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Huseyin Ince

Personal Details

First Name:Huseyin
Middle Name:
Last Name:Ince
Suffix:
RePEc Short-ID:pin52
[This author has chosen not to make the email address public]

Affiliation

İşletme Fakültesi
Gebze Teknik Üniversitesi

Kocaeli, Turkey
http://www.gtu.edu.tr/kategori/44/3/isletme-fakultesi.aspx
RePEc:edi:ifgyttr (more details at EDIRC)

Research output

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Jump to: Articles

Articles

  1. Levent Gun & Salih Zeki Imamoglu & Hulya Turkcan & Huseyin Ince, 2024. "Effect of Digital Transformation on Firm Performance in the Uncertain Environment: Transformational Leadership and Employee Self-Efficacy as Antecedents of Digital Transformation," Sustainability, MDPI, vol. 16(3), pages 1-17, January.
  2. Neslihan Latifoglu & Salih Zeki Imamoglu & Huseyin Ince & Erkut Altindag, 2023. "Effect of Leader–Member Exchange on Proactive Employee Behavior and Employee Performance: The Moderating Role of Innovative Climate," Sustainability, MDPI, vol. 15(20), pages 1-14, October.
  3. Turkcan, Hulya & Imamoglu, Salih Zeki & Ince, Huseyin, 2022. "To be more innovative and more competitive in dynamic environments: The role of additive manufacturing," International Journal of Production Economics, Elsevier, vol. 246(C).
  4. Ali Fehim Cebeci & Huseyin Ince & Murat Anil Mercan, 2020. "The intrinsic fallacy of market mechanism and private property rights in alleviating the tragedy of the commons," Applied Economics, Taylor & Francis Journals, vol. 52(33), pages 3629-3636, June.
  5. Huseyin Ince & Ali Fehim Cebeci & Salih Zeki Imamoglu, 2019. "An Artificial Neural Network-Based Approach to the Monetary Model of Exchange Rate," Computational Economics, Springer;Society for Computational Economics, vol. 53(2), pages 817-831, February.
  6. Huseyin INCE & Theodore B. TRAFALİS, 2017. "A Hybrid Forecasting Model for Stock Market Prediction," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 51(3), pages 263-280.
  7. Huseyin Ince & Bora Aktan, 2010. "A Comparative Analysis of Individual and Ensemble Credit Scoring Techniques in Evaluating Credit Card Loan Applications," Journal of BRSA Banking and Financial Markets, Banking Regulation and Supervision Agency, vol. 4(1), pages 74-90.
  8. Huseyin Ince & Bora Aktan, 2009. "A comparison of data mining techniques for credit scoring in banking: A managerial perspective," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 10(3), pages 233-240, March.
  9. Huseyin Ince, 2006. "Non-Parametric Regression Methods," Computational Management Science, Springer, vol. 3(2), pages 161-174, April.
  10. Hüseyin İNCE, 2006. "Yapay sinir ağlarının portföy yönetiminde kullanılması," Iktisat Isletme ve Finans, Bilgesel Yayincilik, vol. 21(241), pages 114-127.
  11. Bülent SEZEN & Hüseyin İNCE & Selim AREN, 2005. "Türkiye''deki Hayat Dışı Sigorta Şirketlerinin Veri Zarflama Analizi Tekniği İle Göreli Etkinlik Değerlendirmesi," Iktisat Isletme ve Finans, Bilgesel Yayincilik, vol. 20(236), pages 87-95.

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. Turkcan, Hulya & Imamoglu, Salih Zeki & Ince, Huseyin, 2022. "To be more innovative and more competitive in dynamic environments: The role of additive manufacturing," International Journal of Production Economics, Elsevier, vol. 246(C).

    Cited by:

    1. Marić, Josip & Opazo-Basáez, Marco & Vlačić, Božidar & Dabić, Marina, 2023. "Innovation management of three-dimensional printing (3DP) technology: Disclosing insights from existing literature and determining future research streams," Technological Forecasting and Social Change, Elsevier, vol. 193(C).
    2. Wong, David T.W. & Ngai, Eric W.T., 2023. "The impact of advanced manufacturing technology, sensing and analytics capabilities, and planning comprehensiveness on sustained competitive advantage: The moderating role of environmental uncertainty," International Journal of Production Economics, Elsevier, vol. 265(C).
    3. Jiawang Tang & Along Liu & Jibao Gu & Hefu Liu, 2024. "Can CEO environmental awareness promote new product development performance? Empirical research on Chinese manufacturing firms," Business Strategy and the Environment, Wiley Blackwell, vol. 33(2), pages 985-1003, February.
    4. Haug, Anders & Wickstrøm, Kent Adsbøll & Stentoft, Jan & Philipsen, Kristian, 2023. "Adoption of additive manufacturing: A survey of the role of knowledge networks and maturity in small and medium-sized Danish production firms," International Journal of Production Economics, Elsevier, vol. 255(C).

  2. Huseyin Ince & Ali Fehim Cebeci & Salih Zeki Imamoglu, 2019. "An Artificial Neural Network-Based Approach to the Monetary Model of Exchange Rate," Computational Economics, Springer;Society for Computational Economics, vol. 53(2), pages 817-831, February.

