Which Factors Influence a University Student's Entry into the Workforce?
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doi:10.5477/cis/reis.176.59
Which Factors Influence a University Student’s
Entry into the Workforce?
¿Qué factores influyen en el camino hacia la inserción sociolaboral
del estudiante universitario?
Cristina González-Lorente and Pilar Martínez-Clares
Key words Abstract
Competencies The importance of a university student’s transition into the workforce
• Higher Education is a key factor for planning better higher education policies and new
• Employability paths of action. This research analyzes the interrelationship between
• Entering the competences, the satisfaction with career training and their predisposition
Workforce to job mobility with the preparation for entering the workforce of the
• Satisfaction university students through an ad-hoc model approach of a causal
relationship between these factors. 1,328 final year undergraduate
students of four universities participated in this study through the Career
Guidance and Training Questionnaire collect data. The results obtained
show the suitability of the model with a good index fit and causal
relationships that significantly influence the perception that the university
student has when facing the process of entering the workforce.
Palabras clave Resumen
Competencias La inserción sociolaboral de los universitarios es un factor clave a
• Educación superior efectos de planificar apropiadamente las políticas universitarias y
• Empleabilidad las líneas de actuación a seguir. Es el desafío más importante de la
• Inserción universidad. Este trabajo analiza la interrelación que se establece entre
sociolaboral competencias, satisfacción y predisposición a la movilidad laboral con
• Satisfacción la capacitación del alumnado para afrontar el proceso de inserción
sociolaboral. Participan 1.328 estudiantes de último curso de Grado
distribuidos en cuatro universidades mediante la cumplimentación del
Cuestionario de Inserción y Orientación Laboral. A través de un modelo
de ecuaciones estructurales, los resultados muestran su idoneidad
mediante los índices de bondad de ajuste y unas relaciones causales
que influyen de manera significativa en la percepción que tiene el
estudiante para enfrentarse al proceso de inserción.
Citation
González-Lorente, Cristina and Martínez-Clares, Pilar (2021). “Which Factors Influence a University
Student’s Entry into the Workforce?”. Revista Española de Investigaciones Sociológicas, 176: 59-78.
(doi: 10.5477/cis/reis.176.59)
Cristina González-Lorente: Universidad de Murcia | c.gonzalezlorente@um.es
Pilar Martínez-Clares: Universidad de Murcia | pmclares@um.es
Reis. Rev.Esp.Investig.Sociol. ISSN-L: 0210-5233. N.º 176, October - December 2021, pp. 59-7860 Which Factors Influence a University Student’s Entry into the Workforce?
Introduction 2012). Most of these have been descriptive
in nature, as in the case of the reports of the
The majority of young people born between Spanish Ministry of Education and the differ-
the eighties and the beginning of the 21st ent universities, generally focused on ana-
century (also known as “Generation Y” or lysing the factors that influence the entry of
“Millenials”) are currently experiencing ma- graduates into the labour market between
jor transitional changes in their professio- two and four years after completing their ini-
nal, social and personal spheres. They are tial university education (Ruesga, Da Silva
thus compelled to become actively involved and Monsueto, 2014). This study also analy-
in the new culture of lifelong learning and in ses those influential factors that are directly
enhancing their employability. Young people related to work experience after university, in-
with a university education find the process cluding data such as registration with the so-
of entering the workforce increasingly diffi- cial security authorities, salary, suitability of
cult, which results in an uncertain and confu- the education completed, job satisfaction and
sing time for them, due to the contextual and periods of unemployment experienced by
sociostructural factors involved in the tran- graduates.
sition, and to variables linked to life factors In addition, fewer studies have analysed
that have an impact on young people’s lives. the effects derived from other variables such
It is important to differentiate between as socioeconomic differences (Pérez, 2018),
two terms that refer to related concepts in the the different attitudes and motivations for
analysis of labour market entry: employability graduates to face their transition into the
and workforce entry. Throughout this study, workforce (Rondón, Muñoz and Gómez,
the concept of employability is used to refer 2017), and the job search process (Albert and
to the macro-competence of graduate stu- Davia, 2018; Dapía and Fernández, 2016).
dents that allows them to achieve career sta- These studies have shown the importance
bility that is not limited to a specific job, and of considering the students’ individual dif-
to remain active throughout their working life ferences and perceptions when conduct-
(Argos and Ezquerra, 2014; García-Gutiér- ing empirical studies in this field of research
rez, 2014). In contrast, workforce entry is un- (Baquero and Ruesga, 2019). The goal of this
derstood, in general terms, as a process of study is to go further by giving a voice to uni-
searching for and gaining employment (Fern- versity students who are starting this process.
ández-Salinero and García-Álvarez, 2020). In Their perspective is welcomed as an invita-
tion to assess whether factors related to the
this process two aspects play an important
development of employability skills, satisfac-
role: the conditions of entry into the labour
tion with their education, and their willingness
market (García-Blanco and Cárdenas-Sem-
to move for work can influence their ability to
pértegui, 2018) and obtaining a job consistent
meet the demands of entering the labour mar-
with education, and remaining in it for a cer-
ket. A review of the literature related to each
tain period of time. The process of workforce
of these factors is carried out in the next sec-
entry is directly related to the development
tion. A causal relationship model will then be
of one’s personal and professional identity,
used to formulate the research hypotheses.
which is affected by numerous personal, aca-
demic and social factors.
