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Using data from business reorganization processes under Act 1116 of 2006 in Colombia during the period 2008 to 2018, a model for predicting the success of these processes is proposed. The paper aims to validate the model in two different periods. The first one, in 2019, characterized by stability, and the second one, in 2020, characterized by the uncertainty generated by the COVID-19 pandemic.

A set of five financial variables comprising indebtedness, profitability and solvency proxies, firm age, macroeconomic conditions, and industry and regional dummies are used as independent variables in a logit model to predict the failure of reorganization processes. In addition, an out-of-sample analysis is carried out for the 2019 and 2020 periods.

The results show a high predictive power of the estimated model. Even the results of the out-of-sample analysis are satisfactory during the unstable pandemic period. However, industry and regional effects add no predictive power for 2020, probably due to subsidies for economic activity and the relaxation of insolvency legislation in Colombia during that year.

In a context of global reform in insolvency laws, the consistent predictive ability shown by the model, even during periods of uncertainty, can guide regulatory changes to ensure the survival of companies entering into reorganization processes, and reduce the observed high failure rate.

The aim of this paper is to provide an overview of the impact of the implementation of Colombian Corporate Insolvency Act 1116 of 2006 in the period 2008–2018 and to assess the relevance of a broad set of financial predictors, as well as variables related to the economic context or the characteristics of the process itself, in explaining the failure of reorganization processes.

Both logit and probit models are estimated, starting from a large number of variables proposed in the literature which are then narrowed down to a final selection based on their individual significance and machine learning.

The results show the prevalence of a limited number of financial variables related to equity, indebtedness, profits and liquidity as predictors of the failure of reorganization processes. The use of financial information from the year prior to the completion of the reorganization improves predictive accuracy and reliability. The debt-to-equity indicator provides no significant explanatory power, while voluntary entry into a reorganization process favors its success.

While financial and accounting information is used across the literature to predict insolvency events, it is used here to predict success or failure in reorganization processes under the conditions imposed by a specific legislative act in a Latin American context.

Proporcionar una panorámica de la implementación de la Ley 1116 de 2006 a partir de las empresas que suscribieron acuerdos de reorganización en Colombia en el periodo 2008–2018 y evaluar la relevancia de un conjunto amplio de predictores financieros, así como variables relacionadas con el entorno económico o de características del propio proceso, para explicar el fracaso de la reorganización.

Se han estimado tanto modelos logit como probit, partiendo de un amplio número de variables propuestas en la literatura, que luego se reducen a una selección final basada en su significancia individual y una metodología de machine learning.

Un número reducido de variables relacionadas con los fondos propios, el endeudamiento, los beneficios y la liquidez prevalecen como predictores financieros del fracaso de los procesos de reorganización. El uso de información del año anterior al cierre del acuerdo mejora la precisión de las predicciones realizadas. El indicador de conversión de deuda en capital no ofrece capacidad explicativa significativa, mientras que la entrada voluntaria a la reorganización favorece su éxito.

Muchos trabajos han usado información financiera y contable para predecir eventos de insolvencia. En nuestro caso se usa esta información para predecir el éxito o fracaso de los procesos de reorganización bajo una ley específica en el contexto latinoamericano.

The purpose of this paper is to analyze the effect of different reorganization actions on long‐term financial performance of reorganizing small entrepreneurial firms in Finland.

An structural equation model estimated by partial least squares is applied to survey data from 98 reorganizing very small firms to analyze the effect of organizational change (OC), financial reorganization, management control system change (MCSC), and management accounting change (MAC) on performance.

Evidence supports three of the seven research hypotheses. Debt restructuring has a positive effect on performance. Liquidation of assets and OC do not show a significant direct effect but OC has a positive total effect. MCSC has a positive effect whereas the effect of MAC is negative. Compatibility of reorganization actions with the confirmed reorganization plan affects positively performance.

The sample is small. In further studies, larger samples should be used. Effect of reorganization on performance is self‐assessed by the firms. Further studies should apply more objective measures. The constructs of variables are intended for larger firms. New constructs should be developed for very small firms.

