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Investigating The Impact of Emotional Intelligence On
Technology Learning
Abeer Hmoud Ali Al‐Faouri Management Information Systems Department, Petra University, Amman, Jordan ABSTRACT
This study aims to investigate the impact of interpersonal self‐awareness, self‐confidence, and self‐
discipline, as well as intrapersonal empathy, optimism, and social responsibility‐ emotional intelligence (EI) dimensions on technology learning process levels (TLP). An empirical study with a questionnaire, was conducted on 124 voluntary respondents from 10 IT organizations in Jordan. The findings indicated that the EI intrapersonal sub dimensions were responsible for 30% in variation of the TLP basic level. Only the self‐discipline variable could predict average, advanced, and world‐class TLP levels in comparison with optimism which significantly predicted the TLP levels except for the average one, which was predicted by the social responsibility variable. This study is the first study to investigate the relationship between EI and TLP levels. The outcomes provide an empirical support for an interesting parallel between the both. Moreover, the practical implications of this study suggest considering EI competences when selecting and promoting the IT staff; and when designing the TLP training programs.
Keywords‐ Emotional Intelligence, Interpersonal Intelligence, Intrapersonal Intelligence, Technology Learning Levels. I. INTRODUCTION In today's dynamic and complex business environment, organizations need to reinvent themselves to
succeed [7], [49], [24]. Consequently, investment in IT is viewed as a strategic means of organizational
renewal [49], along with improved organizational performance [22], [49], and competitive advantage. Thus,
other supplemental effective efforts should be devoted to change management [35], and organizational
learning in general and technology learning process in particular in order to identify the technological threats
and opportunities in the rapidly changing environment [25]. Empirical studies suggest that organizational
performance and learning are more effective if enacted by emotionally intelligent employees [7], [37], [1]
who tend to achieve outcomes that benefit others as well as themselves [33]. Unfortunately, high-technology
workers are generally perceived as a staff with high intellectual skills but with low interpersonal and
intrapersonal skills [34]. Others ensure that American business annually loses between 5.6 and 16.8 billion
dollars due to the inconsistency in following guidelines to promote emotional intelligence [9]. There is
relatively less research related to the influence of emotional intelligence on technology learning. Therefore,
the purpose of this research is to investigate the impact of both emotional intelligence intrapersonal and
interpersonal dimensions on technology learning levels including the basic, average, advanced, and worldclass levels.
This paper is organized as follows. The next section introduces the concepts of technology learning concept
and its four levels as well as emotional intelligence and its key dimensions, followed by the development of
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the research hypotheses. The research method is presented in the third section. Data analysis and the results of
this study are discussed in the fourth and the fifth sections respectively. Finally, the study’s implications and
limitations are summarized in the sixth section.
II. THEORY AND HYPOTHESES TECHNOLOGY LEARNING
Basically, learning is acquiring new knowledge, behaviors, skills, values, preferences and/or understanding,
and may involve synthesizing different types of information [41] that can be retained and used when needed
[42]. The need for technology learning stems from the fact that technological knowledge options available to
a firm represent a critical factor [16],[30] in shaping the firm’s technological strategy in the light of the
exploitable opportunities as well as the technological threats it may face in the future [4], [30].
According to Boucher et al. (2003), technology learning process (TLP) is defined as an intentional or an
unconscious initiated process of technology scanning, monitoring, and valuation. Consequently, two main
phases in TLP literature were distinguished. Namely, the scanning and the monitoring phases [29], [53].
Through effective technology scanning, firms will not be surprised when new technologies appear. However,
they will be able to develop technological awareness [30]. This shows that TLP is used to understand the
systematic recognition, the observation of new and/or existing technologies in addition to the evaluation of
their significance and potential for the competitiveness of the company [25]. Others agree that the
accumulation of technological capability does not only result from experience but also from scanning,
monitoring and keeping track of global developments aim to increase the companies' ability to respond to new
pressures and opportunities [8], [4].
According to Dabnoon (2008), TLP is classified into four levels including the basic level, which is the
lowest level, along with the average, advanced, and the world-class levels. The latter is considered the
highest. The basic level represents poor factors that companies usually concentrate on in order to learn about
the market changes and some technological developments such as building external co-operations,
participating in some associations, and analyzing several government sources and business literature [25]. The
average level is concerned with informal learning methods. This may include establishment of informal
discussion networks, availability of internet and intranet, application of technology roadmaps, etc [25]. On the
other hand, TLP advanced level is essentially characterized by the need to support R&D department,
providing support and commitment of top management, providing training programs, and coordinating
between human resource planning and learning strategy [25]. The TLP world-class level is seen as a relative
challenge to be accomplished. This level requires the companies to establish centralized and decentralized
units, and to launch projects of limited duration in order to learn about advanced technologies and overall
market changes. In addition, collaboration with universities, research institutes, start-ups and leading
companies as well as arrangement of innovation workshops are also needed. Both this classification, and the
items representing each level are adopted in this research – see tables: II, and I.
