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Article

Conflict (Work-Family and Family-Work) and Task Performance: The Role of Well-Being in This Relationship

1
School of Psychology, ISPA—Instituto Universitário, Rua do Jardim do Tabaco 34, 1149-041 Lisboa, Portugal
2
APPsyCI—Applied Psychology Research Center Capabilities & Inclusion, ISPA—Instituto Universitário, R. Jardim do Tabaco 34, 1149-041 Lisbon, Portugal
3
Psychology Department, Universidade do Algarve, Campus de Gambelas, 8005-139 Faro, Portugal
4
Psychology Department, Universidade de Évora, Escola de Ciências Sociais, Colégio Pedro da Fonseca, PITE—Parque Industrial e Tecnológico de Évora, Rua da Barba Rala, 7005-345 Évora, Portugal
5
Centro de Investigação em Educação e Psicologia da Universidade de Évora (CIEP-UE), Colégio Pedro da Fonseca, Rua da Barba Rala, N.º 1, Edifício B, 7005-345 Évora, Portugal
6
GOVCOPP (UA), Department of Economics, Management, Industrial Engineering and Tourism (DEGEIT), Campus Universitário de Santiago, University of Aveiro, 3810-193 Aveiro, Portugal
7
INESC TEC, Institute for Systems and Computer Engineering, Technology and Science, 4200-465 Porto, Portugal
*
Author to whom correspondence should be addressed.
Adm. Sci. 2023, 13(4), 94; https://doi.org/10.3390/admsci13040094
Submission received: 30 January 2023 / Revised: 17 March 2023 / Accepted: 20 March 2023 / Published: 23 March 2023

Abstract

:
Recent societal changes have brought new challenges to contemporary organisations, e.g., how to properly manage the work-family/family-work dyad and, thus, promote adequate task performance. This paper aimed to study the relationship between conflict (work-family and family-work) and task performance, and whether this relationship was moderated by well-being. Thus, the following hypotheses were formulated: (1) conflict (work-family and family-work) is negatively associated with task performance; (2) conflict (work-family and family-work) is negatively associated with well-being; (3) well-being is positively associated with task performance; and (4) well-being moderates the relationship between conflict (work-family and family-work) and task performance. A total of 596 subjects participated in this study, all employed in Portuguese organisations. The results underlined that only family-work conflict was negatively and significantly associated with task performance. Work-family conflict established a negative and significant relationship with well-being. Well-being was positively and significantly associated with performance and moderated the relationship between conflict (work-family and family-work) and task performance. These results show that organisations should provide employees with situations that promote their well-being, especially in Portugal, where a relationship culture exists (rather than task culture, which is predominant in the USA and Canada, for example) which means that additional and considerable time must be dedicated to personal and family matters for people to fit in and be accepted harmoniously.

1. Introduction

Currently, personal, professional, and family domains present specific characteristics that lead to conflict (Boyar et al. 2003). Research has highlighted the role of job demands, e.g., long working hours, role ambiguity and conflict, shift work, and high physical and psychological loads, as possible sources of conflict in the work-family dyad (Grzywacz et al. 2007; Thompson and Prottas 2006). Thus, the social support received by workers, which can involve emotional (e.g., concern with co-workers), informational (e.g., sharing of information), and practical support (e.g., advice and feedback), facilitates the work process (Hargis et al. 2011; Viseu et al. 2018). Thus, support may be pivotal in decreasing potential conflicts (Frone et al. 1997). The support provided by organisations, i.e., perceived organisational support, may lead to observable improvements in the level of workers’ performance and is related to achieving their goals in the work-family dyad (Akram and Hussain 2020; Eisenberger et al. 1986). This means that individuals who receive support have lower conflict levels (Voydanoff 2004). As such, it is essential to understand that workers’ ways of thinking and feeling are influenced by their lives’ internal and external contexts (e.g., professional activity and work situation) which assume a greater preponderance (Faller 2021), compromising their lifestyle and work performance. Companies can easily achieve their organizational performance targets when employees achieve the set targets. Thus, task performance that reflects employees’ performance becomes organizational performance (Cahyadi et al. 2022).
On the other hand, employee well-being is a principle that requires special attention from organisations because of the diligence in maintaining a bond aimed at creating a satisfied and motivated workforce, which will positively impact performance (Wilson et al. 2004). Well-being should be considered in physical (e.g., safety and health at work) and psychological (e.g., leisure time) terms; these characteristics and dispositions foster the development of a healthy workgroup where productivity prevails (Senthil and Lokesh 2021). Workers are the most precious asset of organisations, thus, it is relevant to invest in this area, intending to promote their satisfaction and contribute to their retention; these aspects are crucial for organisational performance and success. Therefore, well-being establishes a close link with performance. If workers feel satisfied with the conditions provided by their organisation, goal achievement will be facilitated (Gillet et al. 2012).
This study aimed to study the relationship between conflict (work-family and family-work) and task performance and whether this relationship was moderated by well-being. Societal changes resulting from the COVID-19 pandemic, namely at the family (e.g., the obligation to stay at home) and work (e.g., implementation of remote work or hybrid work) levels, brought new challenges for workers and their families, e.g., how to properly manage family and professional obligations while maintaining adequate task performance. In addition, the COVID-19 pandemic also led to the deterioration of well-being due to increased mental health problems (Elahi et al. 2022). These aspects emphasize a mutual interaction between family and work domains and how it can contribute to: (a) well-being and adequate task performance or (b) ill-being and ineffective task performance. This study intended to observe whether well-being acted as a buffer on the relationship between work-family/family-work conflict and task performance. Given recent societal and organisational changes, it is necessary to understand the underlying mechanisms that promote or inhibit workers’ task performance. To our knowledge, no research was performed in Portugal for this purpose. Recent research (e.g., Andrade and Lousã 2021) conducted with Portuguese workers solely observed possible predictors of work-family conflict, not its outcomes or moderators. Based on the obtained results, it will be possible to present measures aimed at reducing conflict and fostering well-being, leading to adequate task performance and, consequently, organisational success.

