A high breakdown,high efficiency and bounded influence modified GM estimator based on support vector regression

Regression analysis aims to estimate the approximate relationship between the response variable and the explanatory variables. This can be done using classical methods such as ordinary least squares. Unfortunately, these methods are very sensitive to anomalous points, often called outliers, in the data set. The main contribution of this article is to propose a new version of the Generalized M-estimator that provides good resistance against vertical outliers and bad leverage points. The advantage of this method over the existing methods is that it does not minimize the weight of the good leverage points, and this increases the efficiency of this estimator. To achieve this goal, the fixed parameters support vector regression technique is used to identify and minimize the weight of outliers and bad leverage points. The effectiveness of the proposed estimator is investigated using real and simulated data sets.     

The Convergence Between Outreach and Financial Performance in Mediterranean MFIs: A Panel Data Analysis

There is a long-standing debate on the relationship between outreach and financial performance in the microfinance institutions (MFIs). Although previous researches have reported contradictory results, many of these studies suffer from problems of misspecified model and/or restricted data. In this paper, we employ a static panel data analysis to empirically examine the impact of outreach on financial performance for a sample of 16 Mediterranean MFIs over the 2001–2008 period. Our evidence implies, first that the non-governmental organizations commercial viability increases with average loan size. Second, this commercial viability also increases with the number of outstanding loans per women. Finally, neither targeting the poor nor targeting women affect the repayment default.     

Analysis of survival data by a Weibull–Bessel distribution

In survival analysis and reliability studies, problems with random sample size arise quite frequently. More specifically, in cancer studies, the number of clonogens is unknown and the time to relapse of the cancer is defined by the minimum of the incubation times of the various clonogenic cells. In this article, we have proposed a new model where the distribution of the incubation time is taken as Weibull and the distribution of the random sample size as Bessel, giving rise to a Weibull–Bessel distribution. The maximum likelihood estimation of the model parameters is studied and a score test is developed to compare it with its special submodel, namely, exponential–Bessel distribution. To illustrate the model, two real datasets are examined, and it is shown that the proposed model, presented here, fits better than several other existing models in the literature. Extensive simulation studies are also carried out to examine the performance of the estimates.     

Feedback Mechanisms,Judgment Bias,and Trust Formation in Online Auctions*

Online markets, like eBay, Amazon, and others rely on electronic reputation or feedback systems to curtail adverse selection and moral hazard risks and promote trust among participants in the marketplace. These systems are based on the idea that providing information about a trader's past behavior (performance on previous market transactions) allows market participants to form judgments regarding the trustworthiness of potential interlocutors in the marketplace. It is often assumed, however, that traders correctly process the data presented by these systems when updating their initial beliefs. In this article, we demonstrate that this assumption does not hold. Using a controlled laboratory experiment simulating an online auction site with 127 participants acting as buyers, we find that participants interpret seller feedback information in a biased (non‐Bayesian) fashion, overemphasizing the compositional strength (i.e., the proportion of positive ratings) of the reputational information and underemphasizing the weight (predictive validity) of the evidence as represented by the total number of transactions rated. Significantly, we also find that the degree to which buyers misweigh seller feedback information is moderated by the presentation format of the feedback system as well as attitudinal and psychological attributes of the buyer. Specifically, we find that buyers process feedback data presented in an Amazon‐like format—a format that more prominently emphasizes the strength dimension of feedback information—in a more biased (less‐Bayesian) manner than identical ratings data presented using an eBay‐like format. We further find that participants with greater institution‐based trust (i.e., structural assurance) and prior online shopping experience interpreted feedback data in a more biased (less‐Bayesian) manner. The implications of these findings for both research and practice are discussed.     

The single-index support vector regression model to address the problem of high dimensionality

ABSTRACT

The last few years, the applications of Support Vector Machine (SVM) for solving classification and regression problems have been increasing, due to its high performance and ability to transform the non-linear relationships among variables to linear form by employing the kernel idea (kernel function). In this work, we develop a semi-parametric approach to fit single-index models to deal with high-dimensional problems. To achieve this goal, we use support vector regression (SVR) for estimating the unknown nonparametric link function, while the single-index is determined by using the semi-parametric least squares method (Ichimura 1993). This development enhances the ability of SVR to solve high-dimensional problem. We design a three simulation examples with high-dimensional problems (linear and nonlinear). The simulations demonstrate the superior performance of the proposed method versus the standard SVR method. This is further illustrated by applying the real data.     

Large urban developments as the new driver for land development in Jeddah

Land development in most Saudi cities including Jeddah is generated by formal land subdivision and informal land development usually referred to as unplanned settlements. Both types of developments contributed to urban sprawl and other urban challenges. Jeddah Municipality attempted to improve land development by encouraging large urban developments. Recently, Jeddah Municipality approved four large urban developments which appear to manifest encouraging implications for urban growth and land development that this paper aims to explore. The paper examines the policy and market contexts that govern land development in general and large urban developments in particular, in order to pave the way to uncover their implications for city growth and land development. The data gathered for this purpose is drawn from published and unpublished reports from relevant authorities. It is found that large urban developments as new mechanisms of land development appear incapable of overcoming key challenges that face city growth and existing land development.     

Information Technology and Process Performance: An Empirical Investigation of the Interaction Between IT and Non‐IT Resources*

Drawing on the resource‐based view, we propose a configurational perspective of how information technology (IT) assets and capabilities affect firm performance. Our premise is that IT assets and IT managerial capabilities are components in organizational design, and as such, their impact can only be understood by taking into consideration the interactions between those IT assets and capabilities and other non‐IT components. We develop and test a model that assesses the impact of explicit and tacit IT resources by examining their interactions with two non‐IT resources (open communication and business work practices). Our analysis of data collected from a sample of firms in the third‐party logistics industry supports the proposed configurational perspective, showing that IT resources can either enhance (complement) or suppress (by substituting for) the effects of non‐IT resources on process performance. More specifically, we find evidence of complementarities between shared business–IT knowledge and business work practice and between the scope of IT applications and an open communication culture in affecting the performance of the customer‐service process; but there is evidence of substitutability between shared knowledge and open communications. For decision making, our results reinforce the need to account for all dimensions of possible interaction between IT and non‐IT resources when evaluating IT investments.