社會福利最大化之大眾運輸補貼雙層數學規劃模式－考量生態足跡限制

國立交通大學

交通運輸研究所

碩士論文

社會福利最大化之大眾運輸補貼雙層數

學規劃模式－考量生態足跡限制

Bi-level Transit Subsidy Programming Models

toward Social Welfare Maximization under

Ecological Footprint Constraint

研 究 生： 劉邦政

指導教授： 邱裕鈞 教授

I 

社會福利最大化之大眾運輸補貼雙層數學規劃模式－考量生態足跡限制

Bi-level transit

subsidy

programming models toward social welfare

maximization under ecological footprint constraint

研 究 生：劉邦政

Student：Pang-Cheng Liu

指導教授：邱裕鈞

Advisor：Yu-Chiun Chiou

國 立 交 通 大 學

交 通 運 輸 研 究 所

碩 士 論 文

A Thesis

Submitted to Institute of Traffic and Transportation College of Management

National Chiao Tung University In Partial Fulfillment of the Requirements

For the Degree of Master

in

Traffic and Transportation June 2010

Taipei, Taiwan, Republic of China

II  社會福利最大化之大眾運輸補貼雙層數學規劃模式－考量生態足跡限制

研究生：劉邦政 指導教授：邱裕鈞博士

國立交通大學交通運輸研究所

摘 要

為了達到永續運輸及社會福利最大化之目的，本研究試圖建構一雙層數學規 劃模式針對預算的分配來訂定最適之永續政策。上層是在有限的預算、運輸系統 的容量及生態足跡的限制下，求得每個旅次的社會福利最大化，並對於大眾運輸 使用者進行票價補貼、大眾運輸班次的虧損補貼及可取得的綠能地來消化運輸所 產生的生態足跡。下層則是經由運具選擇模式決定每個旅次發生所使用的運具， 並針對使用私人運具進行使用者均衡模式來決定旅次路線。根據這些假設，本研 究發展出單一世代雙層數學規劃模式模式(SG)及跨世代雙層數學規劃模式(AG)。 單一世代模式僅考量現在所擁有的資源及預算來決定最適之政策；而跨世代模式 則是兩個世代之間的資源及預算交易來求得最適之結果。 為驗證模式的實用性，本研究建構一模擬路網進行模擬分析，單一世代模式 結果顯示，增加大眾運輸使用者的票價補貼及大眾運輸的班次，會吸引許多使用 者使用大眾運輸，並達到相同的社會福利水準，然而，後者會伴隨著產生大量的 生態足跡對於生態環境帶來莫大的傷害。而跨世代模式結果則顯示，現在這個世 代可以藉由移轉部分的預算給未來的世代以增加整體總效益並達到對兩個世代最 佳之決策。 關鍵字：預算分配，雙層數學規劃，永續，生態足跡

III 

Bi-level transit

subsidy

programming models toward social welfare

maximization under ecological footprint constraint

Student： Pang-Cheng Liu Advisor： Dr. Yu-Chiun Chiou

Institute of Traffic and Transportation

National Chiao Tung University

ABSTRACT

To achieve transportation sustainability and social welfare, bi-level budget allocation models are proposed, in which the upper level is to maximize the social welfare of trip makers under the constraints of government budget, capacity of transport system, and ecological footprint by allocating budget to subsidize bus users for increasing public transportation patronage and reducing usage of private vehicles and/or to acquire additional green land for accommodating excess footprint. The lower level is to determine the mode choice decisions of all trip makers and the route choice decisions of those who use of private vehicles. Two models are developed and compared: the single generation (SG) model and the across generation (AG) model. The SG model assumes these decisions are made under the consideration of the contemporary generation alone, while the AG model compromises these decisions with the following generation. To investigate the applicability of the model, a case study on an exemplified network is conducted. Results of the SG model show that the measure of bus fare discount and the measure of bus frequency increase can both attract remarkable percentage of bus usage and achieve almost the same social welfare, however, the latter will generate much larger footprint than that of bus fare discount

IV 

due to the high emission characteristic of buses. The results of the AG model show that the optimal decision of the contemporary generation will compromise its total utility with that of the next generation by intentionally leaving part of budget to the next generation.

Keywords： budget allocation, bi-level programming model, ecological footprint.

V 

誌

謝

時光荏苒，兩年的北交生活，轉眼間，就在我人生中畫下一個完美的句點。 過程中，有許多美好的景色停留，讓我總是捨不得告別這讓我成長許多、穩重許 多的大家庭。 首先，謝謝邱裕鈞教授，在研究的過程中一路扶持著我成長，在一旁給予我 建議及一直扮演指引我人生方向的燈塔，謝謝您，因為有您，讓我認為我毅然決 然來到北交念書的決定是對的，我真的學到許多受用無窮且寶貴的人生經驗。 而在這即將離別的夜晚，總是讓我想起那一起跳舞表演、一起瘋狂想破頭怎 麼把活動辦得有聲有色的所學會，會長泓均總是和我隨時討論活動細節、副會長 秉宏總是排除萬難、不辭辛苦的帶我們練舞、美麗的祕書佩怡總是適時的聽我吐 些莫名的苦水，但還是掛著那大家熟悉的微笑和我說加油，而和我同班六年的好 兄弟醫仲和細心的千瑜則是負責盡職的總務，賢慧且總是幫我做手工藝的美工寶 慧還有總是和我搶桌子的志偉，以及不管何時都沒任何怨言執行活動的好學長偉 丞和朝偉，謝謝你們，總是配合我天馬行空的活動流程及企畫，過程總是把大家 累得半死卻永遠是最支持我的好伙伴。 邱家的思豪、鎮篷、雅丹，也謝謝你們在我論文和工作忙不過來的同時，提 供我許多資訊及幫助，讓我不會因此分不開身而忽略許多該注意的事項，不管時 間過多久，邱家人，永遠是邱家人，對吧！ 還記得，那一晚晚在計中工作的日子，身邊總是環繞著大家，每個人都在綻 放著魅力及光芒述說著自己的未來以及心中遠大的夢想，那時的我們，是多麼的 令人折服與嚮往，希望，不管過了多久，我們都不要忘了最初衷的自己，別遺棄 了每晚我們共同一起看到攜手前往的未來，雖然我們在人生的道路上，暫時分離， 但我相信，總有一天，我們一定會在某一個特定的時間、特定的地點，再一起聚 首，再一次的創造並開啟屬於我們美好的人生故事，所以在這之前，我們每個人 都要在自己所認定的藍天裡努力自在的翱翔，勇敢去追尋屬於我們的夢想。

