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Perceived learning opportunities,
behavioral intentions and
employee retention in technology
organizations
Andrea Valéria Steil,Denise de Cuffa,Gabriel Horn Iwaya and
Roberto Carlos dos Santos Pacheco
Federal University of Santa Catarina, Florianopolis, Brazil
Abstract
Purpose –This study aims to identify the relation between perceived learning opportunities, behavioral
intentions to voluntarily stay or leave technology organizations and employee retention within these
organizations.
Design/methodology/approach –This is a survey of 440 employees of a technology organization.
Findings –Learning opportunities perceived by managers and technicians presented significant positive
correlations with the intention to stay and significant negative correlations with the intention to leave the
organization. No relation was identified between perceived learning opportunities and manager retention.
Among technicians, the correlation between perceived learning opportunities and retention was near zero.
Practical implications –If the organization wants to guarantee the intention of professionals to stay in
the organization, the “perceived learning opportunities”indicator should have asimilar level of importance as
other objective indicators, such as performance and achievement.
Originality/value –To the best of the authors’knowledge, this is the first study to identify relations
between perceived learning opportunities and behavioral intention to stay and leave of professionals that
work in technology organizations.
Keywords Intention to stay, Intention to leave, Learning opportunities at work, People retention,
Technology organizations
Paper type Research paper
1. Introduction
Technological advances have altered functional demands within technology organizations.
Projections from the World Economic Forum (2016) indicate that five million job positions
will disappear by 2020 because of changes generated by artificial intelligence, robotics and
nanotechnology. Other positions will be transformed, generating changes in organizations
and on-the-job demands.
Regional and global initiatives have been put forward to address these challenges.
Examples include DigComp 2.1, the European digital competence framework for citizens
(Carretero et al.,2017) and the global framework of reference on digital literacy skills for
indicator 4.4.2 (Law et al.,2018). These frameworks present the necessary competences,
proficiency levels and examples of use to improve the level of proficiency in digital literacy
This study was developed with the support of the National Council of Technological and Scientific
Development (CNPq) –Brazil (Process number 446551/2014-7) and of the Coordination of
Improvement for Personnel with a Higher Education –Brazil (CAPES) –Finance Code 001.
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Received 8 April2019
Revised 20 November2019
Accepted 20 November2019
Journal of Workplace Learning
Vol. 32 No. 2, 2020
pp. 147-159
© Emerald Publishing Limited
1366-5626
DOI 10.1108/JWL-04-2019-0045
The current issue and full text archive of this journal is available on Emerald Insight at:
https://www.emerald.com/insight/1366-5626.htm
skills for employment, decent jobs and entrepreneurship (Carretero et al.,2017;Law et al.,
2018).
Technology organizations’capability to innovate, add value to production and gain
competitive advantage depends on the knowledge and the technical, managerial and
interpersonal competence of their employees (Lytras and Pouloudi, 2006). At the same time,
employees are increasingly assuming activities toward the development of their careers and
learning choices to improve their professional development (van Dam, 2004;Boomaars et al.,
2018). Empirical evidence shows that the higher the skills, the higher the employability in
internal and external labor markets (van Dam et al., 2006). The acquisition of knowledge and
skills to increase employability transpires through engaging in learning activities in and
outside organizations.
Learning opportunities in organizations are related to three types of learning:
experiential, social and formal. Experiential learning occurs through challenging work-
based assignments as an integral part of any complex job. Social learning takes place in the
form of peer and management support, mentoring and feedback. Formal learning refers to
structured training and development programs carried out by the organization to improve
the level of knowledge and skills of its workforce (Johnson et al.,2018). Carbery and Garavan
(2007) found that employees who want to develop themselves and plan their activities have
greater knowledge of learning opportunities provided by the organization.
Perceived learning opportunities are considered an important variable because the more
often the employees perceive learning opportunities in the organization, the more they will
undertake employability activities such as acquiring new knowledge and developing new
skills (Boomaars et al., 2018). In a global survey of more than 4,300 managers, executives
and analysts working in digital business, Kane et al. (2018) found that more than 90 per cent
of respondents perceived the need to update their skills at least once a year to work
effectively in the digital world.
