Communication competence of Indian engineers in IT & ITeS sector.
Raina, Reeta ; Pande, Neerja
Communication Skills for Business Professionals
According to Peter Drucker, the ability to communicate well is
essential for success and is perhaps the most important of all the
skills an individual should possess. As business professionals move up
the ranks of management they spend fifty percent more time speaking than
in any other management activity (Rader & Wunsch 1980). Not only do
they spend more time speaking, but their oral communication is seen as
more vital to their success than other skills such as writing. Tom
Peters (2010) says "Communication is everyone's panacea for
everything". There is no denying the fact that effective
communication is at the root of virtually all success which mandates
that even engineers, scientists and technocrats need to translate their
work into understandable communications so that it can be applied
outside their own level of expertise.
An unprecedented rush of information and communication technologies
and expansion of international relations have resulted in the
globalization of engineering education. The actual potential of an
engineer implies not only his professional knowledge, but also a number
of social-humanities skills. These traditionally fall into the category
of soft skills while forming the social-humanities competence of an
expert. These abilities include self-education, critical and lateral
thinking, self-discipline and professional communication (Fofanov et al.
2010).
Corporate demand for employees skilled in interpersonal
communication is on the rise as organizational structures have become
flatter and transformational leadership styles are fostered more and
more. Organizations are working to recruit, promote, develop, and train
transformational leaders who connect with employees emotionally and have
verbal and coaching skills (Bass 1999, 1990). Numerous studies querying
graduates, employers, and faculty members show communication skill as
one of the top areas needing improvement among employees and new
graduates (Maes, Weldy & Icenogle 1997, Morreale, Osborn &
Pearson 2000). Reinsch and Shelby (1996) interviewed students with an
average of 3.3 years work experience who were entering the Georgetown
University Masters in Business Administration programme and found that
their most challenging "workplace episodes were oral events, most
of which required the creation or transmission of information". The
students wanted to improve their abilities in a wide range of oral
communication areas such as self-confidence, poise, explanatory skills,
situational analysis and persuasion. They suggest that students want to
develop these skills because it is a real need in the business world.
Recently, Human Resource managers from Fortune 500 corporations included
listening, speaking, team participation, and communication of
information as most important for business school graduates in the 21st
century (Porterfield & Forde 2001). Empirical research links social
skills and other communication constructs with various organizational
outcomes including job mobility (Kilduff & Day 1994), upward
mobility, job level, and pay (Haas & Sypher 1991, Sypher & Zorn
1986), leadership ability (Flauto 1999) and general mental ability and
job performance (Ferris, Witt & Hochwarter 2001).
Sometimes communication skills are ignored or relegated to the back
seat in favour of more mechanical emphasis on certification in the
technical mechanisms of project management via the Project Management
Programme and other certifications (Heisler and et.al 2000). He further
emphasizes that the incorrect interpretation of communications is
"the root cause of many project failures." In a report
presented by FICCI (and prepared by ICRA) "The Skill Development
Landscape in India and Implementing Quality Skills Training " at
3rd Global Skill Summit in 2010 it was found that a major skill gap
existed among Indian engineering graduates, thus making a strong case
for the engineering colleges and institutions to focus more on
employability and quality. The report indicates that 64 percent of
surveyed employers are "somewhat", "not very", or
"not at all" satisfied with the quality of engineering
graduates' skills. The top three most important general skills
identified were integrity, reliability and teamwork, while the top three
most important specific skills are entrepreneurship, communication in
English and use of modern tools and technologies (Retrieved on 17th
Sept.2010 (http://news.in.msn.com/national/ article.aspx?cp-documentid =
3373712)As). According to Ellet (2007) in the "knowledge
economy" employees are expected to think and act on their own and
with employees distributed all over the world a well written document
can be a hidden source of competitive advantage.
