ASU Scholarship Showcase

Recently the domestic aviation industry has been influenced by rapidly growing ultra low-cost carriers (ULCCs). The pattern of airport markets served by ULCCs is incongruous with legacy carriers and low-cost airlines alike. Existing literature, however, is limited for North American ULCCs: research has only recently begun to identify them separately from mainstream low-cost carriers. This study sought to understand the market factors that influence ULCC service decisions. The relationship between ULCC operations and airport market factors was analyzed using three methods: mapping 2019 flight data for four ULCCs combined, two regression analyses to evaluate variables, and three case studies examining distinct scenarios through interviews with airport managers. Enplanement data were assembled for every domestic airport offering scheduled service in 2019. Independent variables were collected for each Part 139 airport. The first model estimated an ordinary least squares regression model to analyze ULCC enplanements. The second model estimated a binary logistic equation for presence of ULCC service. Case studies for Bellingham, Waco, and Lincoln were selected using compelling airport factors and relevant ULCC experience. Maps of ULCC enplanements revealed concentrations of operations on the East Coast. Both regression analyses showed strong relationships between population and non-ULCC enplanements (two measures of airport market size) and ULCC operations. A significant relationship also existed between tourism and enplanements. In the logit model, distance and competition variables were associated with ULCC presence. Case studies emphasized the importance of airport fees and competition in ULCC preferences, although aeronautical costs were generally not significant in the regressions.

Cities in the Global South face rapid urbanization challenges and often suffer an acute lack of infrastructure and governance capacities. Smart Cities Mission, in India, launched in 2015, aims to offer a novel approach for urban renewal of 100 cities following an area‐based development approach, where the use of ICT and digital technologies is particularly emphasized. This article presents a critical review of the design and implementation framework of this new urban renewal program across selected case‐study cities. The article examines the claims of the so‐called “smart cities” against actual urban transformation on‐ground and evaluates how “inclusive” and “sustainable” these developments are. We quantify the scale and coverage of the smart city urban renewal projects in the cities to highlight who the program includes and excludes. The article also presents a statistical analysis of the sectoral focus and budgetary allocations of the projects under the Smart Cities Mission to find an inherent bias in these smart city initiatives in terms of which types of development they promote and the ones it ignores. The findings indicate that a predominant emphasis on digital urban renewal of selected precincts and enclaves, branded as “smart cities,” leads to deepening social polarization and gentrification. The article offers crucial urban planning lessons for designing ICT‐driven urban renewal projects, while addressing critical questions around inclusion and sustainability in smart city ventures.`

Attitudes and habits are extremely resistant to change, but a disruption of the magnitude of the COVID-19 pandemic has the potential to bring long-term, massive societal changes. During the pandemic, people are being compelled to experience new ways of interacting, working, learning, shopping, traveling, and eating meals. Going forward, a critical question is whether these experiences will result in changed behaviors and preferences in the long term. This paper presents initial findings on the likelihood of long-term changes in telework, daily travel, restaurant patronage, and air travel based on survey data collected from adults in the United States in Spring 2020. These data suggest that a sizable fraction of the increase in telework and decreases in both business air travel and restaurant patronage are likely here to stay. As for daily travel modes, public transit may not fully recover its pre-pandemic ridership levels, but many of our respondents are planning to bike and walk more than they used to. These data reflect the responses of a sample that is higher income and more highly educated than the US population. The response of these particular groups to the COVID-19 pandemic is perhaps especially important to understand, however, because their consumption patterns give them a large influence on many sectors of the economy.

A globally integrated carbon observation and analysis system is needed to improve the fundamental understanding of the global carbon cycle, to improve our ability to project future changes, and to verify the effectiveness of policies aiming to reduce greenhouse gas emissions and increase carbon sequestration. Building an integrated carbon observation system requires transformational advances from the existing sparse, exploratory framework towards a dense, robust, and sustained system in all components: anthropogenic emissions, the atmosphere, the ocean, and the terrestrial biosphere. The paper is addressed to scientists, policymakers, and funding agencies who need to have a global picture of the current state of the (diverse) carbon observations.

We identify the current state of carbon observations, and the needs and notional requirements for a global integrated carbon observation system that can be built in the next decade. A key conclusion is the substantial expansion of the ground-based observation networks required to reach the high spatial resolution for CO₂ and CH₄ fluxes, and for carbon stocks for addressing policy-relevant objectives, and attributing flux changes to underlying processes in each region. In order to establish flux and stock diagnostics over areas such as the southern oceans, tropical forests, and the Arctic, in situ observations will have to be complemented with remote-sensing measurements. Remote sensing offers the advantage of dense spatial coverage and frequent revisit. A key challenge is to bring remote-sensing measurements to a level of long-term consistency and accuracy so that they can be efficiently combined in models to reduce uncertainties, in synergy with ground-based data.

Bringing tight observational constraints on fossil fuel and land use change emissions will be the biggest challenge for deployment of a policy-relevant integrated carbon observation system. This will require in situ and remotely sensed data at much higher resolution and density than currently achieved for natural fluxes, although over a small land area (cities, industrial sites, power plants), as well as the inclusion of fossil fuel CO₂ proxy measurements such as radiocarbon in CO₂ and carbon-fuel combustion tracers. Additionally, a policy-relevant carbon monitoring system should also provide mechanisms for reconciling regional top-down (atmosphere-based) and bottom-up (surface-based) flux estimates across the range of spatial and temporal scales relevant to mitigation policies. In addition, uncertainties for each observation data-stream should be assessed. The success of the system will rely on long-term commitments to monitoring, on improved international collaboration to fill gaps in the current observations, on sustained efforts to improve access to the different data streams and make databases interoperable, and on the calibration of each component of the system to agreed-upon international scales.

