A heuristic framework for ratio-based modelling of corporate collapse

This paper draws on empirical evidence to demonstrate that a heuristic framework signals collapse with significantly higher accuracy than the traditional static approach. Using a sample of 494 US publicly listed companies comprising 247 collapsed matched with 247 financially healthy ones, a heuristic framework is decisively superior the closer one gets to the event of collapse, culminating in 12.5% more overall accuracy than a static approach during
the year of collapse. An even more dramatic improvement occurs in relation to reduction of Type I error, with a heuristic framework delivering an improvement of 66.7% over its static counterpart.

Environmental sustainability orientation and financial resources of small manufacturing firms in the Philippines

Purpose - This study challenges the conventional view that resources determine the extent of environmental sustainability orientation (ESO) of small firms in a developing Southeast Asian country context. First, this study attempts to develop a measurement model of ESO of small firms in the manufacturing sector in the Philippines. Second, the study explores the impact of the financial resources on the ESO of firms.

Design/methodology/approach - The study uses survey data from 166 small manufacturing firms in three Philippine cities. Multiple regression modelling is used to estimate the relationships between firm resources and ESO.

Findings - The results indicate that ESO is a multi-dimensional construct with three facets: awareness of, actions for, and appreciation of environmental sustainability. The empirical evidence does not support the conventional firm resources – ESO proposition.

Research limitations/implications - A proactive ESO is not necessarily beyond the reach of resource-constrained small firms. The generalisability of the findings however is limited to small manufacturing firms in the Philippines.

Practical implications - This study informs owner-managers of small firms that a proactive ESO does not largely depend on financial resources. Government policies and programs to encourage small firms to become sustainable should not only focus on financial forms of assistance.

Originality/value -  To date, this is the only Philippine-based study and one of the scarce small firm-focused studies that examine the proposition that small firms are unable to pursue a proactive ESO due to resource-constraints.

Modelling SME credit risk : a Thai empirical evidence

This paper develops and tests a model to predict small and medium enterprise (SME) financial distress based on empirical evidence from Thailand. A sample comprising 198 financial statements of non-financially distressed and 68 statements of financially distressed SMEs were used. A parametric t-test was conducted to establish differences between financial characteristics of the two groups of SMEs.

Results show statistically significant differences (t values significant at .001) between the two groups of SMEs in the financial ratios used for the study. Discriminant analysis was then conducted to develop a model for predicting the likelihood of an SME experiencing financial distress.

The model hits an accuracy level of 97%, which compares favourably with the probability of accurate classification by chance (i.e., 65% after adjusting for the unequal sample sizes of the two groups of SMEs). A test of the model with a new sample shows the validity of the model beyond the original sample, confirming that Thai SME financial distress is amenable to prediction to a statistically significant extent. The model is expected to serve SME managers and creditors in assessing financial health of SMEs before making important decisions. The results are also expected to inform policymakers in formulating economic policies concerning SMEs.

Modelling, simulation and optimization of maintenance considerations on condition based maintenance

Globalization has increased the pressure on organizations and companies to operate in the most efficient and economic way. This tendency promotes that companies concentrate more and more on their core businesses, outsource less profitable departments and services to reduce costs. By contrast to earlier times, companies are highly specialized and have a low real net output ratio. For being able to provide the consumers with the right products, those companies have to collaborate with other suppliers and form large supply chains. An effect of large supply chains is the deficiency of high stocks and stockholding costs. This fact has lead to the rapid spread of Just-in-Time logistic concepts aimed minimizing stock by simultaneous high availability of products. Those concurring goals, minimizing stock by simultaneous high product availability, claim for high availability of the production systems in the way that an incoming order can immediately processed. Besides of design aspects and the quality of the production system, maintenance has a strong impact on production system availability. In the last decades, there has been many attempts to create maintenance models for availability optimization. Most of them concentrated on the availability aspect only without incorporating further aspects as logistics and profitability of the overall system. However, production system operator’s main intention is to optimize the profitability of the production system and not the availability of the production system. Thus, classic models, limited to represent and optimize maintenance strategies under the light of availability, fail. A novel approach, incorporating all financial impacting processes of and around a production system, is needed. The proposed model is subdivided into three parts, maintenance module, production module and connection module. This subdivision provides easy maintainability and simple extendability. Within those modules, all aspect of production process are modeled. Main part of the work lies in the extended maintenance and failure module that offers a representation of different maintenance strategies but also incorporates the effect of over-maintaining and failed maintenance (maintenance induced failures). Order release and seizing of the production system are modeled in the production part. Due to computational power limitation, it was not possible to run the simulation and the optimization with the fully developed production model. Thus, the production model was reduced to a black-box without higher degree of details.

