Analyzing customer profitability: an empirical study

The purpose of this study was to define the customer profitability of the case company as well as to specify the factors that explain customer profitability. The study was made with a quantitative research method. The research hypotheses were formulated mainly on the grounds of previous research, and were tested with statistical research methods. The research results showed that customer profitability is not equally distributed among the customers of the case company, and the majority of its customers is profitable. The interpreters for absolute customer profitability were sales volume and the customer’s location region. The interpreters for relative customer profitability were the customer’s location region and the product segment into which a customer can be classified on the basis of the products that were sold to this customer.

Kannattavuuden arviointi ja kehittäminen elementtiliiketoiminnassa

Kirjallisuus tukee näkemystä hyvän kannattavuuden positiivisesta merkityksestä yritykselle. Näin sen merkitystä ei voida sivuuttaa menestystekijänä yrityksen kilpailukyvylle ja jatkuvuudelle. Tutkimuksen case-organisaatiossa kannattavuus on ollut heikko jo kolmella viimeisellä tilikaudella. Pitkään jatkuessaan heikko kannattavuus voi johtaa taloudellisiin ongelmiin, joten olisi löydettävä keinot kääntää tulos jälleen positiiviseksi. Tutkimuksen tavoitteina on tutkia mitä kannattavuus on, miten sitä voidaan mitata ja arvioida sekä mitä keinoja on parantaa kannattavuutta. Lisäksi tutkitaan miten soveltaa näitä teoriapohjaisia keinoja tutkimuksen case-organisaatiossa sen kannattavuuden analysoinnin sekä parantamisen kontekstissa. Tutkimuksen teoria aineisto kerätään kannattavuutta käsittelevästä kirjallisuudesta. Empiirinen tutkimus suoritetaan case-organisaation tuottamaa informaatiota hyödyntäen, kyselytutkimuksella sekä tutkijan havainnoin n.12 vuoden ajalta case-organisaation palveluksessa. Kirjallisuus esittää useamman tavan kannattavuuden parantamiseen. Kaikki esitetyt tavat eivät sellaisinaan sovellu case-organisaation kannattavuuden parantamiseen. Tutkimus esittää toiminnan luonteen ja toimintaympäristön huomioiden mahdollisia sopivia keinoja kehittää kannattavuutta.

The role of advance payments in working capital management and profitability

The objective of this thesis is to study the role of received advance payments in working capital management by creating a new measurement and to study the relationship between advance payments and profitability. The study has been conducted using narrative literature review and quantitative research methods. The research was made analyzing 108 companies listed in Helsinki Stock Exchange. The results indicate that 68 % of the studied companies are receiving advance payments and the average cycle time for received advance payments is 13 days. A new key figure is created to include received advance payments into the calculation of working capital. Received advance payments shorten the working capital cycle, by 13 days, when they are used in the calculation. The role of advance payments is not as significant as the role of receivables and inventories but advance payments may have a larger role than payables if the company is receiving noticeable amounts of advance payments. There are three branches where companies are receiving more advance payments than average companies. The branches are project business and ICT and publishing sectors. There is a negative correlation between profitability and advance payments based on the results of this study.

Analyzing the Effects of the New Renewable Energy Policy in Russia on Investments into Wind, Solar and Small Hydro Power