How employees perceived the learning opportunities in the organization also influenced
important organizational behavior variables (Mourão et al., 2014) such as behavioral
intentions. An intention refers to a person’s decision to act and the effort he/she is willing to
take to perform a behavior (Abraham and Sheeran, 2003). The propositions of planned
behavior theory state that people intend to engage in a behavior when they evaluate it
positively (attitude), when they believe that people important to them want to see them
engaged in this behavior (subjective norm) and when they perceive that the behavior is
under their control (perceived behavioral control). Intentions are the most important
cognitive antecedent of behavior (Ajzen, 2011). They are responsible for 20-30 per cent
variance in behavior within different domains (Armitage and Conner, 2001;Sheeran and
Abraham, 2003).
Intention to stay in the organization refers to the conscious and deliberate desire of an
individual to remain in the organization in which he or she works (Mowday et al.,1982); the
intention to leave is the conscious and deliberate desire of an individual to leave his or her
current employment in the near future (Mowday et al., 1982). Although a fast judgment may
lead to the conclusion that the intention to stay and the intention to leave the organization
are the opposite ends of the same construct, that is not the case. Nancarrow et al. (2014)
demonstrated that the intention to leave the organization and the intention to stay in the
organization do not measure the same construct. That is because both constructs refer to
intentions to perform different behaviors, revealing two distinct constructs. Besides,
Nancarrow et al. (2014) and Bello (2017) found out that the factors that influence the
employees’intention to leave the job do not necessarily influence their intention to stay at
the job because there isno complementary relationship between these twoconstructs.
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Failing to attract and maintain qualified personnel was considered the number one issue
in the Conference Board’s 2016 survey of global CEOs, proving more important than
economic growth and level of competition (Keller and Meaney, 2017). Employee retention is
the ability of the organizations to maintain specific groups of professionals working for
them (Brown et al., 2013) to reach their strategic objectives (Frank et al.,2004).
A study by McKinsey Global Institute points out that the European and North American
markets will need 16 million more professionals with a higher education in 2020 than the
prefigured number of professionals with such profile for that period. In addition, it is also
estimated that within these markets 95 million professionals will not have the required skills
to enter the job market. Further, developing economies will have 45 million less
professionals than necessary with a secondary school education and vocational training
(Keller and Meaney, 2017). The need for qualified manpower in positions that demand
continuous learning and the importance of such professionals to organizations lead us to the
reasons that motivated this research: Is there a relation between perceived learning
opportunities in technology organizations and behavioral intentions to stay or to voluntarily
leave such organizations? Is there a relation between perceived learning opportunities and
professional retention within technology organizations?
2. Perceived learning opportunities and behavioral intentions
There is contradictory evidence regarding the relation between perceived learning
opportunities and employees’intentions to stay in the organizations. Although some studies
showed a positive relation (Chiang et al., 2005;Chew and Chan, 2008;Rowden and Conine,
2005), other studies did not identify such relation (Newman et al.,2011;Steil et al., 2018).
The relation between perceived learning opportunities and the intention to voluntarily
leave the organization has been investigated to an even lesser extent. One study with
professors found a negative relation between learning opportunities and the intention of
such professionals to leave their current employment (Proost et al., 2012). This relation was
also found in studies with young doctors (Degen et al., 2014) and technical and scientific
professionals (Steil et al., 2018).
To verify the relation between perceived learning opportunities and the employees’
intentions to stay or to leave technology organizations, the following hypotheses were
raised:
H1. The higher the perception of learning opportunities, the greater the employees’
intentions to stay in technology organizations.
H2. The lower the perception of learning opportunities, the greater the employees’
intentions to leave technology organizations.
3. Perceived learning opportunities and retention
Studies in hotels, the public sector, universities and the steel production industry reveal a
positive relation between training and personnel retention (Moncarz et al.,2009;Oliveira
et al.,2012;Hong et al.,2012).
Further, there is evidence that actions directed toward training individuals also influence
the ability of the organizations to maintain qualified professionals (Walsh and Taylor, 2007).
A study by Moncarz et al. (2009) verified that training and development actions resulted in
improved employee performance, which in turn contributed to their staying within the
organizations researched. Nevertheless, a study on technical and scientific professionals
from research and development organizations did not relate training and development
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opportunities to permanence of such professionals in the organization where they worked
(Steil et al.,2018).
To verify the relation between perceived learning opportunities and employee retention
in technology organizations, the following hypothesis was raised:
H3. A relation exists between perceived learning opportunities and personnel retention
within technology organizations.
4. Methods
4.1 Target audience
The target audience of this study is professionals who worked in technology organizations
in the state of Santa Catarina, Brazil. The research used a non-probabilistic sample of 440
professionals.
