The role of relationship commitment in managing logistics outsourcing in the digital economy

Abstract

Purpose

Digitalization brings complexity and challenges to the relationship governance between logistics outsourcers and their providers. Drawn on resource dependence theory (RDT) and resource-based view (RBV), this study aims to examine the role of relationship commitment in simultaneously managing dependence and improving operational performance in logistics outsourcing in the digital economy, as well as the contingent factors (i.e. communication, relationship length, and company size) that affect the effectiveness of relationship commitment.

Design/methodology/approach

Based on data collected from 130 third-party logistics (3PL) users in China, our model was tested with the partial least squares (PLS) approach.

Findings

First, relationship commitment is necessary for 3PL users to manage dependence on 3PL providers and improve operational performance in the digital economy. Second, communication helps 3PL users to develop higher relationship commitment but weakens the motivating effect of dependence on relationship commitment. Third, a long relationship history develops inertia to diminish the effectiveness of dependence on driving relationship commitment while it boosts the impact of relationship commitment on operational performance. Last, company size is an important signal to amplify the effectiveness of relationship commitment for operational performance enhancement.

Originality/value

This study contributes to the logistics outsourcing literature by integrating RDT and RBV to explain the twofold roles of relationship commitment, simultaneously tackling dependence and enhancing operational performance in the digital economy. Additionally, it expands the understanding of the boundary conditions (e.g. communication, relationship length, and company size) on these twofold roles.

Citation

Shi, R., Yang, B., Chu, Z. and Lai, F. (2024), "The role of relationship commitment in managing logistics outsourcing in the digital economy", Industrial Management & Data Systems, Vol. 124 No. 7, pp. 2440-2466. https://doi.org/10.1108/IMDS-07-2023-0497