Communication Competence
Many scholars have attempted to define interpersonal communication
competence: however, the process is likened to "climbing a greased
pole" (Phillips 1984: 25) and competence is still considered a
"fuzzy" concept (Jablin & Sias 2001: 819). The lack of a
widely-accepted definition is due to the complexity of the communication
process and the problems with its measurement (Rubin & Martin 1994,
Wiemann et al. 1997). Earlier Communication Competence was defined as
the ability to communicate with others with accuracy, clarity,
comprehensibility, coherence, expertise, effectiveness and
appropriateness (Spitzberg 1998). Trenholm and Jenson (1988) define
Communication Competence as the ability to communicate in a personally
effective and socially appropriate manner. The operational definition of
Communication Competence by Friedrich (1994) suggests that it is a
situational ability to set realistic and appropriate goals and to
maximize their achievement by using knowledge of self to generate
adaptive communication performances. Jablin and Sias (2001:125) define
competence as "the set of abilities, henceforth, termed resources,
which a communicator has for use in the communication process".
This definition is a strategic, goal-oriented approach to competence
stressing knowledge and ability. Obviously these definitions go beyond
communication that simply emphasizes the two main components: knowledge
of communication and context and ability to obtain goals (skill).
According to Friestad and Wright (1994), the diversity of definitions
and treatments of competence exists because of the diversity of what
scholars considered the most salient issues to the construct: knowledge
(McCroskey 1982), behaviours (Wiemann 1977), or goal attainment
(Spitzberg 1983).
Definitions of Communication Competence are becoming more specific
as the issue of context is given more consideration. A more contextually
sensitive definition of Communication Competence within organizations is
the judgment of successful communication where
"interactant's" goals are met using messages that are
perceived as appropriate and effective within the organizational
context. Communication Competence in organizations involves knowledge of
the organization and of communication, ability to carry out skilled
behaviours, and one's motivation to perform competently (Payne
2005).
Few researchers have attempted to systematically study competence
within the organizational context. Monge et al. (1982) tested a model
representing a performance-based (behavioural) approach. The
Communication Competence Questionnaire (CCQ) focused primarily on skills
necessary to accomplish work tasks, and did not include relational forms
of communication as essential to workplace communication. Their research
does not incorporate motivation or knowledge, the affective and
cognitive elements of competence. Few studies in management use the
Communication Competence Construct; however, Penley et al.(1991) tested
the impact of communication skills (clarity, articulation, and
accuracy), motivation (oral, non-verbal, and written communication
apprehension), and cognitive skills (cognitive complexity, perspective
taking, and self-monitoring) on managerial performance. Results showed
higher performing managers had higher verbal communication skills and
lower communication apprehension; however, they did not have greater
social cognitive ability.
More recently, Jablin et al (1994) and Jablin & Sias (2001)
investigated threshold Communication Competencies in organizations. They
define threshold Communication Competencies as, "... generic
capabilities which are essential to performing jobs, but which are not
sufficient to cause superior levels of effectiveness in
communication". Jablin et al. (1994) provide a continuum of
employee communication progressing from pre-competent to over-competent
level. The research highlights that knowing the communication rules of
an organization, which are learned primarily through the socialization process, is essential to competent communication.
In another study Payne (2005), applied a three component model of
Communication Competence (motivation, knowledge, and skill) within an
organizational context and analyzed the relationship between job
performance, position level, and Communication Competence. The results
revealed that high job performers had significantly higher levels of
motivation to adapt communication and higher levels of communication
skills. Also, supervisors were more motivated to communicate and
empathize than subordinates; level of job performance and job position
did not influence level of communication competence.
During the past two decades, most theories of Communication
Competence have been developed on the basis of Western conceptualization (Bostrom 1984, Harris 1979, Spitzburg & Cupach 1984, Wiemann 1977)
of white, middle class Americans. Communication behaviour that reflects
the competence of an individual is culture specific, thus behaviours
that are understood as a reflection of competence in one culture may not
necessarily be understood as competent in another (Cooley & Roach
1984). Echoing their thought, Miyahara (2010) also, advocates that the
notion of Communication Competence as is currently conceptualized by
Western researchers may not necessarily be relevant for non-Western
cultures. He implies that the overall social, political, and economic
surrounds of the Japanese society that influence people's
perceptions of norms, rules and competence must be taken into account
for a more meaningful and useful approach to theorizing interpersonal
Communication Competence for Japanese.