4.2 Measures
Scales validated for the Brazilian scenario were used to measure intention to stay, intention
to leave and perceived learning opportunities (Table I).
4.2.1 Intention to stay. Intention to stay was measured by seven items. Each of the items
presented a scenario, with two alternatives representing two extremes on a five-point scale.
The following is an example of a scenario:
You learned that a new company, larger than yours, operating in the same area and offering
equivalent working conditions to the company you work is recruiting new workers. Given this
information, what would you do?
For this scenario, there were two alternatives:
(1) I would take some initiative to move to the new company.
(2) I would not take any initiative to move to the new company.
4.2.2 Intention to leave. Intention to leave was measured with three items. The first item was
“I think about leaving the company where I work.”The second item was “I plan to leave the
company where I work.”The third item was “I want to leave the company where I work,”
which was rated on a scale ranging from 1 (never) to 5 (always).
4.2.3 Perceived learning opportunities. The construct perceived learning opportunities
was measured by 13 items on a five-point scale ranging from 1 = totally disagree to 5 =
totally agree. Some items were as follows: “The organization I work for stimulates the
development of new skills and attitudes at work,”“The organization I work for develops
continuing education programs”and “The organization I work for stimulates knowledge
sharing.”
A pre-test was carried out on 77 professionals who work in technology organizations in
Santa Catarina. The Kaiser–Meyer–Olkin (KMO) test was used to verify whether the
instrument was appropriate to evaluate the constructs and the target audience. Values from
scales of intention to leave the organization (EIR)[1] (KMO = 0.76), behavioral intentions to
stay in the organization (EICPO)[2] (KMO = 0.82) and perceived learning opportunities in
organizations (EPOA)[3] (KMO = 0.95) indicated that the measures present factorability
because the values are above 0.70 (Hair et al.,2005).
The measures also presented good internal consistency for the studied population.
Finally, to verify data normality of each dependent variable (retention, intention to stay and
intention to leave), the Shapiro–Wilk (4 <N<2000) normality test was applied. The test
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rejected the normality hypothesis of data (p-value = 0.000) variables. Thus, non-parametric
tests were used.
Deliberations related to measures of the retention variable are considered
important. Retention has been measured both with objective indicators (length of
service of a professional in the organization) and with subjective indicators
(cognitions related to professional’s staying or leaving) (Yamamoto, 2011). Because
cognitions (such as the intentions) antecede behaviors, in this study, the length of
service of a professional in the organization at the time of data collection was used to
measure retention (objective measure). However, it is important to consider that
although the current length of service may be a retention indicator of these
professionals, this period is not representative of their total time in the organization.
The total time of a professional in an organization is the measure that truly reflects
his or her retention, but this may only be assessed after that employee has effectively
left the organization. Hence, current length of service in an organization does not fully
reflect retention, as it is not yet known how much longer the respondent will remain in
the organization (he or she may stay for one day or many years). Despite this
restriction, this still is the best measure for research on professionals who are
currently employed in the organization.
4.3 Data collection
This study used secondary data drawn from a research project survey titled “Rewards and
professional retention in knowledge-intensive technological organizations in Santa
Catarina,”which was carried out between December 2, 2014 and December 2, 2017.
4.4 Data treatment and analysis
Data were compiled and treated through SPSS version 25 statistical software. The Kruskal–
Wallis test was applied to compare values of twogroups (managers and technical staff) from
independent samples. The Spearman test was also used to verify the existing correlation
between variables.
Table I.
Variables studied
Variables
Cronbach’s
(original scale)
Cronbach’s alpha
(found in this study) Measures
Retention of personnel ––Length of service in organization
measured in months
Intention to stay (EICPO) 0.95 0.74 Seven items evaluated on a scale
of 1 = totally disagree to 5 =
totally agree (Menezes and Bastos,
2010)
Intention to leave (EIR) 0.95 0.94 Three items evaluated on a scale
of 1 = never to 5 = always
(Siqueira et al., 2014)
Perceived learning
opportunities (EPOA)
0.94 0.96 A total of 13 items evaluated on a
scale of 1 = totally disagree to 5 =
totally agree (Mourão et al., 2014)
Source: Steil et al. (2019)
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5. Results
The research sample was composed of 440 professionals who worked in technology
organizations in Santa Catarina, Brazil. The average age of respondents was 29years (S =
7.36). Most respondents had an undergraduate degree (45.23 per cent) or graduate degree
(34.32 per cent). Finally, 68 per cent of the respondents were male, and 32 per cent of
respondents were female.
