34 results on '"Alaimo Di Loro, P."'
Search Results
2. Semi-parametric Spatio-Temporal Hawkes Process for Modelling Road Accidents in Rome
- Author
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Alaimo Di Loro, Pierfrancesco, Mingione, Marco, and Fantozzi, Paolo
- Published
- 2024
- Full Text
- View/download PDF
3. 2-step Gradient Boosting approach to selectivity bias correction in tax audit: an application to the VAT gap in Italy
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Alaimo Di Loro, Pierfrancesco, Scacciatelli, Daria, and Tagliaferri, Giovanna
- Published
- 2023
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- View/download PDF
4. Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations
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Sherratt, K., Gruson, H., Grah, R., Johnson, H., Niehus, R., Prasse, B., Sandmann, F., Deuschel, J., Wolffram, D., Abbott, S., Ullrich, A., Gibson, G., Ray, E. L., Reich, N. G., Sheldon, D., Wang, Y., Wattanachit, N., Wang, L., Trnka, J., Obozinski, G., Sun, T., Thanou, D., Pottier, L., Krymova, E., Meinke, J. H., Barbarossa, M. V., Leithäuser, N., Mohring, J., Schneider, J., Wlazlo, J., Fuhrmann, J., Lange, B., Rodiah, I., Baccam, P., Gurung, H., Stage, S., Suchoski, B., Budzinski, J., Walraven, R., Villanueva, I., Tucek, V., Smíd, M., Zajícek, M., Pérez Alvarez, C., Reina, B., Bosse, N. I., Meakin, S., Castro, L., Fairchild, G., Michaud, I., Osthus, D., Alaimo Di Loro, P., Maruotti, A., Eclerová, V., Kraus, A., Kraus, D., Pribylova, L., Dimitris, B., Li, M. L., Saksham, S., Dehning, J., Mohr, S., Priesemann, V., Redlarski, G., Bejar, B., Ardenghi, G., Parolini, N., Ziarelli, G., Bock, Wolfgang, Heyder, S., Hotz, T., E. Singh, D., Guzman-Merino, M., Aznarte, J. L., Moriña, D., Alonso, S., Alvarez, E., López, D., Prats, C., Burgard, J. P., Rodloff, A., Zimmermann, T., Kuhlmann, A., Zibert, J., Pennoni, F., Divino, F., Català, M., Lovison, G., Giudici, P., Tarantino, B., Bartolucci, F., Jona Lasinio, G., Mingione, M., Farcomeni, A., Srivastava, A., Montero-Manso, P., Adiga, A., Hurt, B., Lewis, B., Marathe, M., Porebski, P., Venkatramanan, S., Bartczuk, R., Dreger, F., Gambin, A., Gogolewski, K., Gruziel-S?omka, M., Krupa, B., Moszynski, A., Niedzielewski, K., Nowosielski, J., Radwan, M., Rakowski, F., Semeniuk, M., Szczurek, E., Zieli?ski, J., Kisielewski, J., Pabjan, B., Kheifetz, Y., Kirsten, H., Scholz, M., Biecek, P., Bodych, M., Filinski, M., Idzikowski, R., Krueger, T., Ozanski, T., Bracher, J., Funk, S., Sherratt, K., Gruson, H., Grah, R., Johnson, H., Niehus, R., Prasse, B., Sandmann, F., Deuschel, J., Wolffram, D., Abbott, S., Ullrich, A., Gibson, G., Ray, E. L., Reich, N. G., Sheldon, D., Wang, Y., Wattanachit, N., Wang, L., Trnka, J., Obozinski, G., Sun, T., Thanou, D., Pottier, L., Krymova, E., Meinke, J. H., Barbarossa, M. V., Leithäuser, N., Mohring, J., Schneider, J., Wlazlo, J., Fuhrmann, J., Lange, B., Rodiah, I., Baccam, P., Gurung, H., Stage, S., Suchoski, B., Budzinski, J., Walraven, R., Villanueva, I., Tucek, V., Smíd, M., Zajícek, M., Pérez Alvarez, C., Reina, B., Bosse, N. I., Meakin, S., Castro, L., Fairchild, G., Michaud, I., Osthus, D., Alaimo Di Loro, P., Maruotti, A., Eclerová, V., Kraus, A., Kraus, D., Pribylova, L., Dimitris, B., Li, M. L., Saksham, S., Dehning, J., Mohr, S., Priesemann, V., Redlarski, G., Bejar, B., Ardenghi, G., Parolini, N., Ziarelli, G., Bock, Wolfgang, Heyder, S., Hotz, T., E. Singh, D., Guzman-Merino, M., Aznarte, J. L., Moriña, D., Alonso, S., Alvarez, E., López, D., Prats, C., Burgard, J. P., Rodloff, A., Zimmermann, T., Kuhlmann, A., Zibert, J., Pennoni, F., Divino, F., Català, M., Lovison, G., Giudici, P., Tarantino, B., Bartolucci, F., Jona Lasinio, G., Mingione, M., Farcomeni, A., Srivastava, A., Montero-Manso, P., Adiga, A., Hurt, B., Lewis, B., Marathe, M., Porebski, P., Venkatramanan, S., Bartczuk, R., Dreger, F., Gambin, A., Gogolewski, K., Gruziel-S?omka, M., Krupa, B., Moszynski, A., Niedzielewski, K., Nowosielski, J., Radwan, M., Rakowski, F., Semeniuk, M., Szczurek, E., Zieli?ski, J., Kisielewski, J., Pabjan, B., Kheifetz, Y., Kirsten, H., Scholz, M., Biecek, P., Bodych, M., Filinski, M., Idzikowski, R., Krueger, T., Ozanski, T., Bracher, J., and Funk, S.
- Abstract
Methods: We used open-source tools to develop a public European COVID-19 Forecast Hub. We invited groups globally to contribute weekly forecasts for COVID-19 cases and deaths reported by a standardised source for 32 countries over the next 1–4 weeks. Teams submitted forecasts from March 2021 using standardised quantiles of the predictive distribution. Each week we created an ensemble forecast, where each predictive quantile was calculated as the equally-weighted average (initially the mean and then from 26th July the median) of all individual models’ predictive quantiles. We measured the performance of each model using the relative Weighted Interval Score (WIS), comparing models’ forecast accuracy relative to all other models. We retrospectively explored alternative methods for ensemble forecasts, including weighted averages based on models’ past predictive performance. Results: Over 52 weeks, we collected forecasts from 48 unique models. We evaluated 29 models’ forecast scores in comparison to the ensemble model. We found a weekly ensemble had a consistently strong performance across countries over time. Across all horizons and locations, the ensemble performed better on relative WIS than 83% of participating models’ forecasts of incident cases (with a total N=886 predictions from 23 unique models), and 91% of participating models’ forecasts of deaths (N=763 predictions from 20 models). Across a 1–4 week time horizon, ensemble performance declined with longer forecast periods when forecasting cases, but remained stable over 4 weeks for incident death forecasts. In every forecast across 32 countries, the ensemble outperformed most contributing models when forecasting either cases or deaths, frequently outperforming all of its individual component models. Among several choices of ensemble methods we found that the most influential and best choice was to use a median average of models instead of using the mean, regardless of methods of weighting component forecast mod
- Published
- 2023
- Full Text
- View/download PDF
5. Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations
- Author
