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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

What the paper says

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.