跳到主要內容

臺灣博碩士論文加值系統

(3.229.142.104) 您好!臺灣時間:2021/07/30 15:54
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果 :::

詳目顯示

我願授權國圖
: 
twitterline
研究生:王君如
研究生(外文):Chun-Ju WANG
論文名稱:活動停留對於運具選擇影響之研究-以新竹科學園區為例
論文名稱(外文):The Impact of Stop-Making on Commute Mode Choice - An Empirical Analysis
指導教授:高凱高凱引用關係
指導教授(外文):Kao Kai
學位類別:碩士
校院名稱:國立交通大學
系所名稱:運輸科技與管理學系
學門:運輸服務學門
學類:運輸管理學類
論文種類:學術論文
論文出版年:2007
畢業學年度:95
語文別:中文
論文頁數:66
中文關鍵詞:運具選擇活動停留二元羅吉特活動基礎分析
外文關鍵詞:mode choicestop makingbinary logitactivity based analysis
相關次數:
  • 被引用被引用:4
  • 點閱點閱:164
  • 評分評分:
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
繁忙的都市生活,多數通勤者會考慮時間限制、方便性、接送小孩的責任等種種因素,在個人效用極大的情況下,將通勤旅程分為數個旅次完成。過去二、
三十年,在以活動為基礎的旅運分析中,已經發現通勤者在通勤過程中會有活動停留的行為,近年來,國外開始有些研究結合通勤者活動停留的行為及運具選擇。

在本研究中欲利用台灣的實證分析,驗證以下幾點: (1)通勤者的活動停留行為是否與社經背景相關;(2)活動停留與運具選擇間是否具有因果關係;(3)慣性是否會影響通勤者考慮運具使用時的決策;(4)私人運具使用率的偏高是否與大眾運輸旅行時間的可靠性較低有關。為了驗證研究目的,利用活動基礎分析建立通勤者運具選擇模式,將替選方案區分為私人運具及大眾運輸兩種。針對新竹科學園區的通勤者,透過網路及面訪,蒐集得到401份有效問卷,再以二元羅吉特為分析方法,透過LIMDEP軟體對於模式的結果進行探討。

透過實證的結果發現,婚姻及家戶結構對於通勤者是否停留具有明顯的相關,尤以家中有小孩者更為顯著。有關於活動停留的解釋變數,可發現停留天數越多時,越不願意使用大眾運輸,而傾向於使用私人運具。由於通勤者時間上的限制,當通勤途中須停留的持續時間越長,則通勤者為了便利會傾向於使用私人運具。此外通勤者容易受到私人運具的方便性所吸引而習慣使用私人運具,對於大眾運輸的使用較難養成慣性。而在旅行時間可靠性變數中顯示,大眾運輸準確程度及對運具的掌握程度越差,通勤者會選擇使用私人運具。
Most commuters select the travel pattern which derives the maximized utility subject to time and money budget constraints, scheduling convenience and parent responsibility in the busy city life. In other words, the commute tour may be divided into several trips. In the past decades, some activity-based studies detected that a larger number of stops will have a higher degree of separation of activities. These activities are associated with a higher utility. In recent years, some studies start to investigate the relationship between stop-making behavior and mode choice of individuals.
In this study, we consider the impacts of commute stop-making as well as commute travel time reliability on commute mode choice. In Taiwan, we would like to figure out following points based on the empirical analysis, as (1) the relationship between commuter’s stop-making behavior and his/her background; (2) causal relationship between stop-making and mode choice; (3) how could inertia affect the mode choice decision; (4) is lower public mode reliability causing a higher private mode usage. We adopted a survey approach to collect information from Hsinchu Science Park commuters. The complete sample consists of 401 individuals and it uses binary logit framework method to estimate. Furthermore, the commercial software package LIMDEP was used to calibrate parameters.
