Article
Behavioral Sciences
Ladan Shams, Ulrik Beierholm
Summary: The theory of Bayesian causal inference is a powerful and versatile theory that can explain human behavior and brain function, making it highly significant in neuroscience research.
NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS
(2022)
Article
Statistics & Probability
Elizabeth L. Ogburn, Oleg Sofrygin, Ivan Diaz, Mark J. van der Laan
Summary: This study focuses on semiparametric estimation and inference for causal effects using observational data from a single social network. The authors propose new methods that allow for dependence among observations, considering both information transmission across network ties and latent similarities among nodes. The study also reanalyzes a controversial study on obesity causal peer effects using social network data from the Framingham Heart Study, finding no evidence for such effects after accounting for network structure.
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
(2022)
Article
Computer Science, Artificial Intelligence
Sanjoy Kumar Paul, Priyabrata Chowdhury, Kamrul Ahsan, Syed Mithun Ali, Golam Kabir
Summary: This paper integrates qualitative Delphi and quantitative FIS to develop an advanced and intelligent decision-making framework for evaluating manufacturing plant locations. The Delphi method is used for criteria identification, and the FIS framework is utilized for evaluation, assisting industrial managers in intelligent and accurate manufacturing plant location selection.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Psychology, Multidisciplinary
Matthias Hinz, Nico Lehmann, Lisa Musculus
Summary: Expert athletes show a determination to make faster and better decisions. In this study, male athletes with different expertise levels were examined to understand how decision time and confidence depend on the type of embodied choices they make. The results suggest that elite players make better choices but at a slower pace, indicating a focus on accuracy rather than speed. These findings contribute to the understanding of decision-making in expert athletes and provide insights for future experiments.
FRONTIERS IN PSYCHOLOGY
(2022)
Article
Engineering, Aerospace
Peng He, Ruishan Sun
Summary: Efficient management of aviation safety requires accurate analysis of incident trends. This study proposes a causal-ARIMA model grounded in causal inference theory and employs four different modeling strategies to fit the trend of incidents in China's civil aviation sector from 1994 to 2020. The findings reveal that ensemble techniques incorporating the causal-ARIMA model outperform classical trend analysis methods in terms of model fit.
Article
Computer Science, Information Systems
Xiangnan He, Yang Zhang, Fuli Feng, Chonggang Song, Lingling Yi, Guohui Ling, Yongdong Zhang
Summary: This study addresses the issue of confounding factors in recommender systems from a causal perspective. By using a framework called DCR, we can eliminate the impact of confounding factors through intervened inference and improve the accuracy of recommendations. Additionally, to improve computational efficiency, we propose a mixture-of-experts (MoE) model architecture.
ACM TRANSACTIONS ON INFORMATION SYSTEMS
(2023)
Editorial Material
Physics, Applied
Luca Giuggioli, Mukesh Tiwari, Surajit Sen
Summary: This foreword introduces the reason for publishing this special issue, which is to celebrate Professor Vasudev Mangesh (Nitant) Kenkre's distinguished career as a statistical physicist and his influence on a global scale. The contributors are mainly his former students, friends, and collaborators.
INTERNATIONAL JOURNAL OF MODERN PHYSICS B
(2022)
Article
Computer Science, Artificial Intelligence
Ganeshsree Selvachandran, Shio Gai Quek, Luong Thi Hong Lan, Le Hoang Son, Nguyen Long Giang, Weiping Ding, Mohamed Abdel-Basset, Victor Hugo C. de Albuquerque
Summary: This article introduces the Mamdani complex fuzzy inference system (Mamdani CFIS) as a more efficient method for handling time-series data and time-periodic phenomena by implementing complex numbers, which offers greater flexibility in dealing with unexpected nonlinear fluctuations. The proposed CFIS was successfully demonstrated in six commonly available datasets, showcasing its computational efficiency compared to traditional FIS and ANCFIS.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2021)
Article
Mathematics
Andrei Coca, Manuela Rozalia Gabor, Irina Olimpia Susanu
Summary: This research questions the effectiveness of the existing European regional scoreboard in providing accurate inputs for decision-makers in mountainous regions. By conducting comparative analysis on the Alps and Carpathians, the study aims to develop new perspectives on innovation systems' performance for informed policy making. The methodology includes various statistical methods and regression analysis. The results highlight the similarities and differences between the two regions and provide a scientific basis for sustainable development in mountain areas.
