Russ Moro

Personal Details

First Name:	Russ
Middle Name:
Last Name:	Moro
Suffix:
RePEc Short-ID:	pmo490
	[This author has chosen not to make the email address public]
	http://www.rmoro.com

Affiliation

Department of Economics and Finance
Brunel University London

Uxbridge, United Kingdom
https://www.brunel.ac.uk/economics-and-finance
RePEc:edi:debruuk (more details at EDIRC)

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. Russ A. Moro, 2008. "Analysis of the Predictors of Default for Portuguese Firms," Working Papers w200822, Banco de Portugal, Economics and Research Department.

   Cited by:

   1. Nehrebecka Natalia, 2018. "Predicting the Default Risk of Companies. Comparison of Credit Scoring Models: Logit Vs Support Vector Machines," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 22(2), pages 54-73, June.

Articles

1. Braganza, Ashley & Brooks, Laurence & Nepelski, Daniel & Ali, Maged & Moro, Russ, 2017. "Resource management in big data initiatives: Processes and dynamic capabilities," Journal of Business Research, Elsevier, vol. 70(C), pages 328-337.

   Cited by:

   1. Erkan Bayraktar & Ekrem Tatoglu & Arafat Salih Aydiner & Dursun Delen, 2024. "Business Analytics Adoption and Technological Intensity: An Efficiency Analysis," Information Systems Frontiers, Springer, vol. 26(4), pages 1509-1526, August.
   2. Ye, Fei & Liu, Ke & Li, Lixu & Lai, Kee-Hung & Zhan, Yuanzhu & Kumar, Ajay, 2022. "Digital supply chain management in the COVID-19 crisis: An asset orchestration perspective," International Journal of Production Economics, Elsevier, vol. 245(C).
   3. Chen, Yantai & Luo, Haibei & Chen, Jin & Guo, Yanlin, 2022. "Building data-driven dynamic capabilities to arrest knowledge hiding: A knowledge management perspective," Journal of Business Research, Elsevier, vol. 139(C), pages 1138-1154.
   4. Sun, Pengfei & Yuan, Chunhui & Li, Xiaolong & Di, Jia, 2024. "Big data analytics, firm risk and corporate policies: Evidence from China," Research in International Business and Finance, Elsevier, vol. 70(PB).
   5. Rajesh Chidananda Reddy & Biplab Bhattacharjee & Debasisha Mishra & Anandadeep Mandal, 2022. "A systematic literature review towards a conceptual framework for enablers and barriers of an enterprise data science strategy," Information Systems and e-Business Management, Springer, vol. 20(1), pages 223-255, March.
   6. Zhu, Xiumei & Li, Yue, 2023. "The use of data-driven insight in ambidextrous digital transformation: How do resource orchestration, organizational strategic decision-making, and organizational agility matter?," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
   7. Azan, Wilfrid & Ivanaj, Silvester & Rolland, Olivier, 2019. "Modular path customization and knowledge transfer: Causal model learnings," Technological Forecasting and Social Change, Elsevier, vol. 140(C), pages 182-193.
   8. Ciampi, Francesco & Demi, Stefano & Magrini, Alessandro & Marzi, Giacomo & Papa, Armando, 2021. "Exploring the impact of big data analytics capabilities on business model innovation: The mediating role of entrepreneurial orientation," Journal of Business Research, Elsevier, vol. 123(C), pages 1-13.
   9. Elias G. Carayannis & David F. J. Campbell, 2021. "Democracy of Climate and Climate for Democracy: the Evolution of Quadruple and Quintuple Helix Innovation Systems," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 12(4), pages 2050-2082, December.
