電動機車使用特性與購買行為之研究

Abstract

近年來國內各大都市因汽機車數量急遽增加，致使空氣及噪音污染 日益嚴重，發展低污染、低噪音之電動機車為改善都市內污染之一帖良方 。然而電動機車為一嶄新之產品， 目前市場上之使用者極為稀少，未來 若成功推廣，消費者使用與廠商提供服務均可能發生一些無法預知之狀況 ，本研究藉由訪查已有實際騎乘經驗之電動機車車主，以確實明瞭其 使 用狀況。本研究並以敘述性偏好法(Stated Preference Method)設計問卷 ，向一般民眾 及電動機車車主進行調查，以作為構建個體選擇模式( Discrete Choice Models)之依據，為了克服傳統可補償性模式( Compensatory Models)高估效用的情形，將門檻值納入個體選擇模式，並 估算消費者購車決策屬性之門檻值，以作為研擬電動機車推廣策略之參考 。研究結果顯示使用者對電動機車之爬坡能力、續航力、充電時間、殘存 電量顯示可靠度等屬性之評價為不滿意，對於維修地點之方便性亦感到不 滿意，電動機車較常維修保養之項目為電池、充電器與控制器，由此可見 欲成功地推廣電動機車，提昇電池性能與其維修之方便性該是十分重要之 課題。在個體選擇模式方面，引入檻值之模式校估結果以非線性屬性門檻 值模式(Non-linear Attribute Thresholds Logit Models)之預測能力最 佳，且屬性門檻值模式(Attribute Thresholds Logit Models)皆優於羅 吉特模式(Logit Models )。 In recent years, the numbers of vehicle in big cities of our country are increasing, so the air and noise pollution are getting more and more worse. Therefore the research of low pollution and noise electric motorcycles is a good method to ameliorate the pollution in the cities. Electric motorcycles are an new product, and the users are rare now. If the promotion is successful in the future, there will be some unexpected problems in consumer usage and the service which provided by the manufacturers. We interviewed the owners of electric motorcycles who have practice using experience to realize the using situation.We also use Stated Preference Method to design questionnaires.We investigate common peoples and the owners of electrics motorcycles to be the basis of Discrete Choice Models.To overcome the overstated effect of traditional Compensatory Models,we use the thresholds Discrete Choice Models to evaluate the thresholds for the decision of consumers purchase.To be the reference of developing electric motorcycles promotion strategies.The result indicates the users do not satisfy with the climbing ability, range, charging time, dependable remaining electricity indicator, and neitherdo the convenience of repairing places. The items which should be repaired more frequently are batteries, chargers, and controllers. Therefore, to promote electrical motorcycle successfully, the development of battery performance and the convenience of repairing places are very important. In the Discrete Choice Models, the Non-linear Attribute Thresholds Logit Models has better prediction.And the Attribute Thresholds Logit Models are better than the Logit Models.