When Breaking the Rules Relates to Creativity: The Role of Creative Problem-Solving Demands and Organizational Constraints

Drawing on theoretical views of creative deviance, the present study hypothesized that employees with a tendency to break rules are more creative at their jobs (Hypothesis 1). Furthermore, we expected that this is particularly the case when employees face high problem-solving demands (i.e., they are expected to be creative) but at the same time they face high organizational constraints (e.g., they are not given the resources they need in order to be creative; Hypothesis 2). To test these expectations, we conducted a cross-sectional survey study (Study 1) and a daily diary survey study (Study 2) among employees from different occupational groups. Study 1 provided evidence that employee rule-breaking is related to other-rated employee creativity. Study 2 replicated this finding with a day-level measure of self-rated employee creativity. Furthermore, multilevel regression analyses revealed that the link is stronger when day-level problem-solving demands and organizational constraints are both high. Our findings contribute to the literature by providing empirical support to hardly examined propositions, namely, that non-compliant behaviors (i.e., rule-breaking) and obstacles (i.e., organizational constraints) may, in fact, boost creativity. Finally, suggestions for practice are made, recognizing the challenges posed to management in regulating employee rule-breaking.     

Feedback functions, optimization, and the relation of response rate to reinforcer rate

The present experiment arranged a series of inverted U-shaped feedback functions relating reinforcer rate to response rate to test whether responding was consistent with an optimization account or with a one-to-one relation of response rate to reinforcer rate such as linear system theory's rate equation or Herrnstein's hyperbola. Reinforcer rate was arranged according to a quadratic equation with a maximum at a unique response rate. The experiment consisted of two phases, during which 6 Long Evans rats lever pressed for food. In the first phase of the experiment, the rats responded on six fixed-interval-plus-quadratic-feedback schedules, and in the second phase the rats responded on three variable-interval-plus-quadratic-feedback schedules. Responding in both phases was inconsistent with a one-to-one relation of response rate to reinforcer rate. Instead, different response rates were obtained at equivalent reinforcer rates. Responding did vary directly with the vertex of the feedback function in both phases, a finding consistent with optimization of reinforcer rate. The present results suggest that the feedback function relating reinforcer rate to response rate imposed by a reinforcement schedule can be an important determinant of behavior. Furthermore, the present experiment illustrates the benefit of arranging feedback functions to investigate assumptions about the variables that control schedule performance.     

Identifiability of nonlinear logistic test models

The linear logistic test model (LLTM) specifies the item parameters as a weighted sum of basic parameters. The LLTM is a special case of a more general nonlinear logistic test model (NLTM) where the weights are partially unknown. This paper is about the identifiability of the NLTM. Sufficient and necessary conditions for global identifiability are presented for a NLTM where the weights are linear functions, while conditions for local identifiability are shown to require a model with less restrictions. It is also discussed how these conditions are checked using an algorithm due to Bekker, Merckens, and Wansbeek (1994). Several illustrations are given.This article was written while the first author was a post doctoral fellow at the university of Twente. He gratefully acknowledges the university's hospitality and the financial support by NWO (project nr. 30002).     

A global optimization approach for generating efficient points for multiobjective concave fractional programs

In this article, we present a global optimization approach for generating efficient points for multiobjective concave fractional programming problems. The main work of the approach involves solving an instance of a concave multiplicative fractional program (W̄). Problem (W̄) is a global optimization problem for which no known algorithms are available. Therefore, to render the approach practical, we develop and validate a branch and bound algorithm for globally solving problem (W̄). To illustrate the performance of the global optimization approach, we use it to generate efficient points for a sample multiobjective concave fractional program. Copyright © 2006 John Wiley & Sons, Ltd.     

