HEDONIC PRICING MODEL · PHASE 3 INFERENTIAL STATISTICAL ANALYSIS Model 2.2 - Room Rate with Restaurant, Bar, and Tour Agents(adding significant variables). _cons 2 0 9 7 . 2 8 5
Post on 07-Jul-2020
0 Views
Preview:
Transcript
HEDONIC PRICING MODEL
LOCATION ACCESSIBILITY AND
CHARACTERISTICS OF HOTELS IN ASOKE AREA
Melissa Asawachatroj
Faculty Advisor: Daniel Ray
Lewis, Ph.D.
OUTLINE
Introduction
Hedonics Pricing Model
Definition of Location and Hotel
Characteristics
Methodology
Phase 1-Understanding Asoke area
Phase 2-Descriptive Statistical
Phase 3-Inferential Statistical Method
Conclusions
INTRODUCTION
Thailand GDP in Hotel and Restaurant 3
/1993
12/1
993
9/1
994
6/1
995
3/1
996
12/1
996
9/1
997
6/1
998
3/1
999
12/1
999
9/2
000
6/2
001
3/2
002
12/2
002
9/2
003
6/2
004
3/2
005
12/2
005
9/2
006
6/2
007
3/2
008
12/2
008
9/2
009
020,00040,00060,00080,000
100,000120,000140,000
GDP: Hotel and Restaurant (Thailand)
GDP: Hotel and Restaurant (Thailand)
Data Sources: CEIC in GDP: PCE: Trade, Hotel and Restaurant Services: Hotel and Restaurant (Thailand)
INTRODUCTION
“63 ทวนิส ์ลยุต่อธุรกจิคอนโดมิเนียม เอกมยั หลงัจากท าโรงแรม-อพารต์เมน้ทใ์หเ้ช่าย่าน
สขุุมวิททองหล่อ สรา้งรายไดก้ารเช่า 200 ลา้นต่อปี ปจัจบุนับรษิทัเป็นผูด้ าเนินธุรกจิคา้ผา้ย่าน
ส าเพง็ ชื่อเลก็ จูเนียร ์เทก็ซไทล ์สรา้งรายไดต่้อปีกวา่ 100 ลา้นบาท และเมือ่ 20 ปีก่อนไดเ้ริ่มธุรกจิ
โรงแรม และอพารต์เมน้ทใ์หเ้ช่า สุขมุวทิ 49 จ านวน 2 โครงการ ประมาณ 100 หอ้ง และโรงแรม
5 แห่ง ระดบั 3 ดาว บริเวณ สุขมุวทิ 13 ,22 , 49 และ 55 จ านวน 300 หอ้ง ทีส่รา้งรายไดร้วมต่อ
ปีกว่า 200 ลา้นบาท และในปีนี้มแีผนจะสรา้งโรงแรมอกี 3 แห่ง ในย่านสุขมุวทิ ทอง
หลอ่ รวมกนั 500 หอ้ง ใชเ้งนิลงทนุประมาณ 2,000 ลา้นบาท” จาก POST TODAY 14 ตุลาคม 2553
INTRODUCTION
Research contribution
This research is directly contributed to an upcoming hotel project in Asoke area
The investor would like to know :-the price of a room that he could charge for such property,-what characteristics it should have,-and what amenities and facilities it should be given to its guests.
OUTLINE
Introduction
Hedonics Pricing Model
Definition of Location and Hotel
Characteristics
Methodology
Phase 1-Understanding Asoke area
Phase 2-Descriptive Statistical Data
Phase 3-Inferential Statistical Method
Conclusions
HEDONIC PRICING MODEL
Hedonic Pricing Model
treats goods and services as providing a collection of characteristics
and can be applied to a market for any differentiated product and services
(Rosen, 1974).
