Trip Generation at Fast Food Restaurants

Transcription

1 Trip Generation at Fast Food Restaurants in Saudi Arabia This study developed trip generation rates at fast food restaurants in Jeddah, Saudi Arabia. The results showed that vehicle trip rates were not significantly different when compared with respect to the type of food served, the presence of a drivethrough window and origin. A comparative analysis showed that the rates mentioned in Trip Generation were much higher than those found in this study. By Abdulrahem H.M. Al-Zahrani, Ph.D. and Tanweer Hasan, Ph.D. BACKGROUND The Kingdom of Saudi Arabia is a large developing country with an area of 2.25 million square kilometers and a population of about 24 million. The majority of the population lives in urbanized areas, 30 percent of which is concentrated in three major cities Riyadh, Jeddah and Dammam. 1 During the last two decades, these cities have experienced tremendously rapid growth. As a result of this growth, traffic volumes over certain corridors have begun to exceed capacity during peak hours, causing unacceptable levels of congestion. To control the traffic-related problems caused by the dramatic increase in population and automobile ownership and by the unplanned conversion of land-use activity types, the Ministry of Municipalities and Rural Affairs of the Kingdom of Saudi Arabia introduced a memorandum requiring investors in major projects that would generate substantial trips to conduct transportation impact studies. To conduct such studies, transportation planners and traffic engineers require estimates of the anticipated traffic volumes attracted to or produced by land uses. 2 Although many studies have been conducted in various countries to determine the trip rates for land uses, the most comprehensive document available to transportation officials to date is the Institute of Transportation Engineers (ITE) Trip Generation. 3 The main problem with using the trip generation rates mentioned in the ITE publication for different land uses is that the values reflect the conditions that exist in the United States. To get a better estimate of the trips generated by a particular land use, trip rates that reflect local conditions must be developed. This study was undertaken to determine the trip generation rates at fast food restaurants in Saudi Arabia. These types of restaurants are a relatively new concept in Saudi Arabia. They are becoming more popular for the following reasons: changes in Saudi lifestyle; almost 50 percent of the Saudi population is young (under 20 years old); and a large volume of single expatriates working in Saudi Arabia. Consequently, the high demand for this type of restaurant has encouraged many business entrepreneurs to invest in them. CHARACTERISTICS OF STUDY SITES The study sites were located within the city limits of Jeddah, the second largest city in Saudi Arabia. Jeddah can be characterized as a cosmopolitan urban area. It is located in the western region by the Red Sea and is the gateway to the two holy Grand Mosques in Makkah and Madinah. Jeddah has the largest seaport in Saudi Arabia, and 60 percent of the Kingdom s imports come through this port. A sample size should be sufficient to draw valid conclusions from the trip generation study. However, no simple statistical methodology has been established for determining the number of sites that should be studied to obtain statistically significant trip generation results. 4 The Trip Generation Handbook suggests that at least three sites (and preferably at least five) be surveyed. 5 Twenty fast food restaurants were selected for this study. They were all members of national and international chains. The study restaurants were grouped into two categories according to the types of foods they serve: hamburger chain restaurants (McDonald s, Burger King, Hardee s and Wendy s) and chicken chain restaurants (Al-Baik, Al-Tazaj, Kentucky Fried Chicken and Shaish Express). Table 1 lists the restaurants that were studied. Out of 10 hamburger chain restaurants, four were McDonald s, four were Burger King and one each was Hardee s and Wendy s. Of the 10 chicken chain restaurants, four were Al-Baik, three were Al- Tazaj, two were Kentucky Fried Chicken and one was Shaish Express. 24 ITE Journal / February 2008