The results are: (1) Commute stop-making does have an effect on mode choice. (2) Travel time reliability is an important variable in commute mode choice decisions. (3) Household structure significantly influences the activity and travel patterns of commuters. (4) Furthermore, it is hard to change the habit of commute mode, especially from private to public mode.
目 錄
表目錄.....................................II
圖目錄.....................................V
第一章 緒論............................1
1.1研究背景與動機............1
1.2研究目的與研究架構....2
1.3研究範圍及對象............4
1.4 研究方法及進行步驟...4
第二章 文獻回顧....................7
2.1 旅次鏈與活動停留行為.........................................7
2.2旅行時間可靠性..........15
2.3運具選擇理論..............20
第三章 通勤者運具選擇模式之建立...........................27
3.1 通勤方式定義..............27
3.2 家戶結構分類……......27
3.3 研究變數說明……......29
3.4 通勤者運具選擇模型建立....................................33
第四章 資料蒐集與分析......38
4.1園區大眾運輸………………….............................38
4.2問卷設計………………….....................................39
4.3 抽樣設計與資料蒐集…………………................39
4.4 樣本結構分析……………....................................41
第五章 模式驗證結果….....49
5.1大眾運輸與私人運輸之屬性差異.........................49
5.2 解釋變數與一周停留天數之交叉分析................50
5.3 旅行時間可靠性變異數分析................................52
5.4 變數間相關分析…………....................................52
5.5 二元羅吉特分析……………................................53
第六章 結論與建議..............60
6.1 研究結論......................60
6.2 限制與後續研究之建議........................................60
參考文獻..................................62
附錄67
中文文獻:
1. 95年行政院勞工委員會統計資料庫查詢
(http://www.cla.gov.tw/cgi-bin/SM_theme?page=450f92d3)
2. 王郁珍,「新運具運量預測方法之研究」,國立成功大學,碩士論文,民國84年。
3. 周榮昌,「旅次鏈對都市通勤者行為影響之研究」,中華民國運輸學會第十屆論文研討會論文集,第四冊,民國84年。
4. 林卓漢,「捷運到站運具選擇模式之研究」,國立臺灣大學,碩士論文,民國89年。
5. 唐富藏,張有恆,「台北都會區大眾捷運系統運輸工具之評估與選擇」,經濟論文期刊,六卷二期,中央研究院經濟研究所,民國67年。
6. 寇世傑,「實施共乘計程車對旅運者行為之影響—以統聯中港轉運站為例」,逢甲大學,碩士論文,民國84年。
7. 張有恆,「改善都市大眾運輸系統服務可靠性之策略」,運輸計畫季刊運輸季刊第13卷第二期,民國73年。
8. 許書耕,「公路收費站區位與站數決策之分析模式」,國立交通大學,碩士論文,民國81年。
9. 曾華聰,「以敘述性模糊偏好個體模式探討捷運系統木柵線營運後之運具選擇行為」,國立交通大學,碩士論文,民國84年。
10. 馮正民,王基洲,康照宗,「以可靠度觀念分析捷運乘客對行車延誤之可忍受度」,運輸計畫季刊,第三十二卷第二期,民國92年。
11. 謝貴祥,「以旅次鏈探討臺灣城際間運具選擇之研究」,國立成功大學,碩士論文,民國84年。
12. 鍾志成,「屬性門檻多項羅吉特模式之研究」,國立交通大學,碩士論文,民國78年。