The product a given hotel H is offering can be regarded as a set of
attributes, which consist of location and services-based characteristic:
Hi = P(qli, qsi)
o (Hi )=f(X)= β0+β1qli+β2qsi
OUTLINE
Introduction
Hedonics Pricing Model
Definition of Location and
Hotel Characteristics
Methodology
Phase 1-Understanding Asoke area
Phase 2-Descriptive Statistical Data
Phase 3-Inferential Statistical Method
Conclusions
DEFINITION OF LOCATION
ACCESSIBILITY AND HOTEL
CHARACTERISTICS Location Accessibility means the distance from or access to
one or more specific places.
Hotel Characteristics are used for specifying the characteristic
of a hotel accommodation; including room amenities.
o Hotel facility
o Room amenity
o Hotel services
OUTLINE
Introduction
Hedonics Pricing Model
Definition of Location and Hotel
Characteristics
Methodology Phase 1-Understanding Asoke area
Phase 2-Descriptive Statistical Data
Phase 3-Inferential Statistical Method
Conclusions
METHODOLOGY
Phase 3 Inferential Statistical Methods
Hedonics Pricing Modeling Analyse the Model
Phase 2 Descriptive Statistical Data
Specify geographic location of each hotel
Collecting data by survey & observation Evaluate the observed data
Phase 1 Understanding in Asoke Area
TAT, World’s tourist Organization
Gather prospect hotel list
Survey the tourist attraction Places
Interview the hotel managers
Phase 1
Understanding Asoke Area
PHASE 1 UNDERSTANDING ASOKE AREA
Asoke area: located around the intersection of Sukhumvit
and Ratchadapisek road its many adjoining 'soi'
It is surrounded by shopping, eating and nightlife places. While
still have touches of 'Thai' on every corners.
PHASE 1 UNDERSTANDING ASOKE AREA
Hotel industry in Asoke area
PHASE 1 UNDERSTANDING ASOKE AREA
The observation area
•Night life: soi cowboy and soi nana
•Transportation:2 BTS and MRT
Sample Size:53 hotels from soi 1 to 19
Phase 2
Observed Descriptive Statistics
PHASE 2 OBSERVED DESCRIPTIVE STATISTICS
Data collection
Price: the standard room rate per night during April
Location-the distances to BTS, MRT, and others convenient
location
Services hotel characteristics
o Review rating- reflection of guests’ satisfaction form the famous
internet booking websites
o Other hotel characteristics: from observation of each hotel
PHASE 2 OBSERVED DESCRIPTIVE STATISTICS
Prices Assumption•Prices are inclusive the services charge and VAT•Prices are inclusive breakfast•Prices are quoted from hotels’ website
Sample of Observed Data
PHASE 2 OBSERVED DESCRIPTIVE STATISTICS
Location Accessibility
The Hotel accessibility to the attractive tourism points, public transportations, and restaurants are calculated as the exact geographic(road) distances between hotels’ lobby and the target destinations.
PHASE 2 OBSERVED DESCRIPTIVE STATISTICS
Photograph of each Hotel :
PHASE 2 OBSERVED DESCRIPTIVE STATISTICS
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Room Amenities
PHASE 2 OBSERVED DESCRIPTIVE STATISTICS
0.77 0.74
0.45 0.43 0.43
0.34
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Hotel Facility Observation Result
PHASE 2 OBSERVED DESCRIPTIVE STATISTICS
Guest’s satisfaction rating
The analysis of the review rating for hotel uses information from the 4 most popular online internet booking services; including•www.agoda.co.th•www.sawasdee.com•www.tripadvisor.com•www.booking.com
Phase 3
Inferential Statistical Analysis
PHASE 3 INFERENTIAL STATISTICAL ANALYSIS
Hedonics Pricing method
a regression model will be used to estimate the hedonic
valuation and beta coefficients will be used to determine the
relative important factor of the different values factors.