2. Theoretical Framework and Research Hypotheses

2.1. Work-Family Conflict/Family-Work Conflict

The work-family interaction is a complex process that is influenced by the functioning of modern societies, which create demands at the work (e.g., increasing mental workload, number of hours worked, and job insecurity) and family levels (e.g., the existence of dependents and ascendants, and stressors originating in the family environment). Parker and Wang (2013) noted that in the United States of America, over 50% of working fathers and mothers indicated that managing the work-family dyad was complex. Subjects are confronted with a distinct reality which requires a strong ability to manage their roles and the need to remain effective in all domains (Fotiadis et al. 2019). Work-family conflict is a phenomenon that highlights the inability to manage the impositions from the work and family domains, as they are perceived as mutually incompatible (Csikszentmihalyi 2003). According to Greenhaus and Beutell (1985), conflict is divided into three types: (1) time-based, when the responsibilities in one domain use time that is essential to perform tasks in the other domain; (2) tension-based, arising from stressful situations in one sphere, which interfere with the duties of the other sphere; and (3) behaviour-based, when there is a non-conformity of the roles assumed in the respective environments of inclusion.
Initially, this construct was considered as unidirectional (e.g., Gutek et al. 1991); recently, other authors have underlined its bidirectional structure (e.g., Greenhaus and Powell 2006). This concept is cemented in two perspectives: work-family conflict, in which work responsibilities interfere with a subject’s family role, and family-work conflict, when family arrangements undermine the subject’s work performance (Frone et al. 1992; Netemeyer et al. 1996). However, it should be noted that the compatibility between work and family domains leads to feelings of success, promoted by motivation (Baeriswyl et al. 2016). The literature has also stated that work-family conflict can impact organisational and individual well-being (Ford et al. 2007; Kossek and Ozeki 1998), simultaneously worsening job satisfaction, productivity, and employee performance (Johnson et al. 2005).
Organisations have tried to address this issue to identify the possible effects of cross-domain conflict, whether from work to family or from family to work (Grant-Vallone and Donaldson 2001; O’Driscoll et al. 2004). The state of the art clarifies that the relationship between employees’ perceived exhaustion due to high demands originating from work and family environments, coupled with other occupational causes, such as stress, turnover, and individual performance (Khan 2015), can negatively impact organisations’ performance and productivity. Conversely, valuing work principles that encourage work and family stability, such as part-time jobs, career breaks, parental leave, flexible work schedules, and compressed work weeks (Ministerial Task Force on Work and Family 2002), fosters workers’ performance and mental health (Fitzpatrick et al. 2012). As such, it is crucial to balance the family and professional domains (Smith et al. 2016). Individuals who experience happiness at their workplace present higher productivity rates, which drives organisations to focus their understanding of the importance of family life in the search for possible solutions (Obrenovic et al. 2020).
Considering these arguments, the following hypotheses were formulated:
Hypothesis 1.
Conflict (work-family and family-work) is negatively associated with task performance.
Hypothesis 2.
Conflict (work-family and family-work) is negatively associated with well-being.

