Delivery truck drivers’ professional commitment profiles: customer facing matters

Claye-Puaux, Sophie; Jacquemier-Paquin, Laure; Jeanpert-Henry, Sophie

doi:10.1080/16258312.2019.1586269

Cited by 1 publication

(3 citation statements)

References 35 publications

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“…Research conducted by Clye-Puaux et al (2019) shows that truck drivers are reluctant to actively maintain customer relationships, and the more complex the customer conditions, the greater the negative impact [2,11]. This is consistent with the model results, when the distance is farther, the probability of the on-time arrival of the logistics is lower.…”

Section: Discussionsupporting

confidence: 65%

“…Just like Express Mail Service, through the introduction of advanced management technology and modern equipment (mainly reflected in logistics equipment), it has effectively improved the efficiency of logistics services, improved management capabilities and query capabilities. Greatly improved service quality and customer satisfaction [2,15].…”

Section: Discussionmentioning

confidence: 99%

“…Some researchers have studied the relationship between truck drivers' services and user purchase behavior, such as Claye-Puaux et al (2019) discussed the relationship between truck drivers and work: 34% of truck drivers do not like their profession and do not want to maintain customer relationships [2]. They refuse to build better customer relationships and only keep their jobs at a minimum.…”

Section: Related Researchmentioning

confidence: 99%

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Factors Affecting the Punctuality of Logistics Services Using Binary Logistic Regression

Li¹

2022

BCPBM

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The Indian logistics industry is in a period of rapid development. The purpose of this study is to analyze the factors affecting the punctuality of trucks for logistics distribution services in India based on data analysis. The data comes from 6880 pieces of data from the VTS data platform. A binary regression model was established for data analysis, and the model was tested to ensure statistical significance. Binary logistic regression was used to examine truck types, geographic locations, commodity types, order types, and suppliers for logistics services to examine significant differences between on-time and late. Binary logistic regression concluded that the shorter the distance, the signing of the perfect contract, and the selection of a specific type of vehicle, the better development of the logistics level is easier to be on time. This study provides suggestions for improving management strategies, which can be used as a reference for the development of logistics companies.

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Section: Discussionsupporting

confidence: 65%

Section: Discussionmentioning

confidence: 99%

Section: Related Researchmentioning

confidence: 99%

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