Elliot Martin

Bio: Elliot Martin is an academic researcher from University of California, Berkeley. The author has contributed to research in topics: Population & Public transport. The author has an hindex of 22, co-authored 36 publications receiving 2634 citations.

Impact of Carsharing on Household Vehicle Holdings: Results from North American Shared-Use Vehicle Survey

Abstract: Carsharing has grown considerably in North America during the past decade and has flourished in metropolitan regions across the United States and Canada. The new transportation landscape offers urban residents an alternative to automobility, one without car ownership. As carsharing has expanded, there has been a growing demand to understand its environmental effects. This paper presents the results of a North American carsharing member survey (N = 6,281). A before-and-after analytical design is established with a focus on carsharing's effects on household vehicle holdings and the aggregate vehicle population. The results show that carsharing members reduce their vehicle holdings to a degree that is statistically significant. The average number of vehicles per household of the sample drops from 0.47 to 0.24. Most of this shift constitutes onecar households becoming carless. The average fuel economy of carsharing vehicles used most often by respondents is 10 mi/gal more efficient than the average vehicle sh...

Greenhouse Gas Emission Impacts of Carsharing in North America

Abstract: This paper evaluates the greenhouse gas (GHG) emission impacts that result from individuals participating in carsharing organizations within North America. The authors con ducted an online survey with members of major carsharing organizations and evaluated the change in annual household emissions (e.g., impact) of respondents that joined carsharing. The results show that a majority of households joining carsharing are increasing their emissions by gaining access to automobiles. However, individually, these increases are small. In contrast, the remaining households are decreasing their emissions by shedding vehicles and driving less. The collective emission reductions outweigh the collective emission increases, which implies that carsharing reduces GHG emissions as a whole. The results are reported in the form of an observed impact, which strictly evaluates the changes in emissions that physically occur, and a full impact, which also considers emissions that would have happened but were avoided due to carsharing. The mean observed impact is -0.58 t GHG/year per household, whereas the mean full impact is -0.84 t GHG/year per household. Both means are statistically significant. We present a sensitivity analysis to evaluate the robustness of the results and find that the overall results hold across a variety of assumptions. The average observed vehicle kilometers traveled (VKT) per year was found to decline by 27%. We conclude with an evaluation of the annual aggregate impacts of carsharing based on current knowledge of the industry membership population.

China's Hangzhou Public Bicycle: Understanding Early Adoption and Behavioral Response to Bikesharing

Abstract: Over the past 20 years, China has experienced a steady decline in bicycle use. To address this trend, China's central and local government for urban transportation created Public Transit Priority to encourage public transport initiatives. As part of this effort, the government of the city of Hangzhou launched Hangzhou Public Bicycle in 2008. This service allows members to access a shared fleet of bicycles. As of March 2011, Hangzhou Public Bicycle operated 60,600 bicycles with 2,416 fixed stations in eight core districts. To understand factors leading to bikesharing adoption and barriers to adoption, the authors conducted an intercept survey in Hangzhou between January and March 2010. Two separate questionnaires were issued to bikesharing members and nonmembers to identify key differences and similarities between these groups. In total, 806 surveys were completed by 666 members and 140 nonmembers. The authors found that bikesharing was capturing modal share from bus transit, walking, autos, and taxis. App...

The Impact of Carsharing on Public Transit and Non-Motorized Travel: An Exploration of North American Carsharing Survey Data

Abstract: By July 2011, North American carsharing had grown to an industry of nearly 640,000 members since its inception on the continent more than 15 years ago. Carsharing engenders changes in member travel patterns both towards and away from public transit and non-motorized modes. This study, which builds on the work of two previous studies, evaluates this shift in travel based on a 6281 respondent survey completed in late-2008 by members of major North American carsharing organizations. Across the entire sample, the results showed an overall decline in public transit use that was statistically significant, as 589 carsharing members reduced rail use and 828 reduced bus use, while 494 increased rail use and 732 increased bus use. Thus for every five members that use rail less, four members use rail more, and for every 10 members that ride a bus less, almost nine members ride the bus more. The people increasing and decreasing their transit use are fundamentally different in terms of how carsharing impacts their travel environment. This reduction, however, is also not uniform across all organizations; it is primarily driven by a minority (three of eleven) of participating organizations. At the same time, members exhibited a statistically significant increase in travel by walking, bicycling, and carpooling. Across the sample, 756 members increased walking versus a 568 decrease, 628 increased bicycling versus a 235 decrease, and 289 increased carpooling versus a decrease of 99 study participants. The authors found that 970 members reduced their auto commuting to work, while 234 increased it. Interestingly, when these shifts are combined across modes, more people increased their overall public transit and non-motorized modal use

반도체 공정 overview

Abstract: With digital equipment becoming increasingly networked, either on wired or wireless networks, for personal and professional use alike, distributed software systems have become a crucial element in information and communications technologies. The study of these systems forms the core of the ARLES' work, which is specifically concerned with defining new system software architectures, based on the use of emerging networking technologies. In this context, we concentrate on the study of distributed systems which bring to life the vision of ubiquitous computing systems, also known as ambient intelligence.

