Enhancing the Sustainable Development of the ASEAN’s Digital Trade: The Impact Mechanism of Innovation Capability

Abstract

Digital trade, as an emerging and transformative trade model in the digital era, has significantly altered global trade methods, products, services, and regulatory frameworks. This study investigates the impact mechanism of innovation capability on the sustainability of the ASEAN’s digital trade, emphasizing how technological advancements contribute to sustainable economic growth and digital resilience. Utilizing panel data from nine ASEAN countries between 2007 and 2021, this research explores how innovation capability fosters digital trade development by reducing the digital divide and promoting equitable access to digital markets. Findings highlight the substantial disparities in digital trade and innovation capacity across the ASEAN, with innovation capability playing a pivotal role in driving trade practices. This study reveals that digital readiness mediates the relationship between innovation capability and digital trade, while the RCA index serves as a moderating factor enhancing digital trade competitiveness. Furthermore, this study underscores that effective governance, regulatory quality, foreign direct investment (FDI), and a balanced wage–output ratio in the digital industry positively influence digital trade, whereas corruption and inadequate discourse power hinder it. The findings provide valuable policy recommendations for ASEAN countries to develop sustainable digital trade policies, strengthen innovation ecosystems, and bridge the digital divide, thereby contributing to the broader agenda of sustainable development.

1. Introduction

Digital trade has become an important driving force for global economic growth in the 21st century. In July 2013, the concept of digital trade was first introduced by the U.S. International Trade Commission in the report “Digital Trade in the U.S. and Global Economy.” [1]. The term “digital trade” refers to plenty of commercial activities and the international trade of products and services carried out via internet transmission. It involves digital products and services characterized by the provision of digital data and information that enable interaction between supply and demand parties, which is achieved using digital exchange technologies and internet transmission as the primary medium [2].

The fast growth of digital technology is the result of the digital trade’s development, which has become a key driver of global trade enhancement. In 2023, the global digital trade market reached USD 6.67 trillion, accounting for 21.3% of total global trade exports and growing at an average annual rate of 7.52%. Digital trade, as a new trade model and emerging research focus, has garnered significant attention from academia and industry [3]. Current research primarily explores areas such as digital services, service trade, trade digitization, digital property management, cross-border e-commerce, data security, and digital supply chains, providing in-depth discussions [4,5]. Scholars mainly emphasize the direct impact of digital trade on innovation capability [6]. Especially in terms of the generation mechanism of digital trade, existing research primarily focuses on the path of “innovation capability—digitization—trade development” and the reverse impact of digital trade on innovation capability [7]. Empirical evidence from China has been used to prove that technological innovation can promote the development of digital trade [8,9,10]. However, existing studies primarily rely on fixed-effects models, often overlooking the mediating and moderating effects between innovation and digital trade. Additionally, the mechanisms underlying their relationship remain unclear, and the applicability of the data used requires further refinement.

The Association of Southeast Asian Nations (ASEAN) is represented as one of the most promising regions for digital trade development [11]. Between 2020 and 2022, the ASEAN, with 100 million new internet users, became one of the fastest-growing internet markets in the world. By 2025, digital trade is projected to contribute approximately 64% of the total value of goods [12,13]. Current studies focus on trade efficiency, trade competitiveness, and the development of cross-border industrial chains, as well as the direct impact of digital trade on innovation. However, there is only little research on the mechanism by which innovation capability affects the volume and development of digital trade. In addition, most research has focused on developed economies, and the ASEAN as a rapidly growing digital trade hub has yet to be fully explored. Based on existing research, this article addresses limitations by studying the interaction between innovation capability and digital trade in the ASEAN region.

This study used quantitative methods and panel data from nine ASEAN countries in the period from 2007 to 2021 to explore the impact mechanism of innovation capability on the development of the ASEAN’s digital trade. Innovation capability, as the core driving force of technological progress, has a significant impact on the development and adoption of digital trade. This study used econometric models, such as fixed-effects and random-effects models, to test the four following hypotheses: Hypothesis 1: innovation capability positively impacts the development of digital trade; Hypothesis 2: innovation capability significantly enhances the level of digital product trade among ASEAN countries; Hypothesis 3: innovation capability significantly enhances the level of digital service trade among ASEAN countries; and Hypothesis 4: innovation capability significantly enhances the level of digital trade through the mediating effect of increasing digitalization. In addition, an innovation index consisting of patent applications and digital infrastructure indicators was developed to measure innovation capabilities. This study not only explores the direct impact of innovation capability on digital trade but also focuses on indirect impacts and dynamic mechanisms and introduces factors such as digital infrastructure, government governance level, and the wage–value ratio as control variables to gain a more detailed understanding of the relationship between the ASEAN’s innovation capability and digital trade.

This study’s results show that ASEAN countries face significant differences in promoting the development of digital trade, significant disparities in innovation capabilities, and diverse evolutionary characteristics. Empirical evidence also shows that innovation capability has a significant promoting effect on the development of digital trade in ASEAN countries. Further examination revealed that innovation capability affects the development of digital trade through the mediating effect of digital readiness, and the RCA index of the digital industry has a significant positive impact on digital trade as a moderating effect. The results of this study will not only provide empirical evidence for ASEAN policymakers to design effective innovation and digital trade policies but also theoretical insights for global researchers studying emerging markets.

