Symmetric or Asymmetric Interest Rate Adjustments? Evidence from Southeastern Europe

The purpose of this paper is to examine how effectively the wholesale interest rates are transmitted to the retail rates and whether the interest rate passthrough is symmetric or asymmetric in Greece, Bulgaria, and Slovenia. The disaggregated general‐to‐specific methodology is applied for testing the symmetry hypothesis in these economies. It is evident from our results that variations exist across the countries examined regarding the monetary transmission process and the symmetry hypothesis alike. This can be interpreted as an indication of a different level of competition, development, and liberalization among the banking systems in these Southeastern European economies.     

Particle swarm optimization for optimal product line design

Designing optimal products is one of the most critical activities for a firm to stay competitive. Except for genetic algorithms, previous approaches that solve the optimal product line design problem provide the decision maker with a single best solution. Furthermore, they assume a static market, in which the incumbent firms will not respond to the entrance of a new player. In this paper we apply a new population-based algorithm called particle swarm optimization to the problem and employ a Monte Carlo simulation to compare its performance to that of genetic algorithms. The results indicate that the proposed particle swarm optimization algorithm constitutes an attractive alternative for solving the optimal product line design problem because its performance is comparable to that of genetic algorithms concerning the best solution found while it outperforms genetic algorithms regarding the diversity of the final set of provided solutions. Furthermore, we use concepts from game theory to illustrate how the algorithm can be extended to incorporate retaliatory actions from competitors. The dynamic approach is illustrated through a real-world case in which a firm intends to enter the Greek retail milk market. While employing highly simplifying assumptions, the incorporation of the Nash equilibrium concept provides useful insights, such as the attribute levels that may be resistant to competitive reactions and the incumbent firms that will benefit most in the long term.     

Parametric decomposition of the input-oriented Malmquist productivity index: with an application to Greek aquaculture

Using a stochastic frontier approach and a translog input distance function, this paper implements the input-oriented Malmquist productivity index to a sample of Greek aquaculture farms. It is decomposed into the effects of technical efficiency change, scale efficiency change, input-mix and, technical change, which is further attributed to neutral, output- and input-induced shifts of the frontier. Implementable expressions for the aforementioned components are obtained using a discrete changes-approach that is consistent with the usual discrete-form data. Empirical findings indicate that the productivity of the farms in the sample increased during the period 1995–1999 and it was shaped up primarily by the input mix-effect and technical change.     

Cross-Listing, Bonding Hypothesis and Corporate Governance

Abstract:  This paper examines the relationship between cross-listing and corporate governance for Canadian firms, that were cross-listed on US stock exchanges during the period 1997–2003. We find that cross-listed firms have more independent boards and audit committees after the listing relative to a non-cross-listed matched sample of firms and relative to the pre-listing period. Moreover, cross-listed firms experience changes in their ownership structure after the listing. Finally, we provide evidence that the sensitivity of the relation between cross-listed firm valuation with audit committee independence and ownership structure becomes more important after the listing. The results are robust after adjusting for various firm risk characteristics. Overall, the results are consistent with the literature on the bonding role of cross-listings on US stock exchanges.     

Process-oriented knowledge management systems based on KM-services: the PROMOTE® approach

This article describes the PROMOTE^® approach, to define and implement a Service-Based Enterprise Knowledge Management System (E-KMS) that has been developed during the EC-funded project PROMOTE (IST-1999-11658). The aim is to define a modelling language that is used to analyse, document and implement an E-KMS on the basis of so-called Knowledge Management Processes (KMPs). KMPs define the knowledge interaction between knowledge workers in a process-oriented manner and consists of activities that are supported by knowledge management key actions (KA) like searching, categorising or storing information. These knowledge management key actions are supported by Knowledge Management Services (KM-Service). The prototype of PROMOTE^® is briefly mentioned to discuss the KMP-models and the service based E-KMS. Copyright © 2003 John Wiley & Sons, Ltd.     

U-type and column-orthogonal designs for computer experiments

U-type designs and orthogonal Latin hypercube designs (OLHDs) have been used extensively for performing computer experiments. Both have good spaced filling properties in one-dimension. U-type designs may not have low correlations among the main effects, quadratic effects and two-factor interactions. On the other hand, OLHDs are hard to be found due to their large number of levels for each factor. Recently, alternative classes of U-type designs with zero or low correlations among the effects of interest appear in the literature. In this paper, we present new classes of U-type or quantitative \(3\) -orthogonal designs for computer experiments. The proposed designs are constructed by combining known combinatorial structures and they have their main effects pairwise orthogonal, orthogonal to the mean effect, and orthogonal to both quadratic effects and two-factor interactions.     

