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In an era where environmental and social pressures on companies are increasing, sustainable supply chain management is essential for the efficient operation and survivability of the organizations (members of the chain). Digital transformation and the adoption of new technologies could support the development of sustainable strategies, as they support supply chain processes, decrease operational costs, enable control and monitoring of operations and support green practices. The purpose of this paper is to explore the relationship between sustainable supply chain management and digital transformation through the adoption of specific technologies (Blockchain technology, big data analytics, internet of things). It aims at theory building and the development of a conceptual framework, enabling the explanation of under which circumstances the above combination could lead to the development of sustainable performances. It also aims to examine how companies can increase their competitive advantage and/or increase their business performance, contributing both to academics and practitioners. After conducting a literature review analysis, a significant gap was detected. There are a few studies providing theoretical approaches to examining all three pillars of sustainability, while at the same time analyzing the impact of big data analytics, internet of things and blockchain technology on the development of sustainable supply chains. Aiming to address this gap, this paper primarily conducts a literature review, identifies definitions and theories used to explain the different pillars of flexibility, and examines the effect of different technologies. It then develops a theoretical conceptual framework, which could enable both academics and practitioners to examine the impact of the adoption of different technologies on sustainable supply chain management. The findings of this research reveal that digital transformation plays an important role to companies, as the combination of different technologies may lead to the development of significant capabilities, increasing sustainable performances and enabling the development of sustainable strategies, which can improve companies’ position in the market.

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Sustainability, information systems (IS), and sustainable supply chain management (SSCM) are the main research areas of this study. In an era where environmental and social responsibility is becoming increasingly more important, SSCM is very significant for the survivability and competitiveness of organizations. Information systems may facilitate sustainable practices, as they support supply chain processes, decrease costs, and enable the control and monitoring of operations. The aim of this research is to explore the relationship between information systems and SSCM and explain under what circumstances they could lead to competitive advantage or increase internal business performance. To analyze the above, the methodology comprises a literature review enabling the understanding and conceptualization of the main research constructs and revealing the gaps of previous research. It also comprises qualitative research based on a single-case study allowing an in-depth examination of the subject of study. The findings reveal that the use of information systems, combined with strong interorganizational relationships and collaboration, can support SSCM practices. They can bring important business advantages, such as improved business performance and increased customer loyalty, but not necessarily competitive advantage. The results of this research show that SSCM is a promising field of study, with prospects for future research.

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Background: No single test has shown to be an accurate predictor of difficult laryngoscopy. Aims: This study aims to evaluate the effectiveness of the ratio of the sternomental distance (SMD) in neutral and full neck extension position SMD ratio (SMDR) as a predictor of difficult laryngoscopy and any need of assisted intubation. Settings and Design: Prospective, double-blind pilot study. Materials and Methods: This study included 221 consecutive adult patients scheduled to undergo elective surgery under general anesthesia. Physical and airway characteristics, SMDR, difficult laryngoscopy (using Cormack/Lehane [C/L] scale), and any kind of assisted intubation were assessed. Statistical Analysis: The optimal cutoff point for SMDR was identified using receiver operating characteristic (ROC) analysis. The association between SMDR and the intubation method was evaluated through multiple logistic regression analysis. Results: A SMDR below 1.55 led in 33% of the cases to assisted intubation and 33%–53% of C/L III–IV glottic views for McCoy and Macintosh blades, respectively. On the other hand, SMDR above 1.9 led to no C/L IV glottic views for both blades and 4% and 11% C/L III views glottic views for McCoy and Macintosh, respectively. The best sensitivity and specificity cutoff point as defined by the ROC curve was identified for an SMDR value of 1.7 (area[s] under the curve: 0.815; 95% confidence interval: 0.743–0.887). Assisted intubation rates were significantly higher in patients with an SMDR inferior to 1.7 (30.5% compared to 3.5%, P < 0.001). Conclusions: SMDR is a simple, objective, and easy to perform test. The present study indicates that SMDR may be helpful in predicting difficult laryngoscopy and assisted intubation.