The Cycle Times of Working Capital: Financial Value Chain Analysis Method

Interest towards working capital management increased among practitioners and researchers because the financial crisis of 2008 caused the deterioration of the general financial situation. The importance of managing working capital effectively increased dramatically during the financial crisis. On one hand, companies highlighted the importance of working capital management as part of short-term financial management to overcome funding difficulties. On the other hand, in academia, it has been highlighted the need to analyze working capital management from a wider perspective namely from the value chain perspective. Previously, academic articles mostly discussed working capital management from a company-centered perspective. The objective of this thesis was to put working capital management in a wider and more academic perspective and present case studies of the value chains of industries as instrumental in theoretical contributions and practical contributions as complementary to theoretical contributions and conclusions. The principal assumption of this thesis is that selffinancing of value chains can be established through effective working capital management. Thus, the thesis introduces the financial value chain analysis method which is employed in the empirical studies. The effectiveness of working capital management of the value chains is studied through the cycle time of working capital. The financial value chain analysis method employed in this study is designed for considering value chain level phenomena. This method provides a holistic picture of the value chain through financial figures. It extends the value chain analysis to the industry level. Working capital management is studied by the cash conversion cycle that measures the length (days) of time a company has funds tied up in working capital, starting from the payment of purchases to the supplier and ending when remittance of sales is received from the customers. The working capital management practices employed in the automotive, pulp and paper and information and communication technology industries have been studied in this research project. Additionally, the Finnish pharmaceutical industry is studied to obtain a deeper understanding of the working capital management of the value chain. The results indicate that the cycle time of working capital is constant in the value chain context over time. The cash conversion cycle of automotive, pulp and paper, and ICT industries are on average 70, 60 and 40 days, respectively. The difference is mainly a consequence of the different cycle time of inventories. The financial crisis of 2008 affected the working capital management of the industries similarly. Both the cycle time of accounts receivable and accounts payable increased between 2008 and 2009. The results suggest that the companies of the automotive, pulp and paper and ICT value chains were not able to self-finance. Results do not indicate the improvement of value chains position in regard to working capital management either. The findings suggest that companies operating in the Finnish pharmaceutical industry are interested in developing their own working capital management, but collaboration with the value chain partners is not considered interesting. Competition no longer occurs between individual companies, but between value chains. Therefore the financial value chain analysis method introduced in this thesis has the potential to support value chains in improving their competitiveness.

Application of the direct Liapunov method to the problem of symmetric stability in the atmosphere

The problem of symmetric stability is examined within the context of the direct Liapunov method. The sufficient conditions for stability derived by Fjørtoft are shown to imply finite-amplitude, normed stability. This finite-amplitude stability theorem is then used to obtain rigorous upper bounds on the saturation amplitude of disturbances to symmetrically unstable flows.By employing a virial functional, the necessary conditions for instability implied by the stability theorem are shown to be in fact sufficient for instability. The results of Ooyama are improved upon insofar as a tight two-sided (upper and lower) estimate is obtained of the growth rate of (modal or nonmodal) symmetric instabilities.The case of moist adiabatic systems is also considered.

Group analysis method for fission track thermochronology

A methodology to obtain ages and thermal histories of sets of apatite samples from localities with geologically compatible characteristics is described. A methodology exploring the fact that samples with similar geological characteristics should present the same thermal history is proposed. This approach can contribute for the obtainment of more conclusive results by analysing fewer samples than it is necessary when the samples are individually analysed. In order to determine the ages, we use the absolute neutron dosimetry through thin films of natural uranium along with lambda(f) = 8.46 x 10(-17) a(-1). As an example of application of the proposed methodology, we analyse samples collected in a Brazilian region, Sao Francisco Craton, which experienced low tectonic activity. (C) 2008 Elsevier Ltd. All rights reserved.

Thermoeconomic analysis method for optimization of combined heat and power systems

This article presents an thermoeconomic analysis of cogeneration plants, applied as a rational technique to produce electric power and saturated steam. The aim of this new methodology is the minimum exergetic manufacturing cost (EMC), based on the Second Law of Thermodynamics. The decision variables selected for the optimization are the pressure and the temperature of the steam leaving the boiler in the case of using steam turbine, and the pressure ratio, turbine exhaust temperature and mass flow in the case of using gas turbines. The equations for calculating the capital costs of the components and products are formulated as a function of these decision variables. An application of the method using real data of a multinational chemical industry located in São Paulo state is presented. The conditions which establish the minimum cost are presented as finals conclusions.

Thermoeconomic analysis method for optimization of combined heat and power systems - part II

In this paper, a thermoeconomic functional analysis method based on the Second Law of Thermodynamics and applied to analyze four cogeneration systems is presented. The objective of the developed technique is to minimize the operating costs of the cogeneration plant, namely exergetic production cost (EPC), assuming fixed rates of electricity production and process steam in exergy base. In this study a comparison is made between the same four configurations of part I. The cogeneration system consisting of a gas turbine with a heat recovery steam generator, without supplementary firing, has the lowest EPC. (C) 2004 Published by Elsevier Ltd.