This thesis presents an analysis of recently enacted Russian renewable energy policy based on capacity mechanism. Considering its novelty and poor coverage by academic literature, the aim of the thesis is to analyze capacity mechanism influence on investors’ decision-making process. The current research introduces a number of approaches to investment analysis. Firstly, classical financial model was built with Microsoft Excel® and crisp efficiency indicators such as net present value were determined. Secondly, sensitivity analysis was performed to understand different factors influence on project profitability. Thirdly, Datar-Mathews method was applied that by means of Monte Carlo simulation realized with Matlab Simulink®, disclosed all possible outcomes of investment project and enabled real option thinking. Fourthly, previous analysis was duplicated by fuzzy pay-off method with Microsoft Excel®. Finally, decision-making process under capacity mechanism was illustrated with decision tree. Capacity remuneration paid within 15 years is calculated individually for each RE project as variable annuity that guarantees a particular return on investment adjusted on changes in national interest rates. Analysis results indicate that capacity mechanism creates a real option to invest in renewable energy project by ensuring project profitability regardless of market conditions if project-internal factors are managed properly. The latter includes keeping capital expenditures within set limits, production performance higher than 75% of target indicators, and fulfilling localization requirement, implying producing equipment and services within the country. Occurrence of real option shapes decision-making process in the following way. Initially, investor should define appropriate location for a planned power plant where high production performance can be achieved, and lock in this location in case of competition. After, investor should wait until capital cost limit and localization requirement can be met, after that decision to invest can be made without any risk to project profitability. With respect to technology kind, investment into solar PV power plant is more attractive than into wind or small hydro power, since it has higher weighted net present value and lower standard deviation. However, it does not change decision-making strategy that remains the same for each technology type. Fuzzy pay-method proved its ability to disclose the same patterns of information as Monte Carlo simulation. Being effective in investment analysis under uncertainty and easy in use, it can be recommended as sufficient analytical tool to investors and researchers. Apart from described results, this thesis contributes to the academic literature by detailed description of capacity price calculation for renewable energy that was not available in English before. With respect to methodology novelty, such advanced approaches as Datar-Mathews method and fuzzy pay-off method are applied on the top of investment profitability model that incorporates capacity remuneration calculation as well. Comparison of effects of two different RE supporting schemes, namely Russian capacity mechanism and feed-in premium, contributes to policy comparative studies and exhibits useful inferences for researchers and policymakers. Limitations of this research are simplification of assumptions to country-average level that restricts our ability to analyze renewable energy investment region wise and existing limitation of the studying policy to the wholesale power market that leaves retail markets and remote areas without our attention, taking away medium and small investment into renewable energy from the research focus. Elimination of these limitations would allow creating the full picture of Russian renewable energy investment profile.

Matrix Support And Institutional Support: Analyzing Their Construction.

This is an analysis of the theoretical and practical construction of the methodology of Matrix Support by means of studies on Paideia Support (Institutional and Matrix Support), which is an inter-professional work of joint care in recent literature and official documents of the Unified Health System (SUS). An attempt was made to describe methodological concepts and strategies. A comparative analysis of Institutional Support and Matrix Support was also conducted using the epistemological framework of Field and Core Knowledge and Practices.

Analyzing the n→π* Electronic Transition of Formaldehyde in Water. A Sequential Monte Carlo/Time-Dependent Density Functional Theory

The n→π* absorption transition of formaldehyde in water is analyzed using combined and sequential classical Monte Carlo (MC) simulations and quantum mechanics (QM) calculations. MC simulations generate the liquid solute-solvent structures for subsequent QM calculations. Using time-dependent density functional theory in a localized set of gaussian basis functions (TD-DFT/6-311++G(d,p)) calculations are made on statistically relevant configurations to obtain the average solvatochromic shift. All results presented here use the electrostatic embedding of the solvent. The statistically converged average result obtained of 2300 cm-1 is compared to previous theoretical results available. Analysis is made of the effective dipole moment of the hydrogen-bonded shell and how it could be held responsible for the polarization of the solvent molecules in the outer solvation shells.

Food profitability affects intranidal recruitment behaviour in the stingless bee Nannotrigona testaceicornis

Does the food's sugar concentration affect recruitment behaviour in the stingless bee Nan-notrigona testaceicornis? We recorded intranidal forager behaviour while offering sugar water of constant, increasing, or decreasing concentrations. Running speed was not correlated with sugar concentration but the jostling contacts/sec were. Food profitability also affected the recruiter's thorax vibrations: Pulse duration and duty cycle followed both concentration increases and decreases. Sugar concentration also influenced the number of recruited bees. In comparison to the phylogenetically closely related Scaptotrigona, Nan-notrigona's intranidal recruitment behaviour showed a more elaborate association with food profitability. This is likely to reflect differences in ecology and foraging strategies as Nannotrigona - in contrast to Scaptotrigona - does not lay scent trails to guide recruits to a food source.

Predictability Analysis of Voice Signals Analyzing Healthy and Pathologic Samples

Research Foundation of the State of Sao Paulo (FAPESP)

Analyzing static three-dimensional elastic domains with a new infinite boundary element formulation

A new two-dimensionally mapped infinite boundary element (IBE) is presented. The formulation is based on a triangular boundary element (BE) with linear shape functions instead of the quadrilateral IBEs usually found in the literature. The infinite solids analyzed are assumed to be three-dimensional, linear-elastic and isotropic, and Kelvin fundamental solutions are employed. One advantage of the proposed formulation over quadratic or higher order elements is that no additional degrees of freedom are added to the original BE mesh by the presence of the IBEs. Thus, the IBEs allow the mesh to be reduced without compromising the accuracy of the result. Two examples are presented, in which the numerical results show good agreement with authors using quadrilateral IBEs and analytical solutions. (C) 2010 Elsevier Ltd. All rights reserved.

