Regulating ride-sharing in the peer economy

The rise of the peer economy poses complex new regulatory challenges for policy-makers. The peer economy, typified by services like Uber and AirBnB, promises substantial productivity gains through the more efficient use of existing resources and a marked reduction in regulatory overheads. These services are rapidly disrupting existing established markets, but the regulatory trade-offs they present are difficult to evaluate. In this paper, we examine the peer economy through the context of ride-sharing and the ongoing struggle over regulatory legitimacy between the taxi industry and new entrants Uber and Lyft. We first sketch the outlines of ride-sharing as a complex regulatory problem, showing how questions of efficiency are necessarily bound up in questions about levels of service, controls over pricing, and different approaches to setting, upholding, and enforcing standards. We outline the need for data-driven policy to understand the way that algorithmic systems work and what effects these might have in the medium to long term on measures of service quality, safety, labour relations, and equality. Finally, we discuss how the competition for legitimacy is not primarily being fought on utilitarian grounds, but is instead carried out within the context of a heated ideological battle between different conceptions of the role of the state and private firms as regulators. We ultimately argue that the key to understanding these regulatory challenges is to develop better conceptual models of the governance of complex systems by private actors and the available methods the state has of influencing their actions. These struggles are not, as is often thought, struggles between regulated and unregulated systems. The key to understanding these regulatory challenges is to better understand the important regulatory work carried out by powerful, centralised private firms – both the incumbents of existing markets and the disruptive network operators in the peer-economy.

Regulating ride-sharing in the peer economy

The rise of the peer economy poses complex new regulatory challenges for policy-makers. The peer economy, typified by services like Uber and AirBnB, promises substantial productivity gains through the more efficient use of existing resources and a marked reduction in regulatory overheads. These services are rapidly disrupting existing established markets, but the regulatory trade-offs they present are difficult to evaluate. In this paper, we examine the peer economy through the context of ride-sharing and the ongoing struggle over regulatory legitimacy between the taxi industry and new entrants Uber and Lyft. We first sketch the outlines of ride-sharing as a complex regulatory problem, showing how questions of efficiency are necessarily bound up in questions about levels of service, controls over pricing, and different approaches to setting, upholding, and enforcing standards. We outline the need for data-driven policy to understand the way that algorithmic systems work and what effects these might have in the medium to long term on measures of service quality, safety, labour relations, and equality. Finally, we discuss how the competition for legitimacy is not primarily being fought on utilitarian grounds, but is instead carried out within the context of a heated ideological battle between different conceptions of the role of the state and private firms as regulators. We ultimately argue that the key to understanding these regulatory challenges is to develop better conceptual models of the governance of complex systems by private actors and the available methods the state has of influencing their actions. These struggles are not, as is often thought, struggles between regulated and unregulated systems. The key to understanding these regulatory challenges is to better understand the important regulatory work carried out by powerful, centralised private firms – both the incumbents of existing markets and the disruptive network operators in the peer-economy.

Commuting mode choice in transit oriented development: Disentangling the effects of competitive neighbourhoods, travel attitudes, and self-selection

This research identifies the commuting mode choice behaviour of 3537 adults living in different types of transit oriented development (TOD) in Brisbane by disentangling the effects of their “evil twin” transit adjacent developments (TADs), and by also controlling for residential self-selection, travel attitudes and preferences, and socio-demographic effects. A TwoStep cluster analysis was conducted to identify the natural groupings of respondents’ living environment based on six built environment indicators. The analysis resulted in five types of neighbourhoods: urban TODs, activity centre TODs, potential TODs, TADs, and traditional suburbs. HABITAT survey data were used to derive the commute mode choice behaviour of people living in these neighbourhoods. In addition, statements reflecting both respondents’ travel attitudes and living preferences were also collected as part of the survey. Factor analyses were conducted based on these statements and these derived factors were then used to control for residential self-selection. Four binary logistic regression models were estimated, one for each of the travel modes used (e.g. public transport, active transport, less sustainable transport such as the car/taxi, and other), to differentiate between the commuting behaviour of people living in the five types of neighbourhoods. The findings verify that urban TODs enhance the use of public transport and reduce car usage. No significant difference was found in the commuting behaviour between respondents living in traditional suburbs and TADs. The results confirm the hypothesis that TADs are the “evil twin” of TODs. The data indicates that TADs and the mode choices of residents in these neighbourhoods is a missed transport policy opportunity. Further policy efforts are required for a successive transition of TADs into TODs in order to realise the full benefits of these. TOD policy should also be integrated with context specific TOD design principles.

Factors associated with depression among male casual laborers in urban Vietnam

This study examined the level, the prevalence of and the factors associated with depression among male casual laborers in Hanoi. Social mapping was done to recruit and interview 450 men aged over 18 years, mostly unskilled and unregistered laborers from 135 street venues across 13 districts of the city using a structured questionnaire. Most were from rural and mountainous provinces and did manual works such as motorbike taxi drivers, porters, construction workers, small traders and others in the current city. The prevalence of self-reported depressive symptoms (25 %) was high. Structural equation modeling showed that marriage, family separation and living with peers or partners were three significant distal risk factors, while illicit drug use and low social connectedness were proximal predictors of depression. Of all factors, social connectedness appeared to be the most important because it plays a mediating role. Drug use was an independent risk factor. This study provides a model to understand the mental health of male casual laborers and to develop culturally appropriate intervention programs for these men

