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Efficiency analysis for digitalised working systems of truck drivers

Dominic Loske and Matthias Klumpp

A chapter in The Road to a Digitalized Supply Chain Management: Smart and Digital Solutions for Supply Chain Management, 2018, pp 99-119 from Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management

Abstract: The current research discussion postulates a digital transformation, characterized by new and in its extent unknown development and application potentials. At this stage scientists and practitioners know little about how these changes will transform specific work tasks. And the question is still even more opaque, whether there are real gains to be won by digitalization steps. Therefore, this paper develops an efficiency analysis to evaluate the effect of changing levels of digitalization within the working systems of professional truck drivers. Data Envelopment Analysis (DEA) is used in order to quantify truck driver performance in the logistics processes of a German food retailer. As inputs we use loading time and cost. Outputs are load factor of units, invoice charged to shops and value of damage. The findings indicate that a change in the level of digitalization entails a loss of efficiency in the first instance which can partly be compensated later. By using correlation analysis we prove a low statistical linear relationship of age and efficiency plus a strong statistical linear correlation of employer size and efficiency as well as period of employment and efficiency, always regarding the changing levels of digitalization in the working system of professional truck drivers. We derived the importance of employee retention programs for HR management along with a positive working environment provided for truck drivers to reduce fluctuation effects. Furthermore, we advise to design software for truck drivers as commonplace as possible and in the style of widespread smart phone software user interfaces.

Keywords: Digitalisation; Data Envelopment Analysis; Efficiency analysis; Truck driver (search for similar items in EconPapers)
Date: 2018
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