186
CHAPTER 5
ANALYSIS OF THE FUNCTIONAL AND
DYSFUNCTIONAL DIMENSIONS OF
CONFLICTS
187
CHAPTER 5
ANALYSIS OF THE FUNCTIONAL AND DYSFUNCTIONAL
DIMENSIONS OF CONFLICTS
The analyses made in the last chapter were related to the factors that generate
conflicts in organizations. The empirical analysis was based on the data collected
from the respondents. In a research which is exclusively based on qualitative data
as it is the case in this research, the observations and findings based on the data can
also be applicable to further analysis for other related variables. In this chapter the
qualitative factors that contribute to the nature of conflicts along with the
functional and dysfunctional (constructive and destructive) dimensions of conflicts
in organizations are analysed. The interpretation and discussions on the findings of
the analyses is done almost simultaneously as in the previous chapter.
The attitude model of conflicts has been formulated using regression model
analysis in the previous chapter. As it has been stated, the model can be applied to
any form of conflicts in organizations. This is due to the fact that group conflict
theory emphasizes the prevalence of negative attitude as the fundamental source of
conflicts among a collection of individuals (group conflicts). Black and Olzon
(1967, 1992) put forward the concept of negative out group attitudes uprooted in
perceived threat or other negative emotions, influence the perception of the parties
involved. Obviously, other secondary and conventional sources such as goal
diversity, inter group dependence, role ambiguity, limited resources etc. might also
be contributing to these conflict situations, both favourably and unfavourably.
As it has been mentioned in the previous chapters, several other factors are
contributing to the escalation, modulation and moderation of conflicts in
organizations. As far as the public and private sectors are concerned, these factors
are detrimental since the effectiveness and efficiency of these sectors are
depending upon the successful utilization and management of these factors. The
most important among them are emotional intelligence and conflict managing or
handling style. When it comes to the analysis of the functional and dysfunctional
dimensions of conflicts in the public and private sectors, it is essential and
mandatory to have analyses of these factors.
188
5.1 Emotional Intelligence And Conflicts
As it has already been stated in the previous chapters, emotional intelligence
(EQ) is a relatively recent behavioural model rising to prominence with Daniel
Goleman’s 1995 book ‘Emotional Intelligence’. EQ principles provide a new way
to understand and assess people’s behaviours, management styles, attitudes,
interpersonal skills and potentials (Goleman, 1995) Goleman suggested the model
of EI (EQ) with specification to inter personal relationships and skills. Ashlea
Truth (1996) stated that EI differentially influences the relationship between
conflict and decision making performance in teams, depending on the complexity
of the task being performed. (Ashlea Truth,1996 ‘Model of team EI and conflict’).
The relevance of group structures in organisations lies in the fact that teams
produce better performance outputs than individuals for organizations, especially
for problem solving, decision making and concept mastery tasks. (Gigone &
Hastie, 1997).
The model put forward by Goleman suggests the five domains of EQ such as
self identification of emotions, self regulation of emotions, self motivation for
creating positivity in emotions, developing empathy for other’s emotions and
managing relationships (Goleman, 1995). The above process can be converted
from the interpersonal level to inter group or Intra group level (Jehn, 1995). In this
chapter, the EQ levels of different respondents have been analysed. The role of EQ
in the conflict escalation or degradation of different types of conflicts has also been
analysed and interpreted.
Questions 1 to 5 in the questionnaire ‘D’ represent the five domains of EQ.
Question No.6 refers to the role of EQ in making good relationships between
individuals as well as among groups. Questions 7 to 10 denote the role of EQ in
group conflicts. Table No. 5.1. shows the respondents in the public sector with
regard to the EQ domains. The overall score of EQ when all the categories are
taken together, in the two sectors is 17.51 with a standard deviation of 1.03 and
mean item score 3.50. This comes to 70.2% which is almost in the high scoring
category (>60%). Individual category scores show variations at considerable rates.
As shown in the table
C
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Source:
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189
tandard eviation
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190
The highest score is in the category of senior level executives followed by
senior level employees, junior level executives and lower level employees. The
standard deviation S.D. is the lowest in the lower level employee category
followed by junior level executives, senior level employees and senior executives.
It is interesting to note that the high score category of the senior level executives
register the highest S.D. denoting the lowest consistency. The low scoring category
of lower level employees registers highest consistency with lowest S.D. These
observations can be attributed to the high educational qualification coupled with
the orientation programmes undergone by the senior level executives. The lower
level employees are having comparatively low educational qualification and have
not been undergone any orientation programmes in this regard as they are not
supposed to deliver any kind of supervisory roles. The variations can also
attributed to the demographic factors. On informal conversation with the
respondents during the survey, the concerned categories were particular about the
adequacy and inadequacy of the orientation programmes.
All the scores shown above denotes a high level score of EQ among the
respondents with the lowest average score in the lower level employee category
Table 5.2. shows the average scores and S.D. of the private sector regarding the
score of EQ.
Table 5.2
Mean scores of EQ of the private sector categories
Category Average Scores
Mean Item Scores
No. of Respondents
Standard Deviation(S.D.)
Senior level Executives 17.71 3.54 (70.8) 32 1.28
Junior level Executives 17.49 3.49 (69.8) 79 1.09
Senior level Employees 17.75 3.55 (71) 74 1.21
Lower level Employees 17.30 3.4 (68) 41 1.03
TOTAL 226
Source: Survey data
Figures: in parenthesis denote percentage
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191
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192
5.1.1 HYPOTHESIS 5.1
H1: Significant difference between the EQ levels of the private and public sectors.
For testing this hypothesis Z test is administered. The value of Z is computed
using the average scores shown in the table 5.1 and 5.2. Mean score for each sector
is computed from the mean scores of the categories concerned. The calculated
value of Z is o.66. The critical value of Z at 5% level of significance is 1.960 for
the degree of freedom 531. Since the table value is higher than the calculated value
the null hypothesis is accepted. Hence it can be stated that there is no significant
difference in the EQ levels of the public and private sectors.
5.1.2 Difference in EQ Levels of The Executives of The Public And Private
Sectors
‘Z’ value is calculated assuming that the S.D. of the samples in place of the
population S.D. The Z value is calculated as 0.526. The table value of ‘Z’ at 0.05
levels is 1.960 for 201 degrees of freedom which is higher than the calculated
value. Hence it can be stated that there is no significant difference in the EQ levels
of the executives in the private and public sectors. The difference in means is due
to chance errors of sampling. The similarity of the EQ levels of the executives can
be attributed to the similarity of the functions and the educational qualification of
the category in the two sectors.
From the above observations, it can be stated that all the categories of the
two sectors are having high scores of EQ (>60%), though with considerably
different standard deviations.
5.1.3 Conflict Management Styles
The different styles of conflict management are discussed here, with respect
to the respondents in the two sectors. Different adopting strategies of conflict
handing are characterized with the two dyadic terms of assertiveness and co-
operation (Blake and Mouton, 1964,1985). The important model of conflict
management styles consist of the five different modes such as competing,
accommodating, avoiding, collaborating and compromising. (Arrow, Kenneth J,
1995, Rahim,1996). In the competing style the individual pursues his own
193
concerns at the other person’s expenses. In the accommodating style the individual
or the group neglects his own concerns to satisfy the concerns of the other party.
Avoiding style is characterized with the sidestepping an issue, postponing an issue
until a better time, or simply withdrawing from the conflicting situation.
Collaborating, involves an attempt to work with others to find out a solution that
fully satisfies their concerns.
Questionnaire ‘E’ contains 12 questions which represent the five conflict
management styles. The term conflict management and conflict handling are used
inter changeably here in order to integrate the commonality.. Question Nos,1 and 4
represent competing style, while question Nos. 2 and 7 denote compromising style.
Question Nos. 3 and 6 represent the collaborating style and question Nos. 4 and 8
stands for avoiding style. Question No 5 represents accommodating style and the
questions 10,11,12 hint on the effectiveness of the collaborating style.
Table 5.3 shows the comparative scores of each style with the different
categories of the public and private sectors. The altogether average scores for each
of the conflict handling style are as follows.
Table 5.3
Scores of conflict management styles of the two sectors
Sl. No Conflict Management Style
Mean Item Scores Percentage Scores
1 Competing 3.114 62.2
2 Collaborating 3.383 67.7
3 Avoiding 3.110 62.1
4 Compromising 3.381 67.6
5 Accommodating 3.04 60.8
Source: Survey data
Figures: in parenthesis denote percentage
The lowest scoring style is ‘accommodating’ with a mean of 3.04. The
highest scoring item is ‘collaborating’ with a mean score of 3.383 followed by
‘compro
competin
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40
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60
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194
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195
Table 5.4
Mean and S.D. scores of conflict management styles of private & public
sectors
Public sector Private sector
Senior
Executives Junior
Executiv-esSenior
Employe-esLower levelEmploye-es
Senior Executiv-es
Junior Executiv-es
Senior Employe-es
Lower levelEmploye-es
Competing (Forcing)
3.11 (62.2)
1.02 3.17
(63.4) 1.18
2.98 (59.6)
0.983.21
(64.2)1.00
3.35 (67)
1.113.09
(61.8)1.19
2.85 (57)
0.89 3.19
(63.8)0.98
Collaboratng 3.56
(71.2) 0.99
3.45 (69)
1.003.48
(63.6)0.89
3.06 (61.2)
0.983.50 (70)
1.163.25 (65)
1.08 3.48
(69.6) 0.79
3.29 (65.8)
0.88
Avoiding 2.85 (57)
0.95 3.00 (60)
1.152.88
(57.6)1.01
3.11 (62.2)
1.112.99
(59.8)1.80
3.05 (61)
1.11 3.55 (71)
0.95 3.42
(68.4)1.11
Compromising 3.33
(66.6) 1.18
3.41 (68.2)
1.183.55 (71)
1.283.29
(65.8)1.18
3.19 (63.8)
1.163.31
(66.2)1.82
3.48 (69.6)
1.08 3.45 (69)
1.16
Accomodating 2.75 (55)
1.00
2.91 (58.2)
1.172.96
(59.2)1.15
2.82
(56.4)1.21
2.89 (57.8)
1.01
3.78 (75.6)
1.16 3.12
(62.4) 1.6
3.15 (63)
1.12
Source: Survey data
Figures: in parenthesis denote percentage
Some of the important observations are illustrative of the category wise
specifications in conflict management styles. The senior executives of the public
sector have the average scores 3.11, 3.56, 2.88, 3.33 and 2.75 for the five styles
respectively in the order shown in the table. The private sector senior executives
have the score of 3.35, 3.50, 2.99, 3.19, 2.89 respectively for the five styles. In
both cases ‘collaborating style’ dominates among other styles. This is a clear
indication of the professionalized and strategic human management approach
seemed to have been cultivated in that category in the recent years. ‘Job security is
the prime concern of the employees in the post globalised period’is the set of
words adequate to quote at this juncture.