VI  然而，最後要感謝的，還是要謝謝我的家人們，謝謝媽媽總是在我人生重要 道路上扮演著亦師亦友的角色，帶著我走過許多難關，也看著我逐漸成長茁壯， 相信，換我讓媽媽過著幸福快樂且無憂無慮的日子，已經近在眼前了。 而來到台北念書，遇到一個讓我生命完全不一樣的一個人，不但給了我前所 未有的希望與動力，讓我在處理任何事及面對任何難題，都能發揮超乎平常水準 的能力，雖然，有些近乎嚴格的要求總是讓我們吵得不可開交，但靜下來後，卻 又總是指引我整裝出發的明燈，謝謝你，讓我的人生有了不一樣的開端，謝謝你， 讓我朝著自己的夢想奔去時，可以無後顧之憂的盡全力奔馳，因為你永遠是在背 後最支持我，且會在我不小心跌倒、難過時，給予我最大的溫暖及擁抱的人，這 個人大家都知道是誰，寶貝，謝謝你，陪伴著我分享人生種種成功的喜悅，我們 還有許多未來，需要一起牽著手去面對，一起成長去體會。 劉邦政 謹誌於 國立交通大學交通運輸研究所 中華民國九十九年七月

VII 

Content

Chapter 1 Introduction --- 1

1.1 Motivations and background --- 1

1.2 Research objectivities --- 3

1.3 Framework and organization --- 4

1.4 Research procedure --- 5

Chapter 2 Literature Review --- 7

2.1 The idea of sustainable transportation--- 7

2.2 The tools of sustainable development --- 10

2.2.1 The foundation thesis and application of ecological footprint ‐‐‐‐‐‐‐ 15 2.2.2 The meaning and definition of ecological footprint ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ 18 2.2.3 The steps and calculation of ecological footprint ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ 20 2.3 The concept of the quality of life --- 26

2.4 The application of bi-level programming model --- 37

Chapter 3

Methodology --- 40

3.1 The theory and application of bi-level programming model --- 40

3.2 The framework of bi-level programming model --- 41

3.3 Model formulation --- 42 3.3.1 The SG model‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ 42 3.3.2 The AG model ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ 45 3.4 Solution algorithms --- 48 3.4.1 Solution algorithm of the SG model ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ 48 3.4.2 Solution algorithm of the AG model ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ 50

Chapter 4

Computational experiments and analyses --- 53

VIII 

4.1 Simplified example analyses --- 53

4.2 The definition of the parameters --- 54

4.3 Results of the Single Generation model --- 56

4.4 Results of the Across Generation model --- 58

4.5 Sensitive analysis --- 59

4.5.1 Available budget ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ 59 4.5.2 Various values of α associated with in‐vehicle travel time ‐‐‐‐‐‐‐‐‐‐‐‐‐‐62 4.5.3 Various values of β associated with out‐of‐vehicle travel time ‐‐‐‐‐‐‐ 65 4.5.4 Various values of γ associated with travel cost ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ 68

Chapter 5

Conclusion and Suggestion --- 71

5.1 Conclusion --- 71

5.2 Suggestion --- 72

IX 

List of Figures

Figure 1.1 Research flowchart --- 4

Figure 2.1 A city has an “industrial metabolism” to measure ecological footprint ---- 12

Figure 2.2 Expected changes in quality of life indicators by different situations --- 30

Figure 3.1 Framework of the proposed model --- 41

Figure 3.2 The iterative solution algorithm of the AG model --- 50

Figure 4.1 Transport network of the simplified example --- 53

Figure 4.2 footprint under various amounts of available budget. --- 59

Figure 4.3 QOL under various amounts of available budget. --- 60

Figure 4.4 Optimal budget allocation plan under various amounts of available budget. - --- 60

Figure 4.5 QOL and footprint under various values of α --- 62

Figure 4.6 Optimal budget allocation plan under various values of α --- 63

Figure 4.7 QOL and footprint under various values of β --- 65

Figure 4.8 Optimal budget allocation plan under various values of β --- 66

Figure 4.9 QOL and footprint under various values of γ --- 68

X 

List of Tables

Table 2.1 Comparable analysis of tools assessing sustainability --- 10

Table 2.2 Eight major land-use categories and categories --- 18

Table 2.3 Compared ecological footprint of different major countries around the world --- 19

Table 2.4 The purposes and disadvantages of ecological footprint --- 24

Table 2.5 literature review about sustainable transportation --- 25

Table 2.6 Description of importance ratings and mean scores of expected change of 22 quality-of-life indicators --- 33

Table 2.7 literature review about quality of life --- 35

Table 2.8 literature review about bi-level programming model --- 39

Table 4.1 Input data of the simplified example --- 54

Table 4.2 Parameter settings of the models --- 55

Table 4.3 Parameter settings associated with bus and car --- 55

Table 4.4 Comparisons of four strategies --- 57

Table 4.5 Results of the AG model --- 58

Table 4.6 The result of the sensitive analysis under various amounts of available budget. --- 61

Table 4.7 The result of the sensitive analysis under various amounts of α --- 64

Table 4.8 The result of the sensitive analysis under various amounts of β --- 67

1 

Chapter 1 Introduction

1.1 Motivations and background

Transportation plays an important role as a key chain of the social systems and ecosystems. Sustainable transport has drawn increasing worldwide attentions under the policies and initiatives of sustainable development provoked by the Brundtland Commission, formally the World Commission on Environment and Development (WCED) since 1987. The OECD (1996) defined environmentally sustainable transport as transportation that does not endanger public health or ecosystems and meets mobility needs consistent with use of renewable resources at below their rates of regeneration and use of non-renewable resources at below the rates of development of renewable substitutes. Pertaining to this concept, a number of earlier works attempted to address what the scope of transportation sustainability meant and what the directions and indicators of sustainable transportation were. For example, Black (1996) defined sustainable transport as “…satisfying current transport and mobility needs without compromising the ability of future generations to meet these needs.” Whatever it is defined, most researchers have agreed that sustainable transport development is highly affected by such factors as spatial and land-use planning, government policy, economic forces, technology, and social and behavioral trends.

Towards transportation sustainability, it is essential to guide people to choose low- or zero-emission and energy conservation mode. However, people always choose the most economical and convenient mode depending upon their life styles. Use of private vehicles without paying the external pollution and congestion costs seems a popular

2 

choice worldwide, which also explains the rapid growth in the ownership and usage of cars and motorcycles. The greater usage of private vehicles will inevitably lead to a serious environmental disaster.

To control the usage of private vehicles and to encourage public transportation patronage is a classical “Carrot-and-Stick” policy to relieve such an environmental disaster. However, in most of demographic countries, the Stick-related policies are usually not appealing. Therefore, under government budget and ecological footprint constraints, how to provide adequate favorable incentives to encourage the ridership of public transportation deserve in-depth studies.