Most respondents (83 per cent) held technical positions (for example,
administrative analyst, buyers, programmer, business consultant and software
development). The remaining 17 per cent who worked in management positions
performed in areas such as information technology, projects, billing, marketing,
finance and technical support. Because these two categories (technician and
management) exist, a Mann–Whitney test was carried out for independent samples to
verify whether the distribution of variables was the same for both groups. The null
hypothesis was accepted for variables EPOA (p= 0.064), EICPO (p=0.283)andEIR
(p= 0.592), demonstrating that there were no significant differences in variables
distribution related to the job performed.
As for retention variable (length of service in the organization measured in months),
the alternative hypothesis was accepted (p<0.000) because of differences verified in
the distribution of variables between managers and technicians. Descriptive statistics
showed that there were professionals who were working in the surveyed organizations
for less than a year as well as professionals working in the organizations for 30 years.
The average length of service of professionals in the study was 44 months –75 for
managers and 38 for non-managers. Both groups (technicians and managers) had close
average scores for intention to leave, intention to stay and perception of learning
opportunities. On a scale ranging from one to five, results indicate that professionals
have a relatively high intention to stay and a median intention to leave. Moreover, from
the professionals’perception, the researched organizations offer median learning
opportunities. The minimum, maximum, mean and standard deviation values of the
variables are seen on Table II.
Perceived learningopportunities of professionals (managers andtechnicians) presented a
positive correlation with the intention to stay (0.514; 0.435) and a negative correlation with
the intention to leave the organization (0.567; 0.532). In both groups, the level of
correlation was medium and significant (p<0.01). When professionals perceived that the
organization offered learning opportunities, an increase in the intention to stay in the
organization was observed in these professionals. Conversely, professionals with low
perception of learning opportunities demonstrated greater intentions to leave the
organization. The correlation results organized according to the group of managers and
technicians is presented on Table III.
Among managers, retention presented near-zero correlations with the other investigated
variables (EPOA = 0.014; EICPO = 0.011; EIR = 0.135). The ability of the organization to
retain managers is not related to the perceived learning opportunities, the intention to stay
or the intention to leave the organization.
As for technicians, the correlation between retention and perceived learning
opportunities is also near zero (0.056). In contrast, correlations between retention and
professionals’intentions to leave (0.269) and to stay (0.279) in the organization presented
significant values (p<0.01). Despite these correlations being low, evidence shows that
technicians with longer length of service in the organization tend to present lower intentions
to stay and greater intentions to leave.
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6. Discussion and perspectives
Perceived learning opportunities presented medium and significant positive correlations
with intention to stay in the organization both for managers (0.514) and technicians (0.435).
These results confirm H1 and indicate that the greater the perception of learning
opportunities, the greater the intention to stay in the organization will be. These findings
confirm results of earlier studies carried out in other countries and contexts (Chiang et al.,
2005;Chew and Chan, 2008;Govaerts et al.,2011;Hong et al., 2012).
Perceived learning opportunities also presented medium and significant negative
correlations with intention to leave the organization among managers (0.567) and
technicians (0.532). These results confirm H2 and demonstrate that the lower the
perceived opportunities, the greater the intention of professionals to leave organizations will
be. These results also support evidence found in earlier studies in Brazil and abroad (Proost
et al.,2012;Steil et al.,2018). Studies with Brazilian samples that used the same measures for
EPOA and EIR also had a negative correlation between perceived learning opportunities
and intention to leave the organization (Freitas et al., 2015;Germano, 2016).
Learning is concerned with developing reflection and skills through the awareness of and
adaptation to challenges that occur in one’s work experiences. Because of the competition
Table II.
Minimum,
maximum, mean and
standard deviation
values of the
variables
Variables Minimum Maximum Mean SD
Management
Retention 3.00 359.00 75.11 73.23
EPOA 1.00 5.00 3.00 1.00
EIP 1.00 5.00 3.44 1.00
EIR 1.00 5.00 2.57 1.21
Technician
Retention 1.00 353.00 37.96 42.72
EPOA 1.00 5.00 2.76 0.80
EIP 1.00 5.00 3.32 1.01
EIR 1.00 5.00 2.63 1.17
Notes: EPOA –Scale of perceived learning opportunities in organizations; EICPO –Scale of behavioral
intentions to stay in the organization; EIR –Scale of turnover intention; EIP –Scale of Intention to Stay
Source: Steil et al. (2019)
Table III.
