Measuring dynamic efficiency: Theories and an integrated methodology

Almost all dynamic production systems are subject to lagged productive effects, which are an often-ignored latent source of interference in the efficiency measuring process. Existing data envelopment analysis (DEA) approaches rely on a static production environment. They can easily lead to biased ev...

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Bibliographic Details
Published in:European journal of operational research Vol. 203; no. 3; pp. 749 - 760
Main Authors: Chen, Chien-Ming, van Dalen, Jan
Format: Journal Article
Language:English
Published: Amsterdam Elsevier B.V 16.06.2010
Elsevier
Elsevier Sequoia S.A
Series:European Journal of Operational Research
Subjects:
Advertising
Applied sciences
Data envelopment analysis
Dynamic systems
Dynamic systems Data envelopment analysis Parametric programming Lagged effects Advertising
Efficiency
Exact sciences and technology
Firm modelling
Inference from stochastic processes; time series analysis
Inventory control, production control. Distribution
Lagged effects
Linear programming
Mathematics
Nonparametric inference
Operational research and scientific management
Operational research. Management science
Parameter estimation
Parametric programming
Probability and statistics
Sciences and techniques of general use
Statistics
Studies
North America
America
Lagged effects
Dynamic systems
Advertising
Parametric programming
Data envelopment analysis
Performance evaluation
Productivity
Production system
Motor car
Empirical method
Time series
Non parametric estimation
Autoregressive model
Dynamical system
Modeling
Static model
Firm management
Econometrics
Pharmaceutical industry
Dynamic model
Biased estimation
ISSN:0377-2217, 1872-6860
Online Access:Get full text
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Summary:Almost all dynamic production systems are subject to lagged productive effects, which are an often-ignored latent source of interference in the efficiency measuring process. Existing data envelopment analysis (DEA) approaches rely on a static production environment. They can easily lead to biased evaluation results due to the erroneous assumption. To tackle this issue, this paper develops a dynamic DEA model that allows intertemporal effects in efficiency measuring. Specifically, the dynamic DEA model incorporates dynamic factors via a linear parametric formulation. Our model can be applied in place of static DEA models to a wide range of applications, such as analyzing longitudinal firm performance and productivity changes. As for the empirical efficiencies, we demonstrate how the lag parameters in the dynamic model can be estimated by the panel vector autoregressive model (PVAR). We use our methodology to evaluate advertising efficiencies of several major automobile and pharmaceutical firms in North America. The result shows that using static DEA in dynamic production can lead to both rank reversals and changes in efficiency scores.
Bibliography:SourceType-Scholarly Journals-1
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ISSN:0377-2217
1872-6860
DOI:10.1016/j.ejor.2009.09.001