Abstract

This paper presents the details of three scenarios -- leapfrog, lock-in, and lopsided -- that describe an illustrative set of technological states. Based largely on expert interviews, the paper argues that the technology outcomes are heavily attributable to the actions (or in some cases, inaction) of policy makers and incumbents. For each scenario, the paper presents descriptive levels of technology achievement and market outcomes for the energy, transport, and water sectors. One of the central differentiating features of the three scenarios is the extent to which governments perform their roles as enabling, that is, whether the policies are designed to help or hinder innovations that improve service levels, and distributive, that is, whether the policies are designed to ensure that multiple segments of society reap the rewards of innovation. A question raised as part of that theme is how countries can avoid lock-in, or how they might become derailed into a lopsided scenario. Some institutional behavioral markers of the scenarios were identified in these discussions and are noted in the paper. It is important to recognize that multiple combinations of these behaviors can lead to a lock-in or lopsided scenario. In addition to describing the scenarios in detail, the paper discusses the rationale for their creation, along with a brief discussion on the nature of uncertainty. The paper also describes the methodology employed in the creation of the scenarios, including expert interview methods and a day-long workshop. Document type: Book

Abstract

This article models a novel driving-day-based tradable credit scheme (DD-TCS) to alleviate urban traffic congestion. In this model, car-using allowances (in terms of the number of days in a month, termed as “credit”) are freely and uniformly allocated to all travellers, who are also allowed to trade them in a market according to his/her travel needs (e.g. driving more or fewer days than the free endowment). As opposed to most studies on TCS, this paper explicitly considers the transaction cost (e.g. information cost of finding potential traders) in the trading market. To assess the feasibility of DD-TCS, we compare it against the license plate rationing (LPR) scheme, which has been practically implemented in many cities such as Beijing and Chengdu in China. Taking the performance of LPR as a benchmark, we quantify the threshold values of the transaction cost in DD-TCS when the two schemes yield equivalent performance (in terms of the total generalized cost). In numerical studies, we also compare the DD-TCS and LPR with the no-action case and the congestion pricing case (representing the theoretical optimum). Results show that both DD-TCS and LPR outperform the no-action case under certain conditions. With small transaction cost, DD-TCS may achieve a lower system cost that can be very close to the ideal optimum. In addition, parameter analysis shows that DD-TCS performs better than LPR in a wide range of transaction cost, where the threshold values appear to account for a considerable portion of the auto travel time. This implies that DD-TCS will be more appealing than LPR in practice because a transaction cost lower than the extremely large threshold values can be easily achieved for the trading market, e.g. via a mobile platform and modern communication techniques. Document type: Article