Reviewing literature declares the importance of TLP and the role it plays to increase the organizations’
effectiveness. Consequently, we discuss the once of intelligences referred to as (Emotional intelligence) and
its potential role in advancing the TLP.
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EMOTIONAL INTELLIGENCE
The emotional intelligence (EI) phrase has become popular since the 1990s when John Mayer and Peter
Salovey first coined the phrase ‘emotional intelligence’ [23]. According to Anzieu & Martin (1994), emotions
were first associated with organizations when early group dynamics theorists including Mayo and Lewin
introduced the concepts of human relations and social change in the workplace and declared their impacts on
organizational performance. Among the leading factors to EI prominence was the shift from a manufacturing
to a service sector focus which reveals a greater need for effective interpersonal skills, and engaging minds
with hearts [2], [43]. Goleman (1995) believes that IQ contributes around 20 percent to the factors that govern
success, while EI accounts for the remaining 80 percent. Therefore, many recommended that EI, alongside the
socio-cultural cues that influence emotional display, should be learned and understood within the context of
the workplace [27].
Emotional intelligence has been an interesting topic for a number of authors. For example, Salovey &
Mayer (1990) considered EI a subset of social intelligence that involves the ability to monitor one’s own and
others’ feelings and emotions. It is used to distinguish them and to use this information to guide one’s
thinking and actions. Robbins and Judge (2009) defined EI as the ability to detect and manage emotional cues
and information. Goleman (1998) viewed EI as the capacity for recognizing our own feelings and other’s for
the sake of managing emotions in ourselves and in our relationships. In addition, EI is defined as the ability to
understand and trust our own emotions as well as the capacity to read the emotions of others, so that
appropriate action can be taken [43], [5]. Reviewing the mentioned definitions leads to conclude that EI is
related to understanding our feelings and others’ feelings so as to achieve a better guidance in the process of
thinking for ourselves and the others and behaving respectively. EI is also discussed as multidimensional
concept that encompasses complementary dimensions. For example, Goleman (1995) and Robbins (2007)
listed five dimensions of emotional intelligence including self-awareness, self-regulation (management), selfmotivation, empathy, and social skills. Whereas Cook et al., (2004) viewed EI as ‘people-focused’ and based
on two major intrapersonal and interpersonal dimensions that were adopted in this study for their clearness
and comprehensiveness. In the following section, some light will be shed on these EI dimensions and their
influences on technology learning levels.
EMOTIONAL INTELLIGENCE DIMENSIONS AND TECHNOLOGY LEARNING LEVELS
According to Cook et al. (2004), emotions play the driving force behind all human behavior. Robbins and
Judge (2009) argue that people who know their own emotions might be more effective in doing their jobs.
Consequently, this increases the importance of understanding EI and its influence on the different aspects of
organizational practices such as organizational learning and technology learning in particular.
Basically, EI is based on two major dimensions, which are the intrapersonal and interpersonal dimensions.
According to Cook et al., (2004), the intrapersonal dimension focuses on the self, and includes three sub
dimensions, namely, self-awareness, self-confidence, and self-discipline. Self-awareness reflects the
importance of recognizing one’s own feelings, and realizing one’s own strengths and weaknesses [13]. In his
study, Goleman (1998) proved that emotional self-awareness is crucial in financial planners’ job performance.
Others found that accurate self-assessment was the hallmark of superior performance among several hundred
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managers from twelve different organizations [39]. From another perspective, a variety of studies declared
that self-confidence has a positive impact on performance. For example, Boyatzis (1982) and others [48]
found that among supervisors, managers, and executives; a high degree of self-confidence distinguished the
best from the average performers. Similarly based on his analysis of more than 300 top-level executives from
fifteen global companies, Spencer (1997) concluded that self-confidence was a factor among the emotional
competencies that distinguished stares from the average. According to Cook, Macaula and Coldicott (2004),
self-discipline which represents the third sub dimension deals with controlling one's anger as well as
managing frustration and impulse effectively. Lusch and Serpkenci (1990) showed that the most successful
store managers were those best able to handle stress in a retail chain.