For the competing styles, the scores from the senior executives to lower
employees, in the public and private sectors is 3.11, 3.17, 2.98, 3.21, 3.35, 3.09,
2.85 and 3.19 respectively. The highest score for the competing style is for lower
level employees in the public sector and senior level executives in the private
sector. This observation is highly contradictory when compared to the overall
scoring pattern of the whole population. The senior level executives and the lower
level employees who are at the two bipolar ends in the respondent pattern of this
196
research, are having the commonality of having the ‘on the job stress’ generating
from different sources. This latent mode of organizational stress made them
restless and competing. However this is contradictory to the observations made for
the category of senior executives having high score of E.Q.
5.1.4. Difference between The Scores for The Collaborating and
Compromising Styles of the Two Sectors
The scores for each item denoting the collaborative and compromising
styles have been computed from the responses. The value of Z is calculated as
0.04. The table value for Z at 0.05 level of significance is 0.674 ( d.f.=531).
Crirtical value of Z is higher than the calculated value. Hence it can be concluded
that there is no significant difference between the two scores for collaborating and
compromising styles in the two sectors.
5.1.5 Substantive and Relational Outcomes of Conflict Management Styles
Conflict Management handling styles with regard to the dyadic dimensions
of cooperativeness and assertiveness (Blake and Mouton 1990, Rahim, 1992,
Thomas 1992) seek the effectiveness of the styles applied. The effectiveness of the
styles applied by the conflicting parties is, in fact, the substantive and relational
outcomes (Thomas 1992, Jyosvold, 1991). The substantive outcomes(SOT) include
the compromise or agreement reached by the parties with the specific concessions
and promises. Relational outcome (ROT) or effectiveness of the conflict handling
styles refers to strong affective and interactive social bonds, mutual trust and
understanding, willingness to cooperate etc. Questions 10, 11, and 12 of the
questionnaire ‘F’ are related to the substantive and relational outcomes.
5.1.6 Relation between Substantive outcome And Conflict Management Styles
Spearman’s correlation coefficients for the relation between substantive
outcome and each of the conflict management styles are shown below in the
correlation matrices.
197
Table 5.5
Correlation Matrix Between substantial outcome and forcing/competing style
Sl No
Conflict Management Styles
1 2
1 Forcing/
Competing 1 0.44
2 Substantive Outcome
0.44 1
Table 5.6
Correlation Matrix Between substantive outcome and collaborating style
Sl No
Conflict Management Styles
1 2
1 Collaborating 1 0.65
2 Substantive Outcome 0.65 1
Table 5.7
Correlation Matrix Between substantive outcome and compromising style
Sl No
Conflict Management Styles
1 2
1 Compromising 1 0.38
2 Substantive Outcome
0.38 1
198
Table 5.8
Correlation Matrix Between substantive outcome and avoiding style
Table 5.9
Correlation Matrix Between substantive outcome and accommodating style
Source survey data
All the values of ‘r’ are significant at 0.05 level
Tables 5.5 to 5.9 reveal that the Spearman’s correlation coefficient ‘r’
between substantive outcome (SOT) and conflict management styles (CMS) are
0.44, 0.65, 0.38,-0.29 and 0.25, for forcing/competing, collaborating,
Sl No
Conflict Management Styles
1 2
1 Accommodating 1 0.25
2 Substantive Outcome
0.25 1
Sl No
Conflict Management Styles
1 2
1 Avoiding 1 --0.29
2 Substantive Outcome
--0.29 1
199
compromising, accommodating and avoiding respectively. The R2 values also
show the same pattern. It can be noted that the collaborating style is more strongly
and positively correlated to SOT, followed by forcing, compromising and
avoiding. The indication is that the chances for reaching an amicable solution, or
SOT for the conflict issue is more possible with the collaborating style, in the
private and public sectors, followed by forcing, compromising, accomodating and
avoiding styles. Avoiding style denotes a negative correlation. The indication is
that whenever the conflict issue is neglected substantive outcome decreases. The
more the avoidance, the less will be the substantial outcome. Also the later two
styles are weakly correlated. Accommodating style is weakly correlated to SOT
which indicates that whenever the ‘give in’ policy style or win-lose style is adopted
in a conflict issue, the SOT will be less possible, or there are less chances to reach
an amicable solution to the issue in the long run.
The relational outcome (ROT) which indicates the positive emotional
bondage or mutual trust attained through the resolution of the conflict issue is also
differently correlated to different styles.
5.1.6 Relation between Relational Outcome and Conflict Management Styles
Spearman’s correlation coefficients for the relation between relational
outcome and each of the conflict management styles are shown below in the
correlation matrices
Table 5.10
Correlation Matrix between relational outcome and forcing/competing style
Sl No
Conflict Management Styles
1 2
1 Forcing/
Competing 1 --0.49
2 Relational outcome --0.49 1
200
Table 5.11
Correlation Matrix between relational outcome and collaborating style
Sl No
Conflict Management Styles
1 2
1 Collaborating 1 0.78
2 Relational outcome 0.78 1
Table 5.12
Correlation Matrix between relational outcome and compromising styles
Sl No
Conflict Management Styles
1 2
1 Compromising 1 0.21
2 Relational outcome 0.21 1
Table 5.13
Correlation Matrix between relational outcome and avoiding style
Sl No
Conflict Management Styles
1 2
1 Avoiding 1 0.40
2 Relational outcome 0.40 1
201
Table 5.14
Correlation Matrix between relational outcome and accommodating style
Sl No
Conflict Management Styles
1 2
1 Accommodating 1 0.51
2 Relational outcome 0.51 1
All the values of ‘r’ are significant at 0.05 level.
The ‘r’ values for these relations are --0.49, 0.78, 0.21, 0.40 and 0.51
respectively for the five styles of forcing, collaborating, compromising, avoiding
and accommodating styles respectively. The negative correlation of -0.49 for the
forcing or competing style illustrates that the chances for attaining positive
emotional bondage and mutual trust will be negatively affected by the forcing or
aggressive style. The strong positive value of ‘r’ between ROT and the
collaborating style (0.78) indicates that the chances for building up mutual trust
and positive emotional bondage are very high with the collaborating (win-win)
style, followed by accommodating, avoiding and compromising styles. An
interesting fact is that avoiding style which is negatively correlated to SOT is
positively correlated to ROT (r=0.40).
5.1.7 Conglomerate Effect of Conflict Management Styles in the Public and
Private Sectors
The above analysis of the relation between SOT and ROT with the conflict
management styles are unidirectional, or are one to one relations. In practice, it is
more reliable to adopt a combined style or clubbing two or more styles together for
a desirable solution or outcome. (Van de Ulier, 1995, Munduate, Peiro 1999). The
conglomerate effect of conflict management style refers to the combined effect of
the styles for the resolution of the conflict issue (Rubin, 1994). Multiple correlation
202
technique is used to analyse the effect of the conglomerate effect of the conflict
management styles with ROT and SOT.
5.1.8 Conglomerate Effect of Forcing And Collaborative Styles on
Substantive Outcome
Tables 5.5 to 5.9 show the individual ‘r’ values for the five conflict
management styles with regard to SOT. The values of ‘r’ for forcing and
collaborating styles are 0.44 and 0.65 respectively. The multiple correlation
coefficient values (R) for the relation of the two altogether with SOT is shown in
Table 5.15.
Table 5.15
Multiple correlation coefficient value( R) for forcing and collaborating styles
with SOT
Sl. No.
Conglomerating Styles Multiple Correlation
Coefficient (R) R2
1 2
1 Collaborating Forcing 0.76 57.76
Not Significant at 0.05 level, p>0.05
The multiple correlation coefficient ‘R’ between the SOT and forcing and
collaborating styles taken together is 0.76. This indicates a much higher positive
correlation than the individual influence of each of the two values of r. value of R2
= 0.58, which indicates that 58% f the variance in the substantive outcomes are
influenced by forcing and collaborating styles taken together. Hence the
conglomerate of forcing and collaborating creates more effectiveness in the
substantive outcomes of the management of the conflict issue than that of the
individual case. However this value is not significant at 0.05 levels. Still this
indicates a positive correlation.
203
5.1.9 Conglomerate Effect of Collaborating And Compromising
Styles on Substantive Effectiveness
Table 5.16 shows the interrelationship between substantive effectiveness of
conflict issue and the combined or conglomerate of collaborating and
compromising styles.
Table 5.16
Multiple correlation coefficient value( R) for collaborating and compromising
styles with SOT
Sl. No.
Conglomerating Styles Multiple Correlation
Coefficient (R) R2
1 2
1 Collaborating Compromising 0.69 0.48
Significant at 0.05 level
Multiple correlation coefficients ‘R’ is 0.69 which is significant at 0.05 level.
The value of R2 is 0.48 which indicates that 48% of the variance can be explained
by the combined correlation of ‘collaborating’ and ‘compromising’ styles. When,
the combined styles of collaborating and compromising styles are adopted for the
resolution of the conflict issue, the possibility for reaching at a comfortable
substantive outcome zone, will be much higher than If single styles of each of the
above were adopted and correlation with the SOT would have been much weaker.
The indication is that conglomerate of conflict management styles are more
effective than single styles.
5.1.10 Conglomerate Effect of Forcing And Accommodating Styles on
Substantive Effectiveness.
Table 5.17 shows the ‘R’ values between the ‘forcing’ and ‘accommodating’
styles, with individual correlation with substantive outcome of conflicts.
204
Table 5.17
Multiple correlation coefficient value( R) for forcing and accommodating
styles with SOT
Sl. No.
Conglomerating Styles Multiple Correlation
Coefficient (R) R2
1 2
1 Forcing Accomodating 0.67 0.45
The multiple correlation coefficient ‘R’ is calculated as 0.67. This shows a
comparatively higher positive value of R between the substantive outcome and the
combined conflict management styles, than the individual correlation coefficient
value between the SOT and each one of the styles. The value of R2 is 0.45 which
indicates that the extent of influence by the combined or conglomerate effect of the
forcing and accommodating styles on the substantive outcomes is 45%.
Substantive effectiveness increases with the simultaneous application of forcing
and accommodating styles. The conglomerate procures more positive and
compromising solution of the conflict issues than in the case of individual
application of each of the styles.
5.1.11 Conglomerate Effect of Forcing And Collaborating Styles on the
Relational Effectiveness
As explained earlier, the relational outcomes refer to the positive emotional
bondage and trust created between the concerned parties after the resolution of the
conflict issue. Tables 5.10 to 5.14 illustrates the individual correlation coefficient
(r) values of each of the conflicting styles with the relational outcome (ROT).
Forcing style denotes a negative correlation with ROT which indicates that when
forcing / competing style is applied, the trust and positive emotional bondage
between the parties decreases. This can lead to further conflicts (Afzalur Rahim M.
2002). The other styles are positively as well as meagerly correlated to ROT.
Table 5.18 shows the conglomerate effect of forcing and collaborating styles
on the relational effectiveness of conflict resolution.
