Conclusion

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CHAPTER 5: CONCLUSION

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The results of Cluster 1 from both case studies showed that the areas with low density (D1; low population density and low household density) and further away from CBD (D4) are linked with low travel energy consumption. In the case of Fukuoka, less land use mix (D2), less road connectivity (D3) and poor transit accessibilities (D5) are found influencing for lower energy consumption. In contrast, Kathmandu showed that lower energy consumption is related to higher D2, D3 and D5. Further, in both cases, this cluster indicates that higher use of private mode is associated with low density.

The results of Cluster 2 showed almost the same interrelationship between urban form, travel behavior and travel energy consumption for Fukuoka and Kathmandu.

Increase in road connectivity (D3) is found strongly interrelated with the increase in travel energy consumption. Also, higher travel energy consumption is found interlinked with less density (D1; less population density and less household density), less land use mix (D2) and poor transit accessibilities (D5), especially associated with the areas further away to CBD (D4). This type of characteristic associated with higher use of private mode. Higher road connectivity with poor transit accessibilities intentioned people to use private mode.

The results of Cluster 3 from both cities showed that higher density (D1) and higher land use mix (D2) with less road connectivity (D3) is interrelated with less travel energy consumption. The interrelationship between destination accessibility (D4), transit accessibility (D5) and travel mode choice is found different in Fukuoka than of Kathmandu. In Fukuoka, closer to CBD (D4) is associated with better D5 and higher use of public mode followed by walk. So, providing priority to public transportation is viewed as one way to supply an alternative form of mobility to the private car and therefore reduce energy consumption. Whereas, in Kathmandu, closer to CBD (D4) is associated with poor D5 and higher use of walk followed by private mode (motorcycle). This indicates that developing country like Kathmandu, even higher density and close to CBD, use of private mode (motorcycle) is higher due to poor public transportation service. The shift of passengers from private mode to public mode is supposed to be achieved by creating an attractive and competitive public transportation system.

158 5.1.2 Objective 2

The second objective was to identify influencing mechanism of urban form on travel energy consumption. Influencing mechanism analysis was performed based on the two case studies: Fukuoka City, from a developed country and Kathmandu City, from a developing country. Multiple linear regression model (MLRM) was applied to fulfill this objective. MLRM quantifies the degree of correlation between multiple independent variables on a dependent variable. Also, based on MLRM, it is possible to determine the major influencing factors for travel energy consumption with relationships established among all the variables involved.

Firstly, in section 2.6 based on Fukuoka, MLRM analysis was used to understand the effect of urban form on travel energy consumption and identify the influencing factors for energy consumption. Based on five different travel purposes at both trip origin and trip destination, the research framework was established including urban form (5Ds) and socio-demography as independent variables to predict the effect on three dependent variables- non-motorized mode, motorized mode (public and private) and energy consumption. However, the MLRM result at both trip origin and trip destination has a little difference. It is likely that the zone for trip origin also acts as trip destination depending on the travel purpose. To some extent, the types of purpose could represent the types of destination locations. Moreover, the inclusion of return home purpose likely violates the result as it can be seen, almost all return home trips and other trips that start from home use the same mode. So, the research framework established in section 2.6 was realized the need to be improved and thus, in section 2.7 (case of Fukuoka) and section 3.6 (case of Kathmandu), we modified the research framework and came up with two phases of performing MLRMs. In the first phase of MLRM, urban form variables (5Ds) and travel behavior variables (trip for work, school, business, private) were chosen as independent variables where travel mode choice is used as a dependent variable. In the second phase of MLRM for energy consumption, the independent variables consist of mode choice for travel and travel distance where the dependent variable is total travel energy consumption.

In the first phase of MLRM, non-motorized mode (walk and bicycle) showed better model fit for both cities. In the mode-wise stratified models, the model for non-motorized mode showed a better model fit with 90% variance (R² = 0.901, p-value <

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0.000) in the case of Fukuoka and in the case of Kathmandu 92.4% variance (R² = 0.924, p-value < 0.000). Non-motorized mode is found positively associated with density (D1), land use mix (D2), distance to CBD (D4), transit accessibilities (D5) and inversely associated with road connectivity (D3). The use of walking and cycling has a potential role in replacing motorized mode use, especially in dense areas. Non-motorized travel is best viewed not as a substitute for private mode but as a complementary mode of travel together with public transportation specifically in the case of longer travel distance. In the case of Fukuoka, D1, D3 and D4 are identified as the most influencing factor for promoting non-motorized mode and reducing travel energy consumption. Whereas, D4 is found influencing factor for non-motorized mode in Kathmandu but with less significance.