   10. Shamim, Saqib & Zeng, Jing & Shafi Choksy, Umair & Shariq, Syed Muhammad, 2020. "Connecting big data management capabilities with employee ambidexterity in Chinese multinational enterprises through the mediation of big data value creation at the employee level," International Business Review, Elsevier, vol. 29(6).
   11. William Villegas-Ch & Jhoann Molina-Enriquez & Carlos Chicaiza-Tamayo & Iván Ortiz-Garcés & Sergio Luján-Mora, 2019. "Application of a Big Data Framework for Data Monitoring on a Smart Campus," Sustainability, MDPI, vol. 11(20), pages 1-15, October.
   12. J. Piet Hausberg & Kirsten Liere-Netheler & Sven Packmohr & Stefanie Pakura & Kristin Vogelsang, 2019. "Research streams on digital transformation from a holistic business perspective: a systematic literature review and citation network analysis," Journal of Business Economics, Springer, vol. 89(8), pages 931-963, December.
   13. Muhammad Anwar & Sher Zaman Khan & Syed Zulfiqar Ali Shah, 2018. "Big Data Capabilities and Firm’s Performance: A Mediating Role of Competitive Advantage," Journal of Information & Knowledge Management (JIKM), World Scientific Publishing Co. Pte. Ltd., vol. 17(04), pages 1-28, December.
   14. Nguyen Anh Khoa Dam & Thang Le Dinh & William Menvielle, 2019. "A systematic literature review of big data adoption in internationalization," Journal of Marketing Analytics, Palgrave Macmillan, vol. 7(3), pages 182-195, September.
   15. Seunghwan Myeong & Michael J. Ahn & Younhee Kim & Shengli Chu & Woojong Suh, 2021. "Government Data Performance: The Roles of Technology, Government Capacity, and Globalization through the Effects of National Innovativeness," Sustainability, MDPI, vol. 13(22), pages 1-14, November.
   16. de Camargo Fiorini, Paula & Roman Pais Seles, Bruno Michel & Chiappetta Jabbour, Charbel Jose & Barberio Mariano, Enzo & de Sousa Jabbour, Ana Beatriz Lopes, 2018. "Management theory and big data literature: From a review to a research agenda," International Journal of Information Management, Elsevier, vol. 43(C), pages 112-129.
   17. Chong, Woon Kian & Chang, Chiachi, 2024. "Information exploitation of human resource data with persistent homology," Journal of Business Research, Elsevier, vol. 172(C).
   18. Lin, Canchu & Kunnathur, Anand, 2019. "Strategic orientations, developmental culture, and big data capability," Journal of Business Research, Elsevier, vol. 105(C), pages 49-60.
   19. Elias G. Carayannis & David F. J. Campbell & Evangelos Grigoroudis, 2022. "Helix Trilogy: the Triple, Quadruple, and Quintuple Innovation Helices from a Theory, Policy, and Practice Set of Perspectives," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 13(3), pages 2272-2301, September.
   20. Zhou, Zhongsheng & Li, Zhuo & Du, Shanzhong & Cao, June, 2024. "Robot adoption and enterprise R&D manipulation: Evidence from China," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
   21. Paulo Renato de Sousa & Marcelo Werneck Barbosa & Leise Kelli de Oliveira & Paulo Tarso Vilela de Resende & Ricardo Ruiz Rodrigues & Myrian Teixeira Moura & Daniel Matoso, 2021. "Challenges, Opportunities, and Lessons Learned: Sustainability in Brazilian Omnichannel Retail," Sustainability, MDPI, vol. 13(2), pages 1-17, January.
   22. Ren, Yu & Wu, Kuo-Jui & Lim, Ming K. & Tseng, Ming-Lang, 2023. "Technology transfer adoption to achieve a circular economy model under resource-based view: A high-tech firm," International Journal of Production Economics, Elsevier, vol. 264(C).
