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The aim of this paper is to accelerate the convergence of iterative methods on ill‐conditioned linear systems of equations.

First a brief numerical analysis is given of left preconditioners on ill‐conditioned linear systems of equations. From this result, it is deduced that a double preconditioning approach may be better. Then, a double preconditioner based on an iterative diagonal scaling method and an incomplete factorization method is proposed. The efficiency of this approach is illustrated on two finite element models produced by computational electromagnetism.

The double preconditioning approach is efficient for 2D and 3D finite element problems. The bi‐conjugate gradient algorithm always converges when it is double preconditioned. This is not the case when a simple incomplete factorization method is applied. Furthermore, when the two preconditioning techniques lead to the convergence of the iterative solving method, the double preconditioner significantly reduces the number of iterations in comparison with the simple preconditioner. On the proposed 2D problem, the speed‐up is between 6 and 32. On the proposed 3D problem, the speed‐up is between 13 and 20. Finally, the approach seems to reduce the growth of the condition number when higher‐order finite elements are used.

The paper proposes a particular double preconditioning approach which can be applied to any invertible linear system of equations. A numerical evaluation on a singular linear system is also provided but no proof or analysis of stability is given for this case.

The paper presents a new preconditioning technique based on the combination of two very simple and elementary methods: a diagonal scaling method and an incomplete factorization process. Acceleration obtained from this approach is quite impressive.

The purpose of this paper is to test the ability of the theory of planned behaviour to predict worker intent towards an employee involvement (EI) programme, and the impact of union identification on workers’ decision making.

Union workers at a small manufacturing company in the Midwestern United States completed two questionnaires. The first questionnaire provided measures of the attitudinal, normative, and behavioural control components of the theory of planned behaviour and the degree to which they identified with their labour union. In the second questionnaire, the same respondents answered questions to measure their intention to support or oppose an employee involvement (EI) programme.

Intentions to support EI were accurately predicted from attitudes, normative support, and perceived behavioural control (0.05 level). Level of union identification moderated the impact of attitudes on intention to support EI for workers that did not identify heavily with the labour union (0.05 level), but did not moderate the effect of normative support on intention for workers who identified heavily with the labour union.

The results indicate that the theory of planned behaviour has the potential to be an effective tool in predicting the behavioural outcomes of union members in the workplace, and that the level of union identification affects decision making. Research is limited by same source methodology and no direct measure of behaviour.

Leaders, labour and management, who intend to implement new programmes, should give strong consideration to how workers’ social cohorts influence their decision making and plan for this contingency when considering programme changes.

The level of union identification influences perception and decision making but has not been considered in models of member decision making. EI research has tended to center on EI as the antecedent to outcomes such as job satisfaction, cooperation, retention, and quality of work life. This paper addresses the role of union identification in support for EI programmes, and uses a well‐established behavioural theory to explain workers’ decision‐making process.