1. 2009/5/15 Ayu Miyakawa Supervisor: Satoshi FUJII SOCIAL BENEFIT OF PERSUASIVE COMMUNICATION THROUGTH MASS-MEDIA FOR MOBILITY MANAGEMENT

2.  Persuasive MM in Japan  Since 1999, persuasive MM experiment have been implemented.  TFPs (persuasive communication technique) for inhabitant reduced car use by about 19% and increased the transportation use by about 32% in average (by the meta analysis in 2006).  Japanese government is now strongly promoting MM.  Problems  However, some transport policy makers still skeptical about MM s effectiveness.  It is necessary to empirically show the social benefit of the measure and to develop the system to assess MM s effectiveness. 2 This study is to propose an assessment method of social benefit, and apply it for evaluation of MM of persuasive communication through mass-media. PURPOSE

3.  Providing persuasive message to refrain from car dependence through newspaper.  “Living-Kyoto” (weekly newspaper)  circulated to 510,000 households by women called “Living-Lady”  supplies several information about our daily life to women  Area where Living-Kyoto was distributed = Kyoto  Population: about 1,900,000 （ 72% of Kyoto prefecture ）  Modal Share: Car use 32.4%, Railway use 15.6% Bus use 4.6% Target Area 3 Kyoto Prefecture MM project using Mass Media

4. 4 Living-Kyoto on March 24, 2007  To suggest using a car in “smart way” (= refraining from too much use of car)  Explanation of negative impacts of car use on global environment and on people’s health with graphs  Introduction of the project and the results of preliminary TFP (target at Living-Lady to get the outcome inserted into this article)  Message to recruit participant to TFP Leaflet with a simple postal card for application Persuasive Message in the Newspaper

5. 1 page of newspaper Living-Kyoto was provided 2007. 3 2007.6 ・ Distributed goods: greeting letter, questionnaire, little gift ・ Question: travel frequency, psychological factor how they remember the newspaper article ・ Sample: distributed to randomly sampled 5,000 households, and 1,698 returned (34.0%) 5 Questionnaire survey Evaluate how much their behavior changed by reading the newspaper article. Surveys for Evaluation of this project

6.  Classification by the Degree of Remembrance of the Newspaper Article ※ Degree of remembrance: "Do you remember the article about the project to use car in “smart way" on March 24, 2007 ? " 6 Degree of remembrance number % Not read43329.2 Not remember at all29019.5 Not remember the content 54836.9 Remember vaguely1469.8 Remember well443.0 No answer241.6 Total1,485100.0 “Remember well” and “Remember vaguely” might have changed their behavior by reading the newspaper article. 29.1% 19.5% 36.9% 9.8% 3.0% 1.6% Not read Not remember at all Not remember the content Remember vaguely Remember well No answer RESULTS(TARGET POPULATION)

7. 7  Expand to Whole Target Area (510,000 households)  Calculate the effects took into accounts the differences of sex distribution  10 minutes’ car use reduction a day  6 minutes’ walking increase a day (for remember well)  We used these results for cost benefit analysis based on assumptions that 1) Rate of two groups was same to the whole target area （ total: about 65,000 people).  maybe overestimate 2) only one people in any household would change travel behavior  maybe underestimate Differences of travel behavior Remembe r vaguely Remembe r well Car （ times/month ） -1.95-3.79 Car (minutes/day ） -2.60-9.29 Public transportation （ times/month ） -0.592.40 Bike （ times/month ） 1.052.60 Bicycle and walk （ times/month ） 2.083.10 Bicycle (minutes/day ） 6.932.13 Walk (minutes/day ） 7.666.63 EVALUATION OF MM MEASURE

8. 8 difference of travel time for each mode （ minute/person ・ day ） difference of travel distance for each mode （ km/person ・ day ） (Expect for MM participants) Reduction of total travel time by car (1) Health enhancement （ yen/person ・ day ） Indicators for MeasuringEvaluation indicators of MM (2) Reduction of traffic accidents (yen/person ・ day ） (3) difference of travel cost （ yen/person ・ day ） Reduction of travel cost by car (4) Reduction of CO2 emission （ yen/person ・ day ） (6) Increase of freight revenues （ yen/person ・ day ） Transport operators Social benefit (5) Reduction of travel time （ yen/person ・ day ） Benefit of MM participants Average travel time (km/h) Traffic observation data Walk time and medical care cost (yen/minute) Social cost for a traffic accident (yen/case) Average fare (yen/time) Value of time walk car Public transportation car Average fuel cost (yen/km) Average fare (yen/time) EVALUATION INDICATORS OF MM Increase of travel cost by public transportation Cost of CO 2 (yen/g-Co2)

9. 9  Calculate the medical care cost corresponded to walk time based on scientific research report. (1) Health enhancement Walk time (day) More than 1 hour 30 minutes to 1 hour less than 30 minutes Total medical care cost (yen/person ・ day) Men 25,23029,02630,177 Women 18,88920,47621,693 Fig. Walk time and total medical care cost  This benefit is derived from the difference of the medical care cost corresponded to the difference of walk time. Total was 366 (million yen/year) An experimental study about efficiency evaluation of healthcare by analysis of medical care cost, the scientific research report, The report of Ministry of Health, Labor and Welfare, 2005. ⊿Ｍ EDICAL = C’ me - C me （ yen/person ・ day ） ・ C’ me ： medical care cost corresponded to walk time with MM (yen/time). ・ C me ： medical care cost corresponded to walk time without MM (yen/time).