The rest of this study is structured as follows: Section 2 reviews relevant literature and theoretical hypotheses on digital trade and innovation capabilities. Section 3 introduces the research methods and data sources. Section 4 discusses the results and main findings. Section 4 summarizes policy recommendations, research limitations, and future research directions.

2. Literature Review and Theoretical Hypotheses

2.1. The Current Situation and Relationship Between Innovation Capability and Digital Trade

Current Status of ASEAN Innovation Capability

ASEAN countries actively encourage digital innovation, identifying it as an important source of sustainable competitive advantage [14]. Innovation capability serves as a cornerstone for a comprehensive and effective growth strategy. While ASEAN countries have made notable advances in digital trade, digital trade is still rather uneven among them. For instance, Singapore does the best in the region in digital trade, excelling in areas such as digital infrastructure, e-commerce, and fintech. With its highly developed ICT infrastructure and international business environment, Singapore is regarded as the leader of the digital trade sector.

To further promote digital trade and enhance innovation capabilities, ASEAN governments have implemented various innovation policies. During the 26th China–ASEAN (10 + 1) Leaders’ Meeting, the Joint Initiative to Jointly Promote the Implementation of the China–ASEAN Science and Technology Innovation Enhancement Plan was adopted. This initiative emphasizes strengthening bilateral cooperation, fostering exchanges of scientific and technological talent, and jointly building a hub for regional innovation talent. It also aims to establish an open, inclusive, and competitive research collaboration platform, deepen technological innovation partnerships, promote technology transfer, and support innovation and entrepreneurship for regional economic and social prosperity [15].

Singapore, as the regional leader in innovation capacity, has introduced the Research, Innovation and Enterprise 2025 Plan [16], while Vietnam has proposed the Create Digital Innovation and Entrepreneurship policy. These initiatives reflect ASEAN governments’ concerted efforts to encourage digital innovation and develop action plans for progress [17].

Innovation capacity can be quantified by metrics, such as the number of patent applications filed.

Table 1. Number of patent applications in 10 ASEAN countries (Unit: applications).

Year	Singapore	Indonesia	Thailand	Malaysia	Vietnam	Philippines	Cambodia	Brunei	Laos
2007	9951	5134	6818	2372	2860	3473	13	64	23
2008	9692	5133	6741	5303	3199	3313	39	75	37
2009	8736	4518	5857	5737	2890	2997	28	42	18
2010	9773	5630	1937	6383	3582	3393	26	0	20
2011	9794	5830	3924	6452	3560	3196	43	0	43
2012	9685	0	6746	6940	3805	2994	53	31	53
2013	9722	7450	7404	7205	3995	3285	75	35	70
2014	10,312	8023	7930	7620	4447	3589	67	117	44
2015	10,814	9153	8167	7727	5033	3734	65	0	62
2016	10,980	9639	7820	7236	5228	3419	80	89	63
2017	10,930	9303	7865	7072	5382	3395	55	107	100
2018	11,845	9754	8149	7295	6071	4300	161	121	59
2019	14,136	11,481	8172	7551	7520	4380	310	141	0
2020	13,265	8160	7525	6828	7695	3993	248	120	0
2021	14,590	8800	8242	7534	8534	4393	0	139	0
Average	10,948.33	7200.53	6886.47	6617	4920.07	3590.27	84.2	72.07	39.47
Ranking	1	2	3	4	5	6	7	8	9
	1st tier (>10,000)	2nd tier (5000–10,000)			3rd tier (1000–5000)		4th tier (<1000)

Data Source: World Bank’s “Number of Patent Applications in ASEAN Countries”.

presents the patent application statistics for the ten ASEAN countries [18].

From the above table, it is evident that the number of patent applications in ASEAN countries has been steadily increasing year by year. Singapore stands alone in the first tier, with a significantly higher number of patent applications compared to the second-ranked Indonesia. The second tier comprises Indonesia, Thailand, and Malaysia. The third tier includes Vietnam and the Philippines. Finally, the fourth tier consists of Cambodia, Brunei, and Laos, where the number of patent applications remains very low.

2.2. Current Status of ASEAN Digital Trade Development

2.2.1. Emphasis on Digital Trade Development

In the era of the digital economy, ASEAN countries are promoting the development of digital trade; digital transformation is changing the economic landscape of Southeast Asia [19]. To promote the development of digital trade, the ASEAN has successively issued development plans such as the “ASEAN Connectivity Master Plan 2025”and the “ASEAN Digital Master Plan 2025” [20,21], proposing policies and goals for the development of digital trade from the perspective of regional cooperation and integration. At the same time, the ASEAN has signed a number of digital trade cooperation agreements with China, RCEP member countries and other countries, and established digital platforms such as the China–ASEAN Free Trade Area, China–ASEAN Information Port, and China–ASEAN Trade. Connectivity with China helps the ASEAN’s digital trade develop rapidly.

2.2.2. The Rapid Development of E-Commerce

Between 2015 and 2020, the Southeast Asian e-commerce market’s transaction size grew by approximately 11 times, from USD 5.5 billion to USD 62 billion. By 2025, it is anticipated to surpass 172 billion USD [22]. The “2023 Southeast Asia Digital Economy Report” published by Google, Temasek, and Bain & Company states that more than half of all transactions in Southeast Asia are digital payments, particularly in Vietnam, which is currently one of the nations with the fastest rates of growth in the world for cross-border e-commerce and digital payments. Its number of digital payment transactions rose 19% in 2023, and the average annual growth rate of cross-border e-commerce hit 35%, which is 2.5 times faster than Japan’s growth rate [23,24].