It is important that reorganization administrators and consultants prepare a careful reorganization plan to be followed during the program. In small reorganizing firms, it is beneficial to develop management control systems. However, one should be cautious when developing formal management accounting systems for very small firms.

This paper is the first one developing a structural model of the effects of reorganization actions on performance of small firms. It brings new evidence on the effects of organizational and control system change.

The purpose of this paper is to explore how an Higher Education Institution’s (HEI) choice of undergoing a voluntary reorganisation, motivated by its own interest of increasing its autonomy, whilst also having to satisfy the government in order to maintain the level of public funding, impacts on the HEI’s accounting.

The paper draws on the institutional logics perspective to present a single case study of a German HEI that chose to be reorganised from a public into a foundation university. Data were obtained using multiple data collection methods.

The findings suggest that organisational characteristics, which act as filters for institutional logics, play an important role for HEIs’ ability to increase not only their de jure, but also their de facto autonomy through self-motivated, rather than government imposed, reform processes.

The paper is based on a single case study in a country-specific context, limiting the empirical generalisability of the findings.

Germany is not only one of the main nations exporting higher education, but its economy has also been recognised for its stability and development over the last decades. Nevertheless, Germany struggles in its transition to become a knowledge-based economy. Yet, research has so far tended to neglect educational reforms in Continental European countries, such as Germany. By addressing this gap in the literature, this paper is among the first to explore how reform processes shape accounting in German HEIs.

A primary purpose of the voluntary administration legislation is to provide a flexible procedure by which a company can attempt to reorganise its affairs and continue trading. Informed decision‐making regarding which companies should attempt reorganisation is critical to the efficient operation of company rescue legislation. This paper explores decision‐making associated with the voluntary administration process, with a focus on the relevance of financial information to the reorganisation decision. Statistical models are developed to provide some insight into the reorganisation decision and the problem of identifying suitable (successful) reorganisation candidates from a pool of distressed companies. Additionally, insolvency experts’ decisions regarding companies’ prospects in reorganisation are examined. The decision accuracy of insolvency experts was found to be significantly lower than statistical model accuracy, indicating that further development of statistical models may be a useful aid to insolvency experts.

This research seeks to investigate the role of key corporate governance mechanisms in determining a firm's post‐bankruptcy performance following reorganisation.

The study is based on agency theory and uses a unique sample of 111 filing companies whose reorganisation plans have been confirmed by the Thai Central Bankruptcy Court during the period 1999‐2002.

The results indicate that monitoring and incentive mechanisms are significant determinants of a firm's post‐bankruptcy performance. The key monitoring mechanism is ownership concentration, measured by shares held by the largest shareholder, whereas the critical incentive mechanisms are cash compensation and percentage of common shares held by the plan administrator. The results indicate that these mechanisms can mitigate agency problems in previously insolvent companies and increase post‐bankruptcy performance over a three year period.

The study is timely given that many organisations are facing rebuilding programs following the impact of the global financial crisis. Prior research in Thailand and elsewhere has not measured bankruptcy reorganisation outcomes in terms of the difference of actual financial performance to predicted performance and in relation to the governance factors of the reorganisation process. Neither has this aspect been considered within an agency theory framework. This provides a unique opportunity to consider these variables based on the theoretical framework of agency theory and to evaluate the importance of governance mechanisms in reorganisation proceedings.

The purpose of this paper is to develop a data system to assess failure probability in small to medium‐sized enterprise (SME) reorganization.

The data system is based on information from 83 reorganized Finnish SMEs. Information is divided into four types: pre‐filing non‐financial, pre‐filing financial, reorganization submission, and reorganization plan information. Partial least squares (PLS) analysis is used in data mining to factorize information for each type of information. Logistic regression analysis is applied to assess failure probability.

Useful data system can be developed on the basis of pre‐filing non‐financial information to support reorganization decision. Pre‐filing financial information only marginally improves quality of information. Submission and reorganization plan information improve quality in terms of fit but do not significantly improve classification accuracy.

The sample is small and should be expanded in further studies. The system is developed for Finnish reorganizing firms. It can be generalized to any similar reorganization process.

The data system is useful for managers, lending specialists, investors, reorganization lawyers, and judges. It warns a SME about reorganization failure before filing petition (passive use). It is also useful in developing successful reorganization plans (active use).