Numerous studies have investigated grad- Employability skills in higher education
uates’ entry into the workforce from different
perspectives over the last decade (Römgens, In recent years, promoting employability and
Scoupe and Beausaert, 2019; Tomlinson, the acquisition of a set of key or transversal
Reis. Rev.Esp.Investig.Sociol. ISSN-L: 0210-5233. N.º 176, October - December 2021, pp. 59-78Cristina González-Lorente and Pilar Martínez-Clares 61
skills have gained momentum in tackling way of living and functioning in today’s
the growing difficulties related to graduates’ world, based on transversal employability
labour market entry and the mismatches skills that are transferable to different con-
between education and employment. There texts. In order to verify and assess skill ac-
is an increasing number of experiences quisition in higher education, it is not suffi-
and research on the acquisition of skills cient to understand and contrast the vision
in university education (Ruiz-Corbella, of experts, employers, and graduates; it is
Bautista-Cerro and García-Blanco, 2019; also necessary to consider how education
Villardón-Gallego, 2015, among others) and is perceived by students, in order to bet-
their influence on students’ employability ter comprehend the complex process of
and workforce entry (Michavila et al., 2018), acquiring skills at university and the impor-
which are now at the core of the teaching- tance of these for entering the labour mar-
learning process. ket.
These publications include examples
of studies that focus on the analysis of
skills from the point of view of graduates Satisfaction with university education in
and identify the direct relationship be- terms of facing labour market entry
tween skill acquisition and success in en-
tering the labour market (Akkermans et al., While student satisfaction can be defined as
2013; Teijeiro, Rungo and Freire, 2013). a short-term attitude resulting from the edu-
Another group of studies focuses on the cational experience, it is nowadays concei-
viewpoint of employers (Hendarman and ved as an important indicator of quality in
Cantner, 2018). These revealed their low higher education (Ferrante, 2017; Naidu
level of satisfaction with the competence and Derani, 2016). Therefore, this variable
level of university graduates. Some more should be understood and analysed regar-
recent analyses addressed the perspec- ding university students (Hernández-He-
tive of business tutors to assess the skill rrera, 2019).
acquisition of university graduates (Riera- Student satisfaction is sometimes di-
Prunera et al.2018), whereas others car- rectly related to the teaching-learning proc-
ried out comparative studies to contrast ess and other times linked to sociodemo-
the perception of different agents, by com- graphic variables or extracurricular factors
bining the opinions of students, employ- (Martín-González, Merhi and Martínez,
ers and academics (Alcañiz, Claveria and 2018). There are many available studies that
Riera-Prunera, 2014; Wesley, Jackson and seek to find graduates’ satisfaction with
Lee, 2017). their bachelor’s degree and whether this
However, there are fewer examples in has helped them to enter the labour market
the literature that address the acquisition (Blanco, Sánchez and Tallón, 2019; Sonll-
and usefulness of these skills for univer- eva, Martínez and Monjas, 2019). However,
sity students when they are still part of the there is a paucity of studies that work on
education systems but are close to engag- this subject from the perspective of final-
ing in the transition to their working life. year bachelor’s degree students. The few
It is at this point that they begin to ques- analyses available measure graduates’ sat-
tion and have concerns about their entry isfaction with the acquisition of conceptual,
into the workforce. As Morley (2018) high- personal, and civic learning (e.g., Folguei-
lighted, students can be expected to de- ras, Luna and Puig, 2013), without estab-
mand and sometimes require learning ex- lishing its possible usefulness and impor-
periences that reflect and enhance their tance in their transition to working life.
Reis. Rev.Esp.Investig.Sociol. ISSN-L: 0210-5233. N.º 176, October - December 2021, pp. 59-7862 Which Factors Influence a University Student’s Entry into the Workforce?
In order to further explore these lines of employability and can therefore have an
research, this study considers that students’ impact on their expectations of success-
satisfaction with their education can have fully entering the labour market (Komulainen
a favourable effect on how they assess the et al., 2012; Tomlinson, 2012). Hernández-
contribution made by the university to the Fernaud (2011) proposed a 10-item rating
acquisition of skills in terms of their entry into scale to determine how university students
the labour market. Duque and Weeks (2010) experienced their transition to entering the
and Wu, Tennyson and Hsia (2010) identi- labour market based on their beliefs about
fied support resources, educational quality, their likelihood of finding a job after they
faculty performance and learning outcomes had completed their degree, their profes-
(including skill acquisition) as factors that sional skills, and their job prospects. Al-
enhanced student satisfaction, based on a though there are numerous studies that
positive correlation. This is reason enough have addressed graduates’ subjective per-
to broaden knowledge in this area and ana- ceptions about entering the labour market
lyse which skills are currently focused on in (Gowan, 2012; Magnano, Santisi y Zammitti,
higher education (Michavila et al., 2018); and 2019), fewer studies have linked these per-
to see whether they effectively meet the new ceptions to their actual preparation based
education needs and expectations of “Gen- on the skills they have acquired in university
eration Y” through a direct relationship with classrooms and their satisfaction with the
student satisfaction. This relates both to their education they have received.
