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.     

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.     

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.     

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.     

The role of news-based uncertainty indices in predicting oil markets: a hybrid nonparametric quantile causality method

A recent strand in the literature emphasizes the role of news-based economic policy uncertainty (EPU) and equity market uncertainty (EMU) as drivers of oil price movements. Against this backdrop, this paper uses a kth-order nonparametric quantile causality test, to analyse whether EPU and EMU predict stock returns and volatility. Based on daily data covering the period of 2 January 1986 to 8 December 2014, we find that, for oil returns, EPU and EMU have strong predictive power over the entire distribution barring regions around the median, but for volatility, the predictability virtually covers the entire distribution, with some exceptions in the tails. In other words, predictability based on measures of uncertainty is asymmetric over the distribution of oil returns and its volatility.     

Ethical Distance in Corrupt Firms: How Do Innocent Bystanders Become Guilty Perpetrators?

This paper develops the concept of the ‘continuum of destructiveness’ in relation to organizational corruption. This notion captures the slippery slope of wrongdoing as actors engage in increasingly dubious practices. We identify four kinds of individuals along this continuum in corrupt organizations, who range from complete innocence to total guilt. They are innocent bystanders, innocent participants, active rationalizers and guilty perpetrators. Traditional explanations of how individuals move from bystander status to guilty perpetrators usually focus on socialization and institutional factors. In addition to these factors, we propose that the very distance between an act and its ethical consequences (ethical distance) may also play a determining role – if not always in the same way – in the transition process. Having developed this conceptual argument, we conclude with a discussion of managerial and research implications. An Earlier version of this paper was presented at the The Twelfth Annual International Conference Promoting Business Ethics, New York, October 2005     

MODELLING BANKS' LENDING BEHAVIOUR IN A CAPITAL‐REGULATED FRAMEWORK

This paper adds to the literature on the money supply theory by assessing the effect of banks' equity on the loan generating process. First, a new ‘credit’ multiplier is examined, the so‐called ‘equity’ multiplier model. This, in a second stage, is incorporated in a new multivariate lending model. The models are assessed by using panel data cointegration techniques for the G7 countries. According to our results, a feedback relationship exists between banks' loans and equity. Moreover, the factors determining loans are: the aggregate demand, the loan–customer relation, the banks' equity and banks' portfolio adjustments and/or the monetary stance.     

Single Versus Multi-market Approach: An Application to the Greek Cotton Market

Estimation of the price-induced welfare effects in vertical and horizontal market settings may prove a tricky task when multiple price changes are taken into account. Whether a multi-market sequential approach or a single-market approach is used the well-established, theoretical result suggests that these two partial equilibrium methods are equivalent in terms of implied welfare changes. This paper develops the methodology to empirically compare these two methods. We estimate the welfare changes to Greek cotton–yarn producers induced by the simultaneous change in the prices of cotton–yarn and the cost of labor. Results substantiate the multi-market approach offers more accurate welfare estimates than the single-market approach, in empirical work.

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.     

AN EVALUATION OF THE GREEK UNIVERSITIES’ ECONOMICS DEPARTMENTS

This study provides a ranking of Economics Departments of Greek universities. Contrary to the existing literature, we look directly at the citations of the faculty members as a measure of academic performance and avoid the classification of journals. Additionally, the country of the PhD studies was found to be a significant variable that can explain the productivity of Greek economists. PhD holders from US and UK universities are characterized by higher productivity compared to those from other countries.