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Silvia Salini

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Marzio Galeotti & Silvia Salini & Elena Verdolini, 2017. "Measuring Environmental Policy Stringency: Approaches, Validity, and Impact on Energy Efficiency," Development Working Papers 412, Centro Studi Luca d'Agliano, University of Milano.

    Cited by:

    1. Arik Levinson, 2017. "Energy Intensity: Prices, Policy, or Composition in US States," Working Papers gueconwpa~17-17-04, Georgetown University, Department of Economics.
    2. Lilis Yuaningsih & R. Adjeng Mariana Febrianti, 2021. "Spotting the Environmental Effect of the Economy and Technology: How the Development is Causing A Stringency with Carbon Emission?," International Journal of Energy Economics and Policy, Econjournals, vol. 11(6), pages 130-137.
    3. Li, Hai-ling & Zhu, Xue-hong & Chen, Jin-yu & Jiang, Fei-tao, 2019. "Environmental regulations, environmental governance efficiency and the green transformation of China's iron and steel enterprises," Ecological Economics, Elsevier, vol. 165(C), pages 1-1.
    4. Enrico Maria de Angelis & Marina Di Giacomo & Davide Vannoni, 2019. "Climate Change and Economic Growth: The Role of Environmental Policy Stringency," Sustainability, MDPI, vol. 11(8), pages 1-15, April.

  2. Marzio Galeotti & Yana Rubashkina & Silvia Salini & Elena Verdolini, 2014. "Environmental Policy Performance and its Determinants: Application of a three-level random intercept model," IEFE Working Papers 71, IEFE, Center for Research on Energy and Environmental Economics and Policy, Universita' Bocconi, Milano, Italy.

    Cited by:

    1. Francesco Nicolli & Francesco Vona, 2019. "Energy market liberalization and renewable energy policies in OECD countries," Post-Print hal-02562707, HAL.
    2. Bellelli, Francesco S. & Scarpa, Riccardo & Aftab, Ashar, 2023. "An empirical analysis of participation in international environmental agreements," Journal of Environmental Economics and Management, Elsevier, vol. 118(C).
    3. Daniel Armeanu & Georgeta Vintilă & Jean Vasile Andrei & Ştefan Cristian Gherghina & Mihaela Cristina Drăgoi & Cristian Teodor, 2018. "Exploring the link between environmental pollution and economic growth in EU-28 countries: Is there an environmental Kuznets curve?," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-28, May.
    4. Marzio Galeotti & Silvia Salini & Elena Verdolini, 2017. "Measuring Environmental Policy Stringency: Approaches, Validity, and Impact on Energy Efficiency," Development Working Papers 412, Centro Studi Luca d'Agliano, University of Milano.
    5. Juan J. Martínez Hernández & Patricia S. Sánchez‐Medina & René Díaz‐Pichardo, 2021. "Business‐oriented environmental regulation: Measurement and implications for environmental policy and business strategy from a sustainable development perspective," Business Strategy and the Environment, Wiley Blackwell, vol. 30(1), pages 507-521, January.
    6. Galeotti, Marzio & Salini, Silvia & Verdolini, Elena, 2020. "Measuring environmental policy stringency: Approaches, validity, and impact on environmental innovation and energy efficiency," Energy Policy, Elsevier, vol. 136(C).
    7. Elena Verdolini & Valentina Bosetti, 2017. "Environmental Policy and the International Diffusion of Cleaner Energy Technologies," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 66(3), pages 497-536, March.
    8. Cartelle Barros, Juan José & Lara Coira, Manuel & de la Cruz López, María Pilar & del Caño Gochi, Alfredo & Soares, Isabel, 2020. "Probabilistic multicriteria environmental assessment of power plants: A global approach," Applied Energy, Elsevier, vol. 260(C).

  3. Francesca De Battisti & Silvia Salini, 2011. "Robust Analysis of Bibliometric Data," UNIMI - Research Papers in Economics, Business, and Statistics unimi-1113, Universitá degli Studi di Milano.

    Cited by:

    1. Yajie Zhang & Qiang Yu, 2020. "What is the best article publishing strategy for early career scientists?," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 397-408, January.
    2. Silvia Salini & Andrea Cerioli & Fabrizio Laurini & Marco Riani, 2016. "Reliable Robust Regression Diagnostics," International Statistical Review, International Statistical Institute, vol. 84(1), pages 99-127, April.
    3. Andrea Cerioli & Domenico Perrotta, 2014. "Robust clustering around regression lines with high density regions," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 8(1), pages 5-26, March.
    4. Cerioli, Andrea & Farcomeni, Alessio & Riani, Marco, 2014. "Strong consistency and robustness of the Forward Search estimator of multivariate location and scatter," Journal of Multivariate Analysis, Elsevier, vol. 126(C), pages 167-183.
    5. Chioma Okoro & Oluwatobi Mary Owojori & Nnedinma Umeokafor, 2022. "The Developmental Trajectory of a Decade of Research on Mental Health and Well-Being amongst Graduate Students: A Bibliometric Analysis," IJERPH, MDPI, vol. 19(9), pages 1-20, April.
    6. Lorna Wildgaard, 2015. "A comparison of 17 author-level bibliometric indicators for researchers in Astronomy, Environmental Science, Philosophy and Public Health in Web of Science and Google Scholar," Scientometrics, Springer;Akadémiai Kiadó, vol. 104(3), pages 873-906, September.
    7. Claudio Giachetti & Giancarlo Manzi & Cinzia Colapinto, 2019. "Entry Mode Degree of Control, Firm Performance and Host Country Institutional Development: A Meta-Analysis," Management International Review, Springer, vol. 59(1), pages 3-39, February.
    8. Waleed M. Sweileh & Sa’ed H. Zyoud & Samah W. Al-Jabi & Ansam F. Sawalha, 2014. "Bibliometric analysis of diabetes mellitus research output from Middle Eastern Arab countries during the period (1996–2012)," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(1), pages 819-832, October.