   23. Liedong, Tahiru Azaaviele & Rajwani, Tazeeb & Lawton, Thomas C., 2020. "Information and nonmarket strategy: Conceptualizing the interrelationship between big data and corporate political activity," Technological Forecasting and Social Change, Elsevier, vol. 157(C).
   24. Rialti, Riccardo & Zollo, Lamberto & Ferraris, Alberto & Alon, Ilan, 2019. "Big data analytics capabilities and performance: Evidence from a moderated multi-mediation model," Technological Forecasting and Social Change, Elsevier, vol. 149(C).
   25. Di Vaio, Assunta & Hassan, Rohail & Alavoine, Claude, 2022. "Data intelligence and analytics: A bibliometric analysis of human–Artificial intelligence in public sector decision-making effectiveness," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
   26. Daniel Nepelski & Maciej Sobolewski, 2020. "Estimating investments in General Purpose Technologies. The case of AI Investments in Europe," JRC Research Reports JRC118953, Joint Research Centre.
   27. Kamble, Sachin S. & Gunasekaran, Angappa & Gawankar, Shradha A., 2020. "Achieving sustainable performance in a data-driven agriculture supply chain: A review for research and applications," International Journal of Production Economics, Elsevier, vol. 219(C), pages 179-194.
   28. Wang, Hua & Liao, Lingtao & Wu, Ji (George), 2023. "Robot adoption and firm's capacity utilization: Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 82(C).
   29. Carlos Ferreira & Alessandro Merendino & Maureen Meadows, 2023. "Disruption and Legitimacy: Big Data in Society," Information Systems Frontiers, Springer, vol. 25(3), pages 1081-1100, June.
   30. El-Kassar, Abdul-Nasser & Singh, Sanjay Kumar, 2019. "Green innovation and organizational performance: The influence of big data and the moderating role of management commitment and HR practices," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 483-498.
   31. Sharma, Rohit & Jain, Geetika & Paul, Justin, 2023. "Does the world need to change its vaccine distribution strategy for COVID-19?," Technovation, Elsevier, vol. 126(C).
   32. Wang, Jing & Yu, Huaying & Ren, Daowen & Zhang, Jocelyn, 2023. "Promoting mineral resources consumption efficiency: Evidence from technology of big data," Resources Policy, Elsevier, vol. 86(PB).
   33. Sheng, Jie & Amankwah-Amoah, Joseph & Wang, Xiaojun, 2017. "A multidisciplinary perspective of big data in management research," International Journal of Production Economics, Elsevier, vol. 191(C), pages 97-112.
   34. Xiang, Guopeng & Peng, Mixiang & Tang, Fei & Liu, Yuan, 2024. "Unpacking the impact of entrepreneurial learning on business model innovation in internet startups: Mediating roles of digital capabilities," Technology in Society, Elsevier, vol. 77(C).
   35. Manuela Nocker & Vania Sena, 2019. "Big Data and Human Resources Management: The Rise of Talent Analytics," Social Sciences, MDPI, vol. 8(10), pages 1-19, September.
   36. Brinch, Morten & Gunasekaran, Angappa & Fosso Wamba, Samuel, 2021. "Firm-level capabilities towards big data value creation," Journal of Business Research, Elsevier, vol. 131(C), pages 539-548.
   37. Merendino, Alessandro & Dibb, Sally & Meadows, Maureen & Quinn, Lee & Wilson, David & Simkin, Lyndon & Canhoto, Ana, 2018. "Big data, big decisions: The impact of big data on board level decision-making," Journal of Business Research, Elsevier, vol. 93(C), pages 67-78.
   38. Candice WALLS & Brian BARNARD, 2020. "Success Factors of Big Data to Achieve Organisational Performance: Theoretical Perspectives," Expert Journal of Business and Management, Sprint Investify, vol. 8(1), pages 1-16.
