运河作为望加锡市城市交通替代媒介的需求潜力

Amiruddin Akbar Fisu, I. Syabri
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引用次数: 0

摘要

水运是使用水运方式作为连接一个地点到另一个地点的手段的人员和货物的运输。望加锡市中心有三条运河,总长15.11公里。这些运河既是城市的排水系统,也是防洪的主要基地。这条运河已经成为一种潜力,可以用来解开基于道路的运动,同时解决发生在望加锡市的拥堵问题,利用它作为城市交通媒介,作为日常需求(正式)和娱乐活动(非正式)的旅行。本研究旨在了解基于运河的运输方式的需求偏好、影响使用渠道作为运输媒介意愿的变量,以及渠道的作用在多大程度上成为一种可替代的运输媒介。本研究采用描述性定量方法来实现这些目标,使用交叉表分析方法,多项逻辑回归和方法与陈述偏好方法。根据分析结果,有四个变量显著影响受访者使用运河/水路运输服务的意愿,即每月收入、旅行时间、选择方式的原因和关税容忍度。在陈述偏好分析中,结果表明水路运输的运营将导致道路方式用户向出行方式的转变,其中场景1的增幅为31.10%,场景2的增幅为37.26%。
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Demand Potential On Canal Utilization As Alternative Urban Transportation Medium In Makassar City
Water transportation is the transportation of people and goods using water modes as a means of connecting one location to another. There are three canals in the center of Makassar City with a total length of 15.11 km. These canals function as an urban drainage and also as a main base for flood control. This canal has become one of the potentials that can be used to unravel road-based movements while at the same time solving the congestion problems that occur in Makassar City by utilizing it as an urban transportation medium both as a travel for daily needs (formal) and recreational activities (non-formal). This research was conducted to see how the demand preferences of canal-based transportation modes, variables that affect the willingness to use channels as a transportation medium, and the extent to which the role of channels becomes an alternative transportation medium. This study uses a descriptive quantitative method approach to achieve these objectives using the method of crosstab analysis, multinomial logistic regression and approaches with stated preference methods. Based on the results of the analysis, there are four variables that significantly affect respondents' willingness to use canal / waterway based transportation services, namely income per month, travel time, reasons for choosing modes, and tariff tolerance. In the stated preference analysis, the results show that the operation of the waterway transportation will cause the shift of road-based mode users to travel, where the increase is 31.10% for scenario 1 and 37.26% for scenario 2.
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