Spearman’s
correlation coefficient
matrix of variables,
according to job
position
Correlation
matrix
Retention EPOA EICPO EIR
Managers Technicians Managers Technicians Managers Technicians Managers Technicians
Retention 1.000 1.000
EPOA 0.014 0.056 1.000 1.000
EICPO 0.011 0.269*0.514*0.435* 1.000 1.000
EIR 0.135 0.279*0.567*0.532*0.498*0.581* 1.000 1.000
N74 366 74 366 74 366 74 366
Notes: EPOA = Scale of perceived learning opportunities in organizations; EICPO = Scale of behavioral
intentions to stay in the organization; EIR = Scale of turnover intention. *The correlation is significant at
level 0.01 (2 extremes); Nis the number of respondents
Source: Steil et al. (2019)
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between the technology industry, their professionals are expected to develop strong
employability. As Van der Sluis and Poell (2003) posited, organizations can contribute by
offering learning facilities and stimulate their employees to undertake employability
activities (Wynekoop and Walz, 1998). Therefore, the relations suggest that workers of
technology organizations value learning opportunities offered by the organizations because
engaging in such actions increase their employability in the internal and external markets
(van Dam et al.,2006).
Both individual learning motives and work environment contribute to the prediction of
engaging in development activities (Boomaars et al.,2018). Evidence on the role that work
environment plays on development activities helps to explain relations found. In 2018, there
were at least 12,635 technology industries that employed 47,445 professionals, with
revenues surpassingR$15bn or close to $5bn (ACATE, 2018).
The technology industry of Santa Catarina competes for a similar pool of professionals,
generating a talent war. In a study with leaders of technology organization in this region,
Steil et al. (2016) verified that employees are encouraged to perform as headhunters in
exchange for financial compensation. On the one hand, if there exists an ethical problem in
this procedure, on the other it indicates that there is a scarcity of talented professionals and
that the market is willing to recruit them wherever they may be. It also proves that
developing employability is advantageous.
In a study about work and post-industrial occupations, Valdés and Barley (2016)
identified that professionals, managers and technicians were more likely have to learn how
to do their jobs at their workplace than those who worked elementary jobs. This rationale of
employability development through continued learning at the workplace is related to the
development of professional reputation.
Although reputation development is an old phenomenon, an increase has been observed
in the intensity with which this phenomenon is consciously realized by individuals while
striving for improved employability (Dumont, 2017). Statistics on current length of service
of professionals in organizations strengthen this argument. Qualified professionals show
growing work mobility, working in an average of six organizations throughout their career.
The US Bureau of Labor Statistics indicates that workers stay at each job on average for 4.4
years and expects 2.2 years of tenure for youngest workers (Keller and Meaney, 2017). In
Brazil, the average length of service at each job is five years (DIEESE, 2014). That is if the
professional aspires to work in different organizations throughout his or her career, building
a reputation through skills development becomes important in achieving this goal.
Consequently, it makes more sense to have the intention to stay in organizations where
learning opportunities are perceived and to have the intention to leave organizations where
they are not.
Perceived learning opportunities and retention presented a near-zero correlation between
management and technician groups. In similar studies, Steil et al. (2018) and Bezerra (2018)
also identified near-zero correlation values between training and development and retention
(0.02) and length of service and learning opportunities (0.09), respectively. Thus, H3 was
rejected and we accepted the null hypothesis that perceived learning opportunities do not
influence retention. Then how are these results interpreted? Why is there a relation between
perceived learning opportunities and the intention to stay in the organizations when there is
no relation between perceived learning opportunities and retention in the study sample?
This result may seem contradictory because behavioral intention is the principal cognitive
determinant of behavior. There are two issues we consider important in this discussion. The
first is related to the retention measure and the second to the average length of service in an
organization.
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As previously exposed in the methods section, because our study includes professionals
who are currently working in organizations, it is not possible to measure their exact total
length of service in the organizations. We can only measure current length of service in the
organization. Even though this is the quantitative measure that is closest to a true measure
of retention, it is not capable of fully measuring this phenomenon. Further, retention can
only be fully measured when the professional has effectively left the organization. We
consider that this helps to explain the extremely low correlation between perceived learning
opportunities and retention, both for managers and technicians (0.014; 0.056). This
consideration is also important to demonstrate that applying objective retention measures to
professionals that are currently working remains a challenge to scientists in this field.
