小汽車共乘起源於因應1970 年初的石油危機，為常見的都市運輸需求管理策略之一，其優勢在於善用小汽車空位以改善交通。國內相關共乘研究以探討小汽車共乘的推行可能性以及共乘配對演算法為主，尚無針對國內小汽車共乘族群及路線特性的研究，且小汽車共乘相較於其他運輸工具的市場定位也不明確，往往在政策規劃與制定中被遺漏。
本研究利用全臺最大規模的資訊平台（桃北北宜基共乘網資料庫）進行分析，包含潛在共乘者特性與路線特性兩類，以人文與地理為基礎作市場區隔，並以潛在共乘者平日使用運具了解目標市場，之後將共乘資料庫結合城際運輸模式的旅運資料，探討不同共乘路線之運具方案間的選擇彈性，做為市場定位依據。研究結果顯示：
1. 小汽車共乘的潛在族群以 26-35 歲從事服務業、科技業、製造業為主的男性。
2. 高達 65%的共乘路線旅行時間在30 至60 分鐘，且平均發生在一周內的每個工作日，可判斷共乘主要的市場為城際通勤旅次。
3. 小汽車共乘主要發生在人口密度較低、自行開車較普遍的地區，未來可選擇與都市互動較頻繁的市郊或郊區優先推動。
4. 根據選擇彈性定位分析，小汽車共乘的旅行時間屬性與自行開車相近，而旅行成本屬性偏向費用較低廉的大眾運輸，因此定位為兼具時間與成本競爭力的副大眾運輸，宜持續推動。

Carpooling can be traced back to the oil crisis at 1970s. Taking advantage of vacant seats to reduce private vehicle traffic, carpooling is a commonly seen strategy of urban
transportation demand management. Prior studies primarily focused on the feasibility of carpooling or ridematching algorithms, leaving the characteristics of carpoolers and
carpool routes unclear. Also, carpool is usually neglected in transportation policy making due to the non-identified market positioning.
This study retrieved the database of New Taipei City’s Green Carpool Website－the largest carpool information platform in Taiwan. The characteristics of potential carpoolers and carpool routes were explored as the demographic and geographic basis of market segmentation. Then the market target was identified by analyzing the commuting modes for potential carpoolers. Combining the carpool database and the Intercity Transportation
Demand Model formed the choice analysis that revealed the elasticity and positioning of different modes, including carpooling. The findings show that:
1.Majority of the potential carpoolers were aged 26 to 35 years old in the service, technology, and manufacturing industries.
2.Up to 65 percent of the carpool routes had travel time between 30 to 60 minutes in each weekday, indicating the market for carpool is primarily intercity commuting.
3.Carpool demand tended to arise in the low populated area where most people drove alone. Suburban or rural areas with fairly strong connections to cities can be the target
for carpool campaign.
4.According to the elasticity positioning analysis, carpooling and driving alone had similar attributes of low travel time, while carpooling and mass transit had similar
attributes of low travel costs. Carpooling can be positioned as temporally and monetarily competitive para-transit that is worth promoting.

目錄
中文摘要
英文摘要
目錄
圖目錄
表目錄
一、緒論	1
1.1研究背景與動機	1
1.2研究目的	2
1.3研究範圍與對象	2
1.4研究流程	2
二、文獻回顧	4
2.1共乘定義與型態	4
2.2小汽車共乘特性	9
2.3 市場定位	12
2.4小結	15
三、研究架構與模式理論	17
3.1共乘成員與路線分析	17
3.2市場定位	19
四、共乘分析	25
4.1資料形態與限制	26
4.2會員成長與分布趨勢	27
4.2潛在共乘使用者特性	29
4.3路線特性	34
4.4起迄點對應關係	39
4.5行政區劃別	44
4.6共乘路線方向性	48
4.7小結	56
五、市場定位	58
5.1樣本基本資料	58
5.2離散選擇模式	60
5.3選擇彈性定位法	62
5.3.1 Cooper所定義之市場定位指標	63
5.3.2 Kamakura & Russell所定義之市場定位指標	64
5.3.3 競爭圖像	65
5.4小結	68
六、結論與建議	70
6.1結論	70
6.2建議	72
參考文獻	74
附錄：不同巢層分類下之選擇模式結果	80