205
Table 5.18
Multiple correlation coefficient value( R) for forcing and collaborating styles
with ROT
Sl. No.
Conglomerating Styles Multiple Correlation
Coefficient (R) R2
1 2
1 Forcing Collaborating 0.55 0.30
Source survey data, Significant at 0.05 level
The multiple correlation coefficient of the conglomerate of forcing and
collaborating styles with relational outcome (R) is 0.55 which is positive. Though
it is higher than the value of forcing style which is negatively correlated when it is
taken individually, it is lower than the individual ‘r’ value of the collaborating
style.. The value of R2 is 0.30 which points out that 30% of the variance in the
relational effectiveness is explained by the conglomerate of forcing and
collaborating styles. Hence the indication is that the conglomerate of forcing and
collaborating style is less effective than individual collaborating style with regard
to ROT.. However it is more effective than individual forcing style in the private
and public sectors in Kerala.
5.1.12 Conglomerate Effect of Collaborating and Compromising Styles on
`Relational Outcome
Table 5.19
Multiple correlation coefficient value ( R) for collaborating and compromising
styles with ROT
Sl. No.
Conglomerating Styles Multiple Correlation Coefficient
(R)
R2 1 2
1 Collaborating Compromising 0.34 0.116
Significant at 0.05 level
206
The combined correlation coefficient or the multiple correlation coefficient
of collaborating and compromising styles is 0.34 and the R2 value is 0.116. The
indication is that the combined style of the above two is having the positive
correlation of 0.34 which is less than that of the individual collaborating style. The
combined effect of the two has no additional effect at all. In fact it lessens the
relational effectiveness than in the case of only collaborating style is used The
combination explains about 11.6% of the variation in the relational outcome. The
conclusion is that the combined style of the two has no additional effect on the
relational outcome. It is interesting to note that collaborating style when combined
with any other styles is not more effective than when it is used individually as far
as the relational outcome of conflict issue is concerned.
5.1.13 Conglomerate Effect of forcing And Accommodating Styles on
Relational Outcome
Table 5.20 shows the multiple correlation coefficient of the combination of
forcing and accommodating styles which are perfectly opposite characteristically.
Table 5.20
Multiple correlation coefficient value( R) for forcing and Accommodating
styles with ROT
Sl. No.
Conglomerating Styles Multiple Correlation Coefficient
(R)
R2 1 2
1 Forcing Accommodating 0.58 0..34
Significant at 0.05 level
The ‘R’ value is 0.58 which denotes a higher positive correlation than the
individual ‘r’ values. The relational outcome is very high compared to the
individual influence of the component styles. The indication is that more trust and
emotional bondage is created between the conflict parties than with the
conglomerate of forcing style and accommodating style. The R2 value is 0.34
207
which indicates that 34% of the variance in the relational outcome is explained by
the duo, in the private and public sectors in Kerala.
5.1.14 Discussion And Conclusion
On the three occasions of combining two different styles of conflict
management styles, such as collaborating – forcing, collaborating – compromising
and forcing –accommodating, considerable positive and negative change has been
noted in the SOT and ROT compared to the individual execution of each style in
the public and private sectors. Both substantive outcome and relational outcome
are found varying with the conglomerate of forcing – collaborating. Previously the
forcing style alone created negative impact on emotional bondage between the
conflicting parties. The combined effect of the two registers a positive correlation
which is a considerable change for the forcing style alone. However, the combined
effect of the two is less than the individual effect of the collaborating style in terms
of the value of ‘r’. The inference is that the conglomerate of the two is beneficial
for the forcing style at the cost of the collaborating style. Except for the
conglomerate of the compromising and collaborating style, other combinations
show more effectiveness in terms of ROT. Collaborating style is found to be more
effective when it is used individually in terms of ROT. The other two situations
have similar observations. This is exactly coinciding with the conclusion of
previous studies that combination of the styles are common among today’s
managers who are striving for the maximum on the material harmony and
cooperation coupled with emotional satisfaction and strengthened bondage after
the resolution process” (Deutsech, 1973 ).
The no difference observation found in the testing of the hypothesis (5.1)
between the private and public sector respondents in terms of EQ can be attributed
to the common demographic factors such as academic qualification, income,
experience etc.
On the two dimensional approach of cooperativeness and assertiveness also
(Black & Mouton 1970, Rahim 1992) the above observations are meaningful and
appropriate. The forcing style which is having assertiveness only and no
cooperativeness at all is likely to create temporary solutions in the substantive
208
outcomes such as signing in an agreement for the time being. The negative
emotions created such as humility, anger, revenge etc. could create more
destructive conflicts in the organizations of the private and public sectors in
Kerala.
In the case of the duo of collaborative–compromise also, the assertiveness/
cooperativeness factor stands distinct. Both of these styles are characterized by the
dyadic representation of the two dimensions in almost equal magnitudes.
Cooperativeness dominates the other in respect of the collaborating style. The
double effect of cooperativeness coupled with more or less equivalent measures of
assertiveness makes the significant positive influence on the conglomerate in terms
of the substantive and relational outcomes. In the case of the forcing-
accommodating combination also, the domination of assertiveness in one
component (forcing) is nullified by the outstanding cooperativeness component in
the accommodating style (Fischer, Ury 1981) Positive and increased scope for
satisfactory solution and healthy emotional bondage and trust are worked out in the
process. As far as this research is concerned, the observations are based on the
responses of the private and public sector respondents in Kerala.
Hence it can be concluded by stating that combined styles of conflict
management create better outcomes for the conflict issues. It also creates the
positive emotionality of trust and affection as bye products, though in varying
degrees in the private and public sectors of Kerala
5.2 Functional And Dysfunctional Conflicts
The argument on the constructivity and destructivity of conflicts in
organistions has been acquiring momentum with reference to the traditional,
behavioural and inter reactionists point of views as stated in chapter 1
(Introduction). Functional conflicts refer to conflicts that procure positive
outcomes to the organization and its effectiveness. Dysfunctional conflicts are
those which create negative outcomes as far as the organization and its members
are concerned. The categorisation of the constructive and destructive conflicts are,
also made in another nominal groupings such as affective and task conflicts,
relationships and cognitive conflicts, and substantive and emotional conflicts
209
(Jehn, 1995). Generally the conflicts that have positive effects on the individual
and group performance (functional conflicts) relate to disagreements on tasks,
policies and other organizational issues (task conflicts/ issue conflicts). Similarly,
conflicts that have negative effects on the individual and group performance relate
to negative emotions such as anger, disharmony, jealousy, revenge, humility etc.
(Amazon 1996, John, Northcraft & Neale, 1999, Rahim 2001).
In this section of this chapter the constructivity and destructivity of conflicts
are analysed and discussed. Various conflicts in organizations are subjected to
analysis for the factors that constitute particular conflicts. Questionnaire ‘F’
appended to this thesis includes questions related to constructive and destructive
conflicts. Question 1 refers to the unavoidability of conflicts in organizations.
5.2.1 Perception of Public and Private Sector Respondents on the
Unavoidability of Conflicts
Item 1 of questionnaire states that ‘conflicts are unavoidable in
organizations. Table 5.21 presents the frequency distribution of the public and
private sector respondents to the this item which shows their perception whether
they think that conflicts are unavoidable in originations
Table 5.21
Frequency distribution of the responses to ‘ conflicts are unavoidable’
Category Strongly
agree
Almost Agree
Sometimes Agee
Rarely Agree
Not at all agree Total
Public Sector
105 (34.2)
80 (26.05)
60 (19.54)
42 (13.68)
20 (6.51)
307
Private Sector
85 (37.61)
56 (24.78)
47 (20.8)
30 (13.27)
8 (3.53)
226
Total 190
(35.64) 136
(25.51) 107
(20.07) 72
(13.50) 28
(5.25) 533
X2 = 2.818, X2critical=9.488, d.f.=4, not significant at 0.05 level Source: survey data Figures in parenthesis denote percentage
A
unavoid
are 25.5
agree’,
that maj
strongly
significa
sectors.
number
of confl
expected
differenc
5.2.2
‘Unavoi
T
sectors (
24681012
Almost 35.
ablity of co
51%, 20.07
‘sometimes
jority of the
y agreeing to
ance. The v
The concl
of respond
flicts in the
d especially
ces’ as the f
Opi
Perception
idability O
able 5.22 p
(senior and j
0204060800020
agre
Stron
1058
Opic
64 % of t
onflicts in pu
7%, 13.50%
s agree’, ‘ra
e responden
o the statem
value of X2 i
lusion is th
ents in the
eir organiz
y when m
first choice
inion of the
n of Executi
f Conflicts’
presents the
junior) w. r
ee
ngly AlmAgr
8085
nion oconflict
the total re
ublic and pr
% and 5.25
arely agree
nts(61.15%)
ments. Calcu
is not signi
hat there is
two sectors
zations. Ob
majority of
for the pote
Fi
e two sector
ives of Pub
’
frequency
r. to the abo
most ree
SomA
6056
of the twts are u
Public
espondents
rivate secto
5% respecti
’ and ‘stron
) in the two
ulated value
ficant for th
s no signif
s regarding
bviously thi
the respo
ential source
igure 5.4
rs on' confl
blic and Pri
distribution
ove item.
A
metimes Agee
R
4247
wo sect unavoid
Private
are strongl
or units. The
ively for th
ngly disagr
o sectors are
e of X2 =2.8
he differenc
ficant diffe
the questio
is observat
ndents pre
es of conflic
licts are un
ivate Sector
n of the exe
Agree
Rarely N
2230
tors ondable'
ly agreeing
e other distr
he options
ree’. This i
e either agr
818 at 0.05
ce between
rence betw
on of unavo
tion is very
eferred ‘Att
cts.
navoidable’
rs on the
ecutives of
Not at all agree
208
n '
210
g to the
ributions
‘almost
indicates
eeing or
level of
the two
ween the
idability
y much
titudinal
’
the two
Frequen
Categor
PublicSector
Executiv
PrivateSector
Executiv
Total
Source: X2 = 18.Figures
T
significa
sectors,
No. o
ncy distrib
ry StronAgr
c r ves
24(26.0
e r ves
11(9.9
35(17.2
survey data267, X2critiin parenthe
The value o
ant differenc
over the res
f public an
01020304050
agre
Stron
24
No. of
bution of ex
un
ngly ree
AlmAg
4 08)
2(7.