Article
Automation & Control Systems
Enrique Herrera-Viedma, Ivan Palomares, Cong-Cong Li, Francisco Javier Cabrerizo, Yucheng Dong, Francisco Chiclana, Francisco Herrera
Summary: The article provides an overview of fuzzy and linguistic decision-making trends, studies, methodologies, and models developed in the last 50 years. It discusses core decision-making frameworks and new complex decision-making frameworks that have emerged in recent years. The challenges associated with these frameworks and key guidelines for future research in the field are highlighted.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Statistics & Probability
Haoyu Chen, Wenbin Lu, Rui Song
Summary: This article discusses the problem of online decision making with a linear reward model in the contextual bandit framework, utilizing the epsilon-greedy policy to address the exploration-exploitation trade-off, and demonstrating the asymptotic normality of parameter estimators using the martingale central limit theorem.
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
(2021)
Editorial Material
Public, Environmental & Occupational Health
Matthew Sperrin, Karla Diaz-Ordaz, Romin Pajouheshnia
Summary: The study presents a practical and promising method of utilizing causal estimates from external data sources to adjust CPMs for treatment drop-in. This demonstrates the value of incorporating causal inference in prediction and highlights the potential benefits for healthcare prediction models.
AMERICAN JOURNAL OF EPIDEMIOLOGY
(2021)
Article
Biology
Jan Boelts, Jan-Matthis Lueckmann, Richard Gao, Jakob H. Macke
Summary: Inferring parameters of computational models is crucial in cognitive neuroscience. Simulation-based inference (SBI) using neural density estimators provides a more efficient way to capture decision-making data. Compared to traditional methods, this approach demonstrates higher accuracy and training efficiency.
Editorial Material
Engineering, Electrical & Electronic
Wanshi Chen, Xingqin Lin, Juho Lee, Antti Toskala, Shu Sun, Carla Fabiana Chiasserini, Lingjia Liu
Summary: Since the start of the 5G NR work in 3GPP in 2016, there has been significant progress in both standardization and commercial deployments. Release 15 laid a strong foundation for accommodating diverse services, spectra, and deployment scenarios, while being forward compatible. Release 16 introduced expansion to vertical domain services, and Release 17 accelerated this expansion despite the challenges posed by COVID-19.
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
(2023)
Article
Social Sciences, Mathematical Methods
Julian Schuessler, Peter Selb
Summary: This paper discusses the applications of directed acyclic graphs (DAGs) in informing causal inferences, encoding theoretical assumptions about nonprobability samples and survey nonresponse, and determining the identification of population quantities. It explores bias elimination and assumptions in various selection scenarios, graphical representations of multiple selection stages, and critiques the use of design weights. It also highlights the drawbacks of selecting adjustment variables based on correlations and the potential drawbacks of nonresponse weighting in causal inference. The paper concludes by identifying further areas for survey methodology research benefiting from advances in causal graph theory.
SOCIOLOGICAL METHODS & RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Riccardo Ievoli, Lucio Palazzo, Giancarlo Ragozini
Summary: Traditional match statistics may not fully reflect the actual tactical style of a team, but by analyzing passing networks and structural features, it is possible to better understand a team's passing behavior. This paper shows how information from passing networks can significantly impact match outcomes, and how certain network variables are related to a team's offensive and finalization actions.
KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Psychology, Multidisciplinary
Maria Francesca Freda, De Luca Picione Raffaele, Giovanna Esposito, Giancarlo Ragozini, Italo Testa
Summary: This study presents the development and validation of a new instrument, the SInAPSi Academic Engagement Scale (SAES), which measures academic engagement. The SAES shows robust factor structure, good validity, and satisfactory psychometric properties. Its use could have strong implications for assessing academic engagement and implementing intervention programs for university students.
CURRENT PSYCHOLOGY
(2023)
Editorial Material
Statistics & Probability
Maria Prosperina Vitale, Giuseppe Giordano, Giancarlo Ragozini
Summary: In this contribution, the authors discuss the importance of Bayesian graphical models in biological applications, highlighting their extensive use in inferential tasks in biology and medicine. They propose a conceptual connection between graphical models and social network analysis, emphasizing the role of network models and random graphs. Through bibliometric analysis and thematic evolution maps, the main themes characterizing these research fields are mapped out.
STATISTICAL METHODS AND APPLICATIONS
(2022)
Article
Psychology, Social
Luigia Simona Sica, Hansika Kapoor, Giancarlo Ragozini
Summary: This study aims to investigate the role of creativity in individual well-being during late adolescence and young adulthood, specifically looking at positive and negative creativity. The research found distinct associations between creativity and identity, suggesting different types of individuals based on the interaction between creativity and identity. The study provides suggestions for interventions to promote creativity in this age group.
