Predicting the Commercial Viability of Cross-IP Collaboration

Haicheng Zhai

doi:10.47297/wspdecWSP2515-797317.20261004

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Predicting the Commercial Viability of Cross-IP Collaboration

10卷第4期

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Predicting the Commercial Viability of Cross-IP Collaboration
Predicting the Commercial Viability of Cross-IP Collaboration
Parv. de la Défense, 92800, Puteaux
2026年10卷第4期页码：89-102
网络首发：2026-07-29，

纸质出版：2026-04-30
DOI：10.47297/wspdecWSP2515-797317.20261004
Accepted：

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Haicheng Zhai. (2026). Predicting the Commercial Viability of Cross-IP Collaboration. 发展经济学, 10(4), 89-102.

Zhai Haicheng.Predicting the Commercial Viability of Cross-IP Collaboration[J].Development Economics of China,2026,10(04):89-102.
Haicheng Zhai. (2026). Predicting the Commercial Viability of Cross-IP Collaboration. 发展经济学, 10(4), 89-102. DOI： 10.47297/wspdecWSP2515-797317.20261004.

Zhai Haicheng.Predicting the Commercial Viability of Cross-IP Collaboration[J].Development Economics of China,2026,10(04):89-102. DOI： 10.47297/wspdecWSP2515-797317.20261004.

摘要

Abstract

Cross-intellectual-property (cross-IP) collaboration is increasingly used across entertainment

consumer products

digital platforms

games

and cultural institutions

yet firms lack a transparent method for deciding before launch whether a proposed collaboration is commercially viable. This paper defines cross-IP collaboration as the commercial recombination

translation

or extension of independently controlled intellectual-property assets across organizational

product

or media boundaries to create monetizable outputs. It develops an Ex-Ante Cross-IP Commercial Viability Model covering six pre-launch conditions: IP asset strength

cross-IP fit

product-translation capability

incremental-demand potential

financial feasibility

and governance and brand risk. The model separates prediction from validation. Objective indicators are benchmarked against comparable projects; consumer perceptions are collected through concept testing; expert assessments use anchored rubrics; and financial viability is evaluated through scenario-based expected net present value. Post-launch price

attention

sell-through

and secondary-market outcomes are treated as validation targets rather than inputs to the score of the project being assessed. The empirical analysis uses a candidate pool of 1

682 LEGO products

a final sample of 250 products

and 234 products with historical US recommended retail prices. Six hedonic-price specifications associate cross-IP status with a conditional launch-price premium of 13.3% to 19.6%

with every 95% confidence interval remaining above zero. The attention analysis contains 3

904 daily Wikimedia observations but only two independent collaboration events. Two of six controlled interrupted time-series specifications show statistically significant immediate relative effects

and results vary substantially by case and time window. Supplementary secondary-market data comprise 727 Pokemon transactions concentrated in two products and a 28-row LEGO resale pilot covering 14 sets; these records demonstrate measurement feasibility but do not identify collaboration effects. No historical project in the dataset contains all six pre-launch scores

post-launch outcomes

and net economic returns. The evidence therefore supports part of the model's first-stage market-value mechanism

while the XCVS remains an uncalibrated predictive framework rather than a validated probability of success.

关键词

Keywords

references

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