英文文獻:
1. Adler. T., Ben-Akiva. Moshe, “A Theoretical and Empirical Model Of Trip Chaining Behavior,” Transportation Research B, 13, 243-257, 1979.
2. Anas. A., C. Chu., “Discrete Choice Models and the Housing Price and Travel to Work,” Elasticities of Location Demand, Journal of Urban Economics, 15, 107-123, 1984.
3. Bates. J., Polak. J., Jones. P., Cook. A., “The valuation of reliability for personal travel,” Transportation Research E, 37 (2-3), 191-229, 2001.
4. Ben-Akiva, Lerman, Discrete Choice Analysis: Theory and Application to Travel Demand, The MIT Press, 1985.
5. Bhat, C.R., “Accommodating variations in responsiveness to level-of-service variables in travel mode choice modeling,” Transportation Research A, 32 (7), 495-507, 1998.
6. Bhat, C.R., “An analysis of evening commute stop-making behavior using repeated choice observations from a multi-day survey,” Transportation Research B, 33 (7), 495-510, 1999.
7. Bhat, C.R., “Austin commuter survey: findings and recommendations. Technical Report,” Department of Civil, Architectural and Environmental Engineering, The University of Texas at Austin, 2004.
8. Bhat, C.R., “Simulation estimation of mixed discrete choice models using randomized and scrambled Halton sequences,” Transportation Research B, 37, 2003.
9. Bhat, C.R., “Work travel mode choice and number of non-work commute stops,”
Transportation Research B, 31 (1), 41-54, 1997.
10. Bhat, C.R., Saul Castelar., “A unified mixed logit framework for modeling revealed and stated preferences: formulation and application to congestion pricing analysis in the San Francisco Bay area,” Transportation Research B, 36, 2002.
11. Bhat, C.R., Singh, S.K., “A comprehensive daily activity-travel generation model system for workers,” Transportation Research A, 34 (1), 1-22., 2000.
12. Bhat, C.R., Zhao, H., “The spatial analysis of activity stop generation,” Transportation Research B, 36 (6), 557-575., 2002.
13. Black I.G., Towriss J.G., Road Pricing in London: Demand Effects of Travel Time Reliability, UK Department of Transport, HMSO, London, 1993.
14. Brownstone, D., K. A. Small., “Valuing Time and Reliability: Assessing the Evidence from Road Pricing Demonstrations,” Transportation Research A, 39, 4, 279-293, 2005.
15. Chang X.B., Stopher P.R., “Defining the perceived attributes of travel modes for urban work trips,” Transportation Planning and Technology, 7 (1), 55-65, 1981.
16. Cosslett S., “The trip timing decision for travel to work by automobile,” in D. McFadden et al., Demand Model Estimation and Validation, The Urban Travel Demand Forecasting Project, University of California, Berkeley, 201-221, 1977.
17. De Palma, Denis Rochat., “Mode choices for trips to work in Geneva: an empirical analysis,” Journal of Transport Geography, 8, 43-51, 2000.
18. Fujii S, Gärling T., Kitamura R., “Changes in drivers’ perceptions and use of public transport during a freeway closure: Effects of temporary structural change on cooperationin a real-life social dilemma,” Environment and Behaviour, 33, 796- 808, 2001.
19. Fujii S., Kitamura R., “What does a one-month free bus ticket do to habitual drivers? An experiental analysis of habit and attitude change,” Transportation, 30, 81-95, 2003.
20. Gärling T, Fujii S., Boe O., “Empirical tests of a model of determinants of script-based driving choice,” Transportation Research F, 4, 89-102, 2001.
21. Garling. T., Axhausen. K. W., “Introduction:Habitual travel choice,” Transportation, 30, 1-11, 2003.
22. Gaver, D.P., “Headstart strategies for combating congestion,” Transportation Science, 2(3), 172-181, 1968.
23. Golob, T., “A nonlinear canonical correlation analysis of weekly trip chaining behavior,” Transportation Research A, 20 (5), 385-399, 1986.
24. Golob, T.F., “Joint Models of Attitudes and Behavior in Evaluation of the San Diego I-15 Congestion Pricing Program,” Transportation Research A, 35, 495-514, 2000.
25. Golob, T.F., E.T. Canty, R.L. Gustafson and J.E. Vit., “An Analysis of Consumer Preferences for a Public Transport System,” Transportation Research, 6, 1, 81-102, 1972.
26. Golob, T.F., R. Kitamura and C. Lula., “Modeling the Effects of Commuting Time on Activity Duration and Non-Work Travel,” Transportation Research Board, Washington, DC, January 1994.
27. Hägerstrand T., “What about people in regional science,” Papers of the Regional Science Association, 24, 7-21, 1970.
28. Hamed M.M., Olaywah H.H, “Travel-related decisions by bus, servis taxi, and private car commuters in the city of Amman,” Jordan, 17, pp. 63-71(9), February 2000.
29. Hanson S., Huff J. O, “Repetition and day-to-day variability in individual travel patterns: implication for classification Behavioural Modelling in Geography and Planning,” pp. 368-398 in: R. G. Golledge and H. J. P. Timmermans (Eds).
30. Hensher, D.A., Reyes, A.J., “Trip chaining as a barrier to the propensity to use public transport,” Transportation, 27 (4), 341-361, 1988.
31. Jackson, B.W., J.V. Jucker., “An Empirical Study of Travel Time Variability and Travel Choice Behavior,” Transportation Science, 16, 460-475, 1981.
32. Jane Lappin, Jon Bottom., “Understanding and Predicting Traveler Response to Information: A Literature Review,” U.S. Department of Transportation Research and Special Programs Administration, 2001.
33. Kitamura R., “Incorporating chaining into analysis of destination choice,” Transportation Research B, 18, 1, pp.67-81, 1984.
34. Kitamura R., “Review Paper: An evaluation of activity-based travel analysis,” Transportation, 15, 9-34, 1988.
