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Simulating the Emergence of Task Rotation ( S- Q+ L+ v; b% s
Journal of Artificial Societies and Social Simulation vol. 9, no. 1
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work groups(工作组), task rotation(工作轮换),multi agent simulation(多Agent仿真),emerge(涌现),task performance(任务绩效)。* j2 @, E- z A
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Conclusions and Discussion Conclusions 5.1
$ H6 v' s! U3 Z* o9 s$ X& k, RWith regard to self-organisation, we conclude that the influence of self-organisation on expertise and performance shows that in the situations where task rotation emerged, the system delivered a better performance than in case of no self-organisation. This finding suggests that, when performing a task, workers must have the freedom to rotate tasks whenever they feel bored. As regards boredom/recovery, we have arrived at two conclusions: First, if the boredom/recovery rate decreases, it takes more cycles before the agents start to rotate tasks. Consequently, it takes more time before they develop a second skill. If the boredom/recovery rate drops beneath a certain point, the agents will specialise in only one skill, because the time it takes to decrease the motivation enough to rotate tasks exceeds the time that it takes to forget the second best skill. Second, if the boredom/recovery rate decreases, at a certain point the motivational processes become slower than the expertise processes. This implies that, with respect to a particular skill, at the time the agents are bored, the level of their expertise has become quite high. This results in a situation in which the agents only rotate tasks when their level of motivation is very low and rotate back before they have fully recovered. As regards the task rotation frequency, we conclude that with respect to expertise, the decrease in the rotation frequency has the same effect as the decrease in boredom/recovery. We found no significant effects of the interacton of self-organisation and boredom or boredom and task rotation frequency, except in the situation with a low degree of boredom: This situation is 'close to the edge', which means that in the setting with a high task rotation frequency, which we used to manipulate by adjusting the boredom/recovery rate, the agents still rotated tasks. But as soon as we lowered the boredom/recovery rate from 29 to 28, the edge was crossed and task rotation did no longer emerge. The same happens if we lower the task rotation frequency. In the other situation, a frequency of once every 78 cycles still led to task rotation. However, in this particular setting the process of task rotation did no longer occur at a frequency lower than 1/25. Therefore, if an organisation or a work group needs workers that are capable of using multiple skills, for instance to create flexibility, the components described in this study should be taken into account. A low task rotation frequency and a task that is interesting (low level of boredom) more easily lead to the specialisation in one particular skill than a boring task or a high task rotation frequency does.
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In the present study we used expertise and motivation as components that determine group performance. These components can be considered as elements within a broad range of factors that affect team performance, such as work-related attitudes, team composition, commitment, and team cohesion (e.g. Cohen, Ledford & Spreitzer 1996). Although motivation and expertise are important components that affect performance (Wilke et al. 1994), it is obvious that they do not cover all the other factors. Moreover, we supposed that processes, such as getting bored, were solely influenced by the repetitiveness of tasks, whereas it is likely that several other factors might cause boredom, such as for example, the physical condition of an agent. Factors that we consider to be fruitful extensions of our model are, for example, coordination costs (e.g. Cohen et al., 1996), task interdependence (Van der Vegt & Van de Vliert 2005) team size and team composition (e.g. Molleman 2005). Regarding coordination costs, prior tests have indicated that simulation experiments could only produce plausible outcomes if the interactions among agents led to the emergence of rotation rules and routines that decrease coordination costs (see Zoethout et al. in press). Task interdependence might seriously affect the possibilities to divide tasks among agents, and the composition of teams in terms of team size, the distribution of skills, demographic characteristics and personality traits has proven to influence team functioning (Molleman 2005). Inclusion of such factors will bring our model more close to reality, but will also make the results much more difficult to interpret. % |) b0 S5 Z- a- k' k: I7 u3 B1 O
5.3
7 L3 R) M+ y( Q& n, o8 T' e3 hSeveral studies have elucidated the benefits of job rotation within teams (e.g., Van den Beukel 2003). These studies have led to a so-called design-based view on organisations, i.e., since job rotation has proven to bring forth advantages, management should implement it. As a consequence, job rotation has been implemented by management in various settings, even in work designs that are considered as self-managing teams. This may raise the question whether job rotation that is designed for and implemented in a system by an external party has the same effect as job rotation that has spontaneously emerged from the part of the workers themselves. Of course, the discussion about designing job rotation externally versus spontaneous development within the organisation itself involves a lot more issues than dealt with in the present study. Nevertheless, our use of computer simulation has made it possible to start comparing both approaches. We therefore conclude that simulation studies of this kind contribute to the understanding and analysis of the social dynamics of work groups.
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