Based on the O*NET job database, this research performs a typological analysis of US transportation and logistics jobs using two variables--the originality requirement of workers and the decision-making freedom by work design. Based on cluster analysis, we find that Express Lane jobs command the highest average pay due to the greatest worker originality required, have the most decision-making freedom allowed and are least vulnerable to automation. In contrast, Gridlock jobs are paid least on average due to the lowest worker originality, have the least decision-making freedom, and are most vulnerable to automation. In the middle range fall Slow Lane and Bumpy Road jobs, due to less decision-making freedom and lower worker originality required, respectively. Policy and managerial implications concerning training and work redesign are discussed in the context of technological advancements and automation.
Transportation and logistics, competency model, automation, cluster analysis, human resources, employment
While transportation and logistics have played vital roles in driving service quality and market growth of modern businesses, the supply of a well-trained and skilled workforce has been a bottleneck for industry sectors and organizations within these sectors. According to the US Bureau of Labor Statistics (BLS), approximately 5.3 million people are currently employed in the US transportation and warehousing sector, a 17 percent increase over the workforce 10 years ago and a 28 percent increase over the workforce 20 years prior. It was reported that in June 2018 only 230,000 of 285,000 job openings in the US transportation, warehousing, and utility sector were filled (US Bureau of Labor Statistics 2018). Meanwhile, there were a total of 207,000 job turnovers due to voluntary resignations, layoffs, and discharges in this sector. In terms of transportation and logistics occupations, as of May 2017, over 12.3 million people are employed in logistics-related functions across all US private and public sectors. Among them, nearly 1 million are employed in the US manufacturing sector, 2.5 million in the transportation sector, and approximately 600,000 in the warehousing and storage sector (US Bureau of Labor Statistics 2017a).
Due to technological advances and structural changes, the US transportation and logistics industry faces a dilemma: on the one hand, an increasing number of logistics jobs are disappearing or being replaced by automation, making it more difficult to attract new workers; on the other hand, many new job openings remain unfilled without qualified logistics talent. As robots and artificial intelligence are poised to displace jobs in various industries, transportation and logistics professionals are deeply concerned that the transportation and logistics industry may be vulnerable to job losses (PWC 2017). Due to automation of logistics functions, we see drone deliveries of packages and robots on the warehouse floor picking orders with more accuracy than human pickers. Meanwhile, artificial intelligence and data processing technologies are gathering and processing information more efficiently than can humans (Mabe 2017).
The good news within the logistics industry jobs picture, however, is that automation does not mean the end of human work and may have its own limits in terms...