Determinant Factors of Logistics Firm Performance Mediated by Optilog Adoption Using a Mixed Method with an Explanatory Sequential Analysis

Authors

  • Melianie Bina Nusantara University
  • Rindang Widuri Bina Nusantara University
  • Indra Gamayanto University of Dian Nuswantoro
  • Arta Moro Sundjaja Bina Nusantara University

DOI:

https://doi.org/10.21512/commit.v18i2.11090

Keywords:

Logistics Firm Performance, Optilog Adoption, Mixed Method, Explanatory Sequential Analysis

Abstract

Recently, trucking logistics service providers are focusing on adopting technology and Information Technology (IT) capability to improve performance. Hence, it is essential to investigate how the IT capability of the firm can enhance logistics performance and impact technology adoption on performance. Therefore, the research examines the determinant factors of logistics firm performance mediated by Optilog adoption. The research design is a mixed method with an explanatory sequential design using quantitative and qualitative data analysis. Quantitative data analysis uses Structural Equation Modeling (SEM), while qualitative analysis adopts in-depth interviews. The analysis population includes 41 Optilog users in the logistics firm in East Jakarta, with the experts adopting a census sampling method. For qualitative phase, the researchers also recruit four respondents holding supervisory positions or higher using Optilog for daily operations. The results show that logistics firm performance is influenced by service excellence and Optilog adoption. Additionally, perceived risk, traceability, and IT capability positively affect Optilog adoption, which mediates the effects on logistics firm performance. The results confirm the rejection of the hypothesis that Optilog adoption mediates IT capability on logistics firm performance. The thematic analysis further concludes that the system, implemented in March 2022, does not impact logistics firm performance significantly, according to the respondents. Consequently, IT departments depend on responsiveness to address users’ needs and issues since when the vendor develops the system, it faces significant constraints due to the development and maintenance costs.

Dimensions

Plum Analytics

Author Biographies

Melianie, Bina Nusantara University

Accounting Department, School of Accounting – Master of Accounting

Rindang Widuri, Bina Nusantara University

Accounting Department, School of Accounting – Master of Accounting

Indra Gamayanto, University of Dian Nuswantoro

Department of Technology Management, Faculty of Computer Science

Arta Moro Sundjaja, Bina Nusantara University

Management Department, BINUS Business School Master Program

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Published

2024-08-27
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