However, mode choice behaviors are significantly affected by level of service and travel cost of transport modes; while the level of service and travel cost determines the mode choices inversely. In addition, many stakeholders, such as passengers, transit operators, government, are involved during the decision process. The complexity of transport systems not only derives from the pluralism of infrastructures and vehicles, it also sources from the behaviors of people and organizations. Very few studies have employed quantitative methods that can satisfactorily elucidate the interactions among different transport systems under sustainability contexts, perhaps due to the complex nature of transport systems. Without an analytical framework or robust modeling, quantitative results of insightful directions and interactions among different sectors are barely obtained. Therefore, to propose policy towards transportation sustainability, it is necessary to develop an integrated model which can model such complex interactions among various modes and stakeholders and to clearly indicate the directions of effective policies.

3 

In addition, “ecological footprint” is one of tools to measure what natural burdens and how sustainable an activity is, which is defined as the total area of productive land and water area required to provide support for that activity (Wackernagel and Rees, 1996). This tool is helpful to unify different units of resources used and environment burdened during the transportation process and to compare with the amount of natural resource which we enjoy.

1.2 Research objectivities

Based on the abovementioned motivations, the aims of this study are：

1. To review and summarize the studies related to “sustainable transportation”, “ecological footprint”, and “quality of life” to serve as the step stone of this study. 2. To develop a bi-level programming model to determine the optimal strategies for subsidizing public transportation toward Quality of Life maximization and Ecological Footprint minimization under the government budget constraint and lower-level model (user equilibrium model).

3. To validate the proposed model by an exemplified example.

4. To draw conclusions and to recommend the strategies through scenario analysis and sensitivity analysis.

4 

1.3 Framework and organization

The research flowchart of this study is depicted in Figure 1.1.

Introduction

Literature Review

Model Formulation

Quality of Life Ecological Footprint

Solution Algorithm Sensitivity Analysis Scenario Analysis Suggested Policies Discussions and Conclusions Data Collection *Taipei O-D Matrix

*Ecological Footprint of Each Modes *Travel Cost of Travelers

*Travel Time of Travelers Bi-level Programming Model

Case Study

5 

1.4 Research procedure

Following the research objectives and the flowchart in Figure 1.1, the research procedure of this study is designed below：

1. Problem definition

Clearly define the research target and scope of this study and to confirm the objectivities of this study. Determine the potential methodologies and tools related to this research.

2. Literature review

Systematically review the studies related to sustainable transportation, ecological footprint, and quality of life for selecting the key indicators influence sustainability and quality of life.

3. Research framework

Due to the complexity of the transport systems, the proposed model will contain several sub-models. To clearly indicate the relationships among these sub-models, a research framework is developed.

4. Model formulation

The proposed bi-level programming model is formulated as： I. Upper level：

The decision maker in upper level is government, which aims to determine an optimal strategies for subsidizing public transportation to maximize quality of life and minimize ecological footprint under the budget constraint.

II. Lower level：

There are two models in the lower level： a model choice model (Logit model) and an user equilibrium model. The decision maker in lower level is the users of the transportation system. Users attempt to make mode choice and route choice decisions

6  to be better off.

5. Exemplified example

An exemplified example is designed validate the proposed model and to compare the performances of different subsidy strategies.

6. Sensitive analysis

This chapter presents the sensitive analysis of parameters in the proposed model, including changes in budget, mode choice coefficients, and ecological footprint coefficients.

7. Scenario analysis

To further investigate the effect of situation changes, three scenarios： optimistic, neutral, and pessimistic are respectively tested and compared.

8. Conclusion and suggestion

Based on the results of case study, effective strategies towards transportation sustainability are recommended. Suggestions for future studies are also indicated.

7 

Chapter 2 Literature Review

2.1 The idea of sustainable transportation

Sustainable development should include three principles about fairness, sustainability and commonality. In society, we have to distribute the resource fairly to satisfy the need of contemporary and next generations. In economy, we have to develop economy in sustainable progress but protect the natural system of the earth. And in ecological, we look forward to coexist between human and the nature. This idea about sustainable development was proposed from the proposal about World Conservation Strategy by International Union for Conservation of Nature (IUCN), United Nations Environment Programme (UNEP) and World Wide Fund for Nature (WWF) in 1980s. And then, World Commission on Environment and Development of United Nations in 1987 (WCED) put forward the special project report of “our common future”, commonly defined as development that meets the needs and aspirations of current generations while preserving the ability of future generations to meet their own needs and aspirations.

OECD (2000) declaimed the core concern of sustainability is in ensuring that while economic and social development continues, the natural and human environment is preserved, and the impacts of development and environmental management are equitably distributed. They also have clearly explanation about “sustainable transportation”, and based on it to establish the sector of Environment Sustainable Transport (ESI). They set the goal of sustainable transportation to decline the pollution from the vehicles. The way is how do reduce the trips, how to develop and encourage

8 

public transport and how to improve the impact to environment from transportation by technique.

Steg and Gifford (2005) propose the principle of sustainable transportation about how to balance environment, society and economy by seeking and building up the important indicators. Government could take advantage of the effective sustainable goal to keep a watchful eye on the development of sustainable transportation by effective indicators. According to the study from Geurs and Van Wee (2000), they promote some criterions to evaluate CO2, NOx, particles emission and land use. And

then, they present three different scenarios to evaluate sustainable transportation in different levels：high-technology scenario, mobility-change scenario and combination scenario. And we could know from that, if we want to reach the goal of sustainability, we have to make a breakthrough in technology and urgent to change the behavior of human and the style of economy. However, it also causes some problems about that if government always develops forward sustainability, whether it’s accepted by population or not?

There are many different definitions about sustainable transportation in many references. However, they are talking about the same thing. That is how to get balance among economy, society and environment between different generations to reach the goal of sustainable transportation. And government could base on contemporary transportation system to develop sustainability in future, including the land use, pollution emissions, traffic safety, traffic noise, and healthy affection, the cost of emergency and accessibility (Steg and Gifford, 2005). And at the same time, governments also have to consider different strategies which will have different impacts on sustainability. Changing the transportations system in use would have other

9 

influences on any un-sustainability development. That is why the governments have to consider the levels of society, economy and environment when they do some policy making.

Different stakeholders meet their goals with widely different priorities to reach consensus on interim goals. In Amekudzi (2009)’s research, they present a model about sustainability footprint to assess the quality of life for society and the impact of natural environment of transportation system. As the result, constructing a useful and feasible tool to observe and develop sustainability is necessary. We can proof that by the idea from Acutt and Dodgson (1997), they consider transportation department should apply different economic strategies to incline the impact on environment from transportation system and assess the utility of all, including the tax on pollution, fuels and the usage of the vehicles.