1 9)
4(4.4
5 24)
7(34
a ical=9.488,sis denote p
of X2 =18.2
ce in the di
sponses to t
nd private s
ee
ngly AlmAgr
2511
public an'conf
Pub
Table
xecutives in
navoidabilit
most gree
SomA
25 88) (2
46 44) (1
77 .97) (1
d.f.=4,signipercentage
67 which is
stribution o
the unavoida
Figur
sector execu
unavoi
most ree
SomA
20
46
nd privatflicts are
blic Sector
e 5.22
n the public
ty of conflic
metimes Agee
20 21.73) (
17 5.31) (
37 8.22) (
ificant 0.05
s significan
of the execu
ability of co
re 5.5
utives on th
idable’
A
etimes Agee
R
1217
te sector unavoida
Private
c and privat
cts
Rarely Agree D
12 (13.04)
30 (27.02)
42 (20.68)
level
nt at 0.05 le
utives of the
onflicts in o
he opinion
Agree
Rarely StD
2 1
30
executivable'Sector
te sectors o
Strongly Disagree
11 (11.95)
7 (6.31)
18 (8.86)
evel. Hence
e private an
organization
on 'conflict
trongly Disagree
11 7
ves on
211
over the
Total
92
111
203
there is
nd public
ns.
ts are
212
5.2.3 Perceptions of Manufacturing and Service Sector Respondents
Table 5.23 presents the frequency distribution of the manufacturing and
service sector for the responses to the unavoidability of conflicts in organizations.
Table 5.23
Frequency distribution of manufacuring and service sector respondents over the unavoidability of conflicts in the public and private sectors
Category Strongly Agree
Almost Agree
Sometimes Agee
Rarely Agree
Strongly Disagree Total
Manu- facturing
89 (31.01)
86 (29.96)
62 (21.60)
39 (13.59)
11 (3.83)
287
Service 46
(18.69) 108
(49.90) 46
(18.69) 27
(10.97) 19
(7.72) 246
Total 135
(25.32) 194
(36.39) 108
(20.26) 66
(12.38) 30
(5.6) 533
Source: survey data X2 =19.84, X2critical=9.488, d.f.=4,significant, 0.05 level Figures in parenthesis denote percentage
Figure 5.6
No. of the manufacturing and service sectors on' unavoidability of conflicts
89 8662
3911
46
108
4627 19
020406080100120
agree Agree
Strongly Almost Agree Sometimes Agee
Rarely Strongly Disagree
`No. of the manufacturing and service sector on unavoidability of
conflicts'Manufacturing Service sector
213
The frequency distribution of manufacturing and service sector responds
shown in Table 5.23 illustrates that almost 60.97% of the manufacturing sector and
62.59% of the service sector respondents are agreeing with the statement of the
unavoidability of conflicts in organizations. X2 value of 19.84 is significant at 0.05
level indicating significant difference between the manufacturing and service
sectors of the two sectors on the opinion that conflicts are unavoidable in the
public and private sector organizations.
5.2.4. Analysis of The Components of Functional and Dysfunctional
Conflicts.
As it has already been stated items 2,15,16 denote functional conflicts and
items 3,4,5 denote dysfunctional conflicts.in the questionnaire ‘F’. Other items are
related to the interrelationship between task and emotional conflicts and the impact
of these conflicts oneach other. Out of these, questions 2, 15 and 16. are related to
functional conflicts and interrelation between functional and dysfunctional
conflicts. Questions 3, 4,5 and are related to dysfunctional conflicts.
Table 5.24 presents the mean scores for the statement that conflicts on
methods, procedures and ideas on task are good or functional to the organizations.
This score represents the components of the constructive or task or functional
conflicts and In this table, the scores for the statement that emotion based conflicts
are dysfunctional or destructive are also included, for the public and private
sectors.
The mean scores for the functional conflicts reveal that lower level
employees in the public sector have the highest score of 3.95 (79%) for the
functional conflicts due to task, followed by senior executives, (3.84) senior
employees (3.65) and junior executives 3.28 respectively. The standard deviation is
the lowest for the lower level employee group indicating high consistency in the
scores. This is followed by senior executives, junior executives and senior
employees.
214
Table 5.24
Mean scores of different categories in the public and private sectors for the
perception on functional and dysfunctional conflicts
Sect
or
Categories
Functional Conflicts/ Task conflicts
Dysfunctional conflicts/ Emotional conflicts
Mean score per item
SD Nos.
Mean score per item
SD Nos.
Publ
ic S
ecto
r
Senior Executives 3.84 1.05 41 3.62 1.02 41
Junior Executives 3.28 1.11 51 3.54 0.95 51
Senior Employees 3.65 1.17 113 3.81 1.18 113
Lower Level Employees 3.95 0.96 102 3.88 1.11 102
Priv
ate
Sect
or
Senior Executives 3.71 1.17 32 3.96 0.99 32
Junior Executives 3.98 1.00 79 3.87 1.00 79
Senior Employees 4.01 0.92 74 3.98 0.92 74
Lower Level Employees 3.90 0.98 41 3.51 1.15 41
TOTAL 533 533
Source: Survey of data
In the private sector, the highest scoring category is the senior level
employees (4.01, 80.2%) followed by junior executives (3.98, 79.6%) lower level
employees (3.90, 78%) and senior executives (3.71, 74.2%). The lowest S.D. is
noted for the senior employee group (0.92) followed by lower level employees
(0.98), junior executives (1.00) and senior executives (3.71).
It is interesting to note that in the public sector, the lower level employee
group in the public sector scores the highest followed by the senior level
executives which is ironical. This can be attributed to the higher level of
215
cohesiveness in opinions in the lower level group who might be more exposed to
trade union activities than other categories.. In the senior executive category, the
high degree of responsibilities and higher level of professional experience make
the difference. In the private sector also there are contradictory observations. The
higher level of experience of the senior employees who might have witnessed
several conflict situations in the organizational context can be the reason for their
highest score. Junior level executives who are more enthusiastic about the
organizational processes like conflicts and its dynamics are in the second position.
The category of lower level employees have the highest score (3.88, 77.6%)
for dysfunctional conflicts caused by emotions in the public sector.. The next
highest scorer is for senior employees (3.81, 76.2%), senior executives (3.62,
72.4%) and junior executives (3.54, 70.8%). The lowest S.D is for the junior level
executives (0.95) followed by senior executives (0.95) followed by senior
executives (1.02), lower level employees (1.11) and senior employees (1.18). This
may be due to the hardships on economic grounds faced by the lower level
employees, as they are the lowest paid among the four. It is highly contradictory to
note that lower level employees are also having the highest scorers for the
perceptionon task based functional conflicts. The indication is that the lower
employee group perceives the highest level of good and bad conflicts in the two
sectors. This can be attributed to the reason explained before.
In the private sector, senior employees scored the highest for the
dysfunctional conflicts caused by emotions (3.98, 79.6%) followed by senior
executives (3.96, 79.2%), junior executives (3.87, 77.4%) and lower level
employees (3.51, 70.2%). The fact that the lower level employees scoring the
highest in the public sector, score the lowest in the private sector is ironical. This
may be attributed to the fact that the private sector lower level employees are less
vulnerable to the awareness of emotional dysfunctional conflicts due to the close
supervision that they are subjected to, when compared with those in the public
sector. The prolonged experience of the senior level employees can be the reason
for the highest score for the functional task conflict and dysfunctional emotional
conflicts in the private sector.
216
5.2.5 Perceived Difference on the Interrelationship Between Issue Conflicts
and Emotional Conflicts among the Respondents of the Public Sector
The interrelationship between the constructive/functional/ task conflicts and
destructive/ dysfunctional/ emotional conflicts is relevant as far as the analysis of
the two dimensions of the conflicts are concerned. (Rahim, Bonoma & Brown
1997). In the questionnaire ‘F’, questions 4 is related to this aspect. Table 5.25
shows the frequency distribution of the different categories of the public sector on
the statement that differences in the opinion for tasks can create destructive
emotional and personal feelings. The table shows that about 69.7% of the
respondents agree or almost agree that task or issues can create emotional or
personal feelings. It has already found in the previous findings that emotions are
instrumental for destructive conflicts. The indication is that issue related
constructive conflicts give way to emotional related dysfunctional conflicts.
Table 5.25
Frequency distribution of the different categories of public sector
on the interrelationship between task and emotional conflicts
Category Responses from ‘ strongly agree’ to ‘ not at all agree’
5 4 3 2 1 Nos.
Senior Executives 12 13 6 5 5 41
Junior Executives
6 28 6 5 6 51
Senior Employees
18 61 13 12 9 113
Lower/Junior Employees
6 70 14 6 6 102
Total 42 172 39 28 26 307
Source: Survey Data
217
Table 5.25.1
SPSS output of Krushkal-Wallis test for differnces in frequencies
Ranks
N Mean Rank
1 5 6.38
2 5 6.38
3 5 11.75
4 5 9.50
Total 20
Table 5.25.2
SPSS output of Krushkal-Wallis test for difference in frequencies
N Median Chi-square d.f Asym Sig
20 12.00 2.794
3 0.425
Grouping Variable: CATEGORY(Senior Executives, Junior Executives, Senor
Employees, Lower Level Employees)
The four categories are seemed to be differently distributed in terms of
frequencies. The significance of these differences is tested through Krushkal
Wallis test or non- parametric anova. The SPSS output of the Krushkal Wallis test
is shown in Table 5.25.1 and 5.25.2. The mean rank for the four groups of senior
executives to lower level employees are 6.38, 6.38, 11.75 and 9.50 respectively.
Chi-square test statistic is 2.794 with significance value 0.425 which is higher than
the level of significance 0.05. Hence the conclusion is that there is no significant
difference among the frequencies of the four categories in the public sector
regarding the interrelationship between the issue conflicts and emotional conflicts.
218
5.2.6 Perceived Difference on Interrelationship Between Issue Conflicts And
Emotional Conflicts among The Respondents of The Private Sector
Table 5.26 shows the frequency distribution of the private sector categories
on the interrelationship among four groups in the private sector. The finding
regarding the private sector is almost similar for the private sector. About 70 % of
the respondents in the private sector perceive that the issue conflicts generate
emotional destructive conflicts.
Table 5.26
Frequency distribution of private sector categories for the interrelationship
between task and emotional conflicts
Category Responses 5 4 3 2 1 Nos.
Senior Executives 7 10 5 5 5 32
Junior Executives 20 41 7 6 5 79
Senior Employees 19 37 6 7 5 74
Lower/Junior Employees 5 20 6 5 5 41
Total 51 108 24 23 20 226
Source: Survey Data
Table 5.26.1
SPSS output for Krushkal Wallis test for private sector categories for the interrelationship between task and emotional conflicts
Table 5.26.1(a)
Ranks
CATEGORY N Mean Rank Number 1 5 8.30
2 5 13.00 3 5 12.50 4 5 8.20 Total 20
219
Table 5.26.2
Test Statistics (b)
N Median Chi-square df Asymp Sg.
20 6.00 2.222
3 0.528
Krushkal-Wallis test is administered to identify the difference among the
four groups in the private sector, though each group seems to be different from
other. Table 5.26.1 and 5.26.2 present the SPSS output of the Krushkal Wallis test
for identifying the difference among the categories of the private sector.
