Branded hotels, the sample of this study, are mostly in franchise contracts with hotel brands (franchisors). Depending on levels, or contents of these franchise contracts, franchisors have different levels of controls on branded hotels under their umbrellas. For braned hotels with high-quality products, franchisors tend to have more strong control, or involvement in operation and management via a different type of contract: managment contracts. Management contracts are widely used for high-quaility hotels, rather than a typical franchise contract.
Thus, analyzing the multimarket effect among these high quality hotels may circumvent the argument that franchisors have limited controls on franchisees in the hotel industry.
This paper divided sample into two groups: low and high quality hotels. If a hotelโs rating is less 35(3.5 stars), it is sorted into a low quality group. If the rating of a hotel is equal to or higher than 35, it is sorted as a high-quality hotels. The following table summarizes ratings and the number of hotels per rating.
##
## 10 15 20 25 30 35 40 45 50
## 96 5 323 564 280 108 120 16 9The following Analyses are based on the assummption that high-quality hotels are under stronger control by franchisors.Thus, I created a data set only with high-quality hotels. #### Estimation ##### Model The following reduced form model is used with different specification of \(AVMMC\), the average multimarket contact across rivals in the focal markets:
\(adr_{it} = \beta_0 AVMMC_{it} + \sum_i^k \beta_k X_{it}^k + \epsilon_i\)
where \(adr\) is the average room rate, and \(X\) is a vector of hotel characteristics, local competitions, or fixed effects (chain fixed effect).
Similar to the previous analysis(the ones for all hotels in Houston), the same market definitions are used: 1) Distance bands, and 2) kth nearest rivals. Instead of using 2.5 miles as a cut-off, for this exercise, I used 5 miles as the cut-off since hotels in the sample are widely spread. For the kth nearest neighbors, I used 4 rivals.
In addition to these two apporaches, there are two additional ways of recongizing other markets: 1) all other markets, and 2) markets where a forcal firm is also the forcal firm in the market.
## Loading required package: Imap## Market id = 1
## Market id = 2
## Market id = 3
## Market id = 4##
## ====================================================================
## Dependent variable:
## -------------------------------------
## adr
## OLS instrumental
## variable
## (1) (2)
## --------------------------------------------------------------------
## avmmc -0.356 1.620*
## (0.428) (0.835)
##
## hi.sales -56.363 -166.581***
## (35.654) (54.282)
##
## s_rating 47.863*** 44.541***
## (8.057) (8.573)
##
## cbd 10.783* 14.172**
## (5.974) (6.410)
##
## air -16.714 -24.760
## (18.319) (19.517)
##
## factor(chain)2 9.229 13.439*
## (6.606) (7.121)
##
## factor(chain)3 -27.738*** -16.153*
## (8.293) (9.662)
##
## factor(chain)4 -37.618*** -41.517***
## (11.700) (12.408)
##
## factor(chain)7 -23.890* -3.394
## (12.471) (15.027)
##
## factor(chain)14 -85.235*** -60.007***
## (16.655) (19.710)
##
## factor(chain)16 4.216 13.273
## (7.903) (8.929)
##
## factor(chain)17 -100.816*** -81.313***
## (16.202) (18.428)
##
## factor(chain)18 125.369*** 138.470***
## (16.239) (17.736)
##
## factor(chain)19 169.401*** 179.950***
## (31.090) (32.979)
##
## factor(chain)26 -14.784 -7.781
## (11.936) (12.823)
##
## factor(chain)28 -35.099** -24.675
## (16.058) (17.324)
##
## factor(chain)40 24.522*** 35.002***
## (9.066) (10.255)
##
## Constant -16.184 -8.496
## (32.331) (34.182)
##
## --------------------------------------------------------------------
## Observations 211 211
## R2 0.696 0.663
## Adjusted R2 0.669 0.633
## Residual Std. Error (df = 193) 29.467 31.055
## F Statistic 26.011*** (df = 17; 193)
## ====================================================================
## Note: *p<0.1; **p<0.05; ***p<0.01##
## ====================================================================
