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The purpose of this paper is to illustrate the implementation of a web‐based platform integrating benchmarking and data envelopment analysis (DEA) for the Portuguese secondary schools.

The benchmarking platform is designed around a set of key performance indicators that are displayed using benchmarking graphs. These indicators are also aggregated through the methodology of DEA to provide a summary measure of performance.

The benchmarking platform developed enables schools to perform internal and external evaluation through a standard model that is based on indicators of school activities. It encourages schools' efforts of continuous improvement and increases society awareness regarding schools' context and results obtained.

The benchmarking platform can be useful for schools and general public. For the general public, there is a tool that allows the construction of user‐defined rankings online and benchmarking tools that allow the comparison of performance of a specific school with others. In addition to these features, schools have in the BESP platform a repository of historical data, and the possibility to see a set of graphs that show for some indicators their evolution over time.

This paper describes a breakthrough in the Portuguese education context. The BESP platform is the first in this context to combine DEA and benchmarking tools in a web‐based environment, designed to enable real‐time performance assessments.

In a context of international economic crisis the improvement in the efficiency and productivity of public services is seen as a way to maintain high-quality levels at lower costs. Increased productivity can be promoted through benchmarking exercises, where key performance indicators (KPIs), individually or aggregated, are used to compare health units. The purpose of this paper is to describe a benchmarking platform, called Hospital Benchmarking (HOBE), where hospital’s services are used as the unit of analysis.

HOBE platform includes a set of managerial indicators through which hospital services’ are compared. The platform also benchmarks services through aggregate service indicators, and provides an aggregate measure of hospital’s performance based on a composite indicator of the service’s performances. These aggregate indicators were obtained through data envelopment analysis (DEA).

Some results are presented for Portuguese hospitals for the trial years of 2008 and 2009, for which data is publicly available. Details for the service-level analysis are provided for a sample hospital, as well as details on the aggregate performance resulting from services performances.

HOBE’s features and outcomes show that the platform can be used to guide management actions and to support the design of health policies by administrative authorities, provided that good quality and timely data are available, and that hospitals are involved in the design of the KPIs.

The platform is innovative in the sense that it bases its analysis on hospital’s services, which are in general more comparable among hospitals than indicators of hospital overall performance. In addition, it makes use of DEA to aggregate performance indicators, allowing for user choice in the inputs and outputs to be aggregated, and it proposes a novel model to aggregate service’s efficiencies into a single measure of hospital performance.

This study examines the relationship between the innovation ecosystem and performance measurement models. Although the innovation ecosystem and measurement models are widely recognized, the existing literature lacks a comprehensive understanding of the relationship between the proposed themes. Furthermore, it does not reveal how studies can be grouped to propose a thematic typology of the relationship.

The authors present a systematic literature review conducted in the Web of Science and Scopus databases, from a textual corpus that aided the proposition of the typology that aims to provide answers regarding the addressed themes.

The results of this review are based on a total of sixty peer-reviewed articles from the innovation ecosystem literature and performance measurement models between 1995 and 2020. The results make several contributions to the literature. First, by integrating evidence from empirical studies, the authors identified a typology formed by three classes: (1) ecosystem agents (2) analytical focus and (3) structured measurement tools. Second, the authors verified the relationship between the themes and discovered the existence of gaps to be filled, with the proposition of three drivers. Third, the authors presented a comprehensive mapping of field studies with a descriptive analysis of the textual corpus.

The results of the research provide important implications for researchers, managers and policy makers. Furthermore, the authors suggest directions for future research, including the need to examine the performance of the entire innovation ecosystem, integrating the different agents that exist for performance measurement.