  4. P. A. Ferrari & S. Salini, 2008. "Measuring Service Quality: The Opinion of Europeans about Utilities," Working Papers 2008.36, Fondazione Eni Enrico Mattei.

    Cited by:

    1. Silvia FIGINI & Ron S. KENETT & Silvia SALINI, 2010. "Integrating operational and financial risk assessments," Departmental Working Papers 2010-02, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.

  5. Carlo Fiorio & M. Florio & S. Salini & P. Ferrari, 2007. "Consumers’ Attitudes on Services of General Interest in the EU: Accessibility, Price and Quality 2000-2004," Working Papers 2007.2, Fondazione Eni Enrico Mattei.

    Cited by:

    1. Fiorio, Carlo V. & Florio, Massimo, 2011. "«Would you say that the price you pay for electricity is fair?» Consumers' satisfaction and utility reforms in the EU15," Energy Economics, Elsevier, vol. 33(2), pages 178-187, March.
    2. Ferrari, P.A. & Salini, S., 2008. "Measuring Service Quality: The Opinion of Europeans about Utilities," Privatisation Regulation Corporate Governance Working Papers 36758, Fondazione Eni Enrico Mattei (FEEM).
    3. Judith Clifton & Daniel Díaz-Fuentes & Marcos Fernández-Gutiérrez & Julio Revuelta, 2011. "The new regulation of public infrastructure services in the European Union. Challenges for territorial cohesion," ERSA conference papers ersa11p1416, European Regional Science Association.
    4. Ugur, Mehmet, 2009. "Liberalisation in a world of second best: evidence on European network industries," Greenwich Papers in Political Economy 3983, University of Greenwich, Greenwich Political Economy Research Centre.
    5. Fiorio, Carlo V. & Florio, Massimo & Perucca, Giovanni, 2013. "User satisfaction and the organization of local public transport: Evidence from European cities," Transport Policy, Elsevier, vol. 29(C), pages 209-218.
    6. Pier Alda Ferrari & Paola Annoni & Giancarlo Manzi, 2007. "Evaluation and comparison of European countries: public opinion on services," UNIMI - Research Papers in Economics, Business, and Statistics unimi-1058, Universitá degli Studi di Milano.
    7. Silvia SALINI & Ron S. KENETT, 2007. "Bayesian networks of customer satisfaction survey data," Departmental Working Papers 2007-33, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    8. Pier Ferrari & Laura Pagani & Carlo Fiorio, 2011. "A Two-Step Approach to Analyze Satisfaction Data," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 104(3), pages 545-554, December.
    9. Pier Ferrari & Silvia Salini, 2011. "Complementary Use of Rasch Models and Nonlinear Principal Components Analysis in the Assessment of the Opinion of Europeans About Utilities," Journal of Classification, Springer;The Classification Society, vol. 28(1), pages 53-69, April.
    10. Emanuele BACCHIOCCHI & Massimo FLORIO & Marco GAMBARO, 2008. "Telecom prices, regulatory reforms, and consumers’ satisfaction: evidence for 15 EU countries," Departmental Working Papers 2008-10, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano, revised 20 Jun 2008.
    11. Manto LAMPROPOULOU, 2018. "State‐Owned Enterprises In Greece: The Evolution Of A Paradigm 1996–2016," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 89(3), pages 491-526, September.
    12. Simona GRASSI & Riccardo PUGLISI, 2008. "Regulation and consumer satisfaction from public services: an individual fixed effects approach," Departmental Working Papers 2008-21, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    13. Carlo Vittorio FIORIO & Massimo FLORIO, 2008. "Do you pay a fair price for electricity? Consumers’ satisfaction and utility reform in the EU," Departmental Working Papers 2008-12, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.

Articles

  1. S. M. Iacus & G. Porro & S. Salini & E. Siletti, 2022. "An Italian Composite Subjective Well-Being Index: The Voice of Twitter Users from 2012 to 2017," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 161(2), pages 471-489, June.

    Cited by:

    1. Tiziana Carpi & Airo Hino & Stefano Maria Iacus & Giuseppe Porro, 2020. "On a Japanese Subjective Well-Being Indicator Based on Twitter data," Papers 2012.14372, arXiv.org.
    2. Tiziana Carpi & Airo Hino & Stefano Maria Iacus & Giuseppe Porro, 2021. "Twitter Subjective Well-Being Indicator During COVID-19 Pandemic: A Cross-Country Comparative Study," Papers 2101.07695, arXiv.org.

  2. Grané, Aurea & Salini, Silvia & Verdolini, Elena, 2021. "Robust multivariate analysis for mixed-type data: Novel algorithm and its practical application in socio-economic research," Socio-Economic Planning Sciences, Elsevier, vol. 73(C).

    Cited by:

    1. Peiró-Signes, Ángel & Segarra-Oña, Marival & Trull-Domínguez, Óscar & Sánchez-Planelles, Joaquín, 2022. "Exposing the ideal combination of endogenous–exogenous drivers for companies’ ecoinnovative orientation: Results from machine-learning methods," Socio-Economic Planning Sciences, Elsevier, vol. 79(C).
    2. Galati, Antonino & Coticchio, Alessandro & Peiró-Signes, Ángel, 2023. "Identifying the factors affecting citizens' willingness to participate in urban forest governance: Evidence from the municipality of Palermo, Italy," Forest Policy and Economics, Elsevier, vol. 155(C).
    3. Aurea Grané & Alpha A. Sow-Barry, 2021. "Visualizing Profiles of Large Datasets of Weighted and Mixed Data," Mathematics, MDPI, vol. 9(8), pages 1-20, April.
    4. Amparo Baíllo & Aurea Grané, 2021. "Subsampling and Aggregation: A Solution to the Scalability Problem in Distance-Based Prediction for Mixed-Type Data," Mathematics, MDPI, vol. 9(18), pages 1-17, September.