圖目錄
圖1.1 使用者特性與路線研究流程圖	3
圖2.1 共乘行為架構圖 (資料來源：Nelson and Shaheen 2012)	6
圖3.1 目標行銷三步驟 (S: segmentation, T: target, P: position)	13
圖3.1 共乘成員與路線分析流程圖	17
圖3.2 市場定位流程圖	19
圖3.3 巢式羅吉特架構圖	20
圖4.1 桃北北宜基共乘網發展關鍵	25
圖4.2 桃北北宜基共乘網流程架構圖	26
圖4.3 桃北北宜基共乘網成長趨勢	28
圖4.4 原油價格與每月註冊人數趨勢圖	28
圖4.5(a) 縣市別會員註冊總數       圖4.5(b) 縣市別每十萬人會員註冊數	30
圖4.6 年齡性別比例圖	31
圖4.7 桃北北宜基共乘網會員歷年運具使用比例	32
圖4.8 運具組成比對直條圖	33
圖4.9 職業別運具比例	33
圖4.10小汽車共乘頻率年齡比例分布圖	36
圖4.11 路線刊登次數比例圖	36
圖4.12 旅行時間比例分布圖	37
圖4.13 旅行距離比例分布圖	37
圖4.14 小汽車共乘路線起迄散布圖	39
圖4.15 起迄點集群分析散布圖	40
圖4.16 小汽車共乘路線起迄點散布比例圖	41
圖4.17 各集群內起點城市比例圖	42
圖4.18 各集群內迄點城市比例圖	42
圖4.19(a) 小汽車起點累積次數圖(2013) 4.19(b) 小汽車迄點累積次數圖(2013)	44
圖4.20 鄉鎮市區別起點累積數	45
圖4.21 累積路線起點次數排名	46
圖4.22 鄉鎮市區別迄點累積數	47
圖4.23 累積路線迄點次數排名	47
圖4.24 以桃園為起點之共乘路線次數圖	49
圖4.25 以桃園為起點之共乘路線次數長條圖	49
圖4.26 以臺北市為起點之共乘路線次數圖	50
圖4.27 以臺北市為起點之共乘路線次數長條圖	50
圖4.28 以臺北市為迄點之共乘路線次數圖	51
圖4.29 以臺北市為迄點之共乘路線次數長條圖	51
圖4.30 以新北市為起點之共乘路線次數圖	52
圖4.31 以新北市為起點之共乘路線次數長條圖	52
圖4.32 以新北市為迄點之共乘路線次數圖	53
圖4.33 以新北市為迄點之共乘路線次數長條圖	53
圖4.34 以宜蘭為起點之共乘路線次數圖	54
圖4.35 以宜蘭為起點之共乘路線次數長條圖	54
圖4.36 以基隆為起點之共乘路線次數圖	55
圖4.37 以基隆為起點之共乘路線次數長條圖	55
圖4.38 小汽車共乘潛在市場	57
圖5.1 巢式羅吉特結構圖	61
圖5.2 Cooper所定義之市場競爭結構(旅行成本)	65
圖5.3 Cooper所定義之市場競爭結構(旅行時間)	66
圖5.4 Kamamura & Russel所定義之市場競爭結構(旅行成本)	66
圖5.5 Kamamura & Russel所定義之市場競爭結構(旅行時間)	66