Model and Variables :
Model1: Location Accessibility and Hotel Characteristics
Model2: Location Accessibility
Model3: Hotel Characteristics
PHASE 3 INFERENTIAL STATISTICAL ANALYSIS
Model 1 - Room rate with BTS, rating, and swimming
pool
_cons 2317.719 228.3108 10.15 0.000 1858.911 2776.527swimmingpool 413.0783 148.2294 2.79 0.008 115.2002 710.9563 ratingmean 106.6842 36.0674 2.96 0.005 34.20405 179.1644 bts -1569.994 364.3722 -4.31 0.000 -2302.228 -837.761 roomrate Coef. Std. Err. t P>|t| [95% Conf. Interval]
Total 27095206.7 52 521061.668 Root MSE = 522.33 Adj R-squared = 0.4764 Residual 13368426.3 49 272825.026 R-squared = 0.5066 Model 13726780.5 3 4575593.49 Prob > F = 0.0000 F( 3, 49) = 16.77 Source SS df MS Number of obs = 53
. reg roomrate bts ratingmean swimmingpool
PHASE 3 INFERENTIAL STATISTICAL ANALYSIS
Model 2.2 - Room Rate with Restaurant, Bar, and Tour
Agents(adding significant variables).
_cons 2097.285 261.0305 8.03 0.000 1571.858 2622.712 touragent 24.23111 161.9968 0.15 0.882 -301.8515 350.3138 bar -225.3565 151.7865 -1.48 0.144 -530.8869 80.17398 restaurant 365.2299 174.8024 2.09 0.042 13.37092 717.089swimmingpool 439.4678 149.4705 2.94 0.005 138.5993 740.3363 ratingmean 111.8222 35.58153 3.14 0.003 40.20026 183.4441 bts -1542.005 355.4085 -4.34 0.000 -2257.405 -826.6048 roomrate Coef. Std. Err. t P>|t| [95% Conf. Interval]
Total 27095206.7 52 521061.668 Root MSE = 509.06 Adj R-squared = 0.5027 Residual 11920539.3 46 259142.159 R-squared = 0.5600 Model 15174667.4 6 2529111.23 Prob > F = 0.0000 F( 6, 46) = 9.76 Source SS df MS Number of obs = 53
. reg roomrate bts ratingmean swimmingpool restaurant bar touragent
PHASE 3 INFERENTIAL STATISTICAL ANALYSIS
Model 3.2 - Room Rate with Refrigerator, microwave and
coffee maker(adding significant variables)
_cons 2061.613 416.7128 4.95 0.000 1222.814 2900.412 coffeemaker 97.26706 219.7911 0.44 0.660 -345.1495 539.6836 microwave -61.01518 177.6728 -0.34 0.733 -418.652 296.6216refrigerator 167.4994 265.8551 0.63 0.532 -367.6392 702.6381swimmingpool 376.7641 196.8836 1.91 0.062 -19.54203 773.0701 ratingmean 113.2053 38.85612 2.91 0.006 34.992 191.4186 bts -1431.743 419.2924 -3.41 0.001 -2275.735 -587.7515 roomrate Coef. Std. Err. t P>|t| [95% Conf. Interval]
Total 27095206.7 52 521061.668 Root MSE = 535.77 Adj R-squared = 0.4491 Residual 13204322.7 46 287050.494 R-squared = 0.5127 Model 13890884 6 2315147.33 Prob > F = 0.0000 F( 6, 46) = 8.07 Source SS df MS Number of obs = 53
. reg roomrate bts ratingmean swimmingpool refrigerator microwave coffeemaker
PHASE 3 INFERENTIAL STATISTICAL ANALYSIS
Model 3.3 - Room Rate with Safe box, Hair Dryer and
Bathtub(adding significant variables)
_cons 2237.045 288.649 7.75 0.000 1656.024 2818.065 bathtub 27.02331 164.7524 0.16 0.870 -304.606 358.6526 hairdryer 45.88483 179.7024 0.26 0.800 -315.8373 407.6069 safebox 44.47139 168.0755 0.26 0.793 -293.8471 382.7899swimmingpool 390.6283 163.369 2.39 0.021 61.78368 719.473 ratingmean 108.0725 39.08565 2.77 0.008 29.39715 186.7478 bts -1534.141 385.7037 -3.98 0.000 -2310.523 -757.7601 roomrate Coef. Std. Err. t P>|t| [95% Conf. Interval]
Total 27095206.7 52 521061.668 Root MSE = 537.61 Adj R-squared = 0.4453 Residual 13295119.5 46 289024.336 R-squared = 0.5093 Model 13800087.3 6 2300014.54 Prob > F = 0.0000 F( 6, 46) = 7.96 Source SS df MS Number of obs = 53
