• 57 •
Anduli
Revista Andaluza de Ciencias Sociales
ISSN: 1696-0270 • e-ISSN: 2340-4973
HOW DOES EMOTIONAL SALARY INFLUENCE JOB
SATISFACTION? A CONSTRUCT TO BE EXPLORED
¿CÓMO INFLUYE EL SALARIO EMOCIONAL EN LA
SATISFACCIÓN LABORAL? UN CONSTRUCTO POR
EXPLORAR
Gustavo
Díaz-García
Universidad Nacional de
Costa Rica
gustavo.diaz.garcia@una.cr
https://orcid.org/
0000-0002-2840-5048
David
Almorza-Gomar
Universidad de Cádiz,
España
david.almorza@gm.uca.es
https://orcid.org/
0000-0002-2004-2799
Gerson
González-Arrieta
Universidad de Costa Rica
gegonzaleza@racsa.go.cr
https://orcid.org/
0000-0002-8184-4963
Abstract
The objective of this research is to ex-
plore the empirical link between the di-
mensions of emotional salary and job
satisfaction in the time of COVID-19, sta-
tistical studies of which are quite scarce
in the environment of emerging markets.
To address this gap in the literature, a
survey of 190 executives of companies
in Costa Rica was done during the rst
half of 2021. This analysis uses a mul-
tiple hierarchical model and structural
equations to empirically demonstrate
that the creation of value dimension, the
strategic dimension, the motivational di-
mension and the human dimension of
the emotional salary construct of Quin-
tero and Betancur affect the job satisfac-
tion dimension of Costa Rica’s human
capital. The results show that there is a
signicant relationship between each of
the aforementioned dimensions of emo-
tional salary and the dimension of job
satisfaction.
Keywords: satisfaction, emotion-
al salary, motivation, human capital,
competitiveness.
Resumen
El objetivo de esta investigación acadé-
mica es explorar el vínculo empírico entre
las dimensiones de salario emocional y la
satisfacción laboral en la época del CO-
VID-19, cuyos estudios estadísticos son
bastantes escasos en el entorno de los
mercados emergentes. Para abordar este
gap existente en la literatura se ha lleva-
do a cabo una encuesta a 190 directivos
de empresas de Costa Rica en el primer
semestre del 2021. Dicho análisis se ha
efectuado mediante un modelo jerárquico
múltiple y ecuaciones estructurales con la
nalidad de demostrar empíricamente que
las dimensiones creación de valor, estraté-
gica, motivación y humana del constructo
salario emocional de Quintero y Betancur
(2018) inciden sobre la dimensión sa-
tisfacción laboral del capital humano de
Costa Rica. Los resultados muestran que
existen una relación signicativa entre
cada una de las dimensiones señaladas
anteriormente del salario emocional con la
dimensión satisfacción laboral.
Palabras clave: satisfacción, salario
emocional, motivación, capital humano,
competitividad.
Como citar este artículo/citation: Díaz-García, Gustavo; Almorza-Gomar, David; González-Arrieta, Gerson (2023).
How does Emotional Pay influence Job Satisfaction? A Construct to be explored. ANDULI 23 (2023) pp. 57-82.
http://doi.org/10.12795/anduli.2023.i23.04
Recibido: 19-06-2022. Aceptado: 01-10-2022. Publicado: 10.01.2023. http://doi.org/10.12795/anduli.2023.i23.04
Anduli • Revista Andaluza de Ciencias Sociales Nº 23 - 2023
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1. Introduction
Human capital is one of the most important assets that companies possess in order
to compete in the globalised market (Tarigan et al., 2021). Hence the importance for
organisations to carry out strategic management aimed at creating an atmosphere
that stimulates not only the job satisfaction of their employees but also their motivation
and commitment to the company’s mission and objectives (Thompson and Gregory,
2012). An excellent way to achieve these goals is to engage in non-monetary
remuneration models. It is an under-researched aspect of the human resources and
business organisation literature. It is motivated by the neoclassical view that people
work to earn money and not to enjoy more excellent job stability, quality of life, and
interpersonal relationships, among others (Terry et al., 2022; Lee et al., 2020).
In this context, the concept of the emotional wage arises as a non-monetary
compensation instrument created to improve individuals’ satisfaction and happiness
in their daily job performance (Quintero and Betancur, 2018; Gay-Puyal, 2006).
Therefore, the emotional salary is an engaging intangible resource that contributes
positively to the generation of a sunny climate within organisations (Faiza et al., 2019;
Yeol-Kim et al., 2018; Melo-Martínez et al., 2018; Montalvo-Poveda, 2018).
