Abstract:The effect of corporate social responsibility (CSR) on financial performance has important implications for enterprises, communities, and countries, and the significance of this issue cannot be ignored. Therefore, this paper proposes an integrated model to explain the influence of CSR on financial performance with intellectual capital as a mediator and industry type as a moderator. Empirical results indicate that intellectual capital mediates the relationship between CSR and financial performance, and industry type moderates the direct influence of CSR on financial performance. Such results have critical implications for both academia and practice.

This paper presents a hybrid causal model for predicting the occurrence of currency crises by using the neuro fuzzy modeling approach. The model integrates the learning ability of the neural network with the inference mechanism of fuzzy logic. The empirical results show that the proposed neuro fuzzy model leads to a better prediction of crisis. Significantly, the model can also construct a reliable causal relationship among the variables through the obtained knowledge base. Compared to neural network and the traditionally used techniques such as logic, the proposed model can thus lead to a somewhat more prescriptive modeling approach based on determinate causal mechanisms towards finding ways to prevent currency crises. (C) 2008 Elsevier Ltd. All rights reserved

Medication adherence plays an important role in disease management, especially for diabetes. The aim of this study was to examine the impacts of demographic characteristics on medication nonadherence and the impacts of nonadherence on both health status and medical expenses for diabetic patients in Taiwan. A total of 1 million diabetes mellitus patients were randomly selected from the National Health Insurance Research Database between January 1, 2000 and December 31, 2004. All records with missing values and those for participants under 18 years of age were then deleted. Because many patients had multiple clinical visit records, all records within the same calendar year were summarized into 1 single record for each person. This pre-processing resulted in 14,602 total patients with a combined 73,010 records over the course of 5 years. Generalized estimating equation models were then constructed to investigate the effects of demographic characteristics on medication nonadherence and the effects of nonadherence on patient health status and medical expenses. The demographic characteristics examined for each patient include gender, age, residential area, and socioeconomic status. Our analysis of how demographic variables impacted nonadherence revealed that elderly patients exhibited better overall medication adherence, but that male patients exhibited poorer medication adherence than female patients. Next, our analysis of how nonadherence impacted health status revealed that patients who exhibited medication nonadherence had poorer health status than patients with proper medication adherence. Finally, our analysis of how nonadherence impacted medical expenses revealed that patients who exhibited medication nonadherence incurred more medical expenses than those who exhibited proper medication adherence. This study's empirical results corroborate the general relationships expressed in the current literature regarding medication nonadherence. However, this study's results were statistically more reliable and revealed the precise impact on health status in terms of the Charlson comorbidity index and increased annual medical expenses. This indicates the need to improve patient attitudes toward medication adherence, which can have substantial effects both medically and economically.