1. Introduction

The contemporary world continues to grapple with uneven development patterns, which appear to be exacerbating rather than diminishing. Among various contributing factors, the digital infrastructure gap stands out as both a conspicuous manifestation and a significant driver of these global disparities.

This thesis will disclose the disparities in digital infrastructure development among developing countries and their impact on global development imbalances, using China and India as comparative case studies. China's digital infrastructure advancement follows a top-down model, where strategic national planning precedes technological accumulation by private enterprises. Currently, China has achieved breakthroughs in telecommunications networks and computing infrastructure, thereby enabling applications such as e-governance and industrial digitization. However, challenges persist, including regional development gaps and data security concerns. Moving forward, China aims to advance its digital infrastructure through technological self-sufficiency, green digital initiatives, and global collaboration.

Meanwhile, India has also undergone policy evolution, notably with the launch of the "Digital India" initiative in 2015. Concurrently, it possesses significant advantages in its IT service sector, supported by outstanding enterprises that drive software exports, along with a vast demographic dividend evidenced by its 880 million internet users. However, as evidenced by the outcomes, India's digital infrastructure development has not achieved the same level of prominence as China's. This is primarily due to India's persistent challenges in traditional infrastructure areas such as electricity and land resources, which constitute fundamental constraints on its development.

In this study will sequentially pose and address three key questions: First, how are the disparities in infrastructure development manifested between China and India? Second, what impacts do these disparities have on both countries' economic development and the global development imbalance? Third, how can infrastructure gaps be narrowed through policy interventions and international cooperation? This study conducts a comparative analysis of digital infrastructure development between China and India, systematically examining investment inputs, output performance, and economic impacts. Through this dual-country comparison, the research elucidates how national capital allocation and strategic planning shape digital infrastructure advancement, while demonstrating the mechanisms through which digital infrastructure influences macroeconomic growth trajectories.

2. Literature review

In examining the impact of digital infrastructure on global development imbalances and their consequences, the paper has reviewed relevant literature, with particular focus on studies analyzing the concrete economic effects of digital infrastructure. The study mainly read the essay about China. The following section will summarize the key perspectives from these studies.

Research demonstrates that digital infrastructure plays a pivotal role in driving the development of new quality productivity, thereby enhancing overall productive forces. In the paper "Research on digital infrastructure construction empowering new quality productivity," the author employs a static panel model using data from 276 Chinese prefecture-level cities between 2011 and 2020 to empirically examine the impact of digital infrastructure on new quality productivity. The baseline regression results indicate that digital infrastructure significantly promotes the advancement of new quality productivity, with findings remaining robust after a series of stability and endogeneity tests [1]. Meanwhile, the study "Digital Infrastructure and the Formation of Firm-Level New Quality Productivity: A Theoretical and Empirical Analysis" approaches the topic from an enterprise perspective. Based on the theoretical framework of labor, means of production, and objects of labor, the paper constructs a firm-level new quality productivity index and examines the influence of regional digital infrastructure on enterprise productivity using data from China's A-share listed companies from 2011 to 2021. The results reveal that digital infrastructure significantly enhances firm-level new quality productivity. Further mechanism analysis shows that digital infrastructure fosters the formation of new quality productivity in enterprises by promoting technological innovation, improving operational efficiency, and strengthening human capital development [2]. Together, these studies underscore digital infrastructure's dual role as both a macro-level driver of regional productivity growth and a micro-level enabler of enterprise transformation, highlighting its critical importance in shaping China's economic modernization.

