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181. Planning methods using Data Envelopment Analysis and Markov Systems

Invited abstract in session MC-48: DEA and stochastic models, stream Data Envelopment Analysis and its Application.

Monday, 12:30-14:00
Room: 60 (building: 324)

Authors (first author is the speaker)

1. Andreas Georgiou
Quantitative Methods and Decision Analysis Lab, Dpt of Business Administration, University of Macedonia
2. Emmanuel Thanassoulis
Aston Business School, Aston University
3. George Tsaples
University of Macedonia
4. Konstantinos Kaparis
Business Administration, University of Macedonia

Abstract

This paper addresses contexts in manpower or in the progression of chronic diseases. It uses the notion of a cohort whose members advance through various states over time (e.g. employees or patients). The aim is to steer the system towards a desired state, or set of states, through interventions made by recruitment or treatments which are evaluated on their capacity to achieve this goal in fixed or free time control settings. The presentation is based on a modelling framework, which blends DEA with Markov Chains in radial and additive models. The Markov process offers a set of equations that can be used to describe the movement of entities through time in a hierarchical system (e.g. illness states) and makes possible the investigation of interventions in order to guide the system towards a desired future structure. A given set of possible policies (e.g., new treatments used in a health system) are treated as DMUS at each stage and various models, including single or two-stage configurations with recruitment Decision Making Units (DMUs), are presented in single or multiple targeting environments. The paper concludes by deliberating on the merits and constraints inherent in these models.

The research project was supported by the Hellenic Foundation for Research and Innovation (H.F.R.I) under the "2nd Call for H.F.R.I. Research Projects to support Faculty Members & Researchers" (Project Number: 3154).

Keywords

Status: accepted

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