Group membership salience and task performance

Purpose – Social loafing is described in the literature as a frequent problem reducing individuals' performance when working in groups. This paper aims to utilize the social identity approach and proposes that under conditions of heightened group salience social loafing can be reduced and turned into social laboring (i.e. increased performance). Design/methodology/approach – Two experimental studies are conducted to examine the impact of participant's group membership salience on task performance. In Study 1, school teachers work either in coactive or in collective working conditions on brainstorming tasks. In Study 2, participants perform both a brainstorming task and a motor task. Findings – The results show social laboring effects. As predicted, participants in the high salient group conditions outperform participants in the low salient group conditions and the coactive individual condition. Practical implications – The results indicate that rather than individuating group members or tasks to overcome social loafing, managers can increase group performance by focusing on group members' perceptions of their groups as important and salient. Originality/value – The studies presented in this paper show that social identity theory and self categorization theory can fruitfully be applied to the field of group performance. The message of these studies for applied settings is that collective work in groups must not necessarily negatively impact performance, i.e. social loafing. By heightening the salience of group memberships groups can even outperform coactively working individuals.

An alternative formulation for the fuzzy assignment problem

The existing assignment problems for assigning n jobs to n individuals are limited to the considerations of cost or profit measured as crisp. However, in many real applications, costs are not deterministic numbers. This paper develops a procedure based on Data Envelopment Analysis method to solve the assignment problems with fuzzy costs or fuzzy profits for each possible assignment. It aims to obtain the points with maximum membership values for the fuzzy parameters while maximizing the profit or minimizing the assignment cost. In this method, a discrete approach is presented to rank the fuzzy numbers first. Then, corresponding to each fuzzy number, we introduce a crisp number using the efficiency concept. A numerical example is used to illustrate the usefulness of this new method. © 2012 Operational Research Society Ltd. All rights reserved.