This paper builds an extensive data system for assessing reorganization failure risk. It makes use of many variables that have not been analyzed in reorganization studies earlier. It deals with SMEs that is rare in reorganization studies. The paper utilizes PLS in assessing failure probability. It includes new analytical results on PLS.

Small- and medium-sized enterprises (SMEs) often lack adequate accounting systems and may even fail because of accounting inefficiencies. Indeed, accounting can mitigate the course of a crisis and support a troubled SME’s turnaround. Its impact on reorganization success, however, has scarcely been researched so far. Therefore, this paper aims to examine the effects of several accounting parameters, namely, the quality of accounting systems, quality of early warning systems, formal planning, the standard of financial accounting and reorganization planning on the short- and long-term success of court-supervised reorganization.

The impact of accounting on reorganization success is investigated in a sample of all SME bankruptcy cases with ten or more employees (n = 117) in Upper Austria in 2012 including data for short-term survival (in 2016) and long-term survival (in 2019).

This study found evidence that the general quality of accounting systems, the quality of early warning systems and written reorganization plans positively influence the outcomes of the analyzed court-supervised reorganizations of SMEs. In particular, the existence of a reorganization plan significantly increases the short- and long-term reorganization success by ensuring the efficient and effective use of resources in the reorganization process.

This study should increase the awareness of SMEs’ owner managers, consultants, creditors and legislators for the importance of accounting in the context of reorganization. The fact that the effect of accounting on reorganization success is less pronounced in the long-term view indicates the necessity of increasing the strategic focus in SMEs’ accounting instruments.

This study provides new evidence on the impact of specific accounting parameters on the short- and long-term success of the court-supervised reorganization of SMEs. Furthermore, this study points out the high relevance of reorganization plans for SMEs.

The purpose of this paper is to examine March and Olsen’s 1983 study of American Government reorganization attempts between 1904 and 1980 in relation to three debates in management history scholarship. Can explorations of the past yield innovative interpretations of the present and future organizational activities? What is the role of multiple perspectives in understanding complex reality? How should management historians react to the differences in power held by various actors in historical scenarios and to the absence of documented evidence of the stances of many traditionally underrepresented groups?

The paper analyzes March and Olsen’s 1983 historical study on federal government reorganizations in relation to twentieth-century political science/public administration scholarship from 1919 to the present showing the unique focus and conclusion of March and Olsen’s work. The paper relates this focus and conclusions to three management questions.

This analysis shows that March and Olsen’s interpretation of American reorganization has had a significant impact on the work of political scientists studying programs that did not exist in 1983; this impact suggests how historical scholarship can invigorate understanding of current programs. The analysis also gives evidence to support March and Olsen’s focus on the importance of considering multiple perspectives to interpret complex realities. The analysis concludes that despite March’s acknowledging the importance of anti-establishment scholarship, March and Olsen’s 1983 work did not explore the role of power differentials or the voices of the oppressed in government reorganizations.

The value of this paper is that it seeks to relate March and Olsen’s work to a scholarship domain where it has not often been considered. Management historians lament that their work and concerns have often been considered peripheral by the greater management field. By showing how a major management theorist such as March used historical analysis to further understanding of contemporary organizations the paper heightens the visibility and importance of management history work.

The coronavirus disease 2019 (COVID-19) pandemic has had major impacts on the performance of construction projects that have adopted social distancing measures. This study examines the effect of social distancing measures on project schedule performance through job reorganization on construction project sites.

Responses were obtained through a survey of 154 construction projects and analysed using the partial least square structural equation modeling (PLS-SEM) technique.

The findings established that social distancing has a negative effect on schedule performance, social distancing has a positive effect on job re-organization and job re-organization has a positive effect on schedule performance. Additionally, the results indicate that job re-organization partially mediates the relationship between social distancing and schedule performance, while social distancing moderates the relationship between job re-organization and schedule performance with low social distancing having the stronger positive effect.

This study contributes theoretically to a greater understanding of the impact of adopting COVID-19 safety measures such as social distancing on the schedule performance of construction projects. The study also shows how social distancing could lead to schedule performance through job reorganization.