Discussion

According to some studies, we could find out that if we want to develop forward sustainability, economic, environment and equity are the different levels what we have to find out the balance among those. There are also some studies discussing about how to use the different indicators or tools to evaluate the sustainability. Therefore, this study will summarize some tables to point out the difference among different tools which used by evaluating the transportation sustainability.

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2.2 The tools of sustainable development

 

Because of economy improvement, the consumption of resources also increases rapidly. When earth reaches the limit of ecological capacity, there are also some crises for human being surviving. Therefore, the governments around the world have set the goals to solve the problems about sustainability and develop some programs and indicators to assess the system. The results are summarized in table 2.1.

Table 2.1 Comparable analysis of tools assessing sustainability

Tools Contents Factors

Sustainable development indicators

Solve the problem and assess sustainability by three levels of economy, society and environment.  Economy factors  Society factors  Environment factors Ecological footprint

Require how much land and water area to reduce the resources to consume and absorb its wastes under prevailing technology

 Fossil energy land  Build up land  Arable land  Pasture  Sea area  Forest area Environment space

Based on the environment space in 2010to assess the usage of environment resources and consider the problem of resources allocations.

 Energy usage and emission  Reuse materials  Land-use  Forest  Sea Life recycle analysis

Assess the environment impacts of the process from extracts, production, usage and discards  Materials  Pollutions  Discards Ecological effective analysis

Use materials and energy more efficiency, and incline the cost of economy and impact of environment  Materials density  Energy density  Poison spread  Recyclable materials  Re-use resources efficiency

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 Durable materials  Service power In this study, I take advantage of ecological footprint as the tool to evaluate the ecological environment. The characteristic of the ecological footprint is the concept by assessing the natural resources required by various human activities in terms of productive land. That is the productive land and water area required to provide support for that activity, and it is also a resource management tool that measures how much land and water area a human population required to produce the resources it consumes and absorb its wastes under prevailing technology.

Based on the concept of ecological footprint, this study applies it to evaluate sustainable transportation within some development indicators. And this paper uses this concept to measure the consumption of different resources among different vehicles. And we expect we could use this result to let people realize the idea of the transportation behaviors from each person will have heavy impacts on the environment of the earth. Therefore, people should choose the friendlier ways such as shifting the habits of transportation in order to improve the environment of the earth.

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Figure 2.1 A city has an “industrial metabolism” to measure ecological footprint Sources： Rees and Wackernagel, 1996

In other words, we can image the concept of ecological footprint as the metabolism of the city or the global world (Rees and Wackernagel, 1996). In this respect, it can be compared to a large animal grazing in its pasture. Just like the beast, the city consumes resources and all this energy and matter eventually passes through to the environment again. Thus, the footprint question becomes： “How large a pasture is necessary to support that city indefinitely-to produce all its ‘feed’ and to assimilate all its wastes sustainably”

In general, the consumption of ecological footprint produced by higher-development city is the much highest. As this result, higher-development city have to balance the ecological deficit with un-development or developing cites. Therefore, when we calculate the ecological footprint on the special area, we can forward to compare with ecological benchmark to realize the differences between each other.

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Ecological benchmark means that the natural resources what people could use in the earth. The value will change by the real land productivity. If this value is much higher than the real one, we call it “ecological deficit”. We could find out the reflection about how to use the natural capacity and the tradeoff happened by ecological deficit.

Before calculating the ecological benchmark, we have to classify the biological productivity of the different land use. And we can estimate what the alternative lands people can use from different lands and productivity. Biological productivity means the ability of regeneration. Let the productivity of the special land divided by total land area in this category. According to the research from Wackernagel et al. (1999), they separate it into six categories：

1. Arable land

The most productivity land in ecological, people could cultivate the crop like wheat or rice. People have 0.25 hectare per person around the world.

2. Pasture

People take advantage of it to graze cattle, sheep or cow there. People have 0.6 hectare per person around the world.

3. Forest area

People could use it to cultivate or produce the natural woods. There are 34.4 hundred million hectare forest areas around the world. That equals to 0.6 hectare per person around the world.

4. Fossil energy land

In theory, these areas are used to absorb and preserve CO2. However, more

lands have been developed in reality, couldn’t use it to absorb CO2. That means

the consumption and the energy of fossil land couldn’t absorb by these areas. We depend on the natural capital to survive now.

14  5. Build up land

People use it to construct or road building, however, if we continuously develop these area could have harmful damage for arable areas. People have 0.03 hectare per person around the world.

6. Sea area

Studies view sea areas as biological productivity land, because of that people could acquire food from sea. There are 366 hundred million hectare sea areas all over the world. That equals to that people have 6 hectare each person. However, the 95% ecological productivity of the sea only 0.5 hectare, that is the maximum production of the sea.

Summarize the total land areas of biological productivity： 0.25 hectare of arable area, 0.6 hectare of pasture area, 0.6 hectare of forest area, 0.03 hectare of build area and 0.5 hectare of sea. That means people have 2 hectare biological productivity land each person around the world. However, according to the report of the WCED, there are at least 12% ecological capacities preserved to protect biological diversity.

According to this result, people only could use 1.7 hectare area among it, the other 0.9 hectare have been used to protect the biological diversity. And we view this 1.7 hectare land area as “ecological benchmark” to compare with ecological footprint. Although ecological footprint is easier using to evaluate the environment protection and sustainability, there are some opposite opinions from some studies considering this concept is too easier to have the problems about that there may some gaps between theory and reality (Rees and Wackernagel, 1996). For example, the model is static, whereas both nature and the economy are dynamic systems. Therefore, ecological footprint cannot directly take into account such things as technological change or the

15 

adaptability of social systems. In fact, each analysis provides a snapshot of our current demands on nature, a portrait of how things stand right now under prevailing technology and social values. Therefore, we could view ecological footprint as a tool to estimate how much we have to reduce our consumption, improver our technology, or change our behavior to achieve sustainability. And if we add the factor of time, we also could find out the influence change by improvement technology and behavior change.  

2.2.1

The foundation thesis and application of ecological footprint

The overall ecological footprint model should include the land-used directly and indirectly consumed from all the resource and energy. Because the manner of calculating the ecological footprint is set to list, when adding one assessment item into analysis will may increase the total footprint. That result in the ecological what we calculated is smaller and more conservation than the real world. There are two processes of the analysis and calculation about ecological footprint：At first, tracing and analyzing the overall consumption of resource and junk produced, and then transform it into the bio-productivity land area to provide and supply the function around the world.

In theory, ecological footprint model would calculate how much land and water area used for the consumption of resource. But the process is hard and complicated; there are some simplify way to calculate：

1. The land with productivity is sustainable in the assumption; however, it is not true in the reality, the consumption of the lands are usually faster than re-use it.

