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Joao Carvalho Neves

Personal Details

First Name:Joao
Middle Name:Carvalho
Last Name:Neves
Suffix:
RePEc Short-ID:pne54
http://www.iseg.utl.pt/~jcneves
ISEG - School of Economics and Management Rua Miguel Lupi, 20 1249-078 LISBOA Portugal
00-351-213922810

Affiliation

Instituto Superior de Economia e Gestão (ISEG)
Universidade de Lisboa

Lisboa, Portugal
http://www.iseg.ulisboa.pt/
RePEc:edi:isutlpt (more details at EDIRC)

Research output

as
Jump to: Articles

Articles

  1. Joao Neves & Antonio Bugalho, 2008. "Coordination and control in emerging international construction firms," Construction Management and Economics, Taylor & Francis Journals, vol. 26(1), pages 3-13.
  2. J. C. Neves & A. Vieira, 2006. "Improving bankruptcy prediction with Hidden Layer Learning Vector Quantization," European Accounting Review, Taylor & Francis Journals, vol. 15(2), pages 253-271.
  3. Neves, Joao C., 2006. "Controlling strategy: Management, accounting and performance measurement," The International Journal of Accounting, Elsevier, vol. 41(2), pages 202-205.
  4. Joao C. Neves, 2005. "The value of financial freedom and ownership in opportunities of entrepreneurial harvest," International Journal of Entrepreneurship and Innovation Management, Inderscience Enterprises Ltd, vol. 5(5/6), pages 469-482.
  5. João Carvalho das Neves & Pedro Palma Fernandes, 1998. "A reacção do mercado de capitais português à publicação de lucros das «blue chips» no período 1991-1995," Portuguese Journal of Management Studies, ISEG, Universidade de Lisboa, vol. 0(2), pages 119-127.

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.

Articles

  1. Joao Neves & Antonio Bugalho, 2008. "Coordination and control in emerging international construction firms," Construction Management and Economics, Taylor & Francis Journals, vol. 26(1), pages 3-13.

    Cited by:

    1. Martina Sageder & Birgit Feldbauer-Durstmüller, 2019. "Management control in multinational companies: a systematic literature review," Review of Managerial Science, Springer, vol. 13(5), pages 875-918, November.
    2. Alicia Lozano-Torró & Tatiana García-Segura & Laura Montalbán-Domingo & Eugenio Pellicer, 2019. "Risk Management as a Success Factor in the International Activity of Spanish Engineering," Administrative Sciences, MDPI, vol. 9(1), pages 1-20, February.

  2. J. C. Neves & A. Vieira, 2006. "Improving bankruptcy prediction with Hidden Layer Learning Vector Quantization," European Accounting Review, Taylor & Francis Journals, vol. 15(2), pages 253-271.

    Cited by:

    1. Mohammad Mahdi Mousavi & Jamal Ouenniche & Kaoru Tone, 2023. "A dynamic performance evaluation of distress prediction models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 756-784, July.
    2. Situm Mario, 2014. "Inability of Gearing-Ratio as Predictor for Early Warning Systems," Business Systems Research, Sciendo, vol. 5(2), pages 23-45, September.
    3. Tamás Kristóf & Miklós Virág, 2020. "A Comprehensive Review of Corporate Bankruptcy Prediction in Hungary," JRFM, MDPI, vol. 13(2), pages 1-20, February.
    4. Li, Xia & Gupta, Jairaj & Bu, Ziwen & Kannothra, Chacko George, 2023. "Effect of cash flow risk on corporate failures, and the moderating role of earnings management and abnormal compensation," International Review of Financial Analysis, Elsevier, vol. 89(C).
    5. Mselmi, Nada & Lahiani, Amine & Hamza, Taher, 2017. "Financial distress prediction: The case of French small and medium-sized firms," International Review of Financial Analysis, Elsevier, vol. 50(C), pages 67-80.
    6. Christian Lohmann & Thorsten Ohliger, 2020. "Bankruptcy prediction and the discriminatory power of annual reports: empirical evidence from financially distressed German companies," Journal of Business Economics, Springer, vol. 90(1), pages 137-172, February.
    7. Philippe Jardin, 2021. "Forecasting bankruptcy using biclustering and neural network-based ensembles," Annals of Operations Research, Springer, vol. 299(1), pages 531-566, April.
    8. Liébana-Cabanillas, F. & Lara-Rubio, J., 2017. "Predictive and explanatory modeling regarding adoption of mobile payment systems," Technological Forecasting and Social Change, Elsevier, vol. 120(C), pages 32-40.
    9. Korol, Tomasz, 2013. "Early warning models against bankruptcy risk for Central European and Latin American enterprises," Economic Modelling, Elsevier, vol. 31(C), pages 22-30.
    10. Antonio Blanco-Oliver & Ana Irimia-Dieguez & María Oliver-Alfonso & Nicholas Wilson, 2015. "Systemic Sovereign Risk and Asset Prices: Evidence from the CDS Market, Stressed European Economies and Nonlinear Causality Tests," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 65(2), pages 144-166, April.
    11. Beata Gavurova & Sylvia Jencova & Radovan Bacik & Marta Miskufova & Stanislav Letkovsky, 2022. "Artificial intelligence in predicting the bankruptcy of non-financial corporations," Oeconomia Copernicana, Institute of Economic Research, vol. 13(4), pages 1215-1251, December.
    12. Rogelio A. Mancisidor & Kjersti Aas, 2022. "Multimodal Generative Models for Bankruptcy Prediction Using Textual Data," Papers 2211.08405, arXiv.org, revised Feb 2024.
    13. Mohammad Mahdi Mousavi & Jamal Ouenniche, 2018. "Multi-criteria ranking of corporate distress prediction models: empirical evaluation and methodological contributions," Annals of Operations Research, Springer, vol. 271(2), pages 853-886, December.
    14. Denis Kušter & Bojana Vuković & Sunčica Milutinović & Kristina Peštović & Teodora Tica & Dejan Jakšić, 2023. "Early Insolvency Prediction as a Key for Sustainable Business Growth," Sustainability, MDPI, vol. 15(21), pages 1-24, October.
    15. Amélia Ferreira da Silva & José Henrique Brito & Mariline Lourenço & José Manuel Pereira, 2023. "Sustainability of Transport Sector Companies: Bankruptcy Prediction Based on Artificial Intelligence," Sustainability, MDPI, vol. 15(23), pages 1-13, December.

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Featured entries

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