Research further highlights digital infrastructure's role in reducing regional disparities, particularly between urban and rural areas, by boosting economic development in less-developed regions and mitigating nationwide development imbalances. In the paper *"How Does Digital Infrastructure Mitigate Urban–Rural Disparities?"*, the authors employ a staggered difference-in-differences (DID) method to evaluate the long-term effects of broadband adoption on labor market outcomes. The study finds that broadband connectivity increases rural wages by 7–9% with no significant impact on urban wages, primarily driven by job creation and human capital accumulation in rural areas, thereby narrowing the urban-rural wage gap. Additionally, heterogeneous effects are observed, with stronger impacts in less-developed regions and among disadvantaged groups, suggesting that targeted digital infrastructure initiatives, such as broadband expansion, can effectively reduce income inequality and foster more inclusive economic growth [3]. Similarly, the study *"Digital Infrastructure Empowers Rural Common Prosperity: Heterogeneous Effects and Pathway Analysis"* systematically examines the impact of digital infrastructure on rural common prosperity using data from the China General Social Survey (CGSS), National Bureau of Statistics, and regional statistical yearbooks, applying a two-way fixed-effects model. The results demonstrate that digital infrastructure significantly promotes rural common prosperity overall, though its effects vary across regions and skill groups. Mechanism analysis reveals that digital infrastructure primarily enhances both material and cultural well-being for rural residents by facilitating digital financial inclusion, expanding employment opportunities, strengthening social interactions, and transforming cultural mindsets [4]. Together, these findings underscore digital infrastructure's potential as a powerful equalizer in addressing spatial inequalities and fostering balanced development.

Through a review of existing literature, it becomes evident that while numerous studies focus on how China has advanced its digital infrastructure, few identify the specific factors that have enabled China to outperform other developing nations in this domain. To address this gap, the thesis conducts a comprehensive comparative analysis of the processes and outcomes of digital infrastructure development in both China and India. This paper will systematically examines and compares the achievements of China and India in digital infrastructure development, analyzing the disparities between the two countries and their underlying causes. The study ultimately aims to distill China's effective strategies, offering actionable insights for other developing countries seeking to enhance their own digital infrastructure frameworks.

3. Comparative analysis of digital infrastructure investment between China and India

3.1. Concept

In this paper, digital infrastructure is conceptualized as the integrated system of hardware, software, network architectures, and data resources that underpin the operation of digital economies and societies. This encompasses critical components such as broadband networks, data centers, server systems, and satellite internet technologies. Its applications manifest in multiple domains: facilitating smart manufacturing to propel industrial advancement, and enabling mobile payment systems and cross-border settlements to accelerate the development of comprehensive digital finance ecosystems.

The International Telecommunication Union (ITU) notes that well-developed digital infrastructure can significantly enhance a nation's economic competitiveness, while McKinsey research indicates that every 1% increase in digital infrastructure investment drives GDP growth by 0.3% to 0.6%. This demonstrates the vital importance of digital infrastructure for global economic development today. Recognized by the World Bank as "a critical driver of 21st century growth," digital infrastructure plays a pivotal role in promoting balanced global development.

This study focuses on China and India, the two largest developing countries, through a comparative analysis of their investments in digital infrastructure construction, outcomes achieved, and socio-economic impacts, aiming to elucidate the underlying factors shaping their current digital infrastructure development status.

China has adopted a government-led approach characterized by top-level planning and design, with the state guiding the development direction of digital infrastructure. This has fostered a synergistic development model combining government guidance, market participation, and industrial collaboration. These development experiences can provide valuable guidance for other developing nations in planning their digital infrastructure initiatives.

For developing countries that still lag behind in digital infrastructure development, the construction of such infrastructure can serve as a powerful driver for economic growth. This paper seeks to summarize actionable insights and best practices to support these nations in their digital transformation journeys.

3.2. Digital infrastructure investment

3.2.1. Government strategies and policy support

In the last ten years, China has rolled out overarching framework for digital infrastructure deployment: the Digital China Strategy (2017-2025). The Digital China Strategy is a national-level strategic framework formulated by the Chinese government to comprehensively advance digital transformation, deeply integrating digital technologies with economic development, social construction, governance, and institutional building. Its core objectives are to establish world-leading digital infrastructure by 2025, with the digital economy accounting for over 50% of GDP, and to fully empower socioeconomic development with mature Chinese-style digital governance by 2035. Digital infrastructure construction stands as one of the strategy's three central pillars, comprising three key components: 5G and gigabit optical networks (including 5G base stations and fiber-optic cables), data center clusters, and satellite internet (e.g., the Hongyan and Hongyun constellation projects). The Chinese government supports this through multiple channels: financial backing (cumulative investments in gigabit network development), standard-setting (such as mandating contributions to essential 5G patents), and pilot demonstrations (e.g., establishing innovation hubs in Zhejiang and Guangdong for digital economy experimentation) [5].