Charoenngam and Jablin (1999), following the above line of thought,
conducted an exploratory study to build upon their knowledge of the
culture of the Thai people and their organizations to conceptualize and
explore the nature of communication competence in Thai organizations.
Lee and Chen (2000) in their study examine the relationship between
psychological adjustment and cultural Communication Competence among
members of immigrant families. Adolescents' host Communication
Competence was correlated negatively with psychological problems,
whereas their native Communication Competence was non-significantly
associated with psychological problems. In addition, interaction between
adolescents' host and native Communication Competence and
parents' host and native Communication Competence were found to
predict adolescent's psychological adjustment.
Collier (2002) selected four approaches to the study of cultural
and intercultural competence: ethnography of speaking approaches,
behavioural skills approaches, cross cultural attitude approaches, and,
finally, an approach thematizing cultural identity and competence.
Communication Competence in the Indian Context
Making the case for the transformational influence that Information
Technology Enabled Services (ITES) industry has had on the economic and
social fabric of the country, Lesikar et al (2009) elaborate that a
glance at the fast changing skyline and lifestyle of the inhabitants of
Indian metropolitan cities like Bengaluru, Gurgaon, Hyderabad, Mumbai
and Chennai is evidence enough of the impact. Though the Information
Technology entrepreneurs like Azim Premji of Wipro, N R Narayana Murthy
of Infosys and thousands of engineers from the various premier colleges
and Indian Institutes of Technology had already established India's
mettle during the 1980's but the country as a whole was still not
involved in this process of globalization. According to a National
Association for Software and Services Companies (NASSCOM) IT-BPO Status
Report 2009, "the industry gainfully provides direct employment to
2.23 million people and is creating indirect jobs for about 8 million
people....." Indian BPO industry is on a fast track growth
providing services to nearly all the Fortune 500 companies and many
others, covering every conceivable sector that can be outsourced. The
major players being Genpact, WNS Global Services, Wipro BPO, HCL BPO,
ICICI OneSource, IBM Daksh, Infosys BPO to name a few (Lesikar, Flately,
Rentz & Pande 2009).
These software firms are seen as exemplars of organizational forms
and practices that are relatively new to India. They are relatively flat
organizations, with young management teams, informal but professional
management styles, and with an emphasis on efficiency, punctuality and
other virtues that an export orientation brings ((http://www.bpo
india.org/research/attrition-rate-bigchallenge.shtml). Research
indicates that there is a strong link between Communication Competency
and success in the workplace. The present study aims to quantify if the
Communication Competence of the Indian IT engineers matches with their
professional skills. It explores and assesses if the Indian
professionals/ technocrats have the adequate Communication Competence to
communicate best in a cross-cultural environment, reduce barriers to
communication and manage communication demands that one faces on the
job. The study attempts, using the Wiemann and Backlund model (1980)
that defines Communication Competence as:"the ability of an
interactant to choose among available communicative behaviours in order
that he may successfully accomplish his own interpersonal goals during
an encounter while maintain the face and line of his fellow interactant
within the constraints of the situation."
Hypotheses
1) Communication Competence varies across age groups
2) Communication Competence varies across education groups
3) Communication Competence varies across gender
4) Communication Competence varies across experience
Survey Instruments
The study was based on the design and administration of a survey.
For this purpose the Communication Competence scale by Wiemann and
Backlud (1980) was used.
Sample &Data Collection
The list of National Capital Region based I-T organizations was
obtained from the NASSCOM database. We contacted over 70 IT companies
operating from NCR out of which only 14 organizations agreed to respond
to the survey. Data was personally collected from IT firms (mostly from
NCR region) for the study. Scales on Communication Competence were
administered to managers at the middle and lower management levels.