2. Only considering the basic service of naturals and focus on how to use the function by the activities directly and indirectly by human being, including the recycle

16 

energy and disposable  consumption, the absorption of the consumption, the building land area, available water using and some environmental pollution.

3. If there are more than two services or activities in the same land area, not calculating the consumption of ecological doubly, only calculate which use more ecological footprint.

4. Simplify the manner of classification about bio-productivity to make it easier to calculate and analyze. E.g. separate ecological system into eight land categories.

Simplifying will underestimate the needs for land by human being. But if continuously tracing the development, the indicators of ecological footprint are just like camera that could display each step about the needs of human being. Ecological footprint presents the other thought to evaluate the problem of environment. It not only emphasizes the analyst of ecological physical, but also promotes the development and expansions of economy are all limited by the ecological carrying capacity. The consumption of resource and energy from human being also has to consider the limitation from the ecological system.

The major strength of ecological footprint analysis is its conceptual simplicity. This method provides an intuitive and visually graphic tool for communicating the sustainability dilemma, which is one of the most important dimensions in sustainability. It not only aggregates the ecological flows associated with consumption and translates them into appropriated land area, but is an indicator that anyone can understand it. Then, the ecological footprint of population can be compared with the available supply of productive land. Individuals can contrast their personal footprints with their ecological “fair Earth shares”. National footprints can be compared to domestic territories, and the aggregate human footprint can be compared to the productive

17  capacity of the entire planet.

In case that the ecological footprint is significantly larger than a secure supply of productive land, the difference represents a “sustainability gap” and “ecological deficit” (Rees, 1996). This is the amount by which consumption must be reduced for long term ecological sustainability. Thus, unlike ordinary measures of total resource use, ecological footprint analysis provides secondary indices that can be used as policy targets. And then the questions appears：How large is our ecological deficit and what must be done to reduce it？

Although acknowledging its power to communicate a fundamental message, some commentators have suggested that the footprint concept is too simplistic. For example, the model is static, whereas both nature and the economy are dynamic systems. Ecological footprinting therefore cannot directly take into account such things as technological change or the adaptability of social systems.

Footprint analysis is not dynamic modeling and has no predictive capability. However, prediction was never our intent. Ecological footprinting acts, in effect, as an ecological camera－each analysis provides a snapshot of our current demands on nature, a portrait of how things stand right now under prevailing technology and social values. Ecological footprinting also estimates how much we have to reduce our consumption, improve our technology, or change our behavior to achieve sustainability.

18 

2.2.2

The meaning and definition of ecological footprint

Ecological footprint analysis illustrates the fact that as a result of the enormous increase in per capita energy and material consumption made possible by technology, and universally increasing dependencies on trade, the ecological locations of high-density human settlements no longer coincide with their geographic locations. So far, our Ecological Footprint calculations are based on five major categories of consumption－food, housing, transportation, consumer goods and services－and on eight major land-use categories as Table 2.2.

Table 2.2 Eight major land-use categories and categories

(1) Energy land a. ”Transformed land” by fossil energy Energy or the land of CO2

(2) Consumed land b. Build up land Deteriorated land

(3) Available land c. Garden Recuperated build-up land d. Arable land Arable system

e. Pasture

Adjusted system f. Cultivated forest

(4) Limited undeveloped land

g. Uncultivated forest Productivity ecosystem h. Unavailable land Desert; Ice cap

Source： Wackernagel et al. (1999)

However, we have examined only one class of waste flow in detail. We account for carbon dioxide emissions from fossil energy consumption by estimating the area of average carbon-sink forest that would be required to sequester them

[carbon emissions/capita] / [carbon assimilation/hectare],

19 

From Table 2.3, we could find out that most highly urbanized industrial countries run an ecological deficit about an order of magnitude larger than the sustainable natural income generated by the ecologically productive land within their political territories. However, ecological footprint analysis illustrates the fact that as a result of the enormous increase in per capita energy and material consumption made possible by technology, and universally increasing dependencies on trade, the ecological locations of high-density human settlements no longer coincide with their geographic locations. Cities necessarily appropriate the ecological output and life support functions of distant regions all over the world through commercial trade and natural biogeochemical cycles. Perhaps the most important insight from this result is that no city or urban region can achieve sustainability on its own. Regardless of local land use and environmental policies, a prerequisite for sustainable cities is sustainable use of the global hinterland.

Table 2.3 Compared ecological footprint of different major countries around the world

Country Population (thousand people) Ecological footprint （ha/capita） Country Population (thousand people) Ecological footprint （ha/capita） Iceland 274 9.91 Poland 38521 3.35

New Zealand 3654 9.83 Israel 5854 3.05

America 268189 8.36 Thailand 60046 2.77

Australia 18550 8.11 Hong Kong 5913 2.66

Canada 30101 6.99 Malaysia 21018 2.66

Ireland 3577 6.57 South Africa 43325 2.6

Finland 5l49 6.33 Venezuela 22777 2.6

Japan 125672 6.25 Brazil 167046 2.57

C.I.S. 146381 5.98 Costa Rica 3575 2.52

Sweden 8862 5.82 Hungary 10037 2.46

20 

France 58433 5.68 Mexico 97245 2.27

Norway 4375 5.68 Philippines 70375 2.17

Austria 8053 5.39 South Korea 45864 1.99

Singapore 2899 5.29 Turkey 64293 1.89 Portugal 9814 5.05 Peru 24691 1.73 Belgium 10174 5.03 Columbia 36200 1.72 Switzerland 7332 5.00 Nigeria 118369 1.69 Netherlands 15697 4.66 Indonesia 203.631 1.58 Argentina 35405 4.64 Jordan 203631 1.54 Germany 81845 4.61 China 1247315 1.18 England 58587 4.6 Egypt 65445 1.15 Italy 57247 4.51 Ethiopia 58414 0.99

Czech Republic 10311 4.2 Pakistan 148686 0.84

Spain 39729 4.18 India 970230 0.81

Greece 10512 3.91 Bangladesh 125898 0.73

Chile 14691 3.46

Source： Wackernagel et al. (1999)

2.2.3

The steps and calculation of ecological footprint

The calculation of ecological footprint includes the steps below：

1. Calculate annual per capita consumption of major consumption items (ci)

First, we estimate the annual per capita consumption of major consumption items from aggregate regional or national data by dividing total consumption by population size. Much of the data needed for preliminary assessments is readily available from national statistical tables on, for example, energy, food, or forest production and consumption. For many categories, national statistics provide both production and trade figures from which trade-corrected consumption can be assessed：

21 

2. Transform major consumption items into land area (aai)

Estimate the land area appropriated per capita for the production of each consumption item by dividing average annual consumption of that item (ci;

kg/capita) by its average annual productivity or yield (p; kg/ha).