Formation of Exchange Rates on the Russian Market: Dynamics and Modelling

Galina Kovaleva. The Formation of the Exchange Rate on the Russian Market: Dynamics and Modelling. The Russian financial market is fast becoming one of the major sectors of the Russian economy. Assets have been increasing steadily, while new market segments and new financial market instruments have emerged. Kovaleva attempted to isolate the factors influencing exchange rates, determine patterns in the dynamic changes to the rouble/dollar exchange rate, construct models of the processes, and on the basis of these activities make forecasts. She studied the significance of economic indicators influencing the rouble/dollar exchange rate at different times, and developed multi-factor econometric models. In order to reveal the inner structure of the financial indicators and to work out ex-post forecasts for different time intervals, she carried out a series of calculations with the aim of constructing trend-cyclical (TC) and harmonic models, and Box and Jenkins models. She found that: 1. The Russian financial market is dependant on the rouble/dollar exchange rate. Its dynamics are formed under the influence of the short-term state treasury notes and government bonds markets, interbank loans, the rouble/DM exchange rate, the inflation rate, and the DM/dollar exchange rate. The exchange rate is influenced by sales on the Moscow Interbank Currency Exchange and the mechanism of those sales. 2. The TC model makes it possible to conduct an in-depth study of the structure of the processes and to make forecasts of the dynamic changes to currency indicators. 3. The Russian market is increasingly influenced by the world currency market and its prospects are of crucial interest for the world financial community.

A linked data approach to sentiment and emotion analysis of twitter in the financial domain

Sentiment analysis has recently gained popularity in the financial domain thanks to its capability to predict the stock market based on the wisdom of the crowds. Nevertheless, current sentiment indicators are still silos that cannot be combined to get better insight about the mood of different communities. In this article we propose a Linked Data approach for modelling sentiment and emotions about financial entities. We aim at integrating sentiment information from different communities or providers, and complements existing initiatives such as FIBO. The ap- proach has been validated in the semantic annotation of tweets of several stocks in the Spanish stock market, including its sentiment information.

Creating and modelling personal socio-economic networks in on-line banking

The banking industry is observing how new competitors threaten its millennial business model by targeting unbanked people, offering new financial services to their customer base, and even enabling new channels for existing services and customers. The knowledge on users, their behaviour, and expectations become a key asset in this new context. Well aware of this situation, the Center for Open Middleware, a joint technology center created by Santander Bank and Universidad Politécnica de Madrid, has launched a set of initiatives to allow the experimental analysis and management of socio-economic information. PosdataP2P service is one of them, which seeks to model the economic ties between the holders of university smart cards, leveraging on the social networks the holders are subscribed to. In this paper we describe the design principles guiding the development of the system, its architecture and some implementation details.

3D numerical modelling of acoustic horns using the method of fundamental solutions

In the present work, a three-dimensional (3D) formulation based on the method of fundamental solutions (MFS) is applied to the study of acoustic horns. The implemented model follows and extends previous works that only considered two-dimensional and axisymmetric horn configurations. The more realistic case of 3D acoustic horns with symmetry regarding two orthogonal planes is addressed. The use of the domain decomposition technique with two interconnected sub-regions along a continuity boundary is proposed, allowing for the computation of the sound pressure generated by an acoustic horn installed on a rigid screen. In order to reduce the model discretization requirements for these cases, Green’s functions derived with the image source methodology are adopted, automatically accounting for the presence of symmetry conditions. A strategy for the calculation of an optimal position of the virtual sources used by the MFS to define the solution is also used, leading to improved reliability and flexibility of the proposed method. The responses obtained by the developed model are compared to reference solutions, computed by well-established models based on the boundary element method. Additionally, numerically calculated acoustic parameters, such as directivity and beamwidth, are compared with those evaluated experimentally.

