Risk scoring models for trade credit in small and medium enterprises

Trade credit refers to providing goods and services on a deferred payment basis. Commercial credit management is a matter of great importance for most small and medium enterprises (SMEs), since it represents a significant portion of their assets. Commercial lending involves assuming some credit risk due to exposure to default. Thus, the management of trade credit and payment delays is strongly related to the liquidation and bankruptcy of enterprises. In this paper we study the relationship between trade credit management and the level of risk in SMEs. Despite its relevance for most SMEs, this problem has not been sufficiently analyzed in the existing literature. After a brief review of existing literature, we use a large database of enterprises to analyze data and propose a multivariate decision-tree model which aims at explaining the level of risk as a function of several variables, both of financial and non-financial nature. Decision trees replace the equation in parametric regression models with a set of rules. This feature is an important aid for the decision process of risk experts, as it allows them to reduce time and then the economic cost of their decisions

Effects of a single administration of prostaglandin F2alpha, or a combination of prostaglandin F2alpha and prostaglandin E2, or placebo on fertility variables in dairy cows 3–5 weeks post partum, a randomized, double-blind clinical trial

BACKGROUND: Delayed uterine involution has negative effects on the fertility of cows; use of prostaglandin F2alpha alone as a single treatment has not been shown to consistently improve fertility. Combined administration of PGF2alpha and PGE2 increased uterine pressure in healthy cows. We hypothesized, that the combination of both prostaglandins would accelerate uterine involution and have, therefore, a positive effect on fertility variables. In commercial dairy farming, the benefit of a single post partum combined prostaglandin treatment should be demonstrated. METHODS: 383 cows from commercial dairy farms were included in this study. Uterine size and secretion were evaluated at treatment 21–35 days post partum and 14 days later. Cows were randomly allocated to one of three treatment groups: PGF2alpha and PGE2, PGF2alpha or placebo. For every animal participating in the study, the following reproduction variables were recorded: Interval from calving to first insemination, days open, number of artificial inseminations (AI) to conception; subsequent treatment of uterus, subsequent treatment of ovaries. Plasma progesterone level at time of treatment was used as a covariable. For continuous measurements, analysis of variance was performed. Fisher's exact test for categorical non-ordered data and exact Kruskal-Wallis test for ordered data were used; pairwise group comparisons with Bonferroni adjustment of significance level were performed. RESULTS: There was no significant difference among treatment groups in uterine size. Furthermore, there was no significant difference among treatments concerning days open, number of AI, and subsequent treatment of uterus and ovaries. Days from calving to first insemination tended to be shorter for cows with low progesterone level given PGF2alpha and PGE2 in combination than for the placebo-group (P = 0.024). CONCLUSION: The results of this study indicate that the administration of PGF2alpha or a combination of PGF2alpha and PGE2 21 to 35 days post partum had no beneficial effect upon measured fertility variables. The exception was a tendency for a shorter interval from calving to first insemination after administration of the combination of PGF2alpha and PGE2, as compared to the placebo group. Further research should be done in herds with reduced fertility and/or an increased incidence of postpartum vaginal discharge