Before administration of the scales the purpose and importance of the
study was explained to them and they were requested to respond by
providing their free and frank opinions through the given scales. A
total of 700 scales were given to 14 firms and a total of 146 filled in
scales were received back.
The mean age of the sample was 25.72 years as they were distributed
in two age groups: one, with less than 25 years (75 respondents) and the
other with 25 years and more (71 respondents). The sample represented an
age group with a minimum 28 and a maximum 38 years. The sample was
skewed towards the male gender as there were 111 male respondents and 35
female respondents. The respondents were divided into three groups in
terms of their education: one, with Bachelors in Engineering /
Technology degree (89 respondents), second, with any other Bachelors
degree (19 respondents), and third, with Masters degree (38
respondents).With regard to work experience, the sample was divided into
two groups: one, with work experience of 30 months and less (74
respondents), second, with the work experience of more than 30 months
(72 respondents).
Factor Analysis
Factor analysis was conducted using SPSS 18 package. As a part of
preliminary analysis bi-variate correlation was conducted between the 36
variables to test for multi-collinearity. The bi-variate correlation
coefficients were well below the critical mark of 0.9 and hence, there
did not exist any multi-collinearity issues with the data collected.
Also, the coefficients were found to be statistically significant at 95%
confidence interval.
Iteration 1
In the 1st iteration, the KMO statistic was found to be 0.594 at
significance level of 99%, which was sufficiently higher than the
critical mark of 0.5 and hence the sample size was adequate enough to
attain distinct and reliable factors. This iteration yielded 14 factors
which in total explained 72% of variance. There were 6 factors which had
only one variable loaded on them. These variables which loaded
individually on 6 separate factors were q4, q35, q18, q20, q1, q2. There
were eight other variables (q3, q5, q8, q9, q10, q16, q22, q34) that had
very low factor scores (less than 0.4) and hence were not considered to
be loaded on any factors.
Iteration 2
As there were 6 factors that had just one variable loaded on them,
we ignored these variables, and continued the second iteration with the
8 variables that didn't load on any factors. In the 2nd iteration
the KMO statistic was found to be 0.615 at a significance level of 99%,
which was sufficiently higher than the critical mark of 0.5 and hence,
the sample size was adequate enough to attain distinct and reliable
factors. This iteration yielded 10 factors which in total explained 64%
of variance. There were 2 factors which had only one variable loaded on
them (q16 & q9). There were seven other variables (q8, q11, q12,
q14, q22, q28, q31) that had very low factor scores (less than 0.4) and
hence weren't considered to be loaded on any factors.
Iteration 3
In the third and final iteration, we ignored the variables that
loaded individually on 6 separate factors during iteration 1 and also 8
others that had low factor scores. We took this decision because these
variables were either loading individually to factors or had less factor
scores in either of the two earlier iterations. The behaviour of these
variables indicated that they were unsuitable for Indian context and
probably were not required. In the 3rd iteration the KMO statistic was
found to be 0.669 (Table 1) at significance level of 99%, which was
sufficiently higher than the critical mark of 0/5. It could be concluded
that the sample size was adequate enough to attain distinct and reliable
factors. The third iteration yielded 7 factors which in total explained
62% of variance (Table 2), which is reasonable. We yet had four
variables q11, q12, q14 & q28 (Table 3) that had very low factor
scores and hence could not be considered to loading on any factor. Based
on a qualitative assessment we could identify seven distinct factors:
listening (q7, q17, q25, q27), extrovert (q23, q26, q29, q32), openness
(q33, q36), understanding (q15, q19), effectiveness (q6, q21), flexible
(q30, q31), empathy (q13, q24).
ANOVA
Age: The mean age was 25.72 years with standard deviation of 3.79
years and variance of 14.35. We hypothesized that as respondents grew
older, their Communication Competence would mature with time and with
increased experience it would be better for older age group than younger
age group.
