the marketing strategy toward international serviced satisfaction standard for travelers in gas...
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THE MARKETING STRATEGY TOWARD INTERNATIONAL SERVICED SATISFACTION STANDARD FOR TRAVELERS IN
GAS STATION ROADSIDE REST AREA
ANUCHA KUNTRARADUSADEE
EDUCATION BACKGROUND
INDUSTRIAL ENGINEER
RAJCHAMAKALA UNIVERSITY
MASTER OF BUSINESS ADMINISTRATION
KHONKAEN UNIVERSITY
PRESENT
DBA MARKETING (CANDIDATE)
SIAM UNIVERSITY
OCCUPATION
PETRONAS RETAIL (THAILAND) CO.,LTD.
PROJECT MANAGER
Garder and Bosonetto. (2002). Quantify Roadside Rest Area Usage in NETC. University of Maine, Orono, ME.
Blomquite and Carson. (1999). An Investigation of the Needs and Expectations of Rest Area Users in Montana. National Research Council, Washington D.C.
Horn and Tentacostle. (1999). Rest Area Forum: Summary of Proceedings. Atlanta, Georgia.
FHWA.(1996). Commercial Driver Rest Area & Parking Requirements: Making Space for Safety Final Report. Federal Highway Administration, Washington D.C.
AASHTO.(1999). A Guide for Development of Rest Area on Major Arterials and Freeways-Draft. American Association of State Highway and Transportation Officials, Washington D.C.
Kimberlee Langoft.(1996). Investigate the Public’s Perception of Highway Rest Area. Oregon Survey Research Laboratory University of Oregon.
FY 2006 REST AREA CUSTOMER SATISFACTION RESULTS
32 REST AREAS STATEWIDE
GOOD TO GREAT APRIL-JULY 2006
CONCEPTUAL FRAMWORK AND RESEARCH HYPOTHESIS
Personal Factor1. Gender2. Age3. Status4. Occupation5. Average income per month6. Education7. Objective of travel8. Travel colleague9. Nationality of gas station10. Type of vehicle11. Status of travel
Purchase Decision under Utilities Result1. Products and services2. Acceptance3. Sufficiency4. Accessibility5. Appropriateness
Satisfaction 1. Product of service2. Price of service 3. Place of service4. Promotion of service5. People of service6. Process of service7. Physical evidence of service
Marketing Strategy1. Product2. Price3. Place4. Promotion5. People6. Process7. Physical evidence
H 5H 4
H 6
H 3
H 2
H 1
StimulusThe physical Environment
OganismEmotional Response
Behavioral ResponseApproach-Avoidance
Responses
Merhrabian and Russell 1974
METHOD AND PROCEDURES
Population
Travelers Bangchak,
12.4%
Shell, 16.0%Esso, 17.6%
PTT, 32.7%
Petronas, 2.0%
JET, 6.8%
Caltex, 8.1%
Others, 4.4%
3,065 Station
sDepartment of Energy Business, June 2007
991
379
383
895
280
94
43
Located on Upcountry 40
0
Taro Yaman
e
(991 x 400)/3,065 =
130 (379 x 400)/3,065 =
50 (383 x 400)/3,065 =
50
(280 x 400)/3,065 =
35 (94 x 400)/3,065 =
15 (43 x 400)/3,065 = 5
(895 x 400)/3,065 =
115
FUEL
COVENIENCE STORETOILET
1
2
3
PAHOLYOTHIN
1
ASIA
2
RAMA 2
3
PETCHKASEM
4
MITAPHAP
5
SUKHUMVIT
6
SAMPLING PROCEDURES
400
+ =
June – October 2008
400 Sets
= 25
Northern = 81 Sets
= 10= 10
= 8
= 25
= 2= 1= 10
Central = 37 Sets
= 5= 5
= 3
= 10
= 3= 1=
20
Western = 54 Sets
= 10= 5
= 5
= 10
= 3= 1
= 30
North Eastern = 106 Sets
= 10= 10
= 8
= 45
= 2= 1= 20
Eastern = 61 Sets
= 5=
10
= 5
= 15
= 5= 1=
25
Southern = 61 ชุ�ด
= 10= 10
= 6
= 10
= 0= 0
QUESTIONNAIRE COLLECTED
MEASURES
Data Analysis1. Stability
2. ConsistencySPSS 14Reliability
1. Good-of-Fit Indices for the proposed Structural Equation Model
2. Testifying Hypothesis
AMOS 6Model
Questionnaire 1. Marketing Strategy 52 Clauses : Likert 5 Scale
