Prediction of Ideas Number During a Brainstorming Session

2014 | Group Decision and Negotiation | Citations: 0

Authors: Haddou, Hassan Ait; Camilleri, Guy; Zaraté, Pascale

Abstract: In this paper, we present an approach allowing the prediction of ideas number du ... Expand

Abstract: In this paper, we present an approach allowing the prediction of ideas number during a brainstorming session. This prediction is based on two dynamic models of brainstorming, the non-cognitive and the cognitive models proposed by Brown and Paulus (Small Group Res 27(1):91–114, 1996). These models describe for each participant, the evolution of ideas number over time, and are formalized by differential equations. Through solution functions of these models, we propose to calculate the number of ideas of each participant on any time intervals and thus in the future (called prediction). To be able to compute solution functions, it is necessary to determine the parameters of these models. In our approach, we use optimization model for model parameters calculation in which solution functions are approximated by numerical methods. We developed two generic optimization models, one based on Euler’s and the other on the fourth order Runge–Kutta’s numerical methods for the solving of differential equations, and we apply them to the non-cognitive and respectively to the cognitive models. Through some feasibility tests, we show the adequacy of the proposed approach to our prediction context. Collapse

Topics: brainstorming productivity group decision support system decision making

Methods: optimization model experiment mathematical model

Theories: bounded ideation theory

Putting Quality First in Ideation Research

2013 | Group Decision and Negotiation | Citations: 1

Authors: Reinig, Bruce A.; Briggs, Robert O.

Abstract: Teams use ideation techniques such as brainstorming to generate alternatives in ... Expand

Abstract: Teams use ideation techniques such as brainstorming to generate alternatives in response to a crisis or opportunity with the goal of converging on a few high-quality ideas. Ideation research, however, tends to focus on developing techniques that generate a large quantity of ideas, sometimes giving little attention to the cognitive mechanisms that give rise to good-quality ideas, or to the validity of the metrics by which ideation quality is measured . This study examines a theoretical link between idea quality and quantity in the ideation literature using Bounded Ideation Theory (BIT). BIT proposes that the relationship between participant ability and ideation quality is moderated by cognitive factors such as scarcity of attention resources, mental and physical exhaustion, understanding of the problem, and goal congruence, as well as attributes of the problem being addressed. Ideation quality is measured in the literature using a number of approaches which diverge to differing research conclusions, even when applied to the same data set. We use a Monte Carlo simulation to demonstrate conditions under which some of these measures exhibit a bias. We present theoretical and methodological arguments to support our call for future ideation research to shift its focus from quantity to quality by focusing on the cognitive factors that influence ideation quality and using unbiased measures of ideation quality. Collapse

Topics: brainstorming productivity

Methods: Monte Carlo simulation descriptive statistic simulation correlation analysis literature study

Theories: bounded ideation theory organizational behavior theory

Bounded Ideation Theory

2010 | Journal of Management Information Systems | Citations: 32

Authors: Briggs, Robert O.; Reinig, Bruce A.

Abstract: The article presents information on bounded ideation theory (BIT), which is said ... Expand

Abstract: The article presents information on bounded ideation theory (BIT), which is said to be a means of optimizing brainstorming sessions. BIT challenges the rubric that the percentage of good ideas will remain constant as the number of ideas generated rises. It is argued that limitations in solution space, goal congruence, attention span and knowledge typically result in the number of good ideas tapering off on an inflected curve. Six strategies are suggested for improving ideation sessions, which focus on promoting quality at the expense of quantity. Collapse

Topics: idea generation

Theories: bounded ideation theory