35. Kitamura R., J. Robinson, T.F. Golob, M. Bradley and T. van der Hoorn., “A Comparative Analysis of Time Use Data in the Netherlands and California: Effects of Commute Times and Store Operating Hours on Travel and Activity Patterns,” Proceedings of Seminar E, 20th PTRC Summer Annual Meeting PTRC Education and Research Services Ltd., London, 127-138, 1992.
36. Kitamura R., L.P. Kostyniuk, M.J. Uyeno., “Basic properties of urban time-space paths: empirical tests,” Transportation Research Record, 794, 8-19, 1981.
37. Kitramura R, Chen C, Pendyala RM., “Generation of synthetic daily activity-travel patterns,” Transportation Research Record, 1607, 154-162, 1997.
38. Kuppam AR., Pendyala RM., “A Structural Equations Analysis of Commuters' Activity and Travel Patterns,” Transportation, 28, 33-54, 2001.
39. Lam T. C., Small K. A., “The Value of Time and Reliability: Measurement from a Value Pricing Experiment,” Transportation Research E, 37, 2, 231-251, 2001.
40. Liao Y. C., “Trip chaining in Urban Travel,” University of Southern California, Ph.D Dissertation, 1997.
41. Lomax T., Schrank D., Turner S., R. Margiotta., “Selectng Travel Reliability Measures,” Transortation Institiute and Cambridge Systematics, Inc., 2003.
42. Mahmassani H. S., G.L. Chang., “Experiments with Departure Time Choice Dynamics of Urban Commuters,” Transportation Research B, 20(4), 297-320, 1986.
43. Mannering F., Clifford Winston, “A Dynamic Empirical Analysis of Household Vehicle Ownership and Utilization,” The Rand Journal of Economics, 16, 2, 215-236, 1983.
44. Mannering F.L., “Econometric analysis of vehicle use in multivehicle households,” Transportation Research A, 17, 3, 183-189, 1983.
45. McFadden D., “The Mathematical Theory of Demand Models,” Stopher and Meyburg (eds.), Behavioral Travel Demand Models, 305-314, D.C.Heath and Co. Lexington, MA., 1976.
46. McFadden. D., “Disaggregate Behavioral Travel Demand’s RUM Side. A 30-Year Retrospective,” http://elsa.berkeley.edu/users/mcfadden/iatbr00.html.
47. Neveu A.J., Koppelman F.S. and Stopher P. R., “Perceptions of comfort, convenience and reliability for the work trip,” Transportation Research Record, 723, 59-63, 1979.
48. Nicholson A., Schmocker J., and M. Bell, “Assessing Transport Reliability: Malvolence and User Knowledge,” In M.G.H. Bell and Yasunori Iida (eds.), The Network Reliability of Transport: Proceedings of the 1st International Symposium on Transportation Network Reliability. Pergamon: Elsevier Science Ltd., 2003.
49. Noland R.B. and J.W. Polak, “Travel Time Variability: A Review of Theoretical and Empirical Issues,” Transport Reviews, 22, 1, 39-54, 2002.
50. Noland, R.B., Small, K.A., Koskenoja, P. and X. Chu., “Simulating Travel Reliability,” Regional Science and Urban Economics, 28, 535-564, 1998.
51. Noland,R.B., Small,K.A., “Travel time uncertainty, departure time and the cost of the morning commute,” Paper presented to the 74th Annual Meeting of the Transportation Research Board, Washington., 1995.
52. Pas, E.I., “The effects of selected sociodemographic characteristics on daily travelactivity behavior,” Environment and Planning A, 16, 571-581, 1984.
53. Polak,J.W., “Travel time variability and departure time choice: a utility theoretic approach,” Discussion Paper 15, Transport Studies Group, University of Westminster(previously Polytechnic of Central London), 1987.
54. Robinson, J.P., How American Use Time, A social-Psychological Analysis of Everyday Behavior, Praeger Publishers, New York, 1977.
55. Rutherford, G., Scott, Edward Mccormack, and Martina Wilkinson, Travel Impacts of Urban Form: Implications From An Analysis of Two Seattle Area Travel Diaries, 1987.
56. Sardesai Rupali and Bhat C.R. “The impact of stop-making and travel time reliability on commute mode choice,” Transportation Research B, 709-730, 2006.
57. Small, K. A., R. Noland, X. Chu and D. Lewis, “Valuation of Travel-Time Savings and Predictability in Congested Conditions for Highway User-Cost Estimation,” Report 431, National Cooperative Highway Research Program, 1999.
58. Small, K.A., “The Scheduling of Consumer Activities: Work Trips,” American Economic Review, 72, 467-479, 1982.
59. Small, K et al., “Valuation of travel-time savings and predictability in congested conditions for highway user-cost estimation,” Transportation Research Board, US National Research Council, 2000.
60. Triandis, H. C., “Interpersonal behavior,” Monterey, CA: Brooks/Cole., 1977.
61. Vadarevu, R. V. and P. R. Stopher., “Household activities, life cycle, and role allocation,” Transportation Research Record, 1556, pp.77-85, 1996.
62. Verplanken B, Aarts H, van Knippenberg A & van Knippenberg C., “Attitude versus general habit: Antecedents of travel mode choice,” Journal of Applied Social Psychology, 24, 285-300, 1994.
63. Wheeler, J. O., “Trip purposes and urban activity linkages,” Annals of the Association of American Geographers, 62, 4, pp.641-654, 1972.
64. Yang, H., Ka Kan Lo, and W. Tang., “Travel Time versus Capacity Reliability of a Road Network,” In M.G.H. Bell and C. Cassir (eds.), Reliability in Transport Networks. Hertfordshire: Research Studies Press, 2000.
65. Ye, X., Pendyala, R.M., Gottardi, G., “An exploration of the relationship between mode choice and complexity of trip chaining patterns,” Presented at the 83rd Annual Meeting of the Transportation Research Board, Washington, DC, 2004.
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top