The worldwide FDI capital flow that the ASEAN attracted in 2022 was about 17%, up 100% from 2018, according to HSBC data. By 2030, it is anticipated that the ASEAN’s internal digital payments will total USD 1.5 trillion [25]. ASEAN nations are actively enhancing their digital infrastructure to enable the explosive rise of digital payments. For example, Singapore and Thailand are coordinating payments through a real-time payment system that links Singapore Pay Now and Thailand Prompt Pay.

2.2.3. The Increasing Usage and Popularity of the Internet

The World Bank’s “ASEAN Internet User Report 2021” shows that the Internet penetration rate in ASEAN countries continues to increase, and the top three countries with the highest Internet user rates are Brunei (98.08%), Singapore (96.92%), and Malaysia (96.75%). Except for Myanmar, the Internet user rate in other ASEAN countries all exceed 50% [26].

2.3. Relationship Between Innovation Capability and Digital Trade

Research indicates that a one-unit increase in national digital trade leads to a 0.066-unit rise in national innovation capability, with an even stronger effect (0.0711 units) observed in countries and regions along the “Belt and Road” [7]. Technological innovation serves as a crucial driver for the high-quality development of foreign trade. Digital trade enhances innovation capabilities through intermediary effects, such as reducing income inequality and upgrading industrial structures [27], and thereby significantly promotes high-quality trade development [28]. Based on the mechanism of innovation influencing digital trade, this study proposes the first theoretical hypothesis:

Hypothesis 1.

Innovation capability positively impacts the development of digital trade.

2.3.1. Relationship Between Innovation Capability and Digital Product Trade

With the increasing penetration of digital technology in international trade, digital product trade has exhibited robust growth and become a central component of digital trade [9,10]. According to the United Nations Commodity Trade Statistics Database (UN COMTRADE), the export value of digital products reached USD 5.76 trillion in 2020, representing over 30% of the total global goods trade export value [29].

In the context of digital product trade, the existing domestic and international literature primarily investigates the relationship between digital product trade networks and innovation capability. Studies suggest that the structure of a country’s digital product trade network can enhance its position in the global value chain by fostering technological progress, while independent innovation facilitates the upgrading of the digital trade network structure [30,31].

Based on this understanding, the second theoretical hypothesis is proposed:

Hypothesis 2.

Innovation capability significantly enhances the level of digital product trade among ASEAN countries.

2.3.2. Relationship Between Innovation Capability and Digital Service Trade

In the era of the digital economy, more than half of global service trade has been digitized, and over 12% of cross-border physical trade is facilitated through digital platforms [32]. Global digital service trade is experiencing rapid growth. Academic studies on digital service trade primarily focus on developing countries, with data from China revealing a positive correlation between technological innovation and digital service trade [28,33]. Furthermore, promoting service innovation has been shown to effectively enhance competitiveness in the digital service trade [34].

For G20 member countries, technological innovation has also significantly elevated international digital service trade levels [35]. Building on previous research findings, this study proposes the following hypothesis:

Hypothesis 3.

Innovation capability significantly enhances the level of digital service trade among ASEAN countries.

2.3.3. Regulatory Mechanism of Digitalization Level on the Relationship Between Innovation and Digital Trade

In the past decade, the trend of industrial digitization has become an unstoppable wave, with the development of the information service industry growing stronger and the contribution of digital construction to the global economy becoming increasingly significant. In the era of the digital economy, independent innovation driven by digital technology is the core competitive advantage; big data and information elements are the core production factors, achieving deep integration of digital technology and production methods, using modern information networks as the main carrier, continuously improving the systematic and digital level of traditional manufacturing production organization, and accelerating the reconstruction of new economic forms under economic development and government governance [36,37].

Foreign research mainly focuses on digital integrated manufacturing technology and has achieved certain research results. However, the digitalization of ASEAN industries has only entered the manufacturing field for a short time, and its development has just begun. Scholars’ research on digitalization has mainly focused on the strategic level, gradually achieving the goals of transformation and upgrading through integration with the information service industry. However, empirical research on how to enhance innovation capabilities through digitalization and promote the development of digital trade is still limited [38].

This study examines the mechanism through which ASEAN countries’ innovation capability impacts digital trade, focusing on the economic spillover effects and knowledge sharing effects. The regulatory role of the digitalization level on this relationship is illustrated in Figure 1:

The development of digital trade in ASEAN countries is influenced by the improvement of innovation capability, which generates economic spillover effects and knowledge sharing effects:

Economic spillover effects: Innovation accelerates the transformation of digital technologies, introduces advanced technological elements, and fosters the growth of digital infrastructure. These advancements, in turn, promote the development of digital trade across ASEAN countries.

Knowledge sharing effects: Innovation facilitates knowledge dissemination, which reduces trade costs and enhances trade efficiency, thereby stimulating digital trade activities. The new generation of information and communication technology (ICT) has further amplified the inclusiveness, diffusion, and sharing capabilities of digital platforms [39,40]. Platform-based organizations, enabled by digital technologies, create interactive channels that bridge virtual and physical spaces [41]. These interactive networks allow value co-creators to engage in collaborative behavior, enriching and deepening resource integration. This dynamic interaction also supports the construction of a robust digital service ecosystem.

Hypothesis 4.

Innovation capability significantly enhances the level of digital trade through the mediating effect of increasing digitalization. The RCA index of the digital industry has a significant positive impact on digital trade as a moderating effect.