The economic crisis caused by the Covid-19 has led, among other things, to the
fact that the top management of companies is rapidly implementing emotional pay
in their remuneration policy models. It is mainly because using this element means,
on the one hand, not increasing the wage bill of their human capital (Salvador-
Moreno et al., (2021). On the other hand, emotional pay plays a vital role not only in
improving the competitiveness and productivity of companies but also in increasing
organisational commitment and the job satisfaction of their internal customers (e.g.
Inayat and Jahanzeb, 2021; Frankort and Avgoustaki, 2021; Sushmita et al., 2020;
Petit, 2019; Yoel-Kim et al., 2018; Skelton et al., 2018; Cassar et al., 2018; Castillo et
al., 2017; Ahmad, 2017; Poveda-Burgos et al., 2017); Kosfeld et al., 2017; Espinosa
and Toscano, 2017; Cuesta-Santos, 2016).
Based on what we have read so far, the authors of this academic work want to explore
empirically whether emotional pay directly inuences employees’ job satisfaction
in emerging economies, such as Costa Rica. A country characterised by social
inequalities and a labour market does not stimulate stability and worker productivity
(OECD, 2018).
Finally, this article is structured as follows. The rst section reviews the literature
on the psychosocial dimensions of emotional pay and job satisfaction. The second
section explains the research methodology used in this study, which was a structural
equation model. The third section describes the empirical results obtained in this
scientic work. Finally, the conclusions, limitations and future lines of research are
presented.
2. Literature review
In this section, we will carry out a brief literature review of the dimensions that make
up the corpus of this research. These are emotional pay and job satisfaction. This
literature review will serve as a basis for an empirical analysis of the relationship
between the two variables that are the object of this scientic study.
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2.1 The emotional wage
Expectation theories show that companies’ non-monetary compensation schemes
positively impact their internal customers’ job satisfaction. From a human resources
point of view, this leads to two fundamental factors: companies enjoy lower employee
attrition rates, and the attraction of future creative talent is signicantly improved
(Hsingkuang et al., 2017; Cherif, 2020; Tarigan et al., 2021).
In parallel to this academic research, Quintero and Betancur (2018) empirically show
that the construct of emotional pay is affected by the following dimensions: human
management, strategic management, motivation and value generation. For Rocco
(2009) and Prakash (2017), emotional pay strongly predicts employees’ organisational
commitment and job satisfaction. In this sense, Gil-Vera et al. (2019) state that the
variables of motivation and strategic management of companies are directly related
to the two dimensions of this study.
The emotional salary construct plays a transcendental role in organisations that want
to implement management models aimed at encouraging the philosophy of happiness
management, as well as the job satisfaction of their internal customers in the current
globalised market (Ong et al., 2018; Uma and Madhusmita, 2017; Kuvaas et al., 2017;
Ravina-Ripoll et al., 2022; Foncubierta-Rodríguez, 2020). Under this magnifying
glass, the top managers of organisations must stimulate the emotional wage variable
as one of the ways to successfully achieve the objectives set by management (Lin,
2020; Collings and Isichei, 2018). One of the ways to achieve this goal is to associate
emotional pay with employee motivation, commitment and job satisfaction in today’s
globalised market (e.g. Chih-Hui et al., 2022; Söderlund et al.,2021, Colaco and Loi,
2019; Valk and Yousif, 2021).
In light of this literature, the emotional wage dimension can be conceptualized as
a non-monetary HR practice that enhances employees’ corporate happiness and
social and family well-being (Núñez-Barriopedro et al., 2021; Weisz et al., 2020;
Ravina-Ripoll et al., 2019). In this way, organisations can increase productivity,
intrapreneurship, efciency, error tolerance, and commitment (Haque, 2017; Chiang-
Vega et al., 2018; Velte, 2019). Hence, companies must gradually implement
emotional pay in their incentive and human resources policies. Examples of this
are DHL, Cisco, Salesforce, Hilton, 3M, SAP, Roche, AT&T, Stryker, Novo Nordisk,
Johnson & Johnson, Inditex, Novartis, EY, Cadence (Great Place to Work, 2021).
These companies are characterised by encouraging emotional pay as a valid
instrument for attracting creative talent to their organisations in today’s digital society.