Dismantled Spatial Fixes in the Aftermath of Recession: Capital Switching and Labour Underutilization in the Greek Capital Metropolitan Region

The article offers a fresh, empirically grounded look at the spatialities of crisis‐triggered employment forms—a largely overlooked issue in contemporary critical geography literature. Specifically, it discusses the interconnection between investment flows from manufacturing to the built environment (capital switching) and underemployment in urban metropolitan regions to substantiate its impact on emerging spatial fixities. The article, which is based on an empirical analysis informed by a radical political economy, investigates changing fixed capital formations in Greece over an extended period prior to and during the recession, from 1995 to 2012. It traces the evolution of part‐time waged work in the capital metropolitan region of Attica (Athens) vis‐à‐vis the rest of the country's regional labour markets, focusing on the polarized 2005–2012 period and the demise of the construction industry. The article highlights that ‘disrupted’ capital switching that occurred in Greece, closely associated with recalibrated sectoral priorities and institutional interventions, resulted in the uneven sprawling of underemployment. Our findings offer insight into how the dismantling of spatial fixes within core metropolitan regions of the southern European Union (and beyond) are connected to labour surplus and successive slumps in manufacturing and construction. The article closes by calling for new theorizations of contemporary urban regional unevenness and its spatiotemporal fixities, which account for the role of changes in labour turnover time.     

On the construction of <Emphasis Type="Italic">E</Emphasis>(<Emphasis Type="Italic">s</Emphasis><Superscript>2</Superscript>)-optimal supersaturated designs

Supersaturated designs are an important class of factorial designs in which the number of factors is larger than the number of runs. These designs supply an economical method to perform and analyze industrial experiments. In this paper, we consider generalized Legendre pairs and their corresponding matrices to construct E(s ²)-optimal two-level supersaturated designs suitable for screening experiments. Also, we provide some general theorems which supply several infinite families of E(s ²)-optimal two-level supersaturated designs of various sizes.      

Nonparametric tests for Optimal Predictive Ability

A nonparametric method for comparing multiple forecast models is developed and implemented. The hypothesis of Optimal Predictive Ability generalizes the Superior Predictive Ability hypothesis from a single given loss function to an entire class of loss functions. Distinction is drawn between General Loss functions, Convex Loss functions, and Symmetric Convex Loss functions. The research hypothesis is formulated in terms of moment inequality conditions. The empirical moment conditions are reduced to an exact and finite system of linear inequalities based on piecewise-linear loss functions. The hypothesis can be tested in a statistically consistent way using a blockwise Empirical Likelihood Ratio test statistic. A computationally feasible test procedure computes the test statistic using Convex Optimization methods, and estimates conservative, data-dependent critical values using a majorizing chi-square limit distribution and a moment selection method. An empirical application to inflation forecasting reveals that a very large majority of thousands of forecast models are redundant, leaving predominantly Phillips Curve-type models, when convexity and symmetry are assumed.     

Hybrid particle swarm optimization with mutation for optimizing industrial product lines: An application to a mixed solution space considering both discrete and continuous design variables

This article presents an artificial intelligence-based solution to the problem of product line optimization. More specifically, we apply a new hybrid particle swarm optimization (PSO) approach to design an optimal industrial product line. PSO is a biologically-inspired optimization framework derived from natural intelligence that exploits simple analogues of collective behavior found in nature, such as bird flocking and fish schooling. All existing product line optimization algorithms in the literature have been so far applied to consumer markets and product attributes that range across some discrete values. Our hybrid PSO algorithm searches for an optimal product line in a large design space which consists of both discrete and continuous design variables. The incorporation of a mutation operator to the standard PSO algorithm significantly improves its performance and enables our mechanism to outperform the state of the art Genetic Algorithm in a simulated study with artificial datasets pertaining to industrial cranes. The proposed approach deals with the problem of handling variables that can take any value from a continuous range and utilizes design variables associated with both product attributes and value-added services. The application of the proposed artificial intelligence framework yields important implications for strategic customer relationship and production management in business-to-business markets.