2.4. Factors Influencing Digital Trade

Through a literature review, it is evident that both traditional factors and new factors play significant roles in the development of digital trade. Traditional factors include technological innovation, labor endowment, traditional infrastructure, and market size, while new factors encompass digital infrastructure, trust, and risk management. Specifically, foreign direct investment has been found to directly promote the scale of digital trade [42,43]. Similarly, international or regional digital trade frameworks facilitate consensus on digital trade rules, thereby promoting its development [27,44,45,46,47]. Furthermore, internet infrastructure significantly drives the expansion of digital service trade [48], while government regulation enhances the international competitiveness of digital trade [32,49,50]. These influencing factors will be incorporated as control variables in the model to provide a comprehensive analysis of the determinants of digital trade.

3. Methodology and Results

3.1. Analysis of Differences in Digital Trade Among ASEAN Countries

This article uses the Theil index to calculate the differences in digital trade development among ASEAN countries from 2010 to 2021, and the specific results are shown in

Table 2. Theil index and decomposition of digital trade differences among ASEAN countries.

Year	ICT Product Import	ICT Product Export	ICT Service Export	ICT Service Import
2007	0.77	0.86	0.34	0.42
2008	0.73	0.90	0.38	0.29
2009	0.69	0.83	0.36	0.38
2010	0.71	0.86	0.29	0.31
2011	0.72	0.83	0.31	0.28
2012	0.63	0.74	0.36	0.26
2013	0.63	0.73	0.31	0.32
2014	0.61	0.70	0.28	0.26
2015	0.57	0.65	0.32	0.28
2016	0.56	0.65	0.36	0.27
2017	0.57	0.65	0.41	0.33
2018	0.55	0.65	0.38	0.30
2019	0.57	0.63	0.37	0.23
2020	0.60	0.65	0.47	0.25
2021	0.61	0.66	0.47	0.35

.

The Theil index is commonly used to measure inequality and regional economic disparities. It decomposes regional differences at different spatial scales and integrates multiple spatial scales to analyze changes in economic disparities between or within regions. The steps for calculating the Theil index are as follows:

3.1.1. Calculating the Proportion of Each Group or Individual

Calculating the proportion of each group usually uses sum normalization, meaning that the proportion of each group is equal to the sum of the indicators of that group divided by the sum of all group indicators. The formula is as follows:

$${\mathrm{P}}_{\mathrm{i}}={\displaystyle \frac{X_i}{X_{total}}}$$

Here, P_i represents the proportion of the i-th group, X_i is the total index of the i-th group, and X_total is the total index of all groups.

3.1.2. Calculating the Inequality of Each Group

The Formula is as follows.

$${\mathrm{T}}_{\mathrm{i}}={\displaystyle \frac{X_i}{\sum _{j=1}^N{X}_j}}\times \mathrm{l}\mathrm{n}{\displaystyle \frac{X_i}{{\mathrm{X}}_{\mathrm{a}\mathrm{v}\mathrm{e}\mathrm{r}\mathrm{a}\mathrm{g}\mathrm{e}}}}$$

Here, T_i represents the inequality of the i-th group.

3.1.3. Calculating the Theil Index

The Formula is as follows.

$$\mathrm{T}\mathrm{h}\mathrm{e}\mathrm{i}\mathrm{l} \mathrm{I}\mathrm{n}\mathrm{d}\mathrm{e}\mathrm{x}=\sum _{i=1}^N{T}_i$$

The overall inequality, calculated by summing the inequalities of all groups, represents the Theil index. A higher Theil index indicates a greater degree of inequality.

From Table 2, it can be observed that the indicators of digital trade differences among ASEAN countries have been decreasing year by year. This suggests that the digital trade gap initially widened before narrowing. While significant differences remain in the import and export of digital products, the gap in digital service trade has been steadily shrinking.

(a)

The digital trade gap among ASEAN countries initially widened and then narrowed

In the digital trade among ASEAN countries, the gap in digital product trade is significantly larger compared to the digital service trade, displaying a trend of first decreasing and then increasing. Specifically, there is a significant narrowing between 2007 and 2019 but re-widening from 2020 to 2021. A possible explanation is that ASEAN countries have placed greater emphasis on digital trade, invested more in technology and infrastructure, and promoted digital trade transformation. However, the widening gap during the 2020–2021 period was attributed to the impact of the COVID-19 pandemic, which disrupted trade dynamics and amplified disparities between countries.

(b)

Significant differences in digital product trade import and export

As shown in the table, from 2007 to 2021, the Theil index for digital product trade imports among ASEAN countries decreased from 0.77 to 0.61, whereas the Theil index for export decreased from 0.86 to 0.66. Despite the improvement in import and export differences, a significant gap still exists.

One possible explanation is that the ICT industry experiences rapid technological innovation and intense market competition. To achieve mutual benefits, ASEAN countries have implemented measures to balance the import and export volumes of ICT products. However, digital divide [51] (“Digital divide” refers to the disparities in ownership, application, and innovation capabilities of information and network technologies among different countries, regions, industries, enterprises, and communities during the global digitalization process. These disparities contribute to an information gap and further polarization of wealth.)—referring to disparities in the ownership, application, and innovation capabilities of information and communication technologies (ICT) across countries, regions, and industries—has contributed to information inequality and the polarization of wealth. Developing countries, in particular, require more time for industrial transformation and upgrading.

