Influence of ethical beliefs, national culture and institutions on preferences for HRM in Oman

Purpose – The paper seeks to investigate the association between ethical beliefs, aspects of national culture and national institutions, and preferences for specific human resource management practices in the Sultanate of Oman. Design/methodology/approach – A total of 712 individuals working in six organisations (both private and public sectors) responded to a self-administered questionnaire in the Sultanate of Oman. To test the raised research questions of the proposed framework, the methodology of structural equation models was used. Findings – The results highlight significant differences in the belief systems on the basis of different demographic characteristics. The findings also confirm impact of ethical beliefs, and aspects of national culture and national institutions on preferences for human resource management (HRM) practices. Research limitations/implications – Although the goodness-of-fit indexes confirmed the validity of the proposed operational model, some indices were attained at rather flexible levels. Practical implications – Studies on managerial beliefs and values can offer important insights into the extent that work is viewed as an integral life activity. Such information can help differentiate among managerial styles in various cultures, and in predicting managerial behaviour such as ethical decision-making. Based on such understanding, the findings can be used to educate government officials and outside consultants interested in Oman. Originality/value – The study contributes to the accumulation of knowledge about under-researched developing countries such as Oman, as limited data are available on HRM, value orientations and ethical beliefs' issues in this region.

Population pharmacokinetics of single-dose intravenous paracetamol in children

Background To determine the pharmacokinetics (PK) of a new i.v. formulation of paracetamol (Perfalgan) in children ≤15 yr of age. Methods After obtaining written informed consent, children under 16 yr of age were recruited to this study. Blood samples were obtained at 0, 15, 30 min, 1, 2, 4, 6, and 8 h after administration of a weight-dependent dose of i.v. paracetamol. Paracetamol concentration was measured using a validated high-performance liquid chromatographic assay with ultraviolet detection method, with a lower limit of quantification (LLOQ) of 900 pg on column and an intra-day coefficient of variation of 14.3% at the LLOQ. Population PK analysis was performed by non-linear mixed-effect modelling using NONMEM. Results One hundred and fifty-nine blood samples from 33 children aged 1.8–15 yr, weight 13.7–56 kg, were analysed. Data were best described by a two-compartment model. Only body weight as a covariate significantly improved the goodness of fit of the model. The final population models for paracetamol clearance (CL), V1 (central volume of distribution), Q (inter-compartmental clearance), and V2 (peripheral volume of distribution) were: 16.51×(WT/70)0.75, 28.4×(WT/70), 11.32×(WT/70)0.75, and 13.26×(WT/70), respectively (CL, Q in litres per hour, WT in kilograms, and V1 and V2 in litres). Conclusions In children aged 1.8–15 yr, the PK parameters for i.v. paracetamol were not influenced directly by age but were by total body weight and, using allometric size scaling, significantly affected the clearances (CL, Q) and volumes of distribution (V1, V2).

Density forecasts of crude-oil prices using option-implied and ARCH-type models

The predictive accuracy of competing crude-oil price forecast densities is investigated for the 1994–2006 period. Moving beyond standard ARCH type models that rely exclusively on past returns, we examine the benefits of utilizing the forward-looking information that is embedded in the prices of derivative contracts. Risk-neutral densities, obtained from panels of crude-oil option prices, are adjusted to reflect real-world risks using either a parametric or a non-parametric calibration approach. The relative performance of the models is evaluated for the entire support of the density, as well as for regions and intervals that are of special interest for the economic agent. We find that non-parametric adjustments of risk-neutral density forecasts perform significantly better than their parametric counterparts. Goodness-of-fit tests and out-of-sample likelihood comparisons favor forecast densities obtained by option prices and non-parametric calibration methods over those constructed using historical returns and simulated ARCH processes. © 2010 Wiley Periodicals, Inc. Jrl Fut Mark 31:727–754, 2011