education in general, and to the complex This study explores this line of research
process of entering the labour market with in greater depth and furthers the studies initi-
a better match between education and em- ated by authors such as Coetzee (2017), who
ployment, in particular. related graduate employability to the acquisi-
tion of a set of transversal skills that will en-
able them to act proactively both at the start
University students’ subjective and throughout their career. It also aims to
perception of their preparation to face include as a study variable the importance
their entry into the labour market that university students attach to these skills
and how useful they consider them in order
Long gone are the days when a person could
to take their first steps towards labour mar-
move almost automatically from university
ket entry. There is a new perspective of anal-
into the labour market, in most cases into
ysis put forward by Rodríguez et al. (2010),
decent jobs with long-term prospects. Revo-
which argued that success in entering the la-
lution 4.0 has blurred this scenario and chan-
bour market does not solely depend on the
ged the mindset of university students. Their
skills acquired by the person through their
expectations of having a successful transi-
education and work experience, but must
tion to working life are influenced by multi-
be complemented by how these skills and
ple factors, while the process of entering the
resources are presented to employers, and
workforce is becoming ever more complex
their importance according to the employ-
and uncertain for them. This now involves
ment area of choice.
(re)considering their employability in the la-
bour market and constantly assessing their
self-perceived skills in relation to their pro-
Willingness to relocate to find employment
fessional expectations (Räty et al., 2019).
Skill acquisition at university can be a Careers are increasingly defined by flexibi-
measure of students’ assessment of their lity and mobility (Wood, 2011) and, as part
Reis. Rev.Esp.Investig.Sociol. ISSN-L: 0210-5233. N.º 176, October - December 2021, pp. 59-78Cristina González-Lorente and Pilar Martínez-Clares 63
of this growing trend, companies are increa- may have on having successful prospects in
sing their demand for graduates who are entering the workforce from the perspective
willing to work in different environments and of final-year undergraduate students. To de-
settings, including national and international termine the relationship between these fac-
travel. This was shown in the latest report tors, a series of multivariate causal research
published by the University of Murcia on hypotheses were constructed (Martin and
employers’ demands (COIE, 2019), which Bridgmon, 2012) composed of three inde-
highlighted the current reluctance of many pendent variables or causes (DEVSKILLS,
students to change the traditional mindset development of employability skills during
of seeking work within a limited area that is the degree; SATISEDUC, satisfaction with
close to their place of residence. their education in terms of facing labour mar-
Despite this apparent resistance on the ket entry; MOVEMPLOY, willingness to seek
part of students, there are many advantages employment in a search radius limited to city/
to promoting relocation to find work, espe- town or province), and a dependent variable
cially among the younger population, not or effect (PREPENTRY, preparation perceived
only for acquiring language skills but also to by the students to face their entry into the la-
acquire other important employability skills bour market). On the basis of this approach,
such as integration in multicultural groups, the following hypotheses are proposed:
the promotion of independence, initiative, or
autonomy, among many others (COIE, 2019; H1. The development of employability skills
Räty et al., 2019). When it comes to entering by university students has an impact on
a global labour market, mobility programmes the way they face their transition from
such as ERASMUS+ and ILA scholarships study to the labour market, both directly
can contribute to enhancing the start of stu- and indirectly.
dents’ professional careers (Iriondo-Múgica, H2. Student satisfaction with their university
2017). Investing in them can also bring suc- education influences students' belief that
cessful outcomes by acquiring different pro- they are better prepared to engage in the
fessional skills (Baquero and Ruesga, 2019). transition from study to the labour market.
Based on the scientific literature on the
H3. Students’ poor willingness to relocate
subject, this study considers that the lack of
for work has a direct impact on their as-
willingness to seek work beyond the student’s
sessment of their preparedness for en-
place of residence may influence their assess-
tering the labour market.
ment of their chances of successfully entering
the labour market; therefore, it may be factor
Following the state-of-the-art review and
that influences their perception of being bet-
the formulation of the research hypotheses,
ter or worse prepared to start this process.
Figure 1 shows the causal model (MT) that
will be used in the analysis, in which each
of the hypotheses with cause-effect rela-
Method tionships are clearly identified.
Objective, identification of hypotheses
and proposed model
Sample
The objective of this study is to discover and A total of 1,328 final-year undergraduate
analyse the influence that important factors students from four different universities
related to skills training, satisfaction with tra- participated in this study. Three of these
ining, and predisposition to relocate for work universities are located in Spain, namely,
Reis. Rev.Esp.Investig.Sociol. ISSN-L: 0210-5233. N.º 176, October - December 2021, pp. 59-7864 Which Factors Influence a University Student’s Entry into the Workforce?
Figure 1. Proposed model of causal relationship based on the theoretical background (MT)
SATISEDUC
H2
H1
Indirect
relationship
DEVSKILLS PREPENTRY
H1
H3
MOVEMPLOY
Source: Own source.
Universidad de Murcia (UM), Universidade to 12.7 and 23.8, respectively. Although it
da Coruña (UDC) and Universidad de Gra- would have been ideal to increase these
nada (UGR) and one of them is in the United percentages until they were close to the
States, the University of New Haven (UNH). recommended value for n = 1,328, where
In order to obtain a representative sample fh = 0.4109, despite this limitation, the over-
in all the degrees to which the researcher all sample was highly representative of the
had access, the population under study student population. Taking into account a
was taken into account based on probabi- population under study (N) of 3,232 stu-
lity sampling by clusters, as shown in Ta- dents, it has a confidence level of 95%
ble 1. The percentage of participation was and a maximum acceptable error of 2.1%
obtained according to each of the popula- (p = q = 50%).