Additionally, the rise of trade protectionism and increased trade frictions have further exacerbated the gap in digital product trade among ASEAN countries.

(c)

The gap in digital service trade continues to narrow

The data indicate that the gap in digital service trade among ASEAN countries has been steadily narrowing. This trend can be attributed to continuous improvements in network coverage and smartphone penetration rates, along with declining Internet service costs. These advancements have collectively contributed to the reduction of disparities in digital service trade.

3.2. Variable Selection and Data Sources for Empirical Analysis

This study utilizes panel data from nine ASEAN countries covering the period from 2007 to 2021. The data are sourced from reliable international databases, including OECD (Organisation for Economic Co-operation and Development), World Bank, World Intellectual Property Statistics Data Center, Asian Development Bank (ADB), United Nations Conference on Trade and Development (UNCTAD), etc.

3.2.1. Dependent Variables

Digital trade, as an important component of international trade in the new era, reflects the profound transformation of global trade patterns by digital technology. Digital trade can be categorized into digital product trade and digital service trade. Drawing on the research frameworks of [42] and [52], this article selects the following as dependent variables: Total Amount of Digital Trade, Digital Product Trade, and Digital Service Trade.

3.2.2. Explanatory Variables and Control Variables

The growth of digital trade is usually closely related to innovation capability and digitalization level, among which the national innovation level is the core element affecting the development of digital trade and a key indicator for measuring the trade competitiveness of a country or region in the digital economy era. The indicator for intuitively measuring innovation capability is the number of patent applications, which is one of the most direct and representative indicators for measuring innovation capability [53,54], reflecting the investment and achievements of the country and enterprises in technology research and innovation activities.

In addition, foreign direct investment (FDI) means the introduction of technology, capital, and management experience, while per capita GDP reflects a country’s level of economic development and market purchasing power, both of which are important external factors driving the development of the digital economy and trade. The development of digital trade is directly influenced by the wage output rate of the digital economy industry, which can reflect the labor productivity and industrial development level of the digital economy industry. The level of government governance, data flow, and national development level are also influencing factors. Du Youhuang Bai’s (2021) research shows that the external environment has a positive impact on its macroeconomic output [55,56].

The degree of digitization reflects a country’s level of development in digital infrastructure, digital skills, and digital service applications. The Technology Acceptance Model (TAM) states that the higher the level of digitization, the more favorable it is for the development of emerging digital trade models [57]. Therefore, innovation capability has the potential to enhance digitalization and promote the development of digital trade. The degree of digitization may serve as a bridge between innovation capability and digital trade.

The digital economy RCA index can measure a country’s relative competitive advantage in the digital industry and is an important indicator for analyzing digital trade competitiveness. The RCA index may moderate the relationship between innovation capability and digital trade. Innovation capability may have a more significant promoting effect in industries with strong comparative advantages.

Therefore, this article takes the number of national patent applications as the core explanatory variable, with GDP, foreign direct investment (FDI), wage–output ratio, government efficiency, regulatory quality, discourse power and accountability, political stability, and corruption level as control variables, digitalization level as the mediating variable, and RCA index as the moderating variable, to quantitatively analyze the impact mechanism of innovation level on digital trade (

Table 3. Variable selection.

	Indicator	Abbreviation	Description	Data Source
Dependent Variables	Digital Trade	igt	Total trade of ICT products and services (imports and exports)	OECD website, Asian Development Bank
		ist	Total trade of ICT services (imports and exports)	Asian Development Bank
		igs	Total trade of ICT products (imports and exports)	OECD website
Core Explanatory Variable	Number of Patent Applications	patentnew	Total number of patent applications by residents and non-residents	World Bank
Mediating Variable	Degree of Digitization	dig	A digitalization index calculated based on data such as fixed broadband users, mobile cellular users, and internet users in ASEAN countries	United Overseas Bank
Moderating Variable	Revealed Comparative Advantage Index	rca	Revealed Comparative Advantage (RCA) index measures the export advantage of a country or region in specific goods or services compared to others
Control Variables	GDP Growth Rate	gdpg	Reflects changes in the economic development level over a certain period and indicates the economic vitality of a country or region	World Bank
	Foreign Direct Investment	fdi	Refers to economic investments made by foreign enterprises to gain profits locally	World Bank Worldwide Governance Indicators
	Wage–Output Ratio of the Digital Economy Industry	ictsal	Reflects the ratio between the value created by the digital industry during production and the wages earned by employees, indicating the industry’s cost structure. A higher wage–value ratio implies stronger competitiveness in international markets	Calculated
	Government Efficiency	gover	Reflects public perception of the quality of public services, the civil service, the quality of policy formulation and implementation, and government credibility	OECD website
	Regulatory Quality	regu	Reflects perceptions of the government’s ability to promote the healthy development of the private sector	World Bank
	Discourse Power and Accountability	voice	Indicates the extent to which citizens can participate in selecting their government, as well as freedom of speech, association, and media	World Bank Worldwide Governance Indicators
	Political Stability	political	The likelihood of the government being destabilized or overthrown through unconstitutional or violent means, including politically motivated violence and terrorism
	Corruption Level	control	Measures the extent to which public power is used for private gain, including corruption and the capture of the state by elites and private interests

).