表目錄
表2.1 共乘路線型態表	8
表2.2 小汽車共乘特性表	16
表4.1 油價與註冊人數、路線數相關檢定	29
表4.2 潛在共乘使用者特性表	31
表4.3 小汽車共乘路線特性表	35
表4.4 桃北北宜基人口密度(人/km2)前七行政區	40
表4.5 各集群最後集群中心點	41
表4.6 各集群對應之運具組成表	42
表4.7 潛在的小汽車共乘特性表	56
表5.1 有效樣本樞紐分析表	59
表5.2 各方案隨機抽樣數	60
表5.3 離散選擇模式參數估計結果	61
表5.4 旅行成本選擇彈性表	62
表5.5 旅行時間選擇彈性表	62

1.	交通部統計處（2011，2009，2007），自用小客車使用狀況調查摘要分析。

2.	曾國雄（1988），合租共乘Vanpool與合車共乘Carpool在臺灣區之可行性，都市交通，30，10-22。

3.	張有恆（1994），都市公共運輸，臺北：華泰。

4.	陳俞如（2008），高雄都會區大專院校教職員參與共乘之影響因素探討，國立中山大學公共事務管理研究所。

5.	楊志文（2003），考慮選擇集合、市場定位及個體異質性之城際客運選擇模式，國立成功大學交通管理科學研究所。

6.	交通部運輸研究所（1990），推動小客車共乘制度策略研究與示範計畫之研擬，交通部運輸研究所。

7.	交通部運輸研究所（2012），第5期整體運輸規劃研究系列-城際運輸需求模式檢討及參數更新研究，交通部運輸研究所。

8.	鍾智林（2007），由加州經驗展望臺灣地區共乘制度之推動，都市交通，22(1)，50-63。

9.	顏鴻祥（2009），影響小汽車共乘行為因子之研究—以新竹市地區為例，國立交通大學運輸科技與管理研究所。

10.	AASHTO (2013). Commuting in America 2013. American Association of State Highway and Transportation Officials, Washington D.C..

11.	Bukold, S., Hager, W., Olsen, H., van Bodegom, W. (1996). The State of European Infrastructure 1996. European Centre for Infrastructure Studies, Rotterdam, Netherlands.

12.	Brownstone, D., Golob, T.F. (1992). The effectiveness of ridesharing incentives: discrete-choice models of commuting in Southern California. Regional Scienceand Urban Economics 22(1), 5-24.

13.	Bruggeman, J. M., Rubin, R.B., Griffiths, F. (1977). Findings of a study to estimate the effectiveness of proposed carpool incentive policies. Transportation Research Record 650, 36-43.

14.	Calvo, R. W., Luigi, F. L., Haastrup, P., and Maniezzo, V. (2004). A distributed　geographic information system for the daily car pooling problem. Computers & Operations Research, 31, 2263-2278.

15.	Chung, C. L., Yeh, C. C. (2011). Cooperative Relationships between Environmental, Energy, and Transportation Departments on Promoting Ride Sharing in Taiwan. ICTPA 24th Annual Conference, Irvine, California.

16.	Chung, C., Jeng, J., Lee, Z., and Lee, J. (2012). Study of Carpool User Behaviors and Route Characteristics in Taiwan. Sustainable Transportation Systems, 356-363.

17.	Concas, S., Winters, P. L. (2007). The impact of carpooling on trip chaining behavior and emission reductions. In: Proceedings of the Transportation Research Board 86th Annual Meeting, Washington, DC.European Centre for Infrastructure Studies, Rotterdam,Netherlands.
18.	Cooper, L. G. (1988). Competitive maps: the structure underlying asymmetric cross elasticities, Management Science, 34 (6), 707-723.

19.	Dailey, D. J., Loseff, D. and Meyers, D. (1999). Seattle smart traveler: dynamic ridematching on the World Wide Web, Transportation Research Part C, 7(1), 17–32.

20.	Duecker, K. J., Bair, B. O., Levin, I. P. (1977). Ride sharing: psychological factors. Transportation Engineering Journal of ASCE, 103(6), 685-692.

21.	Ferguson, E. (2000). Travel Demand Management and Public Policy. Ashgate,　Aldershot, UK.

22.	Ferrari, E., Manzini, R., Pareschi, A., Persona, A., and Regattieri, A. (2003). “The car pooling problem: heuristic algorithms based on savings functions” Journal of Advanced Transportation, 37, 243-272.