   39. Elisabetta Raguseo & Claudio Vitari, 2017. "Investments in big data analytics and firm performance: an empirical investigation of direct and mediating effects," Post-Print halshs-01923259, HAL.
   40. Haitham Mohsin Kareem & Mohammed Dauwed & Ahmed Meri & Mu’taman Jarrar & Mohammad Al-Bsheish & Ali Abdulameer Aldujaili, 2021. "The Role of Accounting Information System and Knowledge Management to Enhancing Organizational Performance in Iraqi SMEs," Sustainability, MDPI, vol. 13(22), pages 1-13, November.
   41. Wei-wei Zhang & Jyoti Bhola & Rajeev Kumar & Nitin Saluja, 2022. "Study and analysis of big data for characterization of user association in large scale," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(1), pages 375-384, March.
   42. Meadows, Maureen & Merendino, Alessandro & Dibb, Sally & Garcia-Perez, Alexeis & Hinton, Matthew & Papagiannidis, Savvas & Pappas, Ilias & Wang, Huamao, 2022. "Tension in the data environment: How organisations can meet the challenge," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
   43. Kristoffersen, Eivind & Mikalef, Patrick & Blomsma, Fenna & Li, Jingyue, 2021. "Towards a business analytics capability for the circular economy," Technological Forecasting and Social Change, Elsevier, vol. 171(C).
   44. Gao, Yuqiang & Wang, Zishuai & Wang, Kaihua & Zhang, Ruiai & Lu, Yuchen, 2023. "Effect of big data on enterprise financialization: Evidence from China's SMEs," Technology in Society, Elsevier, vol. 75(C).
   45. Jorge António Barbosa Ferreira & Arnaldo Coelho & Laodicéia Amorim Weersma, 2019. "The mediating effect of strategic orientation, innovation capabilities and managerial capabilities among exploration and exploitation, competitive advantage and firm’s performance," Contaduría y Administración, Accounting and Management, vol. 64(1), pages 49-50, Enero-Mar.
   46. Claudio Vitari & Elisabetta Raguseo, 2019. "Big data analytics business value and firm performance: Linking with environmental context," Post-Print hal-02293765, HAL.
   47. Huemer, Lars & Wang, Xiaobei, 2021. "Resource bundles and value creation: An analytical framework," Journal of Business Research, Elsevier, vol. 134(C), pages 720-728.
   48. Kim, Jaemin & Dibrell, Clay & Kraft, Ellen & Marshall, David, 2021. "Data analytics and performance: The moderating role of intuition-based HR management in major league baseball," Journal of Business Research, Elsevier, vol. 122(C), pages 204-216.
   49. Yunis, Manal & Tarhini, Abbas & Kassar, Abdulnasser, 2018. "The role of ICT and innovation in enhancing organizational performance: The catalysing effect of corporate entrepreneurship," Journal of Business Research, Elsevier, vol. 88(C), pages 344-356.
   50. Sher Jahan Khan & Puneet Kaur & Fauzia Jabeen & Amandeep Dhir, 2021. "Green process innovation: Where we are and where we are going," Business Strategy and the Environment, Wiley Blackwell, vol. 30(7), pages 3273-3296, November.
   51. Roßmann, Bernhard & Canzaniello, Angelo & von der Gracht, Heiko & Hartmann, Evi, 2018. "The future and social impact of Big Data Analytics in Supply Chain Management: Results from a Delphi study," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 135-149.
   52. Teresa Martí‐Rosselló & Andrew J. Duncan & Euan Bowditch, 2024. "Seeing the data for the trees: Assessing the data maturity and readiness of a UK forestry company," Business Strategy and the Environment, Wiley Blackwell, vol. 33(2), pages 149-161, February.