  3. Bruno Alessandro Rivieccio & Alessandra Micheletti & Manuel Maffeo & Matteo Zignani & Alessandro Comunian & Federica Nicolussi & Silvia Salini & Giancarlo Manzi & Francesco Auxilia & Mauro Giudici & G, 2021. "CoViD-19, learning from the past: A wavelet and cross-correlation analysis of the epidemic dynamics looking to emergency calls and Twitter trends in Italian Lombardy region," PLOS ONE, Public Library of Science, vol. 16(2), pages 1-20, February.

    Cited by:

    1. Zhou, Baoquan & Han, Bingtao & Jiang, Daqing & Hayat, Tasawar & Alsaedi, Ahmed, 2021. "Ergodic stationary distribution and extinction of a hybrid stochastic SEQIHR epidemic model with media coverage, quarantine strategies and pre-existing immunity under discrete Markov switching," Applied Mathematics and Computation, Elsevier, vol. 410(C).
    2. Giacomo Aletti & Alessandro Benfenati & Giovanni Naldi, 2021. "Graph, Spectra, Control and Epidemics: An Example with a SEIR Model," Mathematics, MDPI, vol. 9(22), pages 1-13, November.
    3. Antonio Vinci & Amina Pasquarella & Maria Paola Corradi & Pelagia Chatzichristou & Gianluca D’Agostino & Stefania Iannazzo & Nicoletta Trani & Maria Annunziata Parafati & Leonardo Palombi & Domenico A, 2022. "Emergency Medical Services Calls Analysis for Trend Prediction during Epidemic Outbreaks: Interrupted Time Series Analysis on 2020–2021 COVID-19 Epidemic in Lazio, Italy," IJERPH, MDPI, vol. 19(10), pages 1-15, May.
    4. Innocensia Owuor & Hartwig H. Hochmair, 2023. "Temporal Relationship between Daily Reports of COVID-19 Infections and Related GDELT and Tweet Mentions," Geographies, MDPI, vol. 3(3), pages 1-26, September.

  4. Galeotti, Marzio & Salini, Silvia & Verdolini, Elena, 2020. "Measuring environmental policy stringency: Approaches, validity, and impact on environmental innovation and energy efficiency," Energy Policy, Elsevier, vol. 136(C).

    Cited by:

