Background The objective of this study was to assess public hospital efficiency, including quality outputs, inefficiency determinants, and changes to efficiency over time, in an Italian region. To achieve this aim, the study used secondary data from the Veneto region for the years 2018 and 2019. Methods A nonparametric approach—that is, multistage data envelopment analysis (DEA)—was applied to a sample of 43 hospitals. We identified three categories of input: capital investments (Beds), labor (FTE), operating expenses. We selected five efficiency outputs (outpatient visits, inpatients, outpatient visit revenue, inpatient revenue, bed occupancy rate) and two quality outputs (mortality rate and inappropriate admission rate). Efficiency scores were estimated and decomposed into two components. Slack analysis was then conducted. Further, DEA efficiency scores were regressed on internal and external variables using a Tobit model. Finally, the Malmquist Productivity Index was applied. Results On average, the hospitals in the Veneto region operated at more than 95% efficiency. Technical and scale inefficiencies often occurred jointly, with 77% of inefficient hospitals needing a downsizing strategy to gain efficiency. The inputs identified as needing significant reductions were full-time employee (FTE) administrative staff and technicians. The size of the hospital in relation to the size of the population served and the length of patient stay were important factors for the efficiency score. The major cause of decreased efficiency over time was technical change (0.908) rather than efficiency change (0.974). Conclusions The study reveals improvements that should be made from both the policy and managerial perspectives. Hospital size is an important feature of inefficiency. On average, the results show that it is advisable for hospitals to reorganize nonmedical staff to enhance efficiency. Further, increasing technology investment could enable higher efficiency levels.

Parametric and non-parametric frontier applications are typical for measuring the efficiency and productivity of many healthcare units. Due to the current COVID-19 pandemic, hospital efficiency is the center of academic discussions and the most desired target for many public authorities under limited resources. Investigating the state of the art of such applications and methodologies in the healthcare sector, besides uncovering strategical managerial prospects, can expand the scientific knowledge on the fundamental differences among efficiency models, variables and applications, drag research attention to the most attractive and recurrent concepts, and broaden a discussion on the specific theoretical and empirical gaps still to be addressed in future research agendas. This work offers a systematic bibliometric review to explore this complex panorama. Hospital efficiency applications from 1996 to 2022 were investigated from the Web of Science base. We selected 65 from the 203 most prominent works based on the Core Publication methodology. We provide core and general classifications according to the clinical outcome, bibliographic coupling of concepts and keywords highlighting the most relevant perspectives and literature gaps, and a comprehensive discussion of the most attractive literature and insights for building a research agenda in the field.

Certified B Corps (B Corps) are firms characterized by a hybrid purpose and a sustainable business model that combines profit with social impact. Prior quantitative studies on B Corps have mainly analyzed the impact of certification on firm performance, while only a few have tried to analyze the antecedents of certification or high sustainability performance. Regression models have been used in most cases, often with inconsistent results and some research limitations. The aim of this study is to test the presence of different possible combinations of firm-level antecedents leading to a high sustainability performance in B Corps. It applies a configurational approach and a qualitative comparative analysis methodology to search for different combinations of organizational factors (size, age, profitability, certification experience, women on board and the "Born B" factor) that lead to a high sustainability outcome, measured by a B Impact Assessment (BIA). Results indicate the existence of four configurations leading to a high BIA, representing as many kinds of impactful B Corps: Born B, small young ventures, small and medium enterprises, and large firms. These results contribute to the literature by showing that a high sustainability performance in B Corps can be reached through different paths (equifinality) entailing both high and low values of each factor (asymmetry) and depends on how factors are combined (conjunction) rather than on their single effect.

Nonprofits that compete for charitable contributions often question which are the most effective factors that lead to high levels of donations. To date, the research has been dominated by linear models mainly based on the economic model of giving, and has reported mixed and sometimes conflictual findings about the net effect of certain individual organization‐specific factors on donations. In this study, we introduce a configurational approach to explore how the factors considered by the economic model of giving may be combined with each other in multiple configurations with the goal of obtaining high levels of donations. Applying fuzzy set qualitative comparative analysis, we focus on a sample of British community foundations and identify four combinations that lead these organizations to collect large amounts of charitable contributions. The results show that, whereas young foundations should rely on high levels of program spending and large amounts of online disclosure combined with, alternatively, efficiency or aggressive fundraising, old foundations should contain administrative costs and strengthen fundraising efforts while, alternatively, spending the most part of their resources on programs or disseminating large amounts of information through their public websites.

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