2 All 20 restaurants were characterized by a large carry-out clientele, long hours of service and high turnover rates for eatin customers. These establishments did not provide table service. Customers order at a cash register and pay before they eat. All study sites were single-use, free-standing sites and were chosen so that they represented the geographical distribution of the city. DATA PROCESSING Data collected in this study can be grouped into two categories: office data and field data. The office data, which were collected from office mannagers, included the area of the facility and the number of employees at the facility. The field data included the number of parking stalls available at the facility, the availibility of drivethrough windows and traffic volume data. Table 1 summarizes the background information on the hamburger and chicken chain restuarants. The range of gross floor area at the hamburger chain restaurants was 258 to 725 square meters, with an average of 475 square meters. The corresponding figure for the chicken restaurants was 270 to 690 square meters, with an average of 465 square meters. The average number of employees at the hamburger chain restaurants was 21; the corresponding figure for the chicken restaurants was 33. The average number of parking stalls available at the hamburger restaurants was 25; the corresponding figure for the chicken restaurants was 24. Visits to the study sites also showed that nine out of the 10 hamburger restaurants had drive-through windows; only three out of the 10 chicken restaurants had drivethrough windows (see Table 1). Trip generation data were collected maually using data forms similar to the ITE trip generation data form. The traffic data were collected between 1998 and 2000 for a full week (five weekdays from Saturday to Wednesday and two weekends, Thursday and Friday) at each study site. The survey was selected so that it included the peak hour. It was observed that the peak hour took place during the evening hours. The usual data collection was from 4:00 p.m. to 7:00 p.m. Table 2 presents the trip data collected at both hamburger and chicken chain restaurant study sites. Name Table 1. Background information for hamburger and chicken chain restaurants. Location The trip data for the hamburger chain restaurants (see Table 2) show that the number of hourly trips during the study was between 58.1 and 117.0, with an average of 95.3 and a standard deviation of During the peak hour, the number of hourly trips was between 73.0 and 134.7, with an average of and a standard deviation of The traffic count data also showed that the approximate directional distribution of traffic was 54 percent entering and 46 percent exiting the establishments during the study as well as during the peak hour. On the other hand, the number of hourly trips at the chicken chain restaurants during the study was between and 159.4, with an average of and a standard deviation of 18.2 (see Table 2). During the peak hour, the number of hourly trips was between and Gross floor area (square meters) Number of employees Number of parking stalls Drivethrough window McDonald s Al-Hamra No McDonald s Palestine Yes McDonald s Tahlia Yes McDonald s Heraa Yes Burger King Jameeah Yes Burger King Tahlia Yes Burger King Sari Yes Burger King Heraa Yes Hardee s Tahlia Yes Wendy s Andalus Yes Average Al-Baik Mosadiah No Al-Baik Sabeen No Al-Baik Rowadah No Al-Baik Sea Port No Al-Tazaj Tahlia Yes Al-Tazaj Salama No Al-Tazaj Kandarah No Kentucky Fried Chicken Tahlia Yes Kentucky Fried Chicken Walii Al-Ahad Yes Shaish Express Sabeen No Average , with an average of and a standard deviation of The traffic count data also showed that the average directional distribution of the traffic was 54 percent entering and 46 percent exiting the establishments during the study as well as during the peak hour. Table 3 presents average peak-hour weekday (Saturday to Wednesday) and weekend (Thursday and Friday) vehicle trip ends at the study restaurants. Table 3 shows that the weekend trips were not much higher than the weekday trips except for the Hardee s and Al-Baik restaurants. In one instance, the peak-hour weekday trips were found to be higher than the corresponding weekend trips. Figure 1a shows the average peak-hour vehicle trip ends with respect to the parking spaces available for restaurants with and without a drive-in window. It is interesting ITE Journal / February

