Argues that operations strategy research should integrate recent theories from the resource‐based view of strategic management. Going beyond the model of Hayes and Wheelwright, this would call for the end of the market‐based view, where operations strategy merely follows the directions set by the marketing function. It would emphasize the dynamic development and leveraging of competencies and capabilities in order to set new business diversification strategies. A new paradigm of operations strategy could emerge, where “management fundamentals” such as learning and culture would be actively integrated within operations, in order to become key sources of competitive advantage. Accordingly, the operations function could progressively: take the leadership of strategy formulation; create “portfolios” of optional capabilities for strategies of organizational agility; and implement world‐class practices more effectively through evolutionary strategic frameworks.

Both public and private hospitals are increasingly under pressure to reduce costs while improving patient care across all medical disciplines and departments. Hospitals must become patient-oriented, lean, and agile in order to properly realign and integrate health care processes, helping to reconcile efficiency imperatives with patient needs and hospital mission. One of the highest potential for improvement can be found in supply chain management (SCM) practices for medical supplies, which often represent more than 40% of a hospital’s operating budget. We report on 3 case studies of business process management and reengineering projects, relying on advanced information technology, focused on the supply chains of two major urban hospitals, involving $2 million in minimum stocks for drug inventory. Case study 1 deals with an in-depth analysis of SCM practices around a key medical asset in pharmaceutical supply, i.e. infusion pumps. Case study 2 builds upon the findings of case 1, and proposes an radio-frequency identification solution to support a new hospital-wide asset location process and system, aiming for just-in-time availability of infusion pumps for critical drugs administration. Case study 3 complements cases 1 and 2 by analysing the feasibility of integrating the various components of the hospital pharmacy inventories, which in turn could be integrated to asset location systems. Our 3 case studies lead us to a number of conclusions on how hospitals can develop a patient-oriented, agile, and lean perspectives and practices, as well as ensure the proper integration of patient needs within optimised supply chains.

Healthcare is considered as one of the most promising application areas for artificial intelligence and analytics (AIA) just after the emergence of the latter. AI combined to analytics technologies is increasingly changing medical practice and healthcare in an impressive way using efficient algorithms from various branches of information technology (IT). Indeed, numerous works are published every year in several universities and innovation centers worldwide, but there are concerns about progress in their effective success. There are growing examples of AIA being implemented in healthcare with promising results. This review paper summarizes the past 5 years of healthcare applications of AIA, across different techniques and medical specialties, and discusses the current issues and challenges, related to this revolutionary technology. A total of 24,782 articles were identified. The aim of this paper is to provide the research community with the necessary background to push this field even further and propose a framework that will help integrate diverse AIA technologies around patient needs in various healthcare contexts, especially for chronic care patients, who present the most complex comorbidities and care needs.

Purpose: The purpose of this paper is to provide a portrait of the main managerial and organizational determinants of organizational capability to innovate (OCI). Despite its importance, research on the subject seems limited, and little attempt has been made, over the years, to offer an in-depth and simultaneous analysis of these particular determinants, as well as an exploration of the underlying and complex mechanisms explaining their relationships to OCI.Design/methodology/approach: A systematic review of articles published between 1991 and 2018 was conducted in ProQuest (ABI/INFORM Collection) and Scopus databases. A total of 64 articles were selected and analysed through the use of a coding grid.Findings: Results highlight five key OCI determinants, namely: leadership, support, communication, culture, and learning. By using the dynamic capabilities theory (DCT) as a framework, this research suggests ways to better understand the dynamic action of these determinants as well as their contributions to OCI. Findings also suggest that OCI should be defined at the confluence of three perspectives (human, procedural and environmental aspects) to embrace the multiple facets of this complex construct. Proposals for future research are provided on how OCI can be better examined.Originality/value: This research helps to understand the five core determinants through an integrated and holistic view and represents the first attempt to systematically analyse the scientific literature on OCI through the DCT lens.

Objective: We present a novel seismocardiography (SCG) -based approach for real-time cardio-respiratory activity measurement called the Autocorrelated Differential Algorithm (ADA). Methods: Measurements were performed on ten male subjects in the supine position for three 7-minute-long sets each, corresponding to 14,619 heartbeats. The ADA utilized temporal variations, windowing, and autocorrelation to produce physiological measurements corresponding to heart rate (HR), and left ventricular ejection time, and estimations of respiration rate, volume, and phase. The versatility of the ADA was investigated in two contexts: physical exertion and heart rate variability. Results: The accuracy of HR measurements at a sampling frequency of 200 Hz resulted in a correlation coefficient (r 2 ) of 0.9808 when compared with a manual annotation of all datasets. Its reproducibility was tested on externally obtained SCG and electrocardiography datasets, which produced an r 2 of 0.8224. The accuracy and computational time was also characterized for different sampling frequencies to quantify performance. The recommended sampling frequency is 200 Hz corresponding to a computation time of 0.05 s per instantaneous measurement using a standard desktop computer. Conclusion: The ADA delivered real-time SCG measurements with a refresh rate that was dependent on the computational time per measurement, which could be decreased by lowering the sampling frequency. Significance: The presented algorithm offers a novel tool towards real-time physiological monitoring in clinical and everyday scenarios.