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Sherratt, K, Gruson, H, Grah, R, Johnson, H, Niehus, R, Prasse, B, Sandmann, F, Deuschel, J, Wolffram, D, Abbott, S, Ullrich, A, Gibson, G, L Ray, E, G Reich, N, Sheldon, D, Wang, Y, Wattanachit, N, Wang, L, Trnka, J, Obozinski, G, Sun, T, Thanou, D, Pottier, L, Krymova, E, H Meinke, J, Vittoria Barbarossa, M, Leithäuser, N, Mohring, J, Schneider, J, Włazło, J, Fuhrmann, J, Lange, B, Rodiah, I, Baccam, P, Gurung, H, Stage, S, Suchoski, B, Budzinski, J, Walraven, R, Villanueva, I, Tucek, V, Smid, M, Zajíček, M, Pérez Álvarez, C, Reina, B, I Bosse, N, R Meakin, S, Castro, L, Fairchild, G, Michaud, I, Osthus, D, Alaimo Di Loro, P, Maruotti, A, Eclerová, V, Kraus, A, Kraus, D, Pribylova, L, Dimitris, B, Lingzhi Li, M, Saksham, S, Dehning, J, Mohr, S, Priesemann, V, Redlarski, G, Bejar, B, Ardenghi, G, Parolini, N, Ziarelli, G, Bock, W, Heyder, S, Hotz, T, E Singh, D, Guzman-Merino, M, L Aznarte, J, Moriña, D, Alonso, S, Álvarez, E, López, D, Prats, C, Pablo Burgard, J, Rodloff, A, Zimmermann, T, Kuhlmann, A, Zibert, J, Pennoni, F, Divino, F, Català, M, Lovison, G, Giudici, P, Tarantino, B, Bartolucci, F, Jona Lasinio, G, Mingione, M, Farcomeni, A, Srivastava, A, Montero-Manso, P, Adiga, A, Hurt, B, Lewis, B, Marathe, M, Porebski, P, Venkatramanan, S, P Bartczuk, R, Dreger, F, Gambin, A, Gogolewski, K, Gruziel-Słomka, M, Krupa, B, Moszyński, A, Niedzielewski, K, Nowosielski, J, Radwan, M, Rakowski, F, Semeniuk, M, Szczurek, E, Zieliński, J, Kisielewski, J, Pabjan, B, Kirsten, H, Kheifetz, Y, Scholz, M, Biecek, P, Bodych, M, Filinski, M, Idzikowski, R, Krueger, T, Ozanski, T, Bracher, J, Funk, S, Katharine Sherratt, Hugo Gruson, Rok Grah, Helen Johnson, Rene Niehus, Bastian Prasse, Frank Sandmann, Jannik Deuschel, Daniel Wolffram, Sam Abbott, Alexander Ullrich, Graham Gibson, Evan L Ray, Nicholas G Reich, Daniel Sheldon, Yijin Wang, Nutcha Wattanachit, Lijing Wang, Jan Trnka, Guillaume Obozinski, Tao Sun, Dorina Thanou, Loic Pottier, Ekaterina Krymova, Jan H Meinke, Maria Vittoria Barbarossa, Neele Leithäuser, Jan Mohring, Johanna Schneider, Jaroslaw Włazło, Jan Fuhrmann, Berit Lange, Isti Rodiah, Prasith Baccam, Heidi Gurung, Steven Stage, Bradley Suchoski, Jozef Budzinski, Robert Walraven, Inmaculada Villanueva, Vit Tucek, Martin Smid, Milan Zajíček, Cesar Pérez Álvarez, Borja Reina, Nikos I Bosse, Sophie R Meakin, Lauren Castro, Geoffrey Fairchild, Isaac Michaud, Dave Osthus, Pierfrancesco Alaimo Di Loro, Antonello Maruotti, Veronika Eclerová, Andrea Kraus, David Kraus, Lenka Pribylova, Bertsimas Dimitris, Michael Lingzhi Li, Soni Saksham, Jonas Dehning, Sebastian Mohr, Viola Priesemann, Grzegorz Redlarski, Benjamin Bejar, Giovanni Ardenghi, Nicola Parolini, Giovanni Ziarelli, Wolfgang Bock, Stefan Heyder, Thomas Hotz, David E Singh, Miguel Guzman-Merino, Jose L Aznarte, David Moriña, Sergio Alonso, Enric Álvarez, Daniel López, Clara Prats, Jan Pablo Burgard, Arne Rodloff, Tom Zimmermann, Alexander Kuhlmann, Janez Zibert, Fulvia Pennoni, Fabio Divino, Marti Català, Gianfranco Lovison, Paolo Giudici, Barbara Tarantino, Francesco Bartolucci, Giovanna Jona Lasinio, Marco Mingione, Alessio Farcomeni, Ajitesh Srivastava, Pablo Montero-Manso, Aniruddha Adiga, Benjamin Hurt, Bryan Lewis, Madhav Marathe, Przemyslaw Porebski, Srinivasan Venkatramanan, Rafal P Bartczuk, Filip Dreger, Anna Gambin, Krzysztof Gogolewski, Magdalena Gruziel-Słomka, Bartosz Krupa, Antoni Moszyński, Karol Niedzielewski, Jedrzej Nowosielski, Maciej Radwan, Franciszek Rakowski, Marcin Semeniuk, Ewa Szczurek, Jakub Zieliński, Jan Kisielewski, Barbara Pabjan, Holger Kirsten, Yuri Kheifetz, Markus Scholz, Przemyslaw Biecek, Marcin Bodych, Maciej Filinski, Radoslaw Idzikowski, Tyll Krueger, Tomasz Ozanski, Johannes Bracher, Sebastian Funk, Sherratt, K, Gruson, H, Grah, R, Johnson, H, Niehus, R, Prasse, B, Sandmann, F, Deuschel, J, Wolffram, D, Abbott, S, Ullrich, A, Gibson, G, L Ray, E, G Reich, N, Sheldon, D, Wang, Y, Wattanachit, N, Wang, L, Trnka, J, Obozinski, G, Sun, T, Thanou, D, Pottier, L, Krymova, E, H Meinke, J, Vittoria Barbarossa, M, Leithäuser, N, Mohring, J, Schneider, J, Włazło, J, Fuhrmann, J, Lange, B, Rodiah, I, Baccam, P, Gurung, H, Stage, S, Suchoski, B, Budzinski, J, Walraven, R, Villanueva, I, Tucek, V, Smid, M, Zajíček, M, Pérez Álvarez, C, Reina, B, I Bosse, N, R Meakin, S, Castro, L, Fairchild, G, Michaud, I, Osthus, D, Alaimo Di Loro, P, Maruotti, A, Eclerová, V, Kraus, A, Kraus, D, Pribylova, L, Dimitris, B, Lingzhi Li, M, Saksham, S, Dehning, J, Mohr, S, Priesemann, V, Redlarski, G, Bejar, B, Ardenghi, G, Parolini, N, Ziarelli, G, Bock, W, Heyder, S, Hotz, T, E Singh, D, Guzman-Merino, M, L Aznarte, J, Moriña, D, Alonso, S, Álvarez, E, López, D, Prats, C, Pablo Burgard, J, Rodloff, A, Zimmermann, T, Kuhlmann, A, Zibert, J, Pennoni, F, Divino, F, Català, M, Lovison, G, Giudici, P, Tarantino, B, Bartolucci, F, Jona Lasinio, G, Mingione, M, Farcomeni, A, Srivastava, A, Montero-Manso, P, Adiga, A, Hurt, B, Lewis, B, Marathe, M, Porebski, P, Venkatramanan, S, P Bartczuk, R, Dreger, F, Gambin, A, Gogolewski, K, Gruziel-Słomka, M, Krupa, B, Moszyński, A, Niedzielewski, K, Nowosielski, J, Radwan, M, Rakowski, F, Semeniuk, M, Szczurek, E, Zieliński, J, Kisielewski, J, Pabjan, B, Kirsten, H, Kheifetz, Y, Scholz, M, Biecek, P, Bodych, M, Filinski, M, Idzikowski, R, Krueger, T, Ozanski, T, Bracher, J, Funk, S, Katharine Sherratt, Hugo Gruson, Rok Grah, Helen Johnson, Rene Niehus, Bastian Prasse, Frank Sandmann, Jannik Deuschel, Daniel Wolffram, Sam Abbott, Alexander Ullrich, Graham Gibson, Evan L Ray, Nicholas G Reich, Daniel Sheldon, Yijin Wang, Nutcha Wattanachit, Lijing Wang, Jan Trnka, Guillaume Obozinski, Tao Sun, Dorina Thanou, Loic Pottier, Ekaterina Krymova, Jan H Meinke, Maria Vittoria Barbarossa, Neele Leithäuser, Jan Mohring, Johanna Schneider, Jaroslaw Włazło, Jan Fuhrmann, Berit Lange, Isti Rodiah, Prasith Baccam, Heidi Gurung, Steven Stage, Bradley Suchoski, Jozef Budzinski, Robert Walraven, Inmaculada Villanueva, Vit Tucek, Martin Smid, Milan Zajíček, Cesar Pérez Álvarez, Borja Reina, Nikos I Bosse, Sophie R Meakin, Lauren Castro, Geoffrey Fairchild, Isaac Michaud, Dave Osthus, Pierfrancesco Alaimo Di Loro, Antonello Maruotti, Veronika Eclerová, Andrea Kraus, David Kraus, Lenka Pribylova, Bertsimas Dimitris, Michael Lingzhi Li, Soni Saksham, Jonas Dehning, Sebastian Mohr, Viola Priesemann, Grzegorz Redlarski, Benjamin Bejar, Giovanni Ardenghi, Nicola Parolini, Giovanni Ziarelli, Wolfgang Bock, Stefan Heyder, Thomas Hotz, David E Singh, Miguel Guzman-Merino, Jose L Aznarte, David Moriña, Sergio Alonso, Enric Álvarez, Daniel López, Clara Prats, Jan Pablo Burgard, Arne Rodloff, Tom Zimmermann, Alexander Kuhlmann, Janez Zibert, Fulvia Pennoni, Fabio Divino, Marti Català, Gianfranco Lovison, Paolo Giudici, Barbara Tarantino, Francesco Bartolucci, Giovanna Jona Lasinio, Marco Mingione, Alessio Farcomeni, Ajitesh Srivastava, Pablo Montero-Manso, Aniruddha Adiga, Benjamin Hurt, Bryan Lewis, Madhav Marathe, Przemyslaw Porebski, Srinivasan Venkatramanan, Rafal P Bartczuk, Filip Dreger, Anna Gambin, Krzysztof Gogolewski, Magdalena Gruziel-Słomka, Bartosz Krupa, Antoni Moszyński, Karol Niedzielewski, Jedrzej Nowosielski, Maciej Radwan, Franciszek Rakowski, Marcin Semeniuk, Ewa Szczurek, Jakub Zieliński, Jan Kisielewski, Barbara Pabjan, Holger Kirsten, Yuri Kheifetz, Markus Scholz, Przemyslaw Biecek, Marcin Bodych, Maciej Filinski, Radoslaw Idzikowski, Tyll Krueger, Tomasz Ozanski, Johannes Bracher, and Sebastian Funk
- Abstract