3 Name Table 2. Trip data at hamburger and chicken chain restaurants. Location Average number of trips during (vehicle trips/hour) Directional distribution (study ) Directional distribution (peak hour) Study Peak hour Percent entering Percent exiting Percent entering Percent exiting McDonald s Al-Hamra McDonald s Palestine McDonald s Tahlia McDonald s Heraa Average McDonald s Burger King Jameeah Burger King Tahlia Burger King Sari Burger King Heraa Average Burger King Hardee s Tahlia Wendy s Andalus All hamburger restaurants Average Range Standard deviation Al-Baik Mosadiah Al-Baik Sabeen Al-Baik Rowadah Al-Baik Sea Port Average Al-Baik Al-Tazaj Tahlia Al-Tazaj Salama Al-Tazaj Kandarah Average Al-Tazaj Kentucky Fried Chicken Tahlia Kentucky Fried Chicken Walii Al-Ahad Average Kentucky Fried Chicken Shaish Express Sabeen All chicken restaurants Average Range Standard deviation to note that the restaurants with a drive-in window had relatively more parking spaces compared to restaurants without a drive-in window. The restaurants without driveins generated more trips than restaurants with drive-ins. The data on number of vehicles parked during the study were used to calculate the turnover of parking spaces. The results indicated that the parking turnover of restaurants without drive-ins ( ) was higher than that of restaurants with drive-ins ( ). DATA ANALYSIS AND DEVELOPMENT OF TRIP RATES A trip generation rate is developed by measuring the traffic volume at an existing land use and relating it to some easily measurable characteristic of that land use. 6 The ITE Trip Generation manual reports trip rates at fast food restaurants based on the floor area of the establishment, the number of seats and the peak-hour traffic on the adjacent street. 7 In this study, however, it was decided to develop trip generation rates based on floor area and number of employees working at fast food restaurants. The hourly vehicle trip ends at the study sites were plotted against respective gross floor area and number of employees and presented in Figure 1b. There are no clear relationships between trips and gross floor area and between trips and number of employees. The regression of number of peak-hour trip ends on gross floor area showed that the R 2 value was only and the coefficient of the independent vari- 26 ITE Journal / February 2008

4 Table 3. Average weekday and weekend vehicle trip ends at fast food restaurants. Restaurant Average peak-hour vehicle trip ends Weekday Weekend McDonald s Burger King Hardee s Wendy s Al-Baik Al-Tazaj Kentucky Fried Chicken Shaish Express able was not significant (p value of 0.869). The regression of number of peak-hour trip ends on number of employees also showed that the R 2 value was only 0.07 and the coefficient of the independent variable was not significant (p value of 0.258). Statistical insignificance does not imply that floor area or number of employees has no effect on vehicle trips. Common sense suggests some correlation between trip ends and floor area as well as between trip ends and number of employees. The low R 2 values and statistical insignificance imply that the floor area or number of employees does not reliably predict vehicle trip ends. It is worth noting that an in-depth analysis and critical review of the trip rates reported in Trip Generation also suggested that floor area cannot reliably predict vehicle trip ends. 8 One reason could be that other factors, besides floor area or number of employees, can explain most of the variations in vehicle trips. The trip rates developed in this study based on gross floor area and number of employees are presented in Table 4. Table 4 shows that the hourly vehicle trip rates at the hamburger chain restaurants during the study and during the peak hour were within a range of 9.3 to 42.1 and 11.6 to 52.2 per 100 square meters of floor area, respectively. While the average hourly trip rate during the study was 19.5 per 100 square meters, 23.1 trips per 100 square meters were observed during the peak hour. Peak Hour Vehicle Trip Ends Peak Hour Vehicle Trip Ends Peak Hour Vehicle Trip Ends Figure 1a. Data plots of peak-hour vehicle trip ends versus available parking spaces at restaurants with and without drive-ins Number of Parking Spaces With Drive-In Gross Floor Area, square meters hamburger chicken Number of Employees hamburger Without Drive-In chicken Figure 1b. Data plots of peak-hour vehicle trip ends versus gross floor area and number of employees. ITE Journal / February