    1. Zhang, Yixiang & Xiong, Yali & Li, Feng & Cheng, Jinhua & Yue, Xiaochen, 2020. "Environmental regulation, capital output and energy efficiency in China: An empirical research based on integrated energy prices," Energy Policy, Elsevier, vol. 146(C).
    2. Limei Ma & Qianying Wang & Dan Shi & Qinglong Shao, 2023. "Spatiotemporal patterns and determinants of renewable energy innovation: Evidence from a province-level analysis in China," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-14, December.
    3. Meng Guo & Shukai Cai, 2022. "Impact of Green Innovation Efficiency on Carbon Peak: Carbon Neutralization under Environmental Governance Constraints," IJERPH, MDPI, vol. 19(16), pages 1-18, August.
    4. Oleg Badunenko & Marzio Galeotti & Lester C. Hunt, 2021. "Better to grow or better to improve? Measuring environmental efficiency in OECD countries with a Stochastic Environmental Kuznets Frontier," Working Papers 2021.28, Fondazione Eni Enrico Mattei.
    5. Li, Hongmei & Xu, Ruizhe, 2023. "Impact of fiscal policies and natural resources on ecological sustainability of BRICS region: Moderating role of green innovation and ecological governance," Resources Policy, Elsevier, vol. 85(PB).
    6. Ahmed Oluwatobi Adekunle & Biliqees Ayoola Abdulmumin & Joseph Olorunfemi Akande & Kehinde Gabriel Ajose, 2022. "Modelling Aggregate Energy Consumption for Growth in Nigeria," International Journal of Energy Economics and Policy, Econjournals, vol. 12(6), pages 389-395, November.
    7. Amalia Rodrigo-González & Alfredo Grau-Grau & Inmaculada Bel-Oms, 2021. "Circular Economy and Value Creation: Sustainable Finance with a Real Options Approach," Sustainability, MDPI, vol. 13(14), pages 1-30, July.
    8. Justyna Godawska & Joanna Wyrobek, 2021. "The Impact of Environmental Policy Stringency on Renewable Energy Production in the Visegrad Group Countries," Energies, MDPI, vol. 14(19), pages 1-23, September.
    9. Burney, Shaheer & Lopez, Rigoberto A., 2021. "Political Economy of State SNAP Participation," 2021 Annual Meeting, August 1-3, Austin, Texas 313895, Agricultural and Applied Economics Association.
    10. Simona Bigerna & Maria Chiara D’Errico & Paolo Polinori, 2022. "Sustainable Power Generation in Europe: A Panel Data Analysis of the Effects of Market and Environmental Regulations," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 83(2), pages 445-479, October.
    11. Deserai A. Crow & Rob A. DeLeo & Elizabeth A. Albright & Kristin Taylor & Tom Birkland & Manli Zhang & Elizabeth Koebele & Nathan Jeschke & Elizabeth A. Shanahan & Caleb Cage, 2023. "Policy learning and change during crisis: COVID‐19 policy responses across six states," Review of Policy Research, Policy Studies Organization, vol. 40(1), pages 10-35, January.
    12. Tan, Yan & Uprasen, Utai, 2022. "The effect of foreign direct investment on renewable energy consumption subject to the moderating effect of environmental regulation: Evidence from the BRICS countries," Renewable Energy, Elsevier, vol. 201(P2), pages 135-149.
    13. Lee, Chien-Chiang & Ho, Shan-Ju, 2022. "Impacts of export diversification on energy intensity, renewable energy, and waste energy in 121 countries: Do environmental regulations matter?," Renewable Energy, Elsevier, vol. 199(C), pages 1510-1522.
    14. Zhu, Xuehong & Zuo, Xuguang & Li, Hailing, 2021. "The dual effects of heterogeneous environmental regulation on the technological innovation of Chinese steel enterprises—Based on a high-dimensional fixed effects model," Ecological Economics, Elsevier, vol. 188(C).
    15. Hartmann, Julia & Inkpen, Andrew & Ramaswamy, Kannan, 2022. "An FsQCA exploration of multiple paths to ecological innovation adoption in European transportation," Journal of World Business, Elsevier, vol. 57(5).
    16. Yi Chen & Zhongwen Xu & Xuehao Wang & Yining Yang, 2023. "How does green credit policy improve corporate social responsibility in China? An analysis based on carbon‐intensive listed firms," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 30(2), pages 889-904, March.
    17. Ozili, Peterson K, 2023. "Financial inclusion and environmental sustainability," MPRA Paper 116586, University Library of Munich, Germany.
    18. Chengyu Fang & Wanyi Wang & Weidong Wang, 2023. "The Impact of Carbon Trading Policy on Breakthrough Low-Carbon Technological Innovation," Sustainability, MDPI, vol. 15(10), pages 1-13, May.
    19. Ullah, Sami & Luo, Rundong & Nadeem, Muhammad & Cifuentes-Faura, Javier, 2023. "Advancing sustainable growth and energy transition in the United States through the lens of green energy innovations, natural resources and environmental policy," Resources Policy, Elsevier, vol. 85(PA).
    20. Yan, Zheming & Zhou, Zicheng & Du, Kerui, 2023. "How does environmental regulatory stringency affect energy consumption? Evidence from Chinese firms," Energy Economics, Elsevier, vol. 118(C).
    21. Lyu, Chaofeng & Xie, Zhe & Li, Zhi, 2022. "Market supervision, innovation offsets and energy efficiency: Evidence from environmental pollution liability insurance in China," Energy Policy, Elsevier, vol. 171(C).
    22. Tobias Eibinger & Hans Manner, 2022. "The Effectiveness of Policy Measures to Reduce CO2 Emissions from Passenger Cars in Austria," Graz Economics Papers 2022-04, University of Graz, Department of Economics.
    23. Strunz, Sebastian & Lehmann, Paul & Gawel, Erik, 2021. "Analyzing the ambitions of renewable energy policy in the EU and its Member States," Energy Policy, Elsevier, vol. 156(C).
    24. Shuping Cheng & Lingjie Meng & Weizhong Wang, 2022. "The Impact of Environmental Regulation on Green Energy Technology Innovation—Evidence from China," Sustainability, MDPI, vol. 14(14), pages 1-23, July.
    25. Afshan, Sahar & Ozturk, Ilhan & Yaqoob, Tanzeela, 2022. "Facilitating renewable energy transition, ecological innovations and stringent environmental policies to improve ecological sustainability: Evidence from MM-QR method," Renewable Energy, Elsevier, vol. 196(C), pages 151-160.
    26. Zhou, Kuo & Luo, Haotian & Qu, Zhi, 2023. "What can the environmental rule of law do for environmental innovation? Evidence from environmental tribunals in China," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    27. Grané, Aurea & Salini, Silvia & Verdolini, Elena, 2021. "Robust multivariate analysis for mixed-type data: Novel algorithm and its practical application in socio-economic research," Socio-Economic Planning Sciences, Elsevier, vol. 73(C).
    28. Miao, Cheng-lin & Duan, Meng-meng & Zuo, Yang & Wu, Xin-yu, 2021. "Spatial heterogeneity and evolution trend of regional green innovation efficiency--an empirical study based on panel data of industrial enterprises in China's provinces," Energy Policy, Elsevier, vol. 156(C).
    29. Mehmet Demiral & Emrah Eray Akça & Ipek Tekin, 2021. "Predictors of global carbon dioxide emissions: Do stringent environmental policies matter?," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(12), pages 18337-18361, December.
    30. Claudiu Tiberiu Albulescu & Maria-Elena Boatca-Barabas & Andra Diaconescu, 2021. "The asymmetric effect of environmental policy stringency on CO2 emissions in OECD countries," Working Papers hal-03303096, HAL.
    31. Wen, Jun & Yin, Hua-Tang & Jang, Chyi-Lu & Uchida, Hideaki & Chang, Chun-Ping, 2023. "Does corruption hurt green innovation? Yes – Global evidence from cross-validation," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
    32. Su, Hongwei & Liang, Biming, 2021. "The impact of regional market integration and economic opening up on environmental total factor energy productivity in Chinese provinces," Energy Policy, Elsevier, vol. 148(PA).
    33. Chen, Maozhi & Sinha, Avik & Hu, Kexiang & Shah, Muhammad Ibrahim, 2020. "Impact of Technological Innovation on Energy Efficiency in Industry 4.0 Era: Moderation of Shadow Economy in Sustainable Development," MPRA Paper 104842, University Library of Munich, Germany, revised 2020.
    34. Alexander Melnik & Irina Naoumova & Kirill Ermolaev & Jerome Katrichis, 2021. "Driving Innovation through Energy Efficiency: A Russian Regional Analysis," Sustainability, MDPI, vol. 13(9), pages 1-19, April.
    35. Barbara Kryk & Małgorzata Klaudia Guzowska, 2021. "Implementation of Climate/Energy Targets of the Europe 2020 Strategy by the EU Member States," Energies, MDPI, vol. 14(9), pages 1-18, May.
    36. Zheng, Mingbo & Feng, Gen-Fu & Jang, Chyi-Lu & Chang, Chun-Ping, 2021. "Terrorism and green innovation in renewable energy," Energy Economics, Elsevier, vol. 104(C).
    37. Juchun Lu & Siqun Zhou & Xiaohan Xiao & Meng Zhong & Yifan Zhao, 2023. "The Dynamic Evolution of the Digital Economy and Its Impact on the Urban Green Innovation Development from the Perspective of Driving Force—Taking China’s Yangtze River Economic Belt Cities as an Exam," Sustainability, MDPI, vol. 15(8), pages 1-21, April.
    38. Prokop, Viktor & Gerstlberger, Wolfgang & Zapletal, David & Gyamfi, Solomon, 2023. "Do we need human capital heterogeneity for energy efficiency and innovativeness? Insights from European catching-up territories," Energy Policy, Elsevier, vol. 177(C).
    39. Mei Feng & Chu Chen & Jia Liu & Wei Jia, 2022. "Does Central Environmental Protection Inspector Improve Corporate Social Responsibility? Evidence from Chinese Listed Companies," Sustainability, MDPI, vol. 14(22), pages 1-22, November.
    40. Badunenko, Oleg & Galeotti, Marzio & Hunt, Lester C., 2023. "Better to grow or better to improve? Measuring environmental efficiency in OECD countries with a stochastic environmental Kuznets frontier (SEKF)," Energy Economics, Elsevier, vol. 121(C).
    41. Yuanyuan Gong & Zhangsheng Liu & Shuangyin Wu & Shuhui Pu & Xiaolu Zhang & Lingkun Chen, 2023. "Study on the Technological Inductive Effects of Product Information Label: Evidence From the Energy-Efficiency Labeling System in China," SAGE Open, , vol. 13(3), pages 21582440231, August.
    42. Huang, Feipeng, 2023. "How does trade and fiscal decentralization leads to green growth; role of renewable energy development," Renewable Energy, Elsevier, vol. 214(C), pages 334-341.
    43. Hu, Xing & Yu, Shiwei & Fang, Xu & Ovaere, Marten, 2023. "Which combinations of renewable energy policies work better? Insights from policy text synergies in China," Energy Economics, Elsevier, vol. 127(PA).
    44. Shantha Indrajith H. Liyanage & Fulu Godfrey Netswera & Abel Motsumi, 2021. "Insights from EU Policy Framework in Aligning Sustainable Finance for Sustainable Development in Africa and Asia," International Journal of Energy Economics and Policy, Econjournals, vol. 11(1), pages 459-470.
    45. Ming Yi & Yiqian Wang & Modan Yan & Lina Fu & Yao Zhang, 2020. "Government R&D Subsidies, Environmental Regulations, and Their Effect on Green Innovation Efficiency of Manufacturing Industry: Evidence from the Yangtze River Economic Belt of China," IJERPH, MDPI, vol. 17(4), pages 1-17, February.
    46. Consoli, Davide & Costantini, Valeria & Paglialunga, Elena, 2023. "We're in this together: Sustainable energy and economic competitiveness in the EU," Research Policy, Elsevier, vol. 52(1).
    47. Levinson, Arik, 2021. "Energy intensity: Deindustrialization, composition, prices, and policies in U.S. states," Resource and Energy Economics, Elsevier, vol. 65(C).