Current research on criminal case processing typically examines a single decision-making point, so drawing reliable conclusions about the impact that factors such as defendants’ race or ethnicity exert across successive stages of the justice system is difficult. Using data from the New York County District Attorney's Office that tracks 185,275 diverse criminal cases, this study assesses racial and ethnic disparity for multiple discretionary points of prosecution and sentencing. Findings from multivariate logistic regression analyses demonstrate that the effects of race and ethnicity vary by discretionary point and offense category. Black and Latino defendants were more likely than White defendants to be detained, to receive a custodial plea offer, and to be incarcerated—and they received especially punitive outcomes for person offenses—but were more likely to benefit from case dismissals. The findings for Asian defendants were less consistent but suggest they were the least likely to be detained, to receive custodial offers, and to be incarcerated. These findings are discussed in the context of contemporary theoretical perspectives on racial bias and cumulative disadvantage in the justice system.

Errors in the specification or utilization of fossil fuel CO₂ emissions within carbon budget or atmospheric CO₂ inverse studies can alias the estimation of biospheric and oceanic carbon exchange. A key component in the simulation of CO₂ concentrations arising from fossil fuel emissions is the spatial distribution of the emission near coastlines. Regridding of fossil fuel CO₂ emissions (FFCO₂) from fine to coarse grids to enable atmospheric transport simulations can give rise to mismatches between the emissions and simulated atmospheric dynamics which differ over land or water. For example, emissions originally emanating from the land are emitted from a grid cell for which the vertical mixing reflects the roughness and/or surface energy exchange of an ocean surface. We test this potential "dynamical inconsistency" by examining simulated global atmospheric CO₂ concentration driven by two different approaches to regridding fossil fuel CO₂ emissions. The two approaches are as follows: (1) a commonly used method that allocates emissions to grid cells with no attempt to ensure dynamical consistency with atmospheric transport and (2) an improved method that reallocates emissions to grid cells to ensure dynamically consistent results. Results show large spatial and temporal differences in the simulated CO₂ concentration when comparing these two approaches. The emissions difference ranges from −30.3 TgC grid cell^-1 yr^-1 (−3.39 kgC m^-2 yr^-1) to +30.0 TgC grid cell^-1 yr^-1 (+2.6 kgC m^-2 yr^-1) along coastal margins. Maximum simulated annual mean CO₂ concentration differences at the surface exceed ±6 ppm at various locations and times. Examination of the current CO₂ monitoring locations during the local afternoon, consistent with inversion modeling system sampling and measurement protocols, finds maximum hourly differences at 38 stations exceed ±0.10 ppm with individual station differences exceeding −32 ppm. The differences implied by not accounting for this dynamical consistency problem are largest at monitoring sites proximal to large coastal urban areas and point sources. These results suggest that studies comparing simulated to observed atmospheric CO₂ concentration, such as atmospheric CO₂ inversions, must take measures to correct for this potential problem and ensure flux and dynamical consistency.

Simons and Burt's (2011) social schematic theory (SST) of crime posits that adverse social factors are associated with offending because they promote a set of social schemas (i.e., a criminogenic knowledge structure) that elevates the probability of situational definitions favorable to crime. This study extends the SST model by incorporating the role of contexts for action. Furthermore, the study advances tests of the SST by incorporating a measure of criminogenic situational definitions to assess whether such definitions mediate the effects of schemas and contexts on crime. Structural equation models using 10 years of panel data from 582 African American youth provided strong support for the expanded theory. The results suggest that childhood and adolescent social adversity fosters a criminogenic knowledge structure as well as selection into criminogenic activity spaces and risky activities, all of which increase the likelihood of offending largely through situational definitions. Additionally, evidence shows that the criminogenic knowledge structure interacts with settings to amplify the likelihood of situational definitions favorable to crime.

Cyberstalking is a relatively understudied area in criminology, with no consensus among scholars as to whether it represents a modified form of stalking or whether it is an entirely new and emerging criminal phenomenon. Using data from the 2006 Supplemental Victimization Survey (SVS) to the National Crime Victimization Survey (NCVS), this study compares stalking and cyberstalking victims across several dimensions, including situational features of their experiences and self-protective behaviors. Results indicate that there are significant differences between stalking and cyberstalking victims, including their number of self-protective behaviors adopted, duration of contact with their stalker, financial costs of victimization, and perceived fear at onset. Perceived fear over time, the occurrence of a physical attack, and sex of the victim were all associated with a higher number of self-protective behaviors for cyberstalking victims compared to stalking victims, net of the effect of the control variables. Implications for stalking theory, research, and criminal justice policy are discussed.

The Phoenix TRUCE Project was modeled after the Chicago CeaseFire program. There have been relatively few process and impact evaluations on the model compared to the level of funding and attention the program has rendered. This paper presents findings related to the evaluation of the TRUCE project. We found that the program engaged in a strong media campaign, conducted conflict mediations, and identified high-risk individuals for case management. The program did not, however, establish a coordinated and collaborative relationship with the faith-based community or other community groups. Time-series analysis showed that program implementation corresponded to a significant decrease in overall levels of violence by more than 16 incidents on average per month, a decrease of 16 assaults on average per month, and resulted in a significant increase of 3.2 shootings on average per month, controlling for the comparison areas and the trends in the data.