The purpose of this study was to explore the contributions of decent work situation to work–life balance of small entrepreneurs. The survey was conducted to uncover the degree and magnitude of essential decent work indicators that can aid the work–life balance situation of small ventures.
The study utilized a survey research design and used a five-point Likert type questionnaire to investigate the research questions. Each construct of the scale has its corresponding items, which were measured specifically. To analyze the latent variables, partial least square (PLS)–structural equation modelling with Smart PLS application was used.
The findings of this study reveal that social dialogue and stability and security of enterprise have the most significant effects in ensuring work–life balance of an enterprise. Additionally, social dialogue among entrepreneurs has influence in maintaining decent working hours and fair treatment at workplace.
The value of this study lies in exploring a new dimension of analyzing working conditions in informal sector economy such as small enterprises. Because this research aims to study ventures that are financed by the microcredit institution, whether social financing plays a role in improving work–life balance situation through empowering decent working conditions can be investigated.
Hussain, A. and Endut, N. (2018), "Do decent working conditions contribute to work–life balance", Asia Pacific Journal of Innovation and Entrepreneurship, Vol. 12 No. 1, pp. 90-104. https://doi.org/10.1108/APJIE-04-2018-045Download as .RIS
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Copyright © 2018, A.H.M. Belayeth Hussain and Noraida Endut.
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In the mid-1970s, the economic oil shocks, worldwide recession and a constellation of technological, political and economic factors halted economic growth and induced transformations in production processes, thus providing a background for transforming the nature of relations between employers and workers (Kalleberg, 2009; Wilson, 2013; Lightman et al., 2008). The current dominant policy discourse over much of the neoliberal globalization would have us believe flexible employment structure an essential component of the new global economy. Thus, the growth of precarious employment should be seen as an outcome of specific and reversible actions by key interest groups, financial community, management consultants and governments.
According to researchers, precarious work is not necessarily new to the current era (Benanch et al., 2014; Kalleberg, 2009). In fact, various dramatic changes that took place during the past three decades paved the way through which precarious forms of employment expanded globally. Experts have shown that precarious work is pervasive throughout the Asia-Pacific region and affects millions of workers. It has also become a critical challenge for governments. Because of differences in their level of development, historical trajectories and cultural traditions, Asian countries differ in the degree of precarious work (Kalleberg and Hewison, 2013). In fact, in Asia, there is a tendency to label the workers in the informal sector as precarious. According to Reza (2016), the construction industry represents a significant proportion of precarious workers in Bangladesh. But, according to other studies (Barkat et al., 2003; Agarwala, 2013), the garment industry is considered to represent precarious work in the sense that the employment contracts bring limited social benefits and statutory entitlements, high job insecurity, low job tenure, low earning, poor working conditions and high health risk.
As long as we consider the informal sector, small- and medium-sized enterprises (SMEs) play a vital part in economic development in developing nations. They provide numerous employment opportunities in local areas and promote flexibility to the economy. There is a common agreement that a strong SME segment is one of the key powers towards the expansion of the overall economy of Bangladesh and hence inspire private ownership, generate employment and stimulate diversified economic activities (Uz Zaman and Islam, 2011). In developing Asia, Bangladesh is one of the countries with plentiful labour supply, and it is often said that under proper conditions, the surplus labour has the potential to promote economic growth. However, increased labour efficiency and improved working conditions in the labour market are required to achieve an optimum outcome from this abundant labour supply.
SMEs are the real motor of employment creation in developing nations, where small enterprises essentially contribute to employment. Thus, the ILO (2015b) considers SMEs as a key zone of mediation and pledges for the sustainable presence of SMEs in guaranteeing decent working conditions in the workplace, as SMEs represent 66 per cent of all employment opportunities around the world. The United Nations Development Group (2015) reports that micro-, small- and medium-sized enterprises (MSMEs) represent more than 90 of all enterprises worldwide and are a critical wellspring of output and employment.
