共享汽車運具服務已潛移默化地深入民眾的日常生活，漸漸成為民眾出行的選擇方式。儘管探討共享汽車屬性研究之文獻數量不斷地出現，不過這些研究的努力大多數均專注於使用者特性或單一共享汽車運具的研究。但在網約車服務逐步霸佔融合傳統計程服務；汽車共享漸入民眾視野後，是否影響民眾對於出行運具的選擇方式的轉變是一大課題。
本研究使用敘述性偏好法探討生活出行的上海與杭州地區的民眾對於現今之行之有年的網約車及逐步發展的汽車共享之偏好，並進一步鎖定最常使用運具外出之18歲以上進入社會工作的民眾。本研究另並探討現今使用者於買車意願的不同想法對於其偏好的影響。
根據本研究結果顯示，「使用距離與使用成本」、「取車便利性」、「停車便利性」及「城市有無限行政策」都為屬性變數中影響最為顯著的部分，而對於擁有自有車輛的民眾而言，其對城市有無限行政策無感，但更為在意於停車之便利程度。另外，具有共享運具使用經驗之用戶更願意在住家附近進行共享出行旅程，本研究亦發現社會經濟變數對於模型之影響程度，如收入、年齡、學歷、買車意願等方案特定變數。透過建構偏好模型，藉希望了解民眾在意的變數因子，以使未來能更精確地反應民眾的出行偏好。

Vehicle sharing services gradually synchronise with daily life by osmosis and become an alternative to travel. Albeit the number of research and documents focusing on the relevant issues consecutively emerges, a myriad of efforts contributes to understanding personal features or only coping with a specific vehicle. However, while ridesoucing services are capable of providing traditional and innovative services to customers, the impact of sharing services inseparable from the public begets an issue that how the novel services affect the way people travel.
This research utilizes a narrative preference method to explore the preferences of people who commute in daily life in Shanghai and Hangzhou. Those who above 18-year-old and having working experience are the testing subjects. This research discusses the interplay between the intention of purchasing a vehicle and customers’ preferences.
Pursuant to the results, distance and cost, availability of hailing, accessibility of parking, and the limitation of speed in a city make a huge and significant influence on the level of customer acceptance. However, for those who possess private vehicles, they are not sensitive to road space rationing, but more concerning the accessibility of parking. Furthermore, customers with experience in using shared vehicles are more willing to make a second attempt in the vicinity of their residences. This research also carries out efforts to analyse socioeconomic variables, including incomes, ages, education, and willingness to pay, and, by constructing a preference model, this research is able to identify factors that make a huge influence on people’s decisions. A model enabling researchers to measure people’s preferences more accurately is proposed.

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