Comparative analysis between statistical and artificial intelligence models in business failure prediction

A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.

Comparative Analysis between Statistical and Artificial Intelligence Models in Business Failure Prediction

A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.

Cluster Analysis of Business Data

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Hierarchical cluster analysis of groups of individuals : application to business data

3rd SMTDA Conference Proceedings, 11-14 June 2014, Lisbon Portugal.

Business plan analysis of a Brazilian software company

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Business model analysis of Mobitto: How to solve the chicken and egg problem of a multi-sided platform?

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Market analysis of a new business opportunity in mobile-casual gaming: Partnership between Nmusic and Rovio Entertainment Ltd

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

International placement analysis of the German business market for a Nova Achool of Business and Economics graduate student

Changes in today’s society led to the evolution of professional migrations and individual searches for more suitable professional opportunities and careers outside one’s countries. International Placement is nowadays one of the world’s biggest trends in higher education for the future ahead and an appealing demand of the Millennium generations. The following work project aims to study the German business market identifying the most attractive German companies and respective graduate programs for a Nova School of Business and Economics graduate student. The study’s conclusion relies on concrete strategic suggestions regarding the implementation of the results and practical use of the outcome provided.

Business intelligence in banking: A literature analysis from 2002 to 2013 using Text Mining and latent Dirichlet allocation

telligence applications for the banking industry. Searches were performed in relevant journals resulting in 219 articles published between 2002 and 2013. To analyze such a large number of manuscripts, text mining techniques were used in pursuit for relevant terms on both business intelligence and banking domains. Moreover, the latent Dirichlet allocation modeling was used in or- der to group articles in several relevant topics. The analysis was conducted using a dictionary of terms belonging to both banking and business intelli- gence domains. Such procedure allowed for the identification of relationships between terms and topics grouping articles, enabling to emerge hypotheses regarding research directions. To confirm such hypotheses, relevant articles were collected and scrutinized, allowing to validate the text mining proce- dure. The results show that credit in banking is clearly the main application trend, particularly predicting risk and thus supporting credit approval or de- nial. There is also a relevant interest in bankruptcy and fraud prediction. Customer retention seems to be associated, although weakly, with targeting, justifying bank offers to reduce churn. In addition, a large number of ar- ticles focused more on business intelligence techniques and its applications, using the banking industry just for evaluation, thus, not clearly acclaiming for benefits in the banking business. By identifying these current research topics, this study also highlights opportunities for future research.

Productivity and human capital: a business-level analysis

This paper aims to analyse the impact of human capital on business productivity, focusing the analysis on the possible effect of the complementarity that exists between human capital and new production technologies, particularly advanced manufacturing technologies (AMTs) for the specific case of small and medium enterprises (SMEs) in Catalonia. Additionally, following the theory of skill-biased technological change, the paper analyses whether technological change produces bias exclusively in the skills required for managers, or whether the bias extends to the skills required of production staff. With this objective, we have compared the possible existence of complementarity between AMTs and the level of human capital for different occupational groups. The results confirm the complementary relationship between human capital and new production technologies. The results by occupational group confirm that to maximise the productivity of new technologies, skilled staff are needed both in management and production, with managers and professionals as well as skilled operatives playing a vital role. Keywords: human capital, process technologies, complementarity, business productivity. (JEL D24, J24, O30).

A three-pronged approach to social business: a Brazilian multi-case analysis

Social businesses present a new paradigm to capitalism, in which private companies, non-profit organizations and civil society create a new type of business with the main objective of solving social problems with financial sustainability and efficiency through market mechanisms. As any new phenomenon, different authors conceptualize social businesses with distinct views. This article aims to present and characterize three different perspectives of social business definitions: the European, the American and that of the emerging countries. Each one of these views was illustrated by a different Brazilian case. We conclude with the idea that all the cases have similar characteristics, but also relevant differences that are more than merely geographical. The perspectives analyzed in this paper provide an analytical framework for understanding the field of social businesses. Moreover, the cases demonstrate that in the Brazilian context the field of social business is under construction and that as such it draws on different conceptual influences to deal with a complex and challenging reality.

Permanent demand excess as business strategy: an analysis of the Brazilian higher-education market

Many Higher Education Institutions (HEIs) establish tuition below the equilibrium price to generate permanent demand excess. This paper first adapts Becker’s (1991) theory to understand why the HEIs price in this way. The fact that students are both consumers and inputs on the education production process gives rise to a market equilibrium where some firms have excess demand and charge high prices, and others charge low prices and have empty seats.Second, the paper analyzes this equilibrium empirically. We estimated the demand for undergraduate courses in Business Administration in the State of São Paulo. The results show that tuition, quality of incoming students and percentage of lecturers holding doctorates degrees are the determining factors of students’ choice. Since the student quality determines the demand for a HEI, it is calculated what the value is for a HEI to get better students; that is the total revenue that each HEI gives up to guarantee excess demand. Regarding the “investment” in selectivity, 39 HEIs in São Paulo give up a combined R$ 5 million (or US$ 3.14 million) in revenue per year per freshman class, which means 7.6% of the revenue coming from a freshman class.

Business Exits entail greater future levels of entrepreneurship? An empirical analysis at country level

Using Global Entrepreneurship Monitor data for 41 countries this study investigates the impact of business exit on entrepreneurial activity at the country level. The paper distinguishes between two types of entrepreneurial activity according with the motive to start a new business: entrepreneurs driven by opportunity and necessity motives. The findings indicate that exits have a positive impact on future levels of entrepreneurial activity in a country. For each exit in a given year, a larger proportion of entrepreneurial activity the following year. Moreover, this e ffect turns out to be higher for opportunity entrepreneurs. The findings indicate that both types of entrepreneurial activity rates are influenced by the same factors and in the same direction. However, for some factors we find a di fferential impact on the entrepreneurship. The results show some important implications given that business exit may be overcome when there is a necessity motivation. This has important implications for both researchers and policy makers. JEL codes: L26. Keywords: Entrepreneurship, business exit, social values

Business Organization and Coordination in Marketing Specialty Hogs: A Comparative Analysis of Two Firms from Iowa, November 2005

We study business organization and coordination of specialty-market hog production using a comparative analysis of two Iowa pork niche-marketing firms. We describe and analyze each firms management of five key organizational challenges: planning and logistics, quality assurance, process verication and management of �credence attributes,� business structure, and profit sharing. Although each firm is engaged in essentially the same activity, there are substantial differences across the two firms in the way production and marketing are coordinated. These differences are partly explained by the relative size and age of each firm, thus highlighting the importance of organizational evolution in agricultural markets, but are also partly the result of a formal organizational separation between marketing and production activities in one of the firm.