The Balanced Scorecard (BSC) methodology focuses on major critical issues of modern business organisations: the effective measurement of corporate performance and the evaluation of the successful ...implementation of corporate strategy. Despite the increased adoption of the BSC methodology by numerous business organisations during the last decade, limited case studies concern non-profit organisations (e.g. public sector, educational institutions, healthcare organisations, etc.). The main aim of this study is to present the development of a performance measurement system for public health care organisations, in the context of BSC methodology. The proposed approach considers the distinguished characteristics of the aforementioned sector (e.g. lack of competition, social character of organisations, etc.). The proposed measurement system contains the most important financial performance indicators, as well as non-financial performance indicators that are able to examine the quality of the provided services, the satisfaction of internal and external customers, the self-improvement system of the organisation and the ability of the organisation to adapt and change. These indicators play the role of Key Performance Indicators (KPIs), in the context of BSC methodology. The presented analysis is based on a MCDA approach, where the UTASTAR method is used in order to aggregate the marginal performance of KPIs. This approach is able to take into account the preferences of the management of the organisation regarding the achievement of the defined strategic objectives. The main results of the proposed approach refer to the evaluation of the overall scores for each one of the main dimensions of the BSC methodology (i.e. financial, customer, internal business process, and innovation-learning). These results are able to help the organisation to evaluate and revise its strategy, and generally to adopt modern management approaches in every day practise.
► Develop a strategic performance measurement system using the BSC approach. ► Apply the UTASTAR multicriteria method in order to model management's preferences. ► Present an application of the approach in a public healthcare organisation. ► Results may help the organisation to evaluate and revise its strategy.
Outranking methods constitute an important class of multicriteria classification models. Often, however, their implementation is cumbersome, due to the large number of parameters that the decision ...maker must specify. Past studies tried to address this issue using linear and nonlinear programming, to elicit the necessary preferential information from assignment examples. In this study, an evolutionary approach, based on the differential evolution algorithm, is proposed in the context of the ELECTRE TRI method. Computational results are given to test the effectiveness of the methodology and the quality of the obtained models.
The financial decisions of an organization are usually included in the context of optimization. Concerning a long-term period, there are decisions related to the optimal allocation of funds, and ...decisions related to the optimal financial structure. In the short-term case, the decisions are related to the optimization of stocks, cash, accounts receivable, current liabilities, etc. The financial theory analyzes these decisions, mainly from an optimal point of view. The optimal character of such decisions has led researchers to propose operations research techniques to solve the problems that are inherent in such decisions. This paper examines the contribution of multicriteria analysis in solving financial decision problems in a realistic context. The paper also includes an extensive bibliography on the subject.
The linkage among customer satisfaction, employee evaluation, and business performance data is very important in modern business organizations. Several previous research efforts have studied this ...linkage, focusing mainly on the financial or business performance in order to analyze the efficiency of an organization. However, recent studies have tried to consider other important performance indicators, which are able to affect business operations and future growth (e.g., external and internal customer satisfaction). In the case of the banking industry, studying the relations among the aforementioned variables is able to give insight in the performance evaluation of bank branches and the viability analysis of the banking organization. This paper presents a real-world study for measuring the relative efficiency of a set of bank branches using a Data Envelopment Analysis (DEA) approach. In particular, a multistage DEA network model is proposed, using a set of performance indicators that combine customer satisfaction, employee evaluation, and business performance indices. The main aim of the presented study is to evaluate the relative efficiency of each customer service delivery step, in the environment of a bank branch. The results are also able to estimate the contribution of the assessed performance indicators to the branch’s overall efficiency, and to determine potential improvement actions.
The extant literature reveals a growing need to rethink urban sustainability. Sustainable urban development is becoming more important to city strategic planning since sustainability is a critical ...aspect of environmental protection, social cohesion, and economic growth. However, decisions are currently not always taking into account the need to maintain sustainability because either decision makers do not fully understand the decision problems at hand or they do not focus on finding realistic, contextualized solutions. In addition, most existing models of urban sustainability assessment are static. Therefore, new urban sustainability assessment systems based on landsenses ecology are needed, which should combine natural elements, physical senses, and psychological perceptions, and assist decision makers develop successful management policies. Using fuzzy cognitive mapping and system dynamics, this study sought to develop a fresh, holistic perspective on urban sustainability. Based on the knowledge and experience of a panel of experts in urban development, some of the most significant determinants of urban sustainability were identified, namely: sustainable construction; urban planning and/or design; health; economy; culture, citizenship, and education; environmental quality; public policies and governance; and mobility and/or accessibility. The results obtained were validated both by the panel members and the director of the Department of Urban Planning of the Lisbon City Council, Portugal. The advantages and limitations of our approach are also discussed, as well as recommendations for future research.
