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1 0 0 Using the WTP Method for an Analysis of Parking Fees - Focusing on Pusan National University in Korea - Gyoungjun Ha Dept. of Urban Eng. Pusan National University, Busandaehak-ro beon-gil, Geumjeong-gu, Busan, Tel: hkj@hanmail.net Hyungjun Park Dept. of Urban Eng. Pusan National University, Busandaehak-ro beon-gil, Geumjeong-gu, Busan, Tel: wingplan@pusan.ac.kr Juchul Jung, Corresponding Author Dept. of Urban Eng. Pusan National University, Busandaehak-ro beon-gil, Geumjeong-gu, Busan, Tel: 0--; Fax: 0--; jcjung@pusan.ac.kr Word count: words text + tables/figures x 0 words (each) =, words Submission Date July, 0

2 Ha, Park, Jung ABSTRACT This study calculated the optimal parking fee through the amount of WTP (willingness to pay) by constituent individuals, which can induce a reduction effect on traffic volume according to the higher adjustment of parking fees on campus. As a result of the estimation of the amount of willingness to pay, the optimal parking fee was estimated to be approximately USD to 0 USD per month on average. Using the analysis models (double bounded dichotomous choice model and open-ended model), the explanatory variables had a significant effect on the probability of the willingness to pay in preference for both the parking policy to reduce traffic volume on campus according to the occupation, sex, and commuting distance, and an increase in the regular parking fee. The results revealed a higher probability of the willingness to pay by professors and part time lecturers with a higher income level than that by administration workers and graduate students. Males had a higher willingness to pay than females, and that there was a higher willingness to pay in those with a longer commuting distance. The probability of the willingness to pay increased with increasing preference for the reduction policy of traffic volume and the higher adjustment of regular parking fee. Keywords: Parking Fee, Vehicle Traffic, Willingness to Pay, University Campus

3 Ha, Park, Jung INTRODUCTION While modern society has promoted policies focused on vehicles, such as road construction and its expansion, many serious social issues have been raised, including traffic congestion, greenhouse gas emission, etc. Advanced countries have started to bring a Transport Demand Management (TDM) plan for sustainable transport, promoted the use of public transportation, and implemented a policy to restrict the use of private cars. On the other hand, despite such situations, modern cities lack appropriate control measures against the increasing number of vehicles. Therefore, as the traffic congestion in major roads of cities reaches a serious level, it is necessary for an effective vehicle demand management plan for this cause (). The methods to manage the demand of vehicles are diverse, but pricing control can be used as an effective demand management plan (). The policies of pricing control to manage the demand of vehicles are generally vehicle tax, fuel tax, toll fee, congestion tax, parking fee, and public transportation fee. Among these, the policy of parking fees has been found to be most effective (). Therefore, to reduce traffic volume, it is essential to have a management plan for the demand of vehicles through the policy of parking fees, concentrating on the downtown areas in respect to the characteristics of highly densified and complex modern cities. In a city space of high density, especially in the downtown areas, spatial competition by users has occurred due to the activities of dwellings and commerce within its limited space (). In particular, it is difficult to select the priority of zone division and space use to utilize the public spaces within the downtown areas for the locations of buildings, spaces for social activities, spaces for greenbelts, and spaces for traffic and parking (). Among public institutions, universities have the largest areas, number of users, and traffic volume, which require preemptive action to reduce energy consumption and traffic volume as its energy use reaches.% of the total energy consumption of Korean business sites (). Generally, in Korea, national universities have long history and tend to be located in downtown area. Therefore, as presented previously, it is necessary to reduce traffic volume on university campuses by applying an effective parking fee policy to university campuses. Despite this, as the decision of parking fees on campus is currently determined by the competent authority, it is difficult to expect empathy and participation by the constituent individuals of a university to the rise of parking fees. Therefore, it is essential to have a plan that can be applied through the decision by the constituent individuals of universities and to evaluate a methodology to estimate this. This study calculated the optimal parking fee through the amount of WTP (willingness to pay) by constituent individuals, which can induce a reduction effect on traffic volume according to the higher adjustment of parking fees on campus. Through this, the policy implications are presented to reduce traffic volume on campus. RESEARCH THEORY AND PREVIOUS STUDIES Necessity of Traffic Demand Management A supply policy of large scale traffic facilities to react to the continuously increasing traffic demand requires vast traffic investment finance, which limits its applicability. Therefore, many attempts have been made to resolve this problem without the vast investment of finance. This is a current trend that largely, two representative plans, TSM (Transportation System Management) and TDM (Transportation Demand Management) have been promoted (). Among these, TSM means a plan to increase the volume of supply facilities through the effective operation of existing