Background: Short-term forecasts of infectious disease contribute to situational awareness and capacity planning. Based on best practice in other fields and recent insights in infectious disease epidemiology, one can maximise forecasts’ predictive performance by combining independent models into an ensemble. Here we report the performance of ensemble predictions of COVID-19 cases and deaths across Europe from March 2021 to March 2022. Methods: We created the European COVID-19 Forecast Hub, an online open-access platform where modellers upload weekly forecasts for 32 countries with results publicly visualised and evaluated. We created a weekly ensemble forecast from the equally-weighted average across individual models’ predictive quantiles. We measured forecast accuracy using a baseline and relative Weighted Interval Score (rWIS). We retrospectively explored ensemble methods, including weighting by past performance. Results: We collected weekly forecasts from 48 models, of which we evaluated 29 models alongside the ensemble model. The ensemble had a consistently strong performance across countries over time, performing better on rWIS than 91% of forecasts for deaths (N=763 predictions from 20 models), and 83% forecasts for cases (N=886 predictions from 23 models). Performance remained stable over a 4-week horizon for death forecasts but declined with longer horizons for cases. Among ensemble methods, the most influential choice came from using a median average instead of the mean, regardless of weighting component models. Conclusions: Our results support combining independent models into an ensemble forecast to improve epidemiological predictions, and suggest that median averages yield better performance than methods based on means. We highlight that forecast consumers should place more weight on incident death forecasts than case forecasts at horizons greater than two weeks. Funding: European Commission, Ministerio de Ciencia, Innovación y Universidades, FEDER; Ag
- Published
- 2023
6. Adopting business models for sustainability and digitalization. A process study of microlevel dynamics in an incumbent firm.
- Author
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Michelini, Laura, Minà, Anna, Alaimo Di Loro, P, Heldt, Lisa, Peck, Philip, Michelini, Laura, Minà, Anna, Alaimo Di Loro, P, Heldt, Lisa, and Peck, Philip
- Abstract
Incumbent firms face growing pressure to transform their business towards sustainability. However, business models for sustainability (BMfS) and circularity are grounded in fundamentally different institutional logic which, for incumbents, creates tensions with existing business models, structures and routines. How organizations manage tensions from conflicting logics is explored comprehensively in research on hybrid organizations and sustainable entrepreneurship – however, focusing on ventures already founded with sustainability-oriented/hybrid missions. It is unclear if and how such logic hybridization processes unfold in incumbents and what role digitalization plays. This research aims to explore and explain microfoundations of how involved actors (struggle to) make sense of BMfS in incumbents and how this is underpinned by broader shifts towards hybrid organizational logics. This longitudinal case study takes a process view (Langley, 2007, 1999), following a large manufacturer’s Swedish division where a team works towards implementing a BMfS grounded in circularity and digitalization while facing doubt and inertia. Triangulating interviews, observations and documents, we track internal processes as they unfold in real-time to study how actors experience and rationalize the BMfS and navigate emerging tensions. Preliminary findings suggest that BMfS trigger diverging interpretations from different logics and therefore cause tensions. Overcoming these benefits from external impulses (e.g. customer or management communication that legitimizes new logic element), finding third-party common denominators (e.g. emphasize BMfS’ digitalization element) and continuous exposure. Upon completion, this research will provide a process model of how microlevel dynamics shape BMfS adoption, while opening for future research on hybridity intersecting with sustainable entrepreneurship literature.
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- 2022
7. Multi-actor business models in the manufacturing industry. Exploring how first-tier suppliers transition towards circularity.
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Michelini, Laura, Minà, Anna, Alaimo Di Loro, P, Forbicini, Martina, Heldt, Lisa, Michelini, Laura, Minà, Anna, Alaimo Di Loro, P, Forbicini, Martina, and Heldt, Lisa
- Abstract
Adopting circular business models (CBM) represents a key lever for industry to address urgent global challenges. Prior research recognizes the need for systems thinking and collaboration, but existing CBM tools and methods often implicitly assume that the focal firm has direct access to end customers, usage data and end-of-life phases. However, upstream suppliers who lack this access often produce key components of the final product – particularly in manufacturing – and could thus be an impactful actor in driving circular solutions. We therefore aim to explore and explain how non-end-user-facing manufacturers, i.e. first-tier suppliers, drive CBM adoption through their value chain and stakeholder partners, and how existing CBM archetypes need to be extended for these novel constellations. For this purpose, we conduct an action research case study with a Swedish first-tier manufacturer who is starting to develop CBMs for its marine engine product lines which are currently sold in a linear fashion through boat manufacturers and dealers to end users. Expected results include an extended CBM canvas that accounts for CBM archetypes based on more complex value chain and stakeholder collaborations. By exploring how companies further upstream in the value chain initiate and build CBMs, we aim to advance and bridge knowledge on multi-actor CBMs and circular supply chains. We thereby hope to invite more research into how non-traditional actors can drive circular industry transitions.
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- 2022
8. Filling Competency Gaps through Collaboration for Circularity : Insights from a gap exploiter business model
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Michelini, L, Minà, A, Alaimo Di Loro, P, Johnson, Emma, Michelini, L, Minà, A, Alaimo Di Loro, P, and Johnson, Emma
- Abstract
The implementation of circular initiatives requires certain capabilities and knowledge that traditional business models often lack, requiring new perspectives and external collaborations. This paper explores the competency needs and partnership dynamics of established companies collaborating for business model innovation for circularity through a case study of a gap exploiter business model, a company called GIAB, and three of its partners. Through the exploration of partner challenges and translation of such into specific needs, this paper matches GIAB’s competences to its partners’ circularity needs. Partners require key resources such as digital platforms, logistic networks, markets for reused goods, repair knowledge and skills, and collaborative values. These needs are provided through several collaboration mechanisms facilitated through information sharing that include joint planning, contractual practices, resource sharing and joint knowledge creation. GIAB’s value proposition to help partners to implement circular strategies is grounded in its configuration of competences that enables the capabilities needed to develop and facilitate circular solutions. The research provides a framework to identify and structure essential competences and associated capabilities for business model innovation for circularity. The examination of GIAB as a case study shows the value of a gap exploiter business model as a CBM itself, as well as a gap exploiter’s role in creating value by enabling other companies to implement circular initiatives.
