Tarja Joro

Portfolio performance evaluation in a mean-variance-skewness framework

Abstract Astronomical amounts of money are being invested in financial markets. Consequently the evaluation of portfolio performance has created a great deal of interest among practitioners as well as academic researchers. The literature suggests that portfolio efficiency based on mean–variance–skewness is more desirable than the one based on mean–variance. However, there are no well-established procedures to measure efficiency in this framework, mainly due to the computational difficulties. The aim of this paper is to develop a portfolio performance measure based on mean–variance–skewness framework by utilizing a non-parametric efficiency analysis tool, namely ‘Data Envelopment Analysis’.

Workforce scheduling with multiple objectives

In workforce scheduling, the optimal schedule has traditionally been determined by minimizing the cost of labor subject to an acceptable service level, which is defined as the percentage of customers served within a predetermined time interval. We propose an alternative multidimensional paradigm, where cost minimization and service level maximization are considered simultaneously, together with other, complementary criteria. The ultimate goal of the proposed approach is to open a broader workforce scheduling paradigm that incorporates service quality into the analysis and provides the possibility to study the interaction between cost and service quality. Furthermore, the approach enables us to avoid strong assumptions. An example with real-world, empirical demand data is provided.

Freight transportation efficiency through horizontal cooperation in Flanders

This paper describes a practical application of data envelopment analysis (DEA) to the Flemish road transportation sector. The efficiency of 82 road transportation companies responding to a large-scale survey focused on horizontal cooperation is evaluated, based on two inputs and two outputs. Various DEA models are used to identify differences between subgroups of respondents. The results demonstrate that, in general, Flemish road transportation companies operate at unacceptably low efficiency levels. Given the findings that the median company is operating on too small a scale, one apparent remedy would be a dramatic increase in market concentration through mergers and acquisitions.

Weight-restricted DEA in action: from expert opinions to mathematical models

A common problem in real-world DEA applications is that all inputs and outputs may not be equally relevant to the organizations analysed and their stakeholders. In many cases, one is also faced with a data set where the decision-making units do not clearly outnumber the quantity of inputs and outputs. This study reports an application where DEA embellished with weight restrictions is used to analyse the efficiency of public organizations to overcome the above-mentioned problems. Whereas there are numerous documented applications of weight-restricted DEA in the literature, the process of defining the actual weight restrictions is seldom described. However, that part — defining the actual weights restrictions based on price, preference or value information — is the most difficult step involved in using the weight-restricted DEA. Comparing various weight restriction schemes with real data suggests that the ability to consider and include preference information in DEA adds important insights into the analysis.

An interactive approach to improve estimates of value efficiency in data envelopment analysis

Abstract Management Science 45 (1) (1999) 103–115 presents an approach for incorporating preference information in data envelopment analysis (DEA). In their paper, they develop value efficiency, an extension of the concept of efficiency in DEA. The paper presented an approach to estimate lower bounds for the value efficiency scores––efficiency measures that reflect the decision-maker’s (DM’s) preferences. In this paper, we develop some related concepts, and present two refinements: (1) Some bounds on the value efficiency scores that may be obtained without any DM involvement; and (2) A way of precisely measuring value efficiency scores with minimal DM involvement. The approach can also be used to explore whether certain underlying assumptions are met.

Dealing with Interval Scale Data in Data Envelopment Analysis

This papaer considers the problem of interval scale data in the most widely used models of Data Envelopment Analysis (DEA), the CCR, and the BCC models. Radial models require inputs and outputs measured on the ratio scale. Our focus is on how to deal with interval scale variables especially when the interval scale variable is a difference of two ratio scale variables like profit or the decrease/increase in bank accounts. Using these ratio scale variables as variables in the DEA model we suggest radial models. An approach to how to deal with interval scale variables when we relax the radiality assumption is also discussed.

PRICING AND INVENTORY STRATEGIES FOR A TWO-STAGE DUAL-CHANNEL SUPPLY CHAIN

The Internet is becoming increasingly important as a sales channel. Thus, most large retail firms have adopted a multi-channel strategy that includes both web-based channels and pre-existing offline channels. In this paper, we consider joint pricing and inventory/production decision problems for members in a monopoly two-stage dual-channel retailer supply chain. For a dual-channel retailer, pricing in one channel will affect the demand in the other channel. This subsequently affects the retailers replenishment (ordering) decisions, which have an impact on the producers inventory/production plans and wholesale price decisions. It is clear then that pricing decisions and inventory/production decisions are interacting in each member of the supply chain and among the members in the chain as well. In this paper, we analyze joint pricing and inventory/production problems under three scenarios by incorporating intra-product line price interaction in the EOQ model. We show that a unique equilibrium exists under certain realistic conditions. We also provide numerical results that offer insights for pricing strategies for the dual-channel retailer supply chain and for product design for different channels.

A value efficiency approach to incorporating preference information in data envelopment analysis [management performance analysis]

Summary form only as given. The traditional way to incorporate preference information in DEA is to restrict the weight flexibility. However, in some cases, this may be problematic. The authors present a method that instead of defining weights gives a new interpretation to efficiency based on preference information of the DM.

A simulation-based First-to-Default (FTD) Credit Default Swap (CDS) pricing approach under jump-diffusion

In recent years, the credit derivatives market has grown explosively and credit derivatives have become popular tools for hedging credit risk of financial institutions. Among the more sophisticated credit derivatives are the ones where the contingent payoffs depend on the dependence relationship among several firms in a basket, such as first-to-default credit default swap. In this paper, we present a simulation-based first-to-default credit derivative swap pricing approach under jump-diffusion and compare it with the popular default-time approach via Copula.

Extension of Data Envelopment Analysis with Preference Information

Introduction.- Data Envelopment Analysis.- Production Possibility Set and Efficiency.- Multiple Objective Linear Programming.- Comparison of Data Envelopment Analysis and Multiple Objective Linear Programming.- Incorporating Preference Information to Data Envelopment Analysis.- Value Efficiency Analysis.- Value Efficiency Analysis in Practice.- Extensions to Value Efficiency Analysis.-Non-Convex Value Efficiency Analysis.- Applications of Value Efficiency Analysis.- Conclusion.