2.2. Job Performance and Well-Being

Due to solid competitiveness, organisations must show dynamism in maintaining their role in a market with constant activity and change (Zakaria et al. 2014). According to Baines and Langfield-Smith (2003), managers seek to add value to their workforce to achieve a competitive advantage over other organisations. Organisational performance is a strongly desired advantage, however, its achievement is conditioned by several factors, such as employee well-being. Healthy employees are expected to contribute more to their organisation’s performance (Zakaria et al. 2014). Given this new work arrangement, employees are seen as vital in achieving competitive advantages and organisations are responsible for leveraging their skills and knowledge, projecting the constant progress of their performance (Atkinson et al. 2012; Roslender and Dyson 1992). Well-being is associated with the daily activities and life experiences of employees. Considering the impact of work on employees’ daily lives, mainly due to the time spent in the workplace, managers should try to strengthen the workforce’s sense of confidence in the work processes and enhance their skills regarding new work methodologies that emerge from changes in modern workplaces (Danna and Griffin 1999; Hantula 2015; Sparks et al. 2001). Preparing workers for organisational challenges points to the organisation’s concern for their well-being and appreciation of their role as an organisational member (Viseu et al. 2020). Consequently, employees will present higher well-being levels, resulting in increased performance.
The World Health Organization (2006) considered health to be a harmonious state involving physical, psychological, and social well-being, and not merely the absence of disease. The existence of well-being is necessary for individual health; since work is one of the most relevant domains for individuals’ lives, mainly due to the time workers spend at their workplaces, it is necessary to assess individual well-being in the organisational context. Individual well-being has a nature that directly interferes with the work and life of workers. The literature is substantial in studies that have assessed the relationship between well-being and work-related outcomes (Karapinar et al. 2019; Turban and Yan 2016). As such, both health and well-being assume a significant role in achieving success and work performance (Bakker et al. 2019; Turban and Yan 2016). Other research has emphasized the role of well-being in workers’ lives, demonstrating that this construct fosters individual outcomes which materialize in increased productivity and performance (Hewett et al. 2018), consumer satisfaction (Sharma et al. 2016), work engagement (Tisu et al. 2020), and organisational citizenship behaviours (Mousa et al. 2020). It is necessary to understand that organisational performance and productivity are founded on individual performance (Shin and Konrad 2017). This statement is grounded in indicators that highlight the importance of good worker performance, measured by their actions and behaviours, and that is associated with the results they achieve, which allow organisational goal accomplishment (Viswesvaran and Ones 2017) and success (Al Hammadi and Hussain 2019; Shin and Konrad 2017).
Organisational well-being encompasses several aspects highlighting individual psychology, physiology, experienced work situations, and even situational satisfaction (De Jong et al. 2016). Additionally, this concept integrates the importance of feelings of happiness, professional intentions, and personal growth (Zheng et al. 2016). According to Warr (2008), happiness is a motivating source that leads to goal achievement. Combining these principles expresses a framework that contemplates the worker’s health and job satisfaction. Thus, the perception of a balance between domains will enable the achievement of greater well-being (Odle-Dusseau et al. 2012). Employees who lack well-being exhibit poor performance, which is reflected in their work quality and psychological health (Attridge 2009). Organisations are increasingly striving to find viable solutions that offer improvements in employee well-being, as noted by Rajaratnam et al. (2014). These authors denoted that the adoption of programs aimed at fostering well-being positively affects the health and productivity of workers, leading to greater organisational efficiency and a reduction in health-related costs. For Zheng et al. (2016), organisations must select work practices that are adjusted to their reality and enable organisational well-being for their employees. Furthermore, organisations must stimulate positive working climates, e.g., climates that value interpersonal relationships and are open to accepting new ideas and methodologies. Viitala et al. (2015) observed that desirable working environments were associated with increased well-being.
Thus, the following hypothesis was formulated:
Hypothesis 3.
Well-being is positively associated with task performance.

2.3. Work-Family Conflict/Family-Work Conflict, Well-Being, and Performance

The state of the art has highlighted several discussions concerning the effect of work-family conflict on organisational and individual well-being (Ford et al. 2007; Kossek and Ozeki 1998). Interdomain conflict negatively affects employees, which is visible through decreased performance, productivity, and job satisfaction (Johnson et al. 2005). In addition to the above, it is worth noting its influence on life satisfaction, psychological distress, and turnover rates (Greenhaus and Beutell 1985). In other words, the conflict experienced between both domains, family and work, not only has harmful consequences for one domain, but for both. Thus, it should be emphasized that an intervention at the level of this conflict should focus on both domains to obtain effective results.
Research has focused on identifying the repercussions of this incompatibility between domains (Grant-Vallone and Donaldson 2001; O’Driscoll et al. 2004). High turnover rates combined with other organizational causes can impact organisational performance. However, adopting a set of work principles and policies which consider a balance between work and family improves individual performance and mental health (Fitzpatrick et al. 2012). Employees who express happiness and satisfaction at work show higher productivity. This means that organisations must adopt a proactive attitude in seeking to create a positive interface between work and family life, which favours the reduction or elimination of the conflicts that may exist (e.g., adoption of family-friendly benefits, such as flexible working hours, the possibility of accompanying family members to medical appointments during working hours, and payment of wages during parental leave.
This reasoning led us to formulate the following hypothesis:
Hypothesis 4.
Well-being moderates the relationship between conflict (work-family and family-work) and task performance.
The following research model summarises the hypotheses formulated in this study (Figure 1).

3. Method

3.1. Procedure

This study had the voluntary participation of 596 subjects working in organisations based in Portuguese territory. After the questionnaire was created via Google Forms, the questionnaire link was sent to employees of organizations exclusively based in Portuguese territory. The links were sent in a mail or individual message via LinkedIn and not in a group or posted on any social network to avoid biases. Data collection took place between April and December 2022 using a non-probabilistic sampling technique, by convenience of the research team and through the snowball method (Trochim 2000). In the first part of the questionnaire, participants were informed about the purpose of the study and guaranteed anonymity and confidentiality. Participants were also told that there were no right or wrong answers, and that we were only interested in their opinion and their responses would never be known, since the analysis to be carried out would be of the set of answers given by all employees. This questionnaire was composed of sociodemographic questions and three self-report measures (work-family and family-work conflict, task performance, and well-being).