The average length of service of professionals in organizations also needs to be weighed
when discussing retention. Johnson (2000) suggests that retention reflects the organizational
ability to maintain professionals desired by the organization for longer lengths of time than
their competitors can maintain their professionals. In Brazil, the average total length of
service at a job in all areas is five years. In this study, the average length of service
of researched professionals was 44 months (under four years), being that the average length
of service of managers was 75months (over six years), with 73.23 standard deviation, and
the average length of service of technicians was 38months (over three years), with 42.71
standard deviation. Despite the removal of extreme values, this result is evidence that
current length of service in the organization is extremely varied, making it difficult to work
with the current average time as a retention measure.
We raised these elements as an attempt to comprehend the near nonexistent relation
between perceived learning opportunities and retention in the research sample. Nonetheless,
it is important to emphasize that transversal data were used for this study. A longitudinal
research could contribute to verify the predictive effect of intentions (to stay and to leave the
organization) on retention. For future studies, we suggest that intentions to stay and to leave
the organization be raised periodically so as to compare them to the total length of service of
employees (real retention measure).
This suggestion is based on several intentions properties that influence the consistency
of the intention–behavior relation which are accessibility, certainty and temporal stability
(Cooke and Sheeran, 2013). Intention stability is the most powerful moderator to influence
the intention–behavior relation. This is to say that intention stability is the best indicator of
an intention’s probability being converted into behavior (Cooke and Sheeran, 2013;Sheeran
and Abraham, 2003). In this sense, the stability level of an intention may be inferred as a
basis for periodical measures of intentions (Sheeran and Webb, 2016).
Furthermore, another inherent challenge in studies regarding the investigation of
behavioral intention has to do with the complexity of collecting measures of real behavior.
Evidence suggests that intentions are more easily translated into actions when the
respective behaviors are easily realized. Intentions to stay and to leave an organization are
related to complex behaviors and involve contextual factors. In such cases, control beliefs
related to perception of difficulty to realize a specific behavior may moderate in a less
consistent intention–behavior relation. This is likely because people underestimate or
overestimate how difficult it is to realize the actual behavior (Sheeran and Webb, 2016).
The results of this study show that perceptions of learning and behavioral intentions
matter in the workplace and have implications for practice. Because learning is integral to
activities in technology organizations, it is suggested that such activities offer opportunities
for learning technical, interpersonal and managerial skills with a focus on complex and non-
structured problem resolution. We stress the importance of not only offering such
opportunities, but also of ensuring that they be effectively comprehended as such by
Perceived
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employees. Employees should understand that these opportunities exist and that they
personally benefit from them.
It is recommended that technology organizations nurture a culture and establish policies
and practices that support thelearning strategies used by their employees, focusing on those
that align with their organizational mission and that are perceived as effective by workers.
Examples of these learning strategies for acquiring expertise, skills and attitudes include
realizing courses and events, engaging in new tasks, working with different people,
e-learning, observing others at work, rewarding initiative rather than demonizing errors,
making time available for reading and research, reflecting on specific actions and receiving
continuous feedback (Crouse et al.,2011).
It is important to also guarantee that there are no barriers to the learning process. The
main groups of barriers that have been described by Crouse et al. (2011) are resource
constraints, lack of access, technological constraints, personal constraints, interpersonal
constraints, structural and cultural constraints, course/learning content and delivery, power
and change pace. Finally, we suggest the organization realize a diagnosis of the learning
strategies used, of learning process facilitators and of existing barriers. The diagnosis must
be the first step in establishing an integrated learning strategy for technology organization
workers, having direct implications in the intention of professionals to stay in the
organization.
This study raises implications both for the learning policies of technology
organizations and for career management of technical and management professionals. In
an organizational plan, this set of measures may either mitigate the risks of losing
professionals or strengthen the reputation of the organization as a place of opportunities,
enhancing its ability to acquire talent. Results also reinforce the responsibility of
organizational leaders to offer new and constant learning opportunities to their direct
contributors. In conclusion, for professionals in the technology sector, results support
studies that prove continued learning to be an increasingly present factor in career
decisions.
Notes
1. EIR –Turnover Intention Scale.
2. EICPO –Behavioral Intentions to Stay in the Organization Scale.
3. EPOA –Perceived Learning Opportunities Scale.
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Corresponding author
Denise de Cuffa can be contacted at: denise_cuffa@hotmail.com
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