企業策略發展中一個立即需要處理的問題是協助廠商分群以及透過適當的標竿學習目標尋找出正確的策略群組。此外，少數的研究己經證實準固定投入對於觀光旅館服務業具有顯著的影響。因此，本論文應用修改後的情境相依資料包絡分析模型來辨別多層次的策略群組，並提出考量準固定投入下的二階段網路方向性函數來探索不同觀光旅館的生產效率, 服務效率與共同邊界技術無效率之來源。第一個實證結果整合吸引力與進步力繪製出一個明確的標竿學習路徑，這個標竿學習路徑能夠引導無效率的觀光旅館辨別出適當的學習榜樣，以達到卓越的績效。最後，第二個實證結果發現造成全體觀光旅館生產無效率的主要原因是因為生產階段投入過多所導致，而全體觀光旅館服務無效率的主要原因則是來自於服務階段產出過少所導致。

The immediate question is how to group firms and choose the right strategic groups of firms from which to determine appropriate benchmark targets is important in the development of business strategies. In addition, few studies have considered the quasi-fixed inputs that have an impact on hospitality. In this dissertation, a revised context-dependent data envelopment analysis model is applied to identify multilevel strategic groups and this study proposes the use of the two-stage network directional distance function with quasi-fixed inputs to explore the productive and service efficiencies of various tourist hotel formats　and identifies the source of the meta-frontier inefficiency. By integrating attractiveness scores and progress scores, a clear benchmarking path is designed for each hotel in the first empirical result. This path can guide inefficient hotels in identifying suitable role models for excellence. Finally, the causes of the overall productive inefficiency and the overall service inefficiency are mainly derived from the input excess of the productive process and the output shortfall of the service process, respectively in the second empirical result.

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