Measuring the Effectiveness of Mutual Learning for Taiwan’s Tourist Hotels with the DEA Approach

Abstract

Taiwan’s international business and leisure hotels have created specific, divergent service operating systems to gain competitive advantage based on their distinctive target markets. For instance, the leisure properties focus on a hospitable, welcoming staff, while the business hotels aim for speedy service by employing relatively more workers. Given that hotel operators frequently benchmark direct competitors to improve on performance, researchers have suggested that hotel operators use a mutual learning strategy by benchmarking strategic techniques from hotels in disparate market segments. This study evaluates the effectiveness of the suggested mutual learning strategy between Taiwan’s business hotels and its leisure hotels, using the Different Systems model of data envelopment analysis (DEA) to examine potential improvements in efficiency. Empirical results show that few of Taiwan’s business hotels can gain efficiency through mutual learning from the leisure hotels—and some business hotels would actually lose efficiency if they adopted leisure properties’ operating practices. On the other hand, more than half of the leisure hotels in this sample would be able to achieve best practices from the mutual learning approach. On balance, both types of hotel can gain efficiency from the more common approach of benchmarking their direct competitors.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 25 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.