  5. Iacus Stefano M. & Salini Silvia & Siletti Elena & Porro Giuseppe, 2020. "Controlling for Selection Bias in Social Media Indicators through Official Statistics: a Proposal," Journal of Official Statistics, Sciendo, vol. 36(2), pages 315-338, June.

    Cited by:

    1. Dean Fantazzini & Julia Pushchelenko & Alexey Mironenkov & Alexey Kurbatskii, 2021. "Forecasting Internal Migration in Russia Using Google Trends: Evidence from Moscow and Saint Petersburg," Forecasting, MDPI, vol. 3(4), pages 1-30, October.
    2. Silvia Facchinetti & Elena Siletti, 2022. "Well-being Indicators: a Review and Comparison in the Context of Italy," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 159(2), pages 523-547, January.
    3. Tiziana Carpi & Airo Hino & Stefano Maria Iacus & Giuseppe Porro, 2020. "On a Japanese Subjective Well-Being Indicator Based on Twitter data," Papers 2012.14372, arXiv.org.
    4. Tiziana Carpi & Airo Hino & Stefano Maria Iacus & Giuseppe Porro, 2021. "Twitter Subjective Well-Being Indicator During COVID-19 Pandemic: A Cross-Country Comparative Study," Papers 2101.07695, arXiv.org.
    5. Rossouw, Stephanie & Greyling, Talita, 2020. "Big Data and Happiness," GLO Discussion Paper Series 634, Global Labor Organization (GLO).
    6. Federica Cugnata & Silvia Salini & Elena Siletti, 2021. "Deepening Well-Being Evaluation with Different Data Sources: A Bayesian Networks Approach," IJERPH, MDPI, vol. 18(15), pages 1-10, July.

  6. Galeotti, Marzio & Rubashkina, Yana & Salini, Silvia & Verdolini, Elena, 2018. "Environmental policy performance and its determinants: Application of a three-level random intercept model," Energy Policy, Elsevier, vol. 114(C), pages 134-144.
    See citations under working paper version above.
  7. F. Cugnata & G. Perucca & S. Salini, 2017. "Bayesian networks and the assessment of universities' value added," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(10), pages 1785-1806, July.

    Cited by:

    1. Paolo Castelnovo & Martina Dal Molin, 2021. "The learning mechanisms through public procurement for innovation: The case of government‐funded basic research organizations," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 92(3), pages 411-446, September.
    2. Lidia Ceriani & Chiara Gigliarano, 2020. "Multidimensional Well-Being: A Bayesian Networks Approach," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 152(1), pages 237-263, November.
    3. Massimo Florio & Francesco Giffoni & Anna Giunta & Emanuela Sirtori, 2018. "Big science, learning, and innovation: evidence from CERN procurement," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 27(5), pages 915-936.