10. 10 ΔAC=C ac × α ac × ΔT car (yen/ person ・ day) C ac ： social cost for a traffic accident (yen/number of traffic accident) α ac ： probability of encountering a traffic accident by using car in target area (number of traffic accident/minute) ΔT car ： difference of car use (minute/person ・ day) (2) Reduction of traffic accidents Total was 390 (million yen/year)  This benefit was derived from the following equation.  C ac = social cost for one casualty （ yen/person ） × casualties of traffic accident in target area (person/year) ÷ the number of traffic accident in target area (number of traffic accident/year) = 4,337 （ yen/ number of traffic accident ）  α ac =average time of car use in target area （ minute/person ・ day ） × population of target area （ person ） = 0.91×10 -6 (number of traffic accident/minute)

11. 11 (3) Reduction of CO 2 emission C CO2 ※ = 1,212×10 -6 （ yen/g-CO 2 ） β car = 94 （ g-CO 2 /minute ）、 β pub = 920 （ g-CO 2 /time ）、 β bike = 380 （ g-CO 2 /time ） ΔCO 2 = C CO2 ×β m × ΔT m (yen/ person ・ day) C CO2 ： cost of CO 2 (yen/g-CO 2 ) β m ： basic unit of CO 2 emission by mode "m“ (g-CO2/time) or (g-CO 2 /minute) ΔT m ： difference of use mode "m“ (time/person ・ day)or (minute/person ・ day) m ： car or bike or public transportation  This benefit was derived from the following equation. ※ Ministry of the environment: The evaluation report about Japan’s Voluntary Emissions Trading Scheme (JVETS) in Japan,2005 Total was 11 (million yen/year)

12. 12 Obtained OD Matrix Total travel costs without MM  Reduction rate of OD in target area Red_O=(X/2)/(S_O), Red_D=(X/2)/(S_D) ・ S_O(=1,681,609) ， S_D(=1,683,818) ：  Total traffic volume depart from ( arrive at ) all zone in target area. ・ X(=155,312) ：  Car trip reduction figured out difference of car use (time/month) ※ Distribution of X is not observed, so we assumed half of X is depart from ( arrive at ) all zone in target area and reduction rate of OD is the same as whole target area. Modified O-D matrix Total travel costs with MM (4) Reduction of travel time  This benefit was derived from the following process. Total was 324 (million yen/year)

13. 13 Increase of freight revenues ΔFARE ＝ C pub × ΔT pub (yen/ person ・ day) ＝ {C bus × (1 － α tra ) + (C tra × α tra ) } × Δt pub C bus ： average fare of bus in target area(yen/time) C tra ： average fare of railway in target area(yen/time) α tra ： rate of railway use Δt pub ： difference of public transportation use(time/person ・ day)  This benefit was derived from the following equation. Total was 23 (million yen/year) C tra = average fare of an ordinary rail ticket （ yen/time ） ×β ＋ average fare of commutation ticket （ yen/time ） × （ 1-β) = 281 （ yen/time ） ※ β:rate of use of ordinary ticket=0.399 C bus = the fare of bus inside Kyoto city =220 (yen/time) α tra = 0.77

14. 14  Health Enhancement = 366 (million yen/year) (= Difference of the medical care cost corresponded to difference of walk time)  Reduction of Traffic Accidents = 390 (million yen/year ） (= Social cost for a traffic accident × Probability of encountering a traffic accident by using car in target area × Difference of car use)  Reduction of CO 2 Emission = 11 （ million yen/year), 8,700 （ t/year ） (= Cost of CO 2 × Basic unit of CO 2 emission × Difference of use mode “m”) m: car or bike or public transportation  Reduction of travel time in whole road network = 324 （ million yen/year ） Total Benefit = 1,091 (million yen/year) Total Cost = 33.5 （ million yen/year ） Cost effectiveness = 32.6  Increase of Freight Revenues = 23 (million yen/year ） (=Average fare of public transportation × Difference of public transportation use) EVALUATION OF MM MEASURE

15. 15  Persuasive message to promote voluntary travel behavior change through domestic news paper could actually change people’s travel behavior.  The social benefit reach a significant level (=32.6) for local municipality.  We have developed a system to assess social benefit of MM while considering various aspects and, that can be used in various cities and areas in Japan. Thank you for your attention.  To evaluate MM measures properly,It is necessary  To discuss the data such as cost of CO2.  To study unconsidered evaluation indicators such as city vitality and value of mobility itself. From now on ・・・ CONCLUSION