2.2 Job Satisfaction.
For Anderson et al. (2007), Rožman et al. (2021) and other authors, job satisfaction is
dened as a pleasant and positive emotional state that workers enjoy while developing
their professional position. Under this approach, job satisfaction becomes a vital
strategic asset for organisations to improve their competitive position in the globalised
market (Salessi and Omar, 2016). In this regard, Elrehail et al. (2019), Cai et al. (2019),
Wojcik (2012) and Wright (2010) empirically show that the construct of job satisfaction
proactively stimulates self-esteem, subjective well-being, corporate happiness and
enthusiasm for internal customers of corporations. Therefore, the leadership styles of
companies should be aimed at cultivating the job satisfaction of their human capital
from the guiding principles of productive efciency, intrapreneurship, organisational
justice and operational functionality (Marshall, 2020). In this way, employees will have
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less desire to leave the organisation, as they perceive their work environment as a
source of motivation and quality of life (Gil-Vera et al., 2019).
A careful reading of recent scientic studies on job satisfaction reveals this concept’s
cross-cutting and multidisciplinary nature. It is basically because this term is affected
by multiple factors of a psychosocial nature, such as monetary remuneration, job
stability or interpersonal relationships (Meemken et al., 2019; Shrotryia and Dhanda,
2019; Springer, 2011; Siqueira, 2008). In this burgeoning line of research, multiple
papers are emerging that explore the statistical relationship of job satisfaction with
other parameters linked to human resource policies, including turnover intention,
organisational commitment, employee loyalty and job performance (e.g., Lee et al.,
2021; Jawaad et al., 2019; Ahmad, 2017).
In contrast to this study, Siqueira (2008) argues that job satisfaction is directly
inuenced by the monetary remuneration dimension rather than by an environment
that generates a positive climate within organisations. In this line of research, Young
and Gavade (2018) and Madera et al. (2018) indicate that although job satisfaction
is strongly conditioned by money, it can observe how, little by little, job satisfaction
is becoming consolidated in the cultures of companies as an intangible resource
that workers highly demand. Consequently, it is not surprising that authors such
as Stefanovska-Petkovska et al. (2019) highlight that the job satisfaction construct
should be analysed comprehensively to explore its contribution to the productive
efciency of its human capital in the short and medium-term.
Based on the literature consulted for the development of this article, the following
research hypothesis is proposed:
H1. Emotional pay positively inuences job satisfaction.
Figure 1. Theoretical Model.
3. Methodology
3.1 Sample
For the practical realisation of this work, the authors of this article carried out an online
survey through the social network LinkedIn during the rst half of 2021. Two facts
justify the choice of this technique. The rst is its low economic cost (Schmidt, 1997),
the second is its anonymity, which leads to more honest responses (Nederhof, 1985),
and the last is its autonomy in answering the questionnaire, which facilitates greater
participation by respondents (Evans and Mathur, 2005).
This empirical research is exploratory, descriptive, quantitative, quantitative,
correlational, cross-sectional and of non-probabilistic convenience. The target
population for this study was 190 senior managers of Costa Rican companies with
more than 250 employees. Of the 190 people surveyed, 86 were from the service
sector, 42 from the education sector, 29 from the industrial sector, 16 from the nancial
sector, eight from the consultancy sector and ve from the IT sector. It assumes an
overall condence level of 95% and a maximum error level of 9.2%.
Artículos • Gustavo Díaz García, David Almorza Gomar, Gerson González Arrieta
• 61 •
Table 1. Sample information
The total range of
enterprises with
+250 workers in
Costa Rica
Participation Non-participation
Absolute Relative Absolute Relative
Services 471 86 18,26 385 81,74
Education 46 42 91,30 8,70
Industry 235 29 12,34 206 87,66
Financial and Insurance 185 8,65 91,35
Consultancy 31 8 25,81 74,19
IT, Scientic and
Technical 124 5 4,03 95,97
Entertainment and
recreation 0 0 100
Human health and social
care 29 0 0 29 100
Total 1123 190 16,92 933 83,08
Z α/2 1,96
DS 157,48
Error 9,210
Source: National Institute of Statistics and Census of Costa Rica and own elaboration, (2020).
From the data provided, it can see that the response rate was 16.9%. About the proles
of the people surveyed, most of them are female (57%), work in public companies
(51%), have a university education (53%) and are aged between 18 and 30 (39%).
In addition to the above, and in order to be able to carry out an exploratory factor
analysis (EFA) with the minimum guarantees of our theoretical model, a Chi-square
analysis applies to check whether the type of company is subject to non-response bias
problems. The result was a p-value of 0.00 with a condence level of 95%. Behind
these gures is a strong dependence between business type and non-response to
the survey. The most signicant discrepancy occurs in the human health, social care,
nancial and industry sectors, which could be because these organisations are the
rst level of response to the Covid-19 crisis.
3.2 Measurements
All primary constructs are measured on a 5-point Likert-type scale (1 = strongly
disagree, ve = strongly agree).