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- 2022
9. Plastic Household Waste Valorization In Developing Countries: Critical design elements for a sustainable and circular business ecosystem
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Derks, Milou J.W., Romijn, H., Michelini, L., Minà, A., Alaimo Di Loro, P., Technology, Innovation & Society, and EIRES
- Subjects
circular business models ,Africa ,waste ,SDG 8 - Decent Work and Economic Growth ,sustainable business models ,SDG 12 - Responsible Consumption and Production ,SDG 11 - Sustainable Cities and Communities - Published
- 2022
10. Circular Economy Ecosystem Coordination: A comparative study of two sectoral cases
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DiVito, Lori, Lubberink, Rob, Michelini, L., Minà, A, Alaimo Di Loro, P., Lectoraat Collaborative Innovation and Entrepreneurship, Centre for Economic Transformation (CET), and AMSIB (CEDIS)
- Abstract
Circular solutions require a systemic approach involving multiple actors within and across industrial sectors. This has implications for the structure and dynamics within geographically bounded entrepreneurial ecosystems. Actors within the entrepreneurial ecosystem assume the role of ‘system coordination’ but very little is known about this role. As circular solutions and transformations cannot be realized in isolation, a better understanding of this coordination role is pertinent, which actors perform it and the strategies they use to overcome challenges. We conduct a comparative study of two sectoral cases in the Netherlands. Our preliminary findings from the case on circular textiles shows that coordination is distributed among several and diverse ecosystem actors to close technical material flows, whereas our preliminary findings in agri-food show that coordination is concentrated among actors that explicitly assume the coordination role to close biological material flows. We intend to make novel contributions to the literature on circular economy business transformation and entrepreneurial ecosystems as well as provide insights on the system coordination role for policy makers and practitioners.
- Published
- 2022
11. Compositional analysis of fish communities in a fast-changing marine ecosystem
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Mingione, M., Alaimo Di Loro, P., Jona Lasinio, G., Martino, S., Colloca, F., Alessio Pollice, Nicola Salvati, Francesco Schirripa Spagnolo, Mingione, M., Alaimo Di Loro, P., Jona Lasinio, G., Martino, S., and Colloca, F.
- Published
- 2020
12. Model-based clustering for monitoring cetaceans population dynamics
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Panunzi, G., Caruso, G., Mingione, M., Alaimo di Loro, P., Moro, S., Bompiani, E., Lanfredi, C., Pace, D. S., Tardella, L., and Jona Lasinio, G.
- Subjects
Jolly-Seber model, capture-recapture analysis, wildlife population, finite mixture models ,capture-recapture analysis ,Jolly-Seber model ,wildlife population ,finite mixture models - Published
- 2021
13. Bayesian Population Size Estimation With a Single Sample
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Alaimo Di Loro, P. and Tardella, L.
- Subjects
pupulation size estimation ,single sample ,genetic markers ,bayesian ,dna - Published
- 2018
14. Spatio-temporal modelling of COVID-19 incident cases using Richards' curve: An application to the Italian regions.
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Mingione, Marco, Alaimo Di Loro, Pierfrancesco, Farcomeni, Alessio, Divino, Fabio, Lovison, Gianfranco, Maruotti, Antonello, and Lasinio, Giovanna Jona
- Abstract
We introduce an extended generalised logistic growth model for discrete outcomes, in which spatial and temporal dependence are dealt with the specification of a network structure within an Auto-Regressive approach. A major challenge concerns the specification of the network structure, crucial to consistently estimate the canonical parameters of the generalised logistic curve, e.g. peak time and height. We compared a network based on geographic proximity and one built on historical data of transport exchanges between regions. Parameters are estimated under the Bayesian framework, using Stan probabilistic programming language. The proposed approach is motivated by the analysis of both the first and the second wave of COVID-19 in Italy, i.e. from February 2020 to July 2020 and from July 2020 to December 2020, respectively. We analyse data at the regional level and, interestingly enough, prove that substantial spatial and temporal dependence occurred in both waves, although strong restrictive measures were implemented during the first wave. Accurate predictions are obtained, improving those of the model where independence across regions is assumed. [ABSTRACT FROM AUTHOR]
- Published
- 2022
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15. Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations
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Katharine Sherratt, Hugo Gruson, Rok Grah, Helen Johnson, Rene Niehus, Bastian Prasse, Frank Sandmann, Jannik Deuschel, Daniel Wolffram, Sam Abbott, Alexander Ullrich, Graham Gibson, Evan L Ray, Nicholas G Reich, Daniel Sheldon, Yijin Wang, Nutcha Wattanachit, Lijing Wang, Jan Trnka, Guillaume Obozinski, Tao Sun, Dorina Thanou, Loic Pottier, Ekaterina Krymova, Jan H Meinke, Maria Vittoria Barbarossa, Neele Leithäuser, Jan Mohring, Johanna Schneider, Jaroslaw Włazło, Jan Fuhrmann, Berit Lange, Isti Rodiah, Prasith Baccam, Heidi Gurung, Steven Stage, Bradley Suchoski, Jozef Budzinski, Robert Walraven, Inmaculada Villanueva, Vit Tucek, Martin Smid, Milan Zajíček, Cesar Pérez Álvarez, Borja Reina, Nikos I Bosse, Sophie R Meakin, Lauren Castro, Geoffrey Fairchild, Isaac Michaud, Dave Osthus, Pierfrancesco Alaimo Di Loro, Antonello Maruotti, Veronika Eclerová, Andrea Kraus, David Kraus, Lenka Pribylova, Bertsimas Dimitris, Michael Lingzhi Li, Soni Saksham, Jonas Dehning, Sebastian Mohr, Viola Priesemann, Grzegorz Redlarski, Benjamin Bejar, Giovanni Ardenghi, Nicola Parolini, Giovanni Ziarelli, Wolfgang Bock, Stefan Heyder, Thomas Hotz, David E Singh, Miguel Guzman-Merino, Jose L Aznarte, David Moriña, Sergio Alonso, Enric Álvarez, Daniel López, Clara Prats, Jan Pablo Burgard, Arne Rodloff, Tom Zimmermann, Alexander Kuhlmann, Janez Zibert, Fulvia Pennoni, Fabio Divino, Marti Català, Gianfranco Lovison, Paolo Giudici, Barbara Tarantino, Francesco Bartolucci, Giovanna Jona Lasinio, Marco Mingione, Alessio Farcomeni, Ajitesh Srivastava, Pablo Montero-Manso, Aniruddha Adiga, Benjamin Hurt, Bryan Lewis, Madhav Marathe, Przemyslaw Porebski, Srinivasan Venkatramanan, Rafal P Bartczuk, Filip Dreger, Anna Gambin, Krzysztof Gogolewski, Magdalena Gruziel-Słomka, Bartosz Krupa, Antoni Moszyński, Karol Niedzielewski, Jedrzej Nowosielski, Maciej Radwan, Franciszek Rakowski, Marcin Semeniuk, Ewa Szczurek, Jakub Zieliński, Jan Kisielewski, Barbara Pabjan, Holger Kirsten, Yuri Kheifetz, Markus Scholz, Przemyslaw Biecek, Marcin Bodych, Maciej Filinski, Radoslaw Idzikowski, Tyll Krueger, Tomasz Ozanski, Johannes Bracher, Sebastian Funk, Sherratt, K, Gruson, H, Grah, R, Johnson, H, Niehus, R, Prasse, B, Sandmann, F, Deuschel, J, Wolffram, D, Abbott, S, Ullrich, A, Gibson, G, L Ray, E, G Reich, N, Sheldon, D, Wang, Y, Wattanachit, N, Wang, L, Trnka, J, Obozinski, G, Sun, T, Thanou, D, Pottier, L, Krymova, E, H Meinke, J, Vittoria Barbarossa, M, Leithäuser, N, Mohring, J, Schneider, J, Włazło, J, Fuhrmann, J, Lange, B, Rodiah, I, Baccam, P, Gurung, H, Stage, S, Suchoski, B, Budzinski, J, Walraven, R, Villanueva, I, Tucek, V, Smid, M, Zajíček, M, Pérez Álvarez, C, Reina, B, I Bosse, N, R Meakin, S, Castro, L, Fairchild, G, Michaud, I, Osthus, D, Alaimo Di Loro, P, Maruotti, A, Eclerová, V, Kraus, A, Kraus, D, Pribylova, L, Dimitris, B, Lingzhi Li, M, Saksham, S, Dehning, J, Mohr, S, Priesemann, V, Redlarski, G, Bejar, B, Ardenghi, G, Parolini, N, Ziarelli, G, Bock, W, Heyder, S, Hotz, T, E Singh, D, Guzman-Merino, M, L Aznarte, J, Moriña, D, Alonso, S, Álvarez, E, López, D, Prats, C, Pablo Burgard, J, Rodloff, A, Zimmermann, T, Kuhlmann, A, Zibert, J, Pennoni, F, Divino, F, Català, M, Lovison, G, Giudici, P, Tarantino, B, Bartolucci, F, Jona Lasinio, G, Mingione, M, Farcomeni, A, Srivastava, A, Montero-Manso, P, Adiga, A, Hurt, B, Lewis, B, Marathe, M, Porebski, P, Venkatramanan, S, P Bartczuk, R, Dreger, F, Gambin, A, Gogolewski, K, Gruziel-Słomka, M, Krupa, B, Moszyński, A, Niedzielewski, K, Nowosielski, J, Radwan, M, Rakowski, F, Semeniuk, M, Szczurek, E, Zieliński, J, Kisielewski, J, Pabjan, B, Kirsten, H, Kheifetz, Y, Scholz, M, Biecek, P, Bodych, M, Filinski, M, Idzikowski, R, Krueger, T, Ozanski, T, Bracher, J, and Funk, S
