Coopetition Analysis Between JD and Tmall in China’s E-Commerce Landscape: A Hybrid Thematic-Latent Dirichlet Allocation Approach

JD and Tmall ended restricted models of their ecosystems in 2024 with a new collaborative approach that opened previously isolated spaces or referred as ‘walled gardens.’ This study explores the key drivers of this shift and how these major e-commerce platforms coordinate logistics and payment systems amidst intense market competition. We adopted a hybrid approach to collect data through word cloud analysis, followed by thematic analysis with verification by Latent Dirichlet Allocation (LDA) modeling, which minimizes coder bias. Our study results show that, while regulatory pressure, including antitrust policies, played a role, several non-regulatory factors were equally or more influential. These include shifting consumer expectations for faster delivery, growing demand for secure and flexible payment options, and competitive pressure from pricing strategies and brand positioning. Through strategic competition initiatives, JD and Tmall achieved balanced collaboration and competition to enhance market efficiency and operational resilience. Firms successfully navigated competitive risks toward maximizing coopetition benefits because of their strong absorptive capacity and agile supply chains. Results indicated that technological turbulence had a minimal effect, and thus market structure and strategic alignment became more critical for their strategic actions. Cooperation advantages are applicable across various levels of market intensity and dynamism, as seen in the JD–Tmall partnership. These companies demonstrate how e-commerce businesses can move past mandatory compliance through open business models, which create superior efficiency and better customer experiences. Through this study, we validate a combined thematic and LDA topic modeling-based approach to analyze coopetition activities in digital ecosystems.

Authors

Publication Details

Journal
Advances in Artificial Intelligence and Machine Learning
Published
2025-01-01
DOI
https://doi.org/10.54364/aaiml.2025.52206
Citations
1
Primary Topic
Business Strategy and Innovation
Type
article
Field-Weighted Citation Impact
2.23
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article

Coopetition Analysis Between JD and Tmall in China’s E-Commerce Landscape: A Hybrid Thematic-Latent Dirichlet Allocation Approach

Pagon Gatchalee
1 citations
Advances in Artificial Intelligence and Machine Learning
Business Strategy and Innovation
2.23
article

Coopetition Analysis Between JD and Tmall in China’s E-Commerce Landscape: A Hybrid Thematic-Latent Dirichlet Allocation Approach

Pagon Gatchalee
article en
1 citations

Abstract

JD and Tmall ended restricted models of their ecosystems in 2024 with a new collaborative approach that opened previously isolated spaces or referred as ‘walled gardens.’ This study explores the key drivers of this shift and how these major e-commerce platforms coordinate logistics and payment systems amidst intense market competition. We adopted a hybrid approach to collect data through word cloud analysis, followed by thematic analysis with verification by Latent Dirichlet Allocation (LDA) modeling, which minimizes coder bias. Our study results show that, while regulatory pressure, including antitrust policies, played a role, several non-regulatory factors were equally or more influential. These include shifting consumer expectations for faster delivery, growing demand for secure and flexible payment options, and competitive pressure from pricing strategies and brand positioning. Through strategic competition initiatives, JD and Tmall achieved balanced collaboration and competition to enhance market efficiency and operational resilience. Firms successfully navigated competitive risks toward maximizing coopetition benefits because of their strong absorptive capacity and agile supply chains. Results indicated that technological turbulence had a minimal effect, and thus market structure and strategic alignment became more critical for their strategic actions. Cooperation advantages are applicable across various levels of market intensity and dynamism, as seen in the JD–Tmall partnership. These companies demonstrate how e-commerce businesses can move past mandatory compliance through open business models, which create superior efficiency and better customer experiences. Through this study, we validate a combined thematic and LDA topic modeling-based approach to analyze coopetition activities in digital ecosystems.

Advances in Artificial Intelligence and Machine LearningVol. 05(02)
Openalex Percentile: Top 11%
Business Strategy and Innovation
2.23
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