Abstract
BACKGROUND:
The Decent Work (DW) concept, proposed by the International Labour Organization, can be enriched by the contributions of a Work, Organizational and Personnel Psychology (WOPP) perspective. Namely, it would be important to relate DW perceptions to the main concepts in the WOPP realm. Understanding these relations would expand our knowledge of the nomological network of the DW concept and of its practical implications.
OBJECTIVE:
To analyze the relationships between DW, work motivation and psychological capital among knowledge workers in Portugal and Brazil.
METHODS:
The Decent Work Questionnaire (DWQ), a previously validated measure of 7 dimensions of DW from a WOPP perspective, the Multidimensional Work Motivation Scale (MWMS), and the Psychological Capital Questionnaire (PCQ) were administered to 2912 knowledge workers. Relations among concepts were analyzed by canonical correlation analyses and linear regression.
RESULTS:
The DW dimension Fulfilling and Productive Work was positively associated with intrinsic and identified work motivation, and negatively with amotivation. A second significant canonical variate related (negatively) Social Protection (DW dimension) to extrinsic material work motivation. Results from regression analysis support the idea that DW promotes psychological capital.
CONCLUSIONS:
Results suggest that DW is an important predictor of work motivation and psychological capital. Practical implications for human resources management are presented.
Introduction
The present research aims to explore the relationships between decent work (DW) [1, 2], work motivation [3] and psychological capital [4], and discuss their implications for business. Decent Work is a concept proposed by the International Labour Organization (ILO) at the International Labour Conference (ILC) in 1999. This concept is the result of a long journey begun in 1919 [5] and its history overlaps the ILO’s history within the United Nations (UN) action [6–10]. Today the globalization and changes witnessed in the economic and work areas bring a remarkable relevance to the DW concept. Due to growing interdependencies, globalization affects local markets (in economic and regulatory aspects) and shared (global) problems are expected to be overcome by joint initiative by governments, businesses and civil society [11]. DW may prove to be a shared social goal for workers in different situations throughout the world.
Considering business agents, there are many developments and implications of the DW concept. The proposition of this concept is in tune with other United Nations (UN) initiatives, such as the Millennium Goals [9] and the UN Global Compact (UNGC) [8]. All of them proposed values to be shared and guide the actions of multiple stakeholders, in order to reach better results for all. Therefore, the success of those proposals depends on their application to practice in people’s daily life. All those initiatives are seen to be inspired in the corporate social responsibility concept [8, 12–14] and in the corporate citizenship concept [11] but go beyond these concepts by try to make people and organizations wake up to global citizenship.
Approaching the DW concept from the perspective of Work, Organizational and Personnel Psychology (WOPP) is recent and underdeveloped so far [15]. The major reason for this underdevelopment is the very limited role played by WOPP in the development of the concept itself. ILO officers and other key people involved in this process were, in the vast majority of cases, trained and working within legal, economic or political domains of expertise. One major consequence of this was that operational definitions of decent work for empirical study have been mainly macro-level statistical, economic, and legal indicators. These approaches are surely important, as are others focused on the worker’s experience. Recently, two instruments aiming to measure the individual experience regarding DW have appeared [15, 16]. In their study delving into the structure and definition of the decent work concept from a psychological perspective, Ferraro et al. [15] have developed the Decent Work Questionnaire (DWQ), and identified a number of dimensions of the concept, presented in Table 1 and assessed by subscales of the instrument.
Decent Work dimensions (DWQ and its subscales)
Decent Work dimensions (DWQ and its subscales)
Fundamental Principles and Values at Work & Justice, dignity, freedom, fair treatment at work, acceptance (without discrimination), clarity of norms, trust, solidarity, participation and mental health. & “I am free to think and express my opinions about my work”. Adequate Working Time and Workload & Decent management of time at work and good balance between working time and time for family and personal life. & “I consider the average number of hours that I work per day as adequate/appropriate”. Fulfilling and Productive Work & Perception that work contributes to the future of new generations, of a connection between work and personal and professional development, and between work and fulfillment (personal and professional). Work is seen as a true creation of value (to multiple stakeholders), and is recognized as worthwhile. & “I consider the work I do as decent”. Meaningful retribution for the exercise of citizenship & Perception that the retribution received for work allows the worker to live life with autonomy and dignity, to provide wellbeing to those depending on the worker, a feeling of personal wellbeing and a perception of fairness associated with what is earned. & “What I earn through my work allows me to live my life with dignity and independence”. Social Protection & Perceptions of being socially protected in case of illness or loss of work, for both the worker and the family, through a system of social security and the prospect of a decent retirement. This dimension expresses the worker’s expectation of what society will or can do in the long term to recognize or repay the worker for committed effort at work. & “I feel that I am protected if I become unemployed (unemployment insurance, government/social benefits, social programs, etc.)”. Opportunities & Perception of the viability of the worker creating his or her own job (entrepreneurship), personal employability and the perspective for retributions, income or benefits to grow. Related to hope or optimism for a better future. & “Currently, I think there are work/job opportunities for an individual like me”. Health and Safety & Perception of being protected from risks to physical health and of having safe environmental conditions at the workplace. & “Overall, environmental conditions in my work are safe and acceptable (temperature, noise, humidity, etc.)”.