4 Ha, Park, Jung traffic facilities, and TDM adjusts the traffic pattern of drivers to readjust the traffic demand fundamentally and improve the traffic congestion. The traffic demand management plan has a goal to create the economics conforming to the construction effect of traffic facilities by inducing a change in passing type of humans. In this respect, the traffic demand management is a plan that does not supply a new traffic facility but controls the traffic demand itself to react to the traffic congestion effectively. According to Broaddu (00) (), pricing control was a suggested plan for effective demand management. The pricing control according to its implementation shows a clear and visual reduction effect on the use vehicles different from other systems and has the great merit of a system settlement effect. On the other hand, pricing control faces the issue of fairness because it resolves the choice of vehicle use through the financial issue. In particular, local or central government is unwilling to implement toll fee control or congestion tax because it may raise the opposition of vehicle users. Therefore, it is important to determine the most effective system to use among the pricing controls. Albert (00) () analyzed the most effective pricing control among traffic demand managements. According to Albert (00) (), who evaluated three scenarios, congestion tax, toll fee, and parking fee control, reported that % of respondents would use other traffic means if the parking fee was increased. On the other hand, it was found that they drove to avoiding those sections where the congestion tax and toll fee were imposed. In contrast to a congestion tax and toll fee, the parking fee control is also a part that local government and public facilities and private institutions can apply themselves so the system is implemented easily. Broaddu (00) () examined the effect by the pricing control and reported that parking fee control had the greatest influence. Effect of Vehicle Reduction through Parking Fee In many developed countries, the supply of parking lots has been recognized as a social service. Therefore, these countries have provided parking lots for free to visitors or workers who visit the stores. Accordingly, an individual who uses their own vehicle never considers the issue of a parking lot when they choose a traffic means. Hulme-Moir (0) () insisted that in respect of the environment, the minimum area for a parking lot should be supplied at an urban development and that the supply of parking lots free of charge for vehicles in downtowns causes traffic congestion and air pollution. According to Donald Shoup (00) (), % of traffic means in the U.S were the use of individual vehicles, and % parking lot were being used free of charge. He insisted that a higher parking fee should be paid to stop this. If the parking fee is increased, the probability of choosing to use an individual private car decreases. If this is examined in view of economics, Small () (), who examined how the consumption choice changed, reported that an increase in the parking fee could result in a reduced use of A's vehicle when individual A uses his/her car mainly for commuting if the pricing control system had been implemented for the expanded use of public transportation. Therefore, can the economic approach be applied equivalently to a real situation? From the survey result of parking probability targeting commuters according to the parking fee, parking lot and distance of destination, Hulme-Moir (0) () reported an increased probability in converting from a car to public transportation when the parking fee was increased from USD to USD. From the survey result of the choice of transportation targeting commuting company workers when the parking fee had been increased, Litman (00) () reported that in the case of Canada, the percentage of those who chose to use a private car decreased by 0% and that the use of public transportation increased by %; in the case of LA, a type involving the use of a

5 Ha, Park, Jung 0 0 carpool was increased by %. The following presents a summary of the analysis results for the above mentioned studies. The parking policy in modern society is facing a turning point of a new paradigm. Vehicles have flowed rapidly into downtown through the procurement of parking spaces with free parking, which has caused considerable traffic congestion and air pollution. In view of economics, it has been predicted that an increase in parking fee will reduce the use of cars while the use of public transportation increases. From the result of the analysis in a real situation, an increase in parking fee affects the choice of transportation. Appropriation of Parking Fee in Universities Among public institutions, universities are excellent for studying a social change and a practical goal. Therefore, previous studies have been carried out to develop eco-friendly universities. For a practical method to accomplish them, it is essential to restraint the use of vehicles. To produce such an eco-friendly environment, many universities including the University of California in the U.S have appropriated the parking fees to reduce the use of vehicles (, ). TABLE National Universities & Local Regional Parking Fees in Korea (Unit: $) National Universities Regions Parking Fee on Campus(Monthly) Public Parking Fee per Land Level (Monthly) Downtown area Seoul City of Seoul 0/0//0 Yes Chungnam City of Daejeon // Yes Pusan City of Busan 0/0/0/0 Yes Chungbuk City of Cheongju 0//0 Yes Kangwon City of Chuncheon Yes Jeonbuk City of Jeonju //0 Yes Gyeongbuk City of Daegu 0/0/0 Yes Gyeongsang City of Jinju 0/ Yes Jeju City of Jeju 0/0 No Jeonnam City of Gwangju /0/ Yes Korean national universities, have comparatively low parking fees (Table ). From the survey result, it has been reported that Korean national universities need to establish an eco-friendly campus environment to collect cheaper parking fees than a nearby public parking lot. Among the Korean national universities, from the analysis result of parking fees in universities that have become the members of the council of provincial Korean national universities, regular parking fees of these universities range from to USD per month, but public parking lots in urban areas where these universities belong have appropriated from at least (City of Jeonju) to a maximum of 0 USD (City of Cheongju) per month (Table). Moreover, of universities are located at downtown area. With a similar parking fee, the users of regular parking in provincial national universities tend to use parking spaces with cheaper prices, and it has been criticized for its instigation of traffic volume (). Universities that wish to develop an eco-friendly campus should adjust the parking fee to reduce the users of vehicles (). To adjust the parking fee, universities should compose a traffic