Land area appropriated per capita for the production of each consumption item

(aai) = ci/p

Form this formulation; we could summary the total ecological area of annual per capita consumption and service (n). That is total average per capita ecological footprint (ef).

Total average per capita ecological footprint：

1 ( ) n _i i ef aa  



3. Calculate total ecological footprint by multiplying the total average per capita footprint by population size (N), then obtaining the ecological footprint (EFp)

EFp ＝ N × ef

According to the idea of ecological footprint, this study applies this concept to transportation, trying to definite the ecological footprint of transport system. That means “To sum up the population who using the transport system, the productivity land area are needed by the consumption of energy and junk produced.” It also produced the burden to the environment when people use the transport system.

Reference and suppose

There is 15 million hectare of road area, car using is the major. The car owner ratio is 1/1.75 (car/capita)

22 

Suppose one bicycle rider needs 900 KJ foods by 10 kilometer riding.

Environment Canada points out that there is 98.4% car using in the traffic urgent time, however, only loading 62% commuter. As this result, we can make the conclusion about that one bus rider only occupied 2.6% road area of car driver.

（0.016/0.38）/（0.984/0.62）＝0.026

Calculation

Bicycle：Bicycle driver needs 900KJ foods to support the 10 kilometer trip back and forth. Suppose that additional energy comes from the sweet corn of breakfast. And sweet corns need land to produce and energy to manufacture. The needs of land are used to cultivate agriculture product and used to manufacture food is the same. Therefore, the land used above is double than cultivation area. Suppose we neglect the road area of bicycle, per kilogram sweet corns include 13000KJ energy and average productivity per hectare per year 2600 kilogram of the sweet corns around the world.

900( / ) 230( . ) 2

0.0122 122

1300( / ) 2600( / / )

KJ year day year

hectare or each rider need square meters

KJ kg kg ha year

 

 

Car：Average consumption of petrol by car in America approximately 12 liter each 100 kilometers. The manufacturers of car indirectly consume carbon dioxide and road maintenance about 45 %. And per liter petro include approximately 35 million J of energy. Therefore, the footprint of fossil fuels by car commuters is

1.45 12( / ) 0.035( / ) 10( / ) 230( / )

100( ) 100( / / )

L kg hundred milion J L kg day wrok day year

km hundred million J ha year

   



= 0.14 (ha/capita) = 1500 (m2/capita)

23  2 15,000,000( ) 0.06( . ) 600( / ) 250,000,000( ) ha ha capita m capita capita  

Cars using about 97.4% road space, commuting 10 km every day occupied about 1/8 of average car using rate each year. However, each car using represents 7.15 capita, so per unit per capita needs （0.974×1/8×600/1.75）＝42（m2）road space when commuting 10 km. As this result, the footprint of one commuting car is 1442 m2.

Bus：Short distance bus needs 0.9 MJ/capita/km energy, and have to plus additional 45% (the same with the car) for the indirectly needs for road, bus and cost of maintenance.

1.45 0.0009( / / ) 230( / ) 10( )

100( / / )

hundred million J capita km work day year km

MJ ha year

  

= 0.03 (ha/capita) = 300 (m2/capita)

Bus also needs the road space, as suppose above, the road space needed by a bus user is 2.6% the same distance by a car driver. That is （42 m2× 2.6％）＝1.092（m2）. Therefore, the total needs of land area by bus user who have to commute 10 km every day is 301 m2

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Discussion

Based on the statements above, this study summaries some key points about ecological footprint below：

1. It can help us to notice the ecological limit when systems running.

2. Avoiding over consumption and helping government to do the right policy making.

3. A way to help assess both current reality and alternative “what if” scenarios on the road to sustainability.

4. How to strongly share the productive land and water area around the world. 5. Distributing productivity and resource equitably by ecological footprint. This study compares the purposes and the disadvantages in the table below： Table 2.4 The purposes and disadvantages of ecological footprint Purposes and characteristics Limits and disadvantages The indicators of sustainable development：

Display the relationship with the consumption of human and natural environment by quantification indicators.

It’s hard to reflect the sustainable goal among different generations in reality.

The observation tool of sustainable development：

Help strategy maker to analyze and execute that the development is on the right way to goal.

It hard to quantification about the consumption of natural environment.

Continuously trace the ecological environment： Observe the difference between people and development by the change of ecological footprint every year.

Lack biological diversity and the capability and demand of all ecological system.

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This study summaries the idea of sustainability and the concept of the ecological footprint in the table 2.5 below： Table 2.5 literature review about sustainable transportation

Authors/year Research Objectives National wide / City Research Approach

Whitelegg（1983） To decrease using less motorized transport for sustainable outcome

City level （Europe）

 Momo effect analysis  Time valued conception  Leisure life promotion Rees and Wackernagel（1996） To evaluate the effect of ecological system

influenced by human activities National wide Ecological footprint analysis

Acutt and Dodgson（1997） To decrease the environmental effect and

influence of transport modes National wide

Indicator proposed：  Emission regulations  Fuel taxes

 Vehicle use restrictions Linster（1999） To compare different transport modes to different

effect of environment National wide Comparative table

Geurs and Van Wee（2000） To develop different sustainability by different

transport scenario National wide

 Scenario analysis

 High-technology scenario  Mobility-change scenario  Combination scenario Steg and Gifford（2005） To find the balance of environment, society and

economy. City level （Dutch） Indicator proposed： 22 indicators to measure sustainability

Amekudzi（2009） To analyze the effect of transport systems to society and natural

City level

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2.3 The concept of the quality of life

In the study from Steg and Gifford (2005), we find out that, in order to develop sustainability, behavioral and technological strategies not only differ in the extent to which they may improve different sustainability aspects, but probably also in the extent to which they affect the quality of life of citizens. In general, people prefer technological solutions much more than behavior changing, because the latter is perceived as more strongly reducing the freedom to move and convenience. For example, reducing car use implies that we need to adjust our lifestyle, which may evoke resistance because it requires effort and reduces freedom, comfort and convenience. And many people believe that technological measures require few behavioral changes. For example, an energy-efficient car allows individuals to drive as much as the used to do, thereby significantly reducing adverse environmental impacts. However, technical measures generally require initial investments, and therefore often rather expensive, especially for low-income groups (Steg and Gifford, 2005).

Therefore, how to reduce the volume of car use are needed to manage the problems caused by traffic and transport. As this result, drivers agree that car use should be reduced, but they are not in favor of measures that restrict their own car use. We find out the truth about that there are some conflict between individual benefit and sustainability transportation. How to use the balance function to choose an acceptable sustainable transport system is a very important task to be dealt with.

