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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