H1: Communication Competence is dissimilar across age groups
The above table results indicate that H1 was not supported. The low
F-values indicate that between two age groups the variance was very low
and hence they overlapped each other to a great extent indicating fewer
differences between them.
Education: We hypothesized that respondents with professional and
higher degrees would be comparatively more matured than respondents with
Bachelors degree and hence would have developed better Communication
Competencies.
H2: Communication Competence is dissimilar across education groups.
The above table results indicate that H2 was not supported. The low
F-values indicate that between the three education groups the variance
was very low and hence they overlapped each other to a great extent
indicating fewer differences between them.
Work Experience: We hypothesized that respondents with higher work
experience during their professional career would be comparatively more
matured and would have developed better Communication Competencies than
the respondents in their early career stage.
H3: Communication Competence is dissimilar across work experience
groups
The above table results indicate that H3 was not supported. The low
F-values indicate that between the three education groups the variance
was very low and hence they overlapped each other to a great extent
indicating fewer differences between them.
Gender: There have been studies in the past which have indicated
that women tend to have better communication skills due to higher
patience, listening capability etc. compared to that of males.
H4: Communication Competence is dissimilar across gender
The above results indicate that H4 was not supported. The low
F-values indicate that between the three education groups the variance
was very low and hence they overlapped each other to a great extent
indicating fewer differences between them.
Discussion & Conclusion
Most studies in the communication area have only addressed
competence from a skills perspective (Monge et al. 1982). This research
expands traditional approaches to the study of communication in
organizations beyond a social skills approach using Wiemann's
(1977) scale of Communication Competence, which incorporates listening,
extrovert, openness, understanding, effectiveness, flexibility and
empathy. The primary findings of this research did not show support for
any of the hypothesis and has resulted in startling inferences. Hence,
it could be inferred that demographic variables have not been strong
enough to differentiate the Communication Competencies between groups.
There could be three possible explanations for the same:
i) The nature of the industry (i.e. IT services) by default needs
every employee to be high on Communication Competence and hence due care
would have been taken at the recruitment stage itself.
ii) Alternatively, they would have been imparted regular
communication skills development training programs because of which no
major difference was found between the groups.
iii) Also, their frequent travelling to different geographic
locations and exposure to wider diaspora could have helped them in
honing their communication competency
The results of the data analysis indicate that managers in IT
sector in India are skilled at interaction management which includes
fluency, verbal ability, and social adaptability(these were some of the
parameters the managers were tested on). They manage interactions
because they have the ability to speak fluently, use their voice and
body expressively to communicate, generally say the right thing at the
right time, and more importantly, do not impose their views on others.
They were found to be effective conversationalists, adapting their
communication, and managing interactions with people including strangers
with comfort irrespective of their age, education, gender or work
experience. They find it easy to get along with others since they treat
people as individuals, understand them by placing themselves in their
shoe and let them know that they understand what they mean. They do not
make unusual demands on them, are flexible and adapt to changing
situations by not arguing with someone just to prove that they are
right.
It seems clear that managing interactions is inseparable from
adaptability. Adaptability is the ability to perceive relationships and
adapt messages accordingly (Duran 1992) and the results indicate that
managers in IT sector in India are flexible enough to adapt to
conversational partners and contexts. They generally know what type of
behaviour is appropriate in any given situation. They are aware what
others feel and display sensitivity to others' needs of the moment.
They make the other person know that they understand what he \she means
and are supportive of the same. These specific skills assist managers in
getting along with others who in turn find it rewarding to talk to them
and share their problems with them respectively. They are good
listeners, pay attention to the conversations and are genuinely
interested in what others have to say. They have the ability to
reciprocate affect displays, send verbal responses showing understanding
and feelings for others, and listen actively. The results further show
that the Communication Competency of the IT managers helps them build
warm relationships with people. They are close and personal with people.
