Measuring the Efficiency of Highway Maintenance Operations: Environmental and Dynamic Considerations

Abstract

Highly deteriorated U.S. road infrastructure, major budgetary restrictions and the significant growth in traffic have led to an emerging need for improving efficiency and effectiveness of highway maintenance practices that preserve the road infrastructure so as to better support society's needs. Effectiveness and efficiency are relative terms in which the performance of a production unit or decision making unit (DMU) is compared with a benchmark (best practice). Constructing the benchmark requires making a choice between an "estimation approach" based on observed best practices (i.e., using data from input and output variables corresponding to observed production units (DMUs) to estimate the benchmark with no elaboration on the details of the production process inside the black box) or an "engineering approach" to find the superior blueprint (i.e., focusing on the transformation process inside the black box for a better understanding of the sources of inefficiencies). This research discusses: (i) the application of the estimation approach (non-parametric approach) for evaluating and comparing the performance of different highway maintenance contracting strategies (performance-based contracting versus traditional contracting) and proposes a five-stage meta-frontier and bootstrapping analytical approach to account for the heterogeneity in the DMUs, the resulting bias in the estimated efficiency scores, and the effect of uncontrollable variables; (ii) the application of the engineering approach by developing a dynamic micro-level simulation model for the highway deterioration and renewal processes and its coupling with calibration and optimization to find optimum maintenance policies that can be used as a benchmark for evaluating performance of road authorities.

This research also recognizes and discusses the fact that utilization of the maintenance budget and treatments that are performed in a road section in a specific year directly affect the road condition and required maintenance operations in consecutive years. Given this dynamic nature of highway maintenance operations, any "static" efficiency measurement framework that ignores the inter-temporal effects of inputs and managerial decisions in future streams of outputs (i.e., future road conditions) is likely to be inaccurate. This research discusses the importance of developing a dynamic performance measurement framework that takes into account the time interdependence between the input utilization and output realization of a road authority in consecutive periods.

Finally, this research provides an overview of the most relevant studies in the literature with respect to evaluating dynamic performance and proposes a classification taxonomy for dynamic performance measurement frameworks according to five issues. These issues account for major sources of the inter-temporal dependence between input and output levels over different time periods and include the following: (i) material and information delays; (ii) inventories; (iii) capital or generally quasi-fixed factors and the related topic of embodied technological change; (iv) adjustment costs; and (v) incremental improvement and learning models (disembodied technological change).

In the long-term, this line of research could contribute to a more efficient use of societal resources, greater level of maintenance services, and a highway and roadway system that is not only safe and reliable, but also efficient.