arXiv 3 May 2024 · Econometrics · publishedInternational Journal of Business Research (2023)
arXiv:2405.01913 · PDF · DOI · OpenAlex · Extracted main text
This pioneering research introduces a novel approach for decision-makers in the heavy machinery industry, specifically focusing on production management. The study integrates machine learning techniques like Ridge Regression, Markov chain analysis, and radar charts to optimize North American Crawler Cranes market production processes. Ridge Regression enables growth pattern identification and performance assessment, facilitating comparisons and addressing industry challenges. Markov chain analysis evaluates risk factors, aiding in informed decision-making and risk management. Radar charts simulate benchmark product designs, enabling data-driven decisions for production optimization. This interdisciplinary approach equips decision-makers with transformative insights, enhancing competitiveness in the heavy machinery industry and beyond. By leveraging these techniques, companies can revolutionize their production management strategies, driving success in diverse markets.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Dormann, Carsten F, Jane Elith, Sven Bacher, Carsten Buchmann, Gudru… (2013) Collinearity: a review of methods to deal with it and a simulation study evaluating their performance | 0.644 | 2 | 2 | 100% |
| 2 | Ranjan, Jayanthi (2009) Business intelligence: Concepts, components, techniques and benefits | 0.405 | 1 | 1 | 100% |
| 3 | Barney, Jay B (1995) Looking inside for competitive advantage | 0.405 | 1 | 1 | 100% |
| 4 | Chinowsky, Paul S, and James E Meredith (2000) Strategic management in construction | 0.405 | 1 | 1 | 100% |
| 5 | Nyambane, JM, and S Bett (2018) Competitive advantage and performance of heavy construction equipment suppliers in Kenya: Case of Nairobi County | 0.405 | 1 | 1 | 100% |
| 6 | Lee, Sang-Hyo, Rak-Keun Jeon, Ju-Hyung Kim, and Jae-Jun Kim (2011) Strategies for developing countries to expand their shares in the global construction market: Phase-based SWOT and AAA analyses… | 0.405 | 1 | 1 | 100% |
| 7 | Lee, Kang-Wook, Seung H Han, Heedae Park, and H David Jeong (2016) Empirical analysis of host-country effects in the international construction market: An industry-level approach | 0.405 | 1 | 1 | 100% |
| 8 | Harstad, Ronald M (1990) Alternative common-value auction procedures: Revenue comparisons with free entry | 0.405 | 1 | 1 | 100% |
| 9 | Netessine, Serguei, and Robert A Shumsky (2005) Revenue management games: Horizontal and vertical competition | 0.405 | 1 | 1 | 100% |
| 10 | Hartmann, George C (2003) Linking R&D spending to revenue growth | 0.405 | 1 | 1 | 100% |
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