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epidemiology ,global health ,none ,General Immunology and Microbiology ,General Neuroscience ,mathematical modeling ,COVID-19 ,infectious diseases forecatsting ,General Medicine ,udc:616 ,General Biochemistry, Genetics and Molecular Biology ,COVID-19, Countries Predictions, Infectious disease, Multivariate Statistical Models, Short-term forecasts ,udc:616-036.22:519.876.5 ,SECS-S/01 - STATISTICA ,infectious diseases forecatsting, epidemiology, mathematical modeling, capacity planning, COVID-19, combining independent models, ensemble forecast ,ensemble forecast ,Settore SECS-S/01 ,napovedovanje nalezljivih bolezni, epidemiologija, matematično modeliranje, načrtovanje zmogljivosti, COVID-19, kombiniranje neodvisnih modelov, skupna napoved ,ddc:600 ,capacity planning ,combining independent models - Abstract
eLife 12, e81916 (2023). doi:10.7554/eLife.81916, Background:Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields and recent insights in infectious disease epidemiology, one can maximise the predictive performance of such forecasts if multiple models are combined into an ensemble. Here, we report on the performance of ensembles in predicting COVID-19 cases and deaths across Europe between 08 March 2021 and 07 March 2022.Methods:We used open-source tools to develop a public European COVID-19 Forecast Hub. We invited groups globally to contribute weekly forecasts for COVID-19 cases and deaths reported by a standardised source for 32 countries over the next 1–4 weeks. Teams submitted forecasts from March 2021 using standardised quantiles of the predictive distribution. Each week we created an ensemble forecast, where each predictive quantile was calculated as the equally-weighted average (initially the mean and then from 26th July the median) of all individual models’ predictive quantiles. We measured the performance of each model using the relative Weighted Interval Score (WIS), comparing models’ forecast accuracy relative to all other models. We retrospectively explored alternative methods for ensemble forecasts, including weighted averages based on models’ past predictive performance.Results:Over 52 weeks, we collected forecasts from 48 unique models. We evaluated 29 models’ forecast scores in comparison to the ensemble model. We found a weekly ensemble had a consistently strong performance across countries over time. Across all horizons and locations, the ensemble performed better on relative WIS than 83% of participating models’ forecasts of incident cases (with a total N=886 predictions from 23 unique models), and 91% of participating models’ forecasts of deaths (N=763 predictions from 20 models). Across a 1–4 week time horizon, ensemble performance declined with longer forecast periods when forecasting cases, but remained stable over 4 weeks for incident death forecasts. In every forecast across 32 countries, the ensemble outperformed most contributing models when forecasting either cases or deaths, frequently outperforming all of its individual component models. Among several choices of ensemble methods we found that the most influential and best choice was to use a median average of models instead of using the mean, regardless of methods of weighting component forecast models.Conclusions:Our results support the use of combining forecasts from individual models into an ensemble in order to improve predictive performance across epidemiological targets and populations during infectious disease epidemics. Our findings further suggest that median ensemble methods yield better predictive performance more than ones based on means. Our findings also highlight that forecast consumers should place more weight on incident death forecasts than incident case forecasts at forecast horizons greater than 2 weeks., Published by eLife Sciences Publications, Cambridge
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- 2023
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16. Covid-19 in Italy: Modelling, Communications, and Collaborations
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Pierfrancesco Alaimo Di Loro, Divino, Fabio, Alessio, Farcomeni, Giovanna Jona Lasinio, Gianfranco, Lovison, Antonello, Maruotti, Marco, Mingione, Alaimo Di Loro, P., Divino, F., Farcomeni, A., Jona Lasinio, G., Lovison, G., Maruotti, A., and Mingione, M.
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Statistics and Probability ,COVID-19 ,statistical modelling ,Settore SECS-S/01 ,Settore SECS-S/01 - Statistica ,Richards generalised logistic curve - Abstract
When Covid-19 arrived in Italy in early 2020, a group of statisticians came together to provide tools to make sense of the unfolding epidemic and to counter misleading media narratives. Here, members of StatGroup-19 reflect on their work to date
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- 2022
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17. Filling Competency Gaps through Collaboration for Circularity : Insights from a gap exploiter business model
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Johnson, Emma, Michelini, L, Minà, A, and Alaimo Di Loro, P
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competences for circularity ,Business model innovation for sustainability ,gap exploiter business model ,collaboration ,circular capabilities ,Business Administration ,circular business model - Abstract
The implementation of circular initiatives requires certain capabilities and knowledge that traditional business models often lack, requiring new perspectives and external collaborations. This paper explores the competency needs and partnership dynamics of established companies collaborating for business model innovation for circularity through a case study of a gap exploiter business model, a company called GIAB, and three of its partners. Through the exploration of partner challenges and translation of such into specific needs, this paper matches GIAB’s competences to its partners’ circularity needs. Partners require key resources such as digital platforms, logistic networks, markets for reused goods, repair knowledge and skills, and collaborative values. These needs are provided through several collaboration mechanisms facilitated through information sharing that include joint planning, contractual practices, resource sharing and joint knowledge creation. GIAB’s value proposition to help partners to implement circular strategies is grounded in its configuration of competences that enables the capabilities needed to develop and facilitate circular solutions. The research provides a framework to identify and structure essential competences and associated capabilities for business model innovation for circularity. The examination of GIAB as a case study shows the value of a gap exploiter business model as a CBM itself, as well as a gap exploiter’s role in creating value by enabling other companies to implement circular initiatives.
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- 2022
18. Innovative business model implementing Value-Based Healthcare. The case of Medtronic Study & Scientific Solutions
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Toni M., Bartolini L., De Seta F., Grovale N., Mattia G., Pratesi C. A., Michelini L., Minà A., Alaimo Di Loro P. (eds), Toni, M., Bartolini, L., De Seta, F., Grovale, N., Mattia, G., and Pratesi, C. A.