Our present research investigates a wide assortment of decent work issues at small enterprise levels. The social finance program of International Labour Organization (ILO) asserts that entrance to microfinance can diminish a decent work deficiency. Among a number of other services, availability of micro insurance, education, health care and legal advice may effectively reduce child labour, diminish vulnerabilities, bring issues to light and enhance overall working conditions (ILO, 2015c). Theoretically, the ILO decent work agenda involves four indistinguishable, interrelated and commonly strong pillars: creating jobs, guaranteeing rights in the workplace, extending social protection and promoting social dialogue (ILO, 2015b). As a noteworthy philosophical strand, the decent work plan declares that development must not come at the cost of dangerous working conditions, precarious employment, unemployment, child labour and forced labour (United Nations Development Group, 2015).
The changing scenario of development practices both in informal and formal sectors in the past decade reveals the large impact on economic growth of the country. The increasing growth of MSMEs is visualized as a key component towards the economic progress in Bangladesh. As a result, the development of SMEs represents a key element of the reduction of poverty and regional inequality (GOB, 2011). Generally, SMEs are considered as a key job creation source and are much diversified, but with a huge gap in policy formulation to avoid potential risks in working environment. Although SMEs host a big number of micro-enterprises which provide a plentiful source of jobs, they do not have decent working conditions to a large extent (ILO, 2015a). MSMEs cover a total of 31 million employees, which is equivalent to 40 per cent of the total population of Bangladesh in the age group of 15 years and above (Rahman, 2009).
In the environment of globalization and technological change, Bangladesh is going through a process of fast transformation in the formal working environment, leaving the large work force in the informal sector. It is now being accepted that the informal sector has been receiving the large part of the labour force in reality. Now, the government must introduce a policy on labour force to should resolve the neglected issues of the informal sector, which is now perceived as a productive basis of employment. Consequently, the general approach should be improved to ensure decent working conditions and self-esteem of the workers. Sarder (2010) argued that it is important to identify the strength and weaknesses of SMEs, especially in policy-making and policy implementation process. Many studies were carried out on the operational limitations faced by the entrepreneurs, but the unbridle growth of informal sector and the decent working condition have been ignored for long.
State of the art
The concept of decent work
The concept of “decent work” was an expression in the form of quality of labour and was presented in the report of the Director General of the International Labour Conference meeting (87th session) in 1999. The report explained four constituent pillars of decent work – employment, social security, workers’ rights and social dialogue. Employment covers all forms of work, and thus, decent work is relevant to not only workers in formal economy but also workers in informal sector, including self-employed, unregulated wage workers and domestic workers (Ghai, 2003). The concept of decent work integrates fundamental rights of workers and the people who work have rights at work (ILO, 1999a). As per ILO prescription (ILO, 1999a), the essential rights are related with freedom of association, quality of work and the non-appearance of enforced labour and child labour in any abusive form. Finally, social dialogue comprises rights of workers in deliberations with employers regarding work-related issues.
The most notable work on decent work has been done by Anker et al. (2002), who identified 11 statistically measurable dimensions of decent work. Among them, practice of decent working hours, presence of unacceptable works including child labour and the practice of workplace relations through social dialogue are the towering indicators. In our present study, we consider these indicators as the latent constructs of our model in which we try to explore path relationships of these constructs to the work–life balance (WLB) of the entrepreneurs who run their venture by their own.
Decent work: Bangladesh context
In the past 25 years, Bangladesh has been experiencing an incredible economic and political changes that urged for a structure of decent work (ILO, 2013). An advisory body of the decent work pilot programme was formed with an equal representation of the government, workers and employers’ organizations. This forum discussed the issues of decent work in Bangladesh and identified the priorities that include campaign of decent and creative employment; promotion of essential values and rights at work comprising progressive removal of worst practices of child labour; and capability building of the ILO ingredients of the country (Decent Work Country Programme) (Mondal, 2010).
Overall, Bangladesh has achieved a little progress in the past 10 years regarding decent working time, but these changes are limited to only urban areas. Employees working above 48 h per week enlarged from 48.1 per cent in 2005-06 to 51.5 per cent in 2010. This trend is more noticeable among male workers and in rural areas (58.6-65.2 per cent). The opposite picture is seen in urban areas, where the trend is 55.7-52.3 per cent (Decent work country profile, ILO, 2013). But, in the past decade, despite the government’s policies, a large and growing part of the active labour force has been engaged in hazardous work, which is defined in this study as precarious work.
