1,627 research outputs found
The relationship between personality types and reward preferences
Abstract: Research has shown that total rewards models structured according to individual preferences, positively influence efforts to attract, retain and motivate key employees. Yet, this is seldom done. Structuring total rewards models according to the preferences of employee segments is a viable alternative to accommodate individual preferences. Research purpose: The primary aim of the study was to determine the relationship between personality types and reward preferences. The secondary aim was to determine the reward preferences for different demographic groups. Motivation for the study: An enhanced understanding of reward preferences for different employee segments will enable employers to offer more competitive reward options to their employees. This may, in turn, have a positive impact on retention. Research design, approach and method: Two measuring instruments, the MBTI® Form GRV and the Rewards Preferences Questionnaire, were distributed electronically to 5 000 potential respondents. The results from 589 sets of questionnaires were used in the data analyses. Primary and secondary factor analyses were done on the items in the Rewards Preferences Questionnaire. Main findings/results: The study confirmed that individuals with certain personality types and personality preferences, have different preferences for certain reward categories. There was a stronger relationship between reward preferences and personality preferences than for reward preferences and personality types. Preferences for reward categories by different demographic groups were confirmed. The significant difference in reward preferences between Black and White respondents in particular was noteworthy, with Black respondents indicating significantly higher mean scores for all reward categories than White respondents. Finally, a total rewards framework influenced by the most prominent preferences for reward categories, was designed..
The relationship between personality types and reward preferences
Abstract: Research has shown that total rewards models structured according to individual preferences, positively influence efforts to attract, retain and motivate key employees. Yet, this is seldom done. Structuring total rewards models according to the preferences of employee segments is a viable alternative to accommodate individual preferences. Research purpose: The primary aim of the study was to determine the relationship between personality types and reward preferences. The secondary aim was to determine the reward preferences for different demographic groups. Motivation for the study: An enhanced understanding of reward preferences for different employee segments will enable employers to offer more competitive reward options to their employees. This may, in turn, have a positive impact on retention. Research design, approach and method: Two measuring instruments, the MBTI® Form GRV and the Rewards Preferences Questionnaire, were distributed electronically to 5 000 potential respondents. The results from 589 sets of questionnaires were used in the data analyses. Primary and secondary factor analyses were done on the items in the Rewards Preferences Questionnaire. Main findings/results: The study confirmed that individuals with certain personality types and personality preferences, have different preferences for certain reward categories. There was a stronger relationship between reward preferences and personality preferences than for reward preferences and personality types. Preferences for reward categories by different demographic groups were confirmed. The significant difference in reward preferences between Black and White respondents in particular was noteworthy, with Black respondents indicating significantly higher mean scores for all reward categories than White respondents. Finally, a total rewards framework influenced by the most prominent preferences for reward categories, was designed..
Three-dimensional vestibular eye and head reflexes of the chameleon: characteristics of gain and phase and effects of eye position on orientation of ocular rotation axes during stimulation in yaw direction
We investigated gaze-stabilizing reflexes in the chameleon using the three-dimensional search-coil technique. Animals were rotated sinusoidally around an earth-vertical axis under head-fixed and head-free conditions, in the dark and in the light. Gain, phase and the influence of eye position on vestibulo-ocular reflex rotation axes were studied. During head-restrained stimulation in the dark, vestibulo-ocular reflex gaze gains were low (0.1-0.3) and phase lead decreased with increasing frequencies (from 100° at 0.04Hz to <30° at 1Hz). Gaze gains were larger during stimulation in the light (0.1-0.8) with a smaller phase lead (<30°) and were close to unity during the head-free conditions (around 0.6 in the dark, around 0.8 in the light) with small phase leads. These results confirm earlier findings that chameleons have a low vestibulo-ocular reflex gain during head-fixed conditions and stimulation in the dark and higher gains during head-free stimulation in the light. Vestibulo-ocular reflex eye rotation axes were roughly aligned with the head's rotation axis and did not systematically tilt when the animals were looking eccentrically, up- or downward (as predicted by Listing's Law). Therefore, vestibulo-ocular reflex responses in the chameleon follow a strategy, which optimally stabilizes the entire retinal images, a result previously found in non-human primate
Collective Electronic Excitation Coupling between Planar Optical Lattices using Ewald's Method
Using Ewald's summation method we investigate collective electronic
excitations (excitons) of ultracold atoms in parallel planar optical lattices
including long range interactions. The exciton dispersion relation can then be
suitably rewritten and efficiently calculated for long range resonance
dipole-dipole interactions. Such in-plane excitons resonantly couple for two
identical optical lattices, with an energy transfer strength decreasing
exponentially with the distance between the lattices. This allows a restriction
of the transfer to neighboring planes and gives rise to excitons delocalized
between the lattices. In general equivalent results will hold for any planar
system containing lattice layers of optically active and dipolar materials.Comment: 6 pages, and 7 figure
Oxygen non-stoichiometry in Ru-1212 and Ru-1222 magnetosuperconductors
Here we report the results of thermogravimetric (TG) analysis on the oxygen
non-stoichiometry of RuSr2GdCu2O8 (Ru-1212) and
RuSr2(Gd0.75Ce0.25)2Cu2O10(Ru-1222) samples. With TG annealings carried out in
O2 and Ar atmospheres it was found that the oxygen content in Ru-1212 remains
less affected upon various annealings, while for Ru-1222 wider-range
oxygen-content tuning is possible. When heated in H2/Ar atmosphere the both
phases release oxygen upon breaking down to mixtures of metals (Ru and Cu) and
binary oxides (CeO2, Gd2O3, and SrO) in two distinct steps around 300 and 450
oC. This reductive decomposition reaction carried out in a thermobalance was
utilized in precise oxygen content determination for these phases. It was found
that the 100-atm O2-annealed Ru-1212 sample was nearly stoichiometric, while
the similarly treated Ru-1222 sample was clearly oxygen deficient. X-ray
absorption near-edge (XANES) spectroscopy was applied to estimate the valence
of Ru in the samples. In spite of the fact that the Ru-1212 phase was shown to
possess less oxygen-deficient RuO2 layer, the valence of Ru as probed with
XANES was found to be lower in Ru-1212 than that in Ru-1222.Comment: 11 pages text, 4 pages Figs. To ISS 2002 YOKOHAMA for PHYSICA
Response to comments on "magnetic resonance spectroscopy identifies neural progenitor cells in the live human brain"
We reported on a neural progenitor cell biomarker, a lipid-based metabolite enriched in these cells, which we detected using spectroscopy both in vitro and in vivo, and singular value decomposition–based signal processing. The study provided an outline of our computational methodology. Herein, we report more extensively on the method of spectrum analysis used, demonstrating the specificity of our findings
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