Workplace design

Purpose: Although both the job and its broader context are likely to drive motivation, little is known about the specific workplace characteristics that are important for motivation. We present the Workplace Characteristics Model, which describes the workplace characteristics that can foster motivation, and the corresponding multilevel Workplace Design Questionnaire. Design/methodology/approach: The model is configured as nine workplace attributes describing climate for motivation at two levels, psychological and organizational. The multilevel multi-time questionnaire was validated with data from 4287 individuals and 212 workplaces and integrated regulation as the criterion outcome. Findings: Multilevel factor analysis and regression indicated good internal reliability, construct validity, and stability over time, and excellent concurrent and predictive validity of the questionnaire. Research/Practical implications: The model could help to optimize job and workplace design by contextualizing motivation. The questionnaire offers advancement over single-level climate measures as it is validated simultaneously at two levels. Further research should focus on overcoming the low response rate typical for online surveys, on need fulfillment as the mediating variable, and on the joint influence of job and workplace characteristics on organizational behavior. Originality/value: This work responds to calls to incorporate context in research into organizational behavior and job design. An understanding of the workplace is a first step in this direction. The questionnaire is the first to be validated at multiple levels of analysis. Ultimately, workplace design could support job design and the development of inherently motivating workplaces

Returns to scale, productivity and efficiency in US banking (1989-2000): the neural distance function revisited

Productivity and efficiency analyses have been indispensable tools for evaluating firms’ performance in the banking sector. In this context, the use of Artificial Neural Networks (ANNs) has been recently proposed in order to obtain a globally flexible functional form which is capable of approximating any existing output distance function while enabling the a priori imposition of the theoretical properties dictated by production theory, globally. Previous work has proposed and estimated the so-called Neural Distance Function (NDF) which has numerous advantages when compared to widely adopted specifications. In this paper, we carefully refine some of the most critical characteristics of the NDF. First, we relax the simplistic assumption that each equation has the same number of nodes because it is not expected to approximate reality with any reasonable accuracy and different numbers of nodes are allowed for each equation of the system. Second, we use an activation function which is known to achieve faster convergence compared to the conventional NDF model. Third, we use a relevant approach for technical efficiency estimation based on the widely adopted literature. Fitting the model to a large panel data we illustrate our proposed approach and estimate the Returns to Scale, the Total Factor Productivity and the Technical Efficiency in US commercial banking (1989-2000). Our approach provides very satisfactory results compared to the conventional model, a fact which implies that the refined NDF model successfully expands and improves the conventional NDF approach.Output distance function; Neural networks; Technical efficiency; US banks

Coupled cluster benchmarks of water monomers and dimers extracted from DFT liquid water: the importance of monomer deformations

To understand the performance of popular density-functional theory (DFT) exchange-correlation (xc) functionals in simulations of liquid water, water monomers and dimers were extracted from a PBE simulation of liquid water and examined with coupled cluster with single and double excitations plus a perturbative correction for connected triples [CCSD(T)]. CCSD(T) reveals that most of the dimers are unbound compared to two gas phase equilibrium water monomers, largely because monomers within the liquid have distorted geometries. Of the three xc functionals tested, PBE and BLYP systematically underestimate the cost of the monomer deformations and consequently predict too large dissociation energies between monomers within the dimers. This is in marked contrast to how these functionals perform for an equilibrium water dimer and other small water clusters in the gas phase, which only have moderately deformed monomers. PBE0 reproduces the CCSD(T) monomer deformation energies very well and consequently the dimer dissociation energies much more accurately than PBE and BLYP. Although this study is limited to water monomers and dimers, the results reported here may provide an explanation for the overstructured radial distribution functions routinely observed in BLYP and PBE simulations of liquid water and are of relevance to water in other phases and to other associated molecular liquids.Comment: 10 pages, 8 figures, Submitted to Journal of Chemical Physics, Related information can be found in http://www.fhi-berlin.mpg.de/th

On how good DFT exchange-correlation functionals are for H bonds in small water clusters: Benchmarks approaching the complete basis set limit