SOURCE: adapted from Ferraro et al. [15].
In the present study we approach the Decent Work concept from a WOPP perspective, by examining its relations to two very important concepts in this domain: those of work motivation and psychological capital. Both of these concepts have shown important contributions to many aspects of worker wellbeing and work performance [17, 18]. The possibility of decent work conditions affecting motivation and psychological capital makes theoretical sense. Detailed examination of the relationships between these concepts would provide a better understanding of the consequences of decent work for: a) individual, family, organizational and social wellbeing; b) work efficiency and productivity; and c) social and economic development. Additional validity evidence for the DWQ can also be provided and compared with the results presented in previous research [15].
One further important aspect of our work is its particular attention to the peculiarities of knowledge workers. Knowledge workers are those whose jobs consist of creating, sharing and using knowledge and thus demand high degrees of expertise, education and/or experience [19]. These characteristics are easily associated with the idea of professionals who have stable employment, are well-paid, have opportunity for career advancement, and are treated with respect and equity at work. In addition it is expected they are able to participate in decisions affecting them and enjoy excellent conditions of health and safety at work. This image, however, is often a stereotype, and many workers, especially in recent years, have often been compelled to take precarious, low-paid positions with few labour rights [20, 21]. These problems affect especially the youngest workers [22] who are setting out on their careers. Everyday professional life has shown many cases where these situations also affect workers in other age groups. The literature has concentrated on the situation of temporary work, contingent work or non-standard employment of workers in general, and little attention has been paid to the contingent employment of knowledge workers [23, 24]. Considering the situation of knowledge workers, it seemed to us that application of the DW concept to this group would be particularly timely, and an important broadening of the usual perspective of the labor movement, focused on less qualified, predominantly manual workers.
In complex tasks, optimism, resilience, motivation and self-confidence are particularly important. We can expect these variables to be especially relevant for knowledge workers [19, 25–27]. In this context, our study attempted to investigate the influence of DW on two very important concepts in Work, Organizational and Personnel Psychology (WOPP): work motivation and Psychological Capital (PsyCap) and the consequences for business.
Concerning work motivation, Self-Determination Theory (SDT) is currently the most influential framework for its study. It states that workers can experience different types of behavior regulation (motivation) within a self-determination continuum from amotivation to intrinsic motivation [3]. This model, with improvements introduced by Gagné et al. [28], was employed in our study and is presented in Table 2.
Work Motivation and its dimensions (according to SDT)
“The stem is ‘Why do you or would you put efforts into your current job?”’ [28]. SOURCE: adapted from Gagné and Deci [3]; Gagné et al., [28].
Each different type of motivation occurs with a varying level of intensity in each worker. Workers with more self-determined motivation tend to feel higher psychological wellbeing and organizational commitment, while those at the opposite pole tend to have negative consequences both for them and the organization [29].
In our study, we hypothesized that Global DW would relate positively to the more self-determined types of motivation (identified and intrinsic; H1) and negatively to amotivation (H2). Intermediate types of extrinsic motivation were expected to be less affected by DW conditions (extrinsic material, extrinsic social and introjected work motivation; H3).
We also put forward a number of other hypotheses regarding the relation between decent work dimensions (subscales) and work motivation. Given the major role postulated by the self-determination perspective for autonomy and relatedness (e.g., communication, trust) in promoting the development of autonomous motivation, we hypothesized that Fundamental Principles and Values at Work would relate positively to self-determined identified and intrinsic types of motivation (H4) and negatively to amotivation (H5). Given the role also attributed to competence in promoting autonomous motivation, we hypothesized that Fulfilling and Productive Work (H6), Opportunities (H7) and Meaningful remuneration for the exercise of citizenship (H8) would also be negatively related to amotivation, and positively related to more autonomous types of work motivation (identified and intrinsic). Due to their focus on the achievement of important goals, more than on pleasure and interest, we expected the latter relationship to be stronger for identified and introjected than for intrinsic motivation (H9).
We were less sanguine, and therefore did not put forward hypotheses regarding other dimensions of decent work. Although it might be expected that excessive working hours would lead to amotivation, very often these excesses occur for workers that have high levels of other types of motivation (intrinsic or extrinsic) that potentially neutralize this effect. As for health and safety or social protection, these are less likely to be often present in the mind of workers, and are therefore less likely to influence work motivation. That is particularly true concerning our samples’ characteristics.
