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Research on Procurement Quality Management Evaluation of Tobacco Commercial Enterprises Based on the Balanced Scorecard

In: Proceedings of the 2026 2nd International Conference on Data Mining and Project Management (DMPM 2026)

Author

Listed:
  • Qianxi Lei

    (Shandong University of Technology, School of Accounting)

  • Zengjun Gu

    (Shandong University of Technology, School of Accounting)

Abstract

In recent years, tobacco commercial enterprises have consistently implemented high-quality development concepts, continuously improving procurement management and supervision systems. Significant enhancements in procurement management and regulatory standards have been achieved, with strengthened integrity risk prevention measures in procurement operations, providing solid safeguards for the sustainable development of the tobacco industry. However, certain operational challenges remain in procurement management practices. Enterprises need to strengthen comprehensive supervision and evaluation throughout the entire procurement process (pre-transaction, during-transaction, and post-transaction) to continuously improve procurement efficiency. Based on the Balanced Scorecard framework, this study establishes an evaluation index system for procurement quality management in tobacco commercial enterprises. Using Shandong Y City Tobacco Company as a case study, the research proposes corresponding safeguard measures for procurement quality management evaluation. The findings demonstrate that this index system effectively reflects current procurement quality management levels in tobacco commercial enterprises, showing practical applicability.

Suggested Citation

  • Qianxi Lei & Zengjun Gu, 2026. "Research on Procurement Quality Management Evaluation of Tobacco Commercial Enterprises Based on the Balanced Scorecard," Advances in Economics, Business and Management Research, in: Ljiljana Trajkovic & José Alfredo F. Costa & Zaher Al Aghbari & Nor Azman Ismail & Dariusz Jacek Jak (ed.), Proceedings of the 2026 2nd International Conference on Data Mining and Project Management (DMPM 2026), pages 168-178, Springer.
    • Handle: RePEc:spr:advbcp:978-94-6239-689-0_16
    DOI: 10.2991/978-94-6239-689-0_16
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