3.2.3. Regression Analysis

This article constructs a panel fixed-effects model for analysis and testing, and the regression equation is as follows:

igt_it = α + β₁patentnew_it + ε_it

igs_it = α + β₁patentnew_it + ε_it

ist_it = α + β₁patentnew_it + ε_it

igt_it = α + β₁patentnew_it + β₂gdpg_it + β₃log_fdi_it + β₄ictsal_it
+ β₅gover_it + β₆regu_it + β₇political_it + β₈voice_it + β₉control_it + ε_it

igs_it = α + β₁patentnew_it + β₂gdpg_it + β₃log_fdi_it + β₄ictsal_it
+ β₅gover_it + β₆regu_it + β₇political_it + β₈voice_it + β₉coutrol_it + ε_it

ist_it = α + β₁patentnew_it + β₂gdpg_it + β₃log_fdi_it + β₄ictsal_it
+ β₅gover_it + β₆regu_it + β₇political_it + β₈voice_it + β₉coutrol_it + ε_it

Here, igt_it, igs_it, and ist_it represent the digital trade volume, digital product trade volume, and digital service trade volume of country i in year t; patentnew_it indicates the number of patent applications filed by country i in year t; gdpg_it represents the per capita GDP growth rate of country i in year t, while log_fdi_it is the logarithm of foreign direct investment in country i in year t; ictsal_it refers to the wage–output ratio of the digital industry in country i in year t.

Additionally, government_it measures the government efficiency of country i in year t, regent reflects the regulatory quality of country i in year t, politiciz_it represents the political stability of country i in year t, and voice_it captures the citizen discourse level of country i in year t. Finally, control_it measures the degree of corruption in country i in year t, and ε_it is a random perturbation term.

3.3. Empirical Analysis of Innovation Capability on ASEAN Digital Trade

3.3.1. Descriptive Statistics

This study also conducted correlation coefficient estimation and variance inflation factor (VIF) tests on the relevant variables, and the results showed that there was no multicollinearity among the selected variables in this article.

Table 4. Descriptive statistics.

Variable	Sample Size	Average	Std. Deviation	Min	Max
log_igt	135	59,166.7	70,793.67	0	292,257
log_igs	135	60,755.76	71,165.76	26.83	293,222.3
log_ist	135	1589.06	1123.474	26.83	4160.18
log_patentnew	127	7.343036	2.192033	2.564949	9.588092
log_fdi	135	21.96975	3.144499	0	25.65445
ictsal	135	3.59049	1.099222	1.528945	5.119914
gdpg	135	4.355513	3.54322	−9.518294	14.51975
political	135	−0.0003056	0.8637988	−1.779236	1.599123
control	135	−0.1587817	0.9922328	−1.356795	2.231618
gover	135	0.325671	0.9223399	−1.00112	2.46966
regu	135	0.1702988	0.8583541	−1.186762	2.252235
voice	135	−0.6848291	0.6178046	−1.815576	0.1848712

presents the descriptive statistical results of the variables.

3.3.2. Benchmark Regression Analysis

The benchmark regression results are shown in

Table 5. Benchmark regression of ASEAN innovation level on digital trade development.

Variable	(1)	(2)	(3)	(1)	(2)	(3)
	log_igt	log_igs	log_ist	log_igt	log_igs	log_ist
log_patentnew	1.2397 *** (0.901)	0.887 *** (0.073)	0.374 *** (0.053)	1.226 *** (0.081)	1.314 *** (0.408)	0.344 *** (0.046)
political				−0.303 (0.239)	−1.274 *** (0.265)	0.269 ** (0.134)
control				−1.166 *** (0.478)	−0.375 (0.565)	−1.125 *** (0.268)
gover				0.539 (0.516)	2.287 *** (0.557)	−0.081 (0.289)
regu				1.606 *** (0.528)	−0.244 (0.588)	0.903 *** (0.296)
voice				−0.927 *** (0.282)	−0.280 (0.322)	0.113 (0.158)
log_fdi				0.027 (0.034)	0.155 *** (0.037)	−0.018 (0.019)
ictsal				0.072 (0.133)	0.836 *** (0.136)	0.379 *** (0.075)
gdpg				0.045 (0.029)	0.031 (0.034)	0.024 (0.016)
Constant	0.093 (0.688)	3.085 *** (0.565)	4.248 *** (0.444)	−2.113 *** (0.815)	−6.621 *** (2.752)	3.386 *** (0.456)
Sample Size	135	135	135	135	135	135
R2	0.96	0.94	0.70	0.98	0.91	0.88

Note: *** p < 0.01, ** p < 0.05; The values in parentheses are clustering standard errors. Unless otherwise specified, this article uses robust standard errors for all regressions.

. The regression coefficients of the model are mostly significant at the 0.01 level, indicating that the model has strong explanatory power. For the core explanatory variable of innovation capability, the table shows that regardless of whether control variables are included, the coefficients remain significantly positive at the 0.01 level. This indicates that the innovation capability of ASEAN countries has a significant positive impact on the development of digital trade volume, digital product trade, and digital service trade. Specifically, for every unit increase in innovation capability, digital trade grows by more than one unit. This improvement enhances the international competitiveness of ASEAN countries, attracts international cooperation and investment, and promotes digital trade openness. Countries with strong innovation capabilities, such as Singapore and Indonesia, further expand their digital trade by leveraging diversified e-commerce platforms to access broader markets.

The level of government governance also positively affects digital trade in ASEAN countries. Providing good governance optimizes the legal and regulatory framework, improves the business environment, and leads to the advancement of digital trade. According to Table 5, the regression coefficients of government efficiency and regulatory quality are statistically significant and positive, with each additional unit increasing digital trade by 2.287 and 1.606 units, respectively.

