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The Proliferation of Artificial Intelligence in the Forklift Industry—An Analysis for the Case of Romania

Author

Listed:
  • Alexandru-Silviu Goga

    (Engineering and Industrial Management, The Faculty of Technological Engineering and Industrial Management, Transilvania University of Brașov, 500036 Brașov, Romania)

  • Zsolt Toth

    (Engineering and Industrial Management, The Faculty of Technological Engineering and Industrial Management, Transilvania University of Brașov, 500036 Brașov, Romania)

  • Mihai-Alin Meclea

    (Engineering and Industrial Management, The Faculty of Technological Engineering and Industrial Management, Transilvania University of Brașov, 500036 Brașov, Romania)

  • Ionela-Roxana Puiu

    (Engineering and Industrial Management, The Faculty of Technological Engineering and Industrial Management, Transilvania University of Brașov, 500036 Brașov, Romania)

  • Mircea Boșcoianu

    (Engineering and Industrial Management, The Faculty of Technological Engineering and Industrial Management, Transilvania University of Brașov, 500036 Brașov, Romania)

Abstract

This paper investigates the impact of artificial intelligence (AI) on the forklift industry, focusing on logistics and procurement within small and medium-sized enterprises (SMEs) in Romania. Using a mixed-methods approach, including interviews with seven managers from a benchmarked company in the forklift industry (BCFI) and quantitative analysis of operational data, we examine the transformative effects of AI integration. Key findings include a 30% reduction in inventory holding costs due to AI-powered predictive analytics; a 15% decrease in procurement costs through AI-driven supplier evaluation systems; a 25% increase in operational efficiency from AI-optimized route planning; a 40% boost in overall productivity attributed to AI-enabled automation; and a projected 20% reduction in low-skilled labor requirements over the next five years. The study employs environmental, social, and corporate governance (ESG), balanced scorecard (BSC), benchmarking, and activity-based management (ABM) models to analyze risks and implications of AI integration. A case study of a leading Romanian SME in the forklift industry is presented, examining financial strategies using McKinsey’s 7S framework. The paper concludes that while AI offers significant operational benefits, it also presents challenges in workforce transition and ethical considerations that require careful management.

Suggested Citation

  • Alexandru-Silviu Goga & Zsolt Toth & Mihai-Alin Meclea & Ionela-Roxana Puiu & Mircea Boșcoianu, 2024. "The Proliferation of Artificial Intelligence in the Forklift Industry—An Analysis for the Case of Romania," Sustainability, MDPI, vol. 16(21), pages 1-25, October.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:21:p:9306-:d:1507234
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    References listed on IDEAS

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    1. Gerda Žigienė & Egidijus Rybakovas & Robertas Alzbutas, 2019. "Artificial Intelligence Based Commercial Risk Management Framework for SMEs," Sustainability, MDPI, vol. 11(16), pages 1-23, August.
    2. Amiri, Zahra & Heidari, Arash & Navimipour, Nima Jafari, 2024. "Comprehensive survey of artificial intelligence techniques and strategies for climate change mitigation," Energy, Elsevier, vol. 308(C).
    3. Ruiqi Wei & Catherine Pardo, 2022. "Artificial intelligence and SMEs : How can B2B SMEs leverage AI platforms to integrate AI technologies?," Post-Print hal-04325639, HAL.
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    Cited by:

    1. Mircea Boșcoianu & Zsolt Toth & Alexandru-Silviu Goga, 2025. "Sustainable Strategies to Reduce Logistics Costs Based on Cross-Docking—The Case of Emerging European Markets," Sustainability, MDPI, vol. 17(14), pages 1-28, July.
    2. Zsolt Toth & Alexandru-Silviu Goga & Mircea Boșcoianu, 2025. "AI Integration in Fundamental Logistics Components: Advanced Theoretical Framework for Knowledge Process Capabilities and Dynamic Capabilities Hybridization," Logistics, MDPI, vol. 9(4), pages 1-22, October.
    3. Pohrib Silvia-Daniela & Goga Alexandru-Silviu & Pîsla Adrian, 2025. "Smart ERP Systems – From Data to Decisions," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 19(1), pages 380-401.

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