6 Ha, Park, Jung management committee (). A method through such a committee cannot gather the opinions of constituent individuals in the university so that it is difficult to expect their empathy and participation at the unilateral rise of transportation fee to reduce traffic volume. As the vehicle demand management changes the type of users, it is important to determine the intention of users (). Therefore, for vehicle demand management, it is more desirable for Korean national universities to estimate the appropriate parking fees according to the opinions of users. Appropriation of Parking Fee in Universities Studies aimed at estimating the optimal parking fee have been implemented mainly in the field of policy study rather than academic thesis. This is because the issue about the parking fee is the field of policy study that can be reflected immediately in the policy as a major issue by the relevant institution who imposes the parking fee. Previous studies attempted to estimate the optimal parking fee with such characteristics. Washbrook et al. (00) () computed the optimal parking fee through a survey presenting five examples of parking fees to estimate the parking cost, targeting commuters in Vancouver, British Colombia. Hess (00) () also calculated the optimal parking fee through an experiment of real parking fee adjustment of Oakland, Oregon. The computation of the optimal parking fee, as reported by Hess (00) (), is comparatively precise through a comparison after increasing the real parking fee, but there is a limitation in calculating the parking fee through real experiments as the parking fee is money with a higher price flexibility by the user of the vehicle (). According to such limitations, the computation study for the parking fee, consists mainly of surveys that have presented examples of parking fees targeting the users of vehicles. As this induces the respondents to judge in a type of presenting a certain amount of money, there is the demerit of a starting point bias (). As a recent plan to supplement the demerits of a survey presenting its limitation and examples through experiments to estimate the optimal parking fee, a computation study reported the optimal parking fee according to the analysis on the amount of WTP by respondents. Newmark et al. (00) () presented the analysis result of the amount of WTP for the optimal parking fee in suburban shopping malls selecting Prague as an example area. Anastasiadou et al. (00) () analyzed the amount of WTP to compute the optimal parking fee at the Rethymno tour area, Greece, and its analysis result revealed. Euro per hour to be the optimal parking fee. As a summary of previous studies on an estimation of the optimal parking fee, an experimental method to compare the real parking fees after a higher adjustment is the optimal one for a study of the computation of parking fee but other study methods have been suggested due to the limitation of its actual applications. Therefore, a survey was implemented in general to present examples of parking fees targeting the users of vehicles, but there are demerits, such as a starting point bias. Regarding the method to overcome such limitations, an analysis study was presented for the optimal parking fee through an analysis of the amount of WTP. RESEARCH METHOD Analysis on the Amount of WTP This study examined the amount of WTP to compute the optimal parking fee of vehicle users according to the conditional value measurement method. The conditional value measurement is a value estimation method that uses a devised survey to deduce the values of public wealth or service (). This is a part of the analysis on the amount of WTP for which people have a WTP according to the amount of wealth or service or change in quality, or a part of such a conditional

