SOCIAL BENEFIT OF PERSUASIVE COMMUNICATION THROUGTH MASSMEDIA FOR
SOCIAL BENEFIT OF PERSUASIVE COMMUNICATION THROUGTH MASS-MEDIA FOR MOBILITY MANAGEMENT 2009/5/15 Ayu Miyakawa Supervisor: Satoshi FUJII
PURPOSE 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. This study is to propose an assessment method of social benefit, and apply it for evaluation of MM of persuasive communication through mass-media. 2
MM project using Mass Media 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) Kyoto Prefecture Modal Share: Car use 32. 4%, Railway use 15. 6% Bus use 4. 6% Target Area 3
Persuasive Message in the Newspaper To suggest using a car in “smart way” (= Living-Kyoto on March 24, 2007 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 Leaflet with a simple postal card for application results of preliminary TFP (target at Living-Lady to get the outcome inserted into this article) Message to recruit participant to TFP 4
Surveys for Evaluation of this project 2007. 3 2007. 6 1 page of newspaper Living-Kyoto was provided Questionnaire survey ・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%) Evaluate how much their behavior changed by reading the newspaper article. 5
RESULTS(TARGET POPULATION) 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 ? " Degree of remembrance Not read Not remember at all Not remember the content Remember vaguely Remember well No answer Total 3. 0% 1. 6% number % 433 290 29. 2 19. 5 548 36. 9 146 9. 8 44 3. 0 24 1. 6 1, 485 100. 0 Not read 9. 8% 29. 1% 36. 9% 19. 5% Not remember at all Not remember the content Remember vaguely Remember well No answer “Remember well” and “Remember vaguely” might have changed their behavior by reading the newspaper article. 6
EVALUATION OF MM MEASURE Expand to Whole Target Area (510, 000 households) Calculate the effects took into accounts the differences of sex distribution Differences of travel behavior 10 minutes’ car use reduction a day 6 minutes’ walking increase a day Car (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 (times/month) Car (minutes/day) Public transportation (times/month) Bike (times/month) Bicycle and walk ( times/month) Bicycle (minutes/day) Walk (minutes/day) Remember vaguely Remember well -1. 95 -3. 79 -2. 60 -9. 29 -0. 59 2. 40 1. 05 2. 60 2. 08 3. 10 6. 93 2. 13 7. 66 6. 63 7
EVALUATION INDICATORS OF MM Indicators for Measuring difference of travel time for each mode (minute/person・day) Evaluation indicators of MM Walk time and medical care cost (yen/minute) walk car Benefit of MM participants Public transportation Average travel time (km/h) difference of travel distance for each mode (km/person・day) car Social benefit Traffic observation data (Expect for MM participants) Transport operators Reduction of total travel time by car Social cost for a traffic accident (yen/case) Average fare (yen/time) Average fuel cost (yen/km) Cost of CO 2 (1) Health enhancement (yen/person・day) (2) Reduction of traffic accidents (yen/person・day) (3) difference of travel cost (yen/person・day) Increase of travel cost by public transportation Reduction of travel cost by car (yen/g-Co 2) Value of time Average fare (yen/time) (4) Reduction of CO 2 emission (yen/person・day) (5) Reduction of travel time( yen/person・day) (6) Increase of freight revenues (yen/person・day) 8
(1) Health enhancement This benefit is derived from the difference of the medical care cost corresponded to the difference of walk time. ⊿MEDICAL = C’me - Cme (yen/person・day) ・C’me :medical care cost corresponded to walk time with MM (yen/time). ・Cme : medical care cost corresponded to walk time without MM (yen/time). Calculate the medical care cost corresponded to walk time based on scientific research report. Fig. Walk time and total medical care cost More than 1 hour Walk time (day) Total medical care cost (yen/person・day) 30 minutes to 1 hour less than 30 minutes Men 25, 230 29, 026 30, 177 Women 18, 889 20, 476 21, 693 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. Total was 366 (million yen/year) 9
(2) Reduction of traffic accidents This benefit was derived from the following equation. ΔAC=Cac × αac × ΔTcar (yen/ person・day) Cac :social cost for a traffic accident (yen/number of traffic accident) αac : 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) Cac = 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) αac=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) Total was 390 (million yen/year) 10
(3) Reduction of CO 2 emission This benefit was derived from the following equation. ΔCO 2 = CCO 2 ×βm × ΔTm (yen/ person・day) CCO 2 βm ΔTm m :cost of CO 2 (yen/g-CO 2) :basic unit of CO 2 emission by mode "m“ (g-CO 2/time) or (g-CO 2/minute) :difference of use mode "m“ (time/person・day)or (minute/person・day) :car or bike or public transportation • CCO 2※= 1, 212× 10 -6(yen/g-CO 2) • βcar = 94(g-CO 2/minute)、βpub= 920(g-CO 2/time)、 βbike= 380(g-CO 2/time) ※ Ministry of the environment: The evaluation report about Japan’s Voluntary Emissions Trading Scheme (JVETS) in Japan, 2005 Total was 11 (million yen/year) 11
(4) Reduction of travel time This benefit was derived from the following process. 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 Total was 324 (million yen/year) 12
Increase of freight revenues This benefit was derived from the following equation. ΔFARE = Cpub × ΔTpub (yen/ person・day) ={Cbus× (1 -αtra ) + (Ctra × αtra ) } × Δtpub Cbus : average fare of bus in target area(yen/time) Ctra :average fare of railway in target area(yen/time) αtra :rate of railway use Δtpub :difference of public transportation use(time/person・day) Ctra = 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 Cbus = the fare of bus inside Kyoto city =220 (yen/time) αtra = 0. 77 Total was 23 (million yen/year) 13
EVALUATION OF MM MEASURE 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) 14
CONCLUSION 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. From now on・・・ To evaluate MM measures properly , It is necessary To discuss the data such as cost of CO 2. To study unconsidered evaluation indicators such as city vitality and value of mobility itself. Thank you for your attention. 15
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