Although the reviewing literature did not refer to studies that explicitly investigate the influence of EI on
technology learning, the researcher refers to extensive related literature review as a step aiming to fill some of
the existing gap in the field investigated.
In general, emotional intelligence is assumed facilitate individual adaptation and change [36]. Other
research areas showed that emotion and learning are closely associated with each other [2], and that learning
success does not only flow from rational capability but also from emotional capability development [17]. In
the learning environment as an example, many educators became increasingly aware of the fact that students'
emotional intelligence should be incorporated and embraced in the classroom [35] because confusing or
hurtful feelings cannot and will not lead to effective learning [26]. Elias et al. (1999), also emphasized that
emotional well-being is not a positively predictive of academic achievement but also of satisfactory and
productive experiences in the world of work. In the business environment, Cherniss and Adler (2000) state
that rapid technological change and diverse workforce make emotional intelligence so vital for organizational
effectiveness. Sparrow and Knight (2006) concluded that emotional intelligence leads to effective
performance [15] where intrapersonal intelligence is needed for effective self-management, interpersonal
intelligence is needed for effective relationship management, and both lead to effective overall performance.
Based on a sample of 280 employees from an Indian company, EI was found to be positively and significantly
related to the three phases of OL - innovation, implementation, and stabilization - and with the five
mechanisms of OL including experimentation, mutuality, planning, uses of temporary systems, and
competency mechanisms [47]. Similarly, others found that employees with high level of emotional
intelligence show higher level of readiness to create and innovate than those with lower level of emotional
intelligence [3]. In his study, Hjerto, (2009) proved that emotional intelligence dimension which strongly
contributes to learning is related the ability of using one’s own emotions, and the self-emotional appraisal
ability [21].
Thus, the researcher elicited the first main hypothesis of this study as follows:
H1: Intrapersonal EI dimensions: self awareness, self confidence, and self-discipline positively influence
technology learning levels: basic, average, advanced, and world-class level.
Four sub hypotheses can be generated from the previous main hypothesis as follows:
H1a: Self-awareness, self-confidence, and self-discipline positively influence the basic level of
technology learning.
H1b: Self-awareness, self-confidence, and self-discipline positively influence the average level of
technology learning.
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H1c: Self-awareness, self-confidence, and self-discipline positively influence the advanced level of
technology learning.
H1d: Self-awareness, self-confidence, and self-discipline positively influence the world-class level of
technology learning.
The interpersonal dimension of EI focusing on others has a deep understanding of others’ emotions, finds
ways to motivate them and maintain harmonious and effective relationships [43]. This dimension
encompasses three sub dimensions including empathy, optimism, and social responsibility [43]. The empathy
competence gives people a perceptive awareness of others’ emotions, and the ability to read others’ needs
[13]. Empathic strategy also distinguished the star sales performers with a higher ability to identify a
customer’s tacit needs from average ones with lower empathy competence. It also matches the former with
products or services [26]. In another study, Pilling and Eroglu (1994) found that skill in empathy correlates
with effective sales on large and small retailers. Steele (1997) concluded that empathy competence helps in
reading people accurately as well as avoiding resorting to stereotyping that might lead to anxiety and
performance deficits. Moreover, empathizing was also crucial to the conflict management skills and to
effective win-win negotiation in manufacturer-retailer relationship [14].
Optimism is the ability to look at the brighter side of life [38]. People who are optimistic are usually those
with a real sense of passion who are able to share their passions and raise a state of infection that motivates
people to be with them [43]. A study found that optimism was one of the important emotional intelligence
competencies that most successful debt collectors scored higher in [45].
The final sub dimension is social responsibility, which represents the ability to demonstrate oneself as a
cooperative, contributing, and constructive member of one’s social group [38]. Cook et al. (2004), argue that
people who have strong social responsibility have a focus on others' serious problems, and may gain new
perspectives on their own problems either through internal and external inter-organizational collaboration
[43].
Current researchers indicate the importance of teamwork and assure the crucial need for emotional
intelligence, and learning for both managers and employees [43], [44], [18]. Robbins and Judge (2009)
suggested that people who are good at reading others' emotions might be more effective in performing their
jobs. Sweeney (1999) found that a deficit in the ability to work cooperatively with peers was, in one survey,
the most common reason for firing managers. Goleman's research (1998) indicated that an individual must be
able to manage emotions at work and interact successfully with the public to produce positive work outcomes.