SDT is a theory attuned to the concept of psychological capital because it “is designed to explain optimal motivation thereby explaining a host of positive outcomes including wellbeing, performance, resilience, and personal growth” (p. 33) [30]. Mache et al. [31] consider that individual resources as optimism, resilience and self-efficacy have “essential influence on employees’ wellbeing and their ability to cope with work related stress factors” (p. 492).
Psychological Capital (PsyCap), a concept proposed by Luthans, Luthans and Luthans [32], and Luthans and Youssef [33], initially included four dimensions [34]:
“(1) having confidence (self-efficacy) to take on and put in the necessary effort to succeed at challenging tasks; (2) making a positive attribution (optimism) about succeeding now and in the future; (3) persevering toward goals and, when necessary, redirecting paths to goals (hope) in order to succeed; and (4) when beset by problems and adversity, sustaining and bouncing back and even beyond (resiliency) to attain success” (p. 3)
It is already studied that changes in individual psychological capital are related to changes in individual work performance [35] and can influence and shape work environment [36]. Potentially, some individual’s psychological positive state can also receive influence of work context, and considering that, this concept may help in understanding the individual factors impacted by decent work. Decent work is likely to help promote and protect workers’ psychological capital, which is conceptualized as a state and not a trait. More specifically, we hypothesized that Global DW would be positively related to Psychological Capital (H10), with especially strong relationships being found with Fundamental Principles and Values at Work (H11), Fulfilling and Productive Work (H12) and Opportunities (H13).
Decent work is a concept created for promoting economic and social human development in the formal and informal economy. Knowledge workers are hardly seen as suffering decent work deficits. Regardless of possible decent work deficits, complex tasks such as those performed by knowledge workers seem to be more dependent on autonomous motivation as well as on psychological capital. The consequences of an autonomously motivated workforce and high-scoring PsyCap knowledge workers on their performance and wellbeing are evident. The study of the effect of various dimensions of decent work on work motivation and PsyCap is then relevant both for individuals and for organizations.
Participants
Professional groups
Professional groups
(*) E.g., agronomists; air traffic controllers; computer engineers; financial analysts; etc.
Data were collected in a research project that emphasized the work experience of knowledge workers, and therefore these were the largest group in the sample, but other professional groups were also recruited. The data collection for this project occurred between August 2015 and March 2016. The sample was composed of workers in Portugal (n = 1327) and Brazil (n = 1585). The composition of the sample in terms of professional groups is presented in Table 3.
To participate in the research, the following criteria were adopted: a) at least six months of professional experience; b) currently employed; and c) receiving payment for the work carried out. The questionnaire was developed so as to be applicable to widely different work situations: business owners, independent professionals, government or private employees either on permanent or temporary contracts (including domestic workers), student workers, researchers paid by grants, individuals doing internships, trainees or apprentices.
Both samples were approximately balanced with regard to gender. The percentage of women was 58% in the Portuguese sample and 47.9% in the Brazilian sample. Participants’ age was divided into five categories, each spanning 15 years. The distribution of each sample is presented in Table 4.
Age distribution
Educational Level Distribution
Level of schooling was classified in six categories, taking into account the structure of the educational system in each country. Table 5 shows the expected predominance of participants with non-Ph.D. or Ph.D. levels of postgraduate education, given the goals of sample recruitment.
Participants were recruited through professional associations, and by sending an invitation to email addresses on institutional websites where no professional associations were found. Both the association and individual professionals were contacted personally, by phone or email, briefed about the study and presented with the informed consent and the survey. Participants were asked to read and sign the consent form after getting answers to any questions they wanted to clarify by email or by phone. In most cases, the survey was answered online (only 24 questionnaires in the Brazilian sample were administered on paper). Confidentiality and anonymity were assured and also that the results would only be used for research purposes. Participants were also informed that they could discontinue participation at any time. The task took around 20 minutes.
Decent Work Questionnaire (DWQ)
The Decent Work Questionnaire [15] measures decent work conditions, based on the perceptions of workers. The questionnaire was validated for Portuguese and Brazilian populations [15]. Its 31 items can be added together to provide a global DW score, or separately into seven sub-scales: Fundamental Principles and Values at Work, Adequate Working Time and Workload, Fulfilling and Productive Work, Meaningful Remuneration for the Exercise of Citizenship, Social Protection, Opportunities, and Health and Safety. Each item is answered on a 5-point Likert scale, from 1 = “I do not agree” to 5 = “I completely agree”. Sample items can be found in Table 1. The Cronbach alpha in the current study was 0.92 in the Portuguese sample, and 0.93 in the Brazilian sample. Alpha coefficients for DW sub-scales can be seen in Table 10 (for the Brazilian sample) and Table 11 (for the Portuguese sample).