Quality of life is a multi-dimensional construct; there are some different definitions about quality of life from some references. Diener (1984) considers that quality of life is individuals’ cognitive and affective evaluations of their lives and is a

27 

cognitive judgmental process of how satisfied people are with their current state of affairs. And Vemuri and Costanza (2006) think about the participation and the number of times in leisure activities is the decisive indicator of quality of life. The frequency and duration of engagement in leisure activities is an important objective determinant of quality of life. They further separate it into place-centered leisure activities and people-centered leisure activities to examine the relative importance of each for self reported quality of life. Place-centered leisure activities are focus on the special facilities and activities and dependent upon location specific activities, e.g. bowling golfing. And people-centered leisure activities are dependent upon social contact specific activities, e.g. socializing, playing cards. While Spinney (2009) purports people-centered leisure activities tend to have the most positive influence on quality of life. Therefore, in my study, the interaction of place-centered and people-centered factors both contribute to quality of life.

Eck et al. (2005) analyze what impact configurations on the quality of life of different population categories. They propose that individuals take participant in the activities in the special time and the potential action space. Calculate it by the distance from origin to destination, available time space, the ratio of travel time and the speed of the principal vehicle. And they use the following three indicators to evaluate quality of life： trip feasibility, efficiency of travel time and efficiency of travel distance. And we could find out the truth based on the study that the higher urbanization city will have much more shorter travel distance. And travel time will influence by traffic congestions and limit parking space due to higher urbanization cites. However, in higher urbanization cities, there are also some higher percentages to use public transport system, bicycle and walking. Available parking areas also have the limitation and the negative influences on the private car owner. As result, how to build up the

28 

sustainable transportation strategies by the characteristic of urbanization is also a challenge that the policy maker has to realize deeper.

In the study of Steg and Gifford (2005), they use the questionnaires and the definition by compensatory decision-making model. The studies reveal that deteriorations in specific quality of life indicators may be compensated for by improvements in other dimension. Clearly, sustainable scenarios typically threaten individual quality of life indicators such as comfort, freedom and privacy, while quality of life indicators that refer to collective qualities such as environmental quality and nature and biodiversity would improve. For example, most current drivers choose to act in their own interest by continuing to drive, especially because cars are be lived to have many advantages over other modes of transport, such as public transport or bicycles.

However, changes typically are resisted at first, because these may have negative consequences. As long as individual are unsure of the consequences, they prefer the status quo (Steg et al., 2005). For example, Gifford et al. (2002) revealed that attitudes toward bus riding improved and bus riding increased after a policy change, because individuals perceive that the problem is being solved. Therefore, clear description of proposed changes in the transport system is important for helping respondents think through possible consequences of the plans for them personally. This may result in better and more acceptable sustainable transport plans.

Table 2.4 reveals that most quality of life indicators are considered to be very important to people’s lives. That means quality of life indicators refer to important needs and values. There are 22 indicators about different levels below. Policy-makers

29 

should especially consider possible impacts on the most important quality of life indicators when designing and implementing sustainable transport policies. De Groot and Steg (2006) use these indicators to examine relationships between value orientations and perceived quality of life-changes when the cost of car use is doubled. Three general value orientations should be distinguished when studying pro-environmental behavior： an egoistic value orientation (in which people will especially consider costs and benefits for them personally); an altruistic value orientation (in which people will focus on perceived costs and benefits for other people); and, a biospheric value orientation (in which people will consider costs and benefits for the ecosystem and biosphere). Different respondents will have different situations depend on the government’s policies, which changes in quality of life respondents would expect from future economic and environmental improvements or deteriorations. But in overall, when government doubled the price of car use would have more disadvantages than advantages and, thus reduce the perceived quality of life. Respondents indicated that environmental quality, nature/biodiversity and safety were believed to improve if the government would implement this policy (Table 2.4 and Figure 2.2).

30 

Figure 2.2 Expected changes in quality of life indicators by different situations Source： De Groot and Steg（2006）

Quality of life is a personal goals and experiences of life. Therefore, policy makers should especially consider possible impacts on the most important quality of life indicators when designing and implementing sustainable transport policies, because the public will especially oppose measures that negatively affect these quality of life indicators. Governments should look for other ways to achieve sustainable

31 

transport that would affect these quality of life indicators in ales negative, or even a positive way. One may also look for possible ways to compensate the expected negative effects (Steg and Gifford, 2005). In general, sustainable strategies will deteriorate individuals’ indicators of quality of life, but will improve public quality of life. That is prove the truth about that the benefit conflicts between individuals and public is exist, especially when individual car users are asked to significantly adapt their lifestyles and transport behavior.

Therefore, knowing how specific quality of life aspects may be influenced positively may enhance policy acceptability. This will facilitate the implementation of sustainability policies and guarantee effective and efficient decision making. And different countries will have different national conditions and cultures, the sustainable strategies are also different by different countries. However, some studies also reveal the truth about that change in transport may influence quality of life initially, but as individuals usually adapt soon, no significant changes in quality of life may occur in the long term. Therefore, this study looks forward to construct an assessment model to evaluate the change of quality of life.

This study creates the relationship with the concept of ecological footprint and quality of life, considering that the change of quality of life will have influence on the development of sustainable transportation. Dominguez and Robin (1992) also propose three different strategies to reduce ecological footprint while not compromising our quality of life：

1. Increase nature’s productivity per unit of land, e.g. terraces on mountain slopes, solar collectors on unused roof areas or less wasteful agricultural systems (Pimentel et.al 1996).

32 

2. Do the same with less through the better use of the harvested resources, e.g. eco-efficient technology such as smart lamps or heat-pumps;

3. Consume less by be fewer people and consuming less per capita, e.g. by avoiding car-ownership and disposable products. This simpler and less expensive life-style may buy people more leisure time and be less harsh on their health (Dominguez and Robin, 1992).

Amekudzi (2009) proposed the sustainability footprint model, including the concept of ecological footprint and quality of life, to assess development impacts of transportation systems. They take advantage those sustainable development paradigms for addressing civil infrastructure systems have framed the core issues using the tripartite framework of impacts on the economy, environment and society. The model in their studies calculated the change of quality of life to assess and evaluate whether the development sustainability or not.

Discussion

Quality of life is the concept including many different levels. In our opinions, the best situation and the ideal sustainable development is that improve public quality of life, but no change even reduce ecological footprint. Therefore, how to evaluate the rate of change of quality of life to compare different stakeholders in different economic development is much more meaningful about sustainability. Based on the study of Wackernagel, how to choose the indicators what we’re concerned to evaluate quality of life, not considering all of the indicators to make the decision of the strategy. Therefore, the problem what we have to resolve is how to maximum the value of the indicators what you choose, but not decline other indicators in different levels.