IDENTITY-AN INTERNATIONAL JOURNAL OF THEORY AND RESEARCH
(2023)
Article
Hospitality, Leisure, Sport & Tourism
Kristijan Breznik, Sasa Zupan Korze, Giancarlo Ragozini, Mitja Gorenak
Summary: This study analyzes the content of hotel brands' mission statements and their relationship with selected attributes. The findings show that hotel brands in luxurious markets emphasize experiences more often than those in midscale markets. Hotel brands with longer traditions and a large number of controlled rooms tend to have a more traditional approach to hospitality in their mission statements. On the other hand, younger hotel brands with fewer controlled rooms opt for a more commercially oriented approach. The analysis also reveals four dimensions of hotel brands' mission statements, instead of the typical nine dimensions. This analysis provides valuable insight for hotel brands in positioning themselves in the competitive tourism accommodation market.
INTERNATIONAL JOURNAL OF CONTEMPORARY HOSPITALITY MANAGEMENT
(2022)
Article
Operations Research & Management Science
Kristijan Breznik, Marialuisa Restaino, Maria Prosperina Vitale, Giancarlo Ragozini
Summary: The phenomenon of internationalization is crucial for higher education institutions, and the Erasmus program plays a vital role in their internationalization strategy by benefiting student recruitment, career outcomes, and staff expertise. This study aims to analyze the performance of European education systems in terms of learning mobility between countries from a longitudinal perspective. It compares international student mobility trajectories between European countries over twelve years, explores factors influencing a country's performance in mobility network exchanges, and offers policy suggestions for universities to enhance their international services.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Social Sciences, Mathematical Methods
Lucio Palazzo, Riccardo Ievoli, Giancarlo Ragozini
Summary: Summary statistics of football matches are not informative enough about the style of play, but networks and graphs can quantify the differences in team play. The distribution of local structures in passing networks of football teams is studied using the triad census. Tests are introduced to verify specific triadic patterns in football data, and they are applied to analyze 288 matches in the UEFA Champions League.
JOURNAL OF QUANTITATIVE ANALYSIS IN SPORTS
(2023)
Article
Statistics & Probability
Vincenzo Giuseppe Genova, Giuseppe Giordano, Giancarlo Ragozini, Maria Prosperina Vitale
Summary: This article discusses an analytic strategy for simplifying multipartite networks by introducing a three-step procedure to simplify, normalize, and filter network data structures. The usefulness of the strategy is demonstrated in two application fields, namely intranational student mobility in higher education and research collaboration in European framework programs.
ADVANCES IN DATA ANALYSIS AND CLASSIFICATION
(2023)
Article
Education & Educational Research
Raffaella Passeggia, Italo Testa, Giovanna Esposito, Raffaele De Luca Picione, Giancarlo Ragozini, Maria Francesca Freda
Summary: This study examined the relationships between academic motivation, retrospective evaluation of school experiences, subjective well-being, engagement, and intention to drop out among first-year university students. The results showed that students with more autonomous motivational styles were more engaged and less likely to drop out. Subjective well-being mediated the relationships between motivation, engagement, and dropout intentions. The findings provide insights into student engagement and dropout mechanisms and have implications for university policies.
INNOVATIVE HIGHER EDUCATION
(2023)
Proceedings Paper
Computer Science, Interdisciplinary Applications
Carla Galluccio, Matteo Magnani, Davide Vega, Giancarlo Ragozini, Alessandra Petrucci
Summary: In the context of textual analysis, network-based procedures are gaining attention as an alternative to classical topic models. However, there is a lack of systematic analysis on how different design choices affect the final results. This work presents the results obtained from analyzing a corpus of news articles, showing the impact of design choices on the detected topics.
COMPLEX NETWORKS AND THEIR APPLICATIONS XI, COMPLEX NETWORKS 2022, VOL 2
(2023)
Article
Education & Educational Research
Luigia Simona Sica, Tiziana Di Palma, Luca Fusco, Laura Aleni Sestito, Giancarlo Ragozini
Summary: The study aims to explore the relationship between creativity and vocational identity in late adolescence, and identifies two types of interaction between creativity and vocational identity based on the findings.
INTERNATIONAL JOURNAL FOR EDUCATIONAL AND VOCATIONAL GUIDANCE
(2023)
Article
Demography
Francesco Santelli, Giancarlo Ragozini, Maria Prosperina Vitale
Summary: This study describes the mobility trajectories of university students in Italy and evaluates the factors influencing their migration from the Campania region using a multilevel logistic regression model.
Correction
Economics
Maria Carmela Schisani, Luigi Balletta, Giancarlo Ragozini
Summary: The article discusses the persistence of business networks and economic elites in the South of Italy after Unification.
Article
Economics
Maria Carmela Schisani, Luigi Balletta, Giancarlo Ragozini
Summary: The article investigates the impact of Unification on the network power of economic elites in Southern Italy and finds that economic elites continue to persist, attributed to long-term business relations, ongoing lobbying power of the financial industry, and close ties with politics.