The information gap and lack of sufficient data may weaken and challenge the advancing gains of the decent work paradigm. It is assumed that in many jobs where the working conditions are weak, social dialogue is poorly practiced or livelihood is not sustainable, the idea of decent work is more challenging. The existing labour scenario in the informal sector has always been untouched or partially ignored, which needs to be addressed properly. There is an irresistible need for sufficient WLB through achieving decent work and reducing precarious works in working place.
Precarity as a problem in work–life balance
The term precarious employment has been broadly used for decades in sociology, economics and political science, as well as in the media (Vosko, 2006; Kalleberg, 2009). Over the past decade, the interest in precarious employment in sociological research has grown rapidly. Although there is still a little consensus in defining the concept, several scholars have sketched out definitions of precarity and the broader social environment in which it is embedded (Benanch et al., 2014; Benanch et al., 2016). From the point of view of various researchers, precarious employment is a multidimensional construct that differs across countries and depends on specific economic and social structure of the labour market (Benanch et al., 2016; Bosmans et al., 2016; Pacheco et al., 2014; Moscone et al., 2016).
Researchers define precarious work as a non-standard work (Campbell, 2010; Mantouvalou, 2012; Lightman et al., 2008). Brackpool and Neil (2017) measured precarious work only through job insecurity, and Mantouvalou (2012), based on domestic workers, focussed only on legal dimension and argue that legislative precariousness refers to the explicit exclusion of workers from protective legislation. Pacheco et al. (2014) argue that precarity is a multidimensional phenomenon that is not reducible to a single latent construct, and they recognized six factors to consider a work as precarious: non-standard working hours, employment instability, collective voice, quality of work environment, duration of employment and part-time work.
From a different point of view, Campbell (2010) argues that not all non-standard forms of employment are precarious. Dividing the non-standard employment into three categories, he found that casual waged work is more precarious than marginal self-employment and fixed term waged work. Using the multidimensional employment precarious scale, Vives et al. (2013) assessed precarious work more concretely. The scale comprised 26 items grouped into six subscales: instability (contract duration), disempowerment (individual-level bargaining over, e.g. wages and working hours), low wages (monthly wage/salary, capacity to cover regular or unexpected expenses), rights (entitlement to workplace rights such as sick leave, weekly rest and vacations), vulnerability (defenselessness to, e.g. unfair, violent and authoritarian treatment) and capacity to exercise rights (e.g. maternity/paternity leave and vacations).
As precarious work is increasing and is expanding on a global scale, various researchers intend to explore its impact on workers’ life. But, most of the studies examine the relationship between employment precarity and health status and ascertain that employment precariousness is a social determinant that affects the physical and mental health of workers, their families and communities (Vives et al., 2013; Lewchak et al., 2003; Benanch et al., 2014; Moscone et al., 2016). To fill up the dearth of the existing literature on the relations of precarious working conditions (which is considered as a negative connotation of decent working conditions), our present study explores degree and magnitude of contributions of decent working conditions to the WLB of SME owners (self-employed). That is to say, whether an entrepreneur with better working conditions (specific to particular indicators of decent working conditions) leads to a better WLB situation in his/her life.
There is an increasing popularity of WLB as a topic of academic and practitioner debate and the mounting prevalence of WLB practices in organizations around the world (Kersley et al., 2005). WLB has emerged as a strategic issue for human resource management and a key element of an organization’s employee retention strategies (Cappelli, 2000). It has been argued that organizations need to be aware of the changing needs of employees and provide flexible WLB strategies to retain their employees (Bruck et al., 2002). Psychology at work today is an important phenomenon to keep employees motivated and satisfied to work and perform well (Murthy and Shastri, 2015). This is essential not only for the organizational benefits but also for personal growth and development such as self-confidence, crisis management and problem-solving strategies, even for a self-employed entrepreneur.