The Digital India Initiative, introduced in 2015 as India's flagship digital transformation strategy, seeks to harness digital technologies to enhance public service delivery, stimulate economic expansion, and improve quality of life. Central to this initiative are three strategic priorities: developing digital infrastructure (through nationwide fiber-optic deployment, 4G/5G network rollout, and data center construction), digitizing government operations, and ensuring equitable digital access to reduce geographical disparities. These interconnected components collectively aim to position India as a digitally empowered society [6-8].

3.2.2. Funding investments

According to the "Communications Industry Statistical Bulletin" issued by China's Ministry of Industry and Information Technology (MIIT), China's total investment in digital infrastructure from 2019 to 2023 reached approximately 10.7 trillion RMB (about 1.5 trillion USD). As reported in India's MeitY 2023 Annual Report, the country's cumulative investment in digital infrastructure during the same period amounted to around 3.5 trillion INR (roughly 420 billion USD).

3.3. Output and scale

3.3.1. Network coverage and quality

The study will utilize the number of 5G base stations as a metric to evaluate network coverage and service quality. According to China's "Communications Industry Statistical Bulletin" released by the Ministry of Industry and Information Technology (MIIT), China had deployed 3.377 million 5G base stations by 2023, accounting for approximately one-third of all mobile network base stations. It shows 24 5G base stations per 10,000 people, marking an increase of 7.6 stations per 10,000 compared to 2022. Full coverage in all prefecture-level urban areas and county towns, with ongoing expansion to key facilities.

In contrast, India's Ministry of Electronics and Information Technology (MeitY) 2023 Annual Report indicates that the country had deployed around 100,000 5G base stations by December 2023, with deployment led primarily by private enterprises: to be more specific, Reliance Jio built 60,000 stations (60% share), Bharti Airtel built 40,000 stations (40% share), 0.7 5G base stations per 10,000 people. It mainly concentrated coverage in major cities like Mumbai, Delhi, and Bengaluru, with rural areas remaining underserved (<20% coverage). It has been concluded in the Table1.

Table 1: Contrast of 5G station of China and India

Data source:China's "Communications Industry Statistical Bulletin" released by the Ministry of Industry and Information Technology (MIIT),India's Ministry of Electronics and Information Technology (MeitY) 2023 Annual Report.

3.3.2. Computing infrastructure

This analysis utilizes dual quantitative indicators for computational infrastructure assessment: installed data center rack units and operational supercomputing facility numbers. The study based on 2023 construction data: Chinese data center racks are 6.5 million and national supercomputing centers are 15, which including under construction. The source is from CAICT “Data Center Industry Development White Paper (2023)”. Indian data center racks are about 120,000, and national supercomputing centers are 3 operational as well as 2 under construction. The source is from NASSCOM "Data Center Report 2023". In conclusion, the data center racks shows China: India = 542:1, and supercomputing centers: 5:1 (operational).

3.4. Next generation technology rollout

3.4.1. China

This paper will use Shenzhen's 5G-A smart port as a case study. Mawan Port in Shenzhen is a core container terminal in the western port area of Shenzhen. As a traditional operation mode port, it faced a series of challenges: the deployment cost of fiber-optic networks was very high; the efficiency of manual container handling had reached a bottleneck.

In 2023, Mawan Port initiated a 5G-A intelligent upgrade, becoming the world's first automated terminal with comprehensive 5G-A coverage. It first deployed over 5,000 5G-A RedCap terminals, a lightweight 5G technology, installed at smart container locks, automated guided vehicle control units, and environmental sensors. Secondly, it established a BeiDou+5G-A integrated positioning system, where BeiDou-3 provided nanometer-level initial positioning, and 5G-A sensing-integrated base stations supplemented millimeter-wave ranging, improving dynamic positioning accuracy and reducing response latency.

