Organizational justice,voluntary learning behavior,and job performance: A test of the mediating effects of identification and leader‐member exchange

This paper presents and tests an integrative model of voluntary learning behavior. Drawing on social exchange theory, we argue that individuals are more likely to pursue learning activities when they identify with their employing organization and have a high quality leader–member exchange (LMX) relationship with their supervisor. We further argue that organizational identification is enhanced by both distributive and procedural fairness, whereas LMX quality is enhanced by interpersonal and informational fairness. Moreover, we contend that effective learning behavior improves job performance. The model was tested with a sample of 398 employees from a large automobile dealership. Results supported most predictions. Copyright © 2009 John Wiley & Sons, Ltd.     

What is most important for safety climate: The company belonging or the local working environment? – A study from the Norwegian offshore industry

Obtaining knowledge about factors affecting health, safety and environment (HSE) is of major interest to the petroleum industry, but there is currently a severe shortage of relevant studies. The aim of this study was to examine the relative influence of offshore installation (local working environment) and company belonging on employees’ opinions concerning occupational health and safety. We analyzed data from a safety climate survey answered by 4479 Norwegian offshore petroleum employees in 2005 on the dimensions “Safety prioritisation”, “Safety management and involvement”, “Safety versus production”, “Individual motivation”, “System comprehension” and “Competence” using one way analysis of variance (ANOVA), effect size and mixed model. The companies differed significantly for “Safety prioritisation”, “Safety versus production”, “Individual motivation”, “System comprehension” and “Competence”. The local offshore installation explained more of the safety climate than the company they were employed in or worked for did.     

Injury and loss concentration by sinkings in fishing fleets

Sinkings of fishing vessels, when accompanied by human loss, are accidents which lead to a great social upheaval, especially in the local area where they occur. In order to avoid or reduce these accidents, national governments must include in their legislation for this sector the appropriate safety measures. These resources and their distribution must be assigned in accordance with the needs of the accidentality, this requiring a detailed knowledge of the concentration of accidentality of a country’s fishing sector. In this context, the aim of the present work is twofold: first, to formulate a methodology for the fishing sector of a country, allowing the inequalities in the concentration of sinking accidents to be analysed; and second, to apply this methodology to the Spanish fishing fleet. Thus, two indices are constructed per region and type of fishing, for two variables: fishermen and vessels. Results are obtained both for the concentration of accidents and the associated Lorenz curves. An increase in the inequality in the spatial and functional distribution of these accidents is verified.     

The major accident risk (MAR) process - developing the profile of major accident risk for a large multi national oil company

The paper describes a programme to develop the profile of major accident risk across a large multi national oil company. It describes the concepts, tools and processes for constructing the risk profile and some of the key learnings from the exercise.     

Air quality and deposition of trace elements in Didouche Mourad, Algeria

Total suspended particulate matter and deposition fluxes of particles were investigated in the town of Didouche Mourad which is located 13 km north of Constantine. Samples of air particulate matter were collected at one site located in the heart of the town and situated 3 km north of a cement plant. Samples were collected from 2 November 2002 to 28 April 2003 every 3 days using a high volume air sampler. Sampling intervals were 24 h in all cases. During the same period, samples of dust fallout were collected at the same site. Samples were collected at 30-day intervals. Lead, chromium, manganese, nickel, copper, cobalt and cadmium deposition fluxes were measured and both the soluble and insoluble fractions were determined. Furthermore, the information gathered by this study was correlated with the corresponding hourly weather data provided by a weather station installed at the study station. The possible sources for dust and trace metals were analyzed by comparing average contributions of wind aspects to the concentrations and depositions of mass and chemical species with the average frequencies of wind direction. The mean concentration was 300 μg/m³. The average dust deposition rate through the period of study was 221 mg/(m².day). Results indicate that anthropogenic sources contribute greatly to trace elements. An exposure assessment to the heavy metals taking into account the inhalation route and soil dust ingestion was carried out and allowed direct comparison of trace metal intakes via these routes.     

Water quality assessment of Almatti Reservoir of Bijapur (Karnataka State, India) with special reference to zooplankton

The present investigation deals with the limnobiotic status of Almatti reservoir from February, 2003 to January, 2005. The study revealed that, the distribution and population density of zooplankton species depend upon the physico-chemical factors of the environment. Statistical analysis showed that there exists a significant relation between the biological and non-biological factors. The benthic fauna constituting the food of fish can be utilized for extensive culture operation so that the nutrients in the reservoir are not only properly cycled but also serve as a check on further eutrophication.     

Extraction of labile metals from solid media by dilute hydrochloric acid

Extraction of labile metals from solid media is environmentally more meaningful than a total digestion. A variety of reagents have been introduced in the literature, but dilute HCl has received the greatest attention. We compare metal concentrations liberated by a dilute HCl leach with the sum of the 3-step optimized (standardized) BCR sequential extraction procedure. This is the first study to compare these procedures over a range of grain sizes. Road-deposited sediments from 10 sites in Honolulu were fractionated into six grain size classes. Aliquots of individual fractions were digested with dilute HCl, the 3-step BCR procedure (‘labile’), and a 4-acid (total) procedure. Results indicated that the weighted labile concentrations of Al, Cu, Fe, Mn, Ni, Pb and Zn were statistically greater than those from the dilute HCl leach. However, regression analysis indicated strong statistically significant relationships between the two partial extraction procedures for all metals. On a whole-sample basis, the toxicity classifications for anthropogenic-enhanced metals (Cu, Pb and Zn) were similar between extractions. Taken together, results suggest that the application of dilute HCl to solid media provides a rapid, cost-effective, and environmentally meaningful approach for contaminant monitoring.     

Artificial neural network based carbon monoxide persistence models for episodic urban air quality management

This paper describes the development of artificial neural network (ANN) based carbon monoxide (CO) persistence (ANNCOP) models to forecast 8-h average CO concentration using 1-h maximum predicted CO data for the critical (winter) period (November–March). The models have been developed for three 8-h groupings of 10 p.m. to 6 a.m., 6 a.m. to 2 p.m. and 2–10 p.m., at two air quality control regions (AQCRs) in Delhi city, representing an urban intersection and an arterial road consisting heterogeneous traffic flows. The result indicates that time grouping of 2–10 pm is dominantly affected by inversion conditions and peak traffic flow. The ANNCOP model corresponding to this grouping predicts the 8-h average CO concentrations within the accuracy range of 68–71%. The CO persistence values derived from ANNCOP model are comparable with the persistence values as suggested by the Environmental Protection Agency (EPA), USA. This work demonstrates that ANN based model is capable of describing winter period CO persistence phenomena.