Materials and methods
In this study, we chose 800 samples with a maximum iteration of 3,000 samples for bootstrapping analysis for the model. Hair et al. (2014) recommend that sample size can be driven by the highest number of arrows indicating at any latent variable in the model. By following the recommendation of Marcoulides and Saunders (2006), the minimum sample size of our model is 75, as we have six arrows indicating our target latent construct (WLB). Although the recommendation for minimum sample size is 75, we decided to collect as many samples as we can proportionately from different strata (areas under a branch office of BRAC’s Progoti program). Using the survey method, we gathered information from the respondents who run small enterprises and are credit beneficiaries of BRAC Progoti programme. The Progoti is a credit ladder, which has the objective to finance small enterprises. BRAC introduced this credit program especially for small- and medium-sized entrepreneurs. The information of this study has been gathered from a number of regions in Sylhet district of Bangladesh. We isolated the regions by using a proportionate stratified sampling method. In this procedure, the items in the sample are designated among the strata in extent to the relative number of items in every stratum in the populace. That is to state, the bigger the stratum size, the bigger the extent of the sample to be looked over that stratum. We considered enrolling clients secretly as a piece of this populace of the present study.
To establish the relationships between the factors of decent working conditions and the WLB of small entrepreneurs in Sylhet district of Bangladesh, we selected small enterprises that have been financed by BRAC’s Progoti (which is an SME loan ladder of BRAC). We used partial least square (PLS) structural equation modelling (SEM) with a goal to investigate the degree and magnitude of the relationships of the constructs which have been used in a form of path modelling. Path models are diagrams that are used to display hypothetical and variable relationships in a structural equation model (Hair et al., 2014). We demonstrate the constructs that have been used to explain the magnitude and significance of relationships among them (Figure 1).
Do decent working conditions contribute to work–life balance of small entrepreneurs?
Each construct has its corresponding indicators, which have been measured specifically. Constructs are commonly known as latent constructs in the model, as they are measured indirectly. In our model, we have various indicators that have been inserted into a Smart PLS application (Ringle et al., 2015). When we surveyed our respondents, we gathered information on the items that have been used for scaling on a 1-5-point scale. The constructs used in our study followed the measurable indicators of decent work studied by Anker et al. (2003). However, we applied their indicators as constructs in our model. We have seven exogenous (UW, PW, WH, SS, FT, HW, SD) and seven endogenous constructs (UW, PW, WH, SS, WLB, FT, HW) in the model. In this study, we focussed on the endogenous construct WLB.
Quality criteria of the measurement model
According to Hair et al. (2014), a model in PLS-SEM requires its quality criteria testing and needs to qualify the evaluation of structural model and measurement model with satisfactory outcomes. In this present study, we used two different types of assessment processes: internal consistency reliability and the discriminant validity of the model constructs.
For evaluating internal consistency reliability, we prefer to use composite reliability over Cronbach’s alpha. According to Hair et al. (2014), Cronbach’s alpha gives us an estimate of reliability based on inter-correlations of the observed indicator variables, but PLS-SEM prioritizes indicators according to their individual reliability. Additionally, Cronbach’s alpha is sensitive to the number of items in the scale and therefore tends to underestimate the internal consistency reliability (Hair et al., 2014). In a quality criteria assessment, composite reliability has the range of values from 0 to 1, where values above 0.70 are considered acceptable for an exploratory study (Hair et al., 2014; Sarstedt et al., 2014). In Table I, we see that the values for all constructs in the model are well above the satisfactory range.
For the second assessment, for a model to qualify in the assessment of discriminant validity of constructs, the heterotrait–monotrait (HTMT) criterion test has been chosen over Fornell–Larcker criterion. According to Henseler et al. (2015), the classical approaches (i.e. the Fornell–Larcker criterion and cross loadings) do not reliably detect a lack of discriminant validity in common research situations. Therefore, they propose HTMT as an alternative approach to assess discriminant validity of a model. For the quality criteria decision, we need to retain if we observe the HTMT value to be less than 0.90 (although there are some researchers who consider 0.85 as the threshold value). We then conclude that the discriminant validity has been established between two reflective constructs of the model (Henseler et al., 2015). In our present model, we see that the all constructs have the value less than 0.90 of HTMT (Table II). In addition, we run HTMT inference criteria to make a decision about the significance of HTMT values. We found that all upper confidence intervals were below 1, which indicates that the discriminant validity of the model has been established for the constructs involved in the model.
