Suchergebnisse

While planning and control and their impact on small firm growth are implicit in many academic discussions, much of our understanding of these phenomena are based on speculation and opinion. Thus, they seem neglected areas of small business research. This paper seeks to improve the understanding of formal planning and control systems and their relationship to the growth of small business in Australian manufacturing. First, a framework is developed which incorporates the main contextual variables which independently and simultaneously have been shown to have a major relationship with growth. Second, the study provides empirically-based qualitative evidence to further the understanding of causality in the growth of small business by focusing on how formal planning and control systems are embedded within the external or internal contextual variables of small business and the characteristics of their management. Evidence is also provided as to the conditions and circumstances under which formal planning and control are likely to be most effective in controlling the effects of contextual variables, and to the differences between high growth and low growth firms in the use of formal planning and control. The findings of this study are important for two principal reasons. First, it has provided the opportunity to conduct exploratory research into how a small business is managed within the context in which the processes are applied. Second, it has provided the opportunity to identify factors which encourage or discourage small firms to plan, thus providing a better understanding of the planning and control process adopted by small firms.

In this work, we present a methodology for measuring and optimizing the credit risk of a loan portfolio taking into account the non‐normality of the credit loss distribution. In particular, we aim at modelling accurately joint default events for credit assets. In order to achieve this goal, we build the loss distribution of the loan portfolio by Monte Carlo simulation. The times until default of each obligor in portfolio are simulated following a copula‐based approach. In particular, we study four different types of dependence structure for the credit assets in portfolio: the Gaussian copula, the Student's t‐copula, the grouped t‐copula and the Clayton n‐copula (or Cook–Johnson copula). Our aim is to assess the impact of each type of copula on the value of different portfolio risk measures, such as expected loss, maximum loss, credit value at risk and expected shortfall. In addition, we want to verify whether and how the optimal portfolio composition may change utilizing various types of copula for describing the default dependence structure. In order to optimize portfolio credit risk, we minimize the conditional value at risk, a risk measure both relevant and tractable, by solving a simple linear programming problem subject to the traditional constraints of balance, portfolio expected return and trading. The outcomes, in terms of optimal portfolio compositions, obtained assuming different default dependence structures are compared with each other. The solution of the risk minimization problem may suggest us how to restructure the inefficient loan portfolios in order to obtain their best risk/return profile. In the absence of a developed secondary market for loans, we may follow the investment strategies indicated by the solution vector by utilizing credit default swaps.

Abstract: This paper concentrates on the regulation of charitable organisations in the state of Victoria, where governments have sought to determine the bona fides of these organisations by obtaining their financial reports. A survey of the financial reports of registered Victorian charities indicates, however, that a significant proportion of charities do not supply this information. This deficiency indicates that government judgements about the bona fides of organisations cannot always be made, and the efficiency of regulation is therefore questioned. Other shortcomings in the regulation of charities are also identified. These include the problems incurred in seeking to implement these regulations and those which arise through the enforcement of the regulations themselves.

[Abstract] The performance of powertrain components in electric vehicles is tightly intertwined with their thermal behavior. In practical applications, their temperature must be monitored and kept below certain thresholds to avoid performance drops and failure. Sensors, however, cannot always be placed at critical locations. Instead, it is possible to use numerical models to estimate relevant magnitudes during system operation. Thermal effects in electric and electronic components can be represented in a compact way using lumped-parameter equivalent circuits. These can be combined with sensor readings from the device under study to develop digital twins and use them to monitor temperatures during test and operation. In this paper, we put forward a method to generate thermal digital twins of e-powertrain elements such as power inverters. The thermal equivalent circuit equations are obtained from a general-purpose simulation software tool and optimized to enable real-time execution. Kalman filters are then used to fuse the simulation results from this model and sensor measurements of component temperatures. The proposed method provides a way to estimate the inputs and parameters of the thermal circuit and can be used to avoid the drift of the simulation away from actual component behavior. The performance of this approach is demonstrated with a simple benchmark example and the thermal equivalent circuit of a three-phase inverter. ; 10.13039/501100011688-High performant Wide Band Gap Power Electronics for Reliable, energy efficient drivetrains and Optimization through Multi-physics simulation (HiPERFORM) Project through the Electronic Components and Systems for European Leadership (ECSEL) Joint Undertaking (Grant Number: 783174) 10.13039/501100009598-AVL List GmbH through the University Partnership Program 10.13039/501100007136-Ministry of Economy of Spain through "Técnicas de co-simulación en tiempo real para bancos de ensayo en automoción" Project (Grant Number: TRA2017-86488-R) 10.13039/501100007136-Ramón y Cajal Program (Grant Number: RYC-2016-20222) 10.13039/501100010801-Galician Government (Grant Number: ED431B2016/031) ; Xunta de Galicia; ED431B2016/031