Browsing by Author "Fogliatto, Flavio S."

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    Measuring the effect of Healthcare 4.0 implementation on hospitals' performance
    (2022) Tortorella, Guilherme Luz; Fogliatto, Flavio S.; Esposto, Kleber Francisco; Mac Cawley Vergara, Alejandro; Vassolo, Roberto; Tlapa Mendoza, Diego; Narayanamurthy, Gopalakrishnan
    In this study, we identify bundles of technologies and associated implementation barriers that could be viewed as part of Healthcare 4.0 (H4.0) and test their impact on performance improvement in a sample of hospitals. For that, we carried out a cross-sectional study with 181 leaders from hospitals in different countries that have already started H4.0 implementation. The collected data were analyzed using multivariate statistical techniques. Results indicate that H4.0 technologies could be organized into two different bundles according to their role within the hospital. Common barriers to H4.0 implementation were also empirically organized in two groups, following the sociotechnical systems theory. Bundles of H4.0 technologies presented a positive and significant effect on hospitals' performance. As their interaction with H4.0 barriers displayed a significant effect on performance improvement, it is important to concurrently consider H4.0 technologies and barriers. Our results allow hospital managers to anticipate potential issues in H4.0 implementation, enabling more assertive efforts to improve performance and deliver high-quality and low-cost care in the fourth industrial revolution era.
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    Modeling the impact of industry 4.0 base technologies on the development of organizational learning capabilities
    (2023) Tortorella, Guilherme Luz; Fogliatto, Flavio S.; Anzanello, Michel J.; Cawley Vergara, Alejandro Mac; Vassolo, Roberto; Garza-Reyes, Jose Arturo
    In this paper, we examine the impact of adopting Industry 4.0 (I4.0) base technologies on the development of seven learning dimensions used as proxies for organization learning capabilities. We conducted a grounded theory approach in which 129 practitioners from different manufacturing companies were surveyed, and their responses analyzed through multivariate techniques. Findings allowed us to raise a theoretical framework for explaining learning development in organizations undergoing I4.0 adoption. We identified three clusters of adopters: (i) beginners, (ii) in-transition, and (iii) advanced. We found an ascending learning trend in clusters (i) and (iii) and a stationary learning pattern in (ii). Our study advances the understanding of how learning capabilities are affected as organizations advance I4.0 adoption. Our findings also gauge expectations regarding the effects of I4.0 base technologies' adoption on learning capabilities, helping academics and practitioners anticipate potential issues and develop countermeasures accordingly.