Article Type : Research Article
Authors : Cruz García Lirios
Keywords : Flexibility; Climate; Leadership; Turnover; Salary
The objective of this work has been to explore the
dimensions of labor flexibility to establish the dependency relationships
between its indicators. An exploratory, cross-sectional and correlational study
was carried out with a sample selection of 100 employees from an organization
in central Mexico. The flexibility is indicated by the turnover, the wage
casual and lack of benefits. Lines of research on the incidence of leadership
styles on the variables in question are recommended.
As of this writing, the SARS CoV-2 pandemic and the
Covid-19 disease have killed three million and infected about 20 million. In
Mexico, about 120 thousand have lost their lives and more than 2 million have
been infected (WHO, 2020) [1]. In this panorama of health and economic crisis,
the policies of containment and mitigation of the pandemic have been
implemented as strategies of confinement and social distancing, causing a labor
crisis which is reflected in labor flexibility such as remote work (PAHO 2020)
[2].
Labor flexibility is indicated by 1) legislation
adjusted to unemployment , subsidies and vacancies informal ; 2) precarious
conditions in the matter of selection, training and education reflected in the
reduction of wages; 3) unfair competition and monopoly led to an increase in
demands and a decrease in the quality of processes and products; 4) export
strategies sponsored by the state and specialized labor willing to work long
hours with low income; 5) energy crisis and its effect on the maquiladora
industry, mainly the automotive industry, which encouraged mass production
without quality control; 6) the contraction of public investment and massive
unemployment that meant the impoverishment of jobs; 7) the proliferation of
power groups as a barrier to entrepreneurship and innovation that promoted mass
production without quality; 8) State intervention that aggravated compensation
for illnesses and accidents, as well as unemployment insurance that caused the
entry of unskilled labor; 9) public policies that generated poverty, pollution
and agglomerations of workers in a single industrial sector; 10) negotiation,
pacts and corporate, union and state agreements associated with corruption,
inequality, sabotage, strikes, boycotts, confrontations [3].
Therefore, the objective of this work is to explore
the structure of labor flexibility from the perception of employees who kept
their jobs even when they have been confined and distanced to carry out their
work. Are there significant differences between the theoretical dimensions of
labor flexibility reported in the literature with respect to the observations
in the present study?
The premise that answers the question lies in assuming
that significant differences prevail between the structure of labor flexibility
reported in the literature with respect to the structure of perceived
flexibility in the surveyed sample [4]. This is so because the state of the
question has been oriented towards the description and explanation of
dimensions related to the work environment without considering the perception
of workers regarding the same work environment, demand and resources that the
organization where they work for Carreon [5].
Labor flexibility reveals a change from state
management to a personalized selection of labor, the replacement of machinery
operated by groups and collectives with automated technologies that not only
allowed to extend the working day, but also transformed it into continuous and
permanent, opening the possibility of employment of unskilled and poorly paid
personnel, which is why it is subcontracted for a short period [6].
In this way, the competition between the organizations
that replaced the parastatals and the emergence of companies in areas of
specialization and innovation after the technological revolution, mainly
informational, has generated a labor demand for jobs that is estimated at 40%
not existed for five years [7].
If we consider that the occupational changes due n to
different dimensions, then it will be possible to see a future scenario in
which occupations are presented in accordance with economic, social, labor,
educational, scientific and technological structures [8].
The prospect of labor flexibility, understood as a
probable scenario to produce knowledge in accordance with technological
development purposes applied to the quality of processes and products, carries
some expected consequences for the 2020-2060 period [9]. It is a scenario in
which migration would reach a limit shared with the level of productivity that
began to be observed since 2015, but whose antecedents go back to 1950 when the
Welfare State was consolidated and the business crisis, innovation, productivity
and competitiveness [10].
Regarding the educational consequences, mainly in
terms of occupational specialization, the trend observed in 2010 not only
prevails for the economically active population, but also worsens in 2030 when
estimating the asymmetries between employment difficulties [11]. In other
words, an increase in occupational skills corresponds to a reduction in work
primary. In this sense, those who do not have a high level of specialization
and updating of knowledge are close to unemployment, although people with
postgraduate degrees do not guarantee formal employment.