Multidimensional Work Motivation Scale (MWMS)
The Multidimensional Work Motivation Scale [28] is a measure of different types of work motivation according to self-determination theory [3]. The scale has been adapted and validated both for Portuguese and Brazilian populations [Dos Santos NR, Mónico L, Pais L, Gagné M, Forest J, Cabral PF, Ferraro T, unpublished data]. It comprises six sub-scales: amotivation, extrinsic social regulation, extrinsic material regulation, introjected regulation, identified regulation and intrinsic motivation, forming a total of 19 items. Response options are on a 7-point Likert scale from 1 = ‘not at all’ to 7 = ‘completely’. Sample items can be found in Table 2. The Cronbach alpha coefficient for each of the six levels of work motivation can be seen in Table 10 (for the Brazilian sample) and Table 11 (for the Portuguese sample).
Psychological Capital Questionnaire (PCQ)
The Psychological Capital Questionnaire [4, 37] is a 24-item scale with a global score and four sub-scales: Self-Efficacy, Hope, Optimism and Resilience. However, following the original authors‘ approach, we have used only the global scale score. Responses to the PCQ are given on a 6-point Likert scale, from 1 = ‘strongly disagree’ to 6 = ‘strongly agree’. A sample item is ‘I can think of many ways to reach my current work goals’. In the current study we used a previously validated Portuguese version [38]. Cronbach’s alpha in the current study was 0.93 for both samples.
Results
Results of canonical correlation analysis of the relationships of DW factors and levels of work motivation for the Brazilian sample
Results of canonical correlation analysis of the relationships of DW factors and levels of work motivation for the Brazilian sample
*ρ< 0.05; **ρ< 0.01; ***ρ< 0.001. Note. Rc = overall canonical correlation; Rc2 = overall squared canonical correlation; Rdx = redundancy index of work motivation levels given the canonical variate for DW factors; Rdy = redundancy index of DW factors given the canonical variate for the levels of work motivation.
Results of canonical correlation analysis of the relationships of DW factors and levels of work motivation for the Portuguese sample
*ρ< 0.05; **ρ< 0.01; ***ρ< 0.001. Note. Rc = overall canonical correlation; Rc2 = overall squared canonical correlation; Rdx = redundancy index of work motivation levels given the canonical variate for DW factors; Rdy = redundancy index of DW factors given the canonical variate for the levels of work motivation.
Our presentation of results is divided in two main parts. In the first, we examined relationships between DW and work motivation. In the second, we related DW to PsyCap. In each of these, all analyses were carried out in parallel for the Portuguese and Brazilian samples, allowing for replication and for the study of cross-cultural differences in the results. Given that examining relationships between DW and work motivations involved relating the several dimensions of each construct, we employed canonical correlation analysis for this purpose. As for PsyCap, because we used only the global scale score, multiple regression analyses relating it to DW sub-scales were appropriate. In both cases, we then examined zero-order correlations among variables, in search of additional effects masked in multivariate analyses.
Canonical correlations
The relationships among the seven factors of DW and the six types of work motivation were examined using canonical correlation analysis. The results of this are summarized in Tables 6 and 8 for the Brazilian sample, and 7 and 9 for the Portuguese sample.
Canonical correlation analysis (CCA) is a multivariate statistical method for investigation of relationships between two sets of variables. One is considered as the set of independent variables (or the predictor set) and the second the set of dependent variables (or the criteria set) [39]. CCA is conceptually analogous to a simple bivariate correlation between synthetic, latent variables [40]. “A canonical variate is similar to a factor in a principal component analysis, […]. Analogous to factor analysis, a maximum of N variates (factors) can be extracted, which are independent of each other. N is the number of variables from the smallest set” (p. 128) [39]. This type of analysis organizes into latent dimensions “the covariation of the variables from both within and across the two sets” (p. 113) [41] and thus, in situations where multiple dependent and independent variables are observed simultaneously, “canonical correlation is the most appropriate and powerful multivariate technique” (p. 444) [42]. Although not very often used, CCA would be adequate for many purposes in psychological research, where very often the numerous variables of interest can have multiples causes and effects, driven by parallel, independent mechanisms [e.g. 43]. An advantage of CCA is the minimization of Type I error, by analyzing the two sets of variables simultaneously and in terms of latent variables, instead of looking at a very large number of individual correlations [40].
In this study, we performed CCA to explore underlying relations between DW Factors and levels of Work Motivation and to test hypotheses H4 to H9. Analyses were carried out in IBM SPSS Statistics version 22 with the help of STATS CANCORR (an extension bundle from IBM SPSS, installed as part of IBM SPSS Statistics - Essentials for Python) [44]. We used the canonical loadings approach in interpreting canonical functions, which involves examining the sign and magnitude of the structure canonical coefficients (also known as canonical loadings) assigned to each variable in its canonical variate [42, 45].
