Monitoring delivery time using a multiaspect distribution-free method

Marco Marozzi (), Filippo Maganza and Amitava Mukherjee
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Marco Marozzi: University of Ferrara
Filippo Maganza: Ca’ Foscari University of Venice
Amitava Mukherjee: Xavier School of Management Jamshedpur

Quality & Quantity: International Journal of Methodology, 2025, vol. 59, issue 1, No 5, 79-110

Abstract: Abstract In the field of food service logistics, monitoring pizza delivery time is an important issue. The importance of timely pizza deliveries mirrors broader societal expectations of instant gratification and time efficiency. In this paper, we propose a new approach for designing distribution-free monitoring methods which is based on the nonparametric combination of dependent tests framework (NPC), borrowed from hypothesis testing and permutation testing theory. We analyze the application of NPC to combine several tests in order to address different aspects of the problem or viewpoints of the data. Studying the corresponding multi-aspect NPC process monitoring schemes, we discovered that combining only linear rank tests leads to a distribution-free NPC methods, whereas combining at least one non linear rank test may lead to a non distribution-free NPC method. One of the most interesting results has been obtained with the NPC Wilcoxon–Van der Waerden process monitoring method. This method takes full advantage of the flexibility of the NPC framework performing well under a wide variety of process distributions. The methods are illustrated by analyzing a real data set.

Keywords: Customer satisfaction; Statistical process control; Nonparametric tests; Permutation tests (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11135-024-01954-2

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