On the other hand, political stability shows mixed effects: a negative impact on digital product trade and a positive effect on digital service trade. One possible reason is that digital product trade involves the production and distribution of physical goods, which are heavily influenced by political order stability and international political relations. Political instability may cause disturbances in supply sources, logistics delays, and potential damage to production facilities. In contrast, digital service trade—such as online education, remote healthcare, and cloud computing services—relies less on physical infrastructure and is less politically fragile. Furthermore, although digital product trade remains constrained by trade barriers and protectionist policies, ASEAN countries’ participation in international trade agreements like the Regional Comprehensive Economic Partnership (RCEP) has fostered the development of digital service trade.

For discourse power and regulatory quality, every unit increase reduces digital trade by 0.927 and 1.166 units, respectively. Countries with low citizen discourse power and poor regulatory quality often suffer from inefficient and cumbersome administrative systems, leading to delayed decision-making and an inability to adapt to the dynamic needs of digital trade development. This results in irregular competition and information asymmetry, hindering the healthy growth of digital trade markets.

Foreign investment and the digital economy industry’s wage output have significant positive effects on digital product trade. Specifically, for every unit increase in foreign direct investment (FDI) and wage output, digital product trade increases by 0.155 and 0.836 units, respectively. Foreign investment introduces capital inflows, promotes technological innovation, and accelerates the development of digital product trade.

In summary, empirical tests confirm that innovation capability has a significant positive effect on the development of digital trade, digital product trade, and digital service trade. Additionally, government efficiency, regulatory quality, foreign direct investment, and the wage–output rate of the digital economy industry positively influence digital trade growth in ASEAN countries. However, low citizen discourse power and corruption reduce the efficiency of digital trade operations and slow the pace of digital transformation, thereby hindering digital trade development. Therefore, assumptions 1, 2, and 3 are satisfied.

3.4. Mediation and Moderation Effect

3.4.1. Mediation Effect

To further verify the impact mechanism of innovation capability on the development of digital trade in ASEAN countries, this study employs the degree of digitalization as a mediating variable and conducts a mediation effect test. By introducing digitalization into the model, the analysis examines whether the level of digitalization in ASEAN countries plays a partial or complete mediating role in the relationship between innovation capability and digital trade development.

Table 6. Regression results of mediation effect test.

Variable	Dependent Variable
	(1) log_igt 1st Step	(2) dig 2nd Step	(3) log_igt 3rd Step
log_patentnew	0.669 *** (0.257)	13.899 *** (2.811)	0.14 * (0.008)
dig			0.669 *** (0.257)
Constant	1.549 (1.054)	12.754 (12.438)	0.932 (1.027)
Observations	135	135	135
R2	0.93	0.68	0.93

Note: *** p < 0.01, * p < 0.1.

presents the regression results of the mediation effect test. Column (1) shows that innovation capability has a significant direct positive impact on the development of digital trade. Column (2) indicates that innovation capability significantly influences the degree of digitization, confirming a mediating effect. The regression result in Column (3) demonstrates that innovation capability affects digital trade development through the degree of digitization, indicating that innovation capability indirectly promotes the improvement of digital trade by increasing the degree of digitization, with the mediating effect accounting for 93% of the total effect. Therefore, assumption 4 is satisfied.

3.4.2. Moderation Effect

To further verify the impact of the ASEAN’s innovation capability on the level of digital trade and the enhancement of its quality, a moderation effect test was conducted using the Revealed Comparative Advantage index (RCA) as the moderating variable.

Table 7. Regression results of moderation effect test.

Variable	Dependent Variable (igt)
	(1)	(2)	(3)
log_patentnew	1.302 *** (0.044)	1.101 *** (0.061)	1.091 *** (0.064)
patrcai	−0.167 *** (0.059)	−0.254 *** (0.048)	−0.248 *** (0.049)
rcaict	1.648 *** (0.499)	2.630 *** (0.418)	2.571 *** (0.424)
political		−0.600 *** (0.188)	−0.610 *** (0.189)
control		−1.133 *** (0.367)	−1.290 *** (0.373)
gover		0.241 (0.380)	0.367 (0.398)
regu		2.246 *** (0.400)	2.365 *** (0.413)
voice		−0.405 * (0.233)	−0.439 * (0.33)
ictsal			0.006 (0.110)
gdpg			0.041 ** (0.020)
Constant	−0.587 * (0.331)	−0.313 (0.506)	−0.539 (0.569)
Sample Size	135	135	135
R2	0.90	0.94	0.94

Note: *** p < 0.01, ** p < 0.05, * p < 0.1.

presents the regression results of the moderation effect. The results show that innovation capability has a significant positive effect on digital trade, and the RCA index of the digital industry also exerts a significant positive impact. However, the interaction term between these two indicators is significantly negative, indicating that the RCA index weakens the positive impact of innovation capability on digital trade.

There are several possible explanations for this finding. First, certain ASEAN nations, like Laos, Cambodia, and Myanmar, possess inadequate digital technology infrastructures, hence constraining their capacity to fully leverage digital benefits. The deficiency of modern technology and infrastructure further constrains the enhancement of innovation capabilities. Second, ASEAN nations encounter obstacles which include a deficiency of digital trade expertise, inadequately designed innovation frameworks, and insufficient investment in research and development. Aside from Singapore, the majority of ASEAN countries possess insufficient talent reserves and funding for research and development in digital technologies, hindering their ability to effectively convert comparative advantages into growth in digital trade. Third, restrictive policies and regulations, including data privacy laws and foreign investment limitations, continue to obstruct innovation and digital trade development. Furthermore, global economic concerns, such as trade tensions and the reconfiguration of global supply chains, have intensified these obstacles and adversely affected the innovation capacities and digital commerce expansion of ASEAN nations.