3.2. Participants

The sample of this study (Table 1) was composed of 596 participants with ages ranging from 20 to 70 years old (M = 37.98; SD = 10.88). Concerning gender, 334 (56%) were females and 262 (44%) were males, among whom 328 (55%) had no children, 121 (20.3%) had one child, 107 (18%) had two children, and 40 (6.7%) had three or more children. Regarding marital status, 249 (41.8%) were single, 292 (49%) were married or cohabiting, 50 (8.4%) were divorced, and 5 (0.8%) were widowed. As for the education level, 70 (11.7%) had a primary education, 157 (26.3%) had a secondary education, 113 (19%) had an undergraduate degree, 173 (29%) had a graduate degree, 76 (12.8) a master’s degree, and 7 (1.2%) a doctorate. Regarding the work contract, 105 (17.6%) had a fixed-term contract, 397 (66.6%) had an open-ended contract, 46 (7.7%) were self-employed, and 48 (8.1%) had another type of contract. In the private sector, 448 (81.9%) participants were employed and 108 (18.1%) worked in the public sector. Most of these employees worked full-time, 551 (92.4%), and 264 (44.3%) were exempt from working hours. Finally, relative to job tenure, 146 (24.5%) had up to one year, 239 (40.1%) had between one and five years, 80 (13.4%) had between five and 10 years, 42 (7%) had between 10 and 15 years, and 89 (14.9%) had more than 15 years.

3.3. Data Analysis Procedure

Data were imported into SPSS Statistics 28 software (IBM Corp., Armonk, NY, USA) to be processed. Initially, the metric qualities of the three measures used were tested. Validity was assessed by confirmatory factor analyses using AMOS 28 for Windows software (IBM Corp., Armonk, NY, USA). The procedure was performed according to a “model generation” logic (Jöreskog and Sörbom 1993), considering the following threshold values: chi-squared statistics (χ2) ≤ 5; Tucker Lewis index (TLI) > 0.90; goodness-of-fit index (GFI) > 0.90; comparative fit index (CFI) > 0.90; root mean square error of approximation (RMSEA) ≤ 0.08; Root Mean Square Residual (RMSR); the lower the value, the better. Subsequently, the reliability of each scale was calculated through the Cronbach’s alpha coefficient, whose value should be greater than 0.70 (Bryman and Cramer 2003; Hill and Hill 2002). Construct reliability was also estimated, as well as the convergent validity, through the average variance extracted (AVE) coefficient, whose value should be greater than 0.50 (Fornell and Larcker 1981). Discriminant validity was assessed by squaring the correlation between the factors, which should be lower than the AVE of each factor (Anderson and Gerbing 1988; Fornell and Larcker 1981). For the sensitivity study, different measures of central tendency, dispersion, and distribution were calculated for the different items, thus performing a normality study. To study the differences in the variables under study according to socio-demographic variables, the t-Student test for independent samples and the One Way ANOVA were used. The association between variables was studied through Pearson’s correlations. The hypotheses formulated were tested through simple and multiple linear regressions.

3.4. Instruments

To measure work-family and family-work conflict, the instrument developed by Netemeyer et al. (1996) was used, namely the version translated and adapted to the Portuguese population by Santos and Gonçalves (2014). This instrument is composed of ten items with a seven-point Likert scale (from 1, “strongly disagree” to 7, “strongly agree”). The ten items assessed the bidirectional component of the conflict: work-family conflict (items 1, 2, 3, 4, and 5) and family-work conflict (items 6, 7, 8, 9, and 10). To test its validity, a two-factor confirmatory factor analysis (CFA) was performed. The adjustment indexes obtained were adequate (χ2/gl = 3.98; GFI = 0.97; CFI = 0.98; TLI = 0.97; RMSEA = 0.071; SRMR = 0.173), which confirmed that this measure was composed of two factors. Regarding internal consistency, a Cronbach’s alpha of 0.90 was obtained for both work-family conflict and family-work conflict. The work-family conflict dimension presented a construct reliability of 0.89, and a family-work conflict of 0.84. The two dimensions possessed convergent validity, with work-family conflict showing an AVE of 0.64 and a family-work conflict of 0.52. This instrument also proved to have discriminant validity, as the squared correlation between factors had a value of 0.41, lower than the AVE value of the two factors.
To measure task performance, seven items that compose the task performance dimension of the instrument developed by Williams and Anderson (1991) were used, which were answered with a five-point Likert scale (from 1 “strongly disagree” to 5 “strongly agree”). After the confirmatory factor analysis, it was found that items 6 and 7 had a low factor weight, so it was necessary to remove them from the analysis. The adjustment indexes obtained were adequate (χ2/gl = 1.76; GFI = 0.99; CFI = 0.99; TLI = 0.99; RMSEA = 0.036; SRMR = 0.003). This instrument presented a good internal consistency, with a Cronbach’s alpha of 0.86. It also showed construct reliability, with a value of 0.86, and convergent validity with an AVE value of 0.56.
Well-being was measured through 16 items of the Perma-Profile Instrument, developed by Butler and Kern (2015) and adapted for the Portuguese population by Alves et al. (2016). These items were rated on an 11-point rating scale (from 0 to 10). A confirmatory factor analysis with a single-factor was performed and it was found that the fit indexes were adequate (χ2/gl = 3.77; GFI = 0.94; CFI = 0.96; TLI = 0.95; RMSEA = 0.068; SRMR = 0.119). This measure presented a good internal consistency, with a Cronbach’s alpha of 0.93. As for construct reliability, it presented a value of 0.93, which is considered good. Regarding convergent validity, the AVE value obtained was marginally below the threshold indicated by Fornell and Larcker (1981).