The median SPSS output for Krushkal wallis test for private sector categories
on inter relationship between task and emotional conflict is shown as 6 for the
whole distribution. Mean ranks for the four categories are 8.30, 13.00, 12.50, and
8.20 respectively. Chi-square value is 2.222 and the significances value of p is
0.528. Since this value is higher than 0.05 (the level of significance), it can be
concluded that there is no significant difference in the frequency distribution of the
categories of the private sector regarding the perception on the interrelationship
among the four different groups.
5.2.7 Overview of The Discussions And Conclusion
The analysis of the functional and dysfunctional conflicts in accordance with
the perceptions of the public and private sector respondents revealed that there is
no significant difference between the two sectors on the frequency distribution for
the unavoidability of conflicts in organization. More than 60% in each category
either agreed or strongly agreed in favour of the unavoidability of conflicts. No
Significant difference in frequencies are noted between the respondents of the
private and public sectors. However significant difference in frequencies are noted
between the respondents of manufacturing and service categories in both of the
sectors.also in this regard., Again, significant difference in frequencies are noted
between the executives of the two sectors. These differences can be attributed to
220
the structural and demographic factors of the concerned categories. The private
sector is distinctive in the close supervisory style, better flexibility to market needs
and in the HR functions delivered by its executives and employees. The public
sector is characterized by less flexibility towards market needs and limited
programmes for updating its manpower competencies. At the same time the
awareness of environmental change is highly recognized in this sector.
Regarding the perception towards the functional and dysfunctional conflicts,
category differences are noted. The overall mean item score for positive task
conflicts and negative (dysfunctional) emotional conflicts is >60% for all the
categories which shows a favourable and appropriate evaluation on the subject.
Majority of the categories perceive good and bad conflicts characterized by the
medium level of issues and emotions respectively. The items related are also
indicating the same relationship. The contradictory mean scores for different
categories of senior executives, lower level employees etc. can be attributed to the
factors already explained in the previous paras. This can also be attributed to the
demographic and structural context of the two sectors.
The analysis of the perceived difference on the interrelationship between task
and emotional conflicts has also been made. The Krushkal wallis test on the
median of the frequency distribution of the four groups also shows no significant
difference among the four groups in each sector in this regard. This finding can
also be attributed to other findings in the previous paras in which it has been
revealed that conflict behaviour is commonly perceived by the majority of the
respondents regardless of the sectors and categories.
Hence the reality of the unavoidability of conflicts in organizations, and
interrelatedness of functional and dysfunctional conflicts have been revealed
through the analysis. These findings seek straight addressal and intervention, as it
has already been stated. (Eisenhardt, Bour Geouis, 1998). These findings are
instrumental for further analyses remaining in this study.
221
5.3 DEVELOPING A LINEAR MODEL FOR THE
INTERERELATIONSHIP BETWEEN ISSUE CONFLICTS AND
EMOTIONAL CONFLICTS.
In the previous paragraphs, the prevalence of conflicts in general have been
established from the scores of the repondents. Fucntional and dysfunctional
conflicts which are synonymously called as ‘task and emotional conflicts’,
‘constructive and destructive conflicts’ etc. have also been a identified from the
respondents of the two sectors. The questions related to the constructive and
destructive conflicts in the questionnaire ’F’ also indicate the factors that create the
same.
Thus, differences in methods, procedures and ideas are constructive (Item
No.2) as far as the organizations are concerned. Similarly, emotions that are
unlimited are fundamental for dysfunctional conflicts (Item No. 3). Table 5.27
depicts the scores of the item (item No.2) which revealed that differences in ideas,
methods and procedures are the reasons for functional (task/issue/cognitive)
conflicts. Previously all the items concerned with the categories of
functional and dysfunctional were taken in to account computing the mean scores
for each of the conflicts separately. In this computation, the fundamental cause of
each has been taken in to account. Item Nos. 2 and 3 are related to functional and
dysfunctional conflicts respectively.
Table 5.27
Scores of the perception on the statement that difference in ideas and prodedures are the reason for functional conflicts (Item No. 2)
Sector Categories Mean SD percentage
Publ
ic
Sect
or Senior Executives 3.99 1.01 79.8
Junior Executives 3.88 1.01 79.8 Senior Employees 4.2 0.98 84.00 Lower Level Employees 3.89 0.96 77.8
Priv
ate
Sect
or Senior Executives 3.86 1.08 77.2
Junior Executives 3.66 1.05 73.2 Senior Employees 3.72 0.92 74.4 Lower Level Employees 3.95 1.11 79
Source: Survey of data
Scores o
Th
the high
lower le
as alread
conflicts
highest
employe
(1.08) an
senior e
group w
conflicts
0102030405060708090
of the state
he category
hest in the p
evel employ
dy have bee
s. In the ca
score (3.95
ee group (3
nd lower le
employee gr
with, high ex
s in their res
Senior Executives
JuniorExecutives
Pub
3.99 3.8
79.8 7
Scores
ement that
for fun
of senior e
public secto
yees (3.89)
en stated, a
se of privat
5), (79%), f
3.72) follow
evel employ
roup,(S.D=0
xposure to i
spective org
Junior Executives
Senior Employees
blic Sector
8 4.2 3
79.8 84
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Senior Executives
3.89 3.86
77.8 77.2
erence inask confli
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3.66 3.7
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223
Table 5.28 presents the mean item scores of the private and public sector
categories on the item of the fundamental cause for dysfunctional conflicts.
(emotional/ relationship/personal conflicts,( item.no.3)
Table 5.28
Scores of the statement ‘unlimited emotional
conflicts are destructive’(Item.No.3)
Sector Categories Mean SD percentage
Publ
ic S
ecto
r Senior Executives 3.98 0.95 79.6
Junior Executives 3.98 0.95 79.6
Senior Employees 4.01 0.98 80.02
Lower Level Employees 3.99 1.10 79.8
Priv
ate
Sect
or Senior Executives 3.95 1.08 79.2
Junior Executives 3.81 1.05 76.00
Senior Employees 3.98 0.92 79.6
Lower Level Employees 4.00 1.11 80.00
Source: survey data
In the public sector, the highest score for the fact that emotions create
destructive or dysfunctional conflicts, is 4.01 in the category of senior employees
(80.2%) which is the same case with the functional conflicts. This highest score is
followed by lower level employees 3.99 (79.8%), junior and senior executives
(79.6%). Highest consistency is noted in the category of junior and senior
executives with the lowest S.D. of 0.95.
Among the private sector categories, lower level employee group scores are
high (4.00, 80.00%), followed by senior employees (3.98, 79.6%), senior
executives (3.95, 79.2%) and junior executives (3.81, 76%). The most consistent
group is that of senior employees with the lowest S.D. (0.92) followed by junior
executives, senior executives and lower level employees. (1.05, 1.08 and 1.11
respectively). The inferences are the same as that have already been mentioned.
S
Ta
regardin
conflicts
Item m
S
To
Scores on u
able 5.29 ex
ng the fact th
s.
mean Score
conflicts f
Sector
Public Se
Private Se
Source: Surv
otal Nos.= 5
Lowe
Lowe
Public Sector
Private Sector
unlimited e
xhibits the
hat unlimite
es for the s
for organisa
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vey of data
533
Senior Exec
Junior Exec
Senior Emp
er Level Emp
Senior Exec
Junior Exec
Senior Emp
er Level Emp
scores destru
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emotions ca
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Table
tatement ‘u
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an score per
3.54
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4
mited emonflicts(tw
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in the two
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76
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80
ause rs)
224
ectors)
o sectors
structive
uctive
100
.6
.6
.02
.8
2
.6
225
In the public sector, the item mean score is 3.54 ( 70.8%). In the private
sector the item mean score is 3.84 (76.8%). In both of the sectors, the item mean is
above 70% which denoted the authenticity of the perceptional pattern of the two
sectors in this regard.
. The highest score of the lower level employees, in the private sector is a
matter of socio economical interest. This lower level employee group is the lowest
paid among the four categories and are having less bargaining power than others.
Consequently the chances for their vulnerability to conflicts arising out of
emotions might be higher than others in the sector. The senior employee group
having more experience with the dynamics of conflicts on emotions and its
outcomes scored the highest among the public sector categories.
5.3.1 The Frequencey Distribution in the Two Sectors on the Functional and
Dysfunctional Conflicts
Table 5.30 shows the frequency distribution of the responses to items on
functional and dysfunctional conflicts. Row total for each item is 533.
Table 5.30
Frequency Distribution of the responses to items on functional and
dysfunctional conflicts (two sectors) (‘strongly agree’ to ‘strongly disagree’)
Source: survey data
(X2=30.87, X2crirical=9.488, significant at 5% level)
Item 5 4 3 2 1 Total No
Emotion causes dysfunctional conflicts
45 257 56 87 88 533
cognitive difference causes functional conflicts
86 185 47 120 95 533
Total 131 442 103 207 183 1066
Freque
Freq
ency of the
quency on '
Freca'st
120
Freqfunction
responses
‘strongly
'cognitive d
agre
56
87
equency oauses dystrongly ag
47
95
quency onal confl
Figur
to 'Emotio
y agree’ to
Figur
difference c
ee’ to ‘stron
488
of the ressfunctiongree 'to '
on 'cogniticts'('str
disag
re 5.8
n causes dy
‘strongly d
re 5.9
causes func
ngly disagr
45
257
sponses nal confli strongly
86
tive differongly aggree')
ysfunctiona
disagree')
ctional conf
ee’)'
to 'Emoticts'( from disagree
185
erence cagree 'to' s
al conflicts’
flicts'(‘stro
tion m e')
uses strongly
226
’( from
ngly
5
4
3
2
1
5
4
3
2
1
227
X2 test for association of frequencies is administered to identify the
association between the sets of frequencies. Value of X2 is calculated as 30.87,
which is significant at 0.05 level. The inference is that the two sets of frequencies
are related or associated. Variation in one set makes positive variation in the other.
Table 5.31 presents the coefficient of correlation ‘r’ between the scores of
the issues and emotions which cause functional and dysfunctional conflicts based
on questionnaire ‘F’. Value of ‘r’ is 0.51 which is significant at 0.05 level. This
indicates a moderate positive correlation between the functional and dysfunctional
conflicts. Presumably, the correlation between functional and dysfunctional
conflicts is in fact the correlation between the affective and cognitive components (
Gustav and Gigr 1964).
The result shows that the frequencies of the perceptions regarding the
functional and dysfunctional conflicts with the concerned radical causes are
generally associated or related in this study. Incidentally In chapter 4 it has been
found that cognitive and affective components are negatively correlated (r= 0.716).
Though the two findings are entirely different in nature, it is seemingly
contradictory. Previous studies of Simmons & Patterson, (1995 ) state that
cognitive part or the issue/task part is positively correlated to emotional part or
dysfunctional part at the low and high levels. At the moderate rate of task /issue,
the correlation to the emotional part is negative. (Simmons & Patterson, 1995).
Hence the contradiction can be attributed to the curvi linear properties of the
relation between the two components. (Simmons, 1995). However in this study the
association found between the frequencies of perception regarding the functional
and dysfunctional properties of conflicts is seemingly having several other
dimensions. The fact that whether this association bears the relationship between
the affective and cognitive components can be confirmed only after further
analyses.