After non-motorized mode, among the models in the mode-wise stratified models presented in the first phase of MLRM, private mode showed a better model fit for both cities. In the case of Fukuoka, the model showed 83% variance for car (R² = 0.833, p-value < 0.000) and in the case of Kathmandu 84.6% variance for motorcycle (R² = 0.846, p-value < 0.000). This result suggests that the purpose of giving priority to reduce private mode should be dealt with differently. In a developed country, it should be dealt with car use whereas, in the case of a developing country, it should be dealt with motorcycle use. For both case studies, density (D1) is found the most influencing factor for reducing private mode. In addition, distance to CBD (D4) is found positively associated with private mode use. In the case of Fukuoka, car is found positively associated with road connectivity (D3). Contrast to this, in case of Kathmandu motorcycle is found inversely associated with D3.

The second phase of MLRM results of both cities showed that travel energy consumption mainly depends on private mode (car in Fukuoka, motorcycle in Kathmandu), non-motorized mode and travel distance. In the regression model for travel energy consumption, private mode use and travel distance are found positively significant (p = 0.000 for both cities) with an increase in travel energy consumption.

Whereas, non-motorized mode showed a significant inverse association (p = 0.012 in Fukuoka, p = 0.000 in Kathmandu) with travel energy consumption. So, the result suggests that the reduction of travel energy consumption can be achieved by reducing

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private mode use and travel distance as well as increasing non-motorized mode. The requisite of achieving the mode shift and lessen the travel distance is achieved through realizing and implementing the results in the first phase of MLRM. The first phase of MLRM for both cities provide many recommendations regarding urban designs to support the land use and mode choice as the models showed the effects of urban form on mode choice.

5.1.3 Objective 3

The third objective was to identify and evaluate energy efficient urban planning approaches for Kathmandu based on micro-scale analysis and influencing mechanism analysis of urban form on travel energy consumption. Recommendations have been proposed based on the results from objectives 1 and 2. Also, evaluation of energy efficiency has been performed at individual ward level and cluster level by thoroughly analyzing influencing factor to identify how much energy efficiency can be achieved by the implication of those proposed recommendations. The evaluation proved that the proposed recommendations for Kathmandu city reduce motorcycle use and energy consumption significantly. All these recommendations need to be integrated for promoting travel energy efficiency in Kathmandu. Overall, the proposed recommendations are summarized in three categories: Integrated land use-transport planning, policy intervention and inspiration.

Integrated Land Use-Transport Planning

 Revitalize the city core sector of Kathmandu city based on transit-oriented development (TOD).

 Develop mix used high rise apartments in low residential areas in CBD, i.e.

where greater land use mix with better transit accessibility.

 Decentralize the daily traveled facilities and services like institutional, and work facilities market areas.

 Provide safe bicycle networks, bicycle parking facilities in strategic places (major road cross-section, near a major transit station, CBD area) to encourage people to cycle.

 Provide safe (installation of street light, traffic light and speed breaker) and attractive street design (landscaping, furniture, aligning shade trees along

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sidewalks, breaking up the horizontal length) with short and direct connections between urban facilities (work areas, schools, market, and parks) to promote walking and cycling.

Policy Intervention

 Providing access to the public mode is not sufficient but also requires improvement on public transit accessibility (dedicated bus lanes in rush hours, more transit stops at a walkable distance in dense residential areas) and services (favorable service routes, punctuality, reasonable charge, safety and security).

 promotion of large buses like Bus rapid transit (BRT) in such a way that it integrates with other public transport modes; which serve as feeder services in the areas of sprawl urban development and less connectivity of roads.

 Promote bicycle sharing system; short-term bicycle rental service in the city core areas and near major transit stations outside the TOD

 Restrict motorcycle accessibility in the city core area to limit the intrusion of private mode and provide better and safer conditions for pedestrians and reduce their negative impacts on pollution, safety and aesthetics of neighborhoods.

 Implement Information Technology (IT) in public transportation of Kathmandu as in Fukuoka. Introducing IC card, providing information on the time schedule, fare and nearest transit stations has a significant role to connect people with public transportation.

 Fix high charges, such as parking charges in CBD areas, vehicle taxes and insurance.

 Like in Fukuoka, people need to encourage send their children to elementary school within the ward they living.

 Regional location policy with other cities to develop clustering of commercial activities or land use mixes nearby public transport nodes and corridors.

Inspiration

 Sufficient inspirational programme needs to change the consolidated habits of the population and encourage people to use transit.

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 The course related to behavior driven interventions need to include from schooling, to raise awareness among school-children and their parents. It also increases road safety and thus makes walking and cycling a safety option for daily commuting.

 Development of a comprehensive marketing campaign to influence cycling by inspiring them how much cycle has health benefits, environmental and financial benefits.

 Offer transit incentives to get people out of their private mode in exchange for public transportation and also to make them feel that public transportation is a valuable transport option.