Quality criteria of the structural model
Before proceeding to measure the coefficients of determination (R2) and path coefficients of the model, we need to assess the issue of collinearity among the predictor constructs (Sarstedt et al., 2014). In the Smart PLS application, we use our model constructs to discover any potential collinearity issues among the predictor constructs. We find that all inner variance inflation factor (VIF) values are well below 5.00 (lowest value is 1.00 and the highest value is 1.391). In an SEM, a VIF statistic measures the increase in the variance of an estimated regression coefficient when predictor constructs are correlated. A VIF value between 5 and 10 indicates that two constructs are highly correlated and therefore may be problematic for the model prediction (blog.minitab.com, 2015). We find in Table III that the highest VIF value is 1.391, indicating that the predictors may be in a very negligible association, which has no problematic influence to the model. Therefore, it is not an issue for the estimation of a path model.
Social dialogue and work–life balance
WLB practices at the workplace typically include flexible working options such as flexible hours, child-care and elder-care facilities and information or financial support pertaining to the non-work sphere of life. Such interventions are typically termed as family-friendly policies or work–life benefits and policies (WLBPs) (Osterman, 1995). WLBPs include flexible work arrangements such as flexibility in scheduling time of arrival and departure to and/or from work, flexibility in choosing the place of work and leave in lieu of family reasons.
In our study, we found from the PLS-SEM algorithm that the path coefficients (demonstrated in Figure 1 and Table IV) have some strong causal linkages among the constructs used in the model. It is clearly demonstrated that the social dialogue (indicator of decent work) amongst the borrower-workers has the highest causal relations, with a path coefficient of 0.418 with working hours followed by 0.398 (social dialogue on fair treatment) and 0.396 (social dialogue on WLB). As the significance of the model coefficients depends on their corresponding t-values, the relationships mentioned above have t-values greater than 1.96 (for 5 per cent significance level). Therefore, we concluded that the path coefficients greater than 1.96 are significant to the 95 per cent significance level. Theoretically, WLB practices create a sense of assurance for employees that their organization/employer is supportive of employee well-being and non-work needs. As our study deals with the decent work issues of small entrepreneurs who run their own ventures, we explored to what extent their social dialogue (in the form of social relations) is important to grasp the sense of WLB. According to perceived organizational support theory (Eisenberger et al., 1986) and social exchange theory, the feeling of supportiveness results in higher positive attitudes towards the organization and promotes employee participation and initiative through a felt obligation to give extra attempt in return for additional benefits (Lambert, 2000). We also obtain results that confirm a very good relationship between social dialogue among borrowers and working hours at their workplace. Many researchers, including Alam et al. (2009), studied the correlation between long working hours and work–family imbalance. We conclude in our study that borrowers-workers would have a feeling of organizational support by their own if they participate in their social relations with other borrowers who are also self-employed in the informal sector, such as small enterprises. We also conclude that social relations among the self-employed other workers have a huge contribution to a better work–life situation.
In our study, we found that our second latent variable, fair treatment at workplace, has a very good relation in ensuring WLB situation. In terms of credit and repay facilities, workplace consideration, race, sex, religion, age, disability, political opinion and social origin are critical in guaranteeing WLB. Hsieh et al. (2005) measured WLB among employees in various settings and also identified the direction of spillovers. Rajadhyaksha and Velgach (2009) investigated the differences between men and women in the experience of work interference with family. Loerch et al. (1989) examined the relationships among family domain variables and three sources of work family conflict (time, strain and behaviour based) for both men and women. Murthy (2014) conducted a qualitative study on impact of interpersonal relation and perceived stress on WLB.
In addition to assessing the path coefficients of the relevant constructs in the model, we need to see whether any substantive change to the endogenous constructs occurs (we concentrate on WLB, working hours and fair treatment at work) when we omit a corresponding exogenous construct from the model. For this effect size estimation (f2), assessment guideline values are 0.02, 0.15 and 0.35, representing small, medium and large effects of an exogenous construct on an endogenous construct of the model (Hair et al., 2014).
