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Green approaches remain little disseminated in the healthcare sector despite growing interest in recent years from practitioners and researchers. Big Data Analytics Capability (BDAC) can play a critical role in the integration of environmental concerns into operations and supply chain management (OSCM) and further strengthen the environmental performance of healthcare facilities. According to the literature, the integration of the environment into operations process remains insufficient to achieve high levels of performance and requires efforts in green process innovation. However, this relationship between BDAC and green process innovation remains poorly justified empirically. To address this theoretical gap, we investigated the relationship between BDAC, environmental process integration, green process innovation in OSCM and environmental performance. The main contribution of this study is the valuable knowledge on how BDAC influences environmental process integration and green process innovation to enhance environmental performance. Moreover, the study highlights the mediating role of green process innovation on environmental performance, a finding that has not been mentioned in the extant literature. The paper provides valuable insight for managers and stakeholders that can assist them in supporting the application of BDAC in healthcare OSCM to create sustainable value.

This article examines the entrepreneurial dimension in local authorities. We use intervention research conducted at the Lorraine Regional Council in France (Conseil Régional de Lorraine), which decided to develop its health care and biotechnologies network, to show that the notion of entrepreneurial orientation is highly relevant in the local authority context. We also conclude that while this particular local authority demonstrates a tendency for innovativeness, proactiveness and risk-taking, the social dimension is a key feature of its entrepreneurial orientation, and consequently argue that particular attention be paid to this feature.

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Primary Immunodeficiencies (PIDs) are associated with more than 400 rare monogenic diseases affecting various biological functions (e.g., development, regulation of the immune response) with a heterogeneous clinical expression (from no symptom to severe manifestations). To better understand PIDs, the ATRACTion project aims to perform a multi-omics analysis of PIDs cases versus a control group patients, including single-cell transcriptomics, epigenetics, proteomics, metabolomics, metagenomics and lipidomics. In this study, our goal is to develop a common data model integrating clinical and omics data, which can be used to obtain standardized information necessary for characterization of PIDs patients and for further systematic analysis. For that purpose, we extend the OMOP Common Data Model (CDM) and propose a multi-omics ATRACTion OMOP-CDM to integrate multi-omics data. This model, available for the community, is customizable for other types of rare diseases (https://framagit.org/imagine-plateforme-bdd/pub-rhu4-atraction).