Book Summary: Provides the information and tools neccessary for nurses to express themselves more effectively using financial principles and data while interfacing with financial personnel.

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A case study examined contractor demographics, business characteristics, costs and production information from twenty-three tree-length logging firms in six southern states from 1988 to 1994. Firms were evaluated in regard to the economic efficiency with which they converted inputs - dollars of capital, consumables, labor, overhead and insurance and contract hauling - into outputs - tons of wood delivered to the mill. While the firms exhibited a wide range of efficiency, average annual efficiency of all firms combined seemed to be relatively stable for the time period. Firms delivered between 20,000 and 250,000 tons of wood annually with a median of 61,000 tons. Coastal plain operations tended to be the largest, followed by piedmont, then Appalachian mountain operations. Annual production as a function of annual expenditures showed no obvious economies of scale in operation size. Most contractors increased annual production during the study, five contractors had production levels in the final year of the study that were less than their first year. Efficiency generally improved in firms that increased production gradually through better utilization of existing capacity. Contractors expanding their operations to increase productivity seemed to suffer efficiency losses more often than gains. Those firms that hauled their own wood had higher efficiencies than firms that contracted out trucking. There were no significant efficiency differences between loggers in the three physiographic regions within their respective trucking strategies. Efficiency generally declined as average annual hauling distance increased, however a regression equation explained only 18% of the variation in total economic efficiency. / Master of Science

Thesis (MBA.) -- University of Limpopo, 2016 / The objective of this study was to determine the environmental impact of agricultural inputs, to know if the environmental impacts of agricultural inputs have environmental costs, and to know who bears the environmental costs of agricultural inputs. Using a purposive sampling method, the researcher studied six farms from Chief Albert Luthuli Municipal area, Mpumalanga. The research design for the study was a mix of qualitative and quantitative research approaches. Data collection was from primary and secondary sources. Data was collected from the six farmers in Albert Lithulu, in addition secondary data was collected from the archives of Index Mundi, the University of Pretoria, the US EPA and the World Bank. Using a mix of correlation and regression analysis, findings from the study provided an answer to the three research objectives. Findings from the analysis of correlation and regression indicated that agricultural input (fertilizer, used in this study) does affect the environment; it causes an agricultural induced emission of greenhouse gases (nitrous oxide and methane). Furthermore, findings from analysis of potential environmental costs of environmental impacts (methane and nitrous oxide) showed that agricultural inputs have social costs for South Africa. Furthermore, the final findings in this study showed that the environmental costs from agricultural inputs are born by the victims. Consequently the study recommends additional environmental regulation to enable farmers internalise some of the environmental costs of agricultural inputs that are born by victims. Further research is suggested to determine the model that may be used to internalise environmental costs of agricultural inputs back to the farms. Key Words: farms, environmental costs, agricultural inputs, externalities

Continued escalation in health care expenditures in the United States has led to an unsustainable model that consumes almost 20% of GDP. Policymakers have recognized the need for industry reform and have taken action through the passage of the Affordable Care Act (ACA). The purpose of this quantitative, longitudinal study was to examine the relationship between the type of health insurance and health care costs. Mechanism theory and game theory provided the theoretical framework. The analysis of secondary data from the Healthcare Cost and Utilization Project included a sample of 1,956,790-inpatient hospital stays from 2007 to 2014. Results of one-way ANOVAs indicated that between 2% and 9% of health care costs could be attributed to type of health insurance, a statistically significant finding. Results also supported the effectiveness of the ACA in stabilizing health care costs. The average annual rate of health care cost increase was 38.6% from 2007 until 2010, decreasing to an average annual increase of 4.3% from 2011 until 2014. Results provide important information to generate positive social change for consumers, providers, and policymakers. This includes improving decisions related to health care costs, improved understanding of the costs of health care services, increased transparency, increased patient engagement, maximizing consumer utility, facilitation of reduction of waste within the industry, and increased understanding of the impact of health policy on health care costs and efficiencies within newly created health policies. Results may also improve transparency of health care costs, which allows consumers, providers, and policymakers to take specific action to reduce health care costs, resulting in a more just and sustainable health care model.

An analytical approach for explaining the variability in labour intensive construction operations has been developed. A consistent method of collecting productivity developed jointly at the Pennsylvania State University and the University of Dundee has been refined and tested. Data has been collected daily from seven Scottish sites for continuous periods of up to 3 months. Not only productivity but many of the factors affecting it have been measured. A comprehensive, computerised database has been designed to facilitate data storage and manipulation. The quantification of the impact of each individual factor is based on the assumption that deviations from an operative?s normal output arise because of disturbances imposed by a multiplicity of site factors. The impact of each individual factor causes the average daily productivity to change.

Thesis (Ph.D.) -- University of Western Sydney, 2004. / Includes bibliography.