These superior levels of effectiveness in communication found in
managers in the IT and ITes sector that go beyond the threshold
Communication Competency could be attributed to the fact that the
manager in the IT sector have to travel a lot within and outside India.
They work closely with people who come from different parts of the
world, leading to the increased awareness of Indians about the different
value systems prevalent in different parts of the world. More so since
their predominant business partners happen to be from US and the Europe,
they could have been impacted heavily by the Western values such as open
communication, collaboration, trust, authenticity, autonomy, and
confrontation for resolving conflicts (Pareek 1988). The close
interaction with geographically spread audience and the periodic
interventions could be the factors impacting the Communication
Competency of the managers. This work clearly supports communication as
a potential contributor in building effective interpersonal and
harmonious working relationships. High levels of Communication
Competence are important to organizations. The communication skill
dimensions supported by this study are all critical thinking skills
involving empathy, effective listening, adaptability and flexibility.
High levels of affective, cognitive, and behavioural competence
components are essential for establishing and developing strong
relationships within organizational systems.
Future Research
Using sample organizations from the same sector to assess the
Communication Competence of the managers is sufficient; however,
different companies especially from different sectors have different
rules of communicating, or different criteria for evaluating the
appropriate ness or effectiveness of communication and different
communication environment. For this reason, future research should apply
this model to different types of organizations to ensure if the managers
in other sectors also display the same communication competence as in IT
and ITes sector. Future directions might involve a comparative study of
testing Communication Competence of managers from multinational
companies and managers from the typically Indian companies which should
throw light on the role of organizational culture in impacting the
Communication Competence of their employees.
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Reeta Raina is Associate Professor (Comm. Area), FORE School of
Management, Qutub Institutional Area, New Delhi 110016. E-mail:
rraina@fsm.ac.in. Neerja Pande is Associate Professor (Comm. Area),
Indian Institute of Management Lucknow, Noida Campus, B-1, Sector 62,
Noida 201307. Email: neerja@iiml.ac.in
Table 1: KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure .669
of Sampling Adequacy.
Bartlett's Test Approx. 798.979
of Sphericity Chi-Square
Df 231
Sig. .000
Table 2: Total Variance Explained
Component Initial Eigenvalues
Total % of Cumulative
Variance %
1 4.381 19.912 19.912
2 2.148 9.765 29.677
3 1.999 9.087 38.763
4 1.570 7.139 45.902
5 1.314 5.971 51.873
6 1.151 5.231 57.104
7 1.101 5.005 62.109
8 .947 4.305 66.414
9 .852 3.872 70.286
10 .817 3.715 74.001
11 .734 3.338 77.339
12 .668 3.035 80.374
13 .646 2.935 83.308
14 .631 2.868 86.176
15 .538 2.444 88.621
16 .492 2.235 90.856
17 .432 1.962 92.818
18 .407 1.851 94.669
19 .367 1.667 96.336
20 .324 1.475 97.811
21 .279 1.266 99.077
22 .203 .923 100.000
Component Extraction Sums of
Squared Loadings
Total % of Cumulative
Variance %
1 4.381 19.912 19.912
2 2.148 9.765 29.677
3 1.999 9.087 38.763
4 1.570 7.139 45.902
5 1.314 5.971 51.873
6 1.151 5.231 57.104
7 1.101 5.005 62.109
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
Component Rotation Sums of
Squared Loadings
Total % of Cumulative
Variance %
1 2.614 11.883 11.883
2 2.136 9.709 21.592
3 2.108 9.583 31.174
4 1.824 8.289 39.463
5 1.790 8.137 47.600
6 1.687 7.668 55.268
7 1.505 6.841 62.109
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
Extraction Method: Principal Component Analysis.
Table 3: Rotated Component Matrix (a)
Component
1 2 3 4 5 6 7
q6 .698
q7 .663
q11 -.644
q12 -.584
q13 .577
q14
q15 .802
q17 .829
q19 .718
q21 .704
q23 .613
q24 .814
q25 .801
q26 .652
q27 .580
q28
q29 .755
q30 .817
q31 .735
q32 .661
q33 .742
q36 .806
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
(a.) Rotation converged in 8 iterations.