Exchange rate forecasting using a combined parametric and nonparametric self-organising modelling approach

Financial prediction has attracted a lot of interest due to the financial implications that the accurate prediction of financial markets can have. A variety of data driven modellingapproaches have been applied but their performance has produced mixed results. In this study we apply both parametric (neural networks with active neurons) and nonparametric (analog complexing) self-organisingmodelling methods for the daily prediction of the exchangerate market. We also propose acombinedapproach where the parametric and nonparametricself-organising methods are combined sequentially, exploiting the advantages of the individual methods with the aim of improving their performance. The combined method is found to produce promising results and to outperform the individual methods when tested with two exchangerates: the American Dollar and the Deutche Mark against the British Pound.

Evaluating the impact of design decisions on the financial performance of manufacturing companies

Product design decisions can have a significant impact on the financial and operation performance of manufacturing companies. Therefore good analysis of the financial impact of design decisions is required if the profitability of the business is to be maximised. The product design process can be viewed as a chain of decisions which links decisions about the concept to decisions about the detail. The idea of decision chains can be extended to include the design and operation of the 'downstream' business processes which manufacture and support the product. These chains of decisions are not independent but are interrelated in a complex manner. To deal with the interdependencies requires a modelling approach which represents all the chains of decisions, to a level of detail not normally considered in the analysis of product design. The operational, control and financial elements of a manufacturing business constitute a dynamic system. These elements interact with each other and with external elements (i.e. customers and suppliers). Analysing the chain of decisions for such an environment requires the application of simulation techniques, not just to any one area of interest, but to the whole business i.e. an enterprise simulation. To investigate the capability and viability of enterprise simulation an experimental 'Whole Business Simulation' system has been developed. This system combines specialist simulation elements and standard operational applications software packages, to create a model that incorporates all the key elements of a manufacturing business, including its customers and suppliers. By means of a series of experiments, the performance of this system was compared with a range of existing analysis tools (i.e. DFX, capacity calculation, shop floor simulator, and business planner driven by a shop floor simulator).

Before and after modelling:risk knowledge management is required

Risk and knowledge are two concepts and components of business management which have so far been studied almost independently. This is especially true where risk management is conceived mainly in financial terms, as, for example, in the banking sector. The banking sector has sophisticated methodologies for managing risk, such as mathematical risk modeling. However. the methodologies for analyzing risk do not explicitly include knowledge management for risk knowledge creation and risk knowledge transfer. Banks are affected by internal and external changes with the consequent accommodation to new business models new regulations and the competition of big players around the world. Thus, banks have different levels of risk appetite and policies in risk management. This paper takes into consideration that business models are changing and that management is looking across the organization to identify the influence of strategic planning, information systems theory, risk management and knowledge management. These disciplines can handle the risks affecting banking that arise from different areas, but only if they work together. This creates a need to view them in an integrated way. This article sees enterprise risk management as a specific application of knowledge in order to control deviation from strategic objectives, shareholders' values and stakeholders' relationships. Before and after a modeling process it necessary to find insights into how the application of knowledge management processes can improve the understanding of risk and the implementation of enterprise risk management. The article presents a propose methodology to contribute to providing a guide for developing risk modeling knowledge and a reduction of knowledge silos, in order to improve the quality and quantity of solutions related to risk inquiries across the organization.

Conceptual Building Information Modelling Framework for Whole‐house Refurbishment based on LCC and LCA