  8. Carrazza, Stefano & Ferrara, Alfio & Salini, Silvia, 2016. "Research infrastructures in the LHC era: A scientometric approach," Technological Forecasting and Social Change, Elsevier, vol. 112(C), pages 121-133.

    Cited by:

    1. Massimo FLORIO & Francesco GIFFONI, 2019. "L’impatto sociale della produzione di scienza su larga scala: come governarlo?," Departmental Working Papers 2019-05, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    2. Holger Graf & Martin Kalthaus, 2022. "Global Knowledge Embeddedness," Jena Economics Research Papers 2022-004, Friedrich-Schiller-University Jena.
    3. Morretta, Valentina & Vurchio, Davide & Carrazza, Stefano, 2022. "The socio-economic value of scientific publications: The case of Earth Observation satellites," Technological Forecasting and Social Change, Elsevier, vol. 180(C).

  9. Silvia Salini & Andrea Cerioli & Fabrizio Laurini & Marco Riani, 2016. "Reliable Robust Regression Diagnostics," International Statistical Review, International Statistical Institute, vol. 84(1), pages 99-127, April.

    Cited by:

    1. Rousseeuw, Peter & Perrotta, Domenico & Riani, Marco & Hubert, Mia, 2019. "Robust Monitoring of Time Series with Application to Fraud Detection," Econometrics and Statistics, Elsevier, vol. 9(C), pages 108-121.
    2. Lisa Crosato & Luigi Grossi, 2019. "Correcting outliers in GARCH models: a weighted forward approach," Statistical Papers, Springer, vol. 60(6), pages 1939-1970, December.
    3. Grané, Aurea & Salini, Silvia & Verdolini, Elena, 2021. "Robust multivariate analysis for mixed-type data: Novel algorithm and its practical application in socio-economic research," Socio-Economic Planning Sciences, Elsevier, vol. 73(C).
    4. Andrea Cerioli & Marco Riani & Anthony C. Atkinson & Aldo Corbellini, 2018. "The power of monitoring: how to make the most of a contaminated multivariate sample," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 27(4), pages 559-587, December.

  10. Francesca De Battisti & Alfio Ferrara & Silvia Salini, 2015. "A decade of research in statistics: a topic model approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(2), pages 413-433, May.

    Cited by:

    1. Ivan Savin & Kristina Chukavina & Andrey Pushkarev, 2023. "Topic-based classification and identification of global trends for startup companies," Small Business Economics, Springer, vol. 60(2), pages 659-689, February.
    2. Hosang Jung & Boram Kim, 2021. "Identifying Research Topics and Trends in Asset Management for Sustainable Use: A Topic Modeling Approach," Sustainability, MDPI, vol. 13(9), pages 1-14, April.
    3. Hakyeon Lee & Hanbin Seo & Youngjung Geum, 2018. "Uncovering the Topic Landscape of Product-Service System Research: from Sustainability to Value Creation," Sustainability, MDPI, vol. 10(4), pages 1-15, March.
    4. Zhou, Yusheng & Wang, Xueqin & Yuen, Kum Fai, 2021. "Sustainability disclosure for container shipping: A text-mining approach," Transport Policy, Elsevier, vol. 110(C), pages 465-477.
    5. Qianqian Jin & Hongshu Chen & Ximeng Wang & Tingting Ma & Fei Xiong, 2022. "Exploring funding patterns with word embedding-enhanced organization–topic networks: a case study on big data," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(9), pages 5415-5440, September.
    6. Chen, Hongshu & Jin, Qianqian & Wang, Ximeng & Xiong, Fei, 2022. "Profiling academic-industrial collaborations in bibliometric-enhanced topic networks: A case study on digitalization research," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    7. Seungsu Paek & Namhyoung Kim, 2021. "Analysis of Worldwide Research Trends on the Impact of Artificial Intelligence in Education," Sustainability, MDPI, vol. 13(14), pages 1-20, July.
    8. Imran Ali & Devika Kannan, 2022. "Mapping research on healthcare operations and supply chain management: a topic modelling-based literature review," Annals of Operations Research, Springer, vol. 315(1), pages 29-55, August.
    9. Sung-Ho Shin & Oh Kyoung Kwon & Xiao Ruan & Prem Chhetri & Paul Tae-Woo Lee & Shahrooz Shahparvari, 2018. "Analyzing Sustainability Literature in Maritime Studies with Text Mining," Sustainability, MDPI, vol. 10(10), pages 1-19, September.
    10. Hongshu Chen & Xinna Song & Qianqian Jin & Ximeng Wang, 2022. "Network dynamics in university-industry collaboration: a collaboration-knowledge dual-layer network perspective," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6637-6660, November.
    11. Nadeem Shafique Butt & Ahmad Azam Malik & Muhammad Qaiser Shahbaz, 2021. "Bibliometric Analysis of Statistics Journals Indexed in Web of Science Under Emerging Source Citation Index," SAGE Open, , vol. 11(1), pages 21582440209, January.
    12. Hakyeon Lee & Pilsung Kang, 2018. "Identifying core topics in technology and innovation management studies: a topic model approach," The Journal of Technology Transfer, Springer, vol. 43(5), pages 1291-1317, October.
    13. Savin, Ivan & Ott, Ingrid & Konop, Chris, 2022. "Tracing the evolution of service robotics: Insights from a topic modeling approach," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    14. Yosuke Miyata & Emi Ishita & Fang Yang & Michimasa Yamamoto & Azusa Iwase & Keiko Kurata, 2020. "Knowledge structure transition in library and information science: topic modeling and visualization," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 665-687, October.
    15. Xu, Ran & Baghaei Lakeh, Arash & Ghaffarzadegan, Navid, 2021. "Examining the characteristics of impactful research topics: A case of three decades of HIV-AIDS research," Journal of Informetrics, Elsevier, vol. 15(1).
    16. Chen, Guo & Xiao, Lu, 2016. "Selecting publication keywords for domain analysis in bibliometrics: A comparison of three methods," Journal of Informetrics, Elsevier, vol. 10(1), pages 212-223.
    17. Hanchen Jiang & Maoshan Qiang & Dongcheng Zhang & Qi Wen & Bingqing Xia & Nan An, 2018. "Climate Change Communication in an Online Q&A Community: A Case Study of Quora," Sustainability, MDPI, vol. 10(5), pages 1-17, May.
    18. Seongyoun Hong & Taejung Park & Jaewon Choi, 2020. "Analyzing Research Trends in University Student Experience Based on Topic Modeling," Sustainability, MDPI, vol. 12(9), pages 1-11, April.
    19. Wu, Jia-Jhou & Chang, Sue-Ting, 2020. "Exploring customer sentiment regarding online retail services: A topic-based approach," Journal of Retailing and Consumer Services, Elsevier, vol. 55(C).

