PBESProceedings of Business and Economic Studies2209-26412209-265XBio-Byword Scientific Publishing Pty. Ltd.10.26689/pbes.v9i2.14132ArticleDigital Reconfiguration of Matching Practices in Platform-Based Logistics Enterprises: A Routine Perspectivehttps://artdesignp.com/journal/PBES/9/2/10.26689/pbes.v9i2.14132JingTaining,KongWenxuan2026922026-03-11In low-frequency, high-risk business-to-business (B2B) platform logistics, the matching of transportation resources with customer demand relies heavily on the experiential judgment of operational personnel. While such reliance ensures flexibility, it also poses challenges, including difficulties in information integration, high cross-departmental coordination costs, and limited traceability of decision-making processes. Existing studies have primarily examined the formation mechanisms of organizational routines or the effects of digitalization on organizational action patterns. However, there is a lack of systematic analysis of how digital systems gradually embed into experience-dependent B2B logistics matching, reconfiguring specific workflows and collaboration practices. Adopting an organizational routines perspective, this study conducts a single-case study of a maritime petrochemical logistics platform. It examines how the progressive embedding of a digital system reconfigures matching practices by integrating dispersed information, generating system-generated plans, and establishing a shared informational basis. This process reshapes the sequence of actions, the locus of judgment, and collaboration modes, stabilizing experiential judgment while enhancing traceability and transmissibility. The findings provide an empirical account of the intervention path of digital technology in experience-dependent platform logistics, offering insights for digital transformation in comparable operational contexts.

Li J, Zhou T, Xu L, et al., 2020, Matching Optimization Decision of City LTL Carpool based on Time Windows on the Freight O2O Platform. Systems Engineering Theory and Practice, 40(4): 978–88.

Papagiannidis E, Mikalef P, Conboy K, 2025, Responsible Artificial Intelligence Governance: A Review and Research Framework. Journal of Strategic Information Systems, 34(2).

Yi S, Knudsen T, Becker M, 2026, Inertia in Routines: A Hidden Source of Organizational Variation. Organization Science, 27(3): 782–800.

Heracleous L, Bartunek J, 2020, Organization Change Failure, Deep Structures and Temporality: Appreciating Wonderland. Human Relations, 74(2): 208–233.

Schaffer N, Hermes S, Weking J, et al., 2022, Continuous Business Model Innovation and Dynamic Capabilities: The Case of Cewe. International Journal of Innovation Management, 26(6): 1–43.

Liu Y, Xie K, Deng H, 2020, Data-Driven R&D Transformation of New Product: A Case Study from the Perspective of Adaptive Change in Organizational Practices. Journal of Management World, 36(3): 163–182.

Jahanmir S, Cavadas J, 2018, Factors Affecting Late Adoption of Digital Innovations. Journal of Business Research, 88(7): 337–343.

Simsek Z, Vaara E, Paruchuri S, et al., 2019, New Ways of Seeing Big Data. Academy of Management Journal, 62(4): 971–978.

Salvatto C, Rerup C, 2018, Routine Regulation: Balancing Conflicting Goals in Organizational Routines. Administrative Science Quarterly, 63(1): 170–209.

Visnjic I, Jovanovic M, Raisch S, 2022, Managing the Transition to a Dual Business Model: Tradeoff, Paradox, and Routinized Practices. Organization Science, 33(5): 1964–1989.

Song J, Chen J, Sun Y, 2024, Impact of Platform Empowerment on Platform Routines Formation. Management Review, 36(11): 227–234.