The Role of Organizational Justice in Pay and Employee Benefit Satisfaction, and Its Effects on Work Attitudes

The objective of our study is to provide a complementary approach with regard to organizational justice in the domain of compensation. It presents research undertaken on a sample of six hundred employees in three different Canadian organizations. The results reveal that employees distinguish clearly between pay satisfaction and benefit satisfaction, and that distributive justice perceptions are better predictors of pay satisfaction than procedural justice perceptions. This result is reversed for employee benefit satisfaction: procedural justice perceptions are better predictors than distributive justice perceptions. Lastly, the results show that distributive justice perceptions with regard to pay play a more important role than procedural justice in job satisfaction and satisfaction with the organization. Cet article a pour but d'apporter un éclairage complémentaire en ce qui concerne la justice organisationnelle dans le domaine de la rémunération. On y fait état de recherches réalisées auprès de six cents salariés appartenant à trois organisations canadiennes différentes. Les résultats révèlent que les salariés dissocient bien la satisfaction à l'égard du salaire, de la satisfaction à l'égard des avantages sociaux. Ils montrent également que les perceptions de justice distributives permettent de mieux prédire la satisfaction à l'égard du salaire que les perceptions de justice procédurales. Le résultat est inverse en ce qui concerne la satisfaction à l'égard des avantages sociaux : les perceptions de justice procédurales sont de meilleurs prédicteurs que les perceptions de justice distributives. Ils montrent enfin que la perception de justice distributive concernant les salaires joue un rôle plus important que la justice procédurale dans la satisfaction à l'égard du travail et à l'égard de l'entreprise.Organizational justice, pay and benefit satisfaction, work attitudes, Justice organisationnelle, satisfaction du salaire, satisfaction des avantages sociaux, attitudes au travail

Growth rate for the expected value of a generalized random Fibonacci sequence

A random Fibonacci sequence is defined by the relation g_n = | g_{n-1} +/- g_{n-2} |, where the +/- sign is chosen by tossing a balanced coin for each n. We generalize these sequences to the case when the coin is unbalanced (denoting by p the probability of a +), and the recurrence relation is of the form g_n = |\lambda g_{n-1} +/- g_{n-2} |. When \lambda >=2 and 0 < p <= 1, we prove that the expected value of g_n grows exponentially fast. When \lambda = \lambda_k = 2 cos(\pi/k) for some fixed integer k>2, we show that the expected value of g_n grows exponentially fast for p>(2-\lambda_k)/4 and give an algebraic expression for the growth rate. The involved methods extend (and correct) those introduced in a previous paper by the second author

Crowd control: Reducing individual estimation bias by sharing biased social information

Cognitive biases are widespread in humans and animals alike, and can sometimes be reinforced by social interactions. One prime bias in judgment and decision-making is the human tendency to underestimate large quantities. Previous research on social influence in estimation tasks has generally focused on the impact of single estimates on individual and collective accuracy, showing that randomly sharing estimates does not reduce the underestimation bias. Here, we test a method of social information sharing that exploits the known relationship between the true value and the level of underestimation, and study if it can counteract the underestimation bias. We performed estimation experiments in which participants had to estimate a series of quantities twice, before and after receiving estimates from one or several group members. Our purpose was threefold: to study (i) whether restructuring the sharing of social information can reduce the underestimation bias, (ii) how the number of estimates received affects the sensitivity to social influence and estimation accuracy, and (iii) the mechanisms underlying the integration of multiple estimates. Our restructuring of social interactions successfully countered the underestimation bias. Moreover, we find that sharing more than one estimate also reduces the underestimation bias. Underlying our results are a human tendency to herd, to trust larger estimates than one’s own more than smaller estimates, and to follow disparate social information less. Using a computational modeling approach, we demonstrate that these effects are indeed key to explain the experimental results. Overall, our results show that existing knowledge on biases can be used to dampen their negative effects and boost judgment accuracy, paving the way for combating other cognitive biases threatening collective systems

