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

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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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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

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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

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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

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ree’. This i

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818 at 0.05

ce between

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Not at all agree

208

n ' 

210

g to the

ributions

‘almost

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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

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f public an

01020304050

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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

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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

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Senior Executives

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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

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able 5.29 ex

ng the fact th

s.

mean Score

conflicts f

Sector

Public Se

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otal Nos.= 5

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Private Sector

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vey of data

533

Senior Exec

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224

ectors)

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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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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.