228
Table 5.31
Correlation matrix for functional (cognitive )and dysfunctional
(affective/emotional) conflicts
Components Column 1 Column 2
Functional conflicts 1 0.51
Dysfunctional conflicts 0.51 1
Source: survey data
Hence it can be concluded that the change of one unit in functional conflicts
results in positive change in dysfunctional conflicts, if it is not managed properly.
This sounds like having serious implications as far as the conflict management
mechanisms of the two sectors are concerned.
The non parametric X2 test of association shows association between the
frequencies of the two. The spearman correlation coefficient also shows a positive
correlation between the functional and dysfunctional conflicts ( at the low and high
levels).
5.3.2 Bivariate Linear Model for Functional Conflicts and Dysfunctional
Conflicts
As it has already been discussed, both functional and dysfunctional conflicts
are positively correlated to each other (r=0.51, at low and high levels). The
indication is that issue or cognitive differences proportionally make changes in the
emotions which in turn create dysfunctional conflicts and negative outcomes.
The linear equation between the two variables, x and y can be written as:
y = a + bx
where, ‘y’ is the dependant variable, ‘x’ is the independent variable, ‘a’ and
‘b’ are constants.
In a regression model, the above equation can be taken as the relation
between an independent variable and a dependent variable. Since the
229
emotional/personal/affectional part is influenced by the issue/task/cognitive part,
the dysfunctional conflicts can be taken as the dependent variable (y) and the
functional conflicts can be taken as independant variable (x).
Based on the survey data, the regression model for the relation between
functional conflicts and dysfunctional conflicts is, given by the summary output of
the analysis in MS Excel as given below.
value of R2 is 0.661 and adjusted R2 = 0.604.
Values of test statistic ’t’ for b and a is 3.423 and -0.525, with the ‘p’ values
of 0.038 and 0.014 respectively. Both are significant since P < 0.05 (level of
significance).
F value for the anova is 11.718 with P value 0.014 which is significant(less
than the level of significance). This indicates that the probability of the value of b,
the regression coefficient becoming zero is rejected and the regression equation is
valid for all the values of X.
Adjusted R2 value indicates that 60.4% of the variance in the independent
variable ‘y’ can be explained by the variance in the value of the dependent variable
X.
The multiple ‘R’ value is 0.813. The regression constant ‘a’, or the ‘y’ intercept is -
0.428 and the value of the regression coefficient b is 0.793. Putting all these in the
above equation, the regression model for functional and dysfunctional conflicts can
be termed as given below.
Y = 0.793X - 0.428
Where,
Y=dysfunctional conflict (intensity/outcome) / dependent variable
X=functional conflicts (intensity/outcome) / independent variable
Since the intesity/outcome/manifestation/behaviour etc. are denoted by the
term conflict (schon, 1996), it can be concluded that each of the above attributes of
dysfunctional conflicts is determined by substracting the regression constant value
0.428 from the 0.793 part of the values of the functional conflict attributes of X, as
230
far as the perceptions of the private and public sector respondents in this research
are concerned. As it has already been stated, this relation is meaningful for the
lower and higher values of X in which case the emotional function is positively
affected by the cognitive/issue function. With the moderate values of X, The
relation can be negative.
5.3.3 DIFFERENTIATING FUNCTIONAL AND DYSFUNCTIONAL
CONFLICTS IN TERMS OF COMPONENTS
The multiple linear equation for attitude model of conflicts presented in
chapter 4 (4.40.1) is ;
Y = 3.0457 + 0.2182X1 - 0.819X2 + 0.0074X3
Where X1, X2, X3 denote the emotional, cognitive and change factors
respectively.
Functional conflicts are characterized by the positive outcomes due to the
cognitive components. Similarly the dysfunctional conflicts are characterized by
the negative outcomes due to the emotional component (Guetzhour and Gyr, 1954,
Rahim, 2001). The destructivity of dysfunctional conflicts and constructivity of
functional conflicts depend upon the intensity of emotional (personal/relationship)
and cognitive (issue/task) factors respectively. (Amazon 1996, Jehn, Neale 1999,
Rahim, 2001).
Conflict handling (management) styles, EQ or EI, the substantive and
relational outcomes and change factors are significant with regard to the significant
relation with the emotional and cognitive factors. These factors are related to
conflict behaviour. Alternatively these factors are significantly correlated to the
conflict behaviour or conflict intensity or outcomes as it has already been stated in
this chapter. The computations are based on the responses to the questions in
questionnaires B,C,D,E and F which include the items related to these variables as
it has already been mentioned. Out of the above mentioned factors, the relationship
of E1 to the cognitive and emotional factors is particularly significant as far as the
multiple linear model for functional and dysfunctional conflicts in the private and
public sectors.
231
Table 5.32 exhibits the inter correlation between E1, emotional factors and
cognitive factors.
Table 5.32
correlation co-efficient ‘r’ between E1, emotional and cognitive factors, in the
public and private sectors
Items
Emotional Intelligence
Emotional Factors
Cognitive Factors
Conflict behaviour
1 2 3
Emotional Intelligence
1
Emotional Factors
-0.65 1
Cognitive Factors
0.73 0.81 1
Conflict behaviour -0.56 0.62 -0.55 1
Source: survey data, Significant at 5% level.
All the values of ‘r’ are significant at 0.05 level. The correlation between E1
and emotional factors is -0.65 which is negative. This denotes that increase in E1
creates low rate of emotional impact. In a conflict situation, high emotional
intelligence rate make low emotional impact which in turn increases the
constuctivity or functional property of the conflicts in organizations. E1 and the
cognitive/issue factors are positively correlated (0.73). The indication is that the
increase in the E1 rate also enhances the cognitive level which is paramount in
creating positive outcomes or substantive outcomes in a conflict situation as it has
been stated. The conflict behaviour factor is also negatively correlated to EI and
cognitive factors and positively related to emotional factors. The indication is that
high value of EI reduces conflict behavior as much as the cognitive factors.
Conflict intensity or behaviour increases with the increase in the emotional level
This indicates that conflict behaviour or intensity decreases with the increase in EI.
Interestingly, the above two observations are identical and collinear with the
232
varying nature of correlation between the cognitive factors and emotional factors
which is highly contextual (Simmons. 1995).
5.3.4 Developing A Model of Functional and Dysfunctional Conflicts
In the attitude model of conflicts explained in the previous chapter, the
conflict outcomes or intensity is synonymously represented as conflict behavior.
The relation between the conflict outcome, and other components of attitude model
such as cognitive, change and emotional have been found to be linear and
formulated as;
Y = 3.0457+0.0218X1 – 0.0819X2 + 0.0074X3.
where X1, X2, X3 are the emotional, cognitive and change factors
respectively.
With this equation, the model of functional and dysfunctional conflicts
which is interchangeably expressed as constructive and destructive conflicts, is
developed based on the responses regarding the items in questionnaire ‘F’.
In addition to the factors of emotional, cognitive and change, the factor of
emotional intelligence is also incorporated in accordance with the analyses and
observations made in this chapter itself related to the role of E1 in moderating
conflicts in organisaitons. Multiple linear regression model is applied to establish
the relationship between the components of the functional and dysfuntional model
of conflicts.
As it has already been stated in the previous chapters, the emotional
component is contributing positively for accelerating the magnitude of the conflict
behavior of the concerned. Simultaneously cognitive component acts as the
negative modulating factor as far as the magnitude, and the dysfunctionality of the
conflicts are concerned.
5.3.5 Functional / Dysfunctional Model of Conflicts for the Public Sector
For the development of the model, responses from the public sector
regarding the cognitive, emotional, change factor, conflict behavior and E1 factor
in the respective questionnaires mentioned previously have been analyzed and
processed using the multiple linear regression model.
233
The summary output is given in the tables 5.33 and 5.33.1
Table 5.33
Multiple regression model for Functional / Dysfunctional conflicts in the
Public sector
SUMMARY OUTPUT
Regression Statistics
Multiple R 0.89048
R Square 0.79295
Adjusted R Square 0.79021
Standard E 132.54
Observation 307
Table 5.33.1
Regression Coefficients
Coefficients t stat P-value
Intercept 2.3018 0.3991 0.0400
X Variable1 0.0488 0.0205 0.0316
X Variable2 -0.8990 0.667 0.0172
X Variable3 0.0422 0.0427 0.0359
X Variable4 -0.0296 0.0264 0.0359
Level of significance 0.05
Calculated F value is 8.915
Table value of F is 3.32 at (4,302) d.f.
Adjusted R2 is 0.79 which indicates that 79% of the variance in the Y
component that is the magnitude of the functional/dysfunctional conflict in this
model, is explained by the independent variables, X1, X2, X3 and X4 where,
X1 is the emotional component
X2 is the cognitive component
234
X3 is the change factor
X4 is the E1 factor.
Analysis of variance (ANONA) provides the ‘F’ value as 8.915 which is
higher than the critical value of ‘F’ at (3,302) d.f., which is 3.32. The indication is
that that regression coefficients b1,b2,b3 # O. hence the regression equation is valid.
Moreover the ‘t’ statistic for all the variables are significant since
concerned p value is less than 0.05 (Significance level). The regression equation
for functional/dysfunctional conflict for the public sector can be formulated as
follows.
Y = 2.3018+0.0488 X1 – 0.8990 X2 + 0.0422X3 – 0.0296X4.
It is interesting to note that the cognitive component and E1 factor have
negative impact on Y, which is the magnitude of conflict behavior. This equation is
valid in any type of conflicts such as interpersonal, intrapersonal, intergroup and
intragroup.
In other words, the conflict intensity itself is manifested through the
magnitude of conflict behaviour (Rentkesh, 1973, Rahim, 1994). Obviously the
above equation emphasizes that the emotional component along with the change
factor positively escalate the magnitude of conflicts. The escalation of conflict
magnitude is instrumental for dysfunctionality or destructivity of conflicts of any
category. Inerestingly, it is evident from the above formulation that while the
cognitive component and E1 component altogether are the promoters of
constructivity or functionality of conflicts, emotional component and change factor
are accounted for the destructivity or dysfunctionality of conflicts in the public
sector.
5.3.6 Functional/Dysfunctional Model of Conflicts for the Private Sector
The response to the above mentioned components of attitude of conflicts
from the private sector have been analysed through multiple linear regression.
Tables 5.34, 5.34.1 and 5.34.2exhibit the summary out put of the regression
analysis.
