The Influence of Big Data on the Definition of Key Logistic Performance Indicators for Customer Satisfaction: A Systematic Literature Review

Authors

  • Luis Alfonso Melgarejo Zelaya Universidad Nacional Mayor de San Marcos, Facultad de Ingeniería de Sistemas e Informática. Lima, Peru
  • Jose Santisteban Universidad Nacional Mayor de San Marcos, Facultad de Ingeniería de Sistemas e Informática. Lima, Peru

DOI:

https://doi.org/10.15381/rpcs.v6i1.28533

Keywords:

Key Performance Indicators (KPIs), Big Data, Customer Satisfaction, Supply Chain

Abstract

The present study conducted a Systematic Literature Review (SLR) on the influence of Big Data in the definition of Key Performance Indicators (KPIs) in logistics and their impact on customer satisfaction. The reviewed literature showed numerous studies on the use of Big Data in logistics; however, there were few efforts that synthesized aspects such as defined KPIs, developed methods, and implemented tools. The objective was to explore and analyze how Big Data supported the definition of logistics KPIs and its influence on customer satisfaction. The methodology encompassed three stages: planning, implementation, and results, following Kitchenham's approach. A review protocol was established with key research questions and inclusion and exclusion criteria. Systematic searches were conducted in relevant databases, and pertinent studies were selected. The results revealed that the definition of KPIs varied according to context and industry; 23 KPIs, 9 Big Data methods, and 7 IT tools were identified. Finally, the conclusions emphasized the importance of adapting logistics KPIs to business priorities and the relevance of Big Data in their definition to improve both decision-making and customer satisfaction.

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Published

2024-06-30

Issue

Section

Review

How to Cite

The Influence of Big Data on the Definition of Key Logistic Performance Indicators for Customer Satisfaction: A Systematic Literature Review. (2024). Revista Peruana De Computación Y Sistemas, 6(1), 91-99. https://doi.org/10.15381/rpcs.v6i1.28533