The Street-Level Organisation in-between Employer Needs and Client Needs: Creaming Users by Motivation in the Norwegian Employment and Welfare Service (NAV)

Employer engagement is increasingly emphasised in the context of efforts to bring more disadvantaged people into work. A new approach in the Norwegian Employment and Welfare Service (NAV) combines demand-side and supply-side measures in a ‘combined workplace-oriented approach’. Through qualitative interviews with frontline staff – including job coaches following the Supported Employment (SE) method – the paper examines the intermediary role of the street-level organisation (SLO) through the targeted use of SE methods directed at young users and employers. The findings suggest that young users are ‘creamed by motivation’ into the SE programme, which can be explained by the importance the SLO places: on maintaining inter-organisational relationships with employers, on job coaches’ performance goals and the need to uphold an organisational structure in the SLO that seemingly works efficient to shift caseloads of young unemployed into work. Hence, creaming is not specific to outsourcing but can also occur when insourcing employer engagement services into a public SLO. Although relational work directed at both employers and young clients is seen as the benefit of a combined workplace-oriented approach, it appears a rather flimsy foundation for successful ALMPs unless supported by more structural demand-side measures.

Phase-Structure in Conditional Simulation of Spatially Varying Ground Motion and Possible Influence on Structural Demand

Recorded ground motion is nonstationary in both intensity and frequency contents. Two methodologies were reported by the authors elsewhere for generating spatially varying ground motion (SVGM), namely, (i) auto-spectral density (ASD)-based framework, and (ii) evolutionary power-spectral density (EPSD)-based framework. While the former framework imparts nonstationarity through a uniform modulation (that accounts for nonstationarity only in intensities), the latter framework accounts for nonstationarity in both intensity and frequency contents. Reported EPSD-based framework was modeled through a decay function and a random component and was investigated only in the context of horizontal ground motion. Reported EPSD-based framework made two strong assumptions that need further investigation: (i) spatial variation of the random component was assumed to be frequency independent; and (ii) phase-structure of the ground excitation simulated around the reference station (with seed motion) was assumed to be same as that of the seed motion. This paper investigates the possible impact of these two assumptions on the simulated SVGM through appropriately revising the framework and introducing the phase-structure accordingly. Possible effects of the phase-structure on structural demand are investigated through an idealized long-span bridge. Revised EPSD-based framework is next assessed against the vertical recordings of SMART1 array along with the auto-spectral density (ASD) framework. Though spectral representation is nearly identical in both the frameworks, the acceleration time series simulated using the revised EPSD-based framework matches the recorded data better when compared with the ASD-based framework. Possible effect of spatially varying vertical ground motion on the seismic design is investigated through the same idealized bridge model. Significant increase in the demand of axial force in piers and mid-span moment in the deck are observed. Although these inferences are contingent on the idealized example considered for illustration, the spatially varying vertical ground motion is expected to contribute significantly to the seismic design of long-span bridges.

Digitization and Pre-Purchase Information: The Causal and Welfare Impacts of Reviews and Crowd Ratings

Digitization has led to many new creative products, straining the capacity of professional critics and consumers. Yet, the digitization of retailing has also delivered new crowd-based sources of pre-purchase information. We compare the relative impacts of professional critics and crowd-based Amazon star ratings on consumer welfare in book publishing. Using various fixed effects and discontinuity-based empirical strategies, we estimate their causal impacts on sales. We use these causal estimates to calibrate a structural demand model. The aggregate effect of star ratings on consumer surplus is, in our baseline estimates, more than ten times the effect of traditional review outlets. (JEL D83, L15, L81, L82)

Long-term loss assessment of coastal bridges from hurricanes incorporating overturning failure mode

Coastal highway bridge is an essential component of the transportation system but threatened by natural hazards such as hurricanes. Damaged highway bridges result in not only transportation disruption, but also tremendous financial, societal, and life loss. Therefore, vulnerability and loss assessments of bridges under hurricane events are becoming primary concerns for decision-makers. This study provides an elaborate framework to assess the vulnerability and long-term loss of coastal bridges subjected to hurricane hazards based on three-dimensional (3D) numerical analyses. A 3D Computational Fluid Dynamics (CFD) numerical model is established to investigate wave-bridge interaction and a Finite Element (FE) model is established for the bridge to calculate structural responses under wave impacts. Based on the numerical results, the effects of wave force and overturning moment on structural capacity are studied and a probabilistic vulnerability model is developed. Structural demand, capacity, and limit states are determined, respectively. Uncertainties associated with wave parameters, structural capacity, and material properties, and the resulting consequences are considered. Then, fragility curves are calculated, and long-term damage loss is assessed. The proposed approach can benefit the management and design of coastal bridges against the impacts of hurricane hazards.

Bike-Share Systems: Accessibility and Availability

The cities of Paris, London, Chicago, and New York (among many others) have set up bike-share systems to facilitate the use of bicycles for urban commuting. This paper estimates the impact of two facets of system performance on bike-share ridership: accessibility (how far the user must walk to reach stations) and bike-availability (the likelihood of finding a bicycle). We obtain these estimates from a structural demand model for ridership estimated using data from the Vélib’ system in Paris. We find that every additional meter of walking to a station decreases a user’s likelihood of using a bike from that station by 0.194% (±0.0693%), and an even more significant reduction at higher distances (>300 m). These estimates imply that almost 80% of bike-share usage comes from areas within 300 m of stations, highlighting the need for dense station networks. We find that a 10% increase in bike-availability would increase ridership by 12.211% (±1.097%), three-fourths of which comes from fewer abandonments and the rest of which comes from increased user interest. We illustrate the use of our estimates in comparing the effect of adding stations or increasing bike-availabilities in different parts of the city, at different times, and in evaluating other proposed improvements. This paper was accepted by Vishal Gaur, operations management.