Entrepreneurs' exit and paths to retirement : theoretical and empirical considerations

The number of ageing entrepreneurs in micro- and small-sized companies is rapidly increasing in Finland and other European Union countries. Over half a million jobs, in over one hundred thousand companies within the EU, are lost annually due to unsuccessful, predominantly retirement-related transfers of businesses. This challenge coincides with EU Grand Challenges and has been highlighted in the Entrepreneurship 2020 Action Plan (European Commission 2013). It has been estimated that in Finland, some 8000 jobs are lost yearly due to the ageing of entrepreneurs. Therefore, entrepreneur ageing has implications not only for the ageing individual but also for the company and the society at large. As entrepreneurs age it becomes more essential for them to start planning when and how they transition into retirement. While they may experience several exits and subsequent re-entries into working life via buying or starting new companies, exiting ones entrepreneurial career due to old age retirement differs from exits that occur earlier during the career. In this chapter, we provide a short overview of the entrepreneur retirement and exit literature from an age perspective. Furthermore, we present a theoretical conceptualization which combines entrepreneur retirement process with exit theories. This will enable scholars to better understand the retirement process, including decision-making, transitioning, and adjustment to retirement. We also provide empirical evidence using data collected among Finnish entrepreneurs in 2012 and 2015, where we outline the types of exits and assess several factors, including age, in association with exit intentions.fi=vertaisarvioitu|en=peerReviewed

Comparison of Physical-chemical and Mechanical Properties of Chlorapatite and Hydroxyapatite Plasma Sprayed Coatings

Chlorapatite can be considered a potential biomaterial for orthopaedic applications. Its use as plasma-sprayed coating could be of interest considering its thermal properties and particularly its ability to melt without decomposition unlike hydroxyapatite. Chlorapatite (ClA) was synthesized by a high-temperature ion exchange reaction starting from commercial stoichiometric hydroxyapatites (HA). The ClA powder showed similar characteristics as the original industrial HA powder, and was obtained in the monoclinic form. The HA and ClA powders were plasma-sprayed using a low-energy plasma spraying system with identical processing parameters. The coatings were characterized by physical-chemical methods, i.e. X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR) and Raman spectroscopy, including distribution mapping of the main phases detected such as amorphous calcium phosphate (ACP), oxyapatite (OA), and HA or ClA. The unexpected formation of oxyapatite in ClA coatings was assigned to a side reaction with contaminating oxygenated species (O2, H2O). ClA coatings exhibited characteristics different from HA, showing a lower content of oxyapatite and amorphous phase. Although their adhesion strength was found to be lower than that of HA coatings, their application could be an interesting alternative, offering, in particular, a larger range of spraying conditions without formation of massive impurities.This study was carried out under a MNT ERA-Net Project named NANOMED. The authors gratefully thank the Midi-Pyrénées region (MNT ERA Net Midi-Pyrénées Région, NANOMED2 project) and the Institute National Polytechnique de Toulouse (BQR INPT 2011, BIOREVE project) for supporting this research work, especially the financial support for research carried out in the CIRIMAT and the LGP laboratories (France), and the Basque government and Tratamientos Superficiales Iontech, S.A. for their financial and technical support under the IG-2007/0000381 grant for the development of the LEPS device and deposition of the coatings carried out in Inasmet-Tecnalia. The French industrial collaborators (TEKNIMED SA and 2PS SA) were financed by the OSEO programs

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Alternative methodologies in studies on business failure: do they produce better results than the classical statistical methods?

Over the last 35 years, the topic of company failure prediction has developed to a major research domain in corporate finance. Academic researchers from all over the world have been developing a gigantic number of corporate failure prediction models, based on various types of modelling techniques. Besides the classical cross-sectional statistical methods, which have produced numerous failure prediction models, researchers have also been using several alternative methods for analysing and predicting business failure. To date, a clear overview and discussion of the application of alternative methods in corporate failure prediction is still lacking. Moreover, frequently, different designations or names are used for one method. Therefore, this study aims to provide a clear overview of the alternative research methods, attributing each of them a fixed designation. More in particular, this paper extensively elaborates on the most popular methods of survival analysis, machine learning decision trees and neural networks. Furthermore, it discusses several other alternative methods, which can be considered to have a certain value added in the empirical literature on business failure: the fuzzy rules-based classification model, the multi-logit model, the CUSUM model, dynamic event history analysis, the catastrophe theory and chaos theory model, multidimensional scaling, linear goal programming, the multi-criteria decision aid approach, rough set analysis, expert systems and self-organizing maps. This paper discusses the main features of these methods and their specific assumptions, advantages and disadvantages and it gives an overview of a number of academically developed corporate failure prediction models. Several issues viewed in isolation by earlier studies are here considered together, which is of major importance for gaining a clear insight into the possible alternative methods of corporate failure modelling and their corresponding features. A second aim of this paper is to find an answer to the question whether the more sophisticated, alternative modelling methods produce better performing failure prediction models than the rather simple classical statistical methods. The analysis of the conclusions of a large number of empirical studies comparing the classification results and/or the prediction abilities of failure prediction models based on different techniques seems to indicate that we may question the benefits to be gained from using the more sophisticated alternative methods.