More specifically, other studies suggested that the emotional climate deeply affects organizational dynamics,
which facilitates the learning processes [52]. Jordan (2004) argued that each organizational learning discipline
including personal mastery, mental models, systems thinking, team learning, and building a shared vision for
the organization – could be linked to specific emotional intelligence abilities including (a) emotional
awareness, (b) emotional facilitation, (c) emotional knowledge, and (d) emotional regulation. Thus, the
second main hypothesis of this study is:
H2: Interpersonal EI dimensions: empathy, optimism, and social responsibility positively influence
technology learning levels including the basic, average, advanced, and world-class level.
From the previous main hypothesis, four sub hypotheses can be generated as follows:
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H2a: Empathy, optimism, and social responsibility positively influence the basic level of technology
learning.
H2b: Empathy, optimism, and social responsibility positively influence the average level of
technology learning.
H2c: Empathy, optimism, and social responsibility positively influence the advanced level of
technology learning.
H2d: Empathy, optimism, and social responsibility positively influence the world-class level of
technology learning.
Figure 1 shows the suggested model that was employed in this study.
III. THE STUDY AND METHOD 124 respondents included CEOs, CIOs, systems analysts, technical support specialists, network
administrators, and programmers represent different managerial levels (10% were top management) from ten
IT organizations in Jordan participated in this study. 75% of these participants were male. The ages of 79.8%
range from 31-40 years. 71.8% have 10-14 years of experience in their current jobs. 43.5% holds Bachelors
degree. All participants were asked to complete a questionnaire to assess the main and sub dimensions of their
emotional intelligence, and their organizations' technology learning levels within two months period in 2011.
The questionnaire was pre-tested with several respondents in three different organizations.
Emotional intelligence construct was measured using Cook et al., (2004) scale that includes 21 items with
anchors ranging from (1- very low; 5 – very high). The scale is divided into six sections representing the two
main dimensions of EI including both intrapersonal and interpersonal dimensions - and their six sub
dimensions, which are self-awareness, self-confidence, self-discipline, empathy, optimism, and social
responsibility as indicated in tables: I, II.
Technology learning levels were measured using Dabnoon's scale (2008). This scale encompasses 46 items
with anchors ranging from (1- almost never; 5 - almost always) distributed into four areas representing the
four levels of technology learning which are the basic, average, advanced, and world-class level as tables III,
IV indicate.
As indicated in tables I-IV, reliability scores for all the study's constructs have values greater than 70.
Thus, they provide adequate levels of reliability [51]. In addition, factor analyses were also conducted with
SPSS 17.0 using the principal components extraction method and Varimax rotation declared that items'
loadings within each construct display desirable convergent validity (loading high on that construct) and
discriminant validity (low cross-loadings) as tables I-IV demonstrate. The means and standard deviations for
each construct are also indicated in these tables.
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IV. DATA ANALYSIS All statistical analyses were conducted using SPSS 17. Initial tests began by performing bivariate
correlations in order to explore the initial relationships among variables measured in the study. This was then
followed by conducting a series of regressions analyses where each of the four technology learning level was
regressed in turn against each of the main emotional intelligence dimensions measures.
V. RESULTS Correlation analysis was used as an initial examination of the relationships among the variables studied.
Table V. summarizes the intercorrelation among all the variables used in the study.
Though several variables are related, table V. indicates no severe problems of multicolinearity as total
intrapersonal EI and its sub dimensions showed minor correlation with Interpersonal EI and its sub
dimensions offer further support for the predominantly independent nature of these two dimensions of EI. So,
none of the related variables exceeded the value of 0.60. Total EI was significantly correlated with its two
main dimensions: intrapersonal EI (r _ 0.889, p _ 0.01), and interpersonal EI (r _ 0.914, p _ 0.01). Total
intrapersonal EI was significantly correlated with its three sub dimensions: self- awareness (r _ 0.625, p _
0.01), self-confidence (r _ 0.671, p _ 0.01), and self-discipline (r _ 0.735, p _ 0.01). Similarly, interpersonal
EI was also significantly correlated with its three sub dimensions: empathy (r _ 0.781, p _ 0.01), optimism (r _
0.809, p _ 0.01), and social responsibility (r _ 0.822, p _ 0.01).
The dependent variable technology learning also correlated with its sub dimensions: basic level (r _ 0.767,
p _ 0.01), average level (r _ 0.757, p _ 0.01), advanced level (r _0.888, p _ 0.01), and world-class level (r _
0.827, p _ 0.01). Both of the total intrapersonal EI and the total interpersonal EI also significantly correlated
with TLP (r _ 0.573, p _ 0.01), (r _ 0.358, p _ 0.01) respectively. The sub dimensions of each EI also
significantly correlated with the total TLP.