5 Table 4. Vehicle trip rates at hamburger and chicken chain restaurants. Name The results also showed that the vehicle trip ends per employee during the study and during the peak hour were within a range of 2.8 to 8.5 and 3.4 to 10.0, respectively. The average hourly trip rates for hamburger chain restaurants during the study and during the peak hour were 5.0 and 5.9 trips per employee, respectively. The hourly vehicle trip rates at the chicken chain restaurants (see Table 4) during the study and during the peak hour were within a range of 15.6 to 47.6 and 18.1 to 53.3 per 100 square Location Hourly vehicle trip ends per 100 square meters Study Peak Hourly vehicle trip ends per employee Study Peak McDonald s Al-Hamra McDonald s Palestine McDonald s Tahlia McDonald s Heraa Average McDonald s Burger King Jameeah Burger King Tahlia Burger King Sari Burger King Heraa Average Burger King Hardee s Tahlia Wendy s Andalus Average Range Standard deviation Al-Baik Mosadiah Al-Baik Sabeen Al-Baik Rowadah Al-Baik Sea Port Average Al-Baik Al-Tazaj Tahlia Al-Tazaj Salama Al-Tazaj Kandarah Average Al-Tazaj Kentucky Fried Chicken Tahlia Kentucky Fried Chicken Walii Al-Ahad Average Kentucky Fried Chicken Shaish Express Sabeen Average Range Standard deviation meters of the floor area, respectively. While the average hourly trip rate during the study was 30.1 per 100 square meters, 34.0 trips per 100 square meters were observed during the peak hour. The results also showed that the vehicle trip ends per employee during the study and during the peak hour were within a range of 1.9 to 6.3 and 2.2 to 7.0, respectively. The average hourly trip rates for chicken chain restaurants during the study and during the peak hour were 4.3 and 4.9 trips per employee, respectively. Further analysis of the trip rates presented in Table 4 revealed that the average trip rate per 100 square meters at the chicken chain restaurants (33.9) was higher than that at the hamburger restaurants (23.1). Similarly, average trip rate per 100 square meters at the eight national chain restaurants (35.2) was higher than that at the 12 international chain restaurants (24.1). When the trip rates were compared based on the availability of a drive-through window, it was found that the average trip rate per 100 square meters at the 12 restaurants with a drive-through window (24.2) was lower than that at the eight restaurants without a drive-through window (35.1). It is worth noting that the rates reported in Trip Generation also showed that the fast food restaurants without a drive-through generated more trips when compared with restaurants with a drive-through window. Statistical analyses were performed to see if there were any significant differences between the average trip rates based on type of food served (hamburger and chicken), availability of drive-through windows and origin (national and international chain). The results indicated at a 95-percent confidence level that the average trip rates per 100 square meters during the peak hour were not significantly different when the study sites were compared based on type of food served (t = -2.03, p = 0.058, DF = 17), availability of drive-through windows (t = -1.93, p = 0.075, DF = 13) and origin (t = 1.98, p = 0.070, DF = 13). When the trip rates per employee were considered, the results indicated at a 95- percent confidence level that the peakhour trip rates also were not significantly different when compared based on type of food served (t = 1.21, p = 0.24, DF = 17), availability of drive through windows (t = 0.14, p = 0.89, DF = 17) and origin (t = -0.80, p = 0.44, DF = 15). Therefore, average trip rates were calculated based on floor area and number of employees considering all 20 study sites irrespective of the types of food they served, availability of drive-through windows and origin. Table 5 presents the average trip rates during the peak hour for the fast food restaurants based on gross floor area as well as on number of employees working at the restaurants. The average trip rates for such fast food restaurants reported in Trip Generation also are shown in Table ITE Journal / February 2008

