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The purpose of this paper is to find out which different failure processes exist among the young manufacturing micro firms, and whether the representation of those processes differs first, in European countries, and second, among exporting and non-exporting firms.

The study is based on financial data of 1,216 manufacturing micro firms from European countries. Failure processes have been detected with a two stage-method: by extracting latent dimensions from financial variables with factor analysis, and then, by clustering the established factor scores.

With firms’ age, the number of different failure processes reduces from four to two. Strong evidence was found about the dominance of different failure processes in different countries for most firm age groups. Failure processes are not strongly associated with (non-)exporting.

This paper is the first one determining young manufacturing micro firms’ failure processes and comparing the representation of those processes in different firm subsets, either based on their country of origin or (non-)exporting behavior. Moreover, previous studies have not encompassed specific sectors, young or very small firms.

The purpose of this paper is to analyze the relationships between different types of performance management system (PMS) and organizational performance. The main task is based on an empirical typology of PMS to show how the different types of PMS are related to organizational performance.

The empirical typology is used on the creation on the sample of Estonian and Finnish firms.

The results show that the highest performance out of the four clusters is achieved by firms from strategy-focused multi-level and strategy-focused one-level clusters. They also show the highest quality of the key characteristics of PMS. Firms from the not-strategy-focused one-level cluster have the lowest performance and quality of the key characteristics of PMS.

The findings give a set of consistent guidelines on how to develop a PMS to achieve high organizational performance in different situations. These give hints, if strategic objectives are important to firm, then for achieving these objectives, also a strong emphasis of strategic aspects in PMS is necessary to gain performance; if the firm suffers from a lack of strategy, the firm should invest on the information aspects of PMS to get more relevant information to increase performance; if the firm, however, decides to move more strategy-oriented, then the strategy aspects of the PMS should get relatively more attention than other aspects in PMS, and they should be developed with care, otherwise performance will suffer.

This paper shows relations between empirically extracted clusters and organizational performance. The results show that clusters of PMS are systematically associated with the level of performance. Firms with different aspects of PMS do not achieve the equal level of performance. Firms with higher performance inside different PMS types have more desirable characteristics and aspects of PMS.

The purpose of this study is to analyze the business-failure-process risk from two perspectives. First, a simplified model of the loss-generation process in a failing firm is developed to show that the linear system embedded in accounting makes financial ratios to depend linearly on each other. Second, a simplified model of the development of the risk during the failure process is developed to introduce a new concept of failure-process-risk line (FPRL) to assess the systematic failure risk of a firm. Empirical evidence from Finnish firms is used to test two hypotheses.

This study makes use of simple mathematical modeling to depict the loss-generation process and the development of failure risk during the failure process. Hypotheses are extracted from the mathematical results for empirical testing. Time-series data originally from 13,082 non-failing and 515 failing Finnish are used to test the hypotheses. Analysis of variance F statistics and Mann–Whitney U test are used in testing of the hypotheses.

The findings show that the linear time-series correlations are generally higher in failing than in non-failing firms because of the loss-generation process. The FPRL depicted efficiently the systematic failure-process risk through the beta coefficient. Beta coefficient efficiently discriminated between failing and non-failing firms. The difference between the last-period risk estimate and FPRL was largely determined by the approximated growth rate of the periodic failure risk.

The loss-generation process is based on a simple cash-based approach ignoring the growth of the firm. In future research, the model could be generalized to a growing firm in an accrual-based framework. The failure-process risk is assumed to grow at a constant rate. In further studies, more general models could be applied. Empirical analyses are based on simple statistical methods and tests. More advanced methods could be used to analyze the data.

This study shows that failure process makes the time-series correlation between financial ratios to increase making their signals of failure consistent and allowing the use of static classification models to assess failure risk. The beta coefficient is a useful tool to reflect systematic failure-process risk. In addition, it can be used in practice to warn a firm about ongoing failure process.