3.2.1 Emotional wage
The Quintero and Betancur (2018) scale use to analyse the emotional wage parameter.
This questionnaire is composed of 34 questions to measure this construct based on
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the dimensions: strategy, motivation, human management and generation of value in
the emotional wage (Appendix A).
Next, exploratory factor analysis determines the dimensionality of the 34 items that
make up the emotional wage parameter. Principal axis factorisation with a varimax
rotation uses. The factor matrix analysis revealed a single-factor solution with an
eigenvalue greater than 0.76, explaining 70.5% of the variance. All item loadings
scored above 0.70. It veries the relevance and internal consistency of the items
that make up the emotional wage dimension. Subsequently, the Cronbach’s Alpha
statistical test was carried out by the data obtained, resulting in an α=0.98 (refer
to appendix D). This value shows the reliability of the scale used to measure the
emotional wage variable.
3.2.2 Job satisfaction
Job satisfaction was measured with the Hackman and Lawler (1971) scale. This
questionnaire consists of 4 questions related to pay, job security, peer relations and
supervision (see Appendix B). This construct showed acceptable equivalent reliability
(α=0.89). On the other hand, exploratory factor analysis was conducted to determine
the dimensionality of the four items of the job satisfaction variable. For this purpose,
principal axis factorisation with a varimax rotation uses. The factor matrix analysis
revealed a one-factor solution with an eigenvalue above 0.865, explaining 67% of the
variance. All item loadings scored above 0.70. It veries the relevance and internal
consistency of the items that make up the job satisfaction dimension.
3.2.3 Control Variables
This study controls for the variables gender, age, education, type of organisation and
number of employees to minimise the possible biases that these control variables may
have on the results of our research. The results show no signicant differences in the
control variables sex, age and number of employees for the variable emotional salary.
The same is not valid for the variables education and type of organisation, which
show signicant differences at p=0.01. Behind this nding, we nd that both variables
signicantly inuence emotional wage. About the dimension type of organisation, it
can see that employees in private companies attach greater importance to emotional
pay than employees in public companies.
Regarding the job satisfaction dimension, the results indicate no signicant differences
in the control variables gender, age, education, type of organisation and number of
employees at p=0.01.
Table 2. ANOVA and Post-Hoc tests. Emotional Wage and Job Satisfaction.
Emotional Salary
Sex Age Education Type of
organisation
Number of
employees
Media 3,78 3,78 3,78 4,31 4,31
Standard
Error 0,06 0,07 0,92 0,05 0,05
95% CI LI 3,65 3,65 3,65 4,22 4,22
95% CI LS 3,91 3,92 3,92 4,40 4,40
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Job Satisfaction
Sex Age Education Type of
organisation
Number of
employees
Media 4,31 4,31 4,31 4,31 4,31
Standard
Error 0,62 0,04 0,45 0,04 0,62
95% CI LI 4,22 4,22 4,22 4,22 4,22
95% CI LS 4,40 4,39 4,39 4,39 4,39
Multiple Comparisons
Emotional
Salary
Difference in
averages Error Sig.
Sex 0,83 0,06 0,96
Age 0,88 0,07 0,16
Education 0,74 0,92 0,52
Type of
organisation 0,01 0,05 0,00
Q Employees 0,83 0,05 0,36
Job
Satisfaction
Difference in
averages
Error Sig.
Sex 0,63 0,62 0,62
Age 0,41 0,04 0,53
Education 0,86 0,45 0,86
Type of
organisation
0,13 0,04 0,13
Q Employees 0,66 0,62 0,62
On another note, the control variables were chosen based on the recommendations of
Lee et al. (2021), Yoel-Kim et al. (2018) and Bernal (2016), whose previous research
has shown that these control variables systematically affect the answers given by the
respondents, considering their particular characteristics and can directly inuence the
design and the objective pursued by the research (Bernal, 2016).
In this sense, a human talent that has been with an organisation for a long time tends to
respond less favourably than novices (Gómez-Garbero et al., 2019). A similar situation
occurs with the education variable, where employees with a higher educational
background have a broader view of the organisation and its business activity (Weisz
et al., 2020); furthermore, concerning the number of employees variable it has been
taken by the suggestion of Errichiello and Pianese (2019), who argue that the number
of employees could be inuenced by the size of the organisation and differentiated
business practices.
