Ride-Hailing Service Adoption and Local Context in Motorcycle-Based Societies: Case Study in Hanoi, Vietnam

The ride-hailing service (RHS) has emerged as a major form of daily travel in many Southeast Asian cities where motorcycles are extensively used. This study aims to analyze the local context in motorcycle-based societies, which may affect the establishment of travelers’ choice set after the appearance of RHSs. In particular, it empirically compares three types of choice-set structures in the context of urban travel mode choice by estimating standard logit and nested logit models to test six hypotheses on the associations of RHS adoption with its determinants. Revealed preference data of 449 trips from both RHS users and non-RHS users were collected through a face-to-face interview-based questionnaire survey in Hanoi, Vietnam, in December 2020. The results of model estimations revealed: (1) a substitutional effect for two-wheelers but not for four-wheelers, (2) a significant positive influence of car ownership on car RHS adoption but not on motorcycle RHS adoption, (3) significantly high sensitivity to travel time of motorcycle RHS but not of car RHS, (4) a significant negative effect of traffic congestion on car RHS adoption but an insignificant one on motorcycle RHS adoption, and (5) a significant positive association of an individual’s experience in using a smartphone with car RHSs but insignificant association with motorcycle RHSs. Our findings suggest that transportation policies of RHS motorcycles should be different from those of RHS cars because of the heterogeneity in travel behaviors of RHS users between them. They also indicate that the transition from motorcycles to cars as well as the difference in service availability among different types of RHSs should be incorporated into the development of transportation policies in Southeast Asian cities.

Using Facebook data to predict the 2016 U.S. presidential election

We use 19 billion likes on the posts of top 2000 U.S. fan pages on Facebook from 2015 to 2016 to measure the dynamic ideological positions for politicians, news outlets, and users at the national and state levels. We then use these measures to derive support rates for 2016 presidential candidates in all 50 states, to predict the election, and to compare them with state-level polls and actual vote shares. We find that: (1) Assuming that users vote for candidates closer to their own ideological positions, support rates calculated using Facebook predict that Trump will win the electoral college vote while Clinton will win the popular vote. (2) State-level Facebook support rates track state-level polling averages and pass the cointegration test, showing two time series share similar trends. (3) Compared with actual vote shares, polls generally have smaller margin of errors, but polls also often overestimate Clinton’s support in right-leaning states. Overall, we provide a method to forecast elections at low cost, in real time, and based on passively revealed preference and little researcher discretion.

On Sense and Preference

Determining the precise nature of the connection between preference, choice, and welfare has arguably been the central project in the field of welfare economics, which aims to offer a proper guide for economists in the making of policy decisions that affect people’s welfare. The two leading approaches here historically – the revealed preference and latent preference approaches – seem equally incapable of so guiding economists. I argue that the deadlock here is due to welfare economists’ failure to recognize a crucial distinction between two senses of “preference.” I analyze and defend these senses of “preference,” and argue that each shares a close connection with just one of choice and welfare. This analysis reveals how economists should conceive of both the connections between “preference,” choice, and welfare, and the proper roles of these concepts in welfare economics. I conclude by showing this analysis to best explain the plausibility of two leading alternative approaches from Hausman and Sugden.

Deconstructing the New Zealand Transport Agency Economic Evaluation Manual: Bringing the best research on transportation and its economic benefit into the applied New Zealand context

<p>This paper explores the New Zealand Transport Agency Economic Evaluation Manual from the perspective of best practices in international literature. Drawing upon research from the international community and policy-focused bodies like the OECD, the paper seeks to improve the NZTA EEM’s quality by employing hedonic and revealed-preference methods to create a more accurate tool to derive the value of certain transport investments. The paper finds that the value of time in New Zealand is far too low, the discount regime improperly reflects the nature of such investments, cycling benefits are undervalued, and property values are not accounted for as well as they could be. The paper then applies these findings to the recently-completed Public Transport Spine Study in Wellington, New Zealand to illustrate the importance of accurate economic evaluation of transport investments.</p>

Deconstructing the New Zealand Transport Agency Economic Evaluation Manual: Bringing the best research on transportation and its economic benefit into the applied New Zealand context

<p>This paper explores the New Zealand Transport Agency Economic Evaluation Manual from the perspective of best practices in international literature. Drawing upon research from the international community and policy-focused bodies like the OECD, the paper seeks to improve the NZTA EEM’s quality by employing hedonic and revealed-preference methods to create a more accurate tool to derive the value of certain transport investments. The paper finds that the value of time in New Zealand is far too low, the discount regime improperly reflects the nature of such investments, cycling benefits are undervalued, and property values are not accounted for as well as they could be. The paper then applies these findings to the recently-completed Public Transport Spine Study in Wellington, New Zealand to illustrate the importance of accurate economic evaluation of transport investments.</p>

Elevating the Value of Urban Location: A Consumer Preference-Based Approach to Valuing Local Amenity Provision

Estimating the non-market monetary values of urban amenities has become commonplace in urban planning research, particularly following Rosen’s seminal article on hedonic theory in 1974. As a revealed preference method, the hedonic approach decouples the market price of a house into price components that are attributable to housing characteristics. Despite the potential contribution of this theory in a planning context, three main limitations exist in the conventional applications: (1) variable measurement issues, (2) model misspecification, and (3) the problematic common use of global regression. These flaws problematically skew our understanding of the urban structure and spatial distribution of amenities, leading to misinformed policy interventions and poor amenity planning decisions. In this article, we propose a coherent conceptual framework that addresses measurement, specification, and scale challenges to generate consistent economic estimates of local amenities. Finally, we argue that, by paying greater attention to the spatial equity of amenity values, governments can provide greater equality of opportunities in cities.

Trend Analysis of Grow-Your-Own Using Social Network Analysis: Focusing on Hashtags on Instagram

Background and objective: The prolonged COVID-19 pandemic has had significant impacts on mental health, which has emerged as a major public health issue around the world. This study aimed to analyze trends and network structure of ‘grow-your-own (GYO)’ through Instagram, one of the most influential social media platforms, to encourage and sustain home gardening activities for promotion of emotional support and physical health. Methods: A total of 6,388 posts including keyword hashtags ‘#gyo’ and ‘#growyourown’ on Instagram from June 13, 2020 to April 13, 2021 were collected. Word embedding was performed using Word2Vec library, and 7 clusters were identified with K-means clustering: GYO, garden and gardening, allotment, kitchen garden, sustainability, urban gardening, etc. Moreover, we conducted social network analysis to determine the centrality of related words and visualized the results using Gephi 0.9.2. Results: The analysis showed that various combinations of words, such as #growourrownfood, #growourrownveggies, and #growwhatyoueat revealed preference and interest of users in GYO, and appeared to encourage their activities on Instagram. In particular, #gardeningtips, #greenfingers, #goodlife, #gardeninglife, #gardensofinstagram were found to express positive emotions and pride as a gardener by sharing their daily gardening lives. Users were participating in urban gardening through #allotment, #raisedbeds, #kitchengarden and we could identify trends toward self-sufficiency and sustainable living. Conclusion: Based on these findings, it is expected that the trend data of GYO, which is a form of urban gardening, can be used as the basic data to establish urban gardening plans considering each characteristic, such as the emotions and identity of participants as well as their dispositions.