6 A cursory look at the values reveals that the ITE trip generation rates are much higher than those developed in this study. The Municipality of Riyadh recently published a trip generation rate manual that uses data collected in The average peakhour trip rate for the restaurants reported in this manual is 18 per 100 square meters with a range of trips per 100 square meters. However, it is worth noting that the Riyadh value is a combined average rate for quality restaurants, sit-down restaurants and fast food restaurants. No exclusive trip rates for fast food restaurants are reported. CONCLUSIONS Trip generation rates at fast food restaurants in Saudi Arabia were developed in this study. Twenty fast food restaurants were selected within the city limits of Jeddah. Of these 20 restaurants, 10 were hamburger chain restaurants and 10 were chicken chain retaurants; 12 had a drivethrough window and eight did not have a drive-through window. Of these 20 study restaurants, 12 were members of international chains and the other eight were members of national chains. Trip generation data were collected at the study sites for a full week including weekends. The study s were selected so that they contained the peak hour. The peak hours occurred from 4:00 p.m. to 7:00 p.m. in the evening for all study sites. The data collected at the study sites were used to determine the trip generation rates based on the gross floor area and number of employees of fast food restaurants. The results showed that, on average, there were 28.6 vehicle trip ends per 100 square meters of gross floor area and 5.4 vehicle trip ends per employee during the peak hour. Statistical analyses revealed that the average vehicle trip rates at the fast food restaurants were not significantly different at a 95-percent confidence level when compared with respect to the type of food served, availability of a drive-through window and origin (national or international chain). The average vehicle trip rates devloped in this study also were compared with those reported in Trip Generation. The comparison showed that the rates mentioned in Trip Generation were much higher than those found in this study. This can be attributed to the fact that Peak-hour vehicle trip ends per 100 square meters Peak-hour vehicle trip ends per employee Table 5. Average vehicle trip ends at fast food restaurants. the lifestyle of an average Saudi citizen is much different than that of an average person living in the United States. Moreover, fast food restaurants are a relatively new concept in Saudi Arabia, even though these types of restaurants are experiencing rapid growth. It is expected that the trip generation rates developed in this study will help transportation planners and traffic engineers better estimate anticipated traffic volumes attracted to fast food restaurants. n References 1. Bureau of Statistics: Census Data Ministry of Planning, Kingdom of Saudi Arabia. 2. Lalani, N. and R.P. Jurasin (eds). Transportation Impact Studies. Washington, DC, USA: Institute of Transportation Engineers (ITE), Trip Generation, 7th Edition, Volume 3. Washington, DC: ITE, Trip Generation Handbook. Washington, DC: ITE, Ibid. 6. Arnold Jr., E.D. Trip Generation At Special Sites. Final Report, No. VHTRC 84-R23: Virginia Highway and Transportation Research Council, Virginia, ITE 2003, note 3 above. 8. Shoup, D.C. Truth in Transportation Planning. Journal of Transportation and Statistics, Vol. 6, No. 1 (2003). Accessible via publications/journal_of_transportation_and_ statistics/volume_06_number_01/html/paper_01; and Shoup, D.C. Truth in Transportation Planning Rejoinder. Journal of Transportation and Parameters Study results ITE values a Average b, c Range b, c Standard deviation b, c Sample size b, 5 c Average 5.4 d Range Standard deviation 1.9 Sample size 20 Notes: a Source: Trip Generation, 7th Edition, Volume 3. Washington, DC, USA: Institute of Transportation Engineers, b Fast food restaurant with drive-through window, weekday, p.m. peak hour of generator. c Fast food restaurant without drive-through window, weekday, p.m. peak hour of generator. d Not reported in ITE Trip Generation. Statistics, Vol. 6, No. 1 (2003). Accessible via paper_01/rejoinder_01_01.html. 9. Riyadh Municipality. Trip Generation Rate Manual for Urban Development in Riyadh City. 1st Edition, Volume 2, Riyadh, Kingdom of Saudi Arabia, Abdulrahem H.M. Al-Zahrani, Ph.D., is a professor of civil engineering at King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia. He has more than 25 years of experience teaching traffic engineering, traffic management, transportation planning and hajj transportation issues. He earned his Ph.D. in 1983 from Washington State University, Pullman. He is a member of ITE. Tanweer Hasan, Ph.D., is an associate professor of civil engineering at King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia. He has 15 years of experience teaching traffic engineering, traffic management and transportation planning. He earned his Ph.D. in 1998 from Kansas State University, Manhattan. ITE Journal / February