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3.3 Data analysis
The Kayser-Meyer-Olkin (KMO) statistic and Bartlett’s test of sphericity (see Appendix
C) were used to verify the adequacy of the exploratory factor analysis of the items
that make up the emotional wage construct. KMO’s measure of sampling adequacy
(.957) and Bartlett’s test of sphericity (χ2 = 31.30; gl = 561; p < .000) indicate that our
inferential analysis can be performed. The exact process was carried out for the job
satisfaction dimension, resulting in a KMO measure of adequacy (.759) and Bartlett’s
test of sphericity (χ2 =44.24 gl = 3; p < .000). These data show, on the one hand, that
all the items that make up the job satisfaction variable are sufciently robust and, on
the other hand, that the four items ideally assess the construct above. In sum, Table
3 shows the means, standard deviations and correlations between the two variables
that make up the corpus of our academic work. The test of bivariate correlations
through Pearson’s correlation coefcient test reveals the distribution of the bivariate
data and the linear and ordinal strength of the emotional wage parameter on job
satisfaction (0.31).
Bivariate Correlations, Means and Standard Deviations
for the variables in our theoretical model.
SE SL
1. Emotional Wage 0,31**
Job Satisfaction 0.97**
Media 3.79 4.31
Standard deviation 0.93 0.63
**Correlation is signicant at p<0.001 (bilateral).
4. Results
In order to explore the relationship between the dimensions that make up the object
of this research, the technique of the structural equation by the covariance method
(CB-SEM) was used using the SPSS-AMOS version 28 programme. This technique
allows the relationships and interactions of items and dimensions to be determined
simultaneously, making it possible to determine the relationship between emotional
salary and job satisfaction.
According to Escobedo-Portillo et al. (2016), these structural equation models
establish the dependence relationship between variables, integrate a series of linear
equations, and establish which are dependent or independent of others. This technique
is considered an extension of several multivariate techniques of multiple regression,
factor analysis and path analysis because it incorporates abstract and unobservable
constructs such as latent and unobserved theoretical variables, allowing for better
analysis (Bollen, 1989).
Before assessing and estimating the validity of our structural equation model,
Cronbach’s alpha and Composite Reliability Index (CFI) tests were carried out to
measure reliability. Both statistical tests recommend values above 0.700. On the other
hand, the average variance extracted (AVE) test uses to assess convergent validity,
which should be above 0.500 (Hair et al., 2014). In this regard, it should be noted that
for Fornell and Larcker (1981), a construct is endowed with discriminant validity if its
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AVE is greater than the squared correlations between this construct and the other
constructs that make up the model, which shows that one construct is different from
another. The results achieved in the different statistical tests show the validity and
reliability of our theoretical model.
Table 4. Convergent and discriminant validity
Dimensions Cronbach’s Alpha - α Composite Reliability
Index - CFI
Average Variance
Extracted - AVE
Emotional wage 0.980 0.787 0.681
Job satisfaction 0.855 0.701 0.623
Source: own elaboration.
From these numerical data, SPSS-AMOS version 28 statistical software was used
to evaluate our structural equation model by generating a complex network of linear
interrelationships (Lévy, 2003; Escobedo-Portillo et al., 2016). This programme
produced the illustration shown below.
Figure 2. Structural Equation Modeling.
Source: own elaboration.
Once the structure of our econometric model was graphically specied, we proceeded
to examine, by the stepwise method, the correlation between emotional wage and job
satisfaction (β= 0.318, RMSEA (95% CI) = (0.095; 0.629), p-value=(0.005). These
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results allow us to afrm that emotional wage has a positive impact on job satisfaction
in our sample population.
Table 5. Model Coefcients
Model Standardised coefcient Unstandardised coefcient
Emotional
wage-job
satisfaction
βStandard
Error BRMS
(95% CI) P-value
0.318 0.162 4.215 0,095 0.005**
Source: own elaboration.
The next step to be undertaken is the analysis of the goodness of t of the model
proposed throughout these pages. To this end, it was decided to apply the criteria of
Hu and Bentler (1999). They state that a good model exists when the Comparative
Fit Index (CFI) is more signicant than (0.9), the Tucker-Lewis Index (TLI) is more
signicant than (0.9), the Goodness of Fit Index (GFI) is more signicant than (0.9),
the Root Mean Square Error of Approximation (RMSEA) is less than 0.05, and the
Chi-Square Index (x2/gl) is less than 2.
Table 6. Model Fit Indicators
IFC TLI GFI RMSEA) Chi-Square (x2/gl)
0.854 0.844 0.754 0.095 1788.770/660
Source: own elaboration.
About the hypothesis in this scientic study, the following table shows the parameter
estimates in the “effect” column between the emotional wage and job satisfaction
dimensions. For this purpose, the measurement error, the critical ratio, which is the
result of the estimation between the error parameters and must oscillate in values
greater than +/-1.96, and the signicance of the relationships have been considered.