4. Results

4.1. Descriptive Statistics of the Variables under Study

The first step was to understand the position of the answers given by the participants to the constructs addressed in this study.
As shown in Table 2, participants were revealed to have low work-family and family-work conflict, significantly below the central point (4). As for their perception of task performance, they perceived high performance, significantly above the central point (3). Finally, they also showed high levels of well-being, significantly above the central point (6).

4.2. Distribution of the Variables According to the Sociodemographic Variables

Subsequently, the effect of the sociodemographic variables on the selected concepts was analysed.
The effect of gender was not significant, with female and male participants showing very similar mean values in all constructs (Figure 2).
The fact that a participant has children, and the number of children, is associated with higher work-family conflict (F (3, 592) = 8.25; p < 0.001) and higher family-work conflict (F (3, 592) = 11.46; p < 0.001) when compared with participants who do not have children. Regarding task performance and well-being, the effect was non-significant (Figure 3).
Marital status had a significant association with work-family (F (3, 592) = 16.17; p < 0.001) and family-work (F (3, 592) = 15.96; p < 0.001) conflict. The widowed participants were found to have the highest levels of conflict. In turn, single participants revealed to have lower levels of conflict (Figure 4).
Education level only significantly affected family-work conflict (F (3, 592) = 3.64; p = 0.003), with participants with elementary school education showing higher levels of this type of conflict and participants with bachelor’s degree showing lower levels (Figure 5).
Regarding job tenure, there were statistically significant differences in work-family conflict (F (4, 591) = 8.70; p < 0.001) and family-work conflict (F (4, 591) = 4.81; p < 0.001). Participants who were between 10 and 15 years in the organisation possessed higher levels of work-family conflict. Regarding work-family conflict, participants who have been in the organisation for more than 15 years had the highest levels. Participants who have been in the organisation for less time reported lower conflict levels, both work-family and family-work (Figure 6).
Contract type only significantly affected work-family conflict (F (3, 592) = 3.59; p = 0.014), with the self-employed experiencing higher levels (Figure 7).
Working sector had a significant association with family-work conflict (t (594) = −2.42; p = 0.008), with participants working in the public sector revealing higher levels than participants working in the private sector (Figure 8).
Another variable assessed was time exemption, which had a significant association with employee well-being (t (594) = −3.29; p = 0.001) and family-work conflict (t (594) = −2.54; p = 0.011). Participants who had time exemptions had higher levels of well-being and family-work conflict (Figure 9).
Whether the employee worked full-time or part-time had no significant association with any of the variables evaluated (Figure 10).

4.3. Correlational Analysis

Pearson’s correlations were used to study the association between the concepts selected.
The results indicate that work-family conflict is negatively and significantly correlated with well-being (Table 3). Family-work conflict is negatively and significantly correlated with performance (Table 3). Well-being is positively and significantly correlated with task performance (Table 3).

4.4. Hypotheses

Subsequently, the research hypotheses defined for this study were tested. To test H1, a multiple linear regression was performed.
The results indicated that only family-work conflict was significantly associated with task performance (β = −0.17; p < 0.001) (Table 4). The model explained the variability in task performance by 2% and was statistically significant (F (2, 593) = 6.85; p = 0.001). This hypothesis was partially supported (Table 4).
The second hypothesis was tested by performing a multiple linear regression.
The results indicated that only work-family conflict was significantly associated with well-being (β = −0.11; p = 0.027) (Table 5). The model explains the variability in well-being by 1% and is statistically significant (F (2, 593) = 3.06; p = 0.048) (Table 4). This hypothesis was partially supported.
The third hypothesis was tested by performing a simple linear regression.
As can be seen in the Table 6, well-being was significantly associated with task performance (β = 0.33; p < 0.001). The model explains the variability of well-being by 11% and is statistically significant (F (1, 594) = 71.96; p < 0.001). This hypothesis was supported.
To test hypothesis 4, the moderation hypotheses, there was a need to centre the independent variables and the moderator variable to avoid multicollinearity problems and to create the interaction variables (Aiken and West 1991). A two-step multiple linear regression was then performed. In the first step, the predictor and moderator variables were introduced as independent variables. In the second step, the interaction variables were introduced as independent variables.
The results indicated that there was an interaction effect of well-being both in the relationship between work-family conflict and task performance (β = 0.17; p < 0.001), and in the relationship between family-work conflict and task performance (β = 0.15; p < 0.001) (Table 7). This hypothesis was partially supported.
For participants with high work-family conflict compared to those with low conflict, perceived well-being became relevant to enhance task performance. In contrast, it decreases significantly in participants with low levels of well-being (Figure 11).
For participants with high family-work conflict, when compared to those with low conflict, well-being became relevant to maintain task performance. In contrast, it decreased significantly in participants with low levels of well-being (Figure 12).

