decision assignment
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2019 ◽  
Vol 123 (3) ◽  
pp. 844-871
Author(s):  
Jeffrey A. Miles

The present study replicated and extended research on the influence of team assignment methods on task performance and fairness perceptions. This study examined the influence of team assignment methods, goal commitment, and partner status on team member performance and fairness perceptions in a laboratory setting. The assignment conditions were comprised of three variables: assignment method (random, self-decision, and ability), performer status (assigned or unassigned), and partner status (unassigned team member stayed or left during task performance). A significant interaction was found between assignment method and performer status when the unassigned team member left during task performance, but not when the unassigned team member stayed. Random and self-decision assignment methods resulted in higher levels of goal commitment and task performance than did ability-based assignment conditions. Lastly, goal commitment was found to mediate the relationship between assignment method and task performance. The implications of these findings for the task performance and organizational justice literatures, as well as for managers in general, are discussed.


1993 ◽  
Vol 22 (438) ◽  
Author(s):  
Gudmund Skovbjerg Frandsen ◽  
Peter Bro Miltersen ◽  
Sven Skyum

Let <em>M</em> be a fixed finite monoid. We consider the problem of implementing a data type containing a vector x=(x_1, x_2, ..., x_n) in M^n, initially (1, 1, ..., 1) with two kinds of operations, for each i in {1, ..., n}, a in M, an operation <code>change</code>_{i,a} which changes x_i to a and a single operation <code> product</code> returning ½_{i=1}^j x_i. This is the dynamic <em>word</em> problem. If we in addition for each j in {1, ..., n} have an operation <code>prefix_j</code> returning ½_{i=1}^j x_i, we talk about the dynamic <em>prefix</em> problem. We analyze the complexity of these problems in the <em>cell probe</em> or <em>decision assignment tree</em> model for two natural cell sizes, 1 bit and log n bits. We obtain a classification of the complexity based on algebraic properties of <em>M</em>. f


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