The results in table VI. reveal that there is a joint influence of intrapersonal EI dimensions: self-awareness,
self-confidence, and self-discipline on the basic level of TLP F (3, 120) = 17,09; p<0.05 with R =0.55 and
R2= 0.30. This implies that the three variables accounted for 30% variations in the basic level of TLP. Thus,
the H1a hypothesis was confirmed.
The results also show the contribution of each of the variables and reveal that each of intrapersonal EI
dimensions contributed significantly as can be seen in figures (2,3,4).
On the other hand, the results of the multiple regressions in Table VI. partially supported H1b, H1c, and
H1d hypotheses.
Although the results indicate that there are joint influences of intrapersonal EI dimensions which are selfawareness, self-confidence, and self-discipline on average, advanced, and world-class TLP levels; only selfdiscipline variable was found to contribute significantly as can be seen in figures (5,6,7).
Similarly, reviewing regression analyses results presented in table VII. Indicate that despite the joint
influences of interpersonal EI dimensions including empathy, optimism, and social responsibility of each TLP
levels including basic, average, advanced, and the world-class level, the results showed that neither empathy
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nor social responsibility predict basic, advanced, and world-class TLP levels. Optimism is the only
interpersonal EI dimension which significantly predicts basic, advanced, and world-class TLP levels as
figures (8,9,10) show.
Social responsibility contributed significantly to the average level of TLP (see Fig. 11). Thus, the second
main hypothesis and its four sub hypotheses –H2a, H2b, H2c, and H2d – were partially supported.
VI. DISCUSSION The main purpose of this study was to examine the influence of EI dimensions on TLP levels. The study
showed that intrapersonal EI dimensions including self-awareness, self-confidence, and self-discipline
account for 30% in variation on the basic level of TLP. This indicates that employees with a good ability to
understand and trust their own feelings and preferences, to have belief in themselves, and to be self-motivated
seem to have higher basic TLP abilities such as dealing effectively with stressful situations, cooperating with
suppliers, customers/users, stockbrokers, and participating in activities of professional associations than
employees with low abilities on these areas. Results from this sample were consistent with those obtained by
Boyatzis (1982), Goleman (1998), Lusch & Serpkenci (1990), and others [3], [48]. Findings also indicated
that despite the joint influences EI dimensions have on TLP levels, only self-discipline variable can predict
average, advanced, and the world-class TLP levels. The latter result lends its support from previous studies
such as Serpkenci & Lusch's (1990) who showed that the most successful store managers were those beset
able to handle stress. The finding is also consistent with other studies, which argued that emotional regulation
could be linked to specific organizational learning disciplines [33], [3], [17], [47]. Thus, we may assume that
flexible and adaptable employees with an ability to manage their anger and impulse are suited to average,
advanced, and the world-class TLP activities such as participating in the company's strategy making,
attending innovation workshops, and acquiring up-to-date research and development tools.
In addition, optimism was the only interpersonal EI dimension, which significantly predicts TLP levels
except the average level, which has been found to be predicted by the social responsibility variable. The latter
findings are also consistent with Robbins’ (2007) who assured the importance of optimism, and with others
who assumed that social responsibility and focusing on others lead to gaining new perspectives on problems
at both intraorganizational [1], [43] and interorganizational levels [43]. Consequently, the results totally
supported H1a, and partially supported the other hypothesized relationships.
The major contribution of the study stems from being the first study to investigate the relationship between
emotional intelligence dimensions and technology learning levels. Therefore, the current results add to a
growing body of research that presents some empirical support and evidence of an interesting parallel
between TLP Levels and EI dimensions.
Some limitations are associated with this study. The first limitation concerns self-report ratings. Although
the researcher does not suspect that method bias significantly affected the pattern of results in this study, the
use of additional data collection strategies or outcome measures would have strengthened the validity of the
study findings. The relatively small sample size of 124 should be also noted. The population upon which this
study is based was drawn from ten IT organizations in Jordan. Therefore, the extent to which the results found
here can be generalized beyond this particular sample to other organizations is unknown. In addition, the
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failure to find any significant relationships between some emotional intelligence dimensions and technology
learning levels might be due to the probability that they may be mediated by other factors such as emotional
climate within the organization. This factor deserves to be investigated in a future study utilizing other
analytic techniques such as structural equation modeling.
VII. CONCLUSION AND IMPLICATIONS In conclusion, the research evidence to date has proved that emotional intelligence has the potential to
predict a range of technology learning levels. By linking emotional intelligence to the organizational and
technology learning principles, we can get a deeper insight into how to make technology change management
programs more effective. Another implication relates to considering emotional intelligence competences
when selecting, promoting IT managers and employees besides the cases of designing and implementing
specialized EI and TLP workshops and training programs.
