A decision model to prioritise logistics performance indicators

Abstract

Performance measurement is an important concern that has recently attracted much attention in the logistics area from both practitioners and academics. The performance measurement of logistics companies is based upon diverse performance indicators. However, to date, limited attention has been paid to the performance measurement of logistics companies and, also, performance measurement processes have become more complex for logistics companies due to the existence of numerous performance indicators. In this regard, the way in which decision makers in logistics companies deal with some vaguenesses, such as deciding on the most important indicators holistically and determining interrelationships between performance indicators, has remained an issue that needs to be resolved. This study, therefore, aims to offer a comprehensive decision model for identifying the key logistics performance indicators and determining the interrelationships among these indicators from logisticians’ perspective. In line with this purpose, the research first presents a stakeholder-based Balanced Scorecard (BSC) model which provides a balanced view by including financial and non-financial performance indicators and a comprehensive approach as a response to the major shortcoming of the generic BSC regarding the negligence of various stakeholders. Then, a large number of performance indicators used in logistics are systematically examined under the proposed model, and the key indicators are selected through an online survey conducted in the Turkish logistics industry. Subsequently, since the performance measurement indicators are not independent of each other, it is critical to understand the causal relationships among different indicators. In such cases, group decision making techniques are capable of modelling such complexities. After a systematic comparison of these techniques, a realistic and easy-to-follow multi-criteria decision making technique, the Analytic Network Process (ANP), is revealed as a suitably powerful method to determine the interrelationships among the indicators. Additionally, a case study approach based on the data obtained from three logistics companies is used to illustrate both the applicability of the model and the practicality of the ANP application. Furthermore, the sensitivity of the results about the case companies is also analysed with several relevant ‘what-if’ scenarios. Thus, real-life practices of three case companies are investigated with the proposed approach. Consequently, this research proposes the BSC-ANP integration which provides a novel way and in-depth understanding to evaluate logistics performance indicators for the competitiveness of logistics companies. Thus, in order to address the aforementioned vaguenesses, the proposed model in this study identifies key performance indicators with the consideration of various stakeholders in the logistics industry to decide on the most important indicators, and evaluates the interrelationships among the indicators by using the ANP. The results of the study show that the educated employee (15.61%) is the most important indicator for the competitiveness of logistics companies and four prominent indicators (educated employee, managerial skills, cost, and profitability) need to be primarily considered by logistics companies. In this way, with this integration, not only the performance indicators in logistics, but also different stakeholders of logistics companies are assessed by the ANP method. This means that the results of this research are not only useful for helping logistics companies to decide which indicators should be focused on to become more competitive, but also can be used as a reference model by different stakeholders in their decision-making processes in order to select the best logistics provider. Keywords: Performance measurement; logistics performance indicators; balanced scorecard (BSC); analytic network process (ANP); multi-criteria decision making (MCDM); stakeholders