The uneven regional distribution of foreign direct investment (FDI) in Turkey poses an interesting question from the perspective of multinational firms (MNFs) and policy-makers alike. This paper focuses on the factors governing the location decisions of MNFs within Turkey with specific reference to policy implications. Using a conditional logit model, it is found that agglomeration, depth of local financial markets, human capital, and coastal access dominate location decisions for the aggregate sample of foreign investors in Turkey. This study reveals no evidence that public investment is successful in attracting MNFs to particular regions. Also importantly, the location determinants vary dramatically by broad industrial category, investment composition, and origin-country characteristics, including income category and region.

Increasing costs of direct marketing campaigns coupled with declining response rates have prompted many direct marketers to turn to more sophisticated techniques to model response behavior. The underlying premise is that even a small improvement in response rate can have significant implications for the bottom line. This article investigates the use of a recently developed technique, Multiple Adaptive Regression Splines (MARS), together with logistic regression in the context of modeling direct response. Specifically, our goal is to assess the relative effectiveness of MARS models vis-à-vis logistic regression with original predictor variables in modeling direct response behavior. Our analysis shows that the MARS models outperforms the logistic model in general, leading us to conclude that MARS offers a number of advantages over a logistic model. Direct marketing strategy implications are also discussed.

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Abstract:With the help of a Kohonen self-organising algorithm, this paper presents a mapping and analysis of the global digital divide along with its main drivers. Several broad groups and subgroups are identified, consisting of countries that are similar in their digital development and in a number of other attributes. We find that the digital divide seems to occur synchronously with divisions in income, social, demographic and infrastructure measures. By examining a large dataset of 160 countries over a short period of three years, we find evidence of both convergence and divergence among the countries over time. We expect these findings to inform the ongoing debate on drivers of the International Digital Divide (IDD). In addition, this paper provides a novel visualisation of the digital divide and its predictors on a two-dimensional grid. Extensions of this work, with the availability of more years of data, could investigate the potential convergence of countries to particular patterns of digital development.

We present to the statistical community an overview of five data mining packages with the intent of leaving the reader with a sense of the different capabilities, the ease or difficulty of use, and the user interface of each package. We are not attempting to perform a controlled comparison of the algorithms in each package to decide which has the strongest predictive power, but instead hope to give an idea of the approach to predictive modeling used in each of them. The packages are compared in the areas of descriptive statistics and graphics, predictive models, and association (market basket) analysis.As expected, the packages affiliated with the most popular statistical software packages (SAS and SPSS) provide the broadest range of features with remarkably similar modeling and interface approaches, whereas the other packages all have their special sets of features and specific target audiences whom we believe each of the packages will serve well. It is essential that an organization considering the purchase of a data mining package carefully evaluate the available options and choose the one that provides the best fit with its particular needs.