  11. Federica Cugnata & Silvia Salini, 2014. "Model-based approach for importance–performance analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(6), pages 3053-3064, November.

    Cited by:

    1. Marcella Corduas & Alfonso Piscitelli, 2017. "Modeling university student satisfaction: the case of the humanities and social studies degree programs," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(2), pages 617-628, March.
    2. Stefania Capecchi & Domenico Piccolo, 2017. "Dealing with heterogeneity in ordinal responses," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(5), pages 2375-2393, September.
    3. Zhou Lu & Zhuyao Zhuo, 2021. "Modelling of Chinese corporate bond default – A machine learning approach," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(5), pages 6147-6191, December.

  12. Francesca De Battisti & Silvia Salini, 2013. "Robust analysis of bibliometric data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 22(2), pages 269-283, June.
    See citations under working paper version above.
  13. Alfio Ferrara & Silvia Salini, 2012. "Ten challenges in modeling bibliographic data for bibliometric analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 93(3), pages 765-785, December.

    Cited by:

    1. Jeong, Yujin & Park, Inchae & Yoon, Byungun, 2019. "Identifying emerging Research and Business Development (R&BD) areas based on topic modeling and visualization with intellectual property right data," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 655-672.
    2. Chyi-Kwei Yau & Alan Porter & Nils Newman & Arho Suominen, 2014. "Clustering scientific documents with topic modeling," Scientometrics, Springer;Akadémiai Kiadó, vol. 100(3), pages 767-786, September.
    3. Sabine Loudcher & Wararat Jakawat & Edmundo Pavel Soriano Morales & Cécile Favre, 2015. "Combining OLAP and information networks for bibliographic data analysis: a survey," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(2), pages 471-487, May.
    4. Massimo FLORIO & Francesco GIFFONI, 2019. "L’impatto sociale della produzione di scienza su larga scala: come governarlo?," Departmental Working Papers 2019-05, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    5. Francesca De Battisti & Silvia Salini, 2013. "Robust analysis of bibliometric data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 22(2), pages 269-283, June.
    6. Francesca De Battisti & Alfio Ferrara & Silvia Salini, 2015. "A decade of research in statistics: a topic model approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(2), pages 413-433, May.
    7. Bornmann, Lutz, 2019. "Does the normalized citation impact of universities profit from certain properties of their published documents – such as the number of authors and the impact factor of the publishing journals? A mult," Journal of Informetrics, Elsevier, vol. 13(1), pages 170-184.
    8. Chen, Guo & Xiao, Lu, 2016. "Selecting publication keywords for domain analysis in bibliometrics: A comparison of three methods," Journal of Informetrics, Elsevier, vol. 10(1), pages 212-223.

  14. Ron S. Kenett & Silvia Salini, 2011. "Modern analysis of customer satisfaction surveys: comparison of models and integrated analysis," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 27(5), pages 465-475, September.

    Cited by:

    1. Paolo Castelnovo & Martina Dal Molin, 2021. "The learning mechanisms through public procurement for innovation: The case of government‐funded basic research organizations," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 92(3), pages 411-446, September.
    2. Domenico Piccolo & Rosaria Simone, 2019. "The class of cub models: statistical foundations, inferential issues and empirical evidence," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(3), pages 389-435, September.
    3. Violetta Simonacci & Michele Gallo, 2017. "Statistical tools for student evaluation of academic educational quality," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(2), pages 565-579, March.
    4. Alfio Ferrara & Silvia Salini, 2012. "Ten challenges in modeling bibliographic data for bibliometric analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 93(3), pages 765-785, December.
    5. Hamed Taherdoost & Mitra Madanchian, 2021. "Empirical Modeling of Customer Satisfaction for E-Services in Cross-Border E-Commerce," Post-Print hal-03741849, HAL.
    6. Peter Martey Addo & Dominique Guegan & Bertrand Hassani, 2018. "Credit Risk Analysis Using Machine and Deep Learning Models," Risks, MDPI, vol. 6(2), pages 1-20, April.
    7. Mohamed Hanafy & Ruixing Ming, 2021. "Machine Learning Approaches for Auto Insurance Big Data," Risks, MDPI, vol. 9(2), pages 1-23, February.
    8. Federica Cugnata & Silvia Salini, 2014. "Model-based approach for importance–performance analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(6), pages 3053-3064, November.
    9. Ron S. Kenett & Giancarlo Manzi & Carmit Rapaport & Silvia Salini, 2022. "Integrated Analysis of Behavioural and Health COVID-19 Data Combining Bayesian Networks and Structural Equation Models," IJERPH, MDPI, vol. 19(8), pages 1-26, April.
    10. Antonino Mario Oliveri & Gabriella Polizzi & Anna Maria Parroco, 2019. "Measuring Tourist Satisfaction Through a Dual Approach: The 4Q Methodology," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 146(1), pages 361-382, November.