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Intrapersonal EI H1a Self- Awareness,
Basic Level H1b Self- Confidence
H1c Self- Discipline Average Level H1d Interpersonal EI Empathy
H2a Advanced Level H2b World‐Class Level Optimism
H2c Social Responsibility H2d Fig. (1): Suggested Research Model
Fig. (2): The Impact of Self-Discipline on TLP Basic Level
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Fig. (3): The Impact of Self-Awareness on TLP Basic Level
Fig. (4): The Impact of Self-Confidence on TLP Basic Level
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Fig. (5): The Impact of Self-Discipline on TLP Average Level
Fig. (6): The Impact of Self-Discipline on TLP Advanced Level
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Fig. (7): The Impact of Self-Discipline on TLP World-Class Level
Fig. (8): The Impact of Optimism on TLP Basic Level
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Fig. (9): The Impact of Optimism on TLP Advanced Level
Fig. (10): The Impact of Optimism on TLP World-Class Level
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Fig. (11): The Impact of Social Responsibility on TLP Average Level
Table II.
Independent Factors: Intrapersonal EI sub-dimensions and items with loadings
Factor/ Construct
Item
Self-Awareness
KMO: 0. 655
Bartlett's Test of Sphericity :
Approx. Chi-Square: 50.780
df 3
Sig 0.000
Eigenvalues (Variance Explained): 59. 419
Mean: 4. 401 Standard Deviation: 0. 512
Alpha Cronpach: 0.701
Self- Confidence
KMO: 0. 546
Bartlett's Test of Sphericity :
Approx. Chi-Square: 25. 897
df 6
Sig. 0. 000
Eigenvalues (Variance Explained): 38. 332
Mean: 4. 466 Standard Deviation: 0. 411
Alpha Cronpach: 0.721
Self-Discipline
KMO: 0 . 611
Bartlett's Test of Sphericity :
Approx. Chi-Square 64. 872
Df 6
Sig. 0. 000
Eigenvalues (Variance Explained): 46. 164
Mean: 4. 420 Standard Deviation: 0. 544
Alpha Cronpach: 0.754
Understanding and trusting your own feelings and
preferences.
Factor
Loading
0.785
Recognizing why you feel that way.
0.783
Recognizing how your feelings impact on yourself and
others.
0.743
Having belief in yourself
0.634
Being self motivated.
0.636
Having a style that is assertive and ‘win–win’.
.638
Being happy to make decisions alone and not being
dependent on others.
Dealing effectively with stressful situations.
0.727
0. 814
Managing your anger and impulse.
0. 687
Being flexible and adaptable.
0. 771
Creating a balance between rational and emotional
considerations.
0. 924
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Factor/ Construct
Table III.
Independent Factors: Interpersonal EI sub-dimensions and items with loadings
Item
Empathy
KMO: 0. 567
Bartlett's Test of Sphericity :
Approx. Chi-Square 25. 337
df 3
Sig. 0.000
Eigenvalues (Variance Explained): 50. 591
Mean: 4. 393 Standard Deviation: 0. 522
Alpha Cronpach: 0.768
Optimism
KMO: 0 .624
Bartlett's Test of Sphericity :
Approx. Chi-Square 42. 554
df 3
Sig. 0.000
Eigenvalues (Variance Explained): 56. 665
Mean: 4.333 Standard Deviation: 0. 544
Alpha Cronpach: 0.801
Social Responsibility
KMO: 0.667
Bartlett's Test of Sphericity :
Approx. Chi-Square 57. 982
df 6
Sig. 0.000
Eigenvalues (Variance Explained): 46. 992
Mean: 4. 300 Standard Deviation: 0. 511
Alpha Cronpach: 0.702
Understanding the feelings of others.
Factor
Loading
0.797
Putting yourself in the shoes of others.
0.724
Picking up what is being said, how it is being said and the
body language that goes with it.
0.624
Taking the initiative, having a ‘can do’ approach.
0.780
Having a happy disposition, seeing a glass that is ‘half full
not half empty’.
0.678
Inspiring others by sharing what you are passionate about and
encouraging others to do the same.
0.795
Putting others’ needs first.
0.637
Finding common ground with others.
0.800
Minimizing conflict.
0.744
Influencing others for the sake of the relationship or group.
0.641
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Factor/ Construct
Table IV.