5. Discussion

This research aimed to study the effect of conflict (work-family and work-family) on task performance as well as whether this relationship was moderated by well-being.
First, a significant and negative association between family-work conflict and task performance was discovered. These results align with the literature, since family-work conflict is reflected in reduced task performance (Johnson et al. 2005; Moreira et al. 2023). This means that when employees experience a conflict situation, in this case, from the family to work domain, they will present decreased performance. On the other hand, a negative and significant association between work-family conflict and task performance was not observed. These results are not in agreement with the literature. According to Khan (2015), work-family conflict reduces task performance. What may explain these results is the fact that this sample was collected during 2022, and that many employees were still telecommuting or in a hybrid work regime. These work regimes allow a better articulation between work and family domains and facilitate time management (Burch 1991; Elahi et al. 2022; Zakhem et al. 2022). Therefore, workers who work remotely or in a hybrid manner end up experiencing less conflict, and its effect on performance decreases or ceases to exist.
Second, a significant negative association was found between work-family conflict and well-being, which is also in line with the literature. In a study conducted by Moreira et al. (2022), it was found that work-family conflict significantly reduced employees’ well-being, i.e., when work roles have an incompatible relationship with family roles, individuals perceive a decrease in their physical and psychological well-being. In turn, the association between family-work conflict and well-being did not prove to be significant. These results are contradictory with the current state-of-the-art, Moreira et al. (2022) obtained different results; a negative and significant association was achieved in their study. Nevertheless, in the study of Moreira et al. (2022), the association between work-family conflict and well-being was stronger than between family-work conflict and well-being. Third, a positive and significant association was found between well-being and task performance. These results agree with past studies, e.g., Rajaratnam et al. (2014) registered that when employees felt higher levels of well-being, their task performance increased.
Finally, the moderating effect of well-being on the relationship between work-family conflict and task performance and the relationship between family-work conflict and task performance were confirmed. These moderating effects were positive, which means that in the presence of high levels of employee well-being, even in high levels of conflict (work-family and family-work), task performance is maintained or slightly increased. These results align with a similar study by Soomro et al. (2018). As such, it can be stated that well-being acts as a protective mechanism of performance, preventing the detrimental effect of conflict.
Descriptive statistics and the effect of sociodemographic variables on the variables under study were also performed. It was found that the participants in this study had higher levels of work-family conflict than family-work conflict. As for their perception of task performance, this also proved to be increased. However, task performance was measured through a self-report instrument, thus, participants may have provided socially desirable responses, seeking to create an image of the ideal worker. The participants in this study also revealed having high levels of well-being. Concerning the role of the socio-demographic variables, gender and whether respondents worked part-time or full-time did not prove significant. Conflict levels (work-family and family-work) of participants with children differed significantly from those without children. Participants with children showed higher levels of conflict than participants without children. Regarding marital status, single participants perceived less conflict (work-family and family-work) than the other participants. Seniority was also significantly associated with conflict (work-family and family-work), with participants who have been with the organisation for less time showing lower levels of conflict. Self-employed participants, as did those working in the public sector, revealed higher levels of family-work conflict. Participants who were exempt from working hours showed higher levels of family-work conflict, but also of well-being. This association between sociodemographic variables and family-work conflict may help explain why only this type of conflict had a significant relationship with task performance.

5.1. Limitations

The first limitation is that the sample was collected through a non-probabilistic sampling technique, intentional and of the snowball type. Another limitation is related to the type of questionnaire used—self-report—which may have influenced the answers given by participants. To reduce the influence of common method variation, we followed the recommendations of Podsakoff et al. (2003). The fact that it is a cross-sectional study is another limitation, since it does not allow for establishing causal relationships. Finally, another limitation was that the self-report questionnaire did not ask a question about the employees’ work regime (face-to-face, teleworking, or hybrid). This question would have been extremely important to help deepen the discussion of the obtained results.

5.2. Practical Implications

This study allows the presentation of several strategies aimed at reducing work-family and family-work conflict. Before acting on these concepts, organisations and managers should focus on their antecedents (e.g., existence of descendants or ascendents, family centrality values, family illness situations, number of working hours, physical or psychological workload), since these are aspects that foster the existence of the types of conflict under analysis (Schonfeld and Chang 2017). At the work level, alternative work arrangements, which can facilitate the management of the work-family dyad, can be implemented, e.g., telecommuting, i.e., individuals work from home through a remote connection to their organisation; compressed work week, i.e., individuals work fewer days per week, but the number of working hours is the same; flextime, i.e., individuals work a fixed number of hours per day and from then on freely manage their daily life; or shared work, i.e., the same tasks are performed by two or more individuals, but one individual can work during the morning shift and another during the afternoon shift (Neves 2014).
According to Wattoo et al. (2017), perceived organisational support arising from family-friendly policies is essential for reducing conflict situations. Hong et al. (2019) also underlined the importance of support for decreasing work-family conflict. When workers feel supported by their organisations, they realize that their personal and family needs are valued and acknowledged. Furthermore, this situation can be positive for organisations, as workers tend to reciprocate and perform their tasks with greater engagement (Viseu et al. 2021). Furthermore, organisations can provide workers with a leave from work so that they can accompany their descendants or ascendants for health reasons (Schonfeld and Chang 2017).
Flexible management of work and family dimensions will allow a greater balance between both domains, leading to a decrease in conflict and tension as well as contributing to better psychological health. If these strategies are implemented, there will be a positive spillover effect from one domain to the other, fostering, e.g., organisational commitment (organisational-related outcome) and happiness (individual-related outcome) (Lee et al. 2018).
At the well-being level, organisations should seek to create a healthy work environment, e.g., by fostering interpersonal relationships that provide social support networks that help workers in emotional, practical, and instrumental dimensions (Giebels and Janssen 2005). However, the existence of healthy relationships should not be limited to the relationships between peers; managers should also be encouraged to adopt positive relations with their subordinates. The literature has underlined that supervisors can be a source of stress at work (Monnot and Beehr 2014). According to Peeters et al. (2009), organisations should also try to implement a culture of family support, as this type of culture is a predictor of well-being.
The implementation of these strategies should not occur in an isolated manner, since they can act synergistically to promote a better task performance. In addition, their implementation must have a critical analysis, e.g., there are organisations, see the case of factories, where it is not possible to create remote workstations.