Table 7. Contrasting hypotheses
Hypothesis Variables Effect Standard
Error - SE.
Composite
Reliability
- CR.
P Contrast
H1
Emotional
Salary
=> Job
Satisfaction
31.800 0.162 0.787 0.05 Accepted
Source: own elaboration.
According to the information in Table 7, the hypothesis proposed in this study is
accepted at p > 0.05, therefore, it can be stated that inferentially emotional pay
positively inuences the job satisfaction dimension. This nding is consistent with
the research objective, but it is also fair to point out that the coefcients Comparative
Fit Index (CFI) = 0.854 < (0.90); the Tucker-Lewis Index (TLI) = 0.844 < (0.90), the
Tucker-Lewis Index (TLI) = 0.844 < (0.90), the Goodness of Fit Index (GFI) = 0.854
< (0.90), the Root Mean Square Error of Approximation (RMSEA) = 0.095 > (0.05
to 0.08), suggest an acceptable value for the theoretical model of this work to be
signicant.
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6. Conclusion
This scientic work shows the inferential existence of a positive association between
the dimensions of emotional pay and job satisfaction. This nding is in line with
the work of Frankort and Avgoustaki (2021), Petit (2019); Quintero and Betancur
(2018); Skelton et al. (2018); Yoel-Kim et al. (2018), among other authors. Therefore,
emotional pay and job satisfaction become fundamental constructs for organisations
to develop competitive governance models in the era of Industry 4.0 (Obermayer et
al., 2022; Matt et al., 2021; Garay-Rondero et al., 2020).
Consequently, the variables in this study play a very relevant role in the human
resources policies of organisations in order to boost the motivation, commitment and
organisational justice of their internal customers (Ravina-Ripoll et al., 2022; Binzafrah
and Taleedi, 2022; Galván-Vela et al., 2021; Cherif, 2020). Companies that carry
out their business activities in emerging economies are no strangers to this reality,
as they have to deal with legislation and an organisational culture that does not
encourage emotional pay and job satisfaction of their human capital (Ellström et al.,
2022; Magnusson et al., 2021; Ibarra-Morales, 2019).
Finally, the results of this research extend, on the one hand, the academic literature
on both constructs. On the other hand, it enriches human talent management
practices that pivot on holistically improving job satisfaction and internal customer
motivation through emotional pay in the post-Covid-19 era (Ravina-Ripoll et al., 2021).
Undoubtedly, one of the aspects that will generate solid added value for companies is
to be more innovative, creative and competitive in today’s globalised market.
6.1 Limitations.
The results of this study should be considered in light of some limitations. First, the
eldwork was conducted during the health crisis caused by Covid-19; therefore, the
data may be biased due to the effect of data size on the sample obtained (Price and
Murnan, 2004). Second, this academic work used a cross-sectional survey design,
limiting its power to assert causality. Third, as this study was conducted in an emerging
economy, it cannot be asserted that this theoretical model works similarly for other
countries with more developed economies. Fourth, the job satisfaction variable is
inuenced by multiple organisational variables that have not been considered in this
article. To solve this problem, future studies should undertake more complex and
dynamic theoretical models with more parameters of a managerial nature. Finally, the
lack of longitudinal data makes it difcult to make solid causal inferences about the
sequential nature of the theoretical model proposed in this article.
6.2 Practical implications.
As has already been expressed throughout the research, emotional pay is a construct
that positively drives employee job satisfaction. It means, among other things, that
the emotional compensation strategies undertaken by organisations should promote
the professional growth of employees to be competitive in today’s globalised market.
It requires implementing dynamic management models that provide employees
with a high level of job satisfaction in their daily professional performance. It cannot
be achieved without a leadership style and a corporate culture that proactively
stimulates collective creativity, happiness management, fairness, loyalty, innovation
and other aspects. All this will signicantly impact the corporate image of companies
and, therefore, their economic and nancial development, as long as the strategic
directions of human resources revolve around emotional pay and job satisfaction.
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6.3 Future lines of research
Three general directions for future research illustrate below. First, scholars should
consider other psychological and managerial variables that may affect the relationship
between emotional pay and job satisfaction. Second, future research can empirically
explore, on the one hand, the long-term effects of implementing emotional pay on
job performance and the other hand, measure employees’ job satisfaction to learn
rst-hand how the two variables under study directly inuence their subjective
well-being and happiness. Moreover, to invite the academic world to study, from a
multilevel perspective, the positive consequences of cultivating emotional pay and
job satisfaction in the post-Covid-19 era for the business success of organisations.