Collocation, interpretation and explanation:the case of just any

This article discusses the question of compositionality by examining whether the indiscriminacy reading of the collocation of just with any can be shown to be a consequence of the schematic meaning-potential of each of these two items. A comparison of justwith other restrictive focus particles allows its schematic meaning to be defined as that of goodness of fit. Any is defined as representing an indefinite member of a set as extractable from the set in exactly the same way as each of the other members thereof. The collocation just any often gives rise to a scalar reading oriented towards the lowest value on the scale due to the fact that focus on the unconstrained extractability of a random indefinite item brings into consideration even marginal cases and the latter tend to be interpreted as situated on the lower end of the scale. The attention to low-end values also explains why just any is regularly found with the adjective old, the prepositional phrase at all and various devaluating expressions. It is concluded that the meanings of the component parts of this collocation do indeed account for the meaning of the whole, and that an appropriate methodology allows identification of linguistic meanings and their interrelations. © 2011 Elsevier B.V.

The enantioselective population pharmacokinetics of intravenous ketorolac in children using a stereoselective assay suitable for microanalysis

Objective: To describe the effect of age and body size on enantiomer selective pharmacokinetic (PK) of intravenous ketorolac in children using a microanalytical assay. Methods: Blood samples were obtained at 0, 15 and 30 min and at 1, 2, 4, 6, 8 and 12 h after a weight-dependent dose of ketorolac. Enantiomer concentration was measured using a liquid chromatography tandem mass spectrometry method. Non-linear mixed-effect modelling was used to assess PK parameters. Key findings: Data from 11 children (1.7–15.6 years, weight 10.7–67.4 kg) were best described by a two-compartment model for R(+), S(−) and racemic ketorolac. Only weight (WT) significantly improved the goodness of fit. The final population models were CL = 1.5 × (WT/46)0.75, V1 = 8.2 × (WT/46), Q = 3.4 × (WT/46)0.75, V2 = 7.9 × (WT/46), CL = 2.98 × (WT/46), V1 = 13.2 × (WT/46), Q = 2.8 × (WT/46)0.75, V2 = 51.5 × (WT/46), and CL = 1.1 × (WT/46)0.75, V1 = 4.9 × (WT/46), Q = 1.7 × (WT/46)0.75 and V2 = 6.3 × (WT/46)for R(+), S(−) and racemic ketorolac. Conclusions: Only body weight influenced the PK parameters for R(+) and S(−) ketorolac. Using allometric size scaling significantly affected the clearances (CL, Q) and volumes of distribution (V1, V2).

A question of fit:cultural and individual differences in interpersonal justice perceptions

This study examined the link between employees’ adult attachment orientations and perceptions of line managers’ interpersonal justice behaviors, and the moderating effect of national culture (collectivism). Participants from countries categorized as low collectivistic (N = 205) and high collectivistic (N = 136) completed an online survey. Attachment anxiety and avoidance were negatively related to interpersonal justice perceptions. Cultural differences did not moderate the effects of avoidance. However, the relationship between attachment anxiety and interpersonal justice was non-significant in the Southern Asia (more collectivistic) cultural cluster. Our findings indicate the importance of ‘fit’ between cultural relational values and individual attachment orientations in shaping interpersonal justice perceptions, and highlight the need for more non-western organizational justice research.

A Stochastic Approach for Finding of Semantically Related Words

2000 Mathematics Subject Classification: 62P99, 68T50

The effect of vision congruence on employee empowerment, commitment, satisfaction, and performance

Five models delineating the person-situation fit controversy were developed and tested. Hypotheses were tested to determine the linkages between vision congruence, empowerment, locus of control, job satisfaction, organizational commitment, and employee performance. Vision was defined as a mental image of a possible and desirable future state of the organization.^ Data were collected from 213 employees in a major flower import company. Participants were from various organizational levels and ethnic backgrounds. The data collection procedure consisted of three parts. First, a profile analysis instrument was used which was developed employing a Q-sort based technique, to measure the vision congruence between the CEO and each employee. Second, employees completed a survey instrument which included scales measuring empowerment, locus of control, job satisfaction, organizational commitment, and social desirability. Third, supervisor performance ratings were gathered from employee files. Data analysis consisted of using Kendall's tau to measure the correlation between CEO's and each employee's vision. Path analyses were conducted using the EQS structural equation program to test five theoretical models for goodness-of-fit. Regression analysis was employed to test whether locus of control acted as a moderator variable.^ The results showed that vision congruence is significantly related to job satisfaction and employee commitment, and perceived empowerment acts as an intervening variable affecting employee outcomes. The study also found that people with an internal locus of control were more likely to feel empowered than were those with external beliefs. Implications of these findings for both researchers and practitioners are discussed and suggestions for future research directions are provided. ^