Dependent Factors: Basic and Average TLP Levels and items with loadings
Item
Basic Level
KMO: 0. 876
Bartlett's Test of Sphericity :
Approx. Chi-Square 741. 248
df 66
Sig. 0.000
Eigenvalues (Variance Explained):
68. 312
Mean: 4. 383
Standard Deviation: 0.640
Alpha Cronpach: 0.893
Average Level
KMO: 0. 896
Bartlett's Test of Sphericity :
Approx. Chi-Square 831. 887
df 78
Sig. 0.000
Eigenvalues (Variance Explained):
58. 176
Mean: 4.338
Standard Deviation: 0. 648
Alpha Cronpach: 0. 904
Factor/ Construct
Cooperate with suppliers.
Cooperate with customers/users.
Check government sources.
Participate in activities of professional associations.
Participate in activities of trade associations.
Scrutinize business literature and those periodicals.
Join local chambers of commerce.
Subscribe to the local press.
Subscribe and review trade press.
Collaborate with stockbrokers.
Keep track of the prospectus.
Contact and visit the investment banks.
Participation of employees in the company's strategy.
Use IT such as Bulletin Board System and E-mails.
Access to the Internet.
Create informal discussion networks.
Rotate jobs among employees.
Establish communication routines.
Provide members with extra travel budget.
Use Technology Roadmaps.
Use a Balanced Scorecard.
Use Listening Posts.
Use a Watch List.
Benchmark key competitors.
Conduct a sensitivity analysis.
Table V.
Dependent Factor: Advanced and World-class TLP levels and items with loadings
Item
Advanced Level
KMO
0.869
Bartlett's Test of Sphericity :
Approx. Chi-Square 834. 406
df 45
Sig. 0.000
Eigenvalues (Variance
Explained):
77. 444
Mean: 4. 247
Standard Deviation: 0.714
Alpha Cronpach: 0.888
World- Class Level
KMO: 0. 948
Bartlett's Test of Sphericity :
Approx. Chi-Square 1337. 003
df 55
Sig. 0.000
Eigenvalues (Variance
Explained): 72. 869
Mean: 4. 163
Standard Deviation: 0. 801
Alpha Cronpach: 0. 963
Establish a suitable pyramidal structure of R&D personnel.
Maintain a reliable and accessible database.
Use R&D documents in comparison to other documents.
Acquire up-to-date R&D tools.
Share knowledge within the R&D departments.
Share information among departments.
Gain support and commitment of top management.
Keep a constant balance between human resource planning and learning
strategy.
Recruit high levels of education, skills, and experience.
Provide training programmes for employees.
Launch projects of limited duration.
Appoint a gatekeeper.
Use venture capital funds.
Send technology envoys throughout the world.
Organize technology colloquia.
Arrange innovation workshops.
Proactively collaborate with universities and research institutes.
Collaborate with start-ups and leading companies.
Establish centralized and/or decentralized units dedicated to learn trends of
new technologies.
Provide incentive systems suitable for technological learning.
Provide researchers with financial resources.
Factor
Loading
0.720
0.603
0.719
0.692
0.747
0.830
0.640
0.611
0.727
0.830
0.661
0.756
0.693
0.610
0.787
0.615
0.816
0.688
0.822
0.796
0.890
0.725
0.777
0.673
0.614
Factor
Loading
0.823
0.797
0.834
0.898
0.795
0815
0.826
0.857
0.907
0.848
0.878
0.882
0.828
0.857
0.864
0.895
0.851
0.794
0.800
0.867
0.870
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Variable
1
2
Total EI
1
0.889*
Total
0.889* 1
Intrapersonal
EI
self
0.625* 0.738*
awareness
self
0.671* 0.701*
confidence
self0.735
0.835
discipline
Total
0.914* 0.426*
Interpersonal
EI
empathy
0.697* 0.456*
optimism
0.766* 0.557*
social
0.741* 0.495*
responsibility
Total TLP
0508*
0.573*
TLP Basic
0. 520
0.543
Level
TLP Average 0.460* 0.488*
Level
TLP
0.376* 0.448*
Advanced
Level
TLP World0.338* 0.413*
class Level
* Significant at p-value < 0.01
3
0.625*
0.738*
4
0.671*
0.701*
Table VII.