2. Purchase Decision under Utilities Result 42 Clauses : Likert 5 Scale
3. Satisfaction after Service’s Delivery 51 Clauses : Likert 5 Scale
4. Personal Factor 11 Clauses : Checklist
IOC >0.50
α = 0.894
156 Clauses
Conclusion
Measurement Model
Findings
OccupationEmployee
62%
Travel StatusDriver 66%
Travel ObjectiveTourism 48.5%
Marriage 53%
VehiclePersonal car 58.5%
EducationB. Degree 68%
Age 31-50 Year68%
NationalityUnbiased 96%
Monthly Income> 30,000 บาท
52%
Traveler’s ProfileTraveler’s Profile1
Male 56.8%
Travel ColleagueFemale 59%
POPULATION CHARACTERISTICS
Model fit statistics collectively demonstrate that the research model fits that data well
MEASUREMENT MODEL
Index Criterion Statistics Value
Chi-Square
CMIN/DF
GFI
AGFI
NFI
IFI
CFI
RMR
RMSEA
P ≥ 0.05
≥ 0.90
≥ 0.90
≥ 0.90
≥ 0.90
≥ 0.90
< 0.05
< 0.05
Closed to 1
0.165
1.085
0.955
0.921
0.927
0.944
0.994
0.012
0.015
strategy
physice7
1
1processe6
1peoplee5
1promoe4
1placee3
1pricee2
1producte1
1
satisfy
sproduct e13
sprice e14
splace e15
spromo e16
speople e17
sprocess e18
sphysic e19
1
1
1
1
1
1
1
1
decision
fast
e12
1
1conven
e11
1volume
e10
1quality
e9
1pattern
e8
1
gender age status occu income edu object group admin vehicle travel
estrategy
1esatisfy
1
edecision
1
Conceptual Model
If factor loading > 0.30 mean model is validity
MEASUREMENT MODEL
strategy
physice7
1
1processe6
1peoplee5
1promoe4
1placee3
1pricee2
1producte1
1
satisfy
sproduct e13
sprice e14
splace e15
spromo e16
speople e17
sprocess e18
sphysic e19
1
1
1
1
1
1
1
1
decision
fast
e12
1
1conven
e11
1volume
e10
1quality
e9
1pattern
e8
1
gender age status occu income edu object group admin vehicle travel
estrategy
1esatisfy
1
edecision
1
Conceptual Model
0.7270.8070.7310.8110.8080.4040.454
Product of servicePrice of service Place of servicePromotion of servicePeople of serviceProcess of servicePhysical evidence of service
0.3550.3180.3880.8380.397
Products and servicesAcceptanceSufficiencyAccessibilityAppropriateness
0.6020.7510.6270.6320.6370.6110.875
ProductPricePlacePromotionPeopleProcessPhysical evidence
SatisfactionPurchase Decision
Marketing Strategy
Factor Loading
Item
Confirmatory Factor Analysis : CFA
STRUCTURAL MODEL
Structural Equation Modeling : SEM
Full Structure Equation Modeling
.17
strategy
.60 physic e7
.87 .35 process e6
.61 .36
people e5 .64
.41 promo e4
.63
.39 place e3 .63
.56 price e2
.75
.36 product e1
.60
.46
satisfy
.54 sproduct e13
.62 sprice e14
.54 splace e15 .66 spromo e16 .69 speople e17
.40 sprocess e18
.33 sphysic e19
.73 .81 .73 .81
.81 .00 .45
.14
decision .17
fast
e12
.40
.70 conven
e11
.84 .08
volume
e10
.39 .00 quality
e9
.32 .00
pattern
e8
.36
gender age status occu income edu object group admin vehicle travel
.46*
.28* .08*
-.06
.12
-.03 .01
-.04
.00 -.15*
.06
-.01 14*
.13
.16 .12
-.11
-.01 .00
.12
-.02 .14*
*-.09
.07 .03
.00
.05 -.23*
-.06
.01 .02
-.02
-.01 -.10
-.01
.09
estrategy esatisfy
edecision
.16 .31
-.05 .17
-.15 -.10
-.19 .00
-.02 .52
.46 -.06
.59 -.11
-.12 .00
.07 .00
.14
.03 .36
-.03 -.08
.12 .02
-.05 .15
-.05 .11
.15 .00
-.11 -.04
-.08
.11 -.01
.07 -.01
.09 .22
.21 .17
-.10 .09
-.07
.24 .04
-.13 -.13
-.01 -.07
-.34 .03
.07 .21
-.21
-.21
-.32
-.30 -.02
-.25 -.14
-.23
-.05
-.08
.01
-.53
-.76
-.37 .36
.22 .15
.56
.25 .22
-.12 .18
.09 .17
.07
.11
-.02
.03
.11
-.17 .14
.01
.08
-.07 .16*
.05
.11
-.03
-.16
.09
.12 .43
-.23
-.26
.03
-.55
