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Purpose

The purpose of this paper is to examine the relationship between primary product network size and the sales of complementary products, and to suggest customer characteristics moderating this relationship.

Design/methodology/approach

A panel dataset in the online video game industry was used to verify the proposed theoretical framework. Two‐level hierarchical linear modeling is used to test several hypotheses.

Findings

The authors' analysis results suggest there is a positive relationship between the primary product network size and the sales of complementary products. Also, two customer characteristics (previous transaction value and customer purchase frequency) were found to positively influence the complementary product sales. The primary product's network size has a stronger impact on complementary product sales for light buyers compared to heavy buyers.

Research limitations/implications

This study only focused on online video industry, and the price differentiation of the products might not be adequately significant. Other relevant factors (such as word‐of‐mouth (WOM)) or other customer characteristics could also be relevant to complementary product sales. Therefore, future research could use data triangulation to collect data in different contexts, through a longer period of time, to test and verify the proposed relationships.

Practical implications

Product managers need to better understand the relationship between the primary product network size and the complementary product sales. They should adjust the marketing strategies toward different customer purchase frequency segments correspondingly. For example, to benefit further from the primary product network size, complementary product retailers can create online forums for all primary product users to influence light complementary product buyers.

Originality/value

This research is one of the first empirical investigations of establishing the relationship between primary product network size and complementary product sales, with customer characteristics as moderators.

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