Opportunities and capacities, from the logic of
occupational flexibility, are factors of gender equity. As of the year 2030,
not only is an occupational parity between men and women expected, but it is
also assumed that the degree of education-training will allow an equitable
distribution of leadership to be observed [10]. The indicators related to the
level of migratory selectivity, education and training will see equity
scenarios in the period from 2020 to 2040, but asymmetric after this period
given the level of competitiveness and technological dependence of the
organizations [12].
Modeling of the Variables of Labor
Flexibility
The specification of a dependency relationship model
consists of the design of the incidence trajectories between the variables
related to labor flexibility on performance [13]. In this sense, the literature
warns that the reduction of flexibility in the field of occupational health
involves the incidence of variables such as quality of life, subjective
well-being, work culture and organizational climate - empathy, trust,
entrepreneurship, innovation, productivity and competitiveness.
However, the literature also notes the influence of
stress -depersonalization, exhaustion, frustration- on well-being and the
cultural-organizational climate. Thus, the resilience emerges as a personal,
group and organizational response to the threats and risks posed by the
implementation of the flexibility work in organizations and institutions [14].
In the case of educational and health institutions,
the stress associated with resilience generates absorption, dedication and
dynamization [15]. These are three factors that distinguish individuals, groups
and organizations that not only develop resilience, but also generate opportunities
and skills linked to occupational satisfaction [16].
Design:
A cross-sectional, exploratory and correlational study was carried out.
Sample:
A non-random selection of 100 managers of micro, small and medium enterprises
was carried out in central Mexico. 67% are women and the remaining 33% are men.
32% completed their baccalaureate studies, 41% completed their bachelor's
degree and the remaining 27% had postgraduate studies. 45% declared that they
had income of less than 3,500 0 pesos per month (M = 3412 0 SD = 23 8 .14), 41%
mentioned that their income ranged between 3,500 0 and 7,000 0 pesos per month
(M = 5813 7 SD = 113 0 .24) and the remaining 14% acknowledged that their
income exceeded 7 0 000 pesos per month (M = 8124 0 SD = 2348.56). 42% are
married, 24% are single and the remaining 34% are in common law.
Instrument:
The Labor Flexibility Scale was used, assuming that the items in the literature
could be adjusted to the study context. Provided that they have been tested in
samples such as those in the study, as well as the inclusion of response
options that imply intervals of significance in the responses of each item.
In the case of job flexibility, respondents'
intentions were weighted against informality and staff turnover. This is the
case of the reactive "If there were unemployment, they would take turns to
have a job opportunity." Each item corresponds to one of the five response
options: 0 = not likely, 1 = very unlikely, 2 = unlikely, 3 = somewhat likely,
and 4 = very likely.
Procedure:
The surveys were conducted online: www.atn.es.tl prior information that the
results of the study would not negatively or positively affect their employment
situation. In addition, the anonymity and confidentiality of the data was
guaranteed in writing.
Analysis:
The information was processed in the Statistical Package for Social Science. Is
the alpha parameter estimated Cronbach for interpreting the consistency
internal of the instrument, the statistical adaptation and sphericity Bartlett
and Kaiser Meyer Olkin. To establish the factorial solution, as well as the
factorial weights and the percentage of variance explained in an exploratory
factor analysis of the main axes with promax rotation [17]. The validity of the
instrument, which supposes a construct that emerges in different contexts and
samples [18]. Finally, the correlation parameter was calculated to establish
the probable trajectories s relationships put forward factors [19].
The overall internal consistency of the instrument (alpha of 0.889) exceeds the minimum required (alpha of 0.80). This means that the Labor Flexibility Scale can be applied in different contexts and samples, yielding results like those of the present study (see Table 1).
Table 1: Instrument descriptions.
