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.     

Intelligent Order Matching Systems for Commodity Markets

Automatic order matching systems have emerged as an electronic alternative to traditional markets. In current automatic order matching systems, price and quantity are the only product dimensions used for the order matching. However, a single-commodity market is made up of many heterogeneous goods which are close to each other but different in qualities and delivery conditions. Price and quantity are important but represent only parts of product attributes that commodity traders want to take into account. This study aims to extend current automatic order matching systems by diversifying product dimensions. An intelligent order matching system not only maximizes the total transaction volume based on the price and quantity but also satisfies traders' qualitative preferences over attributes other than price and quantity. The intelligent order matching mechanism combines an economic model with a preference model to incorporate both quantitative and qualitative utility of market participants. Constraint logic programming is investigated as a new information technology to structure and implement the intelligent order matching system.     

An appreciation of our referees

Editorial

An appreciation of our referees