The 5G-A intelligent upgrade delivered significant results. First, it enhanced operational efficiency, increasing single-crane productivity from 28 containers per hour before the upgrade to 35 containers per hour, a 25% improvement. Second, it reduced path-planning response time from 500ms before the upgrade to 80ms after. Additionally, it achieved cost savings by replacing originally planned fiber-optic cabling and reducing required manpower. Finally, it improved operational safety by decreasing AGV collision incidents and increasing the accuracy of violation behavior recognition [9].

3.4.2. India

This paper will use India's UPI (Unified Payments Interface) as a case study. It employs a real-time settlement system (IMPS) and utilizes standardized interfaces and security mechanisms. In 2023, its annual transaction volume reached 74 billion transactions, accounting for 46% of global transactions. At the same time, it is also establishing cross-border interconnection infrastructure, enabling integration with Singapore's PayNow and the UAE's UAEPay.

It has significantly contributed to economic development. First, it has enhanced financial inclusion by enabling electronic payments for unbanked users and increasing the penetration of digital payments in rural areas. Second, it has integrated government services, allowing individuals to pay income taxes, utility bills, and other fees electronically, while also facilitating the distribution of welfare benefits through digital payments.

However, it also faces challenges. First, India's incomplete traditional infrastructure limits the transmission of large-scale data, resulting in significant pressure during peak transaction periods. Second, security and fraud issues persist, with phishing attacks occurring within the UPI system [10].

3.5. Economic returns from digital infrastructure

3.5.1. Expansion of digital economy

The study has statistically analyzed the scale and the proportion in Chinese and Indian overall GDP of China's digital economy from 2018 to 2022.

From Figure 1 and Figure 2, it can be concluded that both China and India experienced growth in their digital economies between 2018 and 2022, with an increasing share of GDP contributed by the digital sector. However, China's digital economy was significantly larger in scale and accounted for a higher percentage of GDP compared to India, while also demonstrating faster growth rates. This suggests that digital infrastructure development has indeed driven the expansion of the digital economy in both countries, with China benefiting from more advanced and rapidly scaling infrastructure.

Figure 1: The digital economy size of China and India (picture credit: original)

Figure 2: The share of GDP of China and India (picture credit: original)

Data from “China Digital Economy Development White Paper” by China Academy of Information and Communications Technology (CAICT) and “Digital India Outlook” by India's Nasscom.

3.5.2. Case study:industrial transformation and upgrading

For China, the study examines the digital transformation of Sany Heavy Industry's Beijing "Factory 18" as a case example. It represents a typical model of the "Lighthouse Factory" concept. The facility primarily utilizes three key components of digital infrastructure. First, an edge computing quality inspection system, deploying over 50 Atlas 800 inference servers equipped with Ascend 910B AI chips. Second, a 5G+BeiDou intelligent logistics system, featuring: 5G private network base stations within the factory. Integrated BeiDou-3 RDSS short message functionality to maintain operations during extreme weather AGV swarm management capabilities. Third, a blockchain supply chain platform built on the Chang'an Chain framework. The system has achieved several critical technological breakthroughs. First, Development of a multi-source positioning fusion algorithm resolving BeiDou signal conflicts. Second, Heavy-load AGV collaborative control with significantly reduced latency. Finally, Contributions to manufacturing blockchain standards. Its improvement is also very remarkable. Firstly, it has enhanced production efficiency. Secondly, it has improved economic efficiency. AI technology has been applied to some dangerous jobs, reducing labor costs. Additionally, AGVs (Automated Guided Vehicles) have replaced some forklifts, reducing fuel consumption. Finally, this project has also improved environmental benefits. By using photovoltaic power generation, it has reduced the consumption of polluting energy sources [11].