The long-term viability of a business organization depends on its ability to evaluate the performance of the employees and to examine the contribution of its personnel in achieving the assessed ...goals. In this context, the evaluation of employees may provide a quantitative measure of their appraisal aiming at determining the degree of conformance between the job output and the defined standards. The main aim of this study is to present the development of an employee evaluation system in a healthcare organization. The proposed approach is based on multicriteria analysis and considers the complexity of the different job profiles. In particular, the applied quantitative model constitutes a variant of the UTA method, taking into account the strategy of the organization and the preferences of the management. The main advantage of this approach focuses on its ability to use absolute performance measures and to develop an evaluation system that can handle qualitative (ordinal) information. Moreover, using the proposed approach, employees are evaluated on a set of different but specific job dimensions, providing the ability to perform different types of comparison analyses.
Business failure prediction using rough sets Dimitras, A.I.; Slowinski, R.; Susmaga, R. ...
European journal of operational research,
04/1999, Volume:
114, Issue:
2
Journal Article
Peer reviewed
A large number of methods like discriminant analysis, logit analysis, recursive partitioning algorithm, etc., have been used in the past for the prediction of business failure. Although some of these ...methods lead to models with a satisfactory ability to discriminate between healthy and bankrupt firms, they suffer from some limitations, often due to the unrealistic assumption of statistical hypotheses or due to a confusing language of communication with the decision makers. This is why we have undertaken a research aiming at weakening these limitations. In this paper, the rough set approach is used to provide a set of rules able to discriminate between healthy and failing firms in order to predict business failure. Financial characteristics of a large sample of 80 Greek firms are used to derive a set of rules and to evaluate its prediction ability. The results are very encouraging, compared with those of discriminant and logit analyses, and prove the usefulness of the proposed method for business failure prediction. The rough set approach discovers relevant subsets of financial characteristics and represents in these terms all important relationships between the image of a firm and its risk of failure. The method analyses only facts hidden in the input data and communicates with the decision maker in the natural language of rules derived from his/her experience.
Since accurate forecasting of energy export is very important for planning potential energy demand and improving the energy production sector, various forecasting methods have been developed. The ...present work is focused to apply a novel technique, an integrated neuro-fuzzy controller named PATSOS. The forecasting system is based on two Adaptive Neural Fuzzy Inference Systems (ANFIS) that form an inverse controller. An ANFIS model represents the controller and another ANFIS represents the energy export model that is going to be controlled. ANFIS uses a combination of the least-squares method and the backpropagation gradient descent method to estimate the optimal energy export forecast parameters. The ANFIS controller belongs to direct control and is based on inverse learning, also known as general learning. Hourly data sets during the period 1 January 2009 to 31 December 2009 were used to learn and evaluate the proposed system. The forecast accuracy of the proposed technique was evaluated using out of sample tests. The results of the simulation based on statistical errors and the experimental investigations carried out on the laboratory showed that the model despite the high data volatility, is suitable for forecasting hourly energy exports.
Corporate credit risk assessment decisions involve two major issues: the determination of the probability of default and the estimation of potential future benefits and losses for credit granting. ...The former issue is addressed by classifying the firms seeking credit into homogeneous groups representing different levels of credit risk. Classification/discrimination procedures commonly employed for such purposes include statistical and econometric techniques. This paper explores the performance of the M.H.DIS method (Multi-group Hierarchical DIScrimination), an alternative approach that originates from multicriteria decision aid (MCDA). The method is used to develop a credit risk assessment model using a large sample of firms derived from the loan portfolio of a leading Greek commercial bank. A total of 1411 firms are considered in both training and holdout samples using financial information through the period 1994–1997. A comparison with discriminant analysis (DA), logit analysis (LA) and probit analysis (PA) is also conducted to investigate the relative performance of the M.H.DIS method as opposed to traditional tools used for credit risk assessment.
The evaluation of the performance of mutual funds (MFs) has been a very interesting research topic not only for researchers, but also for managers of financial, banking and investment institutions. ...In this paper, an integrated methodological framework for the evaluation of MF performance is proposed. The proposed methodology is based on the combination of discrete and continuous multicriteria decision aid (MCDA) methods for MFs selection and composition. In the first stage of the analysis the UTADIS MCDA method is employed in order to develop mutual fund's performance models supporting the selection of a small set of MFs, which will compose the final portfolios. In the second stage, a goal programming model is employed to determine the proportion of the selected MFs in the final portfolios. The methodology is applied on data of Greek MFs over the period 1999–2001 with encouraging results.