7 Ha, Park, Jung value measurement method (). Previous analyses on the amount of WTP were mainly estimations of the environmental values by expressing the use values of users as the amount of WTP according to the imaginary scenarios as for the utility of environmental wealth (0). Recently, however, some studies suggested that the range of the amount of WTP is extended to use the analysis on the amount of WTP to estimate the price of corresponding wealth for the purpose of changing the use pattern of wealth that is currently being used by an individual (). To estimate the prices of cigarettes to raise their prices, Go et al. (0) () analyzed the amount of WTP for cigarettes, which correspond to the individual intention for nonsmoking. With such method, this study estimated the amount of WTP to analyze the parking fees that are generated by the use of vehicles by individuals for the purpose of changing the individual vehicles to other transportation means. The analysis on the amount of WTP to compute the parking fees was introduced recently in academies so that it is predicted to be reasonable under the condition of methodology (). Estimation Model of WTP This study has used the utility difference model of Hanemann () () to estimate the Hicks' compensating surplus of vehicle users for parking fees. The respondents to the payment of parking fees will have the maximum WTP to maintain the parking out of the present parking fees. A theoretical basis of the DC (Dichotomous Choice) type CVM (Contingent Valuation Method) model to induce the Hicks' compensation or an estimation of the equivalent surplus is based on an analysis of utility theory (). The utility of respondents to the payment of parking fees can be expressed as an indirect utility function that depends on the income of the respondents (Y) and the social economic characteristic (S). On the other hand, in such a utility function, because a portion exists that cannot be observed for selection or rejection for the level change by the respondent, the utility function will have the following stochastic components, as expressed in equation () (). U(i, Y; S) = V(i, Y; S) + ε i i = or 0 () i = ; when the utility of the target is changed i = 0; when there is no change in utility ε i = Probable error F θ [ΔV] = +exp ([ α+β bid+γs)] α = constant term β = coefficient of presented amount(bid) γ = coefficients of independent variables excluding a variable of presented amount WTP mean = F θ [ΔV]dB = ln [ + exp(α)] () 0 β Here, i = when an individual has a willingness to pay, and otherwise i =0. Respondent shall say "yes" or "no" to the question about the given amount of WTP. If an individual selects "yes", they shall pay the presented payment (B) so that the utility about the change in transportation means will be changed or be same. The DC technique can utilize the linear ()

8 Ha, Park, Jung stochastic model, logit model and probit model as the regression equation for dependent variables (). This study has applied the log logistic function. Therefore, the following equation (), which is a log-logistic function, can be expressed as the linear stochastic model. Finally, the mean WTP amount can be calculated using equation (), with which amount the area of cumulative probability can be estimated by setting the amount B suggested randomly from 0 to infinity (0). TABLE Estimation Model of WTP Classification Model [] Model [] Estimated Model (Double-Bounded Dichotomous Choice CVM) (Open-Ended CVM) Moreover, this study added the open-ended question along with the double bounded dichotomous choice for an estimated model of the WTP (Table ). The open-ended question is a model to answer directly for the amount of WTP different from the closed model that projects the amount of WTP indirectly. This has the merit to respect most the intention of the respondents to the survey, but it has a demerit of adding difficulty to the respondent in evaluating the convenience as a currency unit so that recently its analysis method has not been used (). On the other hand, there is a high likelihood of supplementing the demerit of open-ended question as the question is made to the respondent for its maximum amount of WTP for the parking fee, who is currently paying the parking fee and recognizing the currency unit for current wealth. Therefore, this study analyzes a double bounded dichotomous choice model recommended by the NOAA The panel report along with an open-ended model that respects most the intention of the survey respondent to supplement the limitation of methodological difference for the amount of WTP. Selection of Study Area and Design of Questionnaires This study selected Busan Campus of Pusan National University which is one of the largest Korean national university for an example area. Busan Campus is located at downtown area in Busan city which is one of the metropolitan cities in Korea (Figure). In 0, there were, employees and 0, students with an area of approximately. million m (Table ). In addition, in 0, the daily average number of traffic volume was about thousand. While the number of regular registered vehicles was,, the number of parking spaces was,00 so that there was a lack of supply compared to the demand, which resulted in a parking problem (Table ). Therefore, it is urgent for Busan Campus to FIGURE. Location of Busan City increase the parking fee for vehicle demand management.

