Machine learning for pattern discovery in management research

Citations

Cited by:

1. Carl-Christian Groh, 2024. "Big Data and Inequality," CRC TR 224 Discussion Paper Series crctr224_2024_555, University of Bonn and University of Mannheim, Germany.
2. Stefano Cabras & J. D. Tena, 2023. "Implicit institutional incentives and individual decisions: Causal inference with deep learning models," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(6), pages 3739-3754, September.
   • Stefano Cabras & J.D. Tena, 2022. "Implicit Institutional Incentives and Individual Decisions: Causal Inference with Deep Learning Models," Working Papers 202218, University of Liverpool, Department of Economics.
3. Zhang, Jianhong & van Witteloostuijn, Arjen & Zhou, Chaohong & Zhou, Shengyang, 2024. "Cross-border acquisition completion by emerging market MNEs revisited: Inductive evidence from a machine learning analysis," Journal of World Business, Elsevier, vol. 59(2).
4. Cong Cheng & Jian Dai, 2025. "Predicting Cross-border Merger and Acquisition Completion through CEO Characteristics: A Machine Learning Approach," Management International Review, Springer, vol. 65(1), pages 43-84, February.
5. Zaman, Rashid, 2024. "When corporate culture matters: The case of stakeholder violations," The British Accounting Review, Elsevier, vol. 56(1).
6. Li, Wanqing & Yu, Jiang & Chen, Feng, 2025. "Linking firm performance with innovation culture: An algorithmic approach towards theory building," Journal of Business Research, Elsevier, vol. 187(C).
7. Yingda Lu & Anjana Susarla & Kiron Ravindran & Deepa Mani, 2024. "Machine learning approaches to understand IT outsourcing portfolios," Electronic Commerce Research, Springer, vol. 24(4), pages 2547-2577, December.
8. Majid Majzoubi & Eric Yanfei Zhao, 2023. "Going beyond optimal distinctiveness: Strategic positioning for gaining an audience composition premium," Strategic Management Journal, Wiley Blackwell, vol. 44(3), pages 737-777, March.
9. Prothit Sen & Phanish Puranam, 2022. "Do Alliance portfolios encourage or impede new business practice adoption? Theory and evidence from the private equity industry," Strategic Management Journal, Wiley Blackwell, vol. 43(11), pages 2279-2312, November.
10. Li, Hui & Chen, Xi-Zhuo, 2024. "Tourism-industrial atmosphere and executive change: How can they impact firms? - A mixed context analysis study," Annals of Tourism Research, Elsevier, vol. 109(C).
11. Joseph Raffiee & Daniel Fehder & Florenta Teodoridis, 2022. "Revealing the revealed preferences of public firm CEOs and top executives: A new database from credit card spending," Strategic Management Journal, Wiley Blackwell, vol. 43(10), pages 2042-2065, October.
12. Valerio Veglio & Rubina Romanello & Torben Pedersen, 2025. "Employee turnover in multinational corporations: a supervised machine learning approach," Review of Managerial Science, Springer, vol. 19(3), pages 687-728, March.
13. Bagherzadeh, Mehdi & Ghaderi, Mohammad & Fernandez, Anne-Sophie, 2022. "Coopetition for innovation - the more, the better? An empirical study based on preference disaggregation analysis," European Journal of Operational Research, Elsevier, vol. 297(2), pages 695-708.
14. Benjamin L. Hallen & Susan L. Cohen & Sung Ho Park, 2023. "Are seed accelerators status springboards for startups? Or sand traps?," Strategic Management Journal, Wiley Blackwell, vol. 44(8), pages 2060-2096, August.
15. Graham, Byron & Bonner, Karen, 2024. "The role of institutions in early-stage entrepreneurship: An explainable artificial intelligence approach," Journal of Business Research, Elsevier, vol. 175(C).
16. Schade, Philipp & Schuhmacher, Monika C., 2023. "Predicting entrepreneurial activity using machine learning," Journal of Business Venturing Insights, Elsevier, vol. 19(C).
17. Ricardo Costa-Climent & Samuel Ribeiro Navarrete & Darek M. Haftor & Marcin W. Staniewski, 2024. "Value creation and appropriation from the use of machine learning: a study of start-ups using fuzzy-set qualitative comparative analysis," International Entrepreneurship and Management Journal, Springer, vol. 20(2), pages 935-967, June.
18. Liu, Feng & Wang, Rongping & Fang, Mingjie, 2024. "Mapping green innovation with machine learning: Evidence from China," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
19. Milan Miric & Nan Jia & Kenneth G. Huang, 2023. "Using supervised machine learning for large‐scale classification in management research: The case for identifying artificial intelligence patents," Strategic Management Journal, Wiley Blackwell, vol. 44(2), pages 491-519, February.
20. Joseph S. Harrison & Matthew A. Josefy & Matias Kalm & Ryan Krause, 2023. "Using supervised machine learning to scale human‐coded data: A method and dataset in the board leadership context," Strategic Management Journal, Wiley Blackwell, vol. 44(7), pages 1780-1802, July.
21. Kinkel, Steffen & Baumgartner, Marco & Cherubini, Enrica, 2022. "Prerequisites for the adoption of AI technologies in manufacturing – Evidence from a worldwide sample of manufacturing companies," Technovation, Elsevier, vol. 110(C).
22. Daniel Musafiri Balungu & Avinash Kumar, 2024. "Forecasting The Economic Growth of Sverdlovsk Region: A Comparative Analysis of Machine Learning, Linear Regression and Autoregressive Models," Journal of Applied Economic Research, Graduate School of Economics and Management, Ural Federal University, vol. 23(3), pages 674-695.
23. Islam, Towhidul & Meade, Nigel & Carson, Richard T. & Louviere, Jordan J. & Wang, Juan, 2022. "The usefulness of socio-demographic variables in predicting purchase decisions: Evidence from machine learning procedures," Journal of Business Research, Elsevier, vol. 151(C), pages 324-338.
24. Dahlander, Linus & Beretta, Michela & Thomas, Arne & Kazemi, Shahab & Fenger, Morten H.J. & Frederiksen, Lars, 2023. "Weeding out or picking winners in open innovation? Factors driving multi-stage crowd selection on LEGO ideas," Research Policy, Elsevier, vol. 52(10).
25. Bas Bosma & Arjen Witteloostuijn, 2024. "Machine learning in international business," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 55(6), pages 676-702, August.
26. Constance E. Helfat & Aseem Kaul & David J. Ketchen & Jay B. Barney & Olivier Chatain & Harbir Singh, 2023. "Renewing the resource‐based view: New contexts, new concepts, and new methods," Strategic Management Journal, Wiley Blackwell, vol. 44(6), pages 1357-1390, June.
27. Yuanyang Teng & Yicun Li & Xiaobo Wu, 2024. "Exploring the mechanism of path-creating strategy for latecomers: a combined approach of econometrics and causal machine learning," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-18, December.