A Mixed λ-calculus

The aim of this paper is to define a λ-calculus typed in aMixed (commutative and non-commutative) Intuitionistic Linear Logic. The terms of such a calculus are the labelling of proofs of a linear intuitionistic mixed natural deduction NILL, which is based on the non-commutative linear multiplicative sequent calculus MNL [RuetAbrusci 99]. This linear λ-calculus involves three linear arrows: two directional arrows and a nondirectional one (the usual linear arrow). Moreover, the -terms are provided with seriesparallel orders on free variables. We prove a normalization theorem which explicitly gives the behaviour of the order during the normalization procedure. Special Issue Categorial Grammars and Pregroups Edited by Wojciech Buszkowski and Anne Preller     

Multilevel and Latent Variable Modeling with Composite Links and Exploded Likelihoods

Composite links and exploded likelihoods are powerful yet simple tools for specifying a wide range of latent variable models. Applications considered include survival or duration models, models for rankings, small area estimation with census information, models for ordinal responses, item response models with guessing, randomized response models, unfolding models, latent class models with random effects, multilevel latent class models, models with log-normal latent variables, and zero-inflated Poisson models with random effects. Some of the ideas are illustrated by estimating an unfolding model for attitudes to female work participation. We wish to thank The Research Council of Norway for a grant supporting our collaboration.     

Multilevel Modeling with Correlated Effects

When there exist omitted effects, measurement error, and/or simultaneity in multilevel models, explanatory variables may be correlated with random components, and standard estimation methods do not provide consistent estimates of model parameters. This paper introduces estimators that are consistent under such conditions. By employing generalized method of moments (GMM) estimation techniques in multilevel modeling, the authors present a series of estimators along a robust to efficient continuum. This continuum depends on the assumptions that the analyst makes regarding the extent of the correlated effects. It is shown that the GMM approach provides an overarching framework that encompasses well-known estimators such as fixed and random effects estimators and also provides more options. These GMM estimators can be expressed as instrumental variable (IV) estimators which enhances their interpretability. Moreover, by exploiting the hierarchical structure of the data, the current technique does not require additional variables unlike traditional IV methods. Further, statistical tests are developed to compare the different estimators. A simulation study examines the finite sample properties of the estimators and tests and confirms the theoretical order of the estimators with respect to their robustness and efficiency. It further shows that not only are regression coefficients biased, but variance components may be severely underestimated in the presence of correlated effects. Empirical standard errors are employed as they are less sensitive to correlated effects when compared to model-based standard errors. An example using student achievement data shows that GMM estimators can be effectively used in a search for the most efficient among unbiased estimators. This research was supported by the National Academy of Education/Spencer Foundation and the National Science Foundation, grant number SES-0436274. We thank the editor, associate editor, and referees for detailed feedback that helped improve the paper.     

Phonotactic constraints help to overcome effects of schwa deletion in French

In a crossmodal priming experiment, visual targets (e.g. RENARD, 'fox') were auditorily primed by either an intact [see text] 'the fox' or reduced form [see text] 'the fox' of the word. When schwa deletion gave rise to an initial cluster that respected the phonotactic constraints of French (e.g. [lapluz] 'the lawn' in which /pl/ is a legal word beginning in French), there was a processing cost for the targets primed by the reduced form of the word compared to intact primes (e.g. [see text] 'the lawn'). However, when schwa deletion produced an initial cluster that violated the phonotactic constraints of French (e.g. [see text], where /Rn/ is not allowed as a word beginning), there was no penalty for targets primed by reduced compared to intact forms of the word. Assuming that listeners change their phonemic percept when confronted with phonotactically illegal sequences (Segui, Frauenfelder, & Hallé, 2001), phonotactic constraints may help to restore the deleted schwa in sequences like le renard [see text] in French.     

Effects of decision-phase time constraints on emotion-based learning in the Iowa Gambling Task

Research employing the Iowa Gambling Task (IGT) has frequently shown that learning is impaired in various clinical populations. However, precisely what constitutes "unimpaired" control group learning remains unclear. In order to understand some of the possible factors underlying variability in control group IGT performance, the present study sought to manipulate features of the task to intentionally disrupt learning. Specifically, the present study investigated the effects of time constraints on emotion-based learning during automated administration of the IGT. For two groups of participants, a time-constraint of either 2-s or 4-s was implemented during the critical decision making period, while a control group received no time constraint. We also evaluated participants' subjective experience after every block of 20 trials. Results demonstrated that the 2-s group differed significantly from the control group. Subjective experience measures revealed rapid development of awareness of the advantageous and disadvantageous decks among all three groups. Overall, our findings demonstrate, for the first time, the effects of decision-phase time constraints on emotion-based learning and indicate that the IGT reward/punishment schedules are to some extent cognitively penetrable.