In addition to the rareness of theoretical and empirical research, which extends to every aspect of the production ramp-up literature, the increasing importance of the ramp-up phase – due to the continuously decreasing product lifecycle in almost all industrial sectors –magnifies the need for more research efforts in this field. Based on a comprehensive literature review, no attempts to investigate the role of lean and/or agile logistics during the ramp-up stage were found. Utilizing the survey method, this research empirically explores the effects of lean and agile logistics on production performance during the ramp-up phase in terms of quantity, quality, and cost. A special purpose questionnaire was developed to collect primary data based on a literature review in the fields of production ramp-up, lean logistics, lean production, agile logistics, agile production, performance measurement, and product success. The measurement model was evaluated for validity and reliability and tested for temporal consistency and the existence of common method variance; the collected data were tested for measurement and non-response biases; and the results were evaluated for their statistical power and statistical conclusion error. Out of 63 questionnaires collected from industrial organizations operating in 7 countries and in different sectors, 56 responses were used in the statistical analyses. A two-step methodological approach was utilized in the data analysis. In the first step, the data collected on the research variables were analysed following a theory confirmation procedure to examine the validity of a hypothesized positive effect of lean and agile logistics on ramp-up performance. In addition, the effect of ramp-up performance on new products’ success, the moderating effect of some respondent, organizational, and product-related variables, and the mediating effect of outbound logistics were investigated. The partial least squares method of structural equation modelling (PLS-SEM) was employed during the confirmatory analysis. Different scenarios were evaluated to test the main and subsidiary hypotheses proposed, based on the use of formative and reflective measures and first- or higher-order variable formats. The results of the confirmatory data analysis supported the hypothesized positive effect of lean and agile logistics on production performance during the ramp-up phase. In the second methodological step, exploratory analyses were conducted to explore further patterns in the data collected. Correlation matrices indicated a greater effect of agility on quantity performance and a greater effect of leanness on cost performance. Such trends are generally accepted and supported by the theoretical literature and by practitioners. However, the agreed-upon priorities of time reduction during the ramp-up phase and cost reduction during the steady-state and ramp-down phases motivated the proposition of a mixed model that uses higher levels of agility throughout the ramp-up phase and higher leanness levels thereafter. The proposed mixed system was supposed to outperform the pure lean, pure agile, and leagile strategies. Among the methods proposed to apply such a mixed production system, the development of a specialized agile ramp-up facility was introduced. It was suggested that all products undergoing a ramp-up phase should be produced with an agile system, in a specialized ramp-up facility, and then moved to a lean facility during the steady-state and ramp-down production phases. To examine the feasibility of the proposed system and the magnitude of investment that might be accepted to gain the expected enhancement, the total lifecycle profitability of each system – lean, agile, leagile, and mixed – was calculated and compared to provide insights into the advantages of the mixed system and the conditions that increase or decrease the appeal of investing in such a strategy. It was concluded that the adoption of the proposed system and the asset investment magnitude should be evaluated considering different possible combinations of the product’s type, price, cost, contribution, and lifecycle length, among other variables. The proposed system has been proven to be more attractive to adopt as the proportion of the ramp-up time to the total lifecycle increases, as the product’s price drops faster, as the peak sales are reached earlier, or as the number of ramp-ups increases.