Security Concerns versus Development Needs: Understanding Digital Silk Road Adoption Patterns
Why do states accept Chinese Digital Silk Road infrastructure investments despite well-documented security risks?
This project develops and tests a spatial bargaining model to explain DSR adoption patterns in Southeast Asia, arguing that domestic institutional configuration—not system-level factors—determines acceptance outcomes.
Despite warnings about surveillance capabilities, data sovereignty risks, and technological dependency:
- Vietnam welcomed Alibaba's e-commerce platforms despite experiencing 36 maritime confrontations with China in the South China Sea
- The Philippines dramatically expanded DSR acceptance under Duterte despite winning an international legal ruling against Chinese territorial claims
- Indonesia initially exhibited negative coverage of Chinese tech before reversing course in 2021-2022, despite having fewer direct disputes than its neighbors
Conventional explanations—threat perception, developmental need, alliance commitments—fail to explain this cross-national variation.
The model draws on three theoretical traditions:
| Theory | Author(s) | Key Insight |
|---|---|---|
| Two-Level Games | Putnam (1988) | International bargaining occurs simultaneously at domestic and international levels; win-set size determines outcomes |
| Veto Player Theory | Tsebelis (2002) | Policy stability increases with number of veto players and ideological distance between them |
| Executive Strength | Mo (1995) | Executive power affects outcomes even when formal veto structures remain constant |
Domestic actors hold preferences representable as indifference curves in a two-dimensional policy space:
- Security establishments → Flatter curves (require large developmental benefits to accept security risk)
- Economic ministries → Steeper curves (willing to accept security risks for developmental gains)
- Executives → Broader preferences reflecting wider institutional interests
The win-set—policies all veto players find acceptable—determines feasible DSR outcomes.
H1: DSR acceptance patterns are determined by: (1) veto player configuration, (2) preference alignment/divergence in security-development space, and (3) executive power in preference aggregation
H0 (Null): DSR acceptance is determined by system-level factors (threat magnitude, development level, alliance commitments)
| Source | Description | Coverage | Link |
|---|---|---|---|
| GDELT | Global Database of Events, Language, and Tone—media tone analysis | 2015–2025 | gdeltproject.org |
| CSIS AMTI | South China Sea incident tracking | 2014–2020 | amti.csis.org |
| IISS China Connects | DSR project database (173 countries) | 2013–2024 | chinaconnects.iiss.org |
| FRED | Macroeconomic indicators | Various | fred.stlouisfed.org |
| Category | Count | Examples |
|---|---|---|
| Core BRI/DSR | 6 | digital silk road, belt and road, BRI, OBOR |
| Chinese Tech Companies | 26 | Huawei, ZTE, Alibaba, Tencent, ByteDance, Hikvision |
| Tech Infrastructure | 23 | 5G, smart city, data center, submarine cable, Beidou |
| Digital Economy | 12 | e-commerce, digital payment, fintech |
| General China Tech | 10 | Made in China 2025, China digital |
DSR-Analysis/
├── Anlysis.ipynb # Main analysis & hypothesis testing
├── FRED.ipynb # FRED macroeconomic data retrieval
├── SCS_incidents.ipynb # South China Sea incident analysis
├── Gdelt_full.csv # Full GDELT event data
├── Gdelt_monthly.csv # Monthly aggregated GDELT data
├── csis_incidents.csv # CSIS SCS incident tracking
├── gdelt_dsr_summary.csv # DSR media tone summary statistics
└── README.md
| Variable | Operationalization | Model Component |
|---|---|---|
| DV: DSR Acceptance | GDELT media tone scores | Policy outcome on frontier |
| IV1: Veto Player Config | Institutional analysis of blocking power | Win-set width |
| IV2: Executive Weight | Constitutional powers, governing style | Outcome location (Mo, 1995) |
| IV3: Threat Perception | SCS incidents (AMTI) | Security actor preferences |
| IV4: Developmental Pressure | GDP per capita trajectory | Economic actor preferences |
Three ASEAN states selected via continuum sampling:
| Country | Regime Type | SCS Dispute Status | Key Finding |
|---|---|---|---|
| Vietnam | Authoritarian | Direct territorial/maritime disputes | Narrow win-set → selective acceptance |
| Philippines | Flawed democracy | Direct disputes + legal victory | Executive dominance → wide win-set |
| Indonesia | Flawed democracy | No formal disputes | Preference convergence via learning |
pandas
numpy
matplotlib
requests
fredapi
gdelt # optional, for direct GDELT API access
pip install -r requirements.txt# Clone repository
git clone https://github.com/Ali-Whatley/DSR-Analysis.git
cd DSR-Analysis
# Run notebooks in order
jupyter notebook FRED.ipynb # 1. Pull macroeconomic data
jupyter notebook SCS_incidents.ipynb # 2. Process incident data
jupyter notebook Anlysis.ipynb # 3. Main analysis-
Vietnam: Collective leadership produces 4 effective veto players → narrow win-set → selective acceptance (e-commerce yes, Huawei 5G no)
-
Philippines: Presidential dominance concentrates veto power → wide win-set tracking executive preferences → dramatic expansion under Duterte, reversal under Marcos Jr.
-
Indonesia: Coalition government permits preference convergence through learning → COVID-19 recovery + G20 hosting aligned previously divergent preferences
Bottom line: Domestic institutional configuration, not system-level threat perception or alliance commitments, determines DSR acceptance.
- Putnam, R. D. (1988). "Diplomacy and Domestic Politics: The Logic of Two-Level Games." International Organization, 42(3), 427–460.
- Tsebelis, G. (2002). Veto Players: How Political Institutions Work. Princeton University Press.
- Mo, J. (1995). "Domestic Institutions and International Bargaining." APSR, 89(4), 914–924.
- Farrell, H. & Newman, A. (2019). "Weaponized Interdependence." International Security, 44(1), 42–79.
- Hillman, J. (2021). The Digital Silk Road: China's Quest to Wire the World. Columbia University Press.
MIT License — see LICENSE for details.
Ali Whatley
Georgia Institute of Technology
INTA 8000
This project examines the political economy of technology competition as filtered through domestic institutions of recipient states.