R |
M |
SD |
A |
F1 |
F2 |
F3 |
F4 |
F5 |
F6 |
r1 |
4.14 |
1,469 |
0.885 |
|
|
|
|
|
0.601 |
r2 |
4.53 |
1,429 |
0.884 |
|
|
|
|
|
0.675 |
r3 |
4.65 |
1,639 |
0.882 |
|
|
|
|
|
0.683 |
r4 |
4.23 |
1,178 |
0.881 |
|
|
|
|
0.549 |
|
r5 |
4.48 |
1,303 |
0.882 |
|
|
|
|
0.673 |
|
r6 |
4.85 |
1,108 |
0.881 |
|
|
|
|
0.693 |
|
r7 |
4.40 |
1,483 |
0.881 |
|
|
|
0.671 |
|
|
r8 |
4.85 |
1,993 |
0.888 |
|
|
|
0.543 |
|
|
r9 |
4.57 |
1,141 |
0.881 |
|
|
|
0.581 |
|
|
r10 |
4.11 |
1,204 |
0.882 |
|
|
0.612 |
|
|
|
r11 |
4.57 |
1,289 |
0.889 |
|
|
0.567 |
|
|
|
r12 |
4.94 |
1,055 |
0.888 |
|
|
0.673 |
|
|
|
r13 |
4.57 |
1,910 |
0.885 |
|
0.541 |
|
|
|
|
r14 |
4.74 |
1,100 |
0.888 |
|
0.543 |
|
|
|
|
r15 |
4.52 |
1,798 |
0.892 |
|
0.654 |
|
|
|
|
r16 |
4.47 |
1,472 |
0.883 |
0.623 |
|
|
|
|
|
r17 |
4.40 |
1,599 |
0.884 |
0.635 |
|
|
|
|
|
r18 |
4.32 |
1,126 |
0.886 |
0.625 |
|
|
|
|
|
Source: Prepared
with the study data; M = Mean, SD = Standard
Deviation, A = Alpha removed the value of the item. Extraction
method: main axes, Rotation: Promax. Suitability and
sphericity ?X 2 = 1864.322 (300gl) p =
0.000; KMO = 0,857? F1 = Leadership (0878 and 29878
alpha% of the total variance explained) , F2 = C OMPENSATION
(0.870 and 7.973 alpha% of the total variance explained), F3
= Structuration (0.894 and 7.471 alpha% the total variance explained, F4
= Conditions (alpha 0.892 and 5.84% of the total variance explained) ,
F5 = Contingency (0.782 and 4.996 alpha d% of the total
variance explained) , F6 = Risk (alpha of 0.746 and 4.559% of
the total variance explained.) All items include five response options: 0 =
not likely, 1 = very unlikely, 2 = unlikely, 3 = somewhat likely, and 4 =
very likely. |
In fact, if a minimum requirement of 0.70 and a
maximum of 0.90 is assumed as the exclusion criterion, then none of the items
would be exclude. The prerequisite for estimating the validity of the
instrument is the adequacy and sphericity of the scale, understood as tests
that establish the volume of partial correlations and the absence or presence
of a factor identity. Low correlations circumscribed to one entity suggest that
analyzes are not recommended to establish dimensions or factors. Thus, the
adequacy and sphericity ??2 = 1864.322 (300gl) p = 0.000; KMO = 0.857? suggests
estimating the factors recommended by the theory.
In the case of validity, understood as the efficiency
with which an instrument or scale measures what it intends to measure, from a
confirmatory factor analysis of principal components with promax rotation it
was possible to observe six factors configured by the five theoretical
dimensions, a despite the fact that: The first factor predominantly included
the theoretical dimension of the relationship with the boss (explaining 29.878%
of the total variance). The second factor included the theoretical dimension of
compensation (which explains 7.973% of the total variance). The third factor
included the organizational structure (explaining 7.471% of the total variance).
The fourth factor on working conditions (which explains 5,584% of the total
variance). The fifth factor included s contingencies the organizational
environment (0.782 and 4.996% alpha of the total variance explained). The sixth
factor refers to the risks of the organization's environment (alpha of 0.772
and 4.559% of the total explained varies).
Based on the reliability and validity analyzes, it is
recommended to adjust the observed factors to the theoretical dimensions,
suppressing those items that are dispersed or reconceptualising the dimensions.
This would allow the contrast of model reflection of the organizational
climate, taking into account the theoretical dimensions and the empirical
factors
Furthermore, the correlation matrix shows that there are positive and significant relationships between the five factors, evidencing the possibility of a reflective structure of the organizational climate as a second-order factor (see Table 2).
