Purpose The purpose of this paper is to identify effective factors, their impact, and find estimation models of the most well-known productivity measurement, hours-per-vehicle (HPV), in the automotive industry in North American manufacturing plants. Design/methodology/approach Data used in this study were from North American plants that participated in the Harbour’s survey from 2002 to 2006. Data are synthesized using a uniform methodology from information supplied by the plants and supplemented with plant visits by Harbour Consulting auditors. Overall, there are 355 manufacturing plants in the statistical sample from ten different automakers’ brands including DCX, Ford, GM, Honda, Cami, Nummi, Auto Alliance, Mitsubishi, Nissan, and Toyota. The multiple linear regression was used to analyze the data and derive the HPV regression equations. Findings HPV is a widely recognized production performance indicator that is used by a significant percentage of worldwide automakers. During the study period, the HPV was reduced 54.75 minutes on average in each year. Annual production volume, platform sharing (PS), and flexible manufacturing (FM) factors improve HPV. However, vehicle variety, salaried employees’ percentage of the workforce, available annual working days, and launching a new model penalize HPV. Launching a new model and adding a new variety in body styles or chassis configurations raise the HPV about 2.189 and 0.642 hours, respectively, depending on the car class; however, manufacturing plants compensate for this issue by using PS and FM strategies. Research limitations/implications The plants which stopped production of a specific product also are included in this study and were treated similar to the regular plants. The medium duty segment was excluded from the data set due to the fact that the number of observations available was too low. The study can be repeated with additional new factors such as the level of plants’ automation and lean manufacturing either for North American or European companies. Originality/value The research investigates current strategies that help automakers to enhance their production performance and reduce their productivity gap. HPV regression equations that are provided in this research may be used effectively to help car makers to set guidelines to improve their productivity with respect to internal and external constraints, strength, weakness, opportunities, and threats.