6. Conclusions

The main finding of this study was the existence of a positive moderating effect of well-being on the relationship between conflict (work-family and family-work) and task performance, such as those of a study conducted by Soomro et al. (2018).
As for the direct effect of conflict (work-family and family-work) on task performance and well-being, there was only a significant effect of family-work conflict on task performance and work-family conflict on well-being. It should also be noted that the participants in this study revealed higher levels of work-family conflict than family-work conflict. Concerning the relationship between sociodemographic variables and the assessed constructs, a significant association was observed between almost all sociodemographic variables and family-work conflict.
The changes observed in recent years highlighted the importance of work-family interaction and how it can be related to well-being and task performance. This study was innovative in the Portuguese organisational context. For example, a recent study conducted in Portugal (see Andrade and Lousã 2021) solely identified the predictors of work-family conflict. The present research went further by including the concept of family-work conflict, which is related to the impact of family life on the professional domain of individuals, but also by integrating an outcome of conflict, e.g., task performance, and a moderator, e.g., well-being. Adequate task performance is essential for organisations to achieve their goals and, consequently, organisational success. Studies conducted in other countries (e.g., Lebanon; Zakhem et al. 2022) have demonstrated the importance of performance during the pandemic and in a period of decreased business activity. In addition, while considering the moderating role of well-being, it was possible to identify a variable that can mitigate the adverse effects of conflict. This allowed the presentation of proposals destined to foster this concept, contributing to effective task performance. Of significance is that Portugal was, before the pandemic, identified as being a relationship culture (Solomon and Schell 2009), and this facet of life in Portugal has remained the same according to our study. Hence, more extreme dedication to work rather than personal and family relationships will have a toll on conflict generation. Other, more task-related cultures, such as the USA and Canada (Solomon and Schell 2009), may deal better with the above, albeit as most cultures are indeed relationship cultures, to some degree, companies around the globe must pay attention to work-family interaction. Not doing so involves elevated risks regarding productivity, efficiency, and effectiveness at work.

