1. THE MARKETING STRATEGY TOWARD INTERNATIONAL SERVICED SATISFACTION STANDARD FOR TRAVELERS IN GAS STATION ROADSIDE REST AREA ANUCHA KUNTRARADUSADEE

2.  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

3.  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.

4. FY 2006 REST AREA CUSTOMER SATISFACTION RESULTS 32 REST AREAS STATEWIDE GOOD TO GREAT APRIL-JULY 2006

5. CONCEPTUAL FRAMWORK AND RESEARCH HYPOTHESIS Personal Factor 1. Gender 2. Age 3. Status 4. Occupation 5. Average income per month 6. Education 7. Objective of travel 8. Travel colleague 9. Nationality of gas station 10. Type of vehicle 11. Status of travel Purchase Decision under Utilities Result 1. Products and services 2. Acceptance 3. Sufficiency 4. Accessibility 5. Appropriateness Satisfaction 1. Product of service 2. Price of service 3. Place of service 4. Promotion of service 5. People of service 6. Process of service 7. Physical evidence of service Marketing Strategy 1. Product 2. Price 3. Place 4. Promotion 5. People 6. Process 7. Physical evidence H 5 H 4 H 6 H 3 H 2 H 1 Stimulus The physical Environment Oganism Emotional Response Behavioral Response Approach-Avoidance Responses Merhrabian and Russell 1974

6. METHOD AND PROCEDURES Populati on Travelers 3,065 Stations Department of Energy Business, June 2007 99 1 37 9 38 3 89 5 28 0 94 43 Located on Upcountry 40 0 Taro Yamane (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

7. FUEL COVENIENCE STORE TOILET 1 2 3 PAHOLYOT HIN 1 ASI A 2 RAMA 2 3 PETCHKAS EM 4 MITAPH AP 5 SUKHUM VIT 6 SAMPLING PROCEDURES 400400 + = June – October 2008

8. 400 Sets = 25 Northern = 81 Sets = 10 =8=8 = 25 =2=2 =1=1 = 10 Central = 37 Sets =5=5 =5=5 =3=3 = 10 =3=3 =1=1 = 20 Western = 54 Sets = 10 =5=5 =5=5 =3=3 =1=1 = 30 North Eastern = 106 Sets = 10 =8=8 = 45 =2=2 =1=1 = 20 Eastern = 61 Sets =5=5 = 10 =5=5 = 15 =5=5 =1=1 = 25 Southern = 61 ชุด = 10 =6=6 =0=0 =0=0 QUESTIONNAIRE COLLECTED

9. MEASURES Data Analysis 1. Stability 2. Consistency SPSS 14 Reliability 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

10. Conclusion Measurement Model Findings

11. Occupation Employee 62% Travel Status Driver 66% Travel Objective Tourism 48.5% Marriage 53% Vehicle Personal car 58.5% Education B. Degree 68% Age 31-50 Year 68% Nationality Unbiased 96% Monthly Income > 30,000 บาท 52% Traveler’s Profile 1 Male 56.8% Travel Colleague Female 59% POPULATION CHARACTERISTICS

12. Model fit statistics collectively demonstrate that the research model fits that data well MEASUREMENT MODEL IndexCriterionStatistics Value Chi-Square CMIN/DF GFI AGFI NFI IFI CFI RMR RMSEA P ≥ 0.05 ≥ 0.90 < 0.05 Closed to 1 0.165 1.085 0.955 0.921 0.927 0.944 0.994 0.012 0.015 Conceptual Model

13. If factor loading > 0.30 mean model is validity MEASUREMENT MODEL Conceptual Model 0.727 0.807 0.731 0.811 0.808 0.404 0.454 Product of service Price of service Place of service Promotion of service People of service Process of service Physical evidence of service 0.355 0.318 0.388 0.838 0.397 Products and services Acceptance Sufficiency Accessibility Appropriateness 0.602 0.751 0.627 0.632 0.637 0.611 0.875 Product Price Place Promotion People Process Physical evidence Satisfaction Purchase Decision Marketing Strategy Factor Loading Item Confirmatory Factor Analysis : CFA

14. STRUCTURAL MODEL Structural Equation Modeling : SEM Full Structure Equation Modeling 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; R 2 = 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; R 2 = 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; R 2 = 0.455 (45.5%)

15. Purchase Decision under Utilities Result 1. Products and services 2. Acceptance 3. Sufficiency 4. Accessibility 5. Appropriateness Satisfaction after Services’ Delivery 1. Product of service 2. Price of service 3. Place of service 4. Promotion of service 5. People of service 6. Process of service 7. Physical evidence of service Marketing Strategy 1. Product 2. Price 3. Place 4. Promotion 5. People 6. Process 7. Physical evidence Path Coefficient = 0.158* Personal Factor 1. Status 2. Objective of travel 3. 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. R 2 45.5% (0.455x100) R 2 >0.40 Saris & Strenkhorst, 1984

16. 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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