As for India, the study will use the digital transformation of the Tamil Nadu factory in India as a case study. In 2021, Foxconn established an iPhone-dedicated factory in Tamil Nadu, India, where digital technologies were applied to advance the quality control system. First, its technical framework incorporates a computer vision cluster, deploying over 2,800 industrial cameras, and adopts an edge computing+cloud collaboration architecture: utilizing NVIDIA EGX edge servers and the local AWS Mumbai Node AI training platform. Additionally, it employs algorithmic innovations, including the development of a "dust-resistant defect detection algorithm" and a dynamic learning system to identify defective products. The key breakthroughs include: First,100% fully automated optical inspection (AOI) are adopted in the production process. Second, Adaptive calibration via environmental sensors that adjust parameters such as temperature in real time, reducing false negatives and missed detections. After digital transformation, quality performance improved significantly: First, Motherboard first-pass yield increased from 88.7% to 94.3%. Second, Post-sales return rates dropped, making it the best-performing Apple factory globally. In addition, Costs related to manual inspections, material waste, and other inefficiencies were reduced, lowering expenses and increasing revenue. This case demonstrates India’s rise in the global value chain, transitioning from simple assembly to "manufacturing + digital services", thereby accelerating India’s industrial digital transformation.

These two case studies demonstrate how digital infrastructure has driven industrial transformation in both China and India. Despite differing ownership models (Chinese private vs. India's FDI-driven), both cases prove that tailored digital infrastructure enables developing nations to leapfrog traditional industrialization pathways. The synergy of edge computing, IoT, and AI has become a universal catalyst for industrial advancement.

4. Limitation and future outlook

4.1. Limitation

In the course of this research, the study has encountered several limitations. First, the study did not conduct field visits to digital infrastructure facilities in China and India, and thus could not personally observe the actual development status or identify specific operational challenges in these countries' digital infrastructure systems. Second, during data collection, certain official statistics on digital infrastructure from both China and India were inaccessible. Consequently: The number of comparative indicators used was reduced from the originally planned set; The selected indicators cannot fully represent the complete picture of digital infrastructure development in both countries; The analysis fails to comprehensively reflect the full socioeconomic impact of digital infrastructure development. Additionally, this study primarily focuses on cross-sectional comparisons between China and India within a five-year timeframe, lacking longitudinal analysis to track the dynamic evolution of the digital infrastructure gap between the two nations.

4.2. Future research direction

In the upcoming research, the study should seek indicators that better represent the development of digital infrastructure and are more easily quantifiable. Through the reasonable quantification of these indicators, a multi-faceted and in-depth analysis can be conducted. These quantified metrics can help provide a more accurate assessment of the development level of digital infrastructure, as well as uncover the root causes of disparities. This will offer more practical and actionable development strategies for developing countries to advance their digital infrastructure in the future.

5. Conclusion

In this paper, the study has conducted a comparative analysis of China and India as case studies, examining their respective development models and the economic impacts of digital infrastructure. The study highlights how disparities in digital infrastructure development contribute to global inequality. The study's key findings are as follows: First, the differences in digital infrastructure development between China and India stem from their distinct approaches to resource allocation and strategic planning. China adopts a state-coordinated, top-down model, with centralized investments driving nationwide deployment. In contrast, India’s "Digital India" initiative remains largely influenced by private-sector participation, and China’s overall investment in digital infrastructure significantly surpasses India’s. Second, variations in digital infrastructure directly affect national economic growth. China’s advanced digital infrastructure has played a crucial role in fostering its digital economy and facilitating industrial upgrading, demonstrating a strong positive correlation between infrastructure development and economic progress. These disparities exacerbate global economic imbalances, widening the gap between nations with robust digital infrastructure and those still developing theirs. Finally, for other developing countries, China’s model—featuring government-led planning, policy incentives, and public-private collaboration—offers valuable lessons. Additionally, international cooperation in digital infrastructure development presents a viable pathway for bridging global disparities.

Based on the findings of this study, the following recommendations can be proposed: First, optimize the allocation of digital infrastructure resources. Governments should establish clear plans for the distribution and development goals of digital infrastructure and increase investment in its construction. Additionally, encourage the growth of private high-tech enterprises by providing policy and financial support to digital technology firms, thereby driving technological advancement.