Incorporating destination quality into the measurement of tourism performance: A Bayesian approach

• We incorporate destination quality in a dynamic stochastic frontier model.
• We differentiate between short-run and long-run measures of destination quality and technical efficiency.
• A stochastic frontier model with destination quality outperforms other models that exclude destination quality.

Studies on destination benchmarking have so far ignored destination quality in the measurement of tourism performance. Destination quality plays a critical role in attracting tourism outputs (e.g. arrivals, receipts), and hence ignoring it represents an important shortcoming that might bias the benchmarking outcomes. The present paper develops for the first time a Bayesian stochastic frontier model that incorporates destination quality into the estimation of tourism performance. The model we propose benchmarks tourism destinations based on both overall performance (i.e. technical efficiency) and quality performance. We impose a dynamic structure on both technical efficiency and destination quality, and differentiate between short-run and long-run estimates of these measures. We provide ranking of technical efficiency and destination quality for 101 tourism destinations and discuss the implications of our findings.