Criminal histories of crash and non-crash involved Queensland speeding offenders: Evidence supporting the idea that we drive as we live

Evidence increasingly suggests that our behaviour on the road mirrors our behaviour across other aspects of our life. The idea that we drive as we live, described by Tillman and Hobbs more than 65 years ago when examining off-road behaviours of taxi drivers (1949), is the focus of the current paper. As part of a larger study examining the impact of penalty changes on a large cohort of Queensland speeding offenders, criminal (lifetime) and crash history (10 year period) data for a sub-sample of 1000 offenders were obtained. Based on the ‘drive as we live’ maxim, it was hypothesised that crash-involved speeding offenders would be more likely to have a criminal history than non-crash involved offenders. Overall, only 30% of speeding offenders had a criminal history. However, crash-involved offenders were significantly more likely to have a criminal history (49.4%) than non-crash involved offenders (28.6%), supporting the hypothesis. Furthermore, those deemed ‘most at fault’ in a crash were the group most likely to have at least one criminal offence (52.2%). When compared to the non-crash involved offenders, those deemed ‘not most at fault’ in a crash were also more likely to have had at least one criminal offence (46.5%). Therefore, when compared to non-crash involved speeding offenders, those offenders involved in a crash were more likely to have been convicted of at least one criminal offence, irrespective of whether they were deemed ‘most at fault’ in that crash. Implications for traffic offender management and policing are discussed.

Comparative analysis of traffic state estimation ─ Cumulative counts-based and trajectory-based methods

The Macroscopic Fundamental Diagram (MFD) relates space-mean density and flow. Since the MFD represents the area-wide network traffic performance, studies on perimeter control strategies and network-wide traffic state estimation utilising the MFD concept have been reported. Most previous works have utilised data from fixed sensors, such as inductive loops, to estimate the MFD, which can cause biased estimation in urban networks due to queue spillovers at intersections. To overcome the limitation, recent literature reports the use of trajectory data obtained from probe vehicles. However, these studies have been conducted using simulated datasets; limited works have discussed the limitations of real datasets and their impact on the variable estimation. This study compares two methods for estimating traffic state variables of signalised arterial sections: a method based on cumulative vehicle counts (CUPRITE), and one based on vehicles’ trajectory from taxi Global Positioning System (GPS) log. The comparisons reveal some characteristics of taxi trajectory data available in Brisbane, Australia. The current trajectory data have limitations in quantity (i.e., the penetration rate), due to which the traffic state variables tend to be underestimated. Nevertheless, the trajectory-based method successfully captures the features of traffic states, which suggests that the trajectories from taxis can be a good estimator for the network-wide traffic states.

Of old and new. Messages conveyed by Australian Universities

On arriving at the University of Queensland, I walked from where the taxi dropped me off towards the Great Court. As I walked I could see the carvings in the sandstone on the façade of the building in front of me. The carvings depict images of land, flora, fauna, settlers, and us. In the corner of my right sight of vision, I could see Mayne Hall. My mind flicked back in what was an instant to a time 30 plus years ago. I remember putting on some of my best clothes when my family would travel form the suburb of Inala to the Alumni book fair held in the Hall. We needed to act ‘discrete’ and like we were ‘meant to be there’. Members of my family would work hard to save money to buy the books that had far more substance than the books at our local community or school library. This was my first interaction with the University of Queensland. On the first day of Courting Blakness, I walked towards and then into the Great Court. I began to explore and engage with the artworks and allow them to engage with me. I was conscious of being in the University of Queensland as I had been on all my past visits. I was conscious of the public and the private aspects of the artworks along with the public observance and surveillance of the viewers of the artworks. The contradictions and struggles that Aboriginal and Torres Strait Islander people experience are everywhere when moving in spaces and places, including universities. They contain prevailing social, political and economic values in the same way that other places do. The symbols of place and space within universities are never neutral, and they can work to either marginalise and oppress Aboriginal and Torres Strait Islander people, or demonstrate that they are included and engaged. The artworks in the Great Court were involved in this matrix of mixed messages and the weaves of time contained the borders of the Court and within the minds of those present.

Young at heart, old at work? Relations between age, (meta-)stereotypes, self-categorization, and retirement attitudes

The aims of this study were to examine how workers' negative age stereotypes (i.e., denying older workers' ability to develop) and negative meta-stereotypes (i.e., beliefs that the majority of colleagues feel negative about older workers) are related to their attitudes towards retirement (i.e., occupational future time perspective and intention to retire), and whether the strength of these relationships is influenced by workers' self-categorization as an “older” person. Results of a study among Dutch taxi drivers provided mixed support for the hypotheses. Negative meta-stereotypes, but not negative age stereotypes, were associated with fewer perceived opportunities until retirement and, in turn, a stronger intention to retire. Self-categorization moderated the relationships between negative age (meta-)stereotypes and occupational future time perspective. However, contrary to expectations, the relations were stronger among workers with a low self-categorization as an older person in comparison with workers with a high self-categorization in this regard. Overall, results highlight the importance of psychosocial processes in the study of retirement intentions and their antecedents.

Regulating ride-sharing in the peer economy

This magazine article examines the challenges of digital disruption and the way the struggle for legitimacy is playing out in mainstream and social media. Using ride-sharing as a case study, our team at the QUT Digital media research centre seeks to develop the tools policy-makers need to make evidence-based policy decisions in response to digital disruption.