tions distributed by branch of knowledge, The sample was characterised by the
degree, and university. In accordance with high percentage of female representa-
the contributions by Hernández, Fernán- tion, which reached 72.8% (n = 967),
dez and Baptista (2014), Table 1 shows the with a mean age of around 23 years old
formula (Nh) (fh) = nh, used to calculate the (X = 22.87; SD = 3,895). Among all these
expected sample in each degree, where nh participants, only 27% reported that they
and Nh are the sample and population of had done extracurricular internships dur-
each stratum and fh represents the cons- ing their degree, and nearly 70% were
tant fraction. solely focused on their education and
The sample was stratified by degree did not do any paid work. The latter per-
qualifications. In most cases it reached centage remained stable among the three
or was close to the expected percentage Spanish universities analysed in this
(41%), and even significantly exceeded it. study, while in the case of participants
However, in degrees such as Psychology from the UNH (USA) it dropped signifi-
and Chemistry this percentage dropped cantly to 45.11%.
Reis. Rev.Esp.Investig.Sociol. ISSN-L: 0210-5233. N.º 176, October - December 2021, pp. 59-78Cristina González-Lorente and Pilar Martínez-Clares 65
Table 1. Distribution of the sample by degree and university. Population and percentage of participants
n (expected) % sample reached
Univ. N n (reached)
fh = 0.41 by degree (expected = 41%)
UM 420 173 103
Primary Education UGR 510 210 202 38.0
SVP 143 59 103
UM 186 76 125
Early Childhood Education 64.8
UDC 147 60 91
UM 140 58 92
Pedagogy 44.7
UGR 137 56 32
UM 124 51 41
Social Education 31.4
UGR 137 56 41
Labour Relations and
UM 250 103 59 23.6
Human Resources
Criminal Justice UNH 30 12 11 36.6
Communication UNH 85 35 39 45.8
Forensics Science UNH 64 26 49 76.5
English Studies UM 140 58 73 52.1
Computer Science UNH 76 31 60 78.9
Mechanical
UNH 40 16 18 45.0
Engineering
Speech Therapy UM 100 41 44 44.0
UM 190 78 17
Psychology 12.7
UNH 53 22 14
Pharmaceutical Studies UM 50 21 38 76.0
Biology UNH 35 14 14 41.0
UM 50 21 34
Biotechnology 52.8
UNH 20 8 3
UM 70 29 18
Chemistry 23.8
UNH 35 14 7
Source: Own source.
Data collection instrument tionnaire is part of a broader research pro-
ject of which this study is a part, which aims
The data collection tool used was the Ques- to analyse the process involved in entering
tionnaire on Workforce Entry and Career the labour market faced by higher educa-
Guidance (QWECG) (Cuestionario de Orien- tion students who are close to completing
tación e Inserción Laboral [COIL]). This ques- their initial education (specifically, in the last
Reis. Rev.Esp.Investig.Sociol. ISSN-L: 0210-5233. N.º 176, October - December 2021, pp. 59-7866 Which Factors Influence a University Student’s Entry into the Workforce?
year of their bachelor’s degree). Previous ting an in-person pilot test with 35 university
studies have conducted a thorough content students with the same characteristics as
validation process of this tool through pilo- the study population during the 2015-2016
ting and expert judgement, using the indivi- academic year, to refine aspects related to
dual aggregate method (Martínez-Clares and the wording, understanding, and relevance
González-Lorente, 2018, 2019). The general of the items. The changes made to the initial
recommendations provided by the experts proposal were thus outlined and the QWECG
on the questionnaire were incorporated, in was finally structured into five main blocks,
addition to the data collected after conduc- as summarised in Table 2.
Table 2. Structure of the Workforce Entry and Career Guidance Questionnaire (QWECG)
Block Content Variables
I Personal and academic data Sex, age, degree, university, average grade.
Current employment situation, extracurricular in-
II Academic and professional experience ternships, reason for choosing the degree pro-
gramme.
Further training, development and use of emplo-
III Undergraduate training yability skills, satisfaction with the education re-
ceived.
Expectations, relevant aspects of employment,
achievements and goals, job search radius, pre-
IV Attitudes to, and expectations of, employment
paration to face the labour market entry process,
strengths, and weaknesses.
Career prospects, resources, employment
search techniques and services, access to and
Supporting resources and services for enter-
V satisfaction with career guidance received, op-
ing the labour market
portunities for and threats to labour market en-
try.
Source: Own source.
Once the content validation had been Each of these variables incorporated in
carried out and the wording of some of the the proposed causal model is described
variables introduced had been readjusted, in Table 3. Each of the constructs is listed
Exploratory Factor Analysis (EFA) was un- and named as coded in the model and
dertaken to assess construct validity. This the variables that comprise it within the
was followed by Confirmatory Factor Anal- QWECG. In addition, an operational defi-
ysis (CFA), which was used to determine nition of the scales is provided that serves
the suitability and reliability of the different to understand the metrics that will be used
Likert-type rating scales included in the for the data collected in each construct
survey. In particular, this paper focuses on (Hernández, Fernández and Baptista, 2014)
those scales that concerned the four latent and the results obtained after the valida-
variables of the model proposed for testing tion tests that corroborate the suitabil-
the hypotheses set out at the beginning, ity and appropriateness of the scales pro-
included in blocks II and IV of the QWECG. posed and incorporated in the QWECG.