The ability of several density-functional theory (DFT) exchange-correlation functionals to describe hydrogen bonds in small water clusters (dimer to pentamer) in their global minimum energy structures is evaluated with reference to second order Moeller Plesset perturbation theory (MP2). Errors from basis set incompleteness have been minimized in both the MP2 reference data and the DFT calculations, thus enabling a consistent systematic evaluation of the true performance of the tested functionals. Among all the functionals considered, the hybrid X3LYP and PBE0 functionals offer the best performance and among the non-hybrid GGA functionals mPWLYP and PBE1W perform the best. The popular BLYP and B3LYP functionals consistently underbind and PBE and PW91 display rather variable performance with cluster size.Comment: 9 pages including 4 figures; related publications can be found at http://www.fhi-berlin.mpg.de/th/th.htm

A spatial stochastic frontier model with spillovers:evidence for Italian regions

Efficiency measurement using stochastic frontier models is well established in applied econometrics. However, no published work seems to be available on efficiency analysis using spatial data dealing with possible spatial dependence between regions. This article considers a stochastic frontier model with decomposition of inefficiency into an idiosyncratic and a spatial, spillover component. Exact posterior distributions of parameters are derived, and computational schemes based on Gibbs sampling with data augmentation are proposed to conduct simulation-based inference and efficiency measurement. The new method is illustrated using production data for Italian regions (1970–1993). Clearly, further theoretical and empirical research on the subject would be of great interest

Retinitis pigmentosa-associated cystoid macular oedema: pathogenesis and avenues of intervention

Hereditary retinal diseases are now the leading cause of blindness certification in the working age population (age 16-64 years) in England and Wales, of which retinitis pigmentosa (RP) is the most common disorder. RP may be complicated by cystoid macular oedema (CMO), causing a reduction of central vision. The underlying pathogenesis of RP-associated CMO (RP-CMO) remains uncertain, however, several mechanisms have been proposed, including: (1) breakdown of the blood-retinal barrier, (2) failure (or dysfunction) of the pumping mechanism in the retinal pigment epithelial, (3) Müller cell oedema and dysfunction, (4) antiretinal antibodies and (5) vitreous traction. There are limited data on efficacy of treatments for RP-CMO. Treatments attempted to date include oral and topical carbonic anhydrase inhibitors, oral, topical, intravitreal and periocular steroids, topical non-steroidal anti-inflammatory medications, photocoagulation, vitrectomy with internal limiting membrane peel, oral lutein and intravitreal antivascular endothelial growth factor injections. This review summarises the evidence supporting these treatment modalities. Successful management of RP-CMO should aim to improve both quality and quantity of vision in the short term and may also slow central vision loss over time

Multivariate stochastic volatility with large and moderate shocks

The paper proposes a multivariate stochastic volatility model where shifts in volatility are endogenously driven by large return shocks. The model proposed generalizes the univariate stochastic volatility model of Dendramis and colleagues to a multivariate context. Allowing for multivariate dependence permits the volatility of common return factors to affect individual stock returns volatility jointly. The model is further extended to allow for endogenous thresholds that depend on covariates. Model selection priors are introduced and the new techniques are applied by using data from the FTSE100‐index

Inverse Temperature Dependence of Nuclear Quantum Effects in DNA Base Pairs

Despite the inherently quantum mechanical nature of hydrogen bonding, it is unclear how nuclear quantum effects (NQEs) alter the strengths of hydrogen bonds. With this in mind, we use ab initio path integral molecular dynamics to determine the absolute contribution of NQEs to the binding in DNA base pair complexes, arguably the most important hydrogen-bonded systems of all. We find that depending on the temperature, NQEs can either strengthen or weaken the binding within the hydrogen-bonded complexes. As a somewhat counterintuitive consequence, NQEs can have a smaller impact on hydrogen bond strengths at cryogenic temperatures than at room temperature. We rationalize this in terms of a competition of NQEs between low-frequency and high-frequency vibrational modes. Extending this idea, we also propose a simple model to predict the temperature dependence of NQEs on hydrogen bond strengths in general

Debt dynamics in Europe: a network general equilibrium GVAR approach

In this work, we investigate the dynamic interdependencies among the EU12 economies using a competitive general equilibrium network system representation. Additionally, using Bayesian techniques, we estimate the autoregressive scheme that characterizes the equilibrium price system of the network, while characterizing each economy/node in the universe of our network in terms of its degree of pervasiveness. In this context, we unveil the dominant(s) unit(s) in our model and estimate the dynamic linkages between the economies/nodes. Lastly, in terms of robustness analysis, we compare the findings of the degree pervasiveness of each economy against other popular quantitative methods in the literature. According to our findings, the economy of Germany acts as weakly dominant entity in the EU12 economy. Meanwhile, all shocks die out in the short run, without any long lasting effect