Artículos • Gustavo Díaz García, David Almorza Gomar, Gerson González Arrieta
• 69 •
Appendix A
Instrument to assess emotional pay based on the Quintero and Betancur Model
(2018).
Strategic dimension
Organisational culture style?
Leadership and management support?
Flexible organisational structure?
Organisational resources and capacities?
Leadership style and management direction?
Human talent management?
Working conditions?
Organisational climate?
Motivational Dimension
Working conditions?
Self-improvement?
Job recognition?
Professional growth?
Personal growth?
Remuneration policy
The scale of recognition?
Job exibility?
Happiness at work?
Human Dimension
Self-realisation?
Promotion opportunities?
Training opportunities?
Commitment to the organisation?
Personal attitude?
Employee loyalty policy?
Family time?
Respect for diversity?
Healthy living?
Value Generation Dimension
Financial bonuses?
Compensation and bonuses?
Best employee retention plan?
Budget for training?
Recognition by objectives/results?
Management to retain customers through employee
performance?
Health policy plan?
Compensation to employees according to results with value
creation?
Appendix B
Instrument to assess job satisfaction based on the Hackman and Lawler Model (1971).
• Based on the factors assessed above, what is your perceived level of satisfaction with the
payment received?
• Based on the factors assessed above, what is your perceived level of satisfaction with job
security?
• Based on the factors assessed above, what is your perceived level of satisfaction with the
social variable and relationship with peers?
• Based on the factors assessed above, what is your perceived level of satisfaction with
supervisory relationships?
Anduli • Revista Andaluza de Ciencias Sociales Nº 23 - 2023
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Appendix C
KMO and Bartlett tests.
Kaiser-Mayer-Olkin measure
of sampling adequacy 0.957
Bartlett’s test of sphericity Approx. Chi-square 31.30.677
Gl 561
Sig. 0.000
Total variance explained.
Item
Initial eigen values Sums squared of extraction Sums of
charges
squa-
red by
rotation
Total %
variance
% Accu-
mulated Total %
variance
% Accu-
mulated
1 20.640 60.705 60.705 20.234 59.512 59.512 17.141
2 2.119 6.232 66.936 1.906 5.605 65.116 15.267
3 1.362 4.005 70.941 1.055 3.103 68.219 15.510
4 1.055 3.103 74.043 0.798 2.346 70.565 17.013
5 0.927 2.726 76.769
6 0.817 2.403 79.172
7 0.608 1.788 80.960
8 0.537 1.579 82.539
9 0.504 1.484 84.023
10 0.468 1.376 85.398
11 0.437 1.284 86.683
12 0.411 1.210 87.893
13 0.389 1.143 89.036
14 0.341 1.004 90.040
15 0.316 0.929 90.969
16 0.286 0.842 91.811
17 0.278 0.816 92.627
18 0.267 0.784 93.411
19 0.230 0.677 94.089
20 0.221 0.651 94.740
21 0.208 0.613 95.353
Artículos • Gustavo Díaz García, David Almorza Gomar, Gerson González Arrieta
• 71 •
Item
Initial eigen values Sums squared of extraction Sums of
charges
squa-
red by
rotation
Total %
variance
% Accu-
mulated Total %
variance
% Accu-
mulated
22 0.192 0.565 95.918
23 0.185 0.545 96.463
24 0.166 0.490 96.952
25 0.158 0.466 97.418
26 0.151 0.444 97.862
27 0.130 0.382 98.245
28 0.115 0.338 98.582
29 0.109 0.321 98.903
30 0.091 0.268 99.171
31 0.083 0.245 99.416
32 0.075 0.219 99.636
33 0.069 0.202 99.838
34 0.055 0.162 100.000
KMO and Bartlett tests
Kaiser-Mayer-Olkin measure of sampling adequacy 0.759
Bartlett’s test of sphericity Approx. Chi-square 44.24.240
gl
Sig. 0.000
Anduli • Revista Andaluza de Ciencias Sociales Nº 23 - 2023
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Appendix D
Item total statistics. Cronbach’s Alpha evaluation.