Reis. Rev.Esp.Investig.Sociol. ISSN-L: 0210-5233. N.º 176, October - December 2021, pp. 59-78Cristina González-Lorente and Pilar Martínez-Clares 67
Table 3. Structure and operational definition of the variables used in the causal relationship model
Variable Operational definition* Items
DEVSKILLS Employability skills scale included Self-awareness (DC1).
in the QWECG. the development Analysis. synthesis and critical skills (DC2).
of which obtained a Cronbach’s Planning and organisation skills (DC3).
alpha α = 0.897 for the EFA and Communication skills (DC4).
satisfactory goodness of fit in- Responsibility and perseverance (DC5).
dices in the CFA (CFI = 0.910; Decision-making (DC6).
NFI = 0.884; 0.057). People orientation (DC7).
Teamwork and cooperation (DC8).
Learning and adaptation (DC9).
Flexibility and orientation to change (DC10).
Motivation for achievement (DC11).
Commitment to the organisation (DC12).
Working under pressure (DC13).
Conflict resolution and negotiation techniques (DC14).
Pursuit of excellence (DC15).
Innovation (DC16).
Entrepreneurship (DC17).
Leadership (DC18).
Resilience and tolerance to frustration (DC19).
SATISEDUC Single-item variable included in What is your level of satisfaction with your undergraduate
the QWECG with a Kurtosis coef- education in terms of meeting the demands of labour mar-
ficient of 0.208, indicating a lep- ket entry?
tokurtic distribution of the varia-
ble with a higher concentration of
data around the mean.
PREPENTRY Single-item variable included in Do you feel prepared to meet the demands of entering the
the QWECG with a Kurtosis co- labour market?
efficient of 0.8, which means that
it is very close to being a meso-
kurtic or normal distribution (simi-
lar to the Gaussian distribution).
MOVEMPLOY Likert-type scale made up of two Willingness to seek employment only in the municipality
items that circumscribe the uni- where you live (LOCALWORK).
versity student’s job search to Willingness to seek employment only in the province
the province and the town/city where you live (PROVWORK).
where they reside, included in
the QWECG with normal distri-
bution and a Cronbach’s alpha
α = 0.790.
* Data obtained from content and construct validation in Martínez-Clares and González-Lorente (2018, 2019).
Source: Own source.
Procedure theses of this paper. Next, the QWECG was
designed and subjected to a content vali-
The study began with an in-depth search dation process using the expert judgement
of the literature on the entry into the labour technique and a pilot test in which 35 final-
market of university students. This was fo- year undergraduate students from the Uni-
llowed by the research objective and hypo- versity of Murcia participated. After the ad-
Reis. Rev.Esp.Investig.Sociol. ISSN-L: 0210-5233. N.º 176, October - December 2021, pp. 59-7868 Which Factors Influence a University Student’s Entry into the Workforce?
justments proposed in this validation and using the Kolmogorov-Smirnov test, and
the definitive implementation of the QWECG the null hypothesis was rejected with a sig-
structured in five large blocks, data collec- nificance of less than 0.05.
tion took place during the 2016-2017 and The AMOS v7 statistical software was
2017-2018 academic years. then used to test the goodness of fit of
To collect the data, the researcher went the proposed causal model, and the rela-
personally to each classroom at a time tionship between its variables. Prior to this
previously agreed with each of the lectur- analysis, Bartlett’s test of sphericity was
ers teaching in the final year of the degree used (with a value of p=0.000, which al-
course. The researcher provided the stu- lowed the null hypothesis that there was
dents with directions for completing the no correlation between variables to be re-
questionnaire, and reminded them of the jected). The Kayser-Meyer-Olkin test (KMO)
voluntary, anonymous and confidential na- was also employed, which yielded a value
ture of the QWECG. above 0.80. It was considered appropriate
Following the data collection of proc- to carry out the factorisation in accordance
ess, the construct validation of the QWECG with the parameters established in López-
measurement scales was carried out us- Aguado and Gutiérrez-Provecho (2019).
ing SPSS v24 and AMOS v7 statistical soft- Based on these results, it was decided
ware, with values for Cronbach’s alpha to apply structural equation modelling
(alpha skill development = 0.897; alpha rel- (SEM) to test the hypotheses and determine
evance of skills = 0.894; alpha willingness the strength of the relationship between the
to relocate for work = 0.769) and optimal latent variables (constructs represented by
goodness-of-fit indices (RMSEA 0.90 for all scales). These demon- observable variables (represented by rec-
strated the internal consistency and reliabil- tangles), because of its advantages over
ity of the instrument. A structural regression other multivariate statistical techniques for
model was then developed, based both on model analysis. One of the main advan-
the theory and on the data obtained. Its aim tages pointed out by García (2011) is that
was to further enquire into the possible rela- SEM allows for the same variable to behave
tionship between different variables and the as a response variable in one equation and
beliefs of students regarding their prepara- then appear as an explanatory variable in
tion for entry into the labour market. Finally, another equation. It also makes it possible
the results of the study of this hypothetical to specify a reciprocal effect, in which two
model were analysed and presented. variables feed back on each other. Both of
these situations are present in the hypo-
thetical model proposed in this study.