In the model, we see that the effect size (f2) of exogenous construct social dialogue to working hours is 0.211, followed by 0.188 for social dialogue (SD) to fair treatment at workplace and 0.173 for social dialogue to WLB. Therefore, we conclude that social dialogue has the largest effect on its corresponding endogenous latent variables, including working hours, fair treatment at workplace and WLB of an entrepreneur. Stability and security of enterprise have the largest effects on the model (targeting WLB). In this model, social dialogue and fair treatment at workplace are considered vital indicators of WLB situation. Table V demonstrates the different effect size estimations (f2) of the exogenous constructs with their corresponding endogenous constructs (including WLB).
Stability and security of enterprise to work–life balance
Benanch et al. (2016) elucidated precarious employment as a concept encompassing dimensions of employment insecurity, individualized bargaining relations between workers and employers, low wages and economic deprivation, limited workplace rights and social protection and powerlessness to exercise legally granted workplace rights. From a similar viewpoint, Edralin (2013) also clarified precarious work, and her findings revealed that precarious work is undermining workers’ rights, the scope and coverage of collective bargaining and wages and working conditions.
In our study, the path coefficient of stability and security of enterprise (SS) on WLB is 0.396. This path coefficient is significant to the 95 per cent confidence level. Therefore, we see that this latent variable of decent work has a very good and significant impact on WLB of an entrepreneur. In the model, we find that the effect size (f2) of exogenous construct stability and security of enterprise to WLB is 0.222, which is considered a worthy influence. As this is the largest effect size in the model, we conclude that keeping an enterprise running with stability in regard to financial availability, sustainability and ease of getting credits can ensure WLB of an entrepreneur.
Quinlan (2001), in a review of a number of studies, described that an extensive use of precarious employment is not essentially new, and that is why, all insecure or fluctuating employments, small workshops, home-based work, self-employments and other arrangements may be labelled as contingent works or precarious employments. If we follow Vives et al. (2013), we find that instability, disempowerment and vulnerabilities and capacity to secure rights are important indicators that can enhance decent working conditions at workplace.
Together with social dialogue, the sustainability of enterprise in terms of continuous income generation and financing has the most crucial impact on the harmony between work and non-work life. This explains that a great social association and work environment relations among business runners influence the WLB situation.
Do decent work conditions contribute to work–life balance?
The most common measurement used to assess a structural model is the coefficient of determination (R2), which measures the model’s accuracy and predictive capacity (Hair et al., 2014). In our model, we see in the diagram (Figure 1) that the coefficient of determinant (R2) represents the exogenous constructs’ combined effects on the endogenous latent constructs. The R2 value of a model ranges from 0 to 1 (where 0.20 is considered high in discipline related to consumer behaviour, also in behavioural sciences), with higher values indicating a better level of predictive accuracy (Hair et al., 2014). In this model, we see that the endogenous construct WLB has an R2 value of 0.349, which indicates that the relevant exogenous constructs of the model explain 34.9 per cent variance of the endogenous construct WLB. As the value is above the threshold level of 0.20, we can conclude that the endogenous construct (WLB) can be explained well by the connected predictor constructs in the model. Therefore, as we found, all related exogenous variables can have substantial influence to secure WLB situation. Among them, social dialogue and stability and security of enterprise have the largest effects on WLB. However, social dialogue also has a substantial effect on decent working hours and fair treatment at workplace, which are also considered vital indicators to guarantee WLB of entrepreneurs.
This study aims to explore any contribution of decent working conditions to the state of WLB of entrepreneurs. The results confirm that the social dialogue and the stability and security of the enterprise have the largest effects on an entrepreneur’s WLB. The model also estimates that “social dialogue” has a very good effect on fair treatment at the workplace, which in turn has a very good effect on the “stability and security of enterprise”. Again, social dialogue has a very good effect on the working hours of entrepreneurs.
We infer that in a condition where other constructs remain constant, the performance of WLB of an entrepreneur can be improved if there is an increase in the performance of social dialogue among the entrepreneurs. The same happens to the stability and security of enterprise, which is also responsible in ensuring WLB situation of an entrepreneur. Therefore, we recommend that social relations among borrowers (who are also self-employed venture runners) in the form of formal and informal discussions about various challenges and issues regarding entrepreneurship can lessen the precarious working conditions and advance WLB through ensuring decent working conditions at workplace and developing social relations among small entrepreneurs. We assert that the different factors, with different capacities, of decent working conditions can contribute to the WLB situation of a small entrepreneur.
