Jurnal Ekonomi Manajemen Sistem Informasi (JEMSI) · e-ISSN: 2686-5238 · p-ISSN: 2686-4916

Strategic Analysis of the Five Pillars in Optimizing Customer Experience in The Express Logistics Industry (Case Study of Tiki Indonesia)

Trie Maulana Apriyanto Juliater Simarmata Lira Agusinta Yulianti Keke Mustikasari Mustikasari
Vol. 7 No. 5 (2026) 01 June 2026 Pages 4578-4589

Abstract

This study aims to analyze the influence of the Strategic 5 Pillars (Customer, Network, Process, Technology, and People) on Customer Experience in the express logistics industry, with a case study on the courier service company TIKI Indonesia. The background of this research stems from the increasing demand for courier services driven by the growth of e-commerce, alongside persistent customer complaints that indicate the need to evaluate user experiences. The research adopts a quantitative approach, utilizing data collected through questionnaires. The population includes all users of TIKI's courier services in 2022–2023, totaling 288,366 users. A purposive sampling technique was applied, and using the Slovin formula, a total of 400 respondents were selected. The data were analyzed using multiple linear regression to examine the influence of each independent variable on customer experience, complemented by Importance–Performance Analysis (IPA) and the Customer Satisfaction Index (CSI). The findings reveal that the variables Customer, Network, Technology, and People have a positive and significant effect on customer experience, while Process shows no significant influence. Simultaneously, all five variables significantly affect customer experience. The CSI score of 78.49 indicates that customers are generally satisfied with TIKI’s services. Additionally, the IPA results identify several service attributes that require priority improvements. This study provides strategic implications for TIKI’s management in enhancing service quality through the continuous optimization of the five key pillars examined.

Keywords

Customer Experience Strategic 5 Pillars CSI IPA Multiple Linear Regression