235
Table 5.34
Regression analysis for functional conflicts in private sector organizations
SUMMARY OUTPUT
Regression Statistics
Multiple R 0.7090
R Square 0.5027
Adjusted R square 0.4937
Standard E 0.9892
Observation 226
Table 5.34.1
Anova Out Put
df SS MS Significance F
Significance F
Regression 4 218.6812 54.6703 55.86938 0.0323
Residual 221 21.2568 0.978538
Total 225 439.9381
Table 5.34.2
Regression Coefficients
Coefficient t stat P-value
Intercept 6.4338 6.06356 0.0412
X Variable1 0.0742 1.087094 0.0321
X Variable2 -0.0267 -0.3745 0.0083
X Variable3 0.0245 -1.96818 0.0409
X Variable4 -0.0348 12.89234 0.0491
( 0.05 level)
Multiple R is 0.70 and adjusted Rsquare is 0.49, which indicates that 49
percent of the variance of dependent variable is explained by the change in the
independent variables.
The ANOVA table provides the F value 55.86 which is higher than the
table value of ‘F’ 3.32 at d.f. (4,221).
Hence regression coefficients b1,b2,b3,b4 #O for X1, X2, X3 and X4 etc.
making it a valid formulation.
236
The p values are <0.05 (level of significance)
The regression equation for functional and dysfunctional conflicts in the
private sector can be expressed as follows.
Y = 6.4338+0.0742X1 – 0.0267X2 + 0.0245X3 – 0.0348X4
Y = Magnitude/intensity of functional/dysfunctional conflict behavior or
conflicts.
X1 = Emotional component
X2 = Cognitive component
X3= Change component
X4 = EI component
The pattern of the above relationship is almost following the model for the
public sector. Significant difference is noted for the values of the y intercept ‘a’
and the regression coefficients b1,b2,b3 etc.
5.3.7 Functional/Dysfunctional Conflict Model for Public Sector Executives.
Table 5.35, 5.35.1., and 5.35.2 exhibit the summary output.
Table 5.35
Regression analysis for functional conflicts among
public sector executives
SUMMARY OUTPUT
Regression Statistics
Multiple R 0.540301
R Square 0.291926
Adjusted R Square 0.281032
Standard E 0.254445
Observation 307
237
Table 5.35.1
Anova Output
df SS MS Significance F
Significance F
Regression 4 168.6823 42.17058 4.79 0.0412
Residual 302 409.1441 1.573631
Total 306 577.8264
Table 5.35.2
Regression Coefficients
Coefficients t stat P-value
Intercept 1.2697 1.832619 0.008003
X Variable1 0.6439 6.740012 0.02010
X Variable2 -0.1610 2.826814 0.005067
X Variable3 0.1801 7.266793 0.0212
X Variable4 -0.3773 -5.95725 0.06151
( 0.05 level)
Multiple R and adjusted R2 values for the public sector executives are 0.54
and 0.28 respectively.
F value of 4.79 is significant at 0.05 level ;{table value is 3.32 at (4,149)}.
This satisfies the optimum level for the validity of a linear regression model. The
‘t’ statistics is significant (p< 0.05) and significant F value shows that all the values
of the regression coefficients are #0. Hence the regression equation exists.
The model of the functional/dysfunctional conflicts for the private sector
executives can be formulated as follows.
Y = 1.2697 + 0.6439X1 – 0.1610 X2 + 0.1801X3 – 0.3773X4
El factor (X4) and cognitive factor (X3) hold the negative sign. Obviously
these two variables are negative moderators of conflict behavior or outcomes.
238
5.3.8. Functional/Dysfunctional Conflict Model for Public Sector
Employees
Table 5.36
Functional conflict analysis among public sector employees
df SS MS Significance F
Significance F
Regression 4 21.89107 5.472768 8.98103 0.0041
Residual 210 67.03067 0.609937
Total 214 88.92174
Table 5.36, 5.36.1 and 5.36.2 show the summary output of the multiple
regression analysis of the responses of public sector employees. This category
comprises both lower and senior level employees.
SUMMARY OUTPUT
Table 5.36.1
Anova Out Put
Regression Statistics
Multiple R 0.616
R Square 0.379
Adjusted R Square 0.218
Standard E 0.780
Observation 215
ANOVA
Table 5.36.2
Regression Coefficients
Coefficients t stat P-value
Intercept 1.6450 2.6578 0.0090
X Variable1 0.0494 0.9027 0.0386
X Variable2 -0.0356 1.4225 0.0477
X Variable3 0.3003 5.3992 0.0214
X Variable4 -0.1642 -3.3014 0.0012
( 0.05 level)
239
Multiple R is 0.616 and adjusted R2 is 0.218. The indication is that 21% of
the Y variance is explained by the independent variable X. F value of 8.9810 is
significant (table value 3.48) at 0.05 level. Hence the values are not equal to zero,
indicating the validity of the equation. All the P values for the interpet and X
variables are <0.05. Hence, b # O, assuming the significance of the ‘t’ statistic. The
functional/dysfunctional conflict model for the public sector employee category is
as follows.
Y = 1.6450+0.0494 X1 – 0.0356X2 + 0.3003X3 – 0.1642X4.
In this model also E1 and cognitive factors are holding negative sign.
5.3.9 Functional / Dysfunctional Conflict Model for Private Sector
Executives
The summary outputs of the regression analysis are shown in tables 5.37,
5.37.1 and 5.37.2
Table 5.37.
Regression analysis for functional conflicts among private sector Executives
SUMMARY OUTPUT
Regression Statistics
Multiple R 0.5987
R Square 0.3584
Adjusted R Square 0.2198
Standard E 0.2118
Observation 111
Table 5.37.1
Anova Out Put
df SS MS Significance F
Significance F
Regression 4 50.55746 12.63937 8.606825 0.0216
Residual 106 152.7269 1.468528
Total 110 203.2844
240
Table 5.37.2
Regression Coefficients
Coefficients t-Stat P-value
Intercept 0.2632 0.1827 0.0053
X Variable1 0.0913 1.2132 0.0277
X Variable2 -0.3494 2.3217 0.0221
X Variable3 0.2537 -3.1708 0.0019
X Variable4 -0.3569 3.8183 0.0002
(0.05 level)
Multiple R is 0.598 and adjusted R2 is 0.219 indicating 21% of the Y
variance can be explained by the independent variable X. ANONA table indicates
significant F value of 8.60 (table value 3.48). The indication is that b # O assuring
the validity of the proposed model. P values for the ‘t’ statistic are the less than the
significance level (p< 0.05). Hence the t values are significant. The model of
functional/dysfunctional conflict model can be summarized as follows.
Y = 0.2632+0.0913 X1 – 0.3494 X2 + 0.2537X3 – 0.3569 X4.
The model differs in magnitude for the â values of the independent variable
X. Qualitatively private sector executives are having the similar pattern of conflict
model to that of the public sector executives.
5.3.10 Functional/Dysfunctional Model for Private Sector Employees
Tables 5.38, 5.38.1 and 5.38.2 shows the summary output of the multiple
regression analysis of the responses of private sector employees.
Table 5.38
Regression analysis for functional conflicts among private sector Employees SUMMARY OUTPUT
Regression Statistics
Multiple R 0.54480
R Square 0.29681
Adjusted R square 0.27780
Standard E 0.26484
Observation 115
241
Table 5.38.1
Anova Out Put
ANOVA
df SS MS Significance F
Significance F
Regression 4 99.94291 24.98573 15.61766 0.0229
Residual 110 236.776 1.599838
Total 114 336.719
Table 5.38.2
Regression Coefficients
Coefficients. t stat P-value
Intercept 1.2982 1.4313 0.0883
X Variable1 0.6502 5.1082 0.0613
X Variable2 0.1585 2.1347 0.0344
X Variable3 0.1803 5.5668 0.0126
X Variable4 -0.385 -4.5642 0.0392
(0.05 level)
Multiple R and adjusted R2 values are 0.5448 and 0.2778 respectively.
Hence almost 27 percentage of the variance of the dependable is explained by the
independent variables X. F value obtained from analysis of variance (15.61) is
significant (table value 3.32). The inference is that regression coefficients are not
equal to zero. Hence X values exist. Values of ‘t’ stastistic are significant (P<
0.05). A significant difference for this model from that the previous category
models is the positive sign of the cognitive component (X2). This can be due to the
state of beyond optimum level of the cognitive component apart from which it
generates emotions. These emotions can moderate conflicts ( Simmons 1995).The
conflict model (functional/dysfunctional) for private sector employees can be
formulated as follows.
Y =1.2982+0.6502X1 + 0.1585X2 + 0.1803 X3 – 0.385X4.
242
Only the E1 factor is the negative accelerator of destructive conflicts in this
category as explained earlier.
5.4. RELATIONSHIP BETWEEN INTRAPERSONAL CONFLICTS AND
COMPONENTS OF FRUSTRATION AND ROLE CONFLICT
The dysfunctional properties associated with frustration and role conflict
are critical and relevant as far as the conflicts in the two sectors are concerned.
Questionnaire ‘G’ includes items related to interpersonal conflicts
generated through the components of intrapersonal conflicts such as frustration and
role conflicts. Items 1 to 7 are related to intrapersonal conflicts. Out of these items
1 to 3 are related to frustration and 4 to7 are related to role conflicts. Items 8 to 10
are related to interpersonal conflicts. Items 11 to14 are related to group conflicts.
Items no. 15 is related to the interrelation between intrapersonal conflicts and
interpersonal conflicts. Item no.16 represents the link between interpersonal and
group conflicts.
Mean scores of each variable are computed for the correlation between the
variables.
Tables 5.39 5.39.1, 5.39.2, 5.39.3 exhibit the Spearman correlation
coefficient ‘r’ between the variables of intrapersonal conflicts, frustration and role
conflicts.
Table 5.39
Correlation between intrapersonal conflicts, frustration and role conflict
Variable Intra
personal conflicts
Frustration role
conflicts
Intra personal conflicts
1
Frustration 0.61 1
Role Conflicts
0.41 0.29 1
Source: Survey data
Significant at 0.05 level
243
Frustration and role conflicts are postively correlated to intrapersonal
conflicts. Frustraton is more strongly and significantly correlated to intrapersonal
conflicts with the ‘r’ value 0.61 than that of role conflicts (r = 0.41).The indication
is that when the two sectors are taken together, intrapersonal conflicts within the
individuals are mainly generated by frustration followed by role conflicts. This
factor can be attributed to ‘attitudinal difference’ as it has been revealed by the
analyses made in the previous chapter. The frustration factor might be generating
from work family conflicts and structural factors.(Beena c. et al,2004). The so
called latent or hidden inner psyche of Keralites with the behaviour of
hopelessness, and worthlessness which is evident from the high rate of suicide
(Table 7a, Appendix 2) and alcohol consumption in the state might also have
contributed to the frustration factor. Multiple regression model for analyzing the
relationship between intrapersonal conflicts and its components is shown in the
tables 5.39.1 and 5.39.2
Table 5.39.1
Regression analysis showing relationship between intrapersonal
conflicts and the components of frustration and role conflict
SUMMARY OUTPUT
Regression Statistics
Multiple R 0.717
R Square 0.5145
Adjusted R Square 0.501
Standard E 20.835
Observation 533
Table 5.39.2
Anova Output
df SS MS F Significance F
Regression 7 7878 3939.007 0.0735 0.0001
Residual 525 216626.546 434.1213
Total 532 224504.56
244
Table 5.39.3
Regression Coefficients
Coefficients t stat P-value
Intercept 2.2239 0.2367 0.04521
X Variable1 0.6988 4.2338 0.01548
X Variable2 0.223 -0.067 0.01215
( 0.05 level)
X1 = Frustration
X2 = Role conflicts
Adjusted R2 is 0.501 which indicates that 50 % of the variance in the
dependent variable is explained by the independent variables X1 and X2. F value is
0.0735. The value of F is significant since the significance value is lower than the
level of significance. value 0.05. Hence the values of the regression coefficients are
not equal to zero and the equation exists.
