A data envelopment analysis of organizational climate and performance in public transit operations

Concern about the spiraling growth of the national debt will focus more attention on the efficiency of government subsidized operations. Since public transit relies heavily on government subsidies to cover operating revenue shortfalls and to provide capital investment funds, transit management must be concerned with how efficiently input resources are used to produce the services demanded.;Transit managers have traditionally used cost efficiency and service effectiveness metrics to gauge organizational performance. However, these measures can be flawed by relative advantage when comparing similar operations. This study extends the application of Data Envelopment Analysis, a linear programming technique, which was designed to measure the relative efficiency of operating units with the same goals and objectives. This research hypothesized that Data Envelopment Analysis (DEA) would produce a more consistent view of transit performance than traditional performance statistics and that it would capture the impact of human resource development in the attainment of organizational goals.;A sample of 24 mid-sized agencies, Federal Transit Administration data, and an organizational climate survey were used to examine the research questions. There was some evidence of a positive relationship between DEA and traditional-statistics efficiency rankings; yet, different views of organizational performance were possible. Further examination failed to make a case for DEA as the better "discriminator" in individual agency comparisons as the traditional approach yielded a larger mean ranking. To estimate the impact of human resource development, possible organizational climate scores were related to Likert's System Four Management typology. The supposition was that more open, participative organizational climates would be positively linked with higher DEA efficiency scores. Correlation analysis using three different DEA algorithms produced only one significant relationship. Further statistical analysis dispelled a hypothesis that organizational climates of top performing agencies were significantly different from those of moderate-to-low performers.;Although this study did not make a superior case for using Data Envelopment Analysis to evaluate the efficiency of public transit agencies, it extends DEA's application and provides insight for future studies. Returns from the organizational climate survey show that transit management is moving towards a more open, participative environment.