For each of the samples, four significant canonical functions were produced (see Tables 6 and 7). However, for only two of these did the canonical correlations (RC) that is, the correlation between the linear composites (canonical variates) created for each of the variable sets, attain non-trivial values. Therefore, considering that the other two canonical variates only attained significance due to the large size of the samples, and following the recommendation of Pituch and Stevens [46], we interpreted only the first two canonical variates in each sample.
Interpretable Canonical Functions for the Brazilian sample
Interpretable Canonical Functions for the Brazilian sample
Note. Raw Can. Coeff. = Raw Canonical Coefficient (or unstandardized coefficient); Stand. Coeff. = standardized canonical variate coefficients (or canonical weights); Struc. Coeff. = structure coefficients (or canonical loadings). Percent of variance = Within-set variance accounted for by canonical variates (i.e., proportion of variance times 100). Noteworthy coefficients are indicated in bold.
Other statistical indicators attest the relevance of our canonical functions, Wilks’s λ “represents the variance unexplained by the model, and thus 1 – λ yields the full model effect size” (p. 48) [40]. In the Brazilian sample, the Wilks’s λ value indicates that the full model explains 52% of the variance shared between the two variable set. In the Portuguese sample, it explains 48% of the shared variance. For each canonical function, the percentage of shared variance tells us that, for the Brazilian sample, the first canonical function explains approximately 81% of the shared variance, with the second canonical function explaining an additional 15% The first two canonical functions together accumulate more than 96% of the explained variance. For the Portuguese sample, the first canonical function accounts for 78% of the shared explained variance, and the second canonical function again adds another 15% These two canonical functions accumulate more than 93% of the explained variance (values based on eigenvalues) [47]. For each set of variables, in the first canonical function, for the Brazilian sample, DW factors explained approximately 44% of the variance of work motivation. For the Portuguese sample, DW factors explained 38% of the variance of work motivation. In the second canonical function, for the Brazilian sample, DW factors explained approximately 13% of the variance of work motivation. For the Portuguese sample, DW factors explained 11% of the variance of work motivation (see Tables 6 and 7, values based on Rc2) [47].
These results appear to indicate that the relationships between decent work facets and work motivation are explained by two main mechanisms, upon which the interpretation of the canonical variate should throw light.
Interpretable Canonical Functions for the Portuguese sample
Note. Raw Can. Coeff. = Raw Canonical Coefficient (or unstandardized coefficient); Stand. Coeff. = standardized canonical variate coefficients (or canonical weights); Struc. Coeff. = structure coefficients (or canonical loadings). Percent of variance = Within-set variance accounted for by canonical variates (i.e., proportion of variance times 100). Noteworthy coefficients are indicated in bold.
For each of the two canonical variates, we present, in Tables 8 and 9, the standardized coefficients (canonical weights), structure coefficients (canonical loadings) and cross loadings associated with each variable. The standardized coefficients are the optimized weights of the DW and Work Motivation variables in the estimation of canonical variates, whereas the structure coefficients are the correlations of these linear combinations with each variable. Although authors disagree on which would be the most adequate coefficients for use in interpreting canonical variates, we have decided to follow Hair et al.’s [42], advice and base our interpretation on the structure coefficients, focusing on the highest values of the structure coefficients [47]. Tabachnick and Fidell [48] suggest using a value of 0.30. We decided to use a more conservative value of 0.45 following Joo and Nimon [49], closer to common practice in factor analysis.
Within the DW Factors set both Fulfilling and Productive Work (DW3) and Fundamental Principles and Values at Work (DW1) stand out strongly in the first canonical variate. Additionally, in the Brazilian sample, Opportunities (DW6) also narrowly crossed the threshold. However, a comparison of the correlations indicates that the first variable is a much stronger characteristic of this variate. Within the Motivations set, the significant correlations are positive with intrinsic work motivation, identified work motivation and an inverted relationship with amotivation. This first canonical function appears to indicate that when workers feel their work is Fulfilling and productive, they have a higher degree of the more autonomous types of motivation (intrinsic and identified), and are less likely to be amotivated (which is expected in H4, H5, H6 and H7, the last one for the Brazilian sample only). The absence or lack of the same DW factors (DW1 and DW3) seems to contribute to amotivation. To a lesser extent, respect for principles and values at work, and the perception of opportunities for employment and improved work situations also help lead to this desirable motivational pattern. This pattern of results is also consistent with our hypotheses. Namely, the fact that the most important linear composite of DW variables was positively related to the most autonomous types of motivation, negatively to amotivation and only weakly to intermediate extrinsic types is in agreement with our hypotheses 1, 2 and 3 (these also can be confirmed on Tables 10 and 11). In addition, the strong presence of the Fundamental Principles and Values at Work and of the Fulfilling and Productive Work, and Opportunities sub-scales in this variate is also in agreement with our hypotheses 4 to 6 (H7 was supported only for the Brazilian sample). Only H8 and H9, concerning the role of Meaningful Remuneration, were not supported by the results.