-.12
-.10
-.10
-.09
-.16
-.14 .16
.11 -.14
.11
.20
.07
-.09
-.02 .18 -.29
Chi-square = 282.232, df = 263, p-value = 0.165, CMIN/DF = 1.085, GFI = 0.955, NFI = 0.927, CFI = 0.994, RMSEA = 0.015, RMR = 0.012, *p <0.05
= - 0.063 gender + 0.011age - 0.153* status + 0.142* occu + 0.123 income + 0.00 edu + 0.140* object + 0.027 colleag – 0.232* nation
+ 0.023 vehicle - 0.105 travel; R2 = 0.169 (16.9%)
Marketing strategy
= 0.115 gender –0.037 age + 0.057 status + 0.126* occu – 0.114 income + 0.125 edu – 0.094 object + 0.005 colleag –0.056 nation - 0.020 vehicle -0.005 travel + 0.277* strategy; R2 = 0.144 (14.4%)
Purchase decision under utilities result
Satisfaction after services’ delivery= -0.034 gender +0.000 age –0.015 status + 0.158* occu –0.012
income - 0.020 edu + 0.073 object + 0.050 group + 0.014 admin – 0.012vehicle + 0.088 travel + 0.462* strategy + 0.083* decision; R2 = 0.455 (45.5%)
Purchase Decision under Utilities Result1. Products and services2. Acceptance3. Sufficiency4. Accessibility5. Appropriateness
Satisfaction after Services’ Delivery1. Product of service2. Price of service 3. Place of service4. Promotion of service5. People of service6. Process of service7. Physical evidence of service
Marketing Strategy1. Product2. Price3. Place4. Promotion5. People6. Process7. Physical evidence
Path Coefficient =0.158*
Personal Factor1. Status2. Objective of travel3. Nationality of gas station
4. Occupation
Path Coefficient = 0.083*
Path Coefficient = 0.126*
Path Coefficient = 0.462*
Path Coefficient = 0.277*
Path Coefficient = 0.142*
Path Coefficient = -0.153*, 0.140*, and -
0.232 respectively
Parsimonious Model
CONCLUSION
Marketing strategy quite significant related to international serviced satisfaction standard in gas station roadside rest area.
R2
45.5%(0.455x100)
R2>0.40 Saris & Strenkhorst, 1984
BIBLIOGRAPHY
AASHTO. (1999). A Guide for Development of Rest Areas on Major Arterials and Freeways-Draft. American Association of State Highway and Transportation Officials, Washington D.C.
Blomquist, D. and Carson, J.L. (1999). An Investigation of the Needs and Expectations of Rest Area Users in Montana. Transportation Research Board 79th Annual Meeting Preprint CD-ROM, National Research Council, Washington D.C.
FHWA. (1996). Commercial Driver Rest Area & Parking Requirements: Making Space for Safety Final Report. Federal Highway Administration, Washington D.C.
Garder, Per. (1999). Quantifying Roadside Rest Area Usage. Proposal to NETC. University of Maine, Orono, ME.
Haworth, N.L. (1998). Fatigue and fatigue research: The Australian experience paper presented to 7th Biennial Australasian Traffic Education Conference, Speed, Alcohol, Fatigue, Effects, Brisbane.
Michael, A. Perfater. (1988). Operation and Motorist Usage of Interstate Rest Areas and Welcome Centers in Virginia, Transportation Research Record, Virginia Transportation Research Council.
Taylor, William, C. and Sung, Nakmoon. (1998). A Study of Highway Rest Areas and Fatigue Related Truck Crashes. Transportation Research Board 79th Annual Meeting Preprint CD-ROM, National Research Council, Washington D.C.
Tyrrell, Timothy J. (1999). Rhode Island Travel and Tourism Research Report v.16,#1. Office of Travel, Tourism and Recreation, Department of Resource Economics, University of Rhode Island.
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