The UK government aims at achieving 80% CO2 emission reduction by 2050 which requires collective efforts across all the UK industry sectors. In particular, the housing sector has a large potential to contribute to achieving the aim because the housing sector alone accounts for 27% of the total UK CO2 emission, and furthermore, 87% of the housing which is responsible for current 27% CO2 emission will still stand in 2050. Therefore, it is essential to improve energy efficiency of existing housing stock built with low energy efficiency standard. In order for this, a whole‐house needs to be refurbished in a sustainable way by considering the life time financial and environmental impacts of a refurbished house. However, the current refurbishment process seems to be challenging to generate a financially and environmentally affordable refurbishment solution due to the highly fragmented nature of refurbishment practice and a lack of knowledge and skills about whole‐house refurbishment in the construction industry. In order to generate an affordable refurbishment solution, diverse information regarding costs and environmental impacts of refurbishment measures and materials should be collected and integrated in right sequences throughout the refurbishment project life cycle among key project stakeholders. Consequently, various researchers increasingly study a way of utilizing Building Information Modelling (BIM) to tackle current problems in the construction industry because BIM can support construction professionals to manage construction projects in a collaborative manner by integrating diverse information, and to determine the best refurbishment solution among various alternatives by calculating the life cycle costs and lifetime CO2 performance of a refurbishment solution. Despite the capability of BIM, the BIM adoption rate is low with 25% in the housing sector and it has been rarely studied about a way of using BIM for housing refurbishment projects. Therefore, this research aims to develop a BIM framework to formulate a financially and environmentally affordable whole‐house refurbishment solution based on the Life Cycle Costing (LCC) and Life Cycle Assessment (LCA) methods simultaneously. In order to achieve the aim, a BIM feasibility study was conducted as a pilot study to examine whether BIM is suitable for housing refurbishment, and a BIM framework was developed based on the grounded theory because there was no precedent research. After the development of a BIM framework, this framework was examined by a hypothetical case study using BIM input data collected from questionnaire survey regarding homeowners’ preferences for housing refurbishment. Finally, validation of the BIM framework was conducted among academics and professionals by providing the BIM framework and a formulated refurbishment solution based on the LCC and LCA studies through the framework. As a result, BIM was identified as suitable for housing refurbishment as a management tool, and it is timely for developing the BIM framework. The BIM framework with seven project stages was developed to formulate an affordable refurbishment solution. Through the case study, the Building Regulation is identified as the most affordable energy efficiency standard which renders the best LCC and LCA results when it is applied for whole‐house refurbishment solution. In addition, the Fabric Energy Efficiency Standard (FEES) is recommended when customers are willing to adopt high energy standard, and the maximum 60% of CO2 emissions can be reduced through whole‐house fabric refurbishment with the FEES. Furthermore, limitations and challenges to fully utilize BIM framework for housing refurbishment were revealed such as a lack of BIM objects with proper cost and environmental information, limited interoperability between different BIM software and limited information of LCC and LCA datasets in BIM system. Finally, the BIM framework was validated as suitable for housing refurbishment projects, and reviewers commented that the framework can be more practical if a specific BIM library for housing refurbishment with proper LCC and LCA datasets is developed. This research is expected to provide a systematic way of formulating a refurbishment solution using BIM, and to become a basis for further research on BIM for the housing sector to resolve the current limitations and challenges. Future research should enhance the BIM framework by developing more detailed process map and develop BIM objects with proper LCC and LCA Information.

Pénzgazdálkodási szokások hatása a működőtőkére (The effect of financial management habits on operating capital. The example of the Hungarian Post Office)

A hálózatos iparágakban, ahogy a postai szolgáltatásoknál is, a forgalomban lévő készpénz nagyméretű működőtőkét jelenthet. A Magyar Posta a levél- és csomagkézbesítésen kívül jelentős készpénzforgalmat bonyolít le: nyugdíjakat, segélyeket és készpénz-átutalási megbízásokat továbbít. A forgalom napi ingadozása a vállalat likvideszköz-igényét jelentősen meghatározza. A posta esetében a postahivatalok készpénzgazdálkodása jól működő hüvelykujjszabályokon keresztül történik, ezek a szabályok döntési teret hagynak a hálózat heterogén egyedi szereplőinek. Az egyedi készletezési viselkedést a vállalati működőtőke meghatározásakor figyelembe kell venni. A tanulmány az egyedi készletezési szokások modellezésére új módszertant ajánl, majd a viselkedésmintákat csoportosítva a pénzkészletezésnek, a vállalati működőtőke szintjének és a vállalati likviditási pozíciónak a kapcsolatát elemzi. / === / The cash in circulation within network industries such as post-office services can repre-sent a sizeable quantity of operating capital. The Hungarian Post Office, besides han-dling mail, handles a significant amount of cash turnover, forwarding pensions, welfare benefits, and cash orders. Fluctuation in the daily volume of these is a strong factor in determining the company's liquidity requirements. The management of cash in post of-fices is governed by rules of thumb that operate well; the regulations leave decision-making scope for the diverse individual actors in the network. Attention has to be paid to individual cash holding when determining the corporate operating capital. The study suggests a new methodology for modelling the individual cash-holding habits, and goes on to group the behaviour patterns by analysing the connection between cash holding, level of corporate operating capital, and corporate liquidity position.