   53. Song, Malin & Fisher, Ron & Kwoh, Yusen, 2019. "Technological challenges of green innovation and sustainable resource management with large scale data," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 361-368.
   54. Amit Kumar & Bala Krishnamoorthy, 2020. "Business Analytics Adoption in Firms: A Qualitative Study Elaborating TOE Framework in India," International Journal of Global Business and Competitiveness, Springer, vol. 15(2), pages 80-93, December.
   55. Tugba Karaboga & Cemal Zehir & Ekrem Tatoglu & H. Aykut Karaboga & Abderaouf Bouguerra, 2023. "Big data analytics management capability and firm performance: the mediating role of data-driven culture," Review of Managerial Science, Springer, vol. 17(8), pages 2655-2684, November.
   56. Nan Wang & Wenxuan Xie & Yalan Huang & Zhenzhong Ma, 2023. "Big Data capability and sustainability oriented innovation: The mediating role of intellectual capital," Business Strategy and the Environment, Wiley Blackwell, vol. 32(8), pages 5702-5720, December.
   57. Alberto Bertello & Alberto Ferraris & Stefano Bresciani & Paola Bernardi, 2021. "Big data analytics (BDA) and degree of internationalization: the interplay between governance of BDA infrastructure and BDA capabilities," Journal of Management & Governance, Springer;Accademia Italiana di Economia Aziendale (AIDEA), vol. 25(4), pages 1035-1055, December.
   58. Fernando ALMEIDA & Samantha LOW-CHOY, 2021. "Exploring The Relationship Between Big Data And Firm Performance," Management Research and Practice, Research Centre in Public Administration and Public Services, Bucharest, Romania, vol. 13(3), pages 43-57, September.
   59. Rodríguez-Espíndola, Oscar & Cuevas-Romo, Ana & Chowdhury, Soumyadeb & Díaz-Acevedo, Natalie & Albores, Pavel & Despoudi, Stella & Malesios, Chrisovalantis & Dey, Prasanta, 2022. "The role of circular economy principles and sustainable-oriented innovation to enhance social, economic and environmental performance: Evidence from Mexican SMEs," International Journal of Production Economics, Elsevier, vol. 248(C).
   60. Paolo Bogarelli & Nicola Castellano, 2023. "L?implementazione di tecnologie 4.0 nelle piccole imprese: analisi di un caso di successo," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2023(2), pages 137-164.
   61. Kristoffersen, Eivind & Mikalef, Patrick & Blomsma, Fenna & Li, Jingyue, 2021. "The effects of business analytics capability on circular economy implementation, resource orchestration capability, and firm performance," International Journal of Production Economics, Elsevier, vol. 239(C).
   62. Mahdi, Omar Rabeea & Nassar, Islam A. & Almsafir, Mahmoud Khalid, 2019. "Knowledge management processes and sustainable competitive advantage: An empirical examination in private universities," Journal of Business Research, Elsevier, vol. 94(C), pages 320-334.
   63. Hultman, Johan & Corvellec, Hervé & Jerneck, Anne & Arvidsson, Susanne & Ekroos, Johan & Gustafsson, Clara & Lundh Nilsson, Fay & Wahlberg, Niklas, 2021. "A resourcification manifesto: Understanding the social process of resources becoming resources," Research Policy, Elsevier, vol. 50(9).
   64. Nudurupati, Sai Sudhakar & Budhwar, Pawan & Pappu, Raja Phani & Chowdhury, Soumyadeb & Kondala, Mukesh & Chakraborty, Ayon & Ghosh, Sadhan Kumar, 2022. "Transforming sustainability of Indian small and medium-sized enterprises through circular economy adoption," Journal of Business Research, Elsevier, vol. 149(C), pages 250-269.