Item
Scale
average if
the element
has been
removed
Scale
variance if
the element
has been
suppressed
Total
correlation
of corrected
items
Cronbach’s
Alpha if
the item
has been
removed
DE_1 Organisational culture
style 123.23 873.435 0.706 0.979
DE_2 Leadership and manage-
ment support 123.31 866.181 0.767 0.979
DE_3 Flexible organisational
structure 123.42 861.600 0.768 0.979
DE_4 Organisational resources
and capacities 123.23 874.084 0.709 0.979
DE_5 Leadership style and
management direction 123.29 863.022 0.778 0.979
DE_6 Human talent
management 123.31 865.189 0.725 0.979
DE_7 Working conditions 123.06 879.054 0.631 0.980
DE_8 Organisational climate 123.24 871.303 0.711 0.979
DM_1 Working conditions 123.10 873.995 0.694 0.979
DM_2 Self-improvement 123.27 868.039 0.709 0.979
DM_3 Labour recognitions 123.56 852.353 0.850 0.979
DM_4 Professional growth 123.47 856.631 0.831 0.979
DM_5 Personal growth 123.29 866.799 0.757 0.979
DM_6 Remuneration policy 123.63 856.953 0.793 0.979
DM_7 Scale of awards 123.68 852.092 0.861 0.979
DM_8 Work exibility 123.35 866.515 0.706 0.979
DM_9 Happiness at work 123.38 860.882 0.807 0.979
DH_1 Self-realisation 123.28 864.234 0.829 0.979
DH_2 Promotion opportunities 123.64 855.185 0.807 0.979
DH_3 Training opportunities 123.39 854.736 0.803 0.979
DH_4 Commitment to the
organisation 123.14 869.519 0.779 0.979
DH_5 Personal attitude 123.03 875.158 0.691 0.979
DH_6 Employee loyalty policy 123.48 859.415 0.811 0.979
Artículos • Gustavo Díaz García, David Almorza Gomar, Gerson González Arrieta
• 73 •
Item
Scale
average if
the element
has been
removed
Scale
variance if
the element
has been
suppressed
Total
correlation
of corrected
items
Cronbach’s
Alpha if
the item
has been
removed
DH_7 Family time 123.45 864.556 0.709 0.979
DH_8 Respect for diversity 122.92 881.178 0.529 0.980
DH_9 Healthy living 123.22 866.829 0.724 0.979
DV_1 Financial bonuses 123.79 850.855 0.790 0.979
DV_2 Compensation and
bonuses 123.83 850.130 0.781 0.979
DV_3 Best Employee Reten-
tion Plan 123.87 847.645 0.822 0.979
DV_4 Budget for training 123.61 845.986 0.850 0.979
DV_5 Recognition by
objectives/results 123.66 849.971 0.823 0.979
DV_6
Management to retain
customers through
the performance of
employees
123.60 854.548 0.808 0.979
DV_7 Health PolicyScheme 123.50 857.839 0.677 0.980
DV_8
Compensating emplo-
yees according to results
with value creation
123.82 844.786 0.829 0.979
Source: own elaboration.
Anduli • Revista Andaluza de Ciencias Sociales Nº 23 - 2023
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Appendix F
Results of hierarchical multiple regressions.
ΒP-value R^2-Ad-
justed Effect Testing
Human Dimension
0.866 32.320 Suppor-
ted
Self-realisation 8.239 0.000**
Training opportunities 3.849 0.001**
Commitment to the organisation 4.260 0.007**
Employee loyalty policy 6.312 0.000**
Healthy living 3.310 0.003**
Working conditions 6.350 0.000**
Motivation Dimension
0.878 22.948 Suppor-
ted
Labour recognitions 4.387 0.002**
Personal growth 2.079 0.088**
Scale of awards 6.084 0.000**
Happiness at work 6.132 0.000**
Promotion opportunities 4.265 0.000**
Strategy Dimension
0.808 26.815 Suppor-
ted
Leadership and management
support 3.746 0.039**
Flexible organisational structure 7.542 0.000**
Organisational resources and
capacities 2.836 0.074**
Leadership style and manage-
ment direction 3.221 0.067**
Human talent management 4.112 0.001**
Organisational climate 5.358 0.000**
Value Generation Dimension
0.840 17.917 Suppor-
ted
Best employee retention plan 3.667 0.008**
Budget for training 6.823 0.000**
Recognition by objectives/
results 3.693 0.006**
Management to retain custo-
mers through the performance
of employees
3.734 0.005**
Artículos • Gustavo Díaz García, David Almorza Gomar, Gerson González Arrieta
• 75 •
ΒP-value R^2-Ad-
justed Effect Testing
Job Satisfaction
0.800 31.800 H1
Accepted
Satisfaction 5.247 0.000**
**Signicant correlations at p=0.05
Financing.
This research did not receive external funding.
Conicts of interest.
The authors declare that they have no conict of interest in this research.
Contributions to research.
The co-authors Almorza-Gomar and González Arrieta had a decisive participation
that supported the analysis of data obtained in this research.
Anduli • Revista Andaluza de Ciencias Sociales Nº 23 - 2023
• 76 •
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