Setting key performance targets for Croatian shipyards

Abstract

The aim of this paper is to use the Data Envelopment Analysis (DEA) method to measure and analyze different relative efficiencies of five Croatian shipyards. The indicators are chosen to capture different aspects of shipbuilding performance in Croatia. Window analysis is used to determine shipyard efficiency and observe possible changes in shipyard efficiency over time. This leads to identifying a subset of efficient best practice shipyards, whereas for others the magnitude of their inefficiency is ascertained along with the specified efficient input and output targets. The importance of window analysis is that its results serve as an early warning system to all inefficient shipyards. In identifying the sources of inefficiencies and formulating proposals for improving shipyard performance observed over a six-year period (2007-2012), the results presented in this paper can be used to enhance and alter decisions.

Manufacturing Process Performance Measurement Model Using Categorical DEA Approach – a Case of Dry-Docking

“…An analysis using the DEA studying twelve repair shipyards in China was published by (Yang & Wang, 2017). The Croatian shipbuilding industry analysis using DEA methodology, assessing the shipyard's performance over time, identifying sources of inefficiency as well as propositions for increasing performance and altering decisions, was proposed by (Rabar, 2015). The United States East Coast repair shipyards capability estimation using DEA was made by (Mayo et al, 2020) to find the optimal repair solution for the ferry vessel fleet.…”

An empirical analysis of airport efficiency: the Croatian case

“…Accordingly, DEA models are molded to reflect input or output-orientation. [13] Since an improvement in airport performance requires a reduction of all three inputs, as well as an augmentation of output, both model orientations are suitable. Nevertheless, input-orientation is selected as more appropriate for the purpose of this study, since the airports have more control over the inputs than over the output, i.e.…”

“…Such an approach may involve simultaneous evaluation of different types of productivity that can be indirectly achieved by a performance measurement technique and which includes all parameters used to calculate these productivities and, at the same time, provides a comparison of efficiency levels among airports over a period of time. Therefore, the purpose of this paper is to propose Data Envelopment Analysis (DEA) as a suitable efficiency measurement method that satisfies the aforementioned requirements, and to present the results of analyzed efficiencies of airports in Croatia [13]. DEA is a linear programming-based non-parametric technique used for evaluating the relative efficiency of homogenous operating entities or decision-making units (DMUs) on the basis of empirical data on their multiple inputs and outputs.…”

“…DEA is a linear programming-based non-parametric technique used for evaluating the relative efficiency of homogenous operating entities or decision-making units (DMUs) on the basis of empirical data on their multiple inputs and outputs. It leads to an efficient frontier determined by the existing DMUs which are identified as best practice units (benchmarks) and given a rating of 1, whereas the degree of inefficiency of other entities is calculated on the basis of their distances from the efficient frontier and attributed to input excesses and output shortfalls [13]. The first literature survey focusing on DEA applications is the study of Liu et al [9] that covers DEA papers indexed in the Web of Science database over the period of 32 years (from 1978 through August 2010).…”