Table 2: Correlations and covariations between the factors.
|
M |
S |
N |
F1 |
F2 |
F3 |
F4 |
F5 |
F6 |
F1 |
F2 |
F3 |
F4 |
F5 |
F6 |
F1 |
29.7756 |
5,05445 |
205 |
1,000 |
|
|
|
|
|
1,896 |
|
|
|
|
|
F2 |
22,4078 |
4.25856 |
206 |
0.799 ** |
1,000 |
|
|
|
|
0.564 |
1,897 |
|
|
|
|
F3 |
17.8349 |
2,83280 |
212 |
0.832 ** |
0.744 ** |
1,000 |
|
|
|
0.671 |
0.672 |
1,804 |
|
|
|
F4 |
20.3173 |
3,29475 |
208 |
0.690 ** |
0.837 ** |
0.657 ** |
1,000 |
|
|
0.694 |
0.604 |
0.547 |
1,875 |
|
|
F5 |
17.4340 |
2.76237 |
212 |
0.688 ** |
0.602 ** |
0.614 ** |
0.638 |
1,000 |
|
0.546 |
0.674 |
0.673 |
0.604 |
1,673 |
|
F6 |
16.28 21 |
2.1923 1 |
219 |
0.561 ** |
0.506 ** |
0.423 ** |
0.332 |
0.4035 |
1.00 |
0.587 |
0.654 |
0.593 |
0.651 |
0.579 |
1,782 |
Source: Prepared
with the study data; M = Mean each factor, standard = Deviation of
each factor, N = N umber of observations in each factor, F1
= Leadership , F2 = Compensation, F3 = Structuration, F4
= Conditions , F5 = Contingency , F6 = Risk. *
p <0.01; ** p <0.001; *** p
<0.0001 |
Table 3: Dependency relationships between the factors and labor flexibility.
Model |
Hypothesis |
Trajectory |
? |
P |
R |
R 2 |
R 2 adjusted |
I |
1 A |
Labor flexibility è Leadership |
0.693 |
0.009 |
0.693 |
0.409 |
0.303 |
|
1 B |
Labor flexibility è Compensation |
0.644 |
0.000 |
0.634 |
0.488 |
0.384 |
|
1 C |
Labor flexibility è Structuring |
0.642 |
0.000 |
0.603 |
0.453 |
0.334 |
|
1D |
Labor flexibility è Conditions |
0.570 |
0.260 |
0.550 |
0.323 |
0.207 |
|
1E |
Labor flexibility è Contingencies |
0.542 |
0.000 |
0.542 |
0.395 |
0.291 |
|
1F |
Labor flexibility è Risks |
0.592 |
0.000 |
0.592 |
0.342 |
0.238 |
II |
2A |
Leadership è Compensation |
0.470 |
0.000 |
0.491 |
0.241 |
0.121 |
|
2B |
Leadership è Structuring |
0.452 |
0.320 |
0.419 |
0.270 |
0.150 |
|
2 C |
Leadership è Conditions |
0.412 |
0.202 |
0.401 |
0.240 |
0.115 |
|
2D |
Leadership è Contingencies |
0.331 |
0.002 |
0.383 |
0.143 |
0.084 |
|
2E |
Leadership è Risks |
0.332 |
0.067 |
0.357 |
0.184 |
0.072 |
III |
3A |
Compensation è Structuring |
0.321 |
0.002 |
0.356 |
0.194 |
0.084 |
|
3B |
Compensation è Conditions |
0.204 |
0.000 |
0.232 |
0.003 |
0.005 |
|
3C |
Compensation è Contingencies |
0.201 |
0.000 |
0.212 |
0.001 |
0.001 |
|
3D |
Compensation è Risks |
0.234 |
0.000 |
0.234 |
0.002 |
0.009 |
IV |
4A |
Structuring è Conditions |
0.134 |
0.127 |
0.134 |
0.023 |
0.020 |
|
4B |
Structuring è Contingencies |
0.189 |
0.135 |
0.165 |
0.024 |
0.021 |
|
4C |
Structuring è Risks |
0.135 |
0.189 |
0.118 |
0.029 |
0.022 |
V |
5A |
Conditions è Contingencies |
0.089 |
0.093 |
0.083 |
0.006 |
0.005 |
|
5B |
Conditions è Risks |
0.073 |
0.032 |
0.094 |
0.008 |
0.006 |
SAW |
6A |
Contingencies è Risks |
0.061 |
0.541 |
0.025 |
0.004 |
0.003 |
Source: Prepared
with the data of the study; ? = Parameter of the dependency
relationship between a dependent variable and an independent one, both in
relation to other determining variables. Significance
= Degree error allocation dependency ratio, R = Statistic or the
dependency relationship, R 2 = Statistic of the
dependence to the square, R 2 adjusted = Statistic
of the dependence to the squared and adjusted, which reflects the total
variance explained for each model.
