Benchmarking of Norwegian Shipbuilding Projects - A Conceptual Platform and an Initial Benchmarking Study
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This thesis was motivated by a challenging market situation for Norwegian shipbuilders, and an expected need to improve performance if Norwegian shipbuilding companies are to remain competitive in the future. With this motivation, the research work in this thesis was an investigation into how benchmarking can be utilized for achieving improved performance in the context of shipbuilding. Early on, improving performance through benchmarking was found to require objective performance measurement, so that the performance of different units can be compared. It was also found to require an investigation of why certain units perform better than others, to identify potential performance-enhancing actions. In this thesis, the units addressed in the last two sentences were chosen to be Norwegian shipbuilding projects. Based on this, three objectives for the thesis were defined: (1) identify how the performance of Norwegian shipbuilding projects can be measured and compared, and identify which factors that are likely to have an effect on this performance, (2) develop a conceptual model that represents a conceptual platform for benchmarking studies involving Norwegian shipbuilding projects, and (3) utilize the conceptual model in an empirical analysis.Additionally, three research questions (RQs) were formulated:RQ 1: Which performance objectives and measures are likely to be useful in a benchmarking process, for measuring and comparing the performance of Norwegian shipbuilding projects?RQ 2: Which performance-affecting factors are likely to be useful in a benchmarking process, for explaining differences in measured performance for Norwegian shipbuilding projects?RQ 3: How and how much does each of the identified performance-affecting factors influence the performance of Norwegian shipbuilding projects performed by Ulstein?The research methodology used for answering these questions consisted of a literature review, model development and quantitative statistical analysis of empirical data. First, literature related to benchmarking, performance measurement, determinants of performance and shipbuilding was reviewed. Then, a literature model for benchmarking was developed based on literature. Further, a conceptual benchmarking model was developed based on the literature model and discussions with practitioners. Lastly, an empirical analysis model was developed based on the conceptual model, the nature of the case study and available data. Based on the empirical analysis model, a quantitative analysis of empirical data related to a case company, Ulstein, was performed using multiple regression analysis. The literature model consisted of thirteen performance-affecting factors (regional policies, regional industry structure, workforce, market situation, series production, ship size and complexity, offshoring strategy, technology level, vertical integration, company size, market orientation, flexibility and capacity) and eight variables representing performance (productivity, lead time, quality, delivery precision, flexibility, profitability, cost and competitiveness). The conceptual model, on the other hand, consisted of fourteen performance-affecting factors (regional policies, market situation, series production, ship size and complexity, technology level of main yard, technology level of hull yard, vertical integration, company size, market orientation, flexibility, capacity of main yard, capacity of hull yard and shipyard capabilities) and seven variables representing performance (productivity, lead time, quality, delivery precision, profitability, cost and competitiveness). The multiple regression analysis was completed on a limited version of the conceptual model, consisting of seven performance-affecting factors (regional policies, market situation, series production, ship size and complexity, vertical integration, flexibility and capacity of main yard) and two variables representing performance (productivity and profitability).The analysis results suggested that a greater intensity of regional policies, market situation, series production, ship size and complexity, and flexibility had a positive effect on at least one of the two performance variables, productivity or profitability. Additionally, the results suggested that greater intensity of vertical integration and capacity had a negative effect on at least one of the two performance variables.