Applying Target Costing in the Development of Marketable and Environmentally Friendly Products from Swine Waste

Management of swine waste generated in the United States is a challenging problem facing engineers, farmers, scientists, regulators, and policy-makers. Technologies for processing and storing swine waste have not been fully developed and refined in a manner acceptable to the public and environmental regulators. The primary concerns with improperly disposed swine waste are the effects on human and livestock health, surface and groundwater quality, air quality, and conservation of nitrogen fertilizers (Hagenstein 2003 Hagenstein, P. R. 2003. Air Emissions from Animal Feeding Operations: Current Knowledge, Future Needs, Washington, D. C.: National Research Council, National Academy Press.  [Google Scholar]).

The purpose of this study is to demonstrate the concept of target costing by applying it to a very specific example: the production of biomethanol from swine manure. This study summarizes the analyses that outline a design and calculate a preliminary cost estimate for a proposed system for producing biomethanol from swine manure (initial process). In this study the target costing process is demonstrated with calculation of a target cost. This article also demonstrates an application of value engineering as a systematic, interdisciplinary examination of factors affecting the cost of a product so as to find means to fulfill the product's specified purpose at the required standards of quality and reliability and at an acceptable cost.

The article is organized as follows. First, the purpose of applying target costing methodology to the development of marketable by-products from swine manure is outlined. Next, target cost is calculated for biomethanol made from swine manure based on current methanol prices and currently available subsidies for biomethanol made from swine manure. A system for producing biomethanol from swine manure is described. The current cost is calculated for producing biomethanol. Concepts of value engineering are employed to reduce a significant cost component of the initial process resulting in Process II. Finally, value engineering is employed the second time to further reduce the cost of Process II yielding Process III.     

A NOTE ON BIAS IN CAPITAL BUDGETING INTRODUCED BY STOCHASTIC LIFE

This note extends work by Young and Contreras and by Rosenthal on the present worth of cash flows under uncertain timing. In capital budgeting analysis, the use of the expected life of a project instead of the life distribution of the project biases the estimate of its expected net present value. In most situations the bias results in an overestimate of the expected net present value of the project. When the exact life distribution is unknown, the bias can be approximated by Taylor series expansion. The sensitivity of the bias to the discount rate, to cash flow patterns, and to income taxes is also investigated.     

高新技术企业价值评估方法探析

高新技术产业由于技术含量高及高风险、高收益等特点,已经成为知识经济时代的主要支柱,高新技术企业价值评估成为资本领域的核心问题。针对高新技术企业自身的特点,本文指出了目前传统的企业价值评估方法存在的问题即难以客观地评估高新技术企业价值,提出了引入模糊数学方法来改进高新技术企业价值评估的计算,从而使高新技术企业评估方法更科学、更合理。     

The impact of OEM supplier initiatives on buyer competence development: The moderating roles of collaborative relationship and competitive environment

This paper explains the impact of original equipment manufacturing (OEM) supplier initiatives, which are proactive and deliberate behaviors, on buyer competence development. It argues that these adaptive and proactive behaviors in the outsourcing relationship have a significant impact on buyers’ competence development. The sample population consisted of 800 OEM suppliers in Taiwan. SPSS was used to examine the causal relationships among the variables. The empirical results indicate that OEM supplier initiatives have a positive effect on buyer competence development. In addition, two of three collaborative relationship variables—information sharing and long-term collaboration—foster the relationship between OEM supplier initiatives and buyer competence development. However, the moderating role of competitive environment has a negative effect on this relationship.     

Discrete credit barrier models

The model introduced in this article is designed to provide a consistent representation for both the real-world and pricing measures for the credit process. We find that good agreement with historical and market data can be achieved across all credit ratings simultaneously. The model is characterized by an underlying stochastic process that takes on values on a discrete lattice and represents credit quality. Rating transitions are associated with barrier crossings and default events are associated with an absorbing state. The stochastic process has state-dependent volatility and jumps which are estimated by using empirical migration and default rates. A risk-neutralizing drift is estimated to consistently match the average spread curves corresponding to all the various ratings.     

Modeling default risk with support vector machines

Predicting default risk is important for firms and banks to operate successfully. There are many reasons to use nonlinear techniques for predicting bankruptcy from financial ratios. Here we propose the so-called Support Vector Machine (SVM) to predict the default risk of German firms. Our analysis is based on the Creditreform database. In all tests performed in this paper the nonlinear model classified by SVM exceeds the benchmark logit model, based on the same predictors, in terms of the performance metric, AR. The empirical evidence is in favor of the SVM for classification, especially in the linear non-separable case. The sensitivity investigation and a corresponding visualization tool reveal that the classifying ability of SVM appears to be superior over a wide range of SVM parameters. In terms of the empirical results obtained by SVM, the eight most important predictors related to bankruptcy for these German firms belong to the ratios of activity, profitability, liquidity, leverage and the percentage of incremental inventories. Some of the financial ratios selected by the SVM model are new because they have a strong nonlinear dependence on the default risk but a weak linear dependence that therefore cannot be captured by the usual linear models such as the DA and logit models.     

Better cross hedges with composite hedging? Hedging equity portfolios using financial and commodity futures

Unless a direct hedge is available, cross hedging must be used. In such circumstances portfolio theory implies that a composite hedge (the use of two or more hedging instruments to hedge a single spot position) will be beneficial. The study and use of composite hedging has been neglected; possibly because it requires the estimation of two or more hedge ratios. This paper demonstrates a statistically significant increase in out-of-sample effectiveness from the composite hedging of the Amex Oil Index using S&P500 and New York Mercantile Exchange crude oil futures. This conclusion is robust to the technique used to estimate the hedge ratios, and to allowance for transactions costs, dividends and the maturity of the futures contracts.     

Identifying reference companies using the book-to-market ratio: a minimum spanning tree approach

There is substantial evidence to suggest that the book-to-market (BM) ratio is an important factor in explaining stock market returns. Its role has proved difficult to isolate, however, due to statistical problems in its construction and to its observational equivalence to a number of risk and behavioural explanations. In addition, now widely recognised complex behaviour in financial markets has called into question modelling approaches that are limited in their ability to uncover relationships that are possibly masked during financial crises, for example. As one response, our research explores the value of a newly applied technique which examines the topological properties of minimum spanning trees as applied to both the BM ratio and market returns. Our intention is to identify and report investment signals as determined by the BM ratio and to assess the relationships of these signals to returns outcomes. The approach enables highly nonlinear behaviour to be addressed and the relationships we set out to capture to be reported in novel ways. We motivate and evidence a previously unreported role for BM as an investment signal which is effective over varying stock market conditions, including the financial crisis that began in 2008.