## Dependent variable:
## -------------------------------------
## adr
## OLS instrumental
## variable
## (1) (2)
## --------------------------------------------------------------------
## avmmc 0.032 1.333*
## (0.435) (0.803)
##
## hi.sales -89.588** -162.209***
## (34.827) (51.582)
##
## s_rating 37.733*** 35.419***
## (7.826) (8.096)
##
## n_basic -27.620*** -30.931***
## (5.164) (5.551)
##
## n_room_type 10.710*** 11.819***
## (3.935) (4.066)
##
## n_room_amenity 2.803 2.283
## (1.945) (2.008)
##
## cbd 11.234* 13.143**
## (5.748) (5.963)
##
## air 6.913 4.405
## (17.730) (18.189)
##
## factor(chain)2 7.093 10.143
## (6.269) (6.604)
##
## factor(chain)3 -27.160*** -19.170**
## (7.923) (9.087)
##
## factor(chain)4 -36.382*** -39.402***
## (11.016) (11.379)
##
## factor(chain)7 -16.618 -3.281
## (11.883) (13.956)
##
## factor(chain)14 -80.757*** -60.636***
## (16.677) (19.950)
##
## factor(chain)16 7.310 13.275
## (7.459) (8.224)
##
## factor(chain)17 -68.775*** -53.856***
## (16.542) (18.580)
##
## factor(chain)18 122.700*** 127.894***
## (15.392) (15.975)
##
## factor(chain)19 161.703*** 168.314***
## (29.245) (30.120)
##
## factor(chain)26 -11.326 -9.891
## (11.575) (11.868)
##
## factor(chain)28 -55.337*** -48.738***
## (15.771) (16.491)
##
## factor(chain)40 17.145** 22.201**
## (8.620) (9.195)
##
## Constant 77.139** 93.224**
## (35.081) (36.838)
##
## --------------------------------------------------------------------
## Observations 211 211
## R2 0.737 0.724
## Adjusted R2 0.709 0.695
## Residual Std. Error (df = 190) 27.639 28.284
## F Statistic 26.599*** (df = 20; 190)
## ====================================================================
## Note: *p<0.1; **p<0.05; ***p<0.01##
## ====================================================================
## Dependent variable:
## -------------------------------------
## adr
## OLS instrumental
## variable
## (1) (2)
## --------------------------------------------------------------------
## avmmc2 0.155 13.228
## (4.567) (9.677)
##
## hi.sales -76.951** -138.694***
## (34.205) (53.136)
##
## s_rating 47.231*** 44.371***
## (8.101) (8.477)
##
## cbd 11.408* 12.633**
## (5.954) (6.131)
##
## air -18.264 -26.757
## (18.508) (19.684)
##
## factor(chain)2 10.041 14.581*
## (6.744) (7.489)
##
## factor(chain)3 -25.550*** -17.058*
## (8.457) (10.242)
##
## factor(chain)4 -38.245*** -31.936**
## (11.897) (12.818)
##
## factor(chain)7 -20.032 -6.058
## (12.656) (15.783)
##
## factor(chain)14 -80.499*** -64.373***
## (16.739) (20.037)
##
## factor(chain)16 5.954 14.941
## (8.287) (10.275)
##
## factor(chain)17 -97.143*** -83.725***
## (16.357) (18.832)
##
## factor(chain)18 127.839*** 137.172***
## (16.347) (17.754)
##
## factor(chain)19 171.421*** 181.495***
## (31.261) (32.580)
##
## factor(chain)26 -13.387 -1.953
## (12.515) (14.774)
##
## factor(chain)28 -33.122** -24.790
## (16.191) (17.392)
##
## factor(chain)40 26.514*** 35.283***
## (9.311) (11.079)
##
## Constant -14.730 -8.922
## (32.409) (33.304)
##
## --------------------------------------------------------------------
## Observations 211 211
## R2 0.695 0.682
## Adjusted R2 0.668 0.654
## Residual Std. Error (df = 193) 29.520 30.140
## F Statistic 25.878*** (df = 17; 193)
## ====================================================================
## Note: *p<0.1; **p<0.05; ***p<0.01##
## ====================================================================
## Dependent variable:
## -------------------------------------
## adr
## OLS instrumental
## variable
## (1) (2)
## --------------------------------------------------------------------
## avmmc2 1.972 4.814
## (4.394) (9.128)
##
## hi.sales -97.134*** -110.555**
## (32.476) (49.834)
##
## s_rating 37.392*** 36.819***
## (7.834) (8.007)
##
## n_basic -27.759*** -28.075***
## (5.065) (5.148)
##
## n_room_type 10.661*** 10.630***
## (3.915) (3.921)
##
## n_room_amenity 2.806 2.791
## (1.937) (1.939)
##
## cbd 11.311** 11.490**
## (5.717) (5.745)
##
## air 5.858 4.250