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- 2022
19. Multi-actor business models in the manufacturing industry. Exploring how first-tier suppliers transition towards circularity
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Martina Forbicini, Lisa Heldt, Michelini, Laura, Minà, Anna, and Alaimo Di Loro, P
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First-tier supplier ,Value chain ,Circularity ,Collaboration ,Environmental Sciences ,Business Administration ,Business model - Abstract
Adopting circular business models (CBM) represents a key lever for industry to address urgent global challenges. Prior research recognizes the need for systems thinking and collaboration, but existing CBM tools and methods often implicitly assume that the focal firm has direct access to end customers, usage data and end-of-life phases. However, upstream suppliers who lack this access often produce key components of the final product – particularly in manufacturing – and could thus be an impactful actor in driving circular solutions. We therefore aim to explore and explain how non-end-user-facing manufacturers, i.e. first-tier suppliers, drive CBM adoption through their value chain and stakeholder partners, and how existing CBM archetypes need to be extended for these novel constellations. For this purpose, we conduct an action research case study with a Swedish first-tier manufacturer who is starting to develop CBMs for its marine engine product lines which are currently sold in a linear fashion through boat manufacturers and dealers to end users. Expected results include an extended CBM canvas that accounts for CBM archetypes based on more complex value chain and stakeholder collaborations. By exploring how companies further upstream in the value chain initiate and build CBMs, we aim to advance and bridge knowledge on multi-actor CBMs and circular supply chains. We thereby hope to invite more research into how non-traditional actors can drive circular industry transitions.
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- 2022
20. Hybrid partnerships in the system of International Development Cooperation
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Plinio Limata, Lucia Marchegiani, Grazia Sgarra, Plinio Limata, Lucia Marchegiani, Grazia Sgarra, Michelini L., Minà A., Alaimo Di Loro P., Limata, Plinio, Marchegiani, Lucia, and Sgarra, Grazia
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Development Cooperation, Inclusive Business, Inclusive Business Model, Human Resources, Sustainability - Abstract
The International Development Cooperation system has recently been enriched by opening the possibility for for-profit enterprises to contribute to achieving sustainable development goals through inclusive and sustainable entrepreneurial projects in the target countries of cooperation. However, the entrepreneurial system does not yet seem ready to take up the organizational challenges implicit in the "Profit for Development" paradigm: the creation of inclusive businesses and/or hybrid organizations to create shared value. Through the analysis of the projects presented to the Italian Agency for Development Cooperation, the article highlights the reality, rather distant from the myth. In particular, traditional enterprises still lack the mindset and required competencies to engage and manage hybrid partnerships that put together for-profit and not-forprofit organizations at both national and international levels. This is also testified by the conservative approach in human resources management (HRM) strategies and policies. The paper discusses the empirical results while offering a nove
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- 2022
21. Full throttle! Engaging ethnic minority and majority consumers in car sharing
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Marie-Julie De Bruyne, Katrien Verleye, Hendrik Slabbinck, Saskia Crucke, Michelini, L., Minà, A., and Alaimo Di Loro, P.
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Business and Economics ,Consumer engagement ,Perceived value ,Ethnic minorities ,General Medicine ,Sharing economy ,Trust - Abstract
The world is affected by environmental and social challenges, resulting in calls for engaging consumers with initiatives focused on sharing underutilized resources in Western countries. Meanwhile, these countries are characterized by migration and ethnic diversity, giving rise to ethnic minority consumers. Although ethnicity is a driver of consumer engagement, little is known about the influence of ethnicity on consumer engagement with sharing initiatives in Western countries. To address this gap, we examine the role of perceived value and trust for engaging ethnic minority (vs. majority) consumers with sharing initiatives by relying on survey data gathered in the Belgian car sharing context. The results suggest that ethnic minority consumers perceive more environmental value of car sharing than ethnic majority consumers, yet no differences are observed with regard to perceived economic and social value of car sharing. Meanwhile, ethnic minority consumers have less trust in car sharing than ethnic majority consumers. Moreover, perceived value and trust act as important mediating mechanisms for non-behavioral manifestations of consumer engagement but even more for behavioral manifestations of consumer engagement. From a theoretical perspective, this research advances the sharing economy literature and the literature on sustainable business models by unraveling the mechanisms for engaging ethnic minority and majority consumers with sharing initiatives. From a practical perspective, this research supports practitioners and policymakers to include ethnic minority and majority consumers in the transition to a more sustainable economy by exploring their engagement with sharing initiatives.
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- 2022
22. Nowcasting COVID‐19 incidence indicators during the Italian first outbreak
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Pierfrancesco Alaimo Di Loro, Alessio Farcomeni, Giovanna Jona Lasinio, Antonello Maruotti, Fabio Divino, Marco Mingione, Gianfranco Lovison, Alaimo Di Loro P., Divino F., Farcomeni A., Jona Lasinio G., Lovison G., Maruotti A., Mingione M., Alaimo Di Loro, Pierfrancesco, Divino, Fabio, Farcomeni, Alessio, Jona Lasinio, Giovanna, Lovison, Gianfranco, Maruotti, Antonello, and Mingione, Marco
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FOS: Computer and information sciences ,Statistics and Probability ,Nowcasting ,Epidemiology ,Computer science ,COVID-19, growth curves, Richards’ equation, SARS-CoV-2 ,COVID-19 ,growth curves ,Richards' equation ,SARS-CoV-2 ,Disease Outbreaks ,Humans ,Incidence ,Italy ,Statistics - Applications ,01 natural sciences ,SARS‐CoV‐2 ,010104 statistics & probability ,03 medical and health sciences ,0302 clinical medicine ,COVID‐19 ,Statistics ,Applications (stat.AP) ,030212 general & internal medicine ,0101 mathematics ,Research Articles ,Parametric statistics ,richards' equation ,External variable ,Disease Outbreak ,Estimation theory ,covid-19 ,sars-cov-2 ,Incidence (epidemiology) ,Outbreak ,Regression analysis ,Replicate ,Settore SECS-S/01 ,Settore SECS-S/01 - Statistica ,Research Article ,growth curve ,Human - Abstract
A novel parametric regression model is proposed to fit incidence data typically collected during epidemics. The proposal is motivated by real-time monitoring and short-term forecasting of the main epidemiological indicators within the first outbreak of COVID-19 in Italy. Accurate short-term predictions, including the potential effect of exogenous or external variables are provided. This ensures to accurately predict important characteristics of the epidemic (e.g., peak time and height), allowing for a better allocation of health resources over time. Parameter estimation is carried out in a maximum likelihood framework. All computational details required to reproduce the approach and replicate the results are provided. publishedVersion
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- 2021
23. Adopting business models for sustainability and digitalization. A process study of microlevel dynamics in an incumbent firm
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Lisa Heldt, Philip Peck, Michelini, Laura, Minà, Anna, and Alaimo Di Loro, P
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Sustainability ,Process study ,Hybridity ,Institutional logics ,Environmental Sciences ,Business Administration ,Business model - Abstract
Incumbent firms face growing pressure to transform their business towards sustainability. However, business models for sustainability (BMfS) and circularity are grounded in fundamentally different institutional logic which, for incumbents, creates tensions with existing business models, structures and routines. How organizations manage tensions from conflicting logics is explored comprehensively in research on hybrid organizations and sustainable entrepreneurship – however, focusing on ventures already founded with sustainability-oriented/hybrid missions. It is unclear if and how such logic hybridization processes unfold in incumbents and what role digitalization plays. This research aims to explore and explain microfoundations of how involved actors (struggle to) make sense of BMfS in incumbents and how this is underpinned by broader shifts towards hybrid organizational logics. This longitudinal case study takes a process view (Langley, 2007, 1999), following a large manufacturer’s Swedish division where a team works towards implementing a BMfS grounded in circularity and digitalization while facing doubt and inertia. Triangulating interviews, observations and documents, we track internal processes as they unfold in real-time to study how actors experience and rationalize the BMfS and navigate emerging tensions. Preliminary findings suggest that BMfS trigger diverging interpretations from different logics and therefore cause tensions. Overcoming these benefits from external impulses (e.g. customer or management communication that legitimizes new logic element), finding third-party common denominators (e.g. emphasize BMfS’ digitalization element) and continuous exposure. Upon completion, this research will provide a process model of how microlevel dynamics shape BMfS adoption, while opening for future research on hybridity intersecting with sustainable entrepreneurship literature.