3.5. Robustness Test

To ensure the reliability of the research conclusions, this study conducted a robustness test by lagging the dependent variable and the core explanatory variable by one period. Additionally, the dependent variable was replaced with serGDP, which represents the value added in service trade as a percentage of GDP. As indicated in

Table 8. Estimation results of robustness test.

Variable	Replace the Dependent Variable (sergdp)			Core Variable Lags by One Period (l.log_patentnew)
	(1)	(2)	(3)	(1)	(2)	(3)
log_patentnew	2.348 *** (0.515)	1.850 *** (0.598)	1.337 *** (0.505)
llog_patentnew				2.045 *** (0.494)	1.520 *** (0.607)	1.303 *** (0.512)
political		4.143 *** (1.106)	−7.964 *** (1.593)		3.993 *** (1.086)	−7.724 *** (1.631)
control		6.751 *** (1.943)	7.468 *** (3.196)		3.523 * (2.017)	4.353 (3.322)
gover		−3.931 ** (2.045)	−4.275 (3.387)		−1.850 (1.912)	−3.767 (3.489)
regu		−1.397 (1.785)	10.184 *** (3.474)		0.257 (1.834)	13.488 *** (3.637)
voice		−0.104 (1.922)	−5.913 *** (1.890)		1.119 (1.950)	−6.648 *** (1.864)
ictsal			0.343 (0.889)			0.463 (0.909)
gdpg			0.529 *** (0.175)			0.581 *** (0.177)
Constant	30.954 *** (4.746)	37.105 *** (5.570)	31.446 *** (4.223)	33.338 *** (4.627)	38.917 *** (5.472)	29.696 *** (4.294)
Sample Size	135	135	135	135	135	135
R2	0.51	0.51	0.76	0.52	0.55	0.77

Note: *** p < 0.01, ** p < 0.05, * p < 0.1; The values in parentheses are clustering standard errors. Unless otherwise specified, this article uses Robust standard errors for all regressions.

, after introducing the lagged dependent variable and core explanatory variable, the research findings remain consistent and robust. The results confirm that the positive impact of innovation capability on digital trade still holds, thereby passing the robustness test.

4. Conclusions and Recommendations

This article employs panel data from nine ASEAN countries spanning from 2007 to 2021 to quantitatively examine the impact mechanism of innovation capability on the ASEAN’s digital trade. This study yields the following key findings: Firstly, there are significant disparities among ASEAN countries in promoting the development of digital trade, as well as differences in the import and export of digital products. Secondly, a considerable gap exists in innovation capabilities across ASEAN nations, with diverse evolutionary patterns. Thirdly, empirical evidence demonstrates that innovation capability has a significant positive effect on the development of digital trade. Further analysis reveals that innovation capability influences digital trade through the mediating effect of digital readiness, while the Revealed Comparative Advantage index (RCA) of the digital industry exerts a significant moderating effect. Moreover, government effectiveness, regulatory quality, foreign direct investment (FDI), and the wage–output rate of the digital industry positively contribute to the growth of digital trade. Conversely, low citizen discourse power and corruption negatively affect digital trade performance, reducing operational efficiency and digital transformation progress.

Based on these findings, the following policy recommendations are proposed to advance digital trade among ASEAN countries: First, enhance national innovation capability: Innovation is a core element in promoting digital trade development. Improving innovation capability helps to strengthen human capital and foster the concentration of high-end digital trade talent. Therefore, it is necessary to raise awareness of the importance of digital trade among young people and increase the number of digital technology exchange activities. Second, promote digital service trade and narrow the digital product trade gap: Efforts should focus on improving digital trade infrastructure to support the digital and intelligent transformation of enterprises. Third, strengthen governments’ governance capacity: Reduce the cost of patent applications, alleviate the burden on innovators, and ensure a stable and predictable environment for the development of digital trade. Fourth, enhance the wage–output ratio of the digital industry and promote digital transformation: Strengthen economic cooperation and exchanges between ASEAN countries and other countries through knowledge sharing and other means, while increasing efforts to attract external investment and promote the overall development of digital trade in the ASEAN. Fifth, build and strengthen data centers: In the digital trade era, business activities are increasingly transferring to virtual platforms and the role played by data centers is becoming increasingly prominent. It is necessary to strengthen data integration capabilities and improve data governance systems. By implementing these strategies, ASEAN countries can collectively overcome structural challenges, strengthen innovation capabilities, and unlock the full potential of digital trade in the region.

Although this study has contributions, it still faces some limitations. Firstly, due to the rapid development of digital technology, the panel data used may not be able to capture real-time changes in digital trade trends. Secondly, the analysis is limited by data availability, especially for some ASEAN countries where official statistical data is not comprehensive. Thirdly, this study mainly focuses on quantitative indicators and may overlook institutional factors, such as cultural differences and digital literacy. Future research could consider incorporating real-time data, exploring the impact mechanisms of institutional factors, and applying the proposed framework to other emerging digital markets to enhance the generalizability of research results.