|
The adequacy and sphericity ?X2 = 789.577
(10gl) p = 0.000; KMO = 0.833? suggests performing second order factor
analysis. The second-order factor or labor flexibility included each of the six
factors, explaining 76.690% of the total variance, which suggests the contrast
of the model based on five reflective factors in which the relationship with
the boss would be the predominant factor.
It is possible to observe that the organizational
climate, as a second order factor formed by the relationship with the boss,
compensation, structure, compensation and motivation are determinants of labor
flexibility as a second order factor indicated by isolation, overload,
complicity and consultations (? = .634, p = .000; R = 0.634, R2 =
0.402, R2 jd = 0.399).
Regarding the rest of dependency relationships, low
values tend to be spurious and not significant relationships. Once the six
first-order factors and their linear relationships had been established, their
structure was observed to establish the reflective trajectories of labor flexibility.
Finally, the adjustment parameters ??2 = 5.552 (2gl) p = 0.062; GFI = 0.974; NFI = 0.964; IFI = 0.977; CFI = 0.972; RMSEA = 0.229 ? shows the fit of the theoretical structure with respect to the weighted observations.
Regarding the theoretical, conceptual and empirical
frameworks, where leadership highlighted as a factor of labor flexibility,
establishing two - way communication and intrinsic motivation as indicative
levels of external demands and internal resources, the weighting of balances
the time to establish relationships, tasks, supports and innovations in terms
of conditions, rotations, salaries, rewards and benefits in situations that are
increasingly subject to the market. The present work, rather, proposes that
leadership is an intangible capital in terms of skills, knowledge and
experiences, which will also motivate staff to the point that a climate of
relationships will coexist with a rotation of functions and decrease of wages
in unemployment situations.
However, the non-experimental and exploratory type of
study, as well as the non-probabilistic and rather intentional type of sample
selection, limit the results of the study to the surveyed sample. It is
recommended to carry out an experimental study with probabilistic selection to
be able to contrast the hypotheses in a context and sample different from the
present work.
Regarding the studies that warn of market
contingencies as indirect determinants of the work environment and the performance
of organizations. In other words, to the extent that business development and
microfinance policies encourage productivity, leaders are committed to carrying
out strategies that, due to their degree of improvisation, imply unidirectional
communication and motivation in remuneration that allows them to be at living
up to the demands. From the market. In such a scenario, labor flexibility is a
mediating factor of economic, productive and employment policies, but
leadership prevails, with flexibility being a distinctive feature of the
environment rather than of the organization or groups working within them.
However, the influence of leadership in involves
training a working environment that can be oriented labor flexibility with
other types of work, goals, innovations and supports, which are a traditional
leadership or guidance of employees or subordinates, while motivating the
talent and intellectual capital. If the work environment is the result of local
and simultaneously determines policies a type of casual performance and
rotation, then organizations in establishing a scenario of trust and
expectation could n influence the formation professional.
It is necessary to carry out the contrast of the labor
flexibility model in groups of mycro, small and medium-sized companies in order
to establish the organizational determinants and their influence on the
similarities and differences between MSMEs when weighing their performance,
commitment and satisfaction. This design could also be extended to gender, age,
income and marital status groups to elucidate the profiles that would fit the
informal and austere working conditions.
The
contribution of this work to the state of the art lies in the establishment of
the reliability and validity of an instrument that measures work climate and
flexibility, but the type of design and selection of the sample imitate the
findings in the study sample. The statistical properties of the instrument
indicate that flexibility is multidimensional since, it seems to be a mediator
of the policies of local impulse on the opportunities and informal labor
capacities. This reflects a validity of context that the instrument in question
could develop more in samples and scenarios different from that of the study.
Furthermore, in relation to other variables such as leadership, the instrument
can be extended to incorporate leadership as a determinant of labor
flexibility.