24. Viral Hepatitis: Host Immune Interaction, Pathogenesis and New Therapeutic Strategies.
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Quirino A, Marascio N, Branda F, Ciccozzi A, Romano C, Locci C, Azzena I, Pascale N, Pavia G, Matera G, Casu M, Sanna D, Giovanetti M, Ceccarelli G, Alaimo di Loro P, Ciccozzi M, Scarpa F, and Maruotti A
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Viral hepatitis is a major cause of liver illness worldwide. Despite advances in the understanding of these infections, the pathogenesis of hepatitis remains a complex process driven by intricate interactions between hepatitis viruses and host cells at the molecular level. This paper will examine in detail the dynamics of these host-pathogen interactions, highlighting the key mechanisms that regulate virus entry into the hepatocyte, their replication, evasion of immune responses, and induction of hepatocellular damage. The unique strategies employed by different hepatitis viruses, such as hepatitis B, C, D, and E viruses, to exploit metabolic and cell signaling pathways to their advantage will be discussed. At the same time, the innate and adaptive immune responses put in place by the host to counter viral infection will be analyzed. Special attention will be paid to genetic, epigenetic, and environmental factors that modulate individual susceptibility to different forms of viral hepatitis. In addition, this work will highlight the latest findings on the mechanisms of viral persistence leading to the chronic hepatitis state and the potential implications for the development of new therapeutic strategies. Fully understanding the complex host-pathogen interactions in viral hepatitis is crucial to identifying new therapeutic targets, developing more effective approaches for treatment, and shedding light on the mechanisms underlying progression to more advanced stages of liver damage.
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- 2024
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25. A useful parametric specification to model epidemiological data: Revival of the Richards' curve.
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Mingione M, Alaimo Di Loro P, and Maruotti A
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- Humans, Likelihood Functions, Models, Statistical, Epidemics statistics & numerical data, Disease Outbreaks statistics & numerical data, Epidemiological Models, Epidemiologic Methods, Bayes Theorem
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A useful parametric specification for the expected value of an epidemiological process is revived, and its statistical and empirical efficacy are explored. The Richards' curve is flexible enough to adapt to several growth phenomena, including recent epidemics and outbreaks. Here, two different estimation methods are described. The first, based on likelihood maximisation, is particularly useful when the outbreak is still ongoing and the main goal is to obtain sufficiently accurate estimates in negligible computational run-time. The second is fully Bayesian and allows for more ambitious modelling attempts such as the inclusion of spatial and temporal dependence, but it requires more data and computational resources. Regardless of the estimation approach, the Richards' specification properly characterises the main features of any growth process (e.g. growth rate, peak phase etc.), leading to a reasonable fit and providing good short- to medium-term predictions. To demonstrate such flexibility, we show different applications using publicly available data on recent epidemics where the data collection processes and transmission patterns are extremely heterogeneous, as well as benchmark datasets widely used in the literature as illustrative., Competing Interests: Declaration of conflicting interestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
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- 2024
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26. Finite mixtures in capture-recapture surveys for modeling residency patterns in marine wildlife populations.
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Caruso G, Alaimo Di Loro P, Mingione M, Tardella L, Pace DS, and Jona Lasinio G
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- Animals, Animals, Wild, Bayes Theorem, Computer Simulation, Bottle-Nosed Dolphin, Internship and Residency
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This work aims to show how prior knowledge about the structure of a heterogeneous animal population can be leveraged to improve the abundance estimation from capture-recapture survey data. We combine the Open Jolly-Seber model with finite mixtures and propose a parsimonious specification tailored to the residency patterns of the common bottlenose dolphin. We employ a Bayesian framework for our inference, discussing the appropriate choice of priors to mitigate label-switching and nonidentifiability issues, commonly associated with finite mixture models. We conduct a series of simulation experiments to illustrate the competitive advantage of our proposal over less specific alternatives. The proposed approach is applied to data collected on the common bottlenose dolphin population inhabiting the Tiber River estuary (Mediterranean Sea). Our results provide novel insights into this population's size and structure, shedding light on some of the ecological processes governing its dynamics., (© 2024 The Authors. Biometrical Journal published by Wiley-VCH GmbH.)
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- 2024
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27. Virtual and Reality: A Neurophysiological Pilot Study of the Sarcophagus of the Spouses.
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Giorgi A, Menicocci S, Forte M, Ferrara V, Mingione M, Alaimo Di Loro P, Inguscio BMS, Ferrara S, Babiloni F, Vozzi A, Ronca V, and Cartocci G
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Art experience is not solely the observation of artistic objects, but great relevance is also placed on the environment in which the art experience takes place, often in museums and galleries. Interestingly, in the last few years, the introduction of some forms of virtual reality (VR) in museum contexts has been increasing. This has solicited enormous research interest in investigating any eventual differences between looking at the same artifact either in a real context (e.g. a museum) and in VR. To address such a target, a neuroaesthetic study was performed in which electroencephalography (EEG) and autonomic signals (heart rate and skin conductance) were recorded during the observation of the Etruscan artifact "Sarcophagus of the Spouses", both in the museum and in a VR reproduction. Results from EEG analysis showed a higher level of the Workload Index during observation in the museum compared to VR ( p = 0.04), while the Approach-Withdrawal Index highlighted increased levels during the observation in VR compared to the observation in the museum ( p = 0.03). Concerning autonomic indices, the museum elicited a higher Emotional Index response than the VR ( p = 0.03). Overall, preliminary results suggest a higher engagement potential of the museum compared to VR, although VR could also favour higher embodiment than the museum.
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- 2023
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28. Two years of COVID-19 pandemic: The Italian experience of Statgroup-19.
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Jona Lasinio G, Divino F, Lovison G, Mingione M, Alaimo Di Loro P, Farcomeni A, and Maruotti A
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The amount and poor quality of available data and the need of appropriate modeling of the main epidemic indicators require specific skills. In this context, the statistician plays a key role in the process that leads to policy decisions, starting with monitoring changes and evaluating risks. The "what" and the "why" of these changes represent fundamental research questions to provide timely and effective tools to manage the evolution of the epidemic. Answers to such questions need appropriate statistical models and visualization tools. Here, we give an overview of the role played by Statgroup-19, an independent Italian research group born in March 2020. The group includes seven statisticians from different Italian universities, each with different backgrounds but with a shared interest in data analysis, statistical modeling, and biostatistics. Since the beginning of the COVID-19 pandemic the group has interacted with authorities and journalists to support policy decisions and inform the general public about the evolution of the epidemic. This collaboration led to several scientific papers and an accrued visibility across various media, all made possible by the continuous interaction across the group members that shared their unique expertise., (© 2022 John Wiley & Sons Ltd.)
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- 2022
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29. Decreased severity of the Omicron variant of concern: further evidence from Italy.
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Divino F, Alaimo Di Loro P, Farcomeni A, Jona-Lasinio G, Lovison G, Ciccozzi M, Mingione M, and Maruotti A
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- Humans, Italy epidemiology, COVID-19, SARS-CoV-2
- Abstract
Competing Interests: Conflict of interest We declare that we have no conflict of interest.
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- 2022
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30. Nowcasting COVID-19 incidence indicators during the Italian first outbreak.
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Alaimo Di Loro P, Divino F, Farcomeni A, Jona Lasinio G, Lovison G, Maruotti A, and Mingione M
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- Disease Outbreaks, Humans, Incidence, Italy epidemiology, SARS-CoV-2, COVID-19
- Abstract
A novel parametric regression model is proposed to fit incidence data typically collected during epidemics. The proposal is motivated by real-time monitoring and short-term forecasting of the main epidemiological indicators within the first outbreak of COVID-19 in Italy. Accurate short-term predictions, including the potential effect of exogenous or external variables are provided. This ensures to accurately predict important characteristics of the epidemic (e.g., peak time and height), allowing for a better allocation of health resources over time. Parameter estimation is carried out in a maximum likelihood framework. All computational details required to reproduce the approach and replicate the results are provided., (© 2021 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.)
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- 2021
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31. Capitoline Dolphins: Residency Patterns and Abundance Estimate of Tursiops truncatus at the Tiber River Estuary (Mediterranean Sea).