Data analysis
Therefore, the use of SEM makes it eas-
SPSS v24 statistical software was used for ier for the researcher to test the proposed
the data analysis to calculate the mean and structural theory on the entry into the labour
standard deviation of each variable. The market through hypothesis testing (confirm-
programme was used to optimise the sam- atory approach). In order to more accurately
ple size by calculating the missing values determine whether the model fits the data,
using the expectation-maximisation me- the most commonly used goodness-of-fit
thod. None of the items exceeded 5% of indices in the literature for SEMs were ap-
the missing values (Tabachnick and Fidell, plied using the Maximum Likelihood Estima-
2013). Next, sample normality was tested tion method. The most commonly employed
Reis. Rev.Esp.Investig.Sociol. ISSN-L: 0210-5233. N.º 176, October - December 2021, pp. 59-78Cristina González-Lorente and Pilar Martínez-Clares 69
are absolute indices (Chi-Square) (although (items). These results are shown in Table 4.
they are sometimes too sensitive for the Teamwork and cooperation (DC8) was the
sample size), comparative indices such as most highly developed skill from the point
CFI (Comparative Fix Index), whose values of view of the students surveyed (X = 4.05,
must be close to 1, and other indices, nota- SD = 0.932). This was the only skill that was
bly including the Root Mean Square Error of assessed by a score slightly higher than 4,
Approximation (RMSEA) - which indicates a followed by skill DC5, which refers to stu-
good fit when it is less than 0.05. dent responsibility and perseverance, with
an average of 3.88 (SD = 0.921). For the
other skills, the averages were around 3.5
Results on the proposed 1-5 Likert scale (the lat-
Descriptive analysis ter being the highest score). The averages
that fell closer to 3 were entrepreneurship
The descriptive statistics were used to firstly (DC17) and leadership (DC18), the skills
calculate the mean and standard devia- that the participating students believed had
tion of the students’ assessments of each been least focused on during their univer-
of the observable variables of the model sity education.
Table 4. Descriptive statistics
N Average (X) Std. Dev. Asymmetry Kurtosis
DC1 1,328 3.71 0.857 –0.484 0.284
DC2 1,328 3.57 0.841 –0.229 –0.055
DC3 1,328 3.75 0.894 –0.388 –0.177
DC4 1,328 3.74 0.929 –0.385 –0.379
DC5 1,327 3.88 0.921 –0.522 –0.244
DC6 1,328 3.64 0.900 –0.432 –0.019
DC7 1,328 3.35 0.996 –0.246 –0.387
DC8 1,328 4.05 0.934 –0.880 0.444
DC9 1,328 3.79 0.893 –0.496 0.072
DC10 1,328 3.52 0.913 –0.294 –0.047
DC11 1,328 3.51 1.058 –0.450 –0.273
DC12 1,326 3.40 0.974 –0.319 –0.257
DC13 1,328 3.60 1.128 –0.492 –0.471
DC14 1,328 3.41 1.009 –0.318 –0.383
DC15 1,328 3.48 0.982 –0.423 –0.085
DC16 1,328 3.33 0.997 –0.226 –0.414
DC17 1,328 3.17 1.049 –0.241 –0.417
DC18 1,328 3.28 1.055 –0.207 –0.456
DC19 1,328 3.34 1.098 –0.358 –0.437
SATISEDUC 1,325 3.18 0.839 –0.372 0.175
PREPENTRY 1,328 3.43 0.929 –0.338 0.287
LOCALWORK 1,324 3.94 1.423 –1.008 –0.441
PROVWORK 1,328 4.26 1.060 –1.520 1.762
Source: Own source.
Reis. Rev.Esp.Investig.Sociol. ISSN-L: 0210-5233. N.º 176, October - December 2021, pp. 59-7870 Which Factors Influence a University Student’s Entry into the Workforce?
Students’ satisfaction with their educa- The rest of the results shown in Table 4
tion in terms of facing their entry into the (skewness and kurtosis) were considered
workforce (SATISEDUC) was at a medium- acceptable to demonstrate their normal dis-
low level, close to 3 on the scale, and was tribution in accordance with Gravetter and
somewhat higher when participants as- Wallnau (2014), who placed the suitability of
sessed their general preparation to start this these values at between –2 and +2. In this
process (PREPENTRY). Averages scores case, “skewness” values ranged between
rose in connection with the students’ in- –207 and –1,520, and those of “kurtosis”
tention to look for a job in their local area ranged between –471 and 1,762, which de-
(LOCALWORK) and, even more so, in their noted a normal distribution of the observed
province (PROVWORK), where the highest variables.
score was recorded (X = 4.26; SD = 1.060). The Pearson coefficient (r) was then
These evaluations refer to the willingness used to analyse the relationship between
of which university students to relocate for the variables (constructs) in the model. The
work. Far from being positive, they can limit results of this coefficient are shown in Ta-
the radius of their search and with it, their ble 5, with a level of significance in the cor-
job opportunities in an interconnected and relations between all the variables with a
global market. value of p of less than 0.001.
Table 5. Descriptive data and correlations between the model’s variables. Pearson’s Coefficient
M SD DEVSKILLS MOVEMPLOY PREPENTRY SATISEDUC
DEVSKILLS 3.5545 0.581 1.000
MOVEMPLOY 4.1017 1.140 0.011 1.000
PREPENTRY 3.4300 0.929 0.163 0.113 1.000
SATISEDUC 3.1800 0.839 0.333 –0.033 0.214 1.000
Source: Own source.
