Research Article
Regional Tourism Economic Impact Evaluation Based on Dynamic Input-Output Model
Table 3
Results of technical efficiency on inbound tourism.
| | | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 |
| | Hefei | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | | Huaibei | 0.41 | 1.00 | 0.94 | 1.00 | 1.00 | 1.00 | 0.47 | 1.00 | 0.98 | | Bozhou | 1.00 | 0.18 | 0.65 | 0.76 | 1.00 | 0.80 | 0.85 | 1.00 | 1.00 | | Suzhou | 0.88 | 0.41 | 1.00 | 0.94 | 1.00 | 0.71 | 1.00 | 0.53 | 0.66 | | Bengbu | 0.30 | 0.82 | 0.25 | 0.55 | 0.90 | 0.88 | 0.24 | 1.00 | 0.20 | | Fuyang | 0.80 | 1.00 | 0.56 | 1.00 | 1.00 | 1.00 | 1.00 | 0.50 | 0.80 | | Huainan | 0.50 | 0.52 | 0.44 | 0.83 | 0.94 | 1.00 | 0.90 | 0.62 | 1.00 | | Chuzhou | 0.10 | 0.38 | 0.26 | 0.36 | 1.00 | 0.54 | 0.53 | 1.00 | 0.66 | | Luan | 0.50 | 0.65 | 0.57 | 0.60 | 0.66 | 0.77 | 0.89 | 1.00 | 1.00 | | Maanshan | 0.56 | 1.00 | 1.00 | 1.00 | 0.69 | 1.00 | 0.18 | 0.21 | 0.22 | | Wuhu | 0.18 | 0.69 | 0.61 | 0.95 | 0.52 | 0.89 | 0.50 | 1.00 | 1.00 | | Xuancheng | 0.60 | 0.25 | 0.19 | 0.41 | 0.45 | 0.46 | 0.15 | 0.18 | 0.22 | | Tongling | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 0.33 | 0.14 | 0.17 | 0.39 | | Chizhou | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | | Anqing | 0.11 | 0.71 | 0.54 | 1.00 | 0.82 | 1.00 | 0.25 | 0.56 | 1.00 | | Huangshan | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | | Mean | 0.39 | 0.77 | 0.65 | 0.85 | 0.87 | 0.84 | 0.49 | 0.85 | 0.72 |
|
|