The Rise of the Sharing Economy: Estimating the Impact of Airbnb on the Hotel Industry

Abstract: Peer-to-peer markets, collectively known as the sharing economy, have emerged as alternative suppliers of goods and services traditionally provided by long-established industries. A central question regards the impact of these sharing economy platforms on incumbent firms. We study the case of Airbnb, specifically analyzing Airbnb’s entry into the short-term accommodation market in Texas and its impact on the incumbent hotel industry. We first explore Airbnb’s impact on hotel revenue, by using a difference- in-differences empirical strategy that exploits the significant spatiotemporal variation in the patterns of Airbnb adoption across city-level markets. We estimate that in Austin, where Airbnb supply is highest, the causal impact on hotel revenue is in the 8-10% range; moreover, the impact is non-uniformly distributed, with lower-priced hotels and those hotels not catering to business travelers being the most affected. We find that this impact materializes through less aggressive hotel room pricing, an impact that benefits all consumers, not just participants in the sharing economy. The impact on hotel prices is especially pronounced during periods of peak demand, such as SXSW. We find that by enabling supply to scale – a differentiating feature of peer-to-peer platforms – Airbnb has significantly crimped hotels’ ability to raise prices during periods of peak demand. Our work provides empirical evidence that the sharing economy is making inroads by successfully competing with, differentiating from, and acquiring market share from incumbent firms.

The Rise of the Sharing Economy: Estimating the Impact of Airbnb on the Hotel Industry

Abstract: Peer-to-peer markets, collectively known as the sharing economy, have emerged as alternative suppliers of goods and services traditionally provided by long-established industries. The authors explore the economic impact of the sharing economy on incumbent firms by studying the case of Airbnb, a prominent platform for short-term accommodations. They analyze Airbnb’s entry into the state of Texas and quantify its impact on the Texas hotel industry over the subsequent decade. In Austin, where Airbnb supply is highest, the causal impact on hotel revenue is in the 8%–10% range; moreover, the impact is nonuniform, with lower-priced hotels and hotels that do not cater to business travelers being the most affected. The impact manifests itself primarily through less aggressive hotel room pricing, benefiting all consumers, not just participants in the sharing economy. The price response is especially pronounced during periods of peak demand, such as during the South by Southwest festival, and is due to a di...

The travel and environmental implications of shared autonomous vehicles, using agent-based model scenarios

Abstract: Carsharing programs that operate as short-term vehicle rentals (often for one-way trips before ending the rental) like Car2Go and ZipCar have quickly expanded, with the number of US users doubling every 1–2 years over the past decade. Such programs seek to shift personal transportation choices from an owned asset to a service used on demand. The advent of autonomous or fully self-driving vehicles will address many current carsharing barriers, including users’ travel to access available vehicles. This work describes the design of an agent-based model for shared autonomous vehicle (SAV) operations, the results of many case-study applications using this model, and the estimated environmental benefits of such settings, versus conventional vehicle ownership and use. The model operates by generating trips throughout a grid-based urban area, with each trip assigned an origin, destination and departure time, to mimic realistic travel profiles. A preliminary model run estimates the SAV fleet size required to reasonably service all trips, also using a variety of vehicle relocation strategies that seek to minimize future traveler wait times. Next, the model is run over one-hundred days, with driverless vehicles ferrying travelers from one destination to the next. During each 5-min interval, some unused SAVs relocate, attempting to shorten wait times for next-period travelers. Case studies vary trip generation rates, trip distribution patterns, network congestion levels, service area size, vehicle relocation strategies, and fleet size. Preliminary results indicate that each SAV can replace around eleven conventional vehicles, but adds up to 10% more travel distance than comparable non-SAV trips, resulting in overall beneficial emissions impacts, once fleet-efficiency changes and embodied versus in-use emissions are assessed.

Psychological factors influencing sustainable energy technology acceptance: A review-based comprehensive framework

Abstract: Environmental and societal problems related to energy use have spurred the development of sustainable energy technologies, such as wind mills, carbon capture and storage, and hydrogen vehicles. Public acceptance of these technologies is crucial for their successful introduction into society. Although various studies have investigated technology acceptance, most technology acceptance studies focused on a limited set of factors that can influence public acceptance, and were not based on a comprehensive framework including key factors influencing technology acceptance. This paper puts forward a comprehensive framework of energy technology acceptance, based on a review of psychological theories and on empirical technology acceptance studies. The framework aims to explain the intention to act in favor or against new sustainable energy technologies, which is assumed to be influenced by attitude, social norms, perceived behavioral control, and personal norm. In the framework, attitude is influenced by the perceived costs, risks and benefits, positive and negative feelings in response to the technology, trust, procedural fairness and distributive fairness. Personal norm is influenced by perceived costs, risks and benefits, outcome efficacy and awareness of adverse consequences of not accepting the new technology. The paper concludes with discussing the applicability of the framework.