In all cases, Pearson’s coefficient was that introduced minor changes and/or rela-
(r) > 0; therefore, a positive correlation was tionships to check whether the model was
established between the variables, which suitable, or whether those changes needed
were directly related. The exception to this to be made. Therefore, the objective of the
trend was the negative correlation between first analysis within SEM methodology was
the variables SATISEDUC and MOVEM- to determine the model’s best fit using di-
PLOYMENT, with a value of r = –0.033, fferent approaches, all of which were based
which showed that these variables were in- on the theoretical foundations and literature
versely related. A result that supports the consulted. In this study, two alternative mo-
decision not to establish a direct relation- dels to the theoretical one are proposed: M1
ship between these two variables in the hy- and M2. In these two models, a new cons-
pothetical model proposed from the theory. truct or variable, USEFSKILLS, was inclu-
ded to refer to how useful students believed
the same scale of skills proposed in the DE-
Structural analysis VSKILLS variable were, but in this case, to
face the process of entering the labour mar-
The proposed theoretical model (M T) was ket. The first model (M1) included the direct
compared with a number of related models relationship between USEFSKILLS → PRE-
Reis. Rev.Esp.Investig.Sociol. ISSN-L: 0210-5233. N.º 176, October - December 2021, pp. 59-78Cristina González-Lorente and Pilar Martínez-Clares 71
PENTRY, while M2, in addition to this rela- However, there were differences between
tionship, included USEFSKILLS → SATISE- them, as was the case with the Chi-Square
DUC to measure whether the importance statistic (X2). Although this absolute value
that students attached to the proposed em- was lower in M2, its significance was closer
ployability skills had any influence. to 0.05, thus establishing a worse fit than
The results of this comparative analysis in MT and M1 (which had a p value of 0.153
are shown in Table 6, where it can be seen and 0.103, respectively, that is, considerably
that the goodness-of-fit indices were very higher than 0.05, statistically insignificant in
similar and acceptable for all three models. practice) (Gravetter and Wallnau, 2014).
Table 6. Fit indices for the proposed theoretical model and related ones
Theoretical (MT) M1 M2
Chi-Square (CMIN) 8.066 7.701 6.926
Degrees of freedom (gl) 5 4 3
Chi-Square value p 0.153 0.103 0.074
CMIN/df 1.613 1.925 2.309
CFI 0.992 0.990 0.990
RMSEA 0.020 0.024 0.029
Source: Own source.
A better fit was also observed in the the bachelor’s degree (H1) and the stu-
case of the MT model by calculating the dents’ greater satisfaction with the educa-
ratio between X2 and the degrees of free- tion received in order to meet the process
dom and obtaining a lower value (1,613) of entering the labour market (ß = 0.334).
compared to those obtained in M1 and M2, For H2, the values of p were also lower
as recommended by Schermelleh-Engel, than 0.001 and therefore, the ß coeffi-
Moosbrugger and Müller (2003). For the cients indicated the positive relationship
rest of the indices included in Table 6, CFI that the acquisition of skills had to the
and RMSEA, the results were slightly bet- students’ perception of their chances in
ter in the initial theoretical model (MT), as entering the labour market, with a total in-
CFI was closer to 1 and the RMSEA value fluence of 0.174 as a result of their direct
reached 0.02, and was therefore consid- (ß = 0.110) and indirect (ß = 0.064) rela-
ered to be a good fit (Browne and Cudeck, tionship.
1993). On the basis of these results, it was Finally, Figure 2 shows the standard-
decided to use MT to analyse the relation- ised regression coefficients that both sat-
ships between the variables and test the isfaction with the education received (H3)
research hypotheses. and low willingness to relocate for work
The standardised regression coeffi- (H4) had on the students’ perception of a
cients (ß) shown in Figure 2 allowed the proper transition from study to the labour
hypotheses of this study to be verified market. In both cases, p was less than
(MT). All these coefficients are statistically 0.001 and a positive and direct relationship
significant, which confirms, firstly, a posi- was established with the ß coefficients
tive and direct relationship between the shown in Figure 2, confirming hypothe-
acquisition of employability skills during ses H3 and H4.
Reis. Rev.Esp.Investig.Sociol. ISSN-L: 0210-5233. N.º 176, October - December 2021, pp. 59-7872 Which Factors Influence a University Student’s Entry into the Workforce?
Figure 2. SEM results
SATISEDUC
ơ = 0.334***
H2
ơ = 0.064*** ơ = 0.192***
H1
H1
DEVSKILLS PREPENTRY
ơ = 0.110***
H3
ơ = 0.124***
MOVEMPLOY
*** p < 0.001.
Source: Own source.
Discussion and conclusions Miguens and Lampón, 2014; Räty et al.,
2019) have highlighted how skills of this
One of the first conclusions drawn from this type have not been sufficiently addressed
study lies in the contribution of the causal in traditional university education, marked
model constructed on the basis of expert opi- by academicism, objectives and the as-
nions, in which goodness-of-fit indices were similation of knowledge in a vertical teach-
obtained that endorsed its design. As in this ing approach (Caballero, López-Miguens
study, some previous studies (Chiva, Ramos and Lampón, 2014). An issue that Pineda-
and Moral, 2017; Michavila et al., 2018; Nor- Herrero, Ciraso-Calí and Armijos-Yambay
then and Kurland, 2013; Stokes, 2015; Wu, (2018) argued is one of the most important
Tennyson and Hsia, 2010) focused on unra- deficits of university education from the
velling the complex process involved in the students’ perspective.
