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Impact of the Product Master Data Quality on the Logistics Process Performance

Author

Listed:
  • Diana Božić

    (Faculty of Transport and Traffic Science, University of Zagreb, Vukelićeva 4, 10000 Zagreb, Croatia)

  • Margareta Živičnjak

    (Faculty of Transport and Traffic Science, University of Zagreb, Vukelićeva 4, 10000 Zagreb, Croatia)

  • Ratko Stanković

    (Faculty of Transport and Traffic Science, University of Zagreb, Vukelićeva 4, 10000 Zagreb, Croatia)

  • Andrej Ignjatić

    (Faculty of Organization and Informatics, University of Zagreb, Pavlinska 2, 42000 Varaždin, Croatia)

Abstract

Background: The importance of up-to-date product master data in the digital age should not be underestimated. However, companies still struggle to ensure high-quality product data, especially in the field of logistics. Hence, the focus of our research lies in the disregard of the importance of product data quality to the performance of logistics processes. Methods: The analysis of the influence of product data on the performance of logistics processes was carried out using data from two fast-moving consumer goods (FMCG) distribution and retail companies. Data were gathered via interviews, while process activities were timed using a stopwatch, and interruptions were documented. The significance of the impact was determined using inferential statistical procedures based on the variable and the measurement scale type employed. Results: The quality of product master data has a significant impact on the performance of logistics processes; while managers are aware of the complications, they lack the motivation to detect and analyse such inaccuracies. Conclusions: The findings enhance comprehension of the obstacles generated by inadequate product data in logistics, which obstruct optimisation, and offer numerical proof of the impact of product data quality on logistics performance, thus expanding the current body of research.

Suggested Citation

  • Diana Božić & Margareta Živičnjak & Ratko Stanković & Andrej Ignjatić, 2024. "Impact of the Product Master Data Quality on the Logistics Process Performance," Logistics, MDPI, vol. 8(2), pages 1-19, April.
    • Handle: RePEc:gam:jlogis:v:8:y:2024:i:2:p:43-:d:1374778
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    References listed on IDEAS

    as
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    3. Kai M. Hüner & Andreas Schierning & Boris Otto & Hubert Österle, 2011. "Product data quality in supply chains: the case of Beiersdorf," Electronic Markets, Springer;IIM University of St. Gallen, vol. 21(2), pages 141-154, June.
    4. Tiwari, Sunil & Sharma, Pankaj & Jha, Ashish Kumar, 2024. "Digitalization & Covid-19: An institutional-contingency theoretic analysis of supply chain digitalization," International Journal of Production Economics, Elsevier, vol. 267(C).
    5. Jairo R. Montoya-Torres & Diego A. Ortiz-Vargas, 2014. "Collaboration and information sharing in dyadic supply chains: A literature review over the period 2000–2012," Estudios Gerenciales, Universidad Icesi, November.
    6. Zhao, Nanyang & Hong, Jiangtao & Lau, Kwok Hung, 2023. "Impact of supply chain digitalization on supply chain resilience and performance: A multi-mediation model," International Journal of Production Economics, Elsevier, vol. 259(C).
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