Social Loafing | Conflict Management

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Article 2: Review of the article.

The model uses two independent variables. They are “Communication” and “Structural”. These two independent variables explain functional and dysfunctional conflict. The communication variables are communication frequency, bidirectionality and communication quality. These variables are derived from the interaction approach. The structural variables are formalisation and centralisation. These variables are derived from theory of bureaucracy. The dependent variables are functional and dysfunctional conflict.

The hypotheses of the authors were:

- H1a: Higher communication frequency will lead to higher dysfunctional interpersonal conflict.

H1b: Higher communication frequency will lead to lower functional interpersonal conflict.

- H2a: Higher bidirectional communication will lead to lower dysfunctional interpersonal conflict.

H2b: Higher bidirectional communication will lead to higher functional interpersonal conflict.

- H3a: Higher communication quality will lead to lower dysfunctional interpersonal conflict.

H3b: Higher communication quality will lead to higher functional interpersonal conflict.

- H4a: As centralisation increases, dysfunctional interpersonal conflict will increase.

H4b: As centralisation increases, functional interpersonal conflict will decrease.

- H5a: As formalisation increases, dysfunctional interpersonal conflict will decrease.

H5b: As formalisation increases, functional interpersonal conflict will increase.

Data for the research was collected through a questionnaire. A total of 103 answered questionnaires were used for the research. After collection of data the confirmatory factor analysis was conducted (CFA). The CFAs were conducted in three stages. Stage one included the two reflective communication dimensions (bidirectional communication and communication frequency). Stage two included the two structural/bureaucratic dimensions (centralisation and formalisation), whilst stage three included the two conflict dimensions (dysfunctional and functional conflict).

The results showed that marketing managers enjoyed a good relationship with their counterpart Sales managers. The result also indicated that dysfunctional conflict is low. Moderate number of functional conflict is observed. When the model was tested using OLS regression it showed that 4 out of 5 hypotheses were supported. As seen in the table all of the communication behaviours i.e. communication frequency, bidirectionality and communication quality have a significant effect on dysfunctional conflict. Two communication variables have negative effect. Bidirectional communication has the strongest negative effect followed by communication quality. One variable i.e. communication frequency has a positive effect.[pic 4]

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For structural variables, only formalisation decreases dysfunctional conflict. Beta for centralisation was positive as predicted, but non-significant.

As far as functional conflict was concerned only one hypothesis was not supported.

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The result showed that communication quality has the highest positive effect followed by bidirectionality. One variable i.e. communication frequency had a negative effect. Similar to the result of dysfunctional conflict, of the two structural variables, only formalisation was significantly related to functional conflict, whilst centralisation was non-significant.

To sum it up the authors used five independent variables to explain two conflicts i.e. functional and dysfunctional. Of the five variables used in the model the 3 communication variables (communication frequency, bidirectionality and communication quality) were significant and one structural variable (formalisation) was significant in both functional and dysfunctional conflict. An interesting point can be noted that communication frequency is positively associated with dysfunctional conflict, but negatively associated with functional conflict. This means that low frequency communication may be functional, but at high frequencies it may become dysfunctional. We can understand this by considering an example, if two managers from different manager interact the value of information shared is not always high because they have different deliverables. Where as an interaction between a manager and his subordinates are valuable. Therefore a high frequency of this interaction is productive. However on the other hand if there is high frequency communication between two managers it will lead to dysfunctional conflict because this is considered to be “badgering”.

As far as communication quality is concerned, high quality communication leads functional conflict. Conversely, where communication is poor in quality, this is likely to frustrate peer managers, and lead to conflict with those managers providing poor quality information. This is shown in the above table; communication quality has positive effect on functional conflict, and the second strongest negative effect on dysfunctional conflict.

Under bidirectionality, the research shows that high bidirectionality leads to functional conflict and low bidirectionality leads to dysfunctional conflict.

Finally we analyse the two structural variables. We already know that only formalisation has significance.

The limitation of this research is the data is collected based on marketing managers’ perception. It is important to collect data of both sales managers and marketing managers. For further research we can also include the perception of subordinates about marketing managers and sales managers must be collect because someone outside the situation can judge with a different but important perspective.