35 years of studies on business failure: an overview of the classical statistical methodologiesand their related problems

Over the last 35 years, the topic of business failure prediction has developed to a major research domain in corporate finance. A gigantic number of academic researchers from all over the world have been developing corporate failure prediction models, based on various modelling techniques. The ‘classical cross-sectional statistical’ methods have appeared to be most popular. Numerous ‘singleperiod’ or ‘static’ models have been developed, especially multivariate discriminant models and logit models. As to date, a clear overview and discussion of the application of the classical cross-sectional statistical methods in corporate failure prediction is still lacking, this paper extensively elaborates on the application of (1) univariate analysis, (2) risk index models, (3) multivariate discriminant analysis, and (4) conditional probability models, such as logit, probit and linear probability models. It discusses the main features of these methods and their specific assumptions, advantages and disadvantages and it gives an overview of a large number of academically developed corporate failure prediction models. Despite the popularity of the classical statistical methods, there have appeared to be several problems related to the application of these methods to the topic of corporate failure prediction. However, in the existing literature there is no clear and comprehensive analysis of the diverse problems. Therefore, this paper brings together all criticisms and problems and extensively enlarges upon each of these issues. So as to give a clear overview, the diverse problems are categorized into a number of broad topics: problems related to (1) the dichotomous dependent variable, (2) the sampling method, (3) non-stationarity and data instability, (4) the use of annual account information, (5) the selection of the independent variables, and (6) the time dimension. This paper contributes towards a thorough understanding of the features of the classical statistical business failure prediction models and their related problems.

Financial distress and firm exit: determinants of involuntary exits, voluntary liquidations and restructuring exits

This paper provides new insights on the determinants of firm exit after distress. Using nested logit models and a sample of 6118 distress-related exits from Belgium, we analyze the impacts of available and potential slack and the relative efficiency of voluntary liquidation, compared to acquisition and merger, on the type of exit. It appears essential to examine the type of exit outcome as a two-stage process. The first stage considers the fundamental distinction between voluntary and involuntary exit, the latter being the least favorable and most avoided exit strategy. In this situation, high levels of available and potential slack resources, as reflected by large cash holdings, strong group relations and low current leverage, increase the probability of voluntary exit. High slack allows distressed firms to avoid bankruptcy and decide on their exit process. In the second stage, and provided that exit is voluntary, voluntary liquidation is compared to restructuring exit (acquisition, merger or split). In this stage, a higher relative efficiency of voluntary liquidation compared to a restructuring exit, as indicated by absence of group relations, small firm size, high secured debt level and large cash holdings, increase the likelihood of voluntary liquidation and reduce the probability of a restructuring exit.

From distress to exit: determinants of the time to exit

This paper analyses the duration of the time to exit of distressed firms, differentiating between involuntary exits (mainly bankruptcies) and voluntary liquidations. It examines how long firms survive after initial signs of economic distress. The study is conducted on an extensive dataset of 5,233 Belgian distress-related exits of non-starting firms, the majority being privately held. The results highlight that slack resources have an opposite effect on the timing of involuntary exits and voluntary liquidations. On the one hand, high levels of available and potential slack increase the time to involuntary exit, as they allow distressed firms to postpone an impending involuntary exit. On the other hand, high available slack resources shorten the time to voluntary liquidation as they make voluntary liquidation easier. Further, a high level of stakeholder dependence increases the time to exit after distress, whether the firm exits through a voluntary or through an involuntary procedure. This is explained by the fact that stakeholder dependence increases the complexity of the exit decision and the exit procedure.