Enhancing Digital Innovation Ecosystem Resilience through the Interplay of Organizational, Technological, and Environmental Factors: A Study of 31 Provinces in China Using NCA and fsQCA
Abstract
:1. Introduction
2. Literature Review and Theoretical Framework
2.1. Digital Innovation Ecosystem Resilience
2.2. Research Framework
2.3. Model Construction
2.3.1. Technological Level
2.3.2. Organizational Level
2.3.3. Environmental Level
2.3.4. Research Model
3. Research Design
3.1. Research Methodology
3.2. Samples and Data
3.3. Measurement and Calibration
4. Empirical Analysis
4.1. Analysis of Necessary Conditions
4.2. Configuration Analysis
4.2.1. Configurations of High Digital Innovation Ecosystem Resilience
4.2.2. Configurations of Non-High Digital Innovation Ecosystem Resilience
4.3. Robustness Tests
4.4. Analysis of Substitution Relations
5. Discussion, Conclusions, Recommendations, and Limitations
5.1. General Discussion
5.2. Research Conclusions
5.3. Research Contribution
5.4. Recommendations
- Prioritize R&D investments: First, prioritizing R&D investments is crucial to strengthening the “engine” of a system. As evidenced by its presence in four configurations of digital innovation ecosystem resilience, R&D investments is assumed to be universally pivotal. Policymakers should encourage collaboration and diversified-entity participation in R&D investments.
- Coordinate configurations: Second, emphasis should be placed on recognizing the flexibility in attaining high resilience by combining technological, organizational, and environmental aspects. Strategies should be tailored to leverage an ecosystem’s specific strengths and address its challenges, whether through resource optimization, innovation-environment enhancement, or digital technology utilization.
- Learn from successful regions: Third, emulating the successful strategies of resilient regions and seeking optimal paths to resilience are crucial. As regions with strong resilience frequently demonstrate unique configurations, western regions can learn from the successes of eastern and central regions, tailoring policies to their specific strengths and innovation environments to increase resilience. For example, Guizhou Province could leverage its geographical advantages to establish innovation bases like “China’s Tianyan” and “China’s Digital Valley,” thereby creating a unique edge for the development of its digital economy and the construction of an innovative environment. This strategic approach will contribute to the continuous enhancement of digital innovation ecosystem resilience.
5.5. Research Limitations and Prospects
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Variable | Description | Full Membership | Crossover Point | Full Non-Membership | Data Sources |
---|---|---|---|---|---|
Digital technology application | Breadth of coverage, depth of use, and degree of digitization of digital financial inclusion index in 2019 | 357.403 | 335.267 | 310.492 | The Peking University Digital Financial Inclusion Index of China (2011–2020) |
Human resource | The average years of schooling in 2019 | 12.189 | 11.909 | 11.367 | China statistical yearbook (2020) |
R&D investment | The intensity of R&D investments in 2019 | 2.100 | 1.610 | 0.950 | China statistical yearbook (2020) |
Innovation environment | The score of the innovation environment in 2019 | 26.870 | 21.990 | 19.120 | Evaluation Report on Regional Innovation Ability in China (2019) |
Inter-provincial competitive pressure | The average value of the traditional industry and the digital economy integration index of adjacent provinces in 2019 | 36.150 | 30.500 | 25.867 | Digital economic development index of China (2019) |
Digital innovation ecosystem resilience | The score of the digital innovation ecosystem resilience in 2020 | 173,613.455 | 95,722.222 | 42,611.645 | China statistical yearbook on high technology industry (2021); China statistical yearbook on science and technology (2021); China statistical yearbook (2021); Report of Key Laboratory in China (2016) |
Antecedent Condition | Approach | Accuracy | Upper-Left Area | Scope | Effect Size (d) | p Value |
---|---|---|---|---|---|---|
Digital technology application | CR | 90.3% | 0.248 | 0.98 | 0.253 | 0.000 |
CE | 100% | 0.243 | 0.98 | 0.248 | 0.000 | |
Human resource | CR | 90.3% | 0.065 | 0.99 | 0.065 | 0.019 |
CE | 100% | 0.017 | 0.99 | 0.017 | 0.111 | |
R&D investment | CR | 87.1% | 0.356 | 0.99 | 0.360 | 0.000 |
CE | 100% | 0.328 | 0.99 | 0.331 | 0.000 | |
Innovation environment | CR | 87.1% | 0.237 | 0.99 | 0.240 | 0.000 |
CE | 100% | 0.129 | 0.99 | 0.130 | 0.000 | |
Inter-provincial competitive pressure | CR | 96.8% | 0.017 | 0.99 | 0.017 | 0.258 |
CE | 100% | 0.030 | 0.99 | 0.030 | 0.166 |
Digital Innovation Ecosystem Resilience | Digital Technology Application | Human Resource | R&D Investment | Innovation Environment | Inter-Provincial Competitive Pressure |
