日月潭國家風景區民宿業之營運效率初探

Operation Efficiency of the B&B Industry in Taiwan's Sun-Moon Lake Scenic Area: First Evidence

林灼榮(Jwu-Rong Lin) ； 郭姿妦 (Tzu-Feng Kuo)

《服務業管理評論》 9期 (2011/12) Pp. 87-103

https://doi.org/10.29858/SIMR.201112.0004

摘要

民宿之總出租客房數，短期往往無法隨著營運環境變遷而輕易調整；基於此特性，本文分別使用不可控制變數（Non-controllable Variable）與非任意變數（Non-discretionary Variable）等二種資料包絡分析法（DEA），推估日月潭國家風景區51家民宿業者之技術效率（簡稱TENC與TEND），並與傳統CCR與BCC模式之效率指標（技術效率（TE）、純技術效率（PE）、規模效率（SE））相比較；此外，本文考量人均住房價格，推估收益效率（RE）；最後，利用Tobit迴歸模型，推估客房住用率與住房價格，對上述效率六指標之衝擊效應。本文主要發現，包括：（1）當我們將總出租客房數視為固定或準固定投入時，DEA之投入導向效率邊界範圍將大於傳統DEA，進而增加標竿業者數目（效率等於1），並提高技術效率估計值；實證結果顯示，此二模式位於效率邊界之民宿家數，分別為19家及13家多於CCR模型之6家，而對應平均技術效率，分別為0.819與0.705，亦大於CCR之0.624。（2）結合CCR與BCC推估結果，發現14家達到純技術效率等於1之業者中，僅有6家屬於固定規模報酬之最適生產階段。（3）收益效率之平均值約0.715，顯示日月潭民宿業者尚有28.5%之收益增加空間；而經由差額變數分析，則仍存在約58.28%之總住宿人數增加空間。（4）經由Tobit迴歸分析結果，顯示提高客房住用率與降低住宿價格等促進需求策略，有助於改善經營效率，進而增加獲利空間。

關鍵字

民宿 ； 不可控制變數DEA ； 非任意變數DEA ； 收益效率DEA

並列摘要

The total number of available rooms in the B&B business cannot be easily adjusted with changes in the operation environment in the short term. This research hence adopts two types of data envelopment analysis (DEA) to assess technical efficiency (TENC based on non-controllable variable DEA versus TEND based on non-discretionary variable DEA) of 51 B&B businesses in Taiwan's Sun-Moon Lake Scenic Area and compare it with standard CCR DEA efficiency indicators (technical efficiency, pure technical efficiency, and scale efficiency). Revenue efficiency is also evaluated with per-person room rate data. Lastly, this paper employs the Tobit model to appreciate shock effects of the occupancy rate and room rate on the six efficiency measures. Major findings are as follows. First, as the total rooms available are regarded as fixed or quasi-fixed input, the efficiency frontier for input-based DEA is greater than that for standard DEA, raising the number of benchmark businesses (19 and 13 by TENC and TEND against 6 by CCR as regards those whose technical efficiency is set to unity) and the value of technical efficiency (0.819 and 0.705 against 0.624). Second, the combined result from CCR and BCC estimation shows that only 6 out of the 14 businesses with unity pure technical efficiency are at the optimal production stage of constant returns to scale. Third, average revenue efficiency is 0.715, suggest a potential increase of 28.5% in revenue for the B&B businesses, while slack variable analysis implies the potential of a 58.27% increase in the total number of guests. Fourth, Tobit regression results demonstrate that demand-orientated strategies such as a rise in the occupancy rate and a fall in the room rate help to improve operation efficiency and raise profit.

並列關鍵字

B&B ； Non-controllable Variable DEA ； Non-discretionary Variable DEA ； Revenue Efficiency DEA