2. Shiyi Chen & W. K. Hardle & R. A. Moro, 2011. "Modeling default risk with support vector machines," Quantitative Finance, Taylor & Francis Journals, vol. 11(1), pages 135-154.

   Cited by:

   1. Sariev, Eduard & Germano, Guido, 2020. "Bayesian regularized artificial neural networks for the estimation of the probability of default," LSE Research Online Documents on Economics 101029, London School of Economics and Political Science, LSE Library.
      • Eduard Sariev & Guido Germano, 2020. "Bayesian regularized artificial neural networks for the estimation of the probability of default," Quantitative Finance, Taylor & Francis Journals, vol. 20(2), pages 311-328, February.
   2. Zieba, Maciej & Härdle, Wolfgang Karl, 2016. "Beta-boosted ensemble for big credit scoring data," SFB 649 Discussion Papers 2016-052, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
   3. Davidescu Adriana AnaMaria & Agafiței Marina-Diana & Strat Vasile Alecsandru & Dima Alina Mihaela, 2024. "Mapping the Landscape: A Bibliometric Analysis of Rating Agencies in the Era of Artificial Intelligence and Machine Learning," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 18(1), pages 67-85.
   4. Ahmed, Shamima & Alshater, Muneer M. & Ammari, Anis El & Hammami, Helmi, 2022. "Artificial intelligence and machine learning in finance: A bibliometric review," Research in International Business and Finance, Elsevier, vol. 61(C).
      • Shamima Ahmed & Muneer Alshater & Anis El Ammari & Helmi Hammami, 2022. "Artificial intelligence and machine learning in finance: A bibliometric review," Post-Print hal-03697290, HAL.
   5. Sariev, Eduard & Germano, Guido, 2018. "An innovative feature selection method for support vector machines and its test on the estimation of the credit risk of default," LSE Research Online Documents on Economics 100211, London School of Economics and Political Science, LSE Library.
      • Eduard Sariev & Guido Germano, 2019. "An innovative feature selection method for support vector machines and its test on the estimation of the credit risk of default," Review of Financial Economics, John Wiley & Sons, vol. 37(3), pages 404-427, July.
   6. Kim Long Tran & Hoang Anh Le & Thanh Hien Nguyen & Duc Trung Nguyen, 2022. "Explainable Machine Learning for Financial Distress Prediction: Evidence from Vietnam," Data, MDPI, vol. 7(11), pages 1-12, November.
   7. Ozturk, Huseyin & Namli, Ersin & Erdal, Halil Ibrahim, 2016. "Modelling sovereign credit ratings: The accuracy of models in a heterogeneous sample," Economic Modelling, Elsevier, vol. 54(C), pages 469-478.
   8. 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.
   9. Härdle, Wolfgang Karl & Prastyo, Dedy Dwi, 2013. "Default risk calculation based on predictor selection for the Southeast Asian industry," SFB 649 Discussion Papers 2013-037, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
   10. Slawomir Juszczyk & Rafal Balina, 2013. "Effectiveness of Polish and Foreign Disdcriminant Models," Diversity, Technology, and Innovation for Operational Competitiveness: Proceedings of the 2013 International Conference on Technology Innovation and Industrial Management,, ToKnowPress.
   11. Zybura, Jan & Zybura, Nora & Ahrens, Jan-Philipp & Woywode, Michael, 2021. "Innovation in the post-succession phase of family firms: Family CEO successors and leadership constellations as resources," Journal of Family Business Strategy, Elsevier, vol. 12(2).
   12. Dedy Dwi Prastyo & Härdle, Wolfgang Karl, 2014. "Localising forward intensities for multiperiod corporate default," SFB 649 Discussion Papers 2014-040, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
   13. 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.
   14. Shiyi Chen & Wolfgang K. Härdle & Kiho Jeong, 2010. "Forecasting volatility with support vector machine-based GARCH model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(4), pages 406-433.
   15. Huseyin Ozturk & Ersin Namli & Halil Ibrahim Erdal, 2016. "Reducing Overreliance on Sovereign Credit Ratings: Which Model Serves Better?," Computational Economics, Springer;Society for Computational Economics, vol. 48(1), pages 59-81, June.
   16. Hector O. Zapata & Supratik Mukhopadhyay, 2022. "A Bibliometric Analysis of Machine Learning Econometrics in Asset Pricing," JRFM, MDPI, vol. 15(11), pages 1-17, November.
   17. Härdle, Wolfgang Karl & Huang, Li-shan, 2013. "Analysis of deviance in generalized partial linear models," SFB 649 Discussion Papers 2013-028, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
   18. Evangelos Liaras & Michail Nerantzidis & Antonios Alexandridis, 2024. "Machine learning in accounting and finance research: a literature review," Review of Quantitative Finance and Accounting, Springer, vol. 63(4), pages 1431-1471, November.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 1 paper announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.

1. NEP-FOR: Forecasting (1) 2011-05-30
2. NEP-SEA: South East Asia (1) 2011-05-30

Corrections

All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. For general information on how to correct material on RePEc, see these instructions.

To update listings or check citations waiting for approval, Russ Moro should log into the RePEc Author Service.

To make corrections to the bibliographic information of a particular item, find the technical contact on the abstract page of that item. There, details are also given on how to add or correct references and citations.

To link different versions of the same work, where versions have a different title, use this form. Note that if the versions have a very similar title and are in the author's profile, the links will usually be created automatically.

Please note that most corrections can take a couple of weeks to filter through the various RePEc services.