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Pace DS, Di Marco C, Giacomini G, Ferri S, Silvestri M, Papale E, Casoli E, Ventura D, Mingione M, Alaimo Di Loro P, Jona Lasinio G, and Ardizzone G
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Periodic assessments of population status and trends to detect natural influences and human effects on coastal dolphin are often limited by lack of baseline information. Here, we investigated for the first time the site-fidelity patterns and estimated the population size of bottlenose dolphins ( Tursiops truncatus ) at the Tiber River estuary (central Mediterranean, Tyrrhenian Sea, Rome, Italy) between 2017 and 2020. We used photo-identification data and site-fidelity metrics to study the tendency of dolphins to remain in, or return to, the study area, and capture-recapture models to estimate the population abundance. In all, 347 unique individuals were identified. The hierarchical cluster analysis highlighted 3 clusters, labeled resident (individuals encountered at least five times, in three different months, over three distinct years; n = 42), part-time (individuals encountered at least on two occasions in a month, in at least two different years; n = 73), and transient (individuals encountered on more than one occasion, in more than 1 month, none of them in more than 1 year; n = 232), each characterized by site-fidelity metrics. Open POPAN modeling estimated a population size of 529 individuals (95% CI: 456-614), showing that the Capitoline (Roman) coastal area and nearby regions surrounding the Tiber River estuary represent an important, suitable habitat for bottlenose dolphins, despite their proximity to one of the major urban centers in the world (the city of Rome). Given the high number of individuals in the area and the presence of resident individuals with strong site fidelity, we suggest that conservation plans should not be focused only close to the Tiber River mouths but extended to cover a broader scale of area.
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- 2021
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32. I stay at home with headache. A survey to investigate how the lockdown for COVID-19 impacted on headache in Italian children.
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Papetti L, Alaimo Di Loro P, Tarantino S, Grazzi L, Guidetti V, Parisi P, Raieli V, Sciruicchio V, Termine C, Toldo I, Tozzi E, Verdecchia P, Carotenuto M, Battisti M, Celi A, D'Agnano D, Faedda N, Ferilli MA, Grillo G, Natalucci G, Onofri A, Pelizza MF, Ursitti F, Vasta M, Velardi M, Balestri M, Moavero R, Vigevano F, and Valeriani M
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- Adolescent, Anxiety etiology, Anxiety psychology, Betacoronavirus, COVID-19, Child, Female, Humans, Italy epidemiology, Male, SARS-CoV-2, Surveys and Questionnaires, Coronavirus Infections, Headache epidemiology, Headache psychology, Life Style, Pandemics, Pneumonia, Viral, Social Isolation psychology
- Abstract
Objective: The present Italian multicenter study aimed at investigating whether the course of primary headache disorders in children and adolescents was changed during the lockdown necessary to contain the COVID-19 emergency in Italy., Methods: During the lockdown, we submitted an online questionnaire to patients already diagnosed with primary headache disorders. Questions explored the course of headache, daily habits, psychological factors related to COVID-19, general mood and school stress. Answers were transformed into data for statistical analysis. Through a bivariate analysis, the main variables affecting the subjective trend of headache, and intensity and frequency of the attacks were selected. The significant variables were then used for the multivariate analysis., Results: We collected the answers of 707 patients. In the multivariate analysis, we found that reduction of school effort and anxiety was the main factor explaining the improvement in the subjective trend of headache and the intensity and frequency of the attacks ( p < 0.001). The greater the severity of headache, the larger was the clinical improvement ( p < 0.001). Disease duration was negatively associated with the improvement ( p < 0.001). It is noteworthy that clinical improvement was independent of prophylaxis ( p > 0.05), presence of chronic headache disorders ( p > 0.05) and geographical area ( p > 0.05)., Conclusions: Our study showed that lifestyle modification represents the main factor impacting the course of primary headache disorders in children and adolescents. In particular, reduction in school-related stress during the lockdown was the main factor explaining the general headache improvement in our population.
- Published
- 2020
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33. Tolerability of Palmitoylethanolamide in a Pediatric Population Suffering from Migraine: A Pilot Study.
- Author
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Papetti L, Sforza G, Tullo G, Alaimo di Loro P, Moavero R, Ursitti F, Ferilli MAN, Tarantino S, Vigevano F, and Valeriani M
- Subjects
- Amides, Child, Female, Humans, Male, Pilot Projects, Treatment Outcome, Analgesics therapeutic use, Ethanolamines therapeutic use, Migraine Disorders prevention & control, Palmitic Acids therapeutic use
- Abstract
Background: Palmitoylethanolamide (PEA) is emerging as a new therapeutic approach in pain and inflammatory conditions, and it has been evaluated in studies on various painful diseases. The aim of this open-label study was to evaluate the efficacy of ultramicronized PEA (umPEA) in the prophylactic treatment of migraine., Methods: The study included 70 patients with mean age of 10.3 ± 2.7 (24.5% M and 75.5% F). All patients had a diagnosis of migraine without aura (ICHD 3 criteria) and received umPEA (600 mg/day orally) for three months. We compared the attack frequency (AF) and attack intensity at baseline and after three months. Patients were asked to classify the intensity of the attack with a value ranging from 1 to 3, where 1 means mild attack, 2 moderate, and 3 severe attack., Results: Nine patients discontinued treatment before the target time of 12 weeks. After 3 months of treatment with umPEA, the headache frequency was reduced by >50% per month in 63.9% patients. The number of monthly attacks at T
1 decreased significantly compared with the baseline assessment (from 13.9 ± 7.5 SD of T0 to 6.5 ± 5.9 SD of T1 ; p < 0.001). The mean intensity of the attacks dropped from 1.67 ± 0.6 ( T0 ) to 1.16 ± 0.5 ( T1 ) ( p < 0.001), and the percentage of patients with severe attacks decreased after treatment (from 8.2% to 1.6%; p < 0.05). The monthly assumptions of drugs for the attack reduced from 9.5 ± 4.4 to 4.9 ± 2.5 ( p < 0.001). Only one patient developed mild side effects (nausea and floating)., Conclusions: Our preliminary data show that umPEA administered for three month reduces pain intensity and the number of attacks per month in pediatric patients with migraine. Although the small number of patients and the lack of control group do not allow us to consider these initial results as definitely reliable, they encourage us to expand the sample., Competing Interests: All authors declare that they have no conflicts of interest., (Copyright © 2020 Laura Papetti et al.)- Published
- 2020
- Full Text
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34. Features of Primary Chronic Headache in Children and Adolescents and Validity of Ichd 3 Criteria.
- Author
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Papetti L, Salfa I, Battan B, Moavero R, Termine C, Bartoli B, Di Nunzio F, Tarantino S, Alaimo Di Loro P, Vigevano F, and Valeriani M
- Abstract
Introduction: Chronic headaches are not a rare condition in children and adolescents with negative effects on their quality of life. Our aims were to investigate the clinical features of chronic headache and usefulness of the International Classification of Headache Disorders 3rd edition (ICHD 3) criteria for the diagnosis in a cohort of pediatric patients. Methods: We retrospectively reviewed the charts of patients attending the Headache Center of Bambino Gesù Children and Insubria University Hospital during the 2010-2016 time interval. Statistical analysis was conducted to study possible correlations between: (a) chronic primary headache (CPH) and demographic data (age and sex), (b) CPH and headache qualitative features, (c) CPH and risk of medication overuse headache (MOH), and (d) CPH and response to prophylactic therapies. Moreover, we compared the diagnosis obtained by ICHD 3 vs. ICHD 2 criteria Results: We included 377 patients with CPH (66.4% females, 33.6% males, under 18 years of age). CPH was less frequent under 6 years of age (0.8%; p < 0.05) and there was no correlation between age/sex and different CPH types. The risk to develop MOH was higher after 15 years of age ( p < 0.05). When we compared the diagnosis obtained by ICHD 2 and ICHD 3 criteria we found a significant difference for the undefined diagnosis (2.6% vs. 7.9%; p < 0.05), while the diagnosis of probable chronic migraine was only possible by using the ICHD2 criteria (11.9% of patients; p < 0.05). The main criterion which was not satisfied for a definitive diagnosis was the duration of the attacks less than 2 h (70% of patients younger than 6 years; p < 0.005). Amitriptyline and topiramate were the most effective drugs ( p < 0.05), although no significant difference was found between them ( p > 0.05). Conclusion: The ICHD 3 criteria show limitations when applied to children under 6 years of age. The risk of developing MOH increases with age. Although our "real word" study shows that amitriptyline and topiramate are the most effective drugs regardless of the CPH type, the lack of placebo-controlled data and the limited follow-up results did not allow us to conclude about the drug efficacy.
- Published
- 2019
- Full Text
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