To the best of the author’s knowledge, this is the first study analyzing systematically business-failure-process risk. It is first in introducing a mathematical loss-generation process and the FPRL based on the beta coefficient assessing the systematic failure risk.

The purpose of this paper is to find out whether the financial predictors of failure differ for exporting and non-exporting firms.

The study is based on two samples of French manufacturing micro firms from Amadeus database. Samples of 468 exporting and 1,148 non-exporting firms were divided equally to survived and bankrupted firms. Logistic regression method was used with five financial ratios portraying liquidity, solidity, cash flow sufficiency, profitability and productivity.

The findings suggest that cash flow sufficiency and solidity were important predictors in both firm groups, although the latter was more important in case of exporters. Liquidity was important in case of non-exporters, while profitability in case of exporters. Productivity was not a significant predictor. With these variables, failure of exporters was predicted with a higher accuracy.

This paper contributes to an under-researched area in the failure prediction and international business literature, namely, it outlines whether failure predictors are the same for similar exporting and non-exporting firms. The results indicate that some predictors differ and similar ones can have different importance for exporters and non-exporters.

This paper presents a model for predicting crises in small businesses using early‐warning signals. It summarises the results of two separate studies carried out in Finland (with 72 per cent response) and the UK (26 per cent) on the decision process of corporate analysts (Finland) and bank managers (UK) in predicting the failure of small and medium‐sized enterprises (SMEs). Both studies consist of seven main headings and over 40 sub‐headings of possible factors leading to failure. Weighted averages were used for both studies to show the importance of these factors. There are significant similarities in the results of the two studies. Management incompetence was regarded as the most important factor, followed by deficiencies in the accounting system and attitude towards customers. However, low accounting staff morale was considered a very important factor in Finland but not in the UK. Unlike Finland, the UK results emphasised the importance of accounting systems and internal control. These two studies differ from previous studies as managerial auditing elements like the importance of internal control departments (UK evidence) and budgetary control systems were included. Similarities in the results of these surveys conducted under two separate EU environments imply that it would be interesting and beneficial to extend these studies to other member states.

The purpose of this paper is to use the logical chain of key factors (KFs) to explain the success of performance management systems (PMS) and corporate performance.

The authors use the strength of the KFs chain to capture PMS success. First, the authors assume that perceived environmental uncertainty (PEU) is positively associated with the strength (H1). The higher the PEU, the stronger is the chain as a response to uncertainty. Second, the authors assume that the strength improves performance (H2) but third, that the impact of the strength is negatively moderated by competition (H3). Fourth, the authors assume that this improvement leads to superior corporate performance (H4). The research model is tested by applying the partial least squares method for a sample of 61 Estonian and Finnish firms.

Empirical evidence shows that PEU is negatively correlated to the strength of the chain but when controlled for a set of control variables, the path coefficient is positive. The strength of the chain is positively associated with improvement in performance. The impact of the strength of the chain on financial performance is negatively moderated by competition. The improvement in performance is positively associated with the attainment level of strategic goals. The improvement in non-financial performance does not significantly affect corporate profitability.

The levels of PEU and competition should be taken into the account when designing, adjusting and assessing the PMS of organization.

The authors give explanation why evidence about the effects of PMS on the performance of the firm is mixed.

Seeks to present a microeconomic model to analyse theoretically BSC, to develop a simplified model version and to apply it empirically.

The model assumes exponential production and demand functions with constant scale factors and elasticities. It is estimated for Nokia's time‐series 1993‐2002 and partly for 35 Compustat firms.

Direct statistical estimates act properly only as initial values iteratively adjusted for the level of the model. Model parameters show in experiments a significant effect on decision variables such as selling price. Most firms show decreasing returns to scale that are found also in a cross‐sectional analysis.