Descriptive statistics and bivariate correlations (Brazilian sample)
Notes: Significant correlations are in bold. **Correlation is significant at the 0.01 level (1 tailed). *Correlation is significant at the 0.05 level (1 tailed).
Descriptive statistics and bivariate correlations (Portuguese sample)
Notes: Significant correlations are in bold. **Correlation is significant at the 0.01 level (1 tailed). *Correlation is significant at the 0.05 level (1 tailed).
The second canonical function was most strongly related to the DW factor of Social Protection (DW5) and, in the opposite direction and only reaching the threshold in the Brazilian sample, Health and Safety (DW7). As for work motivation variables, this second variate is strongly related to extrinsic material work motivation (e.g. money). Therefore, this function appears to indicate that when workers feel they lack adequate social protection, they are highly motivated by extrinsic material gains obtained from work. This pattern, which we had not anticipated in our hypotheses, is open to multiple interpretations addressed in the discussion section.
Tables 10 and 11 present the means, standard deviations and Cronbach alphas of the Global DW and DW factors scores, as well as the Pearson’s correlations of Global DW and these factors with Work Motivation dimensions and PsyCap (in both samples). H1 to H3 were supported in the two samples.
For the Brazilian sample, the correlations between Global DW and the six levels of Work Motivation and PsyCap show that most of them are statistically significant, but only those with intrinsic and identified work motivation (positive) and amotivation
Results of linear regression analysis between the DW factors and PsyCap (Brazilian sample)
Results of linear regression analysis between the DW factors and PsyCap (Brazilian sample)
*ρ< 0.05; **ρ< 0.01; ***ρ< 0.001. Note: B = unstandardized regression coefficient; SEB = Standard Errors of B; β= standardized regression coefficient; R2 = explained variance. Significant correlations are in bold.
Results of linear regression analysis between DW factors and PsyCap (Portuguese sample)
*ρ< 0.05; **ρ< 0.01; ***ρ< 0.001. Note: B = unstandardized regression coefficient; SEB = Standard Errors of B; β= standardized regression coefficient; R2 = explained variance. Significant correlations are in bold.
(negative) are relevant (greater than 0.20), in full agreement with our hypotheses H1 to H3 and H10 to H13. In other aspects, the analysis of individual correlations leads to the same conclusions as the CCA presented above.
Linear regression
Linear regression was used to analyze how DW Factors were related to PsyCap. Results from these analyses can be seen in Table 12 (Brazilian sample) and Table 13 (Portuguese sample).
The results of linear regression analyses indicate R = 0.62 (ρ< 0.001, Brazilian sample) and R = 0.58 (ρ< 0.001, Portuguese sample), showing major effects of DW on PsyCap. DW factors most strongly related to PsyCap are DW3 and DW6, in agreement with our Hypotheses H12 and H13. For both samples, more Fulfilling and Productive Work, Fundamental Principles and Values at Work and Opportunities appear to contribute to greater PsyCap. The effect for Fundamental Principles and Values at Work agrees with our Hypothesis 11, although we expected a larger effect. Meaningful Remuneration for Exercise of Citizenship (DW4), for which we raised no hypotheses, showed a different behavior in each sample, with PsyCap related to greater Remuneration / compensation in the Brazilian sample, but to lower Remuneration / compensation in the Portuguese sample. It may be that economic compensation is perceived differently in each country, but the effects are rather small in both cases.
Zero-order correlations show that Global DW is strongly related to PsyCap as predicted by H10. In other respects, the correlations support the same conclusions we pointed out from the regressions results, the latter having the advantage of eliminating effects of variance shared among DW factors [e.g., showing that most of the effect of Fundamental Principles and Values at Work (DW1) was actually due to its shared variance with other DW factors]. One important exception is the correlation between Meaningful Remuneration for Exercise of Citizenship (DW4) and PsyCap, which is clearly positive even in the Portuguese sample, suggesting that the negative effect found in the regression analysis is most likely an artifact that should be disregarded. The major conclusions to be drawn from this section of the results would therefore be that DW conditions have a very important role in promoting PsyCap (self-efficacy, hope, optimism, and resilience), but that most of this effect is driven by the perception of work as fulfilling and productive, and the perception of professional opportunities in the worker’s current context.