9 Ha, Park, Jung TABLE Status of Study Area No. of Employees No. of Students Area(m ), 0, about,00,000 Daily Average of Traffic Volume Regular Registered Vehicles Parking Spaces about thousands,,00 Source: Yearly Statistics of Pusan National University(0)() and Internal Data by General Affairs, Pusan National University (as of the year 0) Four hundred samples were extracted from employees and graduate students of Pusan National University for the survey target group. The survey involved questionnaires for the possible maximum payment for a monthly parking fee on campus. For the question method to ask the amount of WTP, a double bounded dichotomous choice was selected, which is recommended by the NOAA Panel report along with an open-ended question for questionnaires. In the case of the double bounded dichotomous choice, an initial amount was presented randomly. If the amount is less than or equal to the amount of WTP that a respondent is thinking, Willingness to Pay would be selected, and on the other hand, if the amount is larger than the amount of WTP that a respondent is thinking, Unwilling to Pay would be selected. The double bounded dichotomous choice repeats such selection of the WTP twice (0). For example, if there is no willingness to pay for the initially presented amount X won, the WTP will be answered for the lower amount than X won in the second question. On the other hand, if there is a willingness to pay for X won, the WTP will be answered for the amount higher than X in the second question. Figure presents the flow of double bounded dichotomous choice. 0 FIGURE. Flow of Double Bounded Dichotomous Choice This survey has selected samples of 0 people to calculate the initially presented amount and implemented a pre survey before the survey. Through the open-ended question method, high frequency of 0 USD, 0 USD, 0 USD, 0 USD, and 00 USD have been selected for the initial presented amounts. ANALYSIS ON AMOUNT OF WTP FOR PARKING FEE Variable Setting & Analysis on Basic Statistics

10 Ha, Park, Jung The survey has selected the social economic variables, such as the occupation, sex, present regular parking, commuting distance of a respondent, the degree of awareness of parking problem by the respondent, and the degree of preference to the parking policy as the explanatory variables that were expected to influence the amount of WTP for parking fee. Among the social economic variables, the occupation has been classified into professor, administration worker, part time lecturer, and graduate student. In the classification of occupation, as a difference in income exists according to occupation, there is a higher likelihood that the occupation may act as an important explanatory variable for the amount of WTP. The presence of regular parking may also act as a noteworthy variable that influences the amount of WTP. A significant difference can occur in the amount of WTP according to the commuting distance. TABLE. Variables Setting and Basic Statistics Characteristics Levels Percentage Coding Professors Occupations Part Time Lecturers Administrative Workers Graduate Students Sex Female 0 Male Regular Parking Non parking 0 Parking Commuting Distance Commuting Distance(km). (Average) - Awareness of On Campus Parking Problem [Policy ] Policy to Reduce Traffic Volume [Policy ] Higher Adjustment to Regular Parking Fee Never serious Not serious Moderate A little serious Very serious Never agree Not agree Moderate A little agree Strongly agree Never agree Not agree Moderate A little agree Strongly agree

11 Ha, Park, Jung 0 0 TABLE. Analysis Result of the Amount of WTP Initially Presented Amount Frequency per Answer [Y-Y] [Y-N] [N-Y] [N-N] $0 0 $0 0 $0 0 $0 0 0 $ Total Total 00 The degree of the problem awareness by the respondent for parking and the preference to the parking policy might influence the WTP for a parking fee, and survey questions have been composed for this expectation. The degree of problem awareness by the respondent for parking was inquired for the seriousness of traffic and parking problem on campus. The preference of a parking policy was examined to reduce traffic volume and increase the regular parking fee. Table lists the results of the analysis on the basic statistics according to variable setting and variables. The initially presented amounts of double bounded dichotomous choice for the analysis of the amount of WTP was set to be $US0, $US0, $US0, $US0, and $US00. Samples of 0 people for each presented amount were acquired. Table shows the distribution of respondents for each initially presented amount. Analysis Result of Models According to the case of Busan Campus of Pusan National University, the analysis result of the models for the maximum amount of WTP for the parking fee of regular vehicles shows that there is little difference in the effectiveness of the explanatory variable for each model. From the analysis result of a model [], i.e. the double bounded dichotomous choice, the awareness of occupation, the reduction policy of traffic volume, and the higher adjustment to the regular parking fee were determined to be effective variables. The variables for occupation were composed of professor, part time lecturer, administration worker, and graduate student. According to each stage, the probability of WTP becomes lower. This suggests that the difference in income for each occupation may influence the probability of the WTP. The probability of the WTP increased with increasing preference for the reduction policy for traffic volume and the increasing adjustment to the regular parking fee. As the significance of probability was higher for the awareness of policy and WTP by the respondent, it shows that the awareness of the respondent has been reflected systematically to this survey. For the open-ended model [], the effective variables of sex and commuting distance were additionally deduced in addition to the awareness variables of occupation, the reduction policy of traffic volume, and the higher adjustment to the regular parking fee model []. Among the social characteristics of the respondents for the amount of WTP, in addition to occupation, the amount of WTP by males was higher than that of females. The amount of WTP increased with increasing commuting distance. This can be interpreted as the convenience of using private cars for the commuting distance influencing the amount of WTP. Table presents the values of the analysis result for each model.

