Authors:Ágnes Lublóy, Judit Lilla Keresztúri, and Gábor Benedek
This article studies the determinants of pharmaceutical innovation diffusion among specialists. To this end, it investigates the infl uences of six categories of factors—social embeddedness, socio-demography, scientifi c orientation, prescribing patterns, practice characteristics, and patient panel composition—on the use of 11 new drugs for the treatment of type 2 diabetes mellitus in Hungary. The Cox proportional hazards model identifi es three determinants—social contagion (in the social embeddedness category) and prescribing portfolio and insulin prescribing ratio (in the prescribing pattern category). First, social contagion has a positive effect among geographically close colleagues—the higher the adoption ratio, the higher the likelihood of early adoption—but no infl uence among former classmates and scientifi c collaborators. Second, the wider the prescribing portfolio, the earlier the new drug uptake. Third, the lower the insulin prescribing ratio, the earlier the new drug uptake—physicians’ therapeutic convictions and patients’ socioeconomic statuses act as underlying infl uencers. However, this fi nding does not extend to opinion-leading physicians such as scientifi c leaders and hospital department and outpatient center managers. This article concludes by arguing that healthcare policy strategists and pharmaceutical companies may rely exclusively on practice location and prescription data to perfect interventions and optimize budgets.
The severity and frequency of operational loss events show high variability across the globe. In this paper, we first examine the extent to which the quality of country-level governance measured by the Worldwide Governance Indicators explains cross-country variation of operational losses. We use the comprehensive database of SAS OpRisk Global for the period of 2008–2019 covering 132 countries and 8,144 loss events with a total loss amount of almost 490 billion USD. Our findings indicate that the governance indicators lost their explanatory power over the past decades, which contradicts the academic consensus and calls for new explanatory variables. To find these variables, we hypothesize that the changes are driven by some important megatrends such as economic development and technological advancement, globalization, and sustainability. Accordingly, we propose an extended model where the number of mobile subscribers, the export to GDP ratio, and the poverty headcount ratio were significant for the frequency. For severity, only GDP is a significant and robust explanatory variable. Investors, regulators, and analysts should, therefore, concentrate on these factors if they wish to model, manage, or mitigate operational risks.