Discussion and conclusions
Findings and implications
From the workers’ perspective, the study has clearly shown that DW has important relationships with Work Motivation and PsyCap. Moreover, it allowed us to pinpoint specific facets of DW that seem to play the most important role in these regards. For a start, Global DW is related to a greater degree of more autonomous types of motivation and a lower incidence of amotivation, but has no strong relationship to more extrinsic types of motivation. On the other hand, DW is even more strongly related to PsyCap (self-efficacy, hope, optimism, and resilience). This result is very relevant given that, according to Avey [50], the antecedents of PsyCap are poorly studied. He highlighted that investigation of how PsyCap can be produced or developed and its corresponding antecedents “can offer insight into organizational policies, human resource management systems, management structures, and leadership practices that enhance overall employee PsyCap for the benefit of the person and the firm” (p. 141). Our results therefore seem very important, as they show the potential of the DW concept, when looked at from a WOPP perspective, as an important contribution to the motivation and resilience of employees, with the important gains known to come from these variables in terms of worker productivity and commitment [18, 52].
A second aspect to be highlighted from our results is that, among the DW factors, Fulfilling and Productive Work is the one most consistently related to the variables we studied. Opportunities also seem to play an important role both in terms of work motivation and PsyCap, while Fundamental Principles and Values at Work only seems to play a relevant role on work motivation, having a minor role in PsyCap.
The two canonical functions found, however, compound the picture by showing the role of a second mechanism relating DW to motivation: lower perceptions of Social Protection seem to increase concern for extrinsic material work motivation (e.g. money). This effect is compounded, however, by additional effects of employment Opportunities and Health and Safety perceptions. Although these effects could be given several interpretations, we would like to put forward some of our own. Thus, while the first function may be associated with more psychological (e.g., intrinsic) work motivations, the second would be related to economic motivations. The latter may, then, represent some kind of trade-off between Social Protection and economic compensation, in the sense that, with higher pay, workers might be able to purchase private social protection (e.g., health insurance, pension plans), while those that enjoy greater social protection might be willing to work for lower pay in exchange for it. This interpretation is supported by the presence of Opportunities with a relevant effect in this regard. In fact, it makes sense that, if the worker perceives greater professional opportunities in the economic environment, Social Protection might lose some of its attractiveness in exchange for the prospect of higher pay and taking greater risks in employment terms. This may be related to a profile of workers who think they have great job security. But other variables might also be involved.
A somewhat surprising result appeared, however, related to this second canonical function, and involving Health and Safety. In the Brazilian sample, but to a lesser degree also in Portugal, perceived high Social Protection and low extrinsic material work motivation were related to lower perceived Health and Safety conditions at work. Again this might have several interpretations. It might be that the lower investment in workers manifest in lower remuneration corresponds to a lower investment in their health and safety as well, and again this is compensated, from the worker’s point of view, by increased Social Protection, creating what would be a kind of bipolar labor market.
It should also be noted that this pattern of results ensures that all the main types of work motivation are influenced by decent work conditions. While factors more proximal to the work itself tend to influence the more autonomous aspects of motivation (and their polar opposite, amotivation), the intermediate (extrinsic) type are influenced by the more distal aspects (health and safety, social protection), which are, therefore, not without importance. Perhaps more surprising is the lack of an effect of Adequate Working Time and Workload, which might be expected to be positively related to autonomous types of work motivation and negatively to amotivation. One possible explanation for the absence of such an effect is the composition of our sample and the likely role of professionals’ intrinsic motivation in their long work hours [e.g. 53]. This role of intrinsic motivation in the acceptance of extended working periods would work against, and possibly neutralize or even invert, the expected effect (see section highlighting the particular attitudes of knowledge workers below).
Also perhaps surprising was the lesser effect of the Fundamental Principles and Values at Work, when compared with Fulfilling and Productive Work. It is possible that this minor role was influenced by our choice of constructs to be related to DW perceptions. It seems possible that Fulfilling and Productive Work and Opportunities would be related to more positive feelings regarding work, while disrespect for Fundamental Principles and Values at Work would be at the source of more negative feelings.
Another important aspect of our work is the focus on knowledge workers. According to Mládková, Zouharová and Nový “literature lacks research on the topic of motivation of knowledge workers” (p. 775). They “identified four important categories of motivating factors: achievement of objectives, satisfaction, character of work, and freedom, and two important categories of demotivating factors inefficient use of knowledge worker energy and low moral qualities of manager” (p. 775). In line with these findings, Knowledge workers (KW) have important characteristics to be considered. They are more independent, responsible for their own work. They appreciate being in control of their work (self-control) and the rights and power related to it. They also tend to be more loyal to their profession or occupation than the employer in pursuing self-actualization. They are creative and realize self-value. They seek job autonomy, opportunities for growth, individual and professional achievement, decision participation, and job challenge [25, 27]. Lord and Farrington [54] compared differences and similarities between younger and older Knowledge Workers. They found that “a strong intrinsic motivator for both age groups is the fact that they enjoy and take pride in the job they do” (p. 25), it means, that for all ages, intrinsic motivation is the essence of KW motivation. And, “differences appear to increase the value of the older workers’ to the organization” (p. 25). What we find regarding the interaction between DW and the pattern of motivations (CCA), i.e., the intense canonical correlation between Fulfilling and productive work and intrinsic work motivation, may be a translation of these characteristics in these workers’ practice. The second canonical correlation (commented on previously) seems more related to the type of bond held by workers (job security). However, the very intrinsic motivation most common in KW may also be dominant, which in this case would justify what we find in both samples. Concerning the interaction between DW and PsyCap (regression analysis), once again, Fulfilling and productive work emerged as an important factor for development of PsyCap, followed by Opportunities. That may be related to the characteristics of KW or represents the common desires of any worker. These differentiated characteristics suggest special attention to management of this type of workers. Future study will be important to clarify these possibilities.
