “Disaggregating the motives underlying turnover intentions: when do intentions predict turnover behavior?”, Human Relations, Vol. 52 No. 10, pp. 1313-1336, doi: 10.1177/001872679905201005.
Verbruggen, M. and Van Emmerik, H. (2020), “When staying is dissatisfying: examining when and why turnover cognitions affect stayers' career satisfaction”, Journal of Management, Vol. 46 No. 4, pp. 530-559, doi: 10.1177/0149206318801998.
Wallace, S.L., Lee, J. and Lee, S.M. (2010), “Job stress, coping strategies, and burnout among abuse‐specific counselors”, Journal of Employment Counseling, Vol. 47 No. 3, pp. 111-122.
Wanous, J.P., Reichers, A.E. and Hudy, M.J. (1997), “Overall job satisfaction: how good are single-item measures?”, Journal of Applied Psychology, Vol. 82 No. 2, pp. 247-252, doi: 10.1037/0021-9010.82.2.247.
Weiss, M. and Zacher, H. (2022), “Why and when does voice lead to increased job engagement? The role of perceived voice appreciation and emotional stability”, Journal of Vocational Behavior, Vol. 132 No. 1, p. 103662, doi: 10.1016/j.jvb.2021.103662.
Westman, M. (2004), “Strategies for coping with business trips: a qualitative exploratory study”, International Journal of Stress Management, Vol. 11 No. 2, pp. 167-176, doi: 10.1037/1072-5245.11.2.167.
Westman, M., Etzion, D. and Chen, S. (2009), “Crossover of positive experiences from business travelers to their spouses”, Journal of Managerial Psychology, Vol. 24 No. 3, pp. 269-284, doi: 10.1108/02683940910939340.
Yagil, D., Ben-Zur, H. and Tamir, I. (2011), “Do employees cope effectively with abuse supervision at work? An exploratory study”, International Journal of Stress Management, Vol. 18 No. 1, pp. 5-23, doi: 10.1037/a0020548.
Ye, T. and Xu, H. (2020), “The impact of business travel on travelers' well-being”, Annals of Tourism Research, Vol. 85, 103058, doi: 10.1016/j.annals.2020.103058.
Zacher, H. and Rudolph, C.W. (2022), “Strength and vulnerability: Indirect effects of age on changes in occupational well-being through emotion regulation and physiological disease”, Psychology and Aging, Vol. 37 No. 3, pp. 357-370, doi: 10.1037/pag0000671.
Zacher, H. and von Hippel, C. (2022), “Weight-based stereotype threat in the workplace: Consequences for employees with overweight or obesity”, International Journal of Obesity, Vol. 46 No. 4, pp. 767-773, doi: 10.1038/s41366-021-01052-5.
Acknowledgements
The study reported in this article was supported by funding from Volkswagen Foundation (Az. 96849, “The Role of Work in the Development of Civilization Diseases”).