Exergy-based method for analyzing the composition of the electricity cost generated in gas-fired combined cycle plants

The proposed method to analyze the composition of the cost of electricity is based on the energy conversion processes and the destruction of the exergy through the several thermodynamic processes that comprise a combined cycle power plant. The method uses thermoeconomics to evaluate and allocate the cost of exergy throughout the processes, considering costs related to inputs and investment in equipment. Although the concept may be applied to any combined cycle or cogeneration plant, this work develops only the mathematical modeling for three-pressure heat recovery steam generator (HRSG) configurations and total condensation of the produced steam. It is possible to study any n x 1 plant configuration (n sets of gas turbine and HRSGs associated to one steam turbine generator and condenser) with the developed model, assuming that every train operates identically and in steady state. The presented model was conceived from a complex configuration of a real power plant, over which variations may be applied in order to adapt it to a defined configuration under study [Borelli SJS. Method for the analysis of the composition of electricity costs in combined cycle thermoelectric power plants. Master in Energy Dissertation, Interdisciplinary Program of Energy, Institute of Eletro-technical and Energy, University of Sao Paulo, Sao Paulo, Brazil, 2005 (in Portuguese)]. The variations and adaptations include, for instance, use of reheat, supplementary firing and partial load operation. It is also possible to undertake sensitivity analysis on geometrical equipment parameters. (C) 2007 Elsevier Ltd. All rights reserved.

Variable Demand and Profitability in Service Companies: a case study in the information technology sector

Managing a variable demand scenario is particularly challenging on services organizations because services companies usually have a major part of fixed costs. The article studies how a services organization manages its demand variability and its relation with the organization`s profitability. Moreover, the study searched for alternatives used to reduce the demand variability`s impact on the profitability of the company. The research was based on a case study with a Brazilian services provider on information technology business. The study suggests that alternatives like using outsourced employees to cover demand peaks may bring benefits only on short term, reducing the profitability of the company on long term: Some options are revealed, like the internationalization of employees and the investment on developing its own workforce.

Analyzing the connectivity between regions of interest: An approach based on cluster Granger causality for NRI data analysis

The identification, modeling, and analysis of interactions between nodes of neural systems in the human brain have become the aim of interest of many studies in neuroscience. The complex neural network structure and its correlations with brain functions have played a role in all areas of neuroscience, including the comprehension of cognitive and emotional processing. Indeed, understanding how information is stored, retrieved, processed, and transmitted is one of the ultimate challenges in brain research. In this context, in functional neuroimaging, connectivity analysis is a major tool for the exploration and characterization of the information flow between specialized brain regions. In most functional magnetic resonance imaging (fMRI) studies, connectivity analysis is carried out by first selecting regions of interest (ROI) and then calculating an average BOLD time series (across the voxels in each cluster). Some studies have shown that the average may not be a good choice and have suggested, as an alternative, the use of principal component analysis (PCA) to extract the principal eigen-time series from the ROI(s). In this paper, we introduce a novel approach called cluster Granger analysis (CGA) to study connectivity between ROIs. The main aim of this method was to employ multiple eigen-time series in each ROI to avoid temporal information loss during identification of Granger causality. Such information loss is inherent in averaging (e.g., to yield a single ""representative"" time series per ROI). This, in turn, may lead to a lack of power in detecting connections. The proposed approach is based on multivariate statistical analysis and integrates PCA and partial canonical correlation in a framework of Granger causality for clusters (sets) of time series. We also describe an algorithm for statistical significance testing based on bootstrapping. By using Monte Carlo simulations, we show that the proposed approach outperforms conventional Granger causality analysis (i.e., using representative time series extracted by signal averaging or first principal components estimation from ROIs). The usefulness of the CGA approach in real fMRI data is illustrated in an experiment using human faces expressing emotions. With this data set, the proposed approach suggested the presence of significantly more connections between the ROIs than were detected using a single representative time series in each ROI. (c) 2010 Elsevier Inc. All rights reserved.