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(How) does digital transformation promote boundary-spanning strategies Evidence from Chinese firms' unrelated diversification

Di Zhu et al.

International Journal of Technology Management2025https://doi.org/10.1504/ijtm.2025.143583article
AJG 2ABDC B
Weight
0.41

Abstract

The emergence of new generations of digital technologies has presented firms with important strategic opportunities at the corporate level. This study investigates the digital transformation - unrelated diversification link and theorises the role of industry shakeout and the performance expectation gap in said relationship. Our analysis based on the data of China's A-share listed manufacturing firms from 2015 to 2020 shows that: 1) the degree of firms' digital transformation is positively correlated to the degree of their unrelated diversification; 2) industry shakeout positively moderates the above relationship, i.e., in industries with a higher degree of shakeout, the positive digital transformation-unrelated diversification link is more pronounced; 3) the performance expectation gap negatively moderates the digital transformation-unrelated diversification link, i.e., the greater the performance expectation gap, the weaker the positive correlation between firms' digital transformation and their unrelated diversification.

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https://doi.org/https://doi.org/10.1504/ijtm.2025.143583

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@article{di2025,
  title        = {{(How) does digital transformation promote boundary-spanning strategies Evidence from Chinese firms' unrelated diversification}},
  author       = {Di Zhu et al.},
  journal      = {International Journal of Technology Management},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1504/ijtm.2025.143583},
}

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(How) does digital transformation promote boundary-spanning strategies Evidence from Chinese firms' unrelated diversification

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Evidence weight

0.41

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.25 × 0.4 = 0.10
M · momentum0.55 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.