Composite reliability and R2 of the model
|Unacceptable work (UW)||0.766||0.001|
|Productive work (PW)||0.825||0.048|
|Working hours (WH)||0.723||0.175|
|Stability and security of enterprise (SS)||0.806||0.082|
|Work–life balance (WLB)||0.878||0.349|
|Fair treatment at work (FT)||0.891||0.158|
|Hazardous work (HW)||0.951||0.044|
|Social dialogue at work (SD)||0.796||–|
|Construct||Unacceptable work (UW)||Productive work (PW)||Working hours (WH)||Stability and security of enterprise (SS)||Work–life balance (WLB)||Fair treatment at work (FT)||Hazardous work (HW)|
|Unacceptable work (UW)||–||–||–||–||–||–||–|
|Productive work (PW)||0.469||–||–||–||–||–||–|
|Working hours (WH)||0.311||0.280||–||–||–||–||–|
|Stability and security of enterprise (SS)||0.196||0.197||0.377||–||–||–||–|
|Work–life balance (WLB)||0.216||0.084||0.262||0.545||–||–||–|
|Fair treatment at work (FT)||0.247||0.111||0.482||0.392||0.391||–||–|
|Hazardous work (HW)||0.230||0.055||0.228||0.187||0.148||0.194||–|
|Social dialogue (SD)||0.261||0.138||0.500||0.210||0.547||0.602||0.329|
f2 (First row) and VIF (second row) of the model
|Construct||Unacceptable work (UW)||Productive work (PW)||Working hours (WH)||Stability and security of enterprise (SS)||Work–life balance (WLB)||Fair treatment at work (FT)||Hazardous work (HW)||Social dialogue (SD)|
|Unacceptable work (UW)||–||–||–||0.008||–||–||0.046||–|
|Productive work (PW)||–||–||–||–||0.004||–||–||–|
|Working hours (WH)||–||0.048||–||0.005||0.035||–||–||–|
|Stability and security of enterprise (SS)||–||–||–||–||0.222||–||–||–|
|Work–life balance (WLB)||–||–||–||–||–||–||–||–|
|Fair treatment at work (FT)||–||0.016||–||0.079||0.014||–||–||–|
|Hazardous work (HW)||–||–||–||–||0.000||–||–||–|
|Social dialogue (SD)||0.001||–||0.211||0.001||0.173||0.188||–|
Italic values represent f2 values
|R2 values are shown inside the circle (indicator)|
|Connections and their respective path coefficients are shown below with t-values inside the parenthesis:|
|Social dialogue (SD) to Work–life balance (WLB)||0.396 (4.156)|
|Social dialogue (SD) to Working hours (WH)||0.418 (3.043)|
|Working hours (WH) to productive works (PW)||0.232 (1.842)|
|Social dialogue (SD) to fair treatment at workplace (FT)||0.398 (5.557)|
|Fair treatment at workplace (FT) to stability and security of enterprise (SS)||0.305 (2.355)|
|Stability and security of enterprise (SS) to work–life balance (WLB)||0.396 (4.323)|
Italic data indicate impact of other relevant constructs on the target construct (WLB)
Path coefficients of model (first row) and total effects of exogenous constructs (second row)
|Construct||Unacceptable work (UW)||Productive work (PW)||Working hours (WH)||Stability and security of enterprise (SS)||Work–life balance (WLB)||Fair treatment at work (FT)||Hazardous work (HW)||Social dialogue at work (SD)|
|Unacceptable work (UW)||–||–||–||0.086||–||–||0.209||–|
|Productive work (PW)||–||–||–||–||0.049||–||–||–|
|Working hours (WH)||–||0.232||–||−0.074||−0.178||–||–||–|
|Stability and security of enterprise (SS)||–||–||–||–||0.396||–||–||–|
|Work–life balance (WLB)||–||–||–||–||–||–||–||–|
|Fair treatment at work (FT)||–||−0.136||–||0.305||0.111||–||–||–|
|Hazardous work (HW)||–||–||–||–||0.005||–||–||–|
|Social dialogue at work (SD)||−0.025||–||0.418||−0.039||0.396||0.398||–|
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