Development of safety performance functions for empirical Bayes estimation of crash reduction factors

Crash reduction factors (CRFs) are used to estimate the potential number of traffic crashes expected to be prevented from investment in safety improvement projects. The method used to develop CRFs in Florida has been based on the commonly used before-and-after approach. This approach suffers from a widely recognized problem known as regression-to-the-mean (RTM). The Empirical Bayes (EB) method has been introduced as a means to addressing the RTM problem. This method requires the information from both the treatment and reference sites in order to predict the expected number of crashes had the safety improvement projects at the treatment sites not been implemented. The information from the reference sites is estimated from a safety performance function (SPF), which is a mathematical relationship that links crashes to traffic exposure. The objective of this dissertation was to develop the SPFs for different functional classes of the Florida State Highway System. Crash data from years 2001 through 2003 along with traffic and geometric data were used in the SPF model development. SPFs for both rural and urban roadway categories were developed. The modeling data used were based on one-mile segments that contain homogeneous traffic and geometric conditions within each segment. Segments involving intersections were excluded. The scatter plots of data show that the relationships between crashes and traffic exposure are nonlinear, that crashes increase with traffic exposure in an increasing rate. Four regression models, namely, Poisson (PRM), Negative Binomial (NBRM), zero-inflated Poisson (ZIP), and zero-inflated Negative Binomial (ZINB), were fitted to the one-mile segment records for individual roadway categories. The best model was selected for each category based on a combination of the Likelihood Ratio test, the Vuong statistical test, and the Akaike's Information Criterion (AIC). The NBRM model was found to be appropriate for only one category and the ZINB model was found to be more appropriate for six other categories. The overall results show that the Negative Binomial distribution model generally provides a better fit for the data than the Poisson distribution model. In addition, the ZINB model was found to give the best fit when the count data exhibit excess zeros and over-dispersion for most of the roadway categories. While model validation shows that most data points fall within the 95% prediction intervals of the models developed, the Pearson goodness-of-fit measure does not show statistical significance. This is expected as traffic volume is only one of the many factors contributing to the overall crash experience, and that the SPFs are to be applied in conjunction with Accident Modification Factors (AMFs) to further account for the safety impacts of major geometric features before arriving at the final crash prediction. However, with improved traffic and crash data quality, the crash prediction power of SPF models may be further improved.

An examination of Lotka's law in the field of Library and Information Studies

The purpose of this study was to test Lotka’s law of scientific publication productivity using the methodology outlined by Pao (1985), in the field of Library and Information Studies (LIS). Lotka’s law has been sporadically tested in the field over the past 30+ years, but the results of these studies are inconclusive due to the varying methods employed by the researchers. ^ A data set of 1,856 citations that were found using the ISI Web of Knowledge databases were studied. The values of n and c were calculated to be 2.1 and 0.6418 (64.18%) respectively. The Kolmogorov-Smirnov (K-S) one sample goodness-of-fit test was conducted at the 0.10 level of significance. The Dmax value is 0.022758 and the calculated critical value is 0.026562. It was determined that the null hypothesis stating that there is no difference in the observed distribution of publications and the distribution obtained using Lotka’s and Pao’s procedure could not be rejected. ^ This study finds that literature in the field of Library and Information Studies does conform to Lotka’s law with reliable results. As result, Lotka’s law can be used in LIS as a standardized means of measuring author publication productivity which will lead to findings that are comparable on many levels (e.g., department, institution, national). Lotka’s law can be employed as an empirically proven analytical tool to establish publication productivity benchmarks for faculty and faculty librarians. Recommendations for further study include (a) exploring the characteristics of the high and low producers; (b) finding a way to successfully account for collaborative contributions in the formula; and, (c) a detailed study of institutional policies concerning publication productivity and its impact on the appointment, tenure and promotion process of academic librarians. ^