    Cited by:

    1. Haider A. Khan & Shahryar Ghorbani & Elham Shabani & Shahab S. Band, 2024. "Enhancement of Neural Networks Model’s Predictions of Currencies Exchange Rates by Phase Space Reconstruction and Harris Hawks’ Optimization," Computational Economics, Springer;Society for Computational Economics, vol. 63(2), pages 835-860, February.
    2. Zhaoyi Xu & Yuqing Zeng & Yangrong Xue & Shenggang Yang, 2022. "Early Warning of Chinese Yuan’s Exchange Rate Fluctuation and Value at Risk Measure Using Neural Network Joint Optimization Algorithm," Computational Economics, Springer;Society for Computational Economics, vol. 60(4), pages 1293-1315, December.
    3. de Souza Vasconcelos, Camila & Hadad Júnior, Eli, 2023. "Forecasting exchange rate: A bibliometric and content analysis," International Review of Economics & Finance, Elsevier, vol. 83(C), pages 607-628.
    4. Heo, Wookjae & Lee, Jae Min & Park, Narang & Grable, John E., 2020. "Using Artificial Neural Network techniques to improve the description and prediction of household financial ratios," Journal of Behavioral and Experimental Finance, Elsevier, vol. 25(C).
    5. Chang, Lei & Baloch, Zulfiqar Ali & Saydaliev, Hayot Berk & Hyder, Mansoor & Dilanchiev, Azer, 2022. "Testing oil price volatility during Covid-19: Global economic impact," Resources Policy, Elsevier, vol. 78(C).

  3. Huseyin INCE & Theodore B. TRAFALİS, 2017. "A Hybrid Forecasting Model for Stock Market Prediction," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 51(3), pages 263-280.

    Cited by:

    1. M. Mallikarjuna & R. Prabhakara Rao, 2019. "Evaluation of forecasting methods from selected stock market returns," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 5(1), pages 1-16, December.

  4. Huseyin Ince & Bora Aktan, 2009. "A comparison of data mining techniques for credit scoring in banking: A managerial perspective," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 10(3), pages 233-240, March.

    Cited by:

    1. Ulf Römer & Oliver Musshoff, 2017. "Can agricultural credit scoring for microfinance institutions be implemented and improved by weather data?," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 78(1), pages 83-97, December.
    2. J. Lara‐Rubio & A. Blanco‐Oliver & R. Pino‐Mejías, 2017. "Promoting Entrepreneurship at the Base of the Social Pyramid via Pricing Systems: A case Study," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 24(1), pages 12-28, January.
    3. Tigges, Maximilian & Mestwerdt, Sönke & Tschirner, Sebastian & Mauer, René, 2024. "Who gets the money? A qualitative analysis of fintech lending and credit scoring through the adoption of AI and alternative data," Technological Forecasting and Social Change, Elsevier, vol. 205(C).
    4. Aneta Dzik-Walczak & Mateusz Heba, 2019. "A comparison of credit scoring techniques in Peer-to-Peer lending," Working Papers 2019-16, Faculty of Economic Sciences, University of Warsaw.
    5. Patricia Durango-Gutiérrez & Juan Lara-Rubio & Andrés Navarro-Galera & Dionisio Buendía-Carrillo, 2024. "Microcredit Pricing Model for Microfinance Institutions under Basel III Banking Regulations," IJFS, MDPI, vol. 12(3), pages 1-21, September.
    6. 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.
    7. Oguz Koc & Omur Ugur & A. Sevtap Kestel, 2023. "The Impact of Feature Selection and Transformation on Machine Learning Methods in Determining the Credit Scoring," Papers 2303.05427, arXiv.org.
    8. Aneta Dzik-Walczak & Mateusz Heba, 2021. "An implementation of ensemble methods, logistic regression, and neural network for default prediction in Peer-to-Peer lending," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 39(1), pages 163-197.
    9. Omar H. Fares & Irfan Butt & Seung Hwan Mark Lee, 2023. "Utilization of artificial intelligence in the banking sector: a systematic literature review," Journal of Financial Services Marketing, Palgrave Macmillan, vol. 28(4), pages 835-852, December.
    10. Hossein Hassani & Xu Huang & Emmanuel Silva & Mansi Ghodsi, 2020. "Deep Learning and Implementations in Banking," Annals of Data Science, Springer, vol. 7(3), pages 433-446, September.

  5. Huseyin Ince, 2006. "Non-Parametric Regression Methods," Computational Management Science, Springer, vol. 3(2), pages 161-174, April.

    Cited by:

    1. Peter Winker & Marianna Lyra & Chris Sharpe, 2008. "Least Median of Squares Estimation by Optimization Heuristics with an Application to the CAPM and Multi Factor Models," Working Papers 006, COMISEF.
    2. Doron Sonsino & Tal Shavit, 2014. "Return prediction and stock selection from unidentified historical data," Quantitative Finance, Taylor & Francis Journals, vol. 14(4), pages 641-655, April.
    3. E. Lorenzo & G. Piscopo & M. Sibillo, 2024. "Addressing the economic and demographic complexity via a neural network approach: risk measures for reverse mortgages," Computational Management Science, Springer, vol. 21(1), pages 1-22, June.
    4. Alexandros Agapitos & Anthony Brabazon & Michael O’Neill, 2017. "Regularised gradient boosting for financial time-series modelling," Computational Management Science, Springer, vol. 14(3), pages 367-391, July.

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