The regression coefficients are 0.6988 and 0.2230 respectively which are
significant since the p values are lower than the level of significance (0.05).
Hence the regression equation can be written as,
Y= 2.2239+0.6988X1+0.2230X2.
Where,
Y= intrapersonal conflict behaviour / intensity
X1= Frustration
X2=Role conflicts
5.5 Inter Relationship between Intrapersonal Conflicts and Interpersonal
Conflicts
In the previous unit, the correlation between frustration, role conflict and
intrapersonal conflicts have been computed and analysed. As it has been stated in
the beginning of this chapter, items 1to 7 and 8 to 10 of questionnaire ‘G’ denote
interpersonal and intrapersonal conflicts. the scores for these variables have been
computed for analysis in this unit. The regression equation for the relationship has
245
also been formulated.The relationship between the intrapersonal conflicts and
interpersonal conflicts is also an important part of the objectives of this study.
5.5.1 HYPOTHESIS 5.2
H1: Significant relationship between intrapersonal conflicts and
interpersonal conflicts
. The correlation matrix is shown in the table 5.40
Table 5.40
Correlation matrix for intrapersonal conflicts and interpersonal
conflicts
Column 1 Column 2
Intrapersonal conflicts 1 0.75
Interpersonal conflicts 0.75 1
Source: Survey data,Significant at 5% level.
Table 5.41
Frequency distribution of the perception of the two sectors on the statement
that intrapersonal conflicts cause interpersonal conflicts and group conflicts
(item no.15 of ‘G’)
Item
Strongly Agree
Almost Agree
Sometimes Agee
Rarely Agree
Strongly Disagree Total
Intrapersonal conflicts cause interpersonal conflicts
120 (22.51)
169 (31.70.)
93 (17.44)
97 (18..19)
54 (10.13)
533
Source: Survey data
Figures in parenthesis denote percentage
The value of r is 0.75 which is significant at 5% level. The table shows that
there is strong and significant positive correlation between intrapersonal conflicts
and interpersonal conflicts. The indication is that intensity of interpersonal
conflicts
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246
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247
5.5.2 Bivariate Linear Regression Model for the Relationship between
Intrapersonal and Interpersonal Conflicts
SUMMARY OUTPUT
Table 5.42
Regression analysis showing relationship between intrapersonal
conflicts and the components of frustration and role conflict
Regression Statistics
Adjusted R Square 0.533
Standard E 24.835
Observation 533
Table 5.42.1
Regression Coefficients
Coefficients t stat P-value
Intercept 1.5226 0.1397 0.0411
X Variable1 0.3572 3.1327 0.0321
X1 = Intrapersonal conflicts
5% level
Table 5.42, 5.42.1 exhibit the summary output of the multiple linear
regression analysis. Adjusted R2 is 0.533. The indication is that almost 53% of the
variance in the dependent ‘Y’ variable is explained by the independent ‘X’
variable. Anova output shows ‘F’ value of 5.07 is significant table value (0.0021)
ascertaining that regression coefficient b#0. Hence the equation exists. The ‘t’
statistic is significant at 0.05 level, since (P < 0.05).
The regression equation can be stated as follows.
Y = 1.5226 +0.3572X1
Where Y is the interpersonal conflict behaviour/ intensity,
X1 is intrapersonal conflicts .
248
The relation clearly indicates the positive contribution of intrapersonal
conflicts in escalating interpersonal conflicts. In fact the constituents of
intrapersonal conflicts such as frustration and role conflicts play the role of
escalating interpersonal conflicts as it has been revealed by the analysis. Private
and public sectors altogether have been taken for the above analysis for the
formulation of the above model.
5.6 INTER RELATIONSHIP BETWEEN INTERPERSONAL
CONFLICTS AND GROUP CONFLICTS
The matter of interest of this study comprises the whole dynamic process of
the conflict chart. Conflicts in organizations are distinctive in their origin and
development. In the previous unit, the contribution of intrapersonal conflicts to the
origin of interpersonal conflicts has been modeled and formulated as far as the
public and private sectors are concerned. In this unit the interreltioship between
interpersonal conflicts and group conflicts is analysed and modeled. For the
analysis the responses to items from11 to 14 which denote group conflicts have
been computed.
5.6.1 HYPOTHESIS 5.3
H1 : Significant relationship between group conflicts and interpersonal conflicts
in the public and private sectors
Table 5.43 shows the correlation matrix between the two.
Table 5.43
Correlation matrix for interpersonal conflicts and group conflicts
Column 1 Column 2
Group conflicts
1
0.80
Interpersonal conflicts 0.80 1
Significant at 0.05 level of significance.
It is evident from the above table that the correlation between interpersonal
conflicts and group conflicts is significantly positive and strong (r= 0.80,
249
significant at 5% level). Change in one factor makes positive change in the other.
The high value of r shows the strong positive influence of one factor on the other.
Hence the null hypothesis is rejected stating that there is significant positive
correlation between group conflicts and interpersonal conflicts in the public and
private sectors of Kerala. This finding is significant on the fact that several strikes
and lock outs in the public and private sector units in Kerala were derived out of
simple issues of personal clashes. Eventually these factors are transformed into
group rivalries and ended in bitter conflicts followed by violent incidents, strikes
and lockouts.
5.6.2 Bivariate Linear Regression Model for The Relation
between Group Conflicts and Interpersonal Conflicts
Responses to item no. 16 of the questionnaire ‘G’ concerning the relation of
group conflicts (both intra and intergroup) with interpersonal conflicts has been put
into multiple linear regression for formulating the valid relationship. The causative
relationship between the two is determined from the responses to the same item.
Since the group conflicts are formed in continuation of interpersonal conflicts, the
former and the later can be considered as the dependent and independent variables
respectively.
Table 5.44 shows the frequency distribution of the responses on this item,
when two sectors are taken together.
Table 5.44
Frequency distribution of the perception of the two sectors on the statement that interpersonal conflicts cause group conflicts( item no.16 of ‘G’) Category Strongly
Agree Almost Agree
Sometimes Agree
Rarely Agree
Strongly Disagree Total
Public and private sectors
125 (23.45)
164 (30.76.)
98 (18.38)
92 (17.26)
54 (10.13)
533
Source : survey data
Figures in parentheses denote percentages
It is evident from the above table that 72.60% (nos.387) of the respondents
are more or less agreeing to the statement that interpersonal conflicts cause group
250
conflicts in the two sectors. The indication is that group conflict is the dependent
variable as it is the result of interpersonal conflicts. The bivariate linear regression
model is formulated accordingly.
Tables 5.45,5.45.1and 5.45.2 show the details of the regression analysis
.Table 5.45
Regression analysis for inter personal and group conflicts
SUMMARY OUTPUT
Regression Statistics
R Square 0.641
Adjusted R square 0.604
Standard E 5.697
Observation 533
Table 5.45.1
ANOVA
df SS MS F Significance F
gression 1 32.64242 32.64242 1.0055 0.0244
Residual 531 16230.94 32.46189
Total 532 16263.59
Table 5.45.2
Regression Coefficients
Significant at 0.05 level of significance
X1 = interpersonal conflicts
Adjusted R2 value explains 60% of variance in the dependent variable ‘y’.
Coefficients t Stat P-value
Intercept 5.1976 36.273 0.0322
X Variable1 0.0893 1.0027 0.0164
251
Both F values and t statistic are significant.
(b#0,p<0.05)
The regression equation can be termed as follows.
Y = 5.1976 + 0.0893 X1
Where,
Y denotes group conflicts.
X1 denotes interpersonal conflicts.
The inference drawn from the above relation is that interpersonal conflicts
lead to group conflicts (both intra and intergroup) in the private and public sectors
in Kerala. This inference is relevant especially due to the previous conclusion
about subjective emotional contribution to the dysfunctionality of conflicts.
Subjective or individual emotional contribution is exerted through the variables of
frustration and role conflicts. Dysfunctionality is more or less a group consequence
so far as the organization is concerned.
In the previous unit, it has been established that intrapersonal conflicts cause
interpersonal conflicts. In this unit it has been established that interpersonal
conflicts cause group conflicts. The logical implication of these findings is that
intrapersonal conflicts often cause group conflicts. Item no.16 of questionnaire ’G’
states that interpersonal conflicts often ends in group conflicts. Frequency
distribution of the responses to this item is shown in the table 5.44 which has
already been analysed. Majority of the respondents(>70%) in the two sectors
perceive that intrapersonal conflicts are instrumental for interpersonal as well as
group conflicts. Hence the logical conclusion of the analysis is that intrapersonal
conflicts comprised of individual frustration and role conflicts can be accounted for
interpersonal and group conflicts in the public and private sector organizations in
Kerala (item no. 15). This conclusion absolutely coincides with the major finding
of this research that ‘attitudinal difference’ is the most crucial and decisive
potential source of conflicts in the two sectors. This conclusion is exclusively
significant since individual attitude is inseperably and obviously related to the
variables of frustration and role conflicts.
252
5.7 OVERVIEW OF CONCLUSIONS AND DISCUSSIONS.
In this chapter, different dimensions of functional and dysfunctional
conflicts and the inter relationship between the two have been analysed and
illustrated. Different combinations of conflict management styles have also been
put into analysis and findings have been established. Consequently, different
models for the functional/dysfunctional conflicts have been formulated. In all of
the above occasions, the private sector and the public sector were subjected to
analysis collectively and separately with regard to the indications of the previous
observations. Generally, the peculiar features of E1 functions, conflict handling
styles, and vulnerability to E1 and change factors can be attributed to the peculiar
features of each sector. The notable features of flexibility, adaptability, and
structural balance and imbalance of the features of the private sector are
alsocontributing to these observations. Similarly, varying mode of structural
indifferences, apathy for adaption to change, transparency in social commitment
and structural flexibility are the peculiar features of the public sector which are
instrumental for the findings related to it. Variations in the dimensions of the above
mentioned factors among the categories of each sector are also influencing the
observations revealed in the analyses. Relation between the attitudinal components
and EI, differentiation between functional and dysfunctional conflicts,
interrelationship between interpersonal, intrapersonal and group conflicts etc. can
be attributed to the peculiar structural features of each sector mentioned above.
However, further conclusion in detail in this regard will be made in the coming
chapters.
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