## (17.875) (18.458)
##
## factor(chain)2 7.742 8.784
## (6.389) (7.036)
##
## factor(chain)3 -26.021*** -24.100**
## (8.026) (9.684)
##
## factor(chain)4 -35.407*** -34.107***
## (11.146) (11.743)
##
## factor(chain)7 -14.888 -11.927
## (11.925) (14.558)
##
## factor(chain)14 -78.559*** -74.687***
## (16.389) (19.696)
##
## factor(chain)16 8.513 10.455
## (7.787) (9.521)
##
## factor(chain)17 -66.947*** -63.789***
## (16.504) (18.760)
##
## factor(chain)18 123.664*** 125.235***
## (15.478) (16.113)
##
## factor(chain)19 163.088*** 165.315***
## (29.350) (30.043)
##
## factor(chain)26 -9.949 -7.914
## (11.979) (13.290)
##
## factor(chain)28 -54.232*** -52.408***
## (15.861) (16.687)
##
## factor(chain)40 18.218** 19.942**
## (8.859) (10.108)
##
## Constant 78.272** 80.468**
## (34.816) (35.398)
##
## --------------------------------------------------------------------
## Observations 211 211
## R2 0.737 0.737
## Adjusted R2 0.709 0.709
## Residual Std. Error (df = 190) 27.625 27.656
## F Statistic 26.636*** (df = 20; 190)
## ====================================================================
## Note: *p<0.1; **p<0.05; ***p<0.01## Loading required package: dbscan##
## ====================================================================
## Dependent variable:
## -------------------------------------
## adr
## OLS instrumental
## variable
## (1) (2)
## --------------------------------------------------------------------
## avmmc.knn 0.433 -0.814
## (0.723) (1.070)
##
## hi.sales 67.892 70.405
## (73.977) (74.563)
##
## s_rating 52.088*** 56.167***
## (8.339) (8.786)
##
## cbd 15.861*** 14.181**
## (5.967) (6.105)
##
## air -52.488*** -47.509***
## (16.549) (16.967)
##
## factor(chain)2 15.132** 12.879*
## (6.609) (6.809)
##
## factor(chain)3 -18.641** -23.131***
## (8.268) (8.798)
##
## factor(chain)4 -30.552** -37.193***
## (12.421) (13.195)
##
## factor(chain)7 -16.528 -25.364*
## (12.966) (14.198)
##
## factor(chain)14 -77.085*** -83.809***
## (16.587) (17.241)
##
## factor(chain)16 10.375 6.889
## (7.974) (8.329)
##
## factor(chain)17 -92.591*** -100.151***
## (16.524) (17.316)
##
## factor(chain)18 133.963*** 129.804***
## (16.630) (16.961)
##
## factor(chain)19 175.574*** 165.211***
## (32.301) (33.195)
##
## factor(chain)26 -8.788 -16.115
## (12.860) (13.754)
##
## factor(chain)28 -20.408 -26.637
## (16.506) (17.088)
##
## factor(chain)40 35.398*** 27.503**
## (9.931) (11.172)
##
## Constant -63.123* -71.161*
## (36.317) (36.944)
##
## --------------------------------------------------------------------
## Observations 211 211
## R2 0.684 0.679
## Adjusted R2 0.656 0.651
## Residual Std. Error (df = 193) 30.049 30.280
## F Statistic 24.579*** (df = 17; 193)
## ====================================================================
## Note: *p<0.1; **p<0.05; ***p<0.01##
## ====================================================================
## Dependent variable:
## -------------------------------------
## adr
## OLS instrumental
## variable
## (1) (2)
## --------------------------------------------------------------------
## avmmc.knn 0.305 -0.386
## (0.690) (1.006)
##
## hi.sales 28.662 30.462
## (70.979) (71.191)
##
## s_rating 43.983*** 46.145***
## (8.139) (8.474)
##
## n_basic -25.746*** -25.903***
## (5.219) (5.235)
##
## n_room_type 10.461** 10.897***
## (4.062) (4.099)
##
## n_room_amenity 2.272 2.070
## (2.014) (2.031)
##
## cbd 16.848*** 16.030***
## (5.784) (5.864)
##
## air -29.903* -26.937
## (16.354) (16.694)
##
## factor(chain)2 12.898** 11.628*
## (6.310) (6.467)
##
## factor(chain)3 -20.103** -22.648***
## (7.908) (8.372)
##
## factor(chain)4 -29.212** -32.891***
## (11.812) (12.464)
##
## factor(chain)7 -13.588 -18.366
## (12.348) (13.370)
##
## factor(chain)14 -78.354*** -81.689***
## (16.199) (16.619)
##
## factor(chain)16 11.771 9.854
## (7.573) (7.858)
##
## factor(chain)17 -67.192*** -71.520***
## (16.854) (17.506)
##
## factor(chain)18 131.546*** 129.183***
## (16.101) (16.335)
##
## factor(chain)19 163.555*** 157.685***
