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This paper aimed to contextualize the process of public hospital providing services, based on the measurement of the performance of Federal University Hospitals (HUFs) of Brazil, using the technique of multivariate statistics of principal component analysis.

This research presented a descriptive and quantitative character, as well as exploratory purpose and followed the inductive logic, being empirically structured in two stages, that is, the application of principal component analysis (PCA) in four healthcare performance dimensions; subsequently, the full reapplication of principal component analysis in the most highly correlated variables, in module, with the first three main components (PC1, PC2 and PC3).

From the principal component analysis, considering mainly component I, with twice the explanatory power of the second (PC2) and third components (PC3), it was possible to evidence the efficient or inefficient behavior of the HUFs evaluated through the production of medical residency, by specialty area. Finally, it was observed that the formation of two groups composed of seven and eight hospitals, that is, Groups II and IV shows that these groups reflect similarities with respect to the scores and importance of the variables for both hospitals’ groups.

Among the main limitations it was observed that there was incomplete data for some HUFs, which made it impossible to search for information to explain and better contextualize certain aspects. More specifically, a limited number of hospitals with complete information were dealt with for 60% of SIMEC/REHUF performance indicators.

The use of PCA multivariate technique was of great contribution to the contextualization of the performance and productivity of homogeneous and autonomous units represented by the hospitals. It was possible to generate a large quantity of information in order to contribute with assumptions to complement the decision-making processes in these organizations.

Development of public policies with emphasis on hospitals linked to teaching centers represented by university hospitals. This also involved the projection of improvements in the reach of the efficiency of the services of assistance to the public health, from the qualified formation of professionals, both to academy, as to clinical practice.

The originality of this paper for the scenarios of the Brazilian public health sector and academic area involved the application of a consolidated performance analysis technique, that is, PCA, obtaining a rich work in relation to the extensive exploitation of techniques to support decision-making processes. In addition, the sequence and the way in which the content, formed by object of study and techniques, has been organized, generates a particular scenario for the measurement of performance in hospital organizations.

Based on the resource orchestration perspective, this paper aims to examine whether family firms are more efficient in their collaboration for innovation process than non-family firms, considering different types of collaboration for innovation depending on the kind of partner.

This study empirically develops and tests the hypotheses based on a panel data sample of 14,937 firm-year observations from 1,867 Spanish manufacturing firms over the period 2007–2014, performing a Propensity Score Matching (Propensity score matching)-based analysis.

Results reveal that family firms outperform non-family firms, despite less collaboration and innovation inputs, thereby extending the ongoing debate surrounding the innovation efficiency of family firms. Family firms obtained better results through vertical collaborations for innovation, both in terms of product and process innovations. For horizontal collaborations, family firms only outperform their non-family counterparts in process innovation. When collaborating with universities and other research centers, there are no significant differences in the innovation outcomes between the two groups.

Recent literature points out that more research is needed to know when, how and under what circumstances family firms show superior innovative efficiency. This work empirically proves that family firms outperform non-family firms in collaboration for innovation. However, not all collaboration partners help family firms to reach this superior innovative efficiency. Family firms obtained better results just through vertical and horizontal collaborations.

The purpose of this study is to address a critical gap in the existing literature on business excellence implementation. While various studies have examined different aspects of business excellence, there is still a lack of comprehensive research on the optimal organizational excellence architecture (OEA) for an award-winning business excellence journey. The absence of a unified framework has led to inconsistent practices across organizations. The aim of this research based on data collected from 50 organizations across 17 countries is to address this gap and present a refined OEA model.

This study employed quantitative and qualitative data collection methods. Member organizations from the Global Excellence Model (GEM) Council participated through an online survey administered via the Qualtrics software platform. Quantitative data were analyzed using the SPSS and Microsoft Excel software tools, while content analysis techniques were applied to the qualitative data to gain detailed insights.

The findings refine and extend the OEA model. These contributions lead to a refined OEA definition and open avenues for future research, enriching the current understanding of BE implementation.

This study introduces a novel concept of OEA to the literature on business excellence implementation. The refined OEA model provides a fresh perspective on the critical components necessary for an award-winning business excellence journey. This research offers significant value to both practitioners and academics by presenting a unified approach to BE implementation, effectively addressing the previously identified gap in BE research.