The model assumes constant elasticities and growth which should be relaxed. Most numerical experiments are limited to Nokia's data. Estimates applied in experiments are not fully justified on statistical grounds. More effort should be made to reach a consistent set of estimates at the level of the model.

In growth strategy, price discounts may lead to declining profitability, while productivity is increasing. This results in peculiar causal relationships in strategic mapping of BSC. If strategy is shifted towards revenue maximization, more focus should be given to customer relationships and development and learning in BSC. Firms should in strategic planning pay special attention to rate of discount and planning horizon, because they affect selling price.

This research paper presents a new model specification. It gives novel empirical evidence on parameter estimation and strategic behaviour in BSC framework.

The study develops a mathematical model of the firm to derive theoretical foundations for the balanced scorecard concept (BSC). The model is based on several parts which are integrated into a company model. This model includes the demand function, the production function and the objective function of the firm which are depicted by traditional microeconomic concepts. Demand is presented as a function of price and customer relationship management (CRM) costs. Production is assumed to depend on labor, capital, and development and learning (D&L) costs. Simple dynamics is included both in the demand and production function. The strategy of the firm is depicted by the objective function based on profit and net sales. The output variables of the model are classified as the four perspectives of BSC. The effects of the objectives (strategies) on the importance (shadow prices) of the constraints are analysed. It is shown that a change in the objectives may alter the order of their importance. Thus, a change in the strategy should be accompanied with a change in the focus of BSC. Furthermore, non‐financial and financial performance ratios may change in opposite directions, when the strategy is shifted towards revenue maximization. Thus, inconsistencies with the interpretation of cause and effects may emerge, when the strategy is shifted. Numerical examples are presented to demonstrate the results.

The purpose of the research is to analyse the ability of nonfinancial factors to predict value creation in Finnish technology firms. Nonfinancial factors are defined in terms of a large set of variables on organizational characteristics, strategy, competitive stance, consistency of performance measurement, management control systems (MCSs), and quality of MCSs. Financial ratios are used as a benchmark. The hypotheses are that, firstly, nonfinancial factors include important information for prediction and, secondly, that they provide incremental information over financial ratios. The nonfinancial variables are drawn from a postal survey carried out in 1999. Financial variables for 1998–2001 are obtained for 40 private firms of the 110 firms responding to the survey. Shareholder value is estimated on the basis of the four‐year financial data for 2001. This value divided by the shareholder book value (estimated‐to‐book value ratio, EBV) as well as its drivers are predicted by past non‐financial and financial data. Partial Least Squares (PLS) method is used to analyse the importance of information in prediction. The results give support to the hypotheses. Moreover, the results show that nonfinancial factors yield important incremental information over financial ratios when predicting value drivers, that is, growth, profitability, and risk. Especially, financial ratios are weak in predicting growth.

The purpose of this paper is to develop a simple microeconomic model of the firm to give theoretical foundations for the balanced scorecard concept (BSC).

The model consists of demand, production, and objective functions integrated into a resource allocation model. Costs, sales volume, and sales revenue grow at constant rates. Strategy is depicted by a weighted objective function of profit and net sales. Output variables are classified according to the four perspectives of BSC.

The effects of the parameters, especially growth and strategy, on the importance of the perspectives and on performance measures, are shown.

Many results are based on assumptions of a constant growth; and of constant demand and production functions. Empirical research is welcome to give evidence on demand and production elasticities, the shifts of strategy, their effects on performance measurement; and tension between profit and revenue maximization.

BSC should be elastic to respond to shifts of strategy towards revenue maximization. When a shift is happened, the focus in BSC should be transferred towards customer relationship management and development and learning; and the time‐series of performance measures should be interpreted cautiously. Even for a constant strategy, the time‐series of non‐financial and financial measures may give a contradicting signal.

This research paper introduces a new growth model of the firm useful in the theoretical analysis of BSC. It can be applied to assess the importance of the four perspectives of BSC, trade‐offs between them, and relationships between non‐financial and financial measures.