Table 4: ANOVA Results (H1)
Sum of Squares Df Mean Square F Sig.
Listening Between Groups .131 1 .131 .413 .521
Within Groups 45.659 144 .317
Total 45.790 145
Extrovert Between Groups .007 1 .007 .014 .905
Within Groups 74.638 144 .518
Total 74.646 145
Openness Between Groups .129 1 .129 .373 .542
Within Groups 49.750 144 .345
Total 49.878 145
Understanding Between Groups .015 1 .015 .043 .836
Within Groups 50.733 144 .352
Total 50.748 145
Effectiveness Between Groups .009 1 .009 .022 .884
Within Groups 59.958 144 .416
Total 59.967 145
Flexible Between Groups .755 1 .755 2.361 .127
Within Groups 46.026 144 .320
Total 46.781 145
Empathy Between Groups .190 1 .190 .285 .594
Within Groups 95.817 144 .665
Total 96.007 145
Table 5: ANOVA Results (H2)
Mean
Sum of Squares Df Square F Sig.
Listening Between Groups 4.367 2 2.183 7.537 .001
Within Groups 41.423 143 .290
Total 45.790 145
Extrovert Between Groups .270 2 .135 .259 .772
Within Groups 74.376 143 .520
Total 74.646 145
Openness Between Groups .912 2 .456 1.331 .267
Within Groups 48.967 143 .342
Total 49.878 145
Understanding Between Groups .246 2 .123 .348 .706
Within Groups 50.502 143 .353
Total 50.748 145
Effectiveness Between Groups .098 2 .049 .117 .890
Within Groups 59.869 143 .419
Total 59.967 145
Flexible Between Groups .500 2 .250 .772 .464
Within Groups 46.281 143 .324
Total 46.781 145
Empathy Between Groups 2.640 2 1.320 2.022 .136
Within Groups 93.367 143 .653
Total 96.007 145
Table 6: ANOVA Results (H3)
Mean
Sum of Squares Df Square F Sig.
Listening Between Groups .008 1 .008 .027 .871
Within Groups 43.300 136 .318
Total 43.309 137
Extrovert Between Groups .011 1 .011 .022 .883
Within Groups 71.019 136 .522
Total 71.031 137
Openness Between Groups .256 1 .256 .737 .392
Within Groups 47.253 136 .347
Total 47.509 137
Understanding Between Groups .007 1 .007 .019 .890
Within Groups 49.486 136 .364
Total 49.493 137
Effectiveness Between Groups .546 1 .546 1.293 .257
Within Groups 57.447 136 .422
Total 57.993 137
Flexible Between Groups .687 1 .687 2.074 .152
Within Groups 45.090 136 .332
Total 45.777 137
Empathy Between Groups .040 1 .040 .057 .811
Within Groups 94.786 136 .697
Total 94.826 137
Table 7: ANOVA Results (H4)
Mean
Sum of Squares Df Square F Sig.
Listening Between Groups .934 1 .934 3.109 .080
Within Groups 42.983 143 .301
Total 43.918 144
Extrovert Between Groups 1.264 1 1.264 2.464 .119
Within Groups 73.368 143 .513
Total 74.632 144
Openness Between Groups .373 1 .373 1.109 .294
Within Groups 48.034 143 .336
Total 48.407 144
Understanding Between Groups .030 1 .030 .084 .772
Within Groups 50.718 143 .355
Total 50.748 144
Effectiveness Between Groups .088 1 .088 .209 .648
Within Groups 59.854 143 .419
Total 59.941 144
Flexible Between Groups .047 1 .047 .144 .705
Within Groups 46.591 143 .326
Total 46.638 144
Empathy Between Groups .298 1 .298 .446 .505
Within Groups 95.609 143 .669
Total 95.907 144