AN EVALUATION OF PROCESS‐ORIENTED SUPPLY CHAIN MANAGEMENT FRAMEWORKS

Supply chain management (SCM) is implemented by integrating corporate functions using business processes within and across companies. Several process‐oriented frameworks for SCM have been proposed but only two of these provide sufficient detail to enable implementation. We evaluate the Supply‐Chain Operations Reference (SCOR) framework and The Global Supply Chain Forum (GSCF) framework using four criteria and identify their relative strengths and weaknesses.     

CRIME AND POVERTY: A SEARCH‐THEORETIC APPROACH*

Numerous studies document that criminal activity is positively related to unemployment and negatively related to educational attainment levels within given communities. We study this phenomenon in the context of a search‐equilibrium model, in which agents choose between formal employment and pursuing crime‐related activities (theft). Prior to their “occupational choices,” agents undertake costly schooling, raising their productivity. Crime acts, in essence, as a tax on human capital by affecting the probability that a worker's earnings (possessions) are subsequently appropriated. There are multiple equilibria. High crime, low levels of educational attainment, long spells of unemployment, and poverty are correlated across them.     

The Contingent Value of Responsive and Proactive Market Orientations for New Product Program Performance*

While the benefits of being market oriented are largely accepted, a group of scholars and managers remain skeptical. Marketing scholars have sought to counter the criticisms leveled against market orientation (MO) by arguing that it has both responsive and proactive dimensions. However, few studies have empirically examined the complexity of the effects of these dimensions on firm performance. Drawing on theories of resource‐based advantage and organizational search behavior, this article advances understanding by arguing that responsive and proactive market orientations have curvilinear effects on product development performance, that their interaction may be positively related to product development performance, and that their effects on new product program performance are moderated differentially by the organizational implementation conditions and marketing function power. Survey results of 175 U.S. firms indicate support for most of the hypotheses. Specifically, whereas responsive MO has a U‐shaped relationship with new product program performance, proactive MO has an inverted U‐shaped relationship with new product program performance. Contrary to the arguments presented here, the interaction of both orientations is negatively related to new product program performance. This study finds that both orientations are needed; however, new product program performance is enhanced when one is at higher level and the other is at lower level. Finally, responsive MO is only positively related to new product program performance under specific conditions such as when strategic consensus among managers is high. On the other hand, the positive effect of proactive MO on new product program performance is further strengthened when learning orientation and marketing power are high. Overall, this study suggests that the effects of responsive and proactive MO on new product program performance are more complex than previously theoretically argued and empirically examined.     

Feature selection methods involving support vector machines for prediction of insolvency in non‐life insurance companies

We propose two novel approaches for feature selection and ranking tasks based on simulated annealing (SA) and Walsh analysis, which use a support vector machine as an underlying classifier. These approaches are inspired by one of the key problems in the insurance sector: predicting the insolvency of a non‐life insurance company. This prediction is based on accounting ratios, which measure the health of the companies. The approaches proposed provide a set of ratios (the SA approach) and a ranking of the ratios (the Walsh analysis ranking) that would allow a decision about the financial state of each company studied. The proposed feature selection methods are applied to the prediction the insolvency of several Spanish non‐life insurance companies, yielding state‐of‐the‐art results in the tests performed. Copyright © 2005 John Wiley & Sons, Ltd.     

Artificial neural networks with feature transformation based on domain knowledge for the prediction of stock index futures

A feature transformation method based on domain knowledge for arti?cial neural networks (ANNs) is proposed. The method of feature transformation based on domain knowledge converts continuous values into discrete values in accordance with the knowledge of experts in speci?c application domains. This approach effectively ?lters data, trains the classi?er, and extracts the rules from the classi?er. In addition, it reduces the dimensionality of the feature space, which not only decreases the cost and time in the operation but also enhances the generalizability of the classi?er. The experimental results of the proposed approach will be compared and tested statistically with the results of the linear transformation method. The results show that the method of feature transformation based on domain knowledge outperforms the linear transformation in modelling of ANNs. Copyright © 2004 John Wiley & Sons, Ltd.     

The service sector of Cuba: An analysis and critique

The Cuban economy has experienced a significant increase in foreign direct investment over the past decade due to the end of the Soviet Union and the establishment of more liberal trade policies. Although the U.S. embargo of trade with Cuba still exists, there has been movement lately that suggests the end of the four‐decades‐old policy. The purpose of this article is to analyze the current Cuban business environment and to identify potential entrepreneurial opportunities in the service sector. Major trade partners are also reviewed and managerial implications discussed. © 2006 Wiley Periodicals, Inc.     

This is what the leading indicators lead

We propose an optimal filter to transform the Conference Board Composite Leading Index (CLI) into recession probabilities in the US economy. We also analyse the CLI's accuracy at anticipating US output growth. We compare the predictive performance of linear, VAR extensions of smooth transition regression and switching regimes, probit, non‐parametric models and conclude that a combination of the switching regimes and non‐parametric forecasts is the best strategy at predicting both the NBER business cycle schedule and GDP growth. This confirms the usefulness of CLI, even in a real‐time analysis. Copyright © 2002 John Wiley & Sons, Ltd.     

Linking Public Investment to Private Investment. The Case of Spanish Regions

Public investment constitutes one of the main instruments of regional policies. The existence of a direct link between infrastructure and regional income per capita is usually accepted. Literature also describes a positive effect of public investment on private capital accumulation. This paper seeks to provide new empirical evidence on this latter relationship for the case of Spanish regions over the period 1965–1997 using panel data methodology. The results show a positive effect of productive and social public investment (especially in education) on private investment. The spillover effects generated by the productive infrastructures located in other regions do not seem to encourage the private investment in neighbouring regions. Public consumption and interest rate exert a negative influence on private capital accumulation. These results are robust to changes in the econometric specification.     

Enterprise Risk Management and the Cost of Capital

Enterprise risk management (ERM) is a process that manages all risks in an integrated, holistic fashion by controlling and coordinating any offsetting risks across the enterprise. This research investigates whether the adoption of the ERM approach affects firms' cost of equity capital. We restrict our analysis to the U.S. insurance industry to control for unobservable differences in business models and risk exposures across industries. We simultaneously model firms' adoption of ERM and the effect of ERM on the cost of capital. We find that ERM adoption significantly reduces firm's cost of capital. Our results suggest that cost of capital benefits are one answer to the question how ERM can create value.