23.	Frank, S. K., Chandra R., & Joseph L. S. (1992). Market Research Evalution of　Actions to Reduce Suburban Traffic Congestion: Commuter Travel　Behavior and Response to Demand Reduction Actions. U.S.A:University of Northwestern, Department of Civil Engineering. 

24.	Gilbert, R., Perl, A. (2008). Transport Revolution. Moving People and Freight　without Oil. Earthscan, London, UK.

25.	Giuliano, G., Levine, D.W., Teal, R.F. (1990). Impact of high occupancy vehicle lanes on carpooling behavior. Transportation, 17(2), 159-177.

26.	Jonathan, H., Bento, A., Kaffine, D. (2013). Carpooling and Driver Responses to Fuel Price Changes: Evidence from Traffic Flows in Los Angeles. Journal of Urban Economics, 77, 41-56.

27.	Hunt, J. D., McMillan, J. D. P. (1997). Stated-preference examination of attitudes toward carpooling to work in Calgary. Transportation Research Record 1598, 9-17.

28.	International Energy Agency (1997). Indicators of Energy Use and Efficiency  Understanding the Link between Energy Use and Human Activity. 

29.	Kostyniuk, L. P. (1982). Demand analysis for ridesharing: state-of-the-art review. Transportation Research Record 876, 17-26.

30.	Kotler, P. (1997), Marketing Management: Analysis , Planning ,Implementation and Control, 9th ed., New Jersey , Prentice Hall.

31.	Margolin, J., Misch, M. R., Stahr, M. (1978). Incentives and disincentives of ridesharing. Transportation Research Record 673, 7-15.

32.	McFadden, D. (1973), Conditional logit analysis of qualitative choice behavior, In:Zaremmbka, P. (Ed.), Frontiers in Econometrics, Academic Press, New York.

33.	Nelson, D. Chan & Susan A. Shaheen (2012). Ridesharing in North America: Past, Present, and Future, Transport Reviews, 32(1), 93-112.

34.	Richardson, A. J., & Young, W. (1981). Spatial Relationships between Carpool　Members’s Trip Ends. Transportation Research Record, 823, 1-7.
35.	Rietveld, P., Zwart, B., van Wee, B., & van den Hoorn, T. (1999). On the relationship between travel time and travel distance of commuters – reported versus network travel data in the Netherlands. Annals of Regional Science, 33, 269-287.

36.	Roger, F. T. (1986). Carpooling: Who, How, and Why. U.S.A: University of　California, Department of Civil Engineering and Institute of Transportation Studies.

37.	Russell, G. J., and Bolton, R. N. (1988), Implications of market structure for elasticity structure, Journal of Marketing Research, 25, 229-241.

38.	Schrank, D., Lomax, T. (2005). The 2005 Urban Mobility Report. Texas Transport Institute, Houston.

39.	Shaheen, S. A., Sperling, D., Wagner, C. (1999). Carsharing and partnership management: an international perspective. Transportation Research Record 1666, 118-124.

40.	Shoup, D. C. (1997). Evaluating the effects of cashing out employer-paid parking: eight case studies. Transport Policy 4, 201-216.

41.	Stephen, A., Duecker, K. (1974). Attitudes toward and Evaluation of Carpooling. Institute of Urban and Regional Research, University of Iowa.

42.	Teal, R. F. (1987). Carpooling: who, how and why. Transportation Research Part A 21(3), 203-214.

43.	Vanoutrive, T., Van, D. V. E., Van, M. L., Jourquin, B., Thomas, I., Verhetsel, A., Witlox, F. (2012). What determines carpooling to workplaces in Belgium: location, organisation, or promotion? Journal of Transport Geography, 22, 77-86.

44.	WS DOT (2007). HOV User Survey. Washington State Depart of Transportation.