The inclusion of differentially assessed lands in urban growth model calibration: a comparison of two approaches using SLEUTH

This research sought to understand the role that differentially assessed lands (lands in the United States given tax breaks in return for their guarantee to remain in agriculture) play in influencing urban growth. Our method was to calibrate the SLEUTH urban growth model under two different conditions. The first used an excluded layer that ignored such lands, effectively rendering them available for development. The second treated those lands as totally excluded from development. Our hypothesis was that excluding those lands would yield better metrics of fit with past data. Our results validate our hypothesis since two different metrics that evaluate goodness of fit both yielded higher values when differentially assessed lands are treated as excluded. This suggests that, at least in our study area, differential assessment, which protects farm and ranch lands for tenuous periods of time, has indeed allowed farmland to resist urban development. Including differentially assessed lands also yielded very different calibrated coefficients of growth as the model tried to account for the same growth patterns over two very different excluded areas. Excluded layer design can greatly affect model behavior. Since differentially assessed lands are quite common through the United States and are often ignored in urban growth modeling, the findings of this research can assist other urban growth modelers in designing excluded layers that result in more accurate model calibration and thus forecasting.

Development of safety performance functions for SafetyAnalyst applications in Florida

In 2010, the American Association of State Highway and Transportation Officials (AASHTO) released a safety analysis software system known as SafetyAnalyst. SafetyAnalyst implements the empirical Bayes (EB) method, which requires the use of Safety Performance Functions (SPFs). The system is equipped with a set of national default SPFs, and the software calibrates the default SPFs to represent the agency's safety performance. However, it is recommended that agencies generate agency-specific SPFs whenever possible. Many investigators support the view that the agency-specific SPFs represent the agency data better than the national default SPFs calibrated to agency data. Furthermore, it is believed that the crash trends in Florida are different from the states whose data were used to develop the national default SPFs. In this dissertation, Florida-specific SPFs were developed using the 2008 Roadway Characteristics Inventory (RCI) data and crash and traffic data from 2007-2010 for both total and fatal and injury (FI) crashes. The data were randomly divided into two sets, one for calibration (70% of the data) and another for validation (30% of the data). The negative binomial (NB) model was used to develop the Florida-specific SPFs for each of the subtypes of roadway segments, intersections and ramps, using the calibration data. Statistical goodness-of-fit tests were performed on the calibrated models, which were then validated using the validation data set. The results were compared in order to assess the transferability of the Florida-specific SPF models. The default SafetyAnalyst SPFs were calibrated to Florida data by adjusting the national default SPFs with local calibration factors. The performance of the Florida-specific SPFs and SafetyAnalyst default SPFs calibrated to Florida data were then compared using a number of methods, including visual plots and statistical goodness-of-fit tests. The plots of SPFs against the observed crash data were used to compare the prediction performance of the two models. Three goodness-of-fit tests, represented by the mean absolute deviance (MAD), the mean square prediction error (MSPE), and Freeman-Tukey R2 (R2FT), were also used for comparison in order to identify the better-fitting model. The results showed that Florida-specific SPFs yielded better prediction performance than the national default SPFs calibrated to Florida data. The performance of Florida-specific SPFs was further compared with that of the full SPFs, which include both traffic and geometric variables, in two major applications of SPFs, i.e., crash prediction and identification of high crash locations. The results showed that both SPF models yielded very similar performance in both applications. These empirical results support the use of the flow-only SPF models adopted in SafetyAnalyst, which require much less effort to develop compared to full SPFs.