---|---|---|---|---|---|
0 | NN | NN | NN | NN | NN |
10 | NN | NN | NN | NN | 0.2 |
20 | 4.6 | NN | 6.9 | NN | 0.6 |
30 | 11.3 | NN | 16.3 | NN | 1.0 |
40 | 18.0 | NN | 25.8 | NN | 1.3 |
50 | 24.7 | NN | 35.2 | 6.8 | 1.7 |
60 | 31.5 | 4.6 | 44.6 | 23.2 | 2.1 |
70 | 38.2 | 10.2 | 54.1 | 39.5 | 2.5 |
80 | 44.9 | 15.9 | 63.5 | 55.8 | 2.9 |
90 | 51.6 | 21.5 | 72.9 | 72.2 | 3.2 |
100 | 58.3 | 27.1 | 82.3 | 88.5 | 3.6 |
Antecedent Condition | High Digital Innovation Ecosystem Resilience | Non-High Digital Innovation Ecosystem Resilience | ||
---|---|---|---|---|
Consistency | Coverage | Consistency | Coverage | |
Digital technology application | 0.824 | 0.856 | 0.272 | 0.290 |
~Digital technology application | 0.317 | 0.298 | 0.866 | 0.835 |
Human resource | 0.619 | 0.561 | 0.539 | 0.502 |
~Human resource | 0.451 | 0.488 | 0.528 | 0.587 |
R&D investment | 0.883 | 0.822 | 0.275 | 0.263 |
~R&D investment | 0.208 | 0.218 | 0.813 | 0.877 |
Innovation environment | 0.807 | 0.767 | 0.357 | 0.348 |
~Innovation environment | 0.314 | 0.322 | 0.761 | 0.802 |
Inter-provincial competitive pressure | 0.714 | 0.693 | 0.395 | 0.394 |
~Inter-provincial competitive pressure | 0.375 | 0.376 | 0.693 | 0.713 |
Antecedent Condition | High Digital Innovation Ecosystem Resilience | Non-High Digital Innovation Ecosystem Resilience | ||||||
---|---|---|---|---|---|---|---|---|
H1a | H1b | H2 | H3 | H4 | NH1a | NH1b | NH1c | |
Digital technology application | ||||||||
Human resource | ||||||||
R&D investment | ||||||||
Innovation environment | ||||||||
Inter-provincial competitive pressure | ||||||||
Consistency | 0.921 | 0.942 | 0.954 | 0.997 | 0.968 | 0.914 | 0.925 | 0.957 |
Raw coverage | 0.683 | 0.179 | 0.205 | 0.249 | 0.119 | 0.353 | 0.414 | 0.521 |
Unique coverage | 0.398 | 0.022 | 0.026 | 0.061 | 0.013 | 0.053 | 0.115 | 0.222 |
Overall consistency | 0.914 | 0.941 | ||||||
Overall coverage | 0.827 | 0.690 |
Configuration Name | Configuration View | Configuration Explanation | Case Diagram |
---|---|---|---|
H1a digital technology-enabled organization–environment-driven type | Digital technology application *R&D investment* Innovation environment→high digital innovation ecosystem resilience | ||
H1b organization–environment dual-wheel-driven type | ~Human resource*R&D investment*Innovation environment*~Inter-provincial competitive pressure→high digital innovation ecosystem resilience | ||
H2 digital technology-led environment-driven type | Digital technology application*~Human resource*Innovation environment*Inter-provincial competitive pressure→high digital innovation ecosystem resilience | ||
H3 technology–organization–environment trilateral type | Digital technology application*~Human resource*R&D investment*Inter-provincial competitive pressure→high digital innovation ecosystem resilience | ||
H4 pressure–organization-driven type | ~Digital technology application*Human resource*R&D investment*~Innovation environment*Inter-provincial competitive pressure→high digital innovation ecosystem resilience |
Antecedent Condition | Configurations of High Digital Innovation Ecosystem Resilience | |||||||||
---|---|---|---|---|---|---|---|---|---|---|
Increasing the PRI Consistency Threshold | Changing the Calibration Anchors of Data | |||||||||
H1a * | H1b * | H2 * | H3 * | H4 * | H1a ** | H1b ** | H2 ** | H3 ** | H4 ** | |
Digital technology application | ||||||||||
Human resource | ||||||||||
R&D investment | ||||||||||
Innovation environment | ||||||||||
Inter-provincial competitive pressure | ||||||||||
Consistency | 0.921 | 0.942 | 0.954 | 0.997 | 0.968 | 0.936 | 0.953 | 0.941 | 1.000 | 0.992 |
Raw coverage | 0.683 | 0.179 | 0.205 | 0.249 | 0.119 | 0.663 | 0.209 | 0.217 | 0.262 | 0.157 |
Unique coverage | 0.398 | 0.022 | 0.026 | 0.061 | 0.013 | 0.362 | 0.016 | 0.021 | 0.052 | 0.011 |
Overall consistency | 0.914 | 0.920 | ||||||||
Overall coverage | 0.827 | 0.791 |
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Zhang, M.; Cheng, R.; Fei, J.; Khanal, R. Enhancing Digital Innovation Ecosystem Resilience through the Interplay of Organizational, Technological, and Environmental Factors: A Study of 31 Provinces in China Using NCA and fsQCA. Sustainability 2024, 16, 1946. https://doi.org/10.3390/su16051946
Zhang M, Cheng R, Fei J, Khanal R. Enhancing Digital Innovation Ecosystem Resilience through the Interplay of Organizational, Technological, and Environmental Factors: A Study of 31 Provinces in China Using NCA and fsQCA. Sustainability. 2024; 16(5):1946. https://doi.org/10.3390/su16051946
Chicago/Turabian StyleZhang, Ming, Ruoran Cheng, Jiabao Fei, and Ribesh Khanal. 2024. "Enhancing Digital Innovation Ecosystem Resilience through the Interplay of Organizational, Technological, and Environmental Factors: A Study of 31 Provinces in China Using NCA and fsQCA" Sustainability 16, no. 5: 1946. https://doi.org/10.3390/su16051946