33 

Table 2.6 Description of importance ratings and mean scores of expected change of 22 quality-of-life indicators

Indicators Description Important

rating

Expected change Health Being in good health. Have access to adequate health

care 4.9 0.2

Partner and family Having an intimate relationship. Having a stable

family life and good family relationships 4.7 -0.1 Social justice Having equal opportunities and the same possibilities

and rights as others. Being treated in a just manner 4.7 -0.2

Freedom

Freedom and control over the course of one’s life, to be able to decide for yourself, what you will do, when and how

4.5 -0.7

Safety Being safe at home and in the streets. Being able to

avoid accidents and protected against criminality 4.5 0.6 Education Having the opportunity to get a good education and to

develop one’s general knowledge 4.3 -0.1 Identity/self-respect Having sufficient self-respect and being able to

develop one’s own identity 4.2 0.0

Privacy Having the opportunity to be yourself, to do your own

things and to have place of your own 4.2 -0.3 Environmental quality Having access to clean air, water and soil. Having and

maintaining good environmental quality 4.2 1.2

Social relations

Having good relationships with friends, colleagues and neighbors. Being able to maintain contacts and to make new ones

4.2 -0.3

Work Having or being able to find a job and being able to

fulfill it as pleasantly as possible 4.2 -0.5 Security Feeling attended to and cared for by others 4.1 0.2

Nature/biodiversity

Being able to enjoy natural landscapes, parks and forests. Assurance of the continued existence of plants and animals and maintaining biodiversity

4.1 0.9

Leisure time Having enough time after work and household work

and being able to spend this time satisfactorily 4.0 -0.5 Money/income Having enough money to buy and to do the things that

34  Source： De Groot and Steg（2006）

Comfort Having a comfortable and easy daily life 3.5 -0.9 Aesthetic beauty Being able to enjoy the beauty of nature and culture 3.5 0.4 Change/variation Having a varied life. Experiencing as many things as

possible 3.3 -0.6

Challenge/excitement Having challenges and experiencing pleasant and

exciting things 3.2 -0.2

Status/recognition Being appreciated and respected by others 3.0 0.0 Spirituality/religion Being able to live a life with the emphasis on

spirituality and/or with your own religious persuasion 2.9 0.1 Material beauty Having nice possessions in and around the house 2.6 -0.2

35 

This study summaries the concept of quality of life in the table 2.7 below：

Table 2.7 literature review about quality of life

Authors/year Research Objectives National wide /City Research approach

Diener（1984） Quality of life is a cognitive judgmental process of how satisfied people

Dominguez and Robin（1992）

To take advantage of the change of lifestyle to

decrease ecological footprint. National wide Footprint model analysis

Pimentel（1996） To increase nature’s productivity per unit of land National wide

Approaches proposed：

 Terraces on mountain slopes

 Solar collectors on unused roof areas  Less wasteful agricultural systems Steg and

Gifford（2005）

To establish the important indicators to evaluate

sustainable development City level

（Dutch）

Questionnaire

 Propose 22 important indicators of quality of life

Eck et al. （2005）

To analyze what impact configurations on the quality of life of different population categories

City level （Dutch）

MASTIC model

 The feasibility of carrying out desired activities

 Travel time efficiency  Travel distance efficiency Vemuri and

Costanza

To measure the frequency and duration of

engagement in leisure activities National wide

Regression model Revise regression model

36 

（2006）

De Groot and Steg（2006）

To examine relationships between value orientations and perceived quality of life-changes when the cost of car use is doubled.

City level： 1. Austria, 2. Czech Republic, 3. Italy, 4. The Netherlands, 5. Sweden Questionnaire

Three groups analyze：  Egoistic value orientation  Altruistic value orientation  Biospheric value orientation Amekudzi

（2009）

To evaluate and discuss the study whether

development sustainability or not _{（Atlanta and Chicago）}City level

Sustainability footprint model

Spinney et al. （2009）

To quantify the impacts of transport mobility and investigate their impacts on the quality of life

City level （Canada） Questionnaire  Psychological benefits  Exercise benefits  Community-helping  Community-socializing

37 

2.4 The application of bi-level programming model

Bi-level programming model decides x from upper level, and according to the different set x to decide the decision variable about y from upper level. The attributes are as follows (Bials and Karwan, 1984;Wen and Hsu,1991)：

1. There is an obvious hierarchical structure among different decision makers. 2. The decision makers decide the strategies in upper level, and then, the

decision makers in lower level follow it to decide the strategies for their own. 3. The decision units achieve their goal of optimal their own objective function independence, however, the strategies they decided doesn’t influence each others.

4. The external effects from different decision problem will effect their own objective function and feasible solution.

In the applications of transportation with bi-level programming model, there are some literatures below：

Chen (2004) takes advantage of the conception about bi-level programming model to construct the dynamic signal control system. Upper level is minimum total travel time, lower level is user equilibrium model to get the information about signal variables.

Cao and Chen (2006) promote the model to construct the mathematical model to do the location choice. There are two different decision levels. The decision maker in upper level is primary company and the objection function is how to minimum cost of

38 

opening stations and opportunity cost of available capacity. The decision maker in lower level is each station and objection function is how to minimum the operational cost.

Brotcoren et al.(2000) use bi-level programming model in to the problems of setting freight fares. Upper level has a group of competitive freight carriers, and the profit comes from total fares. Lower level is a specific freight consignor and achieve the goal of how to minimum ship cost.

Huang et al.(2006) take advantage of genetic algorithm and geographic information system (GIS) to solve the multi objective traveling salesman problem. The TSP problem in past, only consider minimum travel cost, travel distance and travel time. However, Huang et al.(2006) take advantage the route planning about tourism, and the route is planned by four traveler business in specific area. And the route planning includes four criteria： travel time, the cost of vehicle operational, safety and the quality of the sightseeing. And upper level decides the weight of each criterion; lower level decides the optimal tourism route by the weight from upper level. And four criterions furthermore quantitative by GIS and evaluate the cost of each route link to find the optimal solution.

39 

Table 2.8 literature review about bi-level programming model

Authors/year Research Objectives Models Algorithm solution

Brotcoren (2000) International freight shipping

 Upper level：

Maximum the benefit from freight shipping of freight company

 Lower level：

Minimum the shipping cost from freight consignor

Heuristics algorithms

Chen H.K. (2004) Dynamic signal control system

 Upper level

Minimum system travel time  Lower level

User equilibrium model with Variational Inequalities

 Sensitive analysis with Variational Inequalities  Generalized Inverse

Approach

Cao and

Chen (2006) Location choice

 Upper level

Minimum cost of opening stations and opportunity cost of available capacity.

 Lower level

Minimum the operational cost.

 Bi-level  single-level  non-linearity

linearity

Huang et al. (2006)

Multi-objective travel salesman problem

 Upper level

Decide the weight of each criterion  Lower level

Decide optimal tourism route

 Generic algorithm  Geographic