BENCHMARKING THE OPERATIONAL EFFICIENCY OF MAJOR U.S. TRUCKING FIRMS USING DATA ENVELOPMENT ANALYSIS.

摘要: INTRODUCTION The trucking industry in the United States has historically operated on profit margins as low 3 to 4 cents every dollar of sales after taxes, compared 7 9% average margin experienced by heavy manufacturing (Dun and Bradstreet, 1999; Lambert Min, 2000). Recently, declined further, from 3.08% 1994 2.60% 1999 (American Trucking Associations Economics Statistic Group, 2001). With tight increasing competition, a key firm's survival is its ability keep operations "lean." Sustaining lean operations, however, not easy given mounting cost pressures rising fuel costs, insurance, labor. For example, national price diesel spiked $1,491 per gallon 2000 $1,044 1998. In addition, for-hire carriers paid 8.4% more federal highway-user taxes than 1998 Statistics Those firms that could handle steep increases outpacing revenue growth failed survive end. alone, 3,670 went out business. This alarming statistic represents an increase 205.8% business failures previous year One way improving operational efficiency learn best practice can be identified setting reliable financial performance standard. Examples such standard are audit, norm, benchmark. Since firm needs measure relative competitors constantly strengthen market position, benchmarking seems most effective then measuring firm. general, continuous quality improvement process which organization assess internal strengths weaknesses, evaluate comparative advantages leading competitors, identify practices leaders, incorporate these findings into strategic action plan geared gain position superiority (Min Galle, 1996). main goals to: * Identify measures for each function operation; Measure one's own levels well those competitors; Compare areas disadvantages; Implement programs close gap between (Furey 1987, p.30). benchmark, this paper will prior periods their competitors. measured input/output ratios reflect true overall productivity better traditional tend focus myopic aspects performance. As comparatively assessing with multiple inputs outputs, research uses data envelopment analysis (DEA), was successfully explored banks (e.g., Thanassoulis, 1999), hospitals (Valdmanis, 1992), nursing homes (Kleinsorge Karney, purchasing departments (Murphy et al., 1996), cellular (Talluri al, 1997), travel demand (Nozick 1998), information technology investments (Shafer Byrd, 2000), customer service performances less-than-truckload (LTL) motor (Poli Scheraga, 2000) international ports (Tongzon, further details other DEA applications, interested readers should refer Seiford (1990). referred linear programming (non-parametric) technique converts incommensurable outputs decision-making unit (DMU) scalar efficiency, competing DMU's. …