. reg roomrate bts ratingmean swimmingpool safebox hairdryer bathtub
PHASE 3 INFERENTIAL STATISTICAL ANALYSIS
Model 3.4 - Room Rate with Satellite TV, Bed style and
Window(adding significant variables)
_cons 1837.271 561.4839 3.27 0.002 707.0621 2967.479 window 50.82232 164.7935 0.31 0.759 -280.8898 382.5345 bedstyle 31.84003 94.04959 0.34 0.736 -157.472 221.152 sattelitetv 353.2059 286.4539 1.23 0.224 -223.3959 929.8077swimmingpool 381.705 162.2625 2.35 0.023 55.08751 708.3226 ratingmean 93.64812 42.284 2.21 0.032 8.534835 178.7614 bts -1522.7 373.9354 -4.07 0.000 -2275.393 -770.0073 roomrate Coef. Std. Err. t P>|t| [95% Conf. Interval]
Total 27095206.7 52 521061.668 Root MSE = 529.24 Adj R-squared = 0.4625 Residual 12884313.9 46 280093.781 R-squared = 0.5245 Model 14210892.8 6 2368482.13 Prob > F = 0.0000 F( 6, 46) = 8.46 Source SS df MS Number of obs = 53
. reg roomrate bts ratingmean swimmingpool sattelitetv bedstyle window
OUTLINE
Introduction
Hedonics Pricing Model
Definition of Location and Hotel
Characteristics
Methodology
Phase 1-Understanding Asoke area
Phase 2-Descriptive Statistical Data
Phase 3-Inferential Statistical Method
Conclusions
CONCLUSION
This research will help investors to :
Make smart decision on how to locate their hotels
Create smart budgeting plan on each facility and amenity What
facilities and characteristics of a hotel should be included, what
are their rank of importance
How the hotel should price its room rate to gain maximum profit
from competition point of view
To develop an accurate and efficient marketing plan.
CONCLUSION
Rank of importance of location and services hotel characteristics :
BTS, guest’s satisfaction rating, swimming pool, hotel
restaurant, Satellite TV, refrigerator, bed style, window, coffee
makers, safe box, hair dryer, bathtub, and microwave
PRACTICAL IMPLICATION
Model 2.2 Room Rate with Restaurant, Bar and Tour Agents
_cons 2097.285 261.0305 8.03 0.000 1571.858 2622.712 touragent 24.23111 161.9968 0.15 0.882 -301.8515 350.3138 bar -225.3565 151.7865 -1.48 0.144 -530.8869 80.17398 restaurant 365.2299 174.8024 2.09 0.042 13.37092 717.089swimmingpool 439.4678 149.4705 2.94 0.005 138.5993 740.3363 ratingmean 111.8222 35.58153 3.14 0.003 40.20026 183.4441 bts -1542.005 355.4085 -4.34 0.000 -2257.405 -826.6048 roomrate Coef. Std. Err. t P>|t| [95% Conf. Interval]
Total 27095206.7 52 521061.668 Root MSE = 509.06 Adj R-squared = 0.5027 Residual 11920539.3 46 259142.159 R-squared = 0.5600 Model 15174667.4 6 2529111.23 Prob > F = 0.0000 F( 6, 46) = 9.76 Source SS df MS Number of obs = 53
. reg roomrate bts ratingmean swimmingpool restaurant bar touragent
For the hotel management, hotelier can use the result of hedonics pricing model to use to estimate revenue effect of an investment and compare this with its cost.
AREA FOR FUTURE RESEARCH
L&H Property has joined hands with Siam Retail Development to develop
Terminal 21, (a Siam Paragon Sized Shopping Mall) aimed at offering a
brand new, ideal shopping experience for middle-income and tourists
around the world
Terminal 21 expected to draw a lot of attention of Asian tourists to the area
Thank you for yours attention
Special Thanks: Aj. Daniel Ray Lewis
top related