entry into the labour market of new genera- The causal model showed that the de-
tions with high education levels. These are velopment of these skills has a direct impact
based on the relationship and effect that di- on the perception that university students
fferent personal, social, economic and acade- have of meeting the challenges involved in
mic factors have during this process. entering the labour market, thus confirming
Today’s social and occupational dy- hypothesis 1. Although with a lower total re-
namics are highly complex and unpre- gression weight than expected, perhaps re-
dictable, which means that graduates are lated to the existence of other external and
faced with new challenges. In addition to internal factors (Pineda-Herrero, Ciraso-Calí
possessing the knowledge and skills spe- and Armijos-Yambay, 2018), this hypothesis
cific to their area of education, they must was validated by a direct and positive rela-
deploy a series of generic or transver- tionship, in line with the contributions from
sal skills. As shown in the present study, Arco and Enciso (2011). The latter noted
where university students reported that the need to make this relationship visible
they possessed these low or mid-level through the European Higher Education
skills, other studies (Caballero, López- Area (EHEA) so that, stronger, more effec-
Reis. Rev.Esp.Investig.Sociol. ISSN-L: 0210-5233. N.º 176, October - December 2021, pp. 59-78Cristina González-Lorente and Pilar Martínez-Clares 73
tive links can be finally established between ship between satisfaction with education
the university and the labour market (Fern- and success in entering the labour market;
ández-Salinero and García-Álvarez, 2020). although in this case, the survey was car-
An important conclusion was the corre- ried out on recent graduates who had al-
lation between the acquisition of transver- ready found their first job.
sal skills and satisfaction with the education However, university students’ percep-
received at the initial stages of university tion of being better prepared to meet the
study. Hypothesis 1 was validated by a high demands of the employment market does
regression coefficient (ß = 0.334), in line not only depend on skills training and their
with other studies such as those by Blanco, overall satisfaction with the education re-
Sánchez and Tallón (2019) and Sonlleva, ceived. Although there are other internal or
Martínez and Monjas (2019). This was also external factors, such as each student’s in-
demonstrated in the study by Ruiz-Cor- terests, personal and contextual opportu-
bella, Bautista-Cerro and García-Blanco nities and their transversal skills (Pineda-
(2019), where university students’ training Herrero, Ciraso-Calí and Armijos-Yambay,
in employability skills increased satisfaction 2018), the proposed causal model pointed
with the education received. In addition, to the influence of another factor: university
this study explores the contributions, beliefs students’ predisposition to relocate in their
and evaluations of final-year undergraduate search for employment (H3).
students about their skills background and
how this can influence their preparation Despite the fact that many experts con-
for working life. Along these lines, Qenani, sider that part of the success in the em-
MacDougall and Sexton (2014) found in a ployability of workers can be attributed to
study conducted among American students their flexibility and willingness to relocate
that the confidence of final-year students (Räty et al., 2019; Pastore and Tomei, 2018;
regarding their employability and employ- Wood, 2011), the university students sur-
ability skills decreased the longer they stud- veyed did not see this as a priority. The re-
ied at university and the closer they came to lationship with their perceived preparation
having to face this process. These authors for entering the labour market reflected a
underlined the direct influence between sat- weaker significance of hypothesis 3. A re-
isfaction with education and the skills ac- sult that suggests that it would be interest-
quired during the years of study, as was the ing to new lines of research in the future
case in the present study with the confirma- using hypotheses that relate the effect of
tion of hypothesis 1. university students’ willingness to relocate
for work and how their experiences abroad
It can be concluded that there is a sig-
can enhance the development of skills that
nificant and direct causal effect of student’s
favour entering a global economy and a
satisfaction with the training received on
permeable market.
the real likelihood of them gaining employ-
ment (H2). The confirmation of this second One of the limitations of this study lies
hypothesis is not only supported by the precisely in having obtained some lower-
results obtained, but also by other stud- than-expected regression coefficients in re-
ies such as the report conducted by Pérez lation to willingness to relocate. However,
(2018). It highlighted that receiving satisfac- and in spite of this, all the causal relation-
tory education encourages employability ships of the hypothetical model have a sig-
by 12% from students’ point of view. The nificant influence on the perception that
study by Blanco, Sánchez and Tallón (2019) university students have when faced with
also stressed that there is a direct relation- entering the workforce.
Reis. Rev.Esp.Investig.Sociol. ISSN-L: 0210-5233. N.º 176, October - December 2021, pp. 59-7874 Which Factors Influence a University Student’s Entry into the Workforce?
A conclusion that looks to the future is Blanco, Marta; Sánchez, Esteban and Tallón, Elena
that, given the complexity of this process at (2019). “La inserción laboral y la satisfacción de
los egresados del Grado en la Facultad de Tra-
present and the number of factors that di-
bajo Social de la Universidad Complutense de
rectly and indirectly influence it, this line of Madrid”. Cuadernos de Trabajo Social, 32(2): 329-
research should be pursued further, and the 340. doi: http://dx.doi.org/10.5209/cuts.60790
sampling scenarios should be expanded in Browne, Michael W. and Cudeck, Robert (1993).
order to be able to draw broader conclu- “Alternative Ways of Assessing Model Fit”. In:
sions in the international context. Universi- Bollen, K. A. and Long, J. S. (eds.). Testing
ties should provide connective tissue ca- Structural Equation Models. Newbury Park: Sage
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Lampón, Jesús F. (2014). “Spanish Universities
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