12 Ha, Park, Jung TABLE Model Analysis Result for the Amount of WTP Variable Model [] Model [] Estimated Coefficient Std. Deviation Estimated Coefficient Std. Deviation Con_.0..***.0 Occupations -.**. -.***.0 Sex...***. Regular Parking Commuting Distance *** 0. Awareness.... Policy.0**..*. Policy.0**..*.0 No. of Samples R - 0. F-Test.*** Log Likelihood -. - Wald Statistics.*** - WTP USD USD note: * % significant level, ** % significant level,*** % significant level 0 Analysis of the Amount of WTP Through equation (), the amount of WTP was calculated for the model []. The maximum amount of WTP was USD per month as a parking fee at Busan Campus, which was computed using the model of double bounded dichotomous choice. The maximum amount of WTP computed with the open-ended model was USD per month. The amount difference of WTP between the double bounded dichotomous choice and open-ended was USD, which suggests that the open-ended model has a higher likelihood for an excessive estimation of the amount of WTP than the closed model (double bounded dichotomous choice), as pointed out in the NOAA Panel report (). Table shows the values of analysis results for the amount of WTP in model [] and model []. A comparison of the estimated amount of WTP with the monthly parking fee in a public parking lot in Busan city showed that the estimated amount for parking fee by this study corresponds to the public parking fee of land levels and of Busan city, as shown in the Table. The land levels of public parking lots in Busan city are classified into levels based on traffic volume and the degree of congestion. Land level is applied to the central commercial area with a large traffic volume, and land levels ~ are applied to residential areas differently according to traffic volume. Therefore, comparing with the amount of WTP by the constituent individuals of universities, it is estimated that traffic volume could be controlled if the parking fee of universities would be adjusted higher to the level of public parking fee of residential areas (land levels ~).

13 Ha, Park, Jung CONCLUSION AND PROPOSAL As a plan to reduce traffic volume, this study calculated the optimal parking fee through the amount of WTP by the constituent individuals, which can have a reduction effect on traffic volume by the higher adjustment to the parking fee in universities. From the estimated result of the amount of WTP, optimal parking fees of approximately to 0 USD have been estimated for an average monthly parking fee. According to the analysis models (double bounded dichotomous choice & open-ended), the significant explanatory variables for the probability of WTP were found to be occupation, sex, commuting distance, the preference for the parking policy to reduce traffic volume on campus, and the preference for an increase in the regular parking fee. The probability of the WTP by professors and part time lecturers with a higher income level was higher than that by administration workers and graduate students. Males have a higher WTP than females, and the WTP increases with increasing commuting distance. If the degree of the response is higher to towards a policy of reducing traffic volume and increasing the regular parking fee, the probability of WTP becomes higher. The maximum amount of WTP for the parking fee (about USD to 0 USD) appropriate in this study was to times higher than the monthly parking fee of Pusan National University ( USD). To utilize the present parking fee of Pusan National University for controlling the volume of vehicles used on campus, it appears that it is necessary to have a policy to increase the parking fee. According to the comparison and analysis with public parking fees in Busan city, it is essential to adjust the public parking fees in local government to control traffic volume on campus. This study selected Busan Campus of Pusan National University as an example area to estimate the parking fee of universities. Therefore, there is a concern that generalization for entire universities may occur. These results estimating the parking fees of all universities may be slightly exaggerated. Therefore, future research is needed to be supplemented with a study of the computation of parking fees through examples of public institutions under a range of conditions. REFERENCES. Goldman, T. and Gorham, R. Sustainable urban transport: Four innovative directions, Technology in Society, Vol., No., 00, pp. -.. Broaddu, Andrea. Transportation Demand Management Training Document, Gtz, 00. Golias, J., Yannis, G. and Harvatis, M. Off-Street Paring Choice Sensitivity, Transportation Planning and Technology, Vol., No., 00, pp... Korea Energy Agency, Energy Statistics, Korea Energy Agency, Seoul, 00. Albert, Gila. Congestion tolls and parking fees: A comparison of the potential effect on travel behavior, Transport Policy, Vol., No., 00, pp Hulme-Moir, Angus. Making Way for the car: Minimum Parking Requirements and Porirua City Centre, Victoria University of Wellington, 0. Shoup, Donald. The High Cost of Free Parking, American Planning Association Press, Chicago, 00.. Small, K. A. Using the revenues from congestion pricing, Transportation, Vol., No.,, pp. -.. Litman, T. Transportation elasticities. How Prices and Other Factors Affect Travel Behavior, Victoria Transport Policy Institute. 00.

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