Managers are suffered from the high turnover rate in sales management. According to relative research results, pay systems have the most powerful impact on organizational performance among all the HR practices. Well-designed pay systems could attract and retain talent employees. They are also coupled with the effectiveness of performance evaluation, which stands for the aim of ensuring attaining organizational goals. Therefore, success or failure of an organization is significantly related to its pay system design. Because of its flexibility and responsiveness to organizational goals, variable pay possesses the ability to grant rewards linking employees to organizational success. From personnel economics perspective, monetary incentives have effects on output. However, a lack of data makes the above statement not corroborated. Based on a 60-month period data from a retailing company, this research conducts longitudinal analysis by fixed-effects regression model to empirically test the effects of variable pay on employees¡¦ job performance. Results verify the effects of variable pay on productivity. Those who are with individual level of performance measure, reasonable goal-setting and equitable payout formula characteristics show the best effect on productivity. Implications for designing variable pay systems are discussed and future research suggestions are provided.

Abstract This article uses the plant-level data of Taiwan manufacturing industry to study the determinants in explaining the timing of information and communication technologies (ICTs) adoption. This paper then investigates whether there exists any difference in determining the utilization of ICTs among high-tech industries and traditional industries. We find size variable has the most significant effect while there appears a different impact in different industries.

Often in statistics it is of interest to investigate whether or not a trend is significant. Methods for testing such a trend depend on the assumptions of the error terms such as whether the distribution is known and also if the error terms are independent. Likelihood ratio tests may be used if the distribution is known but in some instances one may not want to make such assumptions. In a time series, these errors will not always be independent. In this case, the error terms are often modelled by an autoregressive or moving average process. There are resampling techniques for testing the hypothesis of interest when the error terms are dependent, such as, modelbased bootstrapping and the wild bootstrap, but the error terms need to be whitened. In this dissertation, a bootstrap procedure is used to test the hypothesis of no trend for variable stars when the error structure assumes a particular form. In some cases, the bootstrap to be implemented is preferred over large sample tests in terms of the level of the test. The bootstrap procedure is able to correctly identify the underlying distribution which may not be χ2.

Thesis (M.S.)--West Virginia University, 2003. / Title from document title page. Document formatted into pages; contains x, 100 p. : ill. (some col.). Vita. Includes abstract. Includes bibliographical references (p. 82-84).

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The study of variable stars is extremely important to the astronomical field of scientific research. Variable stars must be methodically studied, usually by amateur astronomers over a long period of time, in order to provide professional astronomers important data that allows them to further analyze variable star behavior.Variable stars are unique because their pulsation produces visible changes in luminosity. This pulsation allows amateur astronomers to visually observe and identify variable stars. This type of research and study is special because amateurs can make a real contribution to the field.My objective was to become an amateur astronomer in the hopes that I could discover variable stars and contribute my findings to the greater astronomical scientific community. In completing this task, my overall goal was to better understand the true nature of science in order to improve my teaching in a secondary science classroom.

The proposed work provides a concept for predicting well performance behavior in a gas condensate reservoir using an empirical model for gas mobility. The proposed model predicts the behavior of the gas permeability (or mobility) function in the reservoir as condensate evolves and the gas permeability is reduced in the near-well region due to the "condensate bank". The proposed model is based on observations of simulated reservoir performance and predicts the behavior of the gas permeability over time and radial distance. This model is given by: The proposed concept has potential applications in the development of a pressure-time-radius solution for gas condensate reservoirs experiencing this type of mobility behavior. We recognize that the proposed concept (i.e., a radially-varying gas permeability) is oversimplified, in particular, it ignores the diffusive effects of the condensate (i.e., the viscosity-compressibility behavior). However, we have effectively validated the proposed model using literature results derived from numerical simulation. This new solution is presented graphically in the form of "type curves." We propose that the "time" form of this solution be used for applications in well test analysis. Previous developments used for the analysis of well test data from gas condensate reservoirs consider the radial composite reservoir model, which utilizes a "step change" in permeability at some radial distance away from the wellbore. Using our proposed solution we can visualize the effect of the varying gas permeability in time and radius (a suite of (dimensionless) radius and time format plots are provided). In short, we can visualize the evolution of the condensate zone as it evolves in time and radial distance. A limitation is the simplified form of the kg profile as a function of radius and time - as well as the dependence/appropriateness of the α-parameter. While we suspect that the α-parameter represents the influence of both fluid and rock properties, we do not examine how such properties can be used to calculate the α-parameter.

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Interest in the delta operator as a tool in the development of robust approaches to modelling and control has been revived in the last decade, principally following the work of Goodwin (1985). The use of this discrete differential operator provides improved numerical properties particularly when modelling or implementing control at high sampling frequencies or under finite wordlength restraints. The delta operator also provides for the alliance of continuous time designs and discrete time application, linking traditional control theory with modern implementation through digital computing. In this thesis, a delta operator Simplified Refined Instrumental Variable (SRIV) approach to model estimation is employed, together with model order identification tools, to provide delta operator models for use in control and forecasting. The True Digital Control (TDC) design theory is adopted to develop a delta operator Proportional-Integral-Plus (PIP) controller. The construction of realisable control filters enables implementation of the PIP controller, the structure of which can prove operationally significant. A number of refinements to the standard PIP controller are developed and applications are presented for engineering and environmental examples. The development of a recursive delta operator Kalman filter is presented and incorporated within a forecasting framework. The resulting algorithm is applied to historical data to generate real time stochastic forecasts of river flows from an effective rainfall-flow model.

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