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Indicators and Methods for Assessing the Quality of Logistic Activity Processes

Author

Listed:
  • V.I. Gissin
  • K.F. Mehantseva
  • M.A. Surzhikov

Abstract

Purpose: This article is aimed at identifying and evaluating the quality and safety indicators of processes in the logistics system and solving the problems of product control in the goods’ distribution process. Design/Methodology/Approach: In order to assess the risks and quality of control methods in the goods’ distribution processes, studies were carried out in the process of grain supply, on which the risk assessment was tested using the fault tree using a qualitative approach with a deductive logic, which allowed to identify events at the lower levels of the system. To evaluate the results when comparing various methods of monitoring the characteristics of products in the product distribution process certain statistical tools were used. The evaluation with comparative tests is required in order to determine the way of measuring products in the goods distribution logistics system. The study uses the methods of formalization, analysis, measurement, experimental and comparison. Findings: The considered risk assessment method and the given example allow us to recommend its use for the product distribution processes for various purposes. A technique is proposed for comparing various control methods based on statistical tools that can be recommended for various goods’ distribution operations. Practical implications: The results of the study can be applied in practice to improve the quality of goods’ distribution processes and reduce risks in the various supply chains. Originality/value: The main contribution of this study is to shift the emphasis on the assessment of processes in goods’ distribution to the positions of a risk-based approach and the use of various statistical tools in logistics’ activities.

Suggested Citation

  • V.I. Gissin & K.F. Mehantseva & M.A. Surzhikov, 2019. "Indicators and Methods for Assessing the Quality of Logistic Activity Processes," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), vol. 0(Special 2), pages 16-25.
  • Handle: RePEc:ers:ijebaa:v:vii:y:2019:i:special2:p:16-25
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    References listed on IDEAS

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    1. repec:ers:journl:v:special_issue:y:2018:i:1:p:156-166 is not listed on IDEAS
    2. V.I. Gissin & K.F. Mekhantseva & T.I. Putilina & M.A. Surzhikov, 2018. "«Green Economy»: Emerging National Models, Estimations, Trends in EU and CIS," European Research Studies Journal, European Research Studies Journal, vol. 0(Special1), pages 156-166.
    3. Alizadeh, Morteza & Amiri-Aref, Mehdi & Mustafee, Navonil & Matilal, Sumohon, 2019. "A robust stochastic Casualty Collection Points location problem," European Journal of Operational Research, Elsevier, vol. 279(3), pages 965-983.
    4. A.U. Albekov & T.V. Parkhomenko & A.A. Polubotko1, 2017. "Green Logistics in Russia: The Phenomenon of Progress, Economic and Environmental Security," European Research Studies Journal, European Research Studies Journal, vol. 0(1), pages 13-21.
    5. Giusti, Riccardo & Manerba, Daniele & Bruno, Giorgio & Tadei, Roberto, 2019. "Synchromodal logistics: An overview of critical success factors, enabling technologies, and open research issues," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 129(C), pages 92-110.
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    More about this item

    Keywords

    Logistic system; assessment; quality; indicators; risks control methods.;
    All these keywords.

    JEL classification:

    • M11 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - Production Management

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