Suchergebnisse

AbstractA growing number of digital platforms operate in a dual mode: running marketplaces for third‐party products, while selling their own products on those marketplaces. We build a model to explore the implications of this controversial practice. We analyze the tradeoffs that arise from a regulatory ban on the dual mode, showing how such a ban can harm consumer surplus and welfare even when the platform would otherwise engage in product imitation and self‐preferencing. In the empirically most relevant scenarios, policies that prevent platform imitation and self‐preferencing generate better outcomes than an outright ban on the dual mode.

Introduction: Many strategies have been implemented to address the shortage of medical practitioners in rural areas. One such strategy, the Rural Clinical School Program supporting 18 rural clinical schools (RCSs), represents a substantial financial investment by the Australian Government. This is the first collaborative RCS study summarising the rural work outcomes of multiple RCSs. The aim of this study was to combine data from all RCSs' 2011 graduating classes to determine the association between rural location of practice in 2017 and (i) extended rural clinical placement during medical school (at least 12 months training in a rural area) and (ii) having a rural background. Methods: All medical schools funded under the RCS Program were contacted by email about participation in this study. Deidentified data were supplied for domestic students about their gender, origin (rural background defined as having lived in an Australian Standard Geographic Classification-Remoteness Area (ASGC-RA) 2-5 area for at least 5 years since beginning primary school) and participation in extended rural clinical placement (attended an RCS for at least 1 year of their clinical training). The postcode of their practice location according to the publicly available Australian Health Practitioner Regulation Agency (AHPRA) register was collected (February to August 2017) and classified into rural and metropolitan areas using the ASGC 2006 and the more recent Modified Monash Model (MMM). The main outcome measure was whether graduates were working in a 'rural' area (ASGC categories RA2-5 or MMM categories 3-7) or 'metropolitan' area. Pearson's χ 2 test was used to detect differences in gender, rural background and extended placement at an RCS between rural and metropolitan practice locations. Binary logistic regression was used to determine odds of rural practice and 95% confidence intervals (CIs) were calculated. Results: Although data were received from 14 universities, two universities had not started collecting origin data at this ...