## (30.767) (31.465)
##
## factor(chain)26 -8.430 -12.503
## (12.638) (13.381)
##
## factor(chain)28 -41.478** -44.842***
## (16.373) (16.796)
##
## factor(chain)40 25.814*** 21.307*
## (9.692) (10.821)
##
## Constant 27.517 23.875
## (38.995) (39.286)
##
## --------------------------------------------------------------------
## Observations 211 211
## R2 0.720 0.719
## Adjusted R2 0.691 0.689
## Residual Std. Error (df = 190) 28.496 28.571
## F Statistic 24.461*** (df = 20; 190)
## ====================================================================
## Note: *p<0.1; **p<0.05; ***p<0.01##
## ====================================================================
## Dependent variable:
## -------------------------------------
## adr
## OLS instrumental
## variable
## (1) (2)
## --------------------------------------------------------------------
## avmmc.knn2 3.497 -0.993
## (3.874) (5.229)
##
## hi.sales 71.396 68.019
## (73.934) (74.237)
##
## s_rating 51.293*** 54.134***
## (8.356) (8.671)
##
## cbd 16.655*** 14.886**
## (6.075) (6.250)
##
## air -52.471*** -50.271***
## (16.386) (16.532)
##
## factor(chain)2 15.534** 14.013**
## (6.603) (6.731)
##
## factor(chain)3 -17.674** -20.919**
## (8.324) (8.727)
##
## factor(chain)4 -29.135** -33.918**
## (12.498) (13.082)
##
## factor(chain)7 -14.677 -20.996
## (13.089) (14.026)
##
## factor(chain)14 -75.530*** -80.526***
## (16.671) (17.176)
##
## factor(chain)16 11.614 8.467
## (8.169) (8.556)
##
## factor(chain)17 -90.266*** -96.625***
## (16.834) (17.603)
##
## factor(chain)18 136.223*** 131.465***
## (16.940) (17.398)
##
## factor(chain)19 177.859*** 170.302***
## (32.364) (33.005)
##
## factor(chain)26 -7.177 -12.515
## (12.970) (13.662)
##
## factor(chain)28 -18.932 -23.607
## (16.585) (17.037)
##
## factor(chain)40 37.186*** 31.367***
## (10.136) (11.135)
##
## Constant -62.572* -66.866*
## (36.165) (36.445)
##
## --------------------------------------------------------------------
## Observations 211 211
## R2 0.685 0.683
## Adjusted R2 0.657 0.655
## Residual Std. Error (df = 193) 30.013 30.118
## F Statistic 24.664*** (df = 17; 193)
## ====================================================================
## Note: *p<0.1; **p<0.05; ***p<0.01##
## ====================================================================
## Dependent variable:
## -------------------------------------
## adr
## OLS instrumental
## variable
## (1) (2)
## --------------------------------------------------------------------
## avmmc.knn2 2.501 2.142
## (3.769) (4.817)
##
## hi.sales 30.773 30.584
## (70.938) (70.957)
##
## s_rating 43.476*** 43.686***
## (8.146) (8.333)
##
## n_basic -25.663*** -25.685***
## (5.218) (5.221)
##
## n_room_type 10.098** 10.178**
## (4.122) (4.175)
##
## n_room_amenity 2.446 2.408
## (2.042) (2.066)
##
## cbd 17.321*** 17.201***
## (5.859) (5.944)
##
## air -30.047* -29.838*
## (16.222) (16.316)
##
## factor(chain)2 13.213** 13.087**
## (6.317) (6.404)
##
## factor(chain)3 -19.341** -19.612**
## (8.005) (8.318)
##
## factor(chain)4 -28.175** -28.557**
## (11.914) (12.335)
##
## factor(chain)7 -12.329 -12.813
## (12.462) (13.101)
##
## factor(chain)14 -77.526*** -77.856***
## (16.217) (16.451)
##
## factor(chain)16 12.662 12.412
## (7.776) (8.050)
##
## factor(chain)17 -65.331*** -65.873***
## (17.243) (17.827)
##
## factor(chain)18 133.196*** 132.809***
## (16.427) (16.741)
##
## factor(chain)19 165.329*** 164.702***
## (30.892) (31.334)
##
## factor(chain)26 -7.266 -7.691
## (12.764) (13.249)
##
## factor(chain)28 -40.495** -40.849**
## (16.440) (16.705)
##
## factor(chain)40 27.215*** 26.728**
## (9.985) (10.782)
##
## Constant 27.417 27.200
## (38.866) (38.909)
##
## --------------------------------------------------------------------
## Observations 211 211
## R2 0.721 0.721
## Adjusted R2 0.691 0.691
## Residual Std. Error (df = 190) 28.478 28.478
## F Statistic 24.505*** (df = 20; 190)
## ====================================================================
## Note: *p<0.1; **p<0.05; ***p<0.01