Truck Driver Turnover: A Logistic Regression Approach

Introduction

Currently driver turnover exceeds 70 percent and is expected to rise in the near future (McNally, 2017). One of the most important and complex problems facing both motor carriers and supply chains is the high rate of driver turnover (Costello and Suarez, 2015; Patton, 2011). The Advanced Center for Transportation Technologies at Clark College (2006) estimated that driver shortages and turnover costs the U.S. economy between $1.8 and $3 billion annually. Min and Lambert (2002) put these numbers in perspective and estimated that it costs between $3000 to $12,000 to replace a driver depending on the amount of time and money that the company must invest in the hiring, orientation, and training. During the course of this study it was found that this figure now ranges from $7,000 to $10,000 to hire an experienced driver with no orientation or training costs to between $20,000 and $27,000 if these services are provided. This updated finding is generally supported by an industry report which placed the cost of replacing a driver at $25,000 (Refrigerated Transporter, 2007). High driver turnover rates have been found to increase carriers’ operating costs, reduce driver productivity and result in reductions in service quality and highway safety (Corsi & Fanara, 1988; Curtis & Wright, 2001; Suzuki, 2007; Faulkiner, 2016). High driver turnover rates have also been found to impact shippers when carriers are unable to meet pick-up and delivery schedules due to a lack of drivers or when frustrated or overworked drivers simply walk away and leave their trucks sitting on the side of the road (Keller & Ozment, 1999a; LeMay et al., 2009).

Consequently, driver turnover and retention has been studied from many perspectives. These perspectives include but are not limited to driver recruitment and retention practices (LeMay et al., 1993; Gupta, et al., 1996; Stephenson & Fox, 1996; Keller & Ozment, 1999b; Keller, 2002; Min & Lambert, 2002; Suzuki, et al., 2009), driver training (Mejza & Corsi, 1999; Mejza et al., 2003), work conditions (Rodriguez & Griffen, 1990; LeMay et al. 1993; Richard et al., 1995; Stephenson & Fox, 1996; Keller & Ozment, 1999a; Keller, 2002; Min & Lambert, 2002; Suzuki et al. 2009), equipment (Garver et al., 2008), compensation (Rodriguez & Griffen, 1990; LeMay et al., 1993; Richard et al., 1995; Gupta et al., 1996; Shaw et al., 1998; Stephenson & Fox, 1996; Keller & Ozment, 1999b; Keller, 2002; Min & Lambert, 2002; Suzuki et al., 2009), demographic characteristics (Beilock & Capelle, 1990; Shaw et al. 1998; Min & Lambert, 2002; Suzuki et al. 2009), employment stability and past safety behavior (Cantor et al., 2010; Faulkiner, 2016), driver needs (Williams, et al., 2011), the role of dispatchers or driver managers (Richard et al., 1995; Gupta et al., 1996; Stephenson & Fox, 1996; Keller & Ozment, 1999ab; Keller, 2002; Suzuki et al. 2009), dispatching procedures (Taylor & Whicker, 2010), drivers’ relationship with top management (LeMay & Taylor, 1988), justice in the workplace (Cantor et al., 2011), and driver satisfaction and frustration (Keller & Ozment, 1999b; Johnson et al., 2010; LeMay et al., 2009; Schulz et al., 2014). Other research in this area has looked at predicting which drivers are most at risk of turning over (Richard et al., 1995; Min & Emam, 2003; Garver et al., 2008; Suzuki et al., 2009; Lemay et al., 2013). Readers may also gain useful insights from Crum & Morrow (2002).