Intercorrelation between variables 5
6
7
8
9
0.735* 0.914* 0.697* 0.766* 0.741*
0.835* 0.426* 0.456* 0.557* 0.495*
1
0.243*
0.397*
0.410*
0.309*
0.438*
0.236*
0.625*
0.369*
0.325*
0.306*
0.217*
0.243*
1
0.460*
0.520*
0.353*
0.436*
0.465*
0.362*
0.373*
0.294*
0.208
0.306*
0.397
0.460
1
0.511
0.381
0.407*
0.446*
0.566*
0.490*
0.477*
0.477*
0.416*
0.410*
0.520*
0.511*
1
0.781*
0.809*
0.822*
0.358*
0.405*
0.351*
0.244*
0.210*
0.309*
0.438*
0.236*
0.353*
0.436*
0.465*
0.381*
0.407*
0.446*
0.781*
0.809*
0.822*
1
0.413
0.476*
0.413*
1
0.421*
0.476*
0.421*
1
0.190*
0.378*
0.292*
0.230
0.417*
0.325*
0.188
0.298*
0.362*
0.140
0.279*
0.166
0.091*
0.262*
0.148
0.363*
0.369*
0.362*
0.373*
0.566*
0.490
0.358*
0.405
0.190
0.230*
0.378*
0.417*
0.292*
0.325*
1
0.767
0.767*
1
0.757*
0.423*
0.888*
0.484*
0.827*
0.342*
0.325*
0.294*
0.477*
0.351*
0.188
0.298*
0.362*
0.757*
0.423*
1
0.471*
0.324*
0.306*
0.208
0.477*
0.244*
0.140
0.279*
0.166
0.888*
0.484*
0.471*
1
0.445*
0.217*
0.306*
0.416*
0.210
0.091
0.262*
0.148
0.827*
0.342*
0.324*
0.445*
1
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0.508*
0.573*
11
0.520*
0.543*
12
0.460*
0.488*
13
0.376*
0.448*
14
0.338*
0.413*
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Table VIII.
Results of multiple regression analyses related to intrapersonal EI dimensions and TLP levels
Hypothesis
H1a
Dependent
Variable:
Technology
Learning Level
Basic
Independent Variables
B
t-value
R
R2
Total Intrapersonal EI
0. 547
0. 299
(Constant)
0. 381
0. 618
Self Awareness**
0. 244
2..333
Self Confidence**
0. 268
1. 993
Self Discipline**
0..3 92
3. 658
H1b
Average
Total Intrapersonal EI
0. 505
0. 255
(Constant)
0. 902
1.401
Self Awareness
0.197
1.807
Self Confidence
0.131
0. 937
Self Discipline**
0.448
4.007
H1c
Advanced
Total Intrapersonal EI
0.494
0. 244
(Constant)
1.074
1,503
Self Awareness
0.195
1.615
Self Confidence
0.044
0. 285
Self Discipline**
0.568
4.579
H1d
World Class
Total Intrapersonal EI
0.438
0.192
(Constant)
0. 300
0. 302
Self Awareness
0.096
0. 329
Self Confidence
0.582
0.573
Self Discipline**
0. 567
1.523
* S=supported,
P.S= partially supported, N.S= not supported
** Significant at p-value < 0.05.
Result
*
Fvalue
Sig
17.087
0.000
0.538
0. 021
0.048
0.000
0.00
0.164
0.073
0.351
0.000
0.000
0.135
0.109
0.776
0.000
0.000
0.763
0.567
0.130
0.001
13.679
12.942
9.496
S
P.S
P.S
P.S
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Table IX.
Results of multiple regression analysis related to interpersonal EI dimensions and TLP levels
Hypothesis
H2a
Dependent
Variable:
Technology
Learning Level
Basic
Independent Variables
Total Interpersonal EI
(Constant)
Empathy
Optimism**
Social Responsibility
H2b
Average
Total Interpersonal EI
(Constant)
Empathy
Optimism
Social Responsibility**
H2c
Advanced
Total Interpersonal EI
(Constant)
Empathy
Optimism**
Social Responsibility
H2d
World Class
Total Interpersonal EI
(Constant)
Empathy
Optimism**
Social Responsibility
* S=supported,
P.S= partially supported, N.S= not supported
B
t-value
1. 794
0. 032
0. 392
0. 174
3. 299
0. 276
3. 379
1. 358
2.047
0. 016
0.182
0..365
3.625
0.132
1.512
2.750
2.517
0. 033
0. 339
0. 028
3.893
.235
2.454
0. 181
R
R2
Fvalue
Sig
0.436
0.190
9.392
0.000
0.001
0.783
0.001
0.177
0.000
0000
0.895
0.133
0.007
0. 020
0.000
0. 815
0. 016
0. 857
0. 034
0. 013
0.782
0. 015
0. 811
0..384
0. 280
2.199
0. 052
0. 457
0. 049
0. 148
0. 079
6.924
3.411
0. 263
0. 069
2.979
2.522
0. 277
2.457
0. 240
** Significant at p-value < 0.05.
Result*
P.S
P.S
P.S
P.S
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