Abstract: |
Third-party logistics (3PL) service providers play an instrumental role in the performance of the global Supply chain. Several studies focus on operational as well as financial performance assessment of 3PL service providers with the help of a stand-alone reference-point-based multi criteria decision making (MCDM) method and the influence of the service quality on the 3PL service providers’ performance. In this context, the absence of distinct as well as a holistic performance evaluation of the 3PL service providers highlights the interesting research opportunity. Also, the application of a single MCDM technique often exhibits bias towards specific factors. For this reason, the design of an integrated MCDM framework using multiple MCDM techniques is required to ensure robustness. Additionally, ratio analysis-based MCDM methods such as complex proportional assessment (COPRA) and multi-objective optimisation on the basis of ratio analysis (MOORA) have been ignored. Further, the evaluation of the 3PL service providers’ service quality captured through the customers’ reviews and the effect of this service quality on their financial and operational performance has not been paid enough attention. In this context, the application of text mining methods such as topic modelling, Latent Dirichlet Allocation (LDA), and sentiment analysis can yield practical insights. It acts as a motivation for us to develop an integrated CRITIC-MOORA-COPRA-Text Mining-based methodology to assess the performance and investigate the effect of service quality on the 3PL service providers’ performance. The proposed methodology has been applied to the real-life dataset comprising 21 leading North-American 3PL service providers to exhibit the real-life implementation. The findings highlight the positive relationship between the service quality and performance of 3PL service providers. |