  15. Pier Ferrari & Silvia Salini, 2011. "Complementary Use of Rasch Models and Nonlinear Principal Components Analysis in the Assessment of the Opinion of Europeans About Utilities," Journal of Classification, Springer;The Classification Society, vol. 28(1), pages 53-69, April.

    Cited by:

    1. Marzio Galeotti & Yana Rubashkina & Silvia Salini & Elena Verdolini, 2014. "Environmental Policy Performance and its Determinants: Application of a Three-level Random Intercept Model," Working Papers 2014.90, Fondazione Eni Enrico Mattei.
    2. Federico ANDREIS & Pier Alda FERRARI, 2015. "Customer Satisfaction Evaluation Using Multidimensional Item Response Theory Models," Departmental Working Papers 2015-25, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    3. Luisa ANDERLONI & Emanuele BACCHIOCCHI & Daniela VANDONE, 2011. "Household financial vulnerability: an empirical analysis," Departmental Working Papers 2011-02, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano, revised 03 Nov 2011.
    4. Federica Cugnata & Silvia Salini, 2014. "Model-based approach for importance–performance analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(6), pages 3053-3064, November.
    5. Federico Andreis & Pier Alda Ferrari, 2014. "Multidimensional item response theory models for dichotomous data in customer satisfaction evaluation," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(9), pages 2044-2055, September.

  16. Ron S. Kenett & Silvia Salini, 2011. "Rejoinder to ‘Modern analysis of customer satisfaction surveys: comparison of models and integrated analysis’," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 27(5), pages 484-486, September.

    Cited by:

    1. Paolo Castelnovo & Martina Dal Molin, 2021. "The learning mechanisms through public procurement for innovation: The case of government‐funded basic research organizations," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 92(3), pages 411-446, September.
    2. Domenico Piccolo & Rosaria Simone, 2019. "The class of cub models: statistical foundations, inferential issues and empirical evidence," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(3), pages 389-435, September.
    3. Hamed Taherdoost & Mitra Madanchian, 2021. "Empirical Modeling of Customer Satisfaction for E-Services in Cross-Border E-Commerce," Post-Print hal-03741849, HAL.
    4. Ron S. Kenett & Giancarlo Manzi & Carmit Rapaport & Silvia Salini, 2022. "Integrated Analysis of Behavioural and Health COVID-19 Data Combining Bayesian Networks and Structural Equation Models," IJERPH, MDPI, vol. 19(8), pages 1-26, April.

  17. Silvia Salini & Ron Kenett, 2009. "Bayesian networks of customer satisfaction survey data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(11), pages 1177-1189.

    Cited by:

    1. Massimo Florio, 2021. "Knowledge creation: new frontiers for public investment," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 92(3), pages 379-386, September.
    2. F. Cugnata & G. Perucca & S. Salini, 2017. "Bayesian networks and the assessment of universities' value added," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(10), pages 1785-1806, July.
    3. P. Berchialla & S. Snidero & A. Stancu & C. Scarinzi & R. Corradetti & D. Gregori, 2012. "Understanding the epidemiology of foreign body injuries in children using a data-driven Bayesian network," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(4), pages 867-874, September.
    4. Claudia Tarantola & Paola Vicard & Ioannis Ntzoufras, 2012. "Monitoring and Improving Greek Banking Services Using Bayesian Networks: an Analysis of Mystery Shopping Data," Quaderni di Dipartimento 160, University of Pavia, Department of Economics and Quantitative Methods.
    5. Lidia Ceriani & Chiara Gigliarano, 2020. "Multidimensional Well-Being: A Bayesian Networks Approach," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 152(1), pages 237-263, November.
    6. Flaminia Musella & Paola Vicard, 2015. "Object-oriented Bayesian networks for complex quality management problems," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(1), pages 115-133, January.
    7. Massimo Florio & Francesco Giffoni & Anna Giunta & Emanuela Sirtori, 2018. "Big science, learning, and innovation: evidence from CERN procurement," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 27(5), pages 915-936.
    8. Donata Marasini & Piero Quatto & Enrico Ripamonti, 2017. "Inferential confidence intervals for fuzzy analysis of teaching satisfaction," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(4), pages 1513-1529, July.
    9. Di Pietro, Laura & Guglielmetti Mugion, Roberta & Musella, Flaminia & Renzi, Maria Francesca & Vicard, Paola, 2017. "Monitoring an airport check-in process by using Bayesian networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 106(C), pages 235-247.
    10. Federica Cugnata & Silvia Salini, 2014. "Model-based approach for importance–performance analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(6), pages 3053-3064, November.
    11. Zhang, Ya & Zhao, Hai & He, Xuan & Pei, Fan-Dong & Li, Guang-Guang, 2016. "Bayesian prediction of earthquake network based on space–time influence domain," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 445(C), pages 138-149.
    12. Mandhani, Jyoti & Nayak, Jogendra Kumar & Parida, Manoranjan, 2020. "Interrelationships among service quality factors of Metro Rail Transit System: An integrated Bayesian networks and PLS-SEM approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 140(C), pages 320-336.
    13. Pier Ferrari & Silvia Salini, 2011. "Complementary Use of Rasch Models and Nonlinear Principal Components Analysis in the Assessment of the Opinion of Europeans About Utilities," Journal of Classification, Springer;The Classification Society, vol. 28(1), pages 53-69, April.
    14. E. Cene & F. Karaman, 2015. "Analysing organic food buyers' perceptions with Bayesian networks: a case study in Turkey," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(7), pages 1572-1590, July.

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