Thermoeconomic analysis method for optimization of combined heat and power systems. Part I

This article presents a thermoeconomic analysis of cogeneration plants, applied as a rational technique to produce electric power and saturated steam. The aim of this new methodology is the minimum Exergetic Production Cost (EPC), based on the Second Law of Thermodynamics. The variables selected for the optimization are the pressure and the temperature of the steam leaving the boiler in the case of using steam turbine, and the pressure ratio, turbine exhaust temperature and mass flow in the case of using gas turbines. The equations for calculating the capital costs of the components and products are formulated as a function of these decision variables. An application of the method using real data of a multinational chemical industry located in São Paulo state is presented. The conditions which establish the minimum cost are presented as final output. (C) 2003 Elsevier Ltd. All rights reserved.

Direct analysis of biodiesel microemulsions using an inductively coupled plasma mass spectrometry

An analytical procedure for direct introduction of biodiesel samples into an inductively coupled plasma mass spectrometer (ICP-MS) by using microemulsion for sample preparation was developed here. Cadmium, Co, Cu, Mn, Ni, Pb, Ti, and Zn were determined in biodiesel microemulsified samples prepared from different oleaginous sources (African palm, castor beans, palm, soybeans and an unknown oleaginous). Microemulsions were prepared using 0.25 mL Triton X-100, 0.25 mL 20% v v(-1) HNO(3), 0.50 mL biodiesel sample and 4.0 mL n-propanol. Argon-oxygen mixture was added to the plasma as auxiliary gas for correcting matrix effects caused by the high carbon load due to biodiesel microemulsions. The oxygen gas flow rate was set in 37.5 mL min(-1). The accuracy of the developed procedure was evaluated by applying addition-recovery experiments for biodiesel samples from different sources. Recoveries varied from 76.5 to 116.2% for all analytes but Zn in castor beans biodiesel sample (65.0 to 76.2%). Recoveries lower than 86.6% were obtained for palm biodiesel sample, probably due to matrix effects. Detection limits calculated by using oxygen in the composition of the auxiliary gas added to the plasma were higher than those calculated without using it, probably due to the highest formation of oxides. Despite oxides formation, best analytical performance was reached by using oxygen as auxiliary gas and by proper correction of transport interferences. The developed procedure based on microemulsion formation was suitable for direct introduction of biodiesel samples in ICP-MS. (C) 2010 Elsevier B.V. All rights reserved.

Isotope analysis method (δ¹³C) in clarified apple juice

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Isotopic analysis method (δ13C) in apple-flavoured soft drinks

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Continuous Flow Analysis Method for Determination of Dissolved Reactive Phosphorus in Ice Cores

Phosphorus (P) is an essential macronutrient for all living organisms. Phosphorus is often present in nature as the soluble phosphate ion PO43– and has biological, terrestrial, and marine emission sources. Thus PO43– detected in ice cores has the potential to be an important tracer for biological activity in the past. In this study a continuous and highly sensitive absorption method for detection of dissolved reactive phosphorus (DRP) in ice cores has been developed using a molybdate reagent and a 2-m liquid waveguide capillary cell (LWCC). DRP is the soluble form of the nutrient phosphorus, which reacts with molybdate. The method was optimized to meet the low concentrations of DRP in Greenland ice, with a depth resolution of approximately 2 cm and an analytical uncertainty of 1.1 nM (0.1 ppb) PO43–. The method has been applied to segments of a shallow firn core from Northeast Greenland, indicating a mean concentration level of 2.74 nM (0.26 ppb) PO43– for the period 1930–2005 with a standard deviation of 1.37 nM (0.13 ppb) PO43– and values reaching as high as 10.52 nM (1 ppb) PO43–. Similar levels were detected for the period 1771–1823. Based on impurity abundances, dust and biogenic particles were found to be the most likely sources of DRP deposited in Northeast Greenland.

Laser-induced breakdown spectroscopy quantitative analysis method via adaptive analytical line selection and relevance vector machine regression model

Abstract A new LIBS quantitative analysis method based on analytical line adaptive selection and Relevance Vector Machine (RVM) regression model is proposed. First, a scheme of adaptively selecting analytical line is put forward in order to overcome the drawback of high dependency on a priori knowledge. The candidate analytical lines are automatically selected based on the built-in characteristics of spectral lines, such as spectral intensity, wavelength and width at half height. The analytical lines which will be used as input variables of regression model are determined adaptively according to the samples for both training and testing. Second, an LIBS quantitative analysis method based on RVM is presented. The intensities of analytical lines and the elemental concentrations of certified standard samples are used to train the RVM regression model. The predicted elemental concentration analysis results will be given with a form of confidence interval of probabilistic distribution, which is helpful for evaluating the uncertainness contained in the measured spectra. Chromium concentration analysis experiments of 23 certified standard high-alloy steel samples have been carried out. The multiple correlation coefficient of the prediction was up to 98.85%, and the average relative error of the prediction was 4.01%. The experiment results showed that the proposed LIBS quantitative analysis method achieved better prediction accuracy and better modeling robustness compared with the methods based on partial least squares regression, artificial neural network and standard support vector machine.