For business agents, the results show that: a) the more autonomous types of work motivation are related to DW, which suggests that autonomous motivation can be promoted through improvement of DW. At the same time, amotivation seems to be prevented by the same strategy; b) Furthermore, by strengthening DW, workers’ PsyCap will be improved. Both variables are part of wellbeing at work and related to work performance as stated by Luthans, Avey, Avolio and Peterson [17] and Baard, Deci and Ryan [18].
Considering the DW factors, we point out Fulfilling and Productive Work, Fundamental Principles and Values at Work and Opportunities since they have the strongest positive relationship with more autonomous work motivation and PsyCap. This is relevant for managers and business leaders to define human resources management strategies and design practices aiming to improve intrinsic or identified work motivation and PsyCap.
The second canonical correlation suggests that high social protection (perceived as job security) relates negatively to extrinsic material work motivation. Job security can be promoted through improved health, safety and social protection (according to the job function, business sector and social security system of the specific country). The sub-systems of compensations, rewards and developmental opportunities can be the basis for this kind of management action. Developmental opportunities were added here, considering the high loading of the Opportunities factor in the second canonical correlation. Additionally, the findings of the linear regression suggest that the strength of Meaningful Remuneration for the exercise of citizenship can be considered as promoting PsyCap.
As mentioned before, the lack of an effect of Adequate Working Time and Workload on work motivation and PsyCap might be related to the characteristics of the samples. Knowledge workers are usually more intrinsically motivated and are willing or resigned to work long hours [e.g. 53]. However, our research does not suggest that business leaders can neglect this important aspect of DW. In the future, more accurate research (namely qualitative research) can bring a deeper understanding of the role this dimension plays in the dynamics of work motivation and PsyCap.
Considering the relationships found, our study suggests that a decent job/work is highly motivating. Therefore, the business agenda should include DW as a priority in improving workers’ wellbeing and performance.
Limitations and recommendations for future research
Although the results of our study are generally consistent with the hypotheses presented, it is not possible at this preliminary stage in the research to address issues of causality. With regard to the theoretical contributions, this study examined the intuitive link between DW and Work Motivation and between DW and PsyCap. The recent investigation of DW from a Work, Organizational and Personnel Psychological (WOPP) perspective does not allow comparison and contrasts with previous studies.
Regarding the sample, we focus on knowledge workers, a group with homogenous characteristics (i.e. people that work intensively with knowledge and are highly educated). Future studies should replicate our research in other professional groups. Furthermore, the study was conducted in two countries. Although this is better than what is found in most research articles, it should be given continuity by new studies in other cultures. The specific characteristics of the samples might have contributed to some results, and qualitative research can add important inputs to understanding of the relation between the concepts analyzed here, as mentioned in the previous section.
Finally, the present study used a cross-sectional design, which restricts the possibility of causal inferences. The use of a self-administered questionnaire has also known limitations. For future research, a longitudinal design could offer more information about causal mechanisms and about changes in levels of DW, work motivation and PsyCap over time. This kind of design could also bring important data concerning life-cycle changes in the relevance of decent work dimensions throughout life [55, 56].
Conclusion
DW is a relevant concept and we are just at the beginning of research on this subject from a WOPP perspective. This study provided evidence that the presence of DW is able to encourage intrinsic and identified work motivation, to avoid amotivation and contribute to increasing PsyCap. We consider these as highly relevant data. They indicate that the promotion of DW could improve workers’ performance and organizational effectiveness and additionally, could be essential for the strategic management of people at work. The aim of this study was to investigate the relationship between DW and Work Motivation (according to SDT) and DW and PsyCap among knowledge workers in two different cultural settings: Portugal and Brazil and discuss some business implications. The two sets of multivariate variables (DW and work motivation) have two strong dimensions of association (two canonical functions). The relation between DW and PsyCap was also proved relevant. People managers and Work, Organizational and Personnel Psychologists can help leaders and managers to promote DW in their work settings. This might provide a major contribution to intrinsic work motivation and PsyCap of workers, enhancing their wellbeing in the workplace.
Conflict of interest
None to report.
Footnotes
Acknowledgments
This study was supported in part by grant from the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), Ministry of Education of Brazil, Brasília, DF, Brazil (Process Nº BEX 9703/13-6).