Anomalous Drude Model

A generalization of the Drude model is studied. On the one hand, the free motion of the particles is allowed to be sub- or superdiffusive; on the other hand, the distribution of the time delay between collisions is allowed to have a long tail and even a non-vanishing first moment. The collision averaged motion is either regular diffusive or L\'evy-flight like. The anomalous diffusion coefficients show complex scaling laws. The conductivity can be calculated in the diffusive regime. The model is of interest for the phenomenological study of electronic transport in quasicrystals.Comment: 4 pages, latex, 2 figures, to be published in Physical Review Letter

Contest based on a directed polymer in a random medium

We introduce a simple one-parameter game derived from a model describing the properties of a directed polymer in a random medium. At his turn, each of the two players picks a move among two alternatives in order to maximize his final score, and minimize opponent's return. For a game of length $n$, we find that the probability distribution of the final score $S_n$ develops a traveling wave form, ${\rm Prob}(S_n=m)=f(m-v n)$, with the wave profile $f(z)$ unusually decaying as a double exponential for large positive and negative $z$. In addition, as the only parameter in the game is varied, we find a transition where one player is able to get his maximum theoretical score. By extending this model, we suggest that the front velocity $v$ is selected by the nonlinear marginal stability mechanism arising in some traveling wave problems for which the profile decays exponentially, and for which standard traveling wave theory applies

Distance traveled by random walkers before absorption in a random medium

We consider the penetration length $l$ of random walkers diffusing in a medium of perfect or imperfect absorbers of number density $\rho$. We solve this problem on a lattice and in the continuum in all dimensions $D$, by means of a mean-field renormalization group. For a homogeneous system in $D>2$, we find that $l\sim \max(\xi,\rho^{-1/2})$, where $\xi$ is the absorber density correlation length. The cases of D=1 and D=2 are also treated. In the presence of long-range correlations, we estimate the temporal decay of the density of random walkers not yet absorbed. These results are illustrated by exactly solvable toy models, and extensive numerical simulations on directed percolation, where the absorbers are the active sites. Finally, we discuss the implications of our results for diffusion limited aggregation (DLA), and we propose a more effective method to measure $l$ in DLA clusters.Comment: Final version: also considers the case of imperfect absorber

Scaling laws and vortex profiles in 2D decaying turbulence

We use high resolution numerical simulations over several hundred of turnover times to study the influence of small scale dissipation onto vortex statistics in 2D decaying turbulence. A self-similar scaling regime is detected when the scaling laws are expressed in units of mean vorticity and integral scale, as predicted by Carnevale et al., and it is observed that viscous effects spoil this scaling regime. This scaling regime shows some trends toward that of the Kirchhoff model, for which a recent theory predicts a decay exponent $\xi=1$. In terms of scaled variables, the vortices have a similar profile close to a Fermi-Dirac distribution.Comment: 4 Latex pages and 4 figures. Submitted to Phys. Rev. Let

Exponents appearing in heterogeneous reaction-diffusion models in one dimension

We study the following 1D two-species reaction diffusion model : there is a small concentration of B-particles with diffusion constant $D_B$ in an homogenous background of W-particles with diffusion constant $D_W$; two W-particles of the majority species either coagulate ($W+W \longrightarrow W$) or annihilate ($W+W \longrightarrow \emptyset$) with the respective probabilities $p_c=(q-2)/(q-1)$ and $p_a=1/(q-1)$; a B-particle and a W-particle annihilate ($W+B \longrightarrow \emptyset$) with probability 1. The exponent $\theta(q,\lambda=D_B/D_W)$ describing the asymptotic time decay of the minority B-species concentration can be viewed as a generalization of the exponent of persistent spins in the zero-temperature Glauber dynamics of the 1D $q$-state Potts model starting from a random initial condition : the W-particles represent domain walls, and the exponent $\theta(q,\lambda)$ characterizes the time decay of the probability that a diffusive "spectator" does not meet a domain wall up to time $t$. We extend the methods introduced by Derrida, Hakim and Pasquier ({\em Phys. Rev. Lett.} {\bf 75} 751 (1995); Saclay preprint T96/013, to appear in {\em J. Stat. Phys.} (1996)) for the problem of persistent spins, to compute the exponent $\theta(q,\lambda)$ in perturbation at first order in $(q-1)$ for arbitrary $\lambda$ and at first order in $\lambda$ for arbitrary $q$.Comment: 29 pages. The three figures are not included, but are available upon reques