Author Contributions

Conceptualization, A.M., T.E. and J.V.; methodology, A.M. and J.V.; software, A.M. and M.A.-Y.-O.; validation, A.M., T.E. and J.V.; formal analysis, A.M.; investigation, A.M. and J.V.; resources, A.M. and M.A.-Y.-O.; data curation, A.M.; writing—original draft preparation, T.E., J.V. and M.A.-Y.-O.; writing—review and editing, A.M. and M.A.-Y.-O.; visualization, J.V. and T.E.; supervision, A.M., J.V. and M.A.-Y.-O.; project administration, A.M. and J.V.; funding acquisition, A.M. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Ethical review and approval were waived for this study since all participants before answering the questionnaire had to read the informed consent and agree to it. This was the only way they could answer the questionnaire. Participants were informed about the purpose of the study, as well as that the results were confidential, as individual results would never be known, but would only be analysed in the set of all participants.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data presented in this study are available on request from the corresponding author. The data is not publicly available because in their informed consent, participants were informed that the data was confidential and that individual responses would never be known, as data analysis would be of all participants combined.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Research Model.
Figure 1. Research Model.
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Figure 2. Distribution of variables according to gender.
Figure 2. Distribution of variables according to gender.
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Figure 3. Distribution of variables according to the number of children.
Figure 3. Distribution of variables according to the number of children.
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Figure 4. Distribution of variables by marital status.
Figure 4. Distribution of variables by marital status.
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Figure 5. Distribution of variables according to academic qualifications.
Figure 5. Distribution of variables according to academic qualifications.
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Figure 6. Distribution of variables by tenure.
Figure 6. Distribution of variables by tenure.
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Figure 7. Distribution of variables according to work contract.
Figure 7. Distribution of variables according to work contract.
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Figure 8. Distribution of variables according to sector (public and private).
Figure 8. Distribution of variables according to sector (public and private).
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Figure 9. Distribution of variables according to hours exemption or not.
Figure 9. Distribution of variables according to hours exemption or not.
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Figure 10. Distribution of variables by type of work regime (part-time or full-time).
Figure 10. Distribution of variables by type of work regime (part-time or full-time).
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Figure 11. WFC x Well-being interaction chart.
Figure 11. WFC x Well-being interaction chart.
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Figure 12. FWC x Well-being interaction chart.
Figure 12. FWC x Well-being interaction chart.
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Table 1. Sociodemographic Variables Descriptive Statistics.
Table 1. Sociodemographic Variables Descriptive Statistics.
Socio-Demographic VariableFrequencyPercentage
GenderFemale33456%
Male26244%
ChildrenZero32855%
One12120.3%
Two10718%
Three or more406.7%
Marital StatusSingle24941.8%
Married or cohabiting29249%
Divorced508.4%
Widowed50.8%
Academic qualificationsPrimary education7011.7%
Secondary education15726.3%
Undergraduate degree11319%
Graduate degree17329%
Master’s degree7618.2%
Doctorate71.2%
Work contractFixed-term contract10517.6%
Open-ended contract39766.6%
Self-employed467.7%
Other488.1%
SectorPrivate44881.9%
Public10818.2%
RegimeFull-time55192.4%
Part-time457.6%
Exempt from working hoursYes26444.3%
No33255.7%
Job TenureUp to one year14624.5%
Between one and five years23940.1%
Between five and 10 years8013.4%
Between 10 and 15 years427%
More than 15 years8914.9%
AgeMinimumMaximumMeanSD
207037.9810.88
Table 2. Descriptive statistics of the variables under study.
Table 2. Descriptive statistics of the variables under study.
VariabletpMSD
Work-Family Conflict−5.96 ***<0.0013.621.56
Family-Work Conflict−28.67 ***<0.0012.401.36
Task Performance73.63 ***<0.0014.530.51
Well-being29.13 ***<0.0017.521.27
Note. *** p < 0.001. M = mean value; SD = standard-deviation value.
Table 3. Association between the variables under study.
Table 3. Association between the variables under study.
1234
1. Work-Family Conflict--
2. Family-Work Conflict0.56 ***--
3. Task Performance−0.04−0.14 ***--
4. Well-being−0.10 *−0.050.33 ***--
Note. * p < 0.05; *** p < 0.001.
Table 4. Multiple linear regression results (H1).
Table 4. Multiple linear regression results (H1).
Independent
Variable
Dependent
Variable
FpR2aβtp
Work-Family ConflictTask Performance6.85 **0.0010.02−0.05−1.080.280
Family-Work Conflict−0.17 ***−3.54 ***<0.001
Note. ** p < 0.01; *** p < 0.001. F = ANOVA test; p = p-value; R2a = adjusted R square; t = student’s t; β = standardised regression coefficient.
Table 5. Multiple linear regression results (H2).
Table 5. Multiple linear regression results (H2).
Independent
Variable
Dependent VariableFpR2aβtp
Work-Family ConflictWell-being3.06 *0.0480.01−0.11 *−2.22 *0.027
Family-Work Conflict−0.02−0.320.748
Note. * p < 0.05. F = ANOVA test; p = p-value; R2a = adjusted R square; t = student’s t; β = standardised regression coefficient.
Table 6. Simple linear regression results (H3).
Table 6. Simple linear regression results (H3).
Independent VariableDependent VariableFpR2aβtp
Well-beingTask Performance71.96 ***<0.0010.110.33 ***8.48 ***<0.001
Note. *** p < 0.001. F = ANOVA test; p = p-value; R2a = adjusted R square; t = student’s t; β = standardised regression coefficient.
Table 7. Results of the moderation effect (H4).
Table 7. Results of the moderation effect (H4).
Independent VariableTask Performance
β Step 1β Step 2
Work-Family Conflict−0.09−0.04
Family-Work Conflict−0.18 ***−0.15 **
Well-being0.33 ***0.34 ***
WFC x Well-being 0.15 ***
FWC x Well-being 0.17 ***
Overall F29.52 ***22.09 ***
R2a0.130.16
Δ 0.03 ***
Note. ** p < 0.01; *** p < 0.001. F = ANOVA test; p = p-value; R2a = adjusted R square; β = standardised regression coefficient.
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MDPI and ACS Style

Moreira, A.; Encarnação, T.; Viseu, J.; Au-Yong-Oliveira, M. Conflict (Work-Family and Family-Work) and Task Performance: The Role of Well-Being in This Relationship. Adm. Sci. 2023, 13, 94. https://doi.org/10.3390/admsci13040094

AMA Style

Moreira A, Encarnação T, Viseu J, Au-Yong-Oliveira M. Conflict (Work-Family and Family-Work) and Task Performance: The Role of Well-Being in This Relationship. Administrative Sciences. 2023; 13(4):94. https://doi.org/10.3390/admsci13040094

Chicago/Turabian Style

Moreira, Ana, Tiago Encarnação, João Viseu, and Manuel Au-Yong-Oliveira. 2023. "Conflict (Work-Family and Family-Work) and Task Performance: The Role of Well-Being in This Relationship" Administrative Sciences 13, no. 4: 94. https://doi.org/10.3390/admsci13040094

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