Owner operators: employing a segmentation approach to improve retention

Abstract

Purpose – Owner operators are an important group of truck drivers, yet have been the subject of very little academic research. Specifically, no research has explored retention issues among owner operators. Thus, this paper aims to employ a segmentation approach to owner operator retention, examining important independent variables that include: pay and compensation, top management support, time at home, and safety.Design/methodology/approach – Data were collected from a large truckload (TL) carrier. The drivers surveyed were irregular route long‐haul drivers. A total of 239 responses were obtained, for a response rate of 74.6 per cent. Latent class regression (LCR), a technique new to logistics and supply chain management (SCM) research, was utilized for data analysis.Findings – The results show there are four different need‐based driver segments, which means that specific driver retention programs must be developed for each segment.Research limitations/implications – The major limitation of this paper is...