Development, validation and uncertainty analysis of quantitative structure and activity relationship models for Log P of disinfection by -products

Hydrophobicity as measured by Log P is an important molecular property related to toxicity and carcinogenicity. With increasing public health concerns for the effects of Disinfection By-Products (DBPs), there are considerable benefits in developing Quantitative Structure and Activity Relationship (QSAR) models capable of accurately predicting Log P. In this research, Log P values of 173 DBP compounds in 6 functional classes were used to develop QSAR models, by applying 3 molecular descriptors, namely, Energy of the Lowest Unoccupied Molecular Orbital (ELUMO), Number of Chlorine (NCl) and Number of Carbon (NC) by Multiple Linear Regression (MLR) analysis. The QSAR models developed were validated based on the Organization for Economic Co-operation and Development (OECD) principles. The model Applicability Domain (AD) and mechanistic interpretation were explored. Considering the very complex nature of DBPs, the established QSAR models performed very well with respect to goodness-of-fit, robustness and predictability. The predicted values of Log P of DBPs by the QSAR models were found to be significant with a correlation coefficient R2 from 81% to 98%. The Leverage Approach by Williams Plot was applied to detect and remove outliers, consequently increasing R 2 by approximately 2% to 13% for different DBP classes. The developed QSAR models were statistically validated for their predictive power by the Leave-One-Out (LOO) and Leave-Many-Out (LMO) cross validation methods. Finally, Monte Carlo simulation was used to assess the variations and inherent uncertainties in the QSAR models of Log P and determine the most influential parameters in connection with Log P prediction. The developed QSAR models in this dissertation will have a broad applicability domain because the research data set covered six out of eight common DBP classes, including halogenated alkane, halogenated alkene, halogenated aromatic, halogenated aldehyde, halogenated ketone, and halogenated carboxylic acid, which have been brought to the attention of regulatory agencies in recent years. Furthermore, the QSAR models are suitable to be used for prediction of similar DBP compounds within the same applicability domain. The selection and integration of various methodologies developed in this research may also benefit future research in similar fields.

An Assessment of the Performances of Several Univariate Tests of Normality

The importance of checking the normality assumption in most statistical procedures especially parametric tests cannot be over emphasized as the validity of the inferences drawn from such procedures usually depend on the validity of this assumption. Numerous methods have been proposed by different authors over the years, some popular and frequently used, others, not so much. This study addresses the performance of eighteen of the available tests for different sample sizes, significance levels, and for a number of symmetric and asymmetric distributions by conducting a Monte-Carlo simulation. The results showed that considerable power is not achieved for symmetric distributions when sample size is less than one hundred and for such distributions, the kurtosis test is most powerful provided the distribution is leptokurtic or platykurtic. The Shapiro-Wilk test remains the most powerful test for asymmetric distributions. We conclude that different tests are suitable under different characteristics of alternative distributions.

An Examination of Lotka’s law in the Field of Library and Information Studies

The purpose of this study was to test Lotka’s law of scientific publication productivity using the methodology outlined by Pao (1985), in the field of Library and Information Studies (LIS). Lotka’s law has been sporadically tested in the field over the past 30+ years, but the results of these studies are inconclusive due to the varying methods employed by the researchers. A data set of 1,856 citations that were found using the ISI Web of Knowledge databases were studied. The values of n and c were calculated to be 2.1 and 0.6418 (64.18%) respectively. The Kolmogorov-Smirnov (K-S) one sample goodness-of-fit test was conducted at the 0.10 level of significance. The Dmax value is 0.022758 and the calculated critical value is 0.026562. It was determined that the null hypothesis stating that there is no difference in the observed distribution of publications and the distribution obtained using Lotka’s and Pao’s procedure could not be rejected. This study finds that literature in the field of library and Information Studies does conform to Lotka’s law with reliable results. As result, Lotka’s law can be used in LIS as a standardized means of measuring author publication productivity which will lead to findings that are comparable on many levels (e.g., department, institution, national). Lotka’s law can be employed as an empirically proven analytical tool to establish publication productivity benchmarks for faculty and faculty librarians. Recommendations for further study include (a) exploring the characteristics of the high and low producers